THE ROLE OF BETA-AMYLOID AND INFLAMMATION IN NEURONAL CELL CYCLE

THE ROLE OF BETA-AMYLOID AND INFLAMMATION IN NEURONAL CELL CYCLE EVENTS IN ALZHEIMER’S DISEASE MOUSE MODELS by NICHOLAS H. VARVEL Submitted in partial fulfillment of the requirements For the degree of Doctor of Philosophy Department of Neurosciences CASE WESTERN RESERVE UNIVERSITY January, 2009 CASE WESTERN RESERVE UNIVERSITY SCHOOL OF GRADUATE STUDIES We hereby approve the thesis/dissertation of Nicholas H. Varvel _____________________________________________________ Ph.D. candidate for the ______________________degree *. (signed)_______________________________________________ (chair of the committee) Gary E. Landreth ________________________________________________ Bruce T. Lamb Karl Herrup ________________________________________________ ________________________________________________ Robert H. Miller Jerry Silver ________________________________________________ ________________________________________________ (date) _______________________ November 11, 2008 *We also certify that written approval has been obtained for any proprietary material contained therein. Table of Contents List of Tables.............................................................................................. 2 List of Figures............................................................................................. 3 Abstract...................................................................................................... 6 Chapter 1: Introduction and Research Objectives..................................... 8 Chapter 2: Ectopic Cell Cycle Events Link Human Alzheimer’s Disease and Amyloid Precursor Protein Transgenic Mouse Models... 45 Chapter 3: Aβ Oligomers Induce Neuronal Cell Cycle Events in Alzheimer’s Disease.............................................................. 82 Chapter 4: NSAIDs Prevent Neuronal Cell Cycle Re-Entry in Alzheimer’s Disease Mouse Models.................................... 117 Chapter 5: Conclusions and Future Directions...................................... 160 Bibliography ........................................................................................... 180 1 List of Tables Table 1.1: APP Transgenic Mouse Models ............................................ 41 Table 4.1: Chronic Dosing with NSAIDs Does Not Alter Steady-State Brain Aβ Levels ................................................................... 156 2 List of Figures Figure 1.1: Processing of the Amyloid Precursor Protein....................... 39 Figure 1.2: Amyloid Cascade Hypothesis .............................................. 42 Figure 1.3: The Mitotic Cell Cycle .......................................................... 43 Figure 2.1: Appearance of cell cycle proteins in the neurons of 22-month old transgenic R1.40 mice.................................... 69 Figure 2.2: DNA replication in neurons of transgenic R1.40 mice .......... 71 Figure 2.3: Confocal images of increased ploidy in some of the neurons of the adult R1.40 transgenic mouse brain........................... 73 Figure 2.4: CCEs are observed in multiple AD transgenic mouse models...................................................................... 74 Figure 2.5: Expression of cell cycle proteins in subcortical structures in 22-month old R1.40 mice................................. 76 Figure 2.6: Expression of cell cycle protein at various ages of R1.40 mice....................................................................... 78 Figure 2.7: DNA replication in neurons at various ages in the R1.40 mouse model ....................................................................... 79 Figure 2.8: An inflammatory response is observed in the cortex of 22-month old R1.40 mice ..................................................... 80 Figure 3.1: Appearance of cell cycle proteins and DNA synthesis in frontal cortical layers II/III in B6-R1.40 mice at 6 months of age ................................................................................. 104 3 Figure 3.2: Expression of cell cycle proteins in frontal cortical layers V/VI in B6-R1.40 at 12 months of age................................ 106 Figure 3.3: Quantification of neuronal cell cycle activity within cortical layers ................................................................................. 108 Figure 3.4: Neuronal expression of cell cycle proteins is delayed in D2-R1.40 animals .............................................................. 110 Figure 3.5: B6-R1.40;Bace1-/- animals do not display neuronal cell cycle re-entry at 6 months of age in frontal cortical layers II/III.... 112 Figure 3.6: Western blot of monomer (M)- and oligomer (O)-rich Aβ1-42 in vitro preparations ............................................... 114 Figure 3.7: Aβ oligomers induce neuronal BrdU incorporation in cortical neurons in vitro .................................................................. 115 Figure 4.1: Aβ-dependant alterations in brain microglia in 151 R1.40 transgenic mice ....................................................... 146 Figure 4.2: Lipopolysaccaride (LPS) administration provokes neuroinflammation and neuronal cell cycle events............. 148 Figure 4.3: Prevention trial of NSAIDs inhibits microglial alterations.... 150 Figure 4.4: Prevention trial of NSAIDs inhibits neuronal CCEs ............ 152 Figure 4.5: Quantification of inhibition of neuronal CCEs in NSAIDs prevention trial...................................................... 154 Figure 4.6: Lack of effect of NSAIDs on APP processing..................... 155 4 Figure 4.7: Therapeutic trial of NSAIDs inhibits subsequent, but does not reverse extant neuronal CCEs ...................... 157 Figure 4.8: Quantification of inhibition of neuronal CCEs in NSAIDs therapeutic trial .....................................................159 5 The Role of Beta-Amyloid and Inflammation in Neuronal Cell Cycle Events in Alzheimer’s Disease Mouse Models Abstract by NICHOLAS H. VARVEL Alzheimer’s disease (AD) is a devastating and increasingly prevalent neurodegenerative condition of the elderly. Characterized clinically by memoryloss, dementia, and eventual decline in motor skills; the disease is only definitively diagnosed after post-mortem demonstration of the neuropatholgical hallmarks of the disease. These hallmarks include extracellular deposits of the β-amyloid (Aβ) protein in senile plaques, intracellular aggregates of phosphorylated tau in neurofibrillary tangles, activation of microglia and astrocytes and neuronal cell loss in specific populations within the brain. These pathologic alterations progress in a characteristic pattern within the AD brain; however, the mechanistic relationships between the various neuropathological alterations remain unclear. Recently, it has become increasingly evident that neuronal populations at risk for degeneration in the AD brain exhibit reexpression of cell cycle proteins as well as DNA replication. We and others have proposed that these ectopic cell cycle events (CCEs) are the first step in a long, slow atrophy and eventual death. In addition, we believe neuronal CCEs may be 6 a valuable biomarker for disease risk and progression as well as the efficacy of therapeutic interventions. In efforts to identify the initiating factors underlying these CCEs, we have characterized the appearance of the neuronal CCEs in the R1.40 mouse model of AD. Interestingly, the genomic-based R1.40 mice exhibit neuronal CCEs in a temporal and spatial pattern that closely recapitulates that observed in human AD. In addition, neuronal CCEs are dependent on the steady-state levels and generation of Aβ peptides. Furthermore, the appearance of CCEs occurs coincidently with alterations in brain microglia, linking the presence of particular Aβ species with neuroinflammation and neuronal CCEs. These data suggest that neuroinflammation is involved in the induction of neuronal CCEs. In support of this idea, promotion of neuroinflammation at younger ages in the R1.40 mice induces neuronal CCEs, while treatments with two different anti-inflammatory non-steroidal drugs block both the alterations in brain microglia as well as neuronal CCEs. However, anti-inflammatory treatments fail to reverse extant CCEs. These studies suggest that efficacious therapeutic treatments in human AD will require initiation at early stages of disease progression. 7 Chapter 1: Introduction to Alzheimer’s Disease and Research Objectives Alzheimer’s disease (AD) was first described by the Bavarian psychiatrist Alois Alzheimer in the early 20th century. His patient, August D., was presented to him with severe delirium and dementia. After her death, post-mortem examination of her brain revealed the presence of two neuropathological lesions, which Dr. Alzheimer referred to as “milar foci”, which would later be known as senile plaques, and “neurofibrils”, now known as neurofibrilary tangles. Dr. Alzheimer then made the assertion that these neuropathologies were the cause of the dementia exhibited by August D. Years later, Dr. Alzheimer examined another individual suffering from virtually same symptoms as August D. Neuropathological analysis of the brain material revealed, similar to those encountered previously, the presence of the “milar foci”. However, the “neurofibrils” were absent from the cells of the brain. Dr. Alzheimer commented that it was difficult to make any conclusions regarding the interactions between the two distinct pathologies (Moller and Graeber, 1998). Over 100 years after the first description of the disease by Dr. Alzheimer, it is still unclear how the pathological hallmarks lead to region specific neurodegeneration evident in the AD brain as well as the behavioral symptoms associated with AD. Today AD is a devastating and increasingly prevalent neurodegenerative condition of the elderly and now the fourth leading cause of death in the United States (Cummings and Cole, 2002). Alzheimer’s disease (AD) is the leading cause of dementia in individuals over the age of seventy and current estimates speculate that by 2050 over 14 million Americans will have AD (Brookmeyer et 8 al., 1998). Characterized clinically by progressive memory loss, cognitive decline and eventual loss of motor skills, the disease is only definitively diagnosed after post-mortem demonstration of the neuropathological hallmarks of the disease, senile plaques and neurofibrillary tangles. Senile plaques are extracellular deposits of the β-amyloid (Aβ) peptide, formed by the proteolytic cleavage of the larger amyloid precursor protein (APP). Neurofibrillary tangles (NFTs) are intracellular, hyperphosphorylated aggregates of the microtubule-associated protein tau (MAPT). In addition to senile plaques and NFTs, other pathological characteristics include the presence of dystrophic neurites, activation of microglia and astrocytes, re-activation of a mitotic cell cycle in neurons and subsequent neuronal cell loss and atrophy in specific populations within the brain (Akiyama et al., 2000; Herrup and Arendt, 2002). Neuronal populations susceptible to death in AD include the frontal and entorhinal cortices, hippocampus, as well as certain subcortical populations of neurons including the locus ceruleus (Zarow et al., 2003), dorsal raphe (Zweig et al., 1988), and cholinergic neurons of the basal nucleus of Meynart (Whitehouse et al., 1982). However, more than 100 years after Dr. Alzheimer’s famous reports the underlying mechanistic relationships between the neuropathological features of AD remain poorly defined. Furthermore, it is not understood how the pathologies contribute to the neurodegeneration and cognitive impairments encountered in AD patients. 9 Alzheimer’s Disease and Cognitive Impairment A defining symptom of AD is overall reduced cognition. The characteristic progression of AD is marked by a decreased ability to learn and deficits in memory; these features culminate in severe dementia. Initially, individuals begin to exhibit deterioration of episodic memory, namely AD patients loose the ability to recall events and facts specific to time and place (Welsh et al., 1992). Before the clinical onset of AD, many individuals begin to exhibit age-associated loss of mental ability, a condition known as mild cognitive impairment (MCI). An individual with MCI will exhibit subtle problems with memory and other complex mental tasks; however, while minor, these deficits are clinically significant. Studies have indicated that ~33% of individuals with MCI will progress into AD within a four year period (Bennett et al., 2002). Thus, MCI is believed by many to be a prodromal stage of AD (Petersen, 2000; Morris et al., 2001). In the later stages of the disease, severe deficits in executive function, an inability to plan and loss of language skills are often evident (Galton et al., 2000). General cognition continues to deteriorate until a state of dementia is reached and the individual looses ability to interact in a normal social as well as occupational setting. Alzheimer’s Disease Epidemiology Epidemiological studies have identified a number of environmental and genetic etiologies that contribute to the development of AD. These include age, gender, brain injury and family history. 10 The greatest risk factor for the development of AD is age, with the incidence of AD rising dramatically with increasing age. It is estimated that around 3 percent of men and women between the ages of 65 and 74 have the disease while, nearly half of all individuals over the age of 85 may be at some stage of the disease (Katzman, 1993). However, because AD has such a strong age component, modest attenuation of disease onset could significantly reduce the impact of the disease on society. Indeed, a five year delay in the age of onset of the disease could potentially decrease the future prevalence of AD by as much as 50 percent (Brookmeyer et al., 1998). Gender also appears to contribute to the pathogenesis of AD. Women are more affected than men and exhibit an increased risk for development of disease symptoms with age. While the causes of these gender differences are not well understood, it was been suggested that female inheritance of the ε4 allele of apolipoprotein E gene might contribute to this gender bias (Payami et al., 1996). Also, loss of hormones, especially estrogen, in post-menopausal women may be a factor (Brinton, 2004). Importantly, studies that control for decreased longevity in men also indicate that the incidence of AD remains elevated in woman (Breteler et al., 1992; Lendon et al., 1997). Another risk factor increasing the incidence of AD is head trauma. Studies have identified an increased risk of AD in individuals with a history of head injury (Breteler et al., 1992). Interestingly, boxers diagnosed with dementia pugilistica exhibit tangle pathologies similar to those encountered in the AD brain (Allsop et al., 1990). 11 While epidemiological studies have been valuable in identifying populations susceptible to the development of AD, their correlation with the disease has led to little insight into disease pathogenesis. By contrast, the identification of genetic factors causative for the disease in a subset of patients has provided us with important insights with regard to the molecular pathogenesis of AD. In the early 1980’s it was reported that relatives of 125 subjects who had autopsy confirmed AD exhibited a significant excess of dementing illness consistent with genetic inheritance (Heston et al., 1981). More recent twin studies have demonstrated that the rate of AD is nearly 2 times greater in monozygotic twin pairs than their fraternal twin counterparts (Gatz et al., 2006). These observations first suggested a genetic link between AD and certain genetic variants. Today, AD is grouped into three varieties that are dependent on the genetic abnormalities associated with the disease and the age of onset. These subclasses are early-onset familial AD (EOFAD), late-onset AD and sporadic AD. Early-Onset Familial AD Linkage analysis in families exhibiting a high incidence of AD at young ages led to the identification of several mutations causative for the disease. These families exhibit a unique and rare form of AD that first begins to manifest itself between 30 and 60 years of age, now known as early-onset familial Alzheimer’s disease (EOFAD). The identification of families exhibiting this rare form of AD has contributed greatly to our understanding of AD pathogenesis. 12 Initially, a disease-causing locus on chromosome 21 was linked to AD in the late 1980s (St George-Hyslop et al., 1987). In 1991, sequencing of exons 16 and 17 of the amyloid precursor protein (APP) in individuals from families exhibiting a high rate of dementia consistent with autosomal dominant genetic transmission led to the discovery of the first mutation to be found causative for EOFAD (Glenner and Wong, 1984a; Goate et al., 1991). This mutation, later named the London mutation, alters a single amino acid located at residue 717 within the transmembrane domain of APP, near the C-terminus of the Aβ sequence (Figure 1.1). An additional gene mutation was identified in the same location and is known as the Indiana mutation (Murrell et al., 1991). Analysis of two large related families from Sweden identified EOFAD individuals with another mutation in APP at a different location (Mullan et al., 1992). This mutation alters two amino at positions 670 and 671 that resulted in the substitution of Asn for Lys and Leu for Met, noted as KM670/671NL. This double point mutation is located in the region flanking the N-terminus of the Aβ sequence and is now known as the Swedish mutation. Finally, numerous mutations causative for the disease have been identified within the Aβ sequence of APP. These include the Flemish mutation at position 692 (Ala692Gly) (Hendriks et al., 1992), the Iowa mutation at position 694 (Asp694Asn) (Grabowski et al., 2001), as well as the Dutch (Glu693Gln) (Levy et al., 1990) and the Artic (Glu693Gly) (Kamino et al., 1992) mutations at amino acid 693. To date, over 30 mutations have been identified in APP causative for EOFAD. 13 In addition to the mutations in APP, over 100 mutations in the presenilin 1 (PSEN1) gene on chromosome 14 have been implicated in EOFAD (Sherrington et al., 1995). Mutations in the related presenilin 2 (PSEN2) gene on chromosome 1 have also been identified (Levy-Lahad et al., 1995; Rogaev et al., 1995). Genetic analysis of families with EOFAD indicates that mutations in APP, PSEN1, or PSEN2 exhibit a autosomal dominant mode of inheritance and are causative for AD. On the molecular level, most mutations causative for AD have been demonstrated to increase production of Aβ peptides, the principal component of senile plaques in AD brain tissue. Interestingly, individuals with dosage imbalance for chromosome 21, as occurs in Down Syndrome (DS), have an extra copy of APP and develop amyloid pathology and AD in their fourth of fifth decade of life (Wisniewski et al., 1985). In one important report an individual with partial trisomy 21, excluding the genomic segments containing APP, exhibited no clinical and neuropathological evidence of AD (Prasher et al., 1998). The importance of APP was further confirmed by the identification of a French kindred having microduplications of small genomic segments containing APP and exhibiting AD neuropathology at an early age (Rovelet-Lecrux et al., 2006). Together these studies provide compelling direct genetic evidence that increased dosage of APP itself can be causative for the disease, indicating APP plays an important role in AD pathogenesis. 14 Late-onset AD While mutations in APP, PSEN1 and PSEN2 have been valuable in facilitating our understanding of AD risk and Aβ generation, they account for only a small fraction of all AD cases (Rocchi et al., 2003; Tanzi and Bertram, 2005). The majority of AD cases are encountered in individuals over 60 years of age and do not have mutations in the three genes thus far discussed. Therefore, other genetic determinates must contribute to the disease. Interestingly, even within EOFAD families with the same mutation there is substantial variation in symptoms, age of onset and duration of the disease (Axelman et al., 1998; Gomez-Isla et al., 1999; Finckh et al., 2000). These findings suggest that although single mutations are capable of causing completely penetrant EOFAD, other genetic factors are capable of modifying disease pathogenesis even in the presence of a strong EOFAD mutation. An important distinction between EOFAD and late-onset AD is that the latter exhibits a more complicated mode of inheritance. The genes identified thus far affect a number of different pathways that are likely to be involved in the production, aggregation and removal of Aβ. To date the single most significant genetic risk factor for late-onset AD is the ε4 allele of apolipoprotein E (APOE) located on chromosome 19 (Schmechel et al., 1993; Strittmatter et al., 1993). Initially, polymorphisms in APOE were identified through linkage analyses in late-onset AD families. Numerous studies have confirmed that the ε4 allele is strongly associated with increased risk of AD (Farrer et al., 1997). Association studies have also shown that the ε4 allele occurs at a much greater frequency in populations of AD individuals with no 15 family history of AD (Rebeck et al., 1993; Saunders et al., 1993). In addition, the ε2 allele has been associated with a reduced risk of developing AD. APOE has been shown to bind to Aβ directly and co-localize with senile plaques in the AD brain (Shao et al., 1997). In addition, a variety of experimental paradigms indicate that APOE is also involved in the formation of Aβ deposition (Holtzman et al., 2000; Irizarry et al., 2000) as well as Aβ clearance (Jiang et al., 2008). In addition to APOE, linkage analysis in AD families has identified several candidate genes involved in AD. Genetic variants in alpha-2 macroglobin on chromosome 12 (Blacker et al., 1998), low-density lipoprotein receptor protein also on chromosome 12 (Beffert et al., 1999) and insulin degrading enzyme on chromosome 10 (Bian et al., 2004) are associated with increased risk of AD. Another gene recently implicated in late-onset AD is the neuronal sortilin-related receptor 1 gene that is believed to influence Aβ levels through modulation of intracellular trafficking (Rogaeva et al., 2007). Importantly, inheritance of one or more of these alleles only increases the risk for AD, unlike the familial dominant mutant genes identified in EOFAD, which exhibit complete penetrance. Molecular Pathogenesis of Alzheimer’s Disease In 1984 Glenner and Wong identified Aβ as the primary constituent of cerebrovascular amyloid derived from patients with Alzheimer’s disease as well as Down syndrome (Glenner and Wong, 1984b, a). Shortly thereafter Aβ was isolated from senile plaques in AD brain tissue (Masters et al., 1985). It was subsequently determined that Aβ is part of a larger precursor protein, termed the 16 amyloid precursor protein (APP), a type 1 transmembrane protein ubiquitously expressed in human tissues (Goldgaber et al., 1987; Kang et al., 1987; Robakis et al., 1987; Tanzi et al., 1987). The coding sequence of APP encompasses ~200 kb of DNA, contains 19 exons and gives rise to several alternatively spliced APP mRNA that encode proteins between 677 and 770 amino acids. Two primary APP isoforms include 751 and 770 amino acids and contain a Kunitz protease inhibitor (KPI) domain located near the N-terminus (Figure 1.1). KPIcontaining APP isoforms are expressed in most peripheral tissues and nonneuronal cells. In contrast, the APP-695 isoform is highly enriched in neuronal tissues with the highest levels of expression encountered in neurons and, to a lesser degree, in glial cells (Selkoe, 2001). Molecular studies have demonstrated that APP is capable of being proteolytically cleaved in one of two pathways. Cleavage of APP by α-secretase, a transmembrane enzyme believed to be one of two ADAM family members (Buxbaum et al., 1998; Skovronsky et al., 2000; Asai et al., 2003), cleaves APP within the canonical Aβ sequence at position 687, generating a secreted Nterminal fragment, known as sAPPα and a membrane-bound C-terminal fragment alpha, CTFα (Figure 1.1). This membrane-bound CTFα is subsequently cleaved by γ-secretase, to generate a small peptide known as p3. The γ-secretase complex is composed of four membrane-associated proteins, presenilin, nicastrin, Aph-1 and Pen-2 (Francis et al., 2002; Fraering et al., 2004). Importantly, α-secretase cleavage prevents the formation of full length Aβ 17 peptides, thus the α-secretase pathway is considered to be protective against the development of AD. In addition to the α-secretase pathway, APP can be alternatively cleaved by β-secretase or BACE1 , a membrane bound aspartyl protease. Cleavage by BACE1 produces a secreted N-terminal fragment, known as sAPPβ and a larger C-terminal fragment beta, CTFβ (Vassar et al., 1999; Yan et al., 1999). Further cleavage of CTFβ by γ-secretase generates a secreted Aβ peptide. The Cterminal end of Aβ is truncated depending on the specificity of the γ-secretase cleavage site. Therefore, the exact length of Aβ varies between 38 and 43 amino acids. The predominant species are Aβ1-40 and Aβ1-42 (Selkoe, 2001) (Figure 1.1). Although Aβ1-40 can be a major contributor to senile plaques, Aβ1-42 is the more insoluble and amyloidogenic peptide, with a high propensity to aggregate into soluble low-molecular weight Aβ oligomers and insoluble Aβ fibrils. For example, in vitro aggregation studies utilizing synthetic peptides indicate that Aβ peptides ending at position 42 form amyloid fibrils far more rapidly and at lower concentrations than Aβ1-40, suggesting Aβ1-42 is critical for initial plaque formation (Jarrett et al., 1993). In support of this idea, immunohistochemical evidence from post-mortem brain tissue derived from AD as well as DS patients indicates Aβ1-42 peptides generally form the earliest detectable amyloid deposits, followed by the addition of shorter Aβ peptides (Iwatsubo et al., 1994; Iwatsubo et al., 1995; Lemere et al., 1996). Therefore, Aβ1-42 mediates a major role in AD pathogenesis. 18 Familial AD Mutations and APP Processing Analysis of cell derived from patients exhibiting EOFAD as well as in vitro transfection studies have linked mutations in APP, PSEN1 and PSEN2 to increased Aβ generation. The Swedish mutation increases the cleavage of APP by BACE1 and therefore leads to production of CTFβ; the immediate precursor for Aβ generation (Citron et al., 1992; Felsenstein et al., 1994). By contrast, the London and Indiana mutations (Mann et al., 1996; Maruyama et al., 1996), as well as mutations in PSEN1 and PSEN2 (Mann et al., 1997), specifically increase levels of Aβ1-42 through modulation of γ-secretase activity (Figure 1.2). Finally, mutations within the canonical Aβ sequence increase the propensity of fibril formation (Nilsberth et al., 2001). The causative nature of these mutations for EOFAD and the subsequent identification of their influence on Aβ generation and aggregation has led to the hypothesis that elevated Aβ levels mediates a pivotal role in the disease process. Amyloid Cascade Hypothesis-Recent Advances The amyloid hypothesis posits that increases in Aβ1-42 are the initial disease causing event in AD. The elevated levels of Aβ1-42 result in formation of Aβ-containing senile plaques that initiate a series of pathological events, such as microglial and astrocytic inflammatory responses and progressive neuritic injury. This sequence of events culminates in cerebral atrophy and regionspecific neurodegeneration evident in the AD brain, thus leading to the clinical symptoms of AD (Hardy and Allsop, 1991; Selkoe, 2002). 19 Although the altered processing of APP is clearly implicated in AD, the exact mechanism through which Aβ generation and deposition cause the pathological and cognitive hallmarks of the disease remains unclear. For example, patient autopsy data has indicated that plaque load does not directly correlate with cognitive decline (Lue et al., 1999; McLean et al., 1999). In addition, neuropathological studies have also documented substantial Aβ deposits in the cerebral cortex of more than a quarter of nondemented persons over 75 yeas of age (Troncoso et al., 1996; Snowdon, 1997; Ferri et al., 2005). Finally, total Aβ levels, as opposed to total Aβ deposition, are highly correlated with cognitive decline (Naslund et al., 1994). Taken together, these findings suggest that in addition to insoluble amyloid deposition in senile plaques other toxic agents may contribute to neuronal cell death and cognitive decline in AD. In light of the fact that the degree of insoluble Aβ deposition in the brain correlates poorly with cognitive decline, investigators have turned their attention to soluble aggregates of Aβ, termed oligomers. Recent experimental evidence has indicated that Aβ oligomers may play a causative role in AD pathogenesis. Oligomeric assemblies of Aβ have been isolated from AD brain material (Gong et al., 2003; Shankar et al., 2008) as well as young, predepositing transgenic mouse models of AD (Lesne et al., 2006; Oddo et al., 2006). In addition, numerous studies have determined that soluble Aβ oligomers are the predominant neurotoxic Aβ species for neurons (Glabe, 2005). In this regard, Aβ oligomers exhibit potent toxic effects, capable of inducing neuronal cell death at nanomolar concentrations in hippocampal slice cultures (Lambert et al., 1998). 20 Furthermore, these soluble Aβ aggregates have been implicated in the rapid interference of memory of learned behaviors (Cleary et al., 2005), inhibition longterm potentiation (Walsh et al., 2002), suppression P/Q-type calcium currents (Nimmrich et al., 2008) and induction of oxidative stresses through interactions with NMDA receptors (De Felice et al., 2007). Together these data suggest that Aβ oligomers may play a causative role in AD pathogenesis. In addition to inflammatory responses, neuronal atrophy and cell loss in specific neuronal populations, the amyloid hypothesis also posits that the intracellular formation of NFTs occur secondary to amyloid deposition. However, the relationships between amyloid plaques, NFTs and cognitive decline remain unclear. Analysis of AD brain tissue indicates that both amyloid plaques and NFTs occur in a characteristic temporal and spatial pattern. For example, amyloid plaques are first observed in the neocortex and subsequently spread to the hippocampus and finally to all cortical areas in the later stages of the disease. In contrast, NFTs are first observed in the entorhinal cortex, then the hippocampus and eventually throughout the neocortex (Braak and Braak, 1997; Braak et al., 1998). Thus, plaques and tangles are encountered in the same brain regions only at later stages of the disease. Furthermore, studies have indicated that NFTs correlate well with cognitive impairments, memory deficits and linguistic ability (Haroutunian et al., 1999; Riley et al., 2002), while a positive correlation between Aβ deposits and reduced cognition is less clear (Lue et al., 1999; McLean et al., 1999). 21 Microtubule-associated Protein Tau and NFTs In addition to the amyloid plaques, the other pathological hallmark of AD is neurofibrillary tangles (NFTs). Many of the neurons in the AD brain subject to degeneration contain NFTs that occupy much of the perinuclear cytoplasm. Immunohistochemical and biochemical studies have determined that many different proteins accumulate in NFTs, including ubiquitin (Perry et al., 1987); however, the primary protein encountered in NTFs is the microtubule-associated protein tau (MAPT) (Kosik et al., 1986; Wood et al., 1986). In addition to intracellular aggregation and fibrilization, tau proteins in the AD undergo extensive hyperphosphorylation (Grundke-Iqbal et al., 1986). Although similar phosphorylation events occur during development (Pope et al., 1993), in the AD brain tau proteins are biochemically distinct, displaying abnormal or hyperphosphorylation. Using phophorylation-specific antibodies, these forms of tau can be detected in post-mortem AD brain tissue. As a major microtubule-associated protein (MAP) in neurons, tau has a role in modulating the functional organization of the neurons, particularly in axonal morphology, growth and polarity. Tau phosphorylation, like other MAPs, is also known to mediate a role in the mitotic cell cycle (Preuss and Mandelkow, 1998). Interestingly, NFTs in the AD brain are immunoreactive for a specific phosphoepitope of tau usually only encountered during M-phase of a mitotic cell division, suggesting the cell cycle specific kinase responsible for this phosphorylation may be active in post-mitotic neurons in the AD brain (Vincent et al., 1996). Indeed, subsequent immunohistochemical and biochemical analysis 22 indicated that the M-phase cyclin B and its relevant kinase, cdc2, are elevated and active in neurons in the AD brain, while these markers were virtually absent from normal controls (Vincent et al., 1997). This pivotal finding suggested for the first time that neuronal cell loss in specific regions of the AD brain might be accompanied by mitotic mechanisms that are not normally encountered in mature neurons. Cell Cycle in Eukaryotic Cells The eukaryotic cell cycle is a series of events that lead to cell growth, DNA replication, chromosomal segregation and the creation of two daughter cell from one original cell. These events can be grouped into four functionally distinct phases: growth 1 phase (G1), DNA synthesis (S), growth 2 phase (G2) and mitosis (M). G1 is a period of growth and preparation for division. S phase follows G1 and is marked by replication of the genetic material in the cell. After duplication of the genetic material the cell prepares for division in the G2 phase. Finally, after chromosome condensation and movement to the opposite poles of the cell the cytoplasm splits and cell division occurs, culminating in the generation of two new cells. In vertebrates, the initiation and progression of the cell cycle is regulated by a family of cyclin dependent kinases (Cdks) formed by a catalytic subunit and a regulatory subunit termed cyclins. These kinases act sequentially during the cell cycle and specific cyclins and kinases are expressed and active during each phase of the cycle. For example, Cdk4 or Cdk6 pair with cyclin D during G1 and the G1/S transition, Cdk2 and cyclin A2 are active during 23 S phase and cdc2/cyclin B exert their activity during M phase. Adding further complexity and regulation to this system are cell cycle inhibitors that block Cdk/cyclin activity by either forming an inactive complex or by acting as a competitive Cdk ligand. Members of the INK family, such as p19INK4d and p15INK4b, inhibit Cdk4(6)/cyclin D. The cyclin A/Cdk2 complex is inhibited by the Cip/Kip family members (Figure 1.3). Progression through the cell cycle requires the synthesis and degradation of both kinases and cyclins. In addition to the interactions of Cdks and cyclins and their activity during the cell cycle, other protein pairs also mediate critical roles in cell cycle initiation and progression. The E2F/DP1 protein pair is a well-studied member of the cell cycle. In non-dividing cells the E2F family of proteins are bound to the retinoblastoma protein (RB) and act as a transcriptional repressor. During the G1 phase of the cell cycle the Cdk4(6)/cyclin D complex phosphorylates RB, rendering it incapable of binding to the E2F proteins. After binding to the DP protein the E2F/DP complex acts as a transcription factor capable of binding to the promoter region of a variety of genes required for cell cycle progression. Neuronal Cell Cycle Events in Alzheimer’s Disease In the central nervous system, after young neuroblasts leave the ventricular zone, they permanently exit a cell-division cycle and become postmitotic. However, emerging evidence suggests that certain neuronal populations in a number of neurological aliments exhibit features of a mitotic cell cycle. For example, numerous studies have provided immunohistochemical evidence that a 24 wide range of range of cell cycle proteins, including cell cycle inhibitors, are elevated in neurons in regions of the AD brain that undergo extensive degeneration. Post-mortem analysis of AD brain material has demonstrated aberrant neuronal expression of cyclin D, cdk4, PCNA, cyclin B1 (McShea et al., 1997; Nagy et al., 1997; Busser et al., 1998). In addition, a number of studies have indicated several Cdk inhibitors are also present (Arendt et al., 1996; Arendt et al., 1998). Importantly, these canonical cell cycle proteins are observed at much lower levels in regions of the AD brain where degeneration is not prevalent. Furthermore, immunohistochemical analysis of brain tissue obtained from aged-matched non-demented individuals routinely shows no significant expression of cell cycle proteins. The immunohistochemical studies discussed indicate that neurons in the AD brain subject to degeneration exhibit elevated levels of a number of proteins normally only encountered during a canonical mitotic cycle. However, these studies do not address if the appearance of increased protein expression is the result of a true cell cycle or if these events are a general non-specific dysregulation of protein synthesis. The laboratory of Karl Herrup has addressed this issue by utilizing flourescent in situ hybridization (FISH) as a direct measure of DNA replication in neurons. Careful analysis revealed that a significant fraction of hippocampal pyramidal and basal forebrain neurons have fully or partially undergone DNA synthesis on separate genetic loci (Yang et al., 2001). Importantly, cerebellar granule cells, a neuronal population spared from degeneration in the AD brain, did not exhibit any evidence of DNA replication 25 These findings demonstrated that, in addition to elevated cell cycle protein levels, neuronal populations at-risk for degeneration in AD also exhibit DNA synthesis. These processes will now be referred to as neuronal cell cycle events or CCEs. In addition to the examples given for neuronal cell cycle events in AD, there is also evidence that neuronal CCEs occur early in the disease process. For example, immunohistochemical studies demonstrate that individuals with mild cognitive impairment (MCI), widely viewed as the clinical predecessor to AD, also exhibit neuronal CCEs (Yang et al., 2003). Indeed, neuronal populations that undergo substantial degeneration and exhibit neuronal as well as CCEs in the AD brain also exhibit expression of cell cycle proteins in MCI brain tissue. The presence of neuronal CCEs in MCI suggests that neuronal cell cycle re-entry is not limited to the final stages of the AD; rather, they are associated with brain regions subject to degeneration throughout the entire period of disease. Cell Cycle and Neuronal Cell Death The linkage between neuronal cell cycle re-entry and cell death was first discovered using transgenic mice. Transgenically engineered mice numerous investigators have shown that forcing a mitotic cell cycle in a mature neuron ultimately induces cell death. Expression of simian virus 40 (SV40) large tumor antigen in various tissues of transgenic mice typically induces cell proliferation and tumorgenesis (Small et al., 1985; Hanahan, 1988). However, transgenic expression of SV40 antigen in photoreceptor cells results in a non-oncogenic 26 effect. Early mitotic processes, such as BrdU incorporation, are observed; however, M phase markers are not encountered. Unexpectedly, the neurons die soon after DNA synthesis (al-Ubaidi et al., 1992). Similar transgenic experiments have been performed in numerous neuronal cell types including Purkinje cells (Feddersen et al., 1992) and more recently, forebrain neurons (Park et al., 2007). The results of these experiments are also the same. Transgenic expression of oncogenes in post-mitotic neuronal cells does not result in cell division; it results in neuronal cell death. Studies in the staggerer mutant mouse have also provided insights into cell cycle associated neuronal cell death. The staggerer mutation causes highly predictable cell losses in the cerebellum (Herrup and Mullen, 1979; Zanjani et al., 1990). This mutant exhibits loss of all cerebellar granule cells due to an absence of trophic support from their postsynaptic target, the Purkinje cells, because they do not develop biochemically (Messer et al., 1981; Messer et al., 1990) or morphologically (Landis and Sidman, 1978). Immunohistological analysis of the staggerer mouse indicates that granule cell exhibit elevated levels eof the G1phase marker, cyclin D, as well as the DNA polymerase subunit, proliferating cell cycle antigen (PCNA). In addition to protein expression, granule cell death is accompanied by incorporation of BrdU, indicating DNA synthesis has taken place (Herrup and Busser, 1995). These findings provide evidence that during some neuronal death responses, neurons enter an unscheduled cell cycle. However, these studies do not address whether cell cycle re-entry causes neuronal cell death. 27 Tissue culture systems have provided some of the most detailed evidence establishing a linkage between neuronal cell cycle re-entry and cell death. For example, withdrawal of nerve growth factor (NGF) from sympathetic neurons results in unexpected increases in transcripts for cyclin D, a G1 cell cycle protein, along with neuronal death (Freeman et al., 1994). This approach has been utilized to establish a causative relationship between neuronal cell cycle re-entry and death. Indeed, neuronal exposure to agents that block cell cycle advance, such as ciclopirox and deferoxamine, prevent neuronal death after NGF withdrawal (Farinelli and Greene, 1996). Similar protective effects were also encountered with inhibitors to cyclin dependent kinases (Park et al., 1996). These in vitro models indicate that neuronal death mediated by trophic factor withdrawal is associated with cell cycle re-entry and the death processes are dependent on cell cycle re-entry. In addition to trophic factor withdrawal, a number of other insults have been identified that are also capable of inducing neuronal cell cycle and cell death. For example, the combination of hypoxia and ischemia in adult rodents induces massive loss of hippocampal neurons. Interestingly, many of the neurons initiate DNA synthesis and are TUNEL-positive before succumbing to death. In addition, the neurons also exhibit elevated expression of cell cycle proteins, suggesting that the combination of hypoxia and ischemia is capable of inducing neuronal CCEs and nerve cell death. However, in the same study the authors noted that neuronal cell death mediated by kainic acid induced excitotoxicity caused neuronal death; however, no CCEs were encountered 28 (Kuan et al., 2004), suggesting that neuronal cell cycle re-entry is not encountered in all neuronal death processes. Neuroinflammation and AD There is a substantial body of evidence that inflammation play an important role in AD pathogenesis. An array of proinflammatory cytokines, such as IL-1α, IL-1β, IL-6 and TNFα, has been associated with amyloid deposits in the AD brain (Bauer et al., 1991; Griffin et al., 1995; Mrak and Griffin, 2001). In addition, there are increased numbers of microglia, the resident immune cell of the brain, found in close proximity to amyloid deposits and NFTs (Perlmutter et al., 1990; Akiyama et al., 2000). Importantly, microglia can bind to amyloid fibrils through a complex of cell surface receptors that activate intracellular signaling pathways. This signaling cascade culminates in the induction of proinflammatory cytokines (Bamberger et al., 2003). It has been postulated that these microglial inflammatory products act in concert to produce neuronal toxicity and death. For example, elevated levels of IL-1 may contribute to widespread astrogliosis seen in AD (Griffin et al., 1989), neurodegeneration (Rothwell, 2003; Cardona et al., 2006b) and tau hyperphosphorylation (Li et al., 2003; Kitazawa et al., 2005) in vivo. In addition, stimulation of microglia by fibrillar Aβ can result in TNFαinduced death of neuronal cells (Combs et al., 2001). Chronically activated microglia also increase reactive oxygen and nitrogen species. Several markers of oxidative damage including lipid peroxidation (Sayre et al., 1997), nucleic acid oxidation (Nunomura et al., 1999b; Nunomura et al., 1999a) and protein oxidation 29 (Smith et al., 1997) are elevated in the AD brain. Interestingly, conditioned media obtained from beta-amyloid activated microglia induces neuronal CCEs and neuronal cell death in cultured cortical neurons, suggesting that a unknown proinflammatory factor or factors can induce neuronal cell cycle re-entry (Wu et al., 2000). In contrast, microglial also exhibit protective roles in a number of neurodegenerative diseases, including AD. For example, exogenous application of microglia can offer protective effects against different types of ischemia and oxygen-glucose deprivation. However, the mechanisms behind this remain elusive. Furthermore, in the healthy brain, resting microglia are highly dynamic, continually surveying their microenvironment for pathogens with far-reaching processes (Davalos et al., 2005; Nimmerjahn et al., 2005). When foreign entities, such as Aβ deposits are encountered microglia display morphologic alterations by retracting and enlarging their extensions enabling the glial cells to clear pathogens (Kreutzberg, 1996). Two-photon in vivo imaging has demonstrated that microglia quickly surround newly formed Aβ deposits, possibly limiting further growth of the deposition (Meyer-Luehmann et al., 2008). In addition, two-photon imaging has also shown that microglia can uptake fibrillar Aβ in the mouse brain (Bolmont et al., 2008); however, robust clearance of Aβ deposits is not encountered. 30 Alzheimer’s Disease and Non-steroidal Anti-inflammatory Drugs Compelling retrospective epidemiological studies have also implicated inflammation in disease prevention and risk. For example, patients undergoing long-term treatment for rheumatoid arthritis or other aliments with non-steroidal anti-inflammatory drugs (NSAIDs) exhibit a decreased risk for developing AD (McGeer et al., 1990). Studies have also indicated that long-term NSAID use delays the age of onset, severity and the progression of AD symptoms. However, these epidemiological studies also indicate that a decreased risk for AD is only encountered in individuals that are subject to high doses of a NSAID for greater than 4 to 5 years. For example, a recent large study examining the US Veterans Affairs Health Care system involving close to 50,000 AD cases and 200,000 case controls indicated that individuals subject to ibuprofen for greater than 5 years exhibited a nearly 50% reduction in AD risk (Vlad et al., 2008). Numerous experimental studies also indicate a protective role of NSAIDs in AD pathogenesis. For example, transgenic mouse models of AD administered ibuprofen, a potent NSAID, in their chow exhibited reductions in activated microglia, markers of oxidative stress and reduced Aβ burden (Lim et al., 2000; Yan et al., 2003). The decreased AD-like pathologies are coupled with better performance in behavioral tests than their control fed counterparts (Lim et al., 2001). In addition to ibuprofen, mouse models of AD administered flurbiprofen as well as indomethacin display reductions in Aβ deposition (Sung et al., 2004; Kukar et al., 2007). The pharmacological action of NSAIDs has long been assumed to inhibition of cyclooxygenase 1 and 2 (COX1 and COX2), resulting in 31 decreased synthesis of the pro-inflammatory protaglandins from arachidonic acid (Wyss-Coray, 2006). Thus, one possible mechanism by which NSAIDs protect against AD is through the inhibition of COX activity. However, recent evidence suggests that certain NSAIDs may exert their effects independently of COX1 and COX2. A subset of NSAIDs associated with reduced risk of AD also agonize the peroxisome proliferators-activated receptor gamma (PPARγ) (Lehmann et al., 1997). Stimulation of PPARγ can suppress expression of pro-inflammatory genes in monocytic cells (Jiang et al., 1998) as well as microglia (Combs et al., 2000). Furthermore, mouse models of AD exposed to pioglitazone, a PPARγ agonist, exhibit reductions in glial inflammation (Heneka et al., 2005). However, recent studies have indicated that PPARγ agonists may also exert their protective effects through transcriptional regulation of Bace1. AD mouse models administered pioglitazone display reductions in Bace1 levels as well as steady-state levels of CTFβ, the immediate precursor of Aβ (Sastre et al., 2006). In addition to these alternative targets, certain NSAIDs have been shown to act as gamma-secretase modulators (GSMs). Acute administration of selective GSMs results in the production of shorter, less amyloidogenic Aβ peptides in vitro and in vivo, likely through interactions with APP that influence γsecretase cleavage (Weggen et al., 2001; Eriksen et al., 2003; Kukar et al., 2008). Importantly, ibuprofen has this effect even in the absence of COX enzymes (Weggen et al., 2001). However, not all NSAIDs exhibit equivalent ability to modulate Aβ production. For example, ibuprofen, idomethacin, sulindac 32 sulfide and flurbiprofen modulate Aβ1-42 levels in APP-expressing cells. In addition, AD mouse models subject to oral dosing with these same NSAIDs, for as little as three days, exhibit ~25% decrease in brain Aβ1-42 levels. In contrast, aspirin and naproxen do not exhibit gamma-secretase modulating ability (Eriksen et al., 2003) and some NSAIDs, such as celecoxib, selectively increase Aβ1-42 generation in culture (Kukar et al., 2005). Mouse Models of AD In order to characterize the consequences of early-onset familial Alzheimer’s disease (EOFAD ) mutations on AD-like phenotypes in vivo many different groups have designed transgenic models that express wt APP, FADlinked APP variants, C-terminal truncations of APP or Aβ itself (Hsiao et al., 1996; Sturchler-Pierrat et al., 1997; Holcomb et al., 1998; Hock and Lamb, 2001). In addition to single transgenic mouse models of AD, numerous double transgenic lines have also been created expressing mutant variants of both APP and PSEN (Holcomb et al., 1998; Radde et al., 2006). Two of the most commonly used transgenic mouse models include Tg2576 (Hsiao et al., 1996) and APP23 (Sturchler-Pierrat et al., 1997). The Tg2576 mouse model of AD expresses human APP harboring the Swedish mutation off the hamster prion promoter and begins to exhibit Aβ deposition at about nine months of age. The APP23 animal model also expresses the Swedish variant of APP off the Thy1 promoter and exhibits the first evidence of Aβ deposits at seven months of age. It is important to note that the accumulations of 33 AD-like pathologies and the age of onset of these phenotypes differ greatly between all of the mouse models of the disease (Table 1.1). These differences are likely attributed to the promoter utilized in transgene construction, expression levels of transgene-derived APP, genetic background in which the transgene is maintained as well as the EOFAD mutation. Another approach towards the generation of accurate genetic models of AD has been pioneered by the Lamb laboratory. This method focuses on the introduction of the complete genomic copies of human FAD transgenes into the mouse genome. The genomic-based mouse model of AD, R1.40, has utilized yeast artificial chromosome (YAC) technologies to express the entire human genomic sequence of APP harboring the Swedish mutation under the control of endogenous human regulatory elements (Lamb et al., 1993; Lamb et al., 1999). Importantly, genomic-based transgenic mice expressing FAD mutations in either APP or PSEN1 exhibit increased Aβ levels and amyloid deposition in a manner that recapitulates the observed effects of these mutations in humans. In addition, these AD mouse models have been invaluable for understanding the genetic interactions that may impact Aβ deposition and other hallmark pathologies. For example, genetic background modulates the onset of AD-like pathologies including amyloid deposition and inflammatory responses (Lehman et al., 2003a). In summary, Alzheimer’s disease is a highly prevalent condition of unknown etiologies. The identification of families exhibiting AD at a very early age has greatly facilitated our genetic and molecular understanding of AD pathogenesis. In addition to the presence of senile plaques and NFTs, there is 34 evidence of synaptic and neuronal cell loss as well as neuroinflammation. Numerous immunohistological and cytogenetic studies have indicated that neuronal populations subject to degeneration in the AD brain exhibit evidence of re-entry into a mitotic cell cycle or cell cycle events (CCEs). Importantly, neuronal CCEs are seen at much lower levels in control brain tissue and in regions of the AD where degeneration is not prevalent. Taken as a whole, these data indicate that neuronal CCEs may be a valuable marker for disease risk and progression. Furthermore, we postulate that neuronal CCEs may be the first step in a long, slow atrophy and eventual death. However, the insult(s) that induce ectopic neuronal cell cycle re-entry in the AD brain remains undefined. For my dissertation I have focused on testing the hypothesis that neuroinflammatory processes, initiated by soluble aggregates of Aβ, termed oligomers, induce neuronal CCEs in mouse models of the disease and by extension the human condition. 35 Research Objectives To determine the insult that induces neuronal CCEs in Alzheimer’s disease I have taken advantage of the genomic-based mouse model of AD, R1.40. The R1.40 animal model of AD expresses mutant human APP under endogenous human regulatory elements. As a result, the R1.40 mouse model of the disease mimics the correct temporal and spatial expression patterns observed in the human brain (Lamb et al., 1993; Lamb et al., 1997). In addition, the R1.40 model is maintained in different inbred mouse strains by repeated backcrossing (Lehman et al., 2003a). These models allow us to modulate a variety of AD-like phenotypes on defined genetic backgrounds. As mentioned above, analysis of human brain tissue indicates that neuronal populations at-risk for death in the AD brain exhibit ectopic expression of canonical cell cycle proteins (Vincent et al., 1996; McShea et al., 1997; Busser et al., 1998). In addition, individuals with MCI also exhibit evidence of cell cycle re-entry, suggesting that neuronal CCEs may be one of the earliest markers of AD (Yang et al., 2003). Thus, genetic mouse models of AD will allow us to examine the nature of the signal that induces neuronal CCEs. I will utilize these genetic systems to test the relationship between Aβ oligomers, neuroinflammation and neuronal cell cycle re-entry. Neuronal Cell Cycle Events and Alzheimer’s Disease Mouse Models: Chapter 2 describes the analysis and characterization of neuronal CCEs in three different mouse models of AD. Each of these models of EOFAD exhibits 36 different levels of transgene-derived APP, steady-state levels of Aβ peptides as well as the age of onset of fibrillar Aβ deposition. Using both immunohistochemistry and fluorescent in situ hybridization, we show that neurons in the three mouse models reproduce neuronal CCEs found in human AD. Interestingly, the genomic-based R1.40 mouse model of AD recapitulates the correct spatial and temporal pattern of neuronal CCEs encountered in human AD brain tissue. These studies indicate that in addition to amyloid deposition, the R1.40 mouse model of AD also exhibits neuronal CCEs in a pattern that closely mimics that encountered in human AD, suggesting that this model can be utilized to identify the factors that induce neuronal cell cycle re-entry. Aβ and Neuronal Cell Cycle Events in AD Mouse Models: Chapter 3 utilizes both the R1.40 mouse model of AD and in vitro tissue culture to test the hypothesis that Aβ oligomers induce neuronal CCEs. First, we characterize the appearance of neuronal CCEs in R1.40 mice maintained on the C57BL/6 (B6R1.40) background. Importantly, we observe that ectopic neuronal cell cycle reentry occurs in disease-relevant neuronal populations six to eight months before detectable Aβ deposits, suggesting that specific amyloid precursor processing products are responsible for the induction of neuronal CCEs. Furthermore, a reduction in the steady-state levels of Aβ (achieved by shifting the genetic background from the C57BL/6 to the DBA/2 mouse strain) dramatically delays the appearance of neruonal CCEs. More significantly, elimination of β-secretase activity blocks the appearance of cell cycle re-entry, providing genetic evidence 37 that the amyloidogenic processing of APP is required for the induction of CCEs. Finally, in vitro preparations of oligomeric, but not monomeric, Aβ induce DNA synthesis in dissociated cortical neurons. Together, these data suggest that Aβ oligomers are both necessary and sufficient for the induction of neuronal cell cycle re-entry in mouse models of AD and by extension the human condition. Neuroinflammation and Neuronal Cell Cycle Events in AD Mouse Models: In chapter 4 we test that hypothesis that neuroinflammation may act as the triggering event for the aberrant neuronal CCEs. In support of this idea, Aβdependent alterations in brain microglia occur coincidently with the appearance of the CCEs in the R1.40 mice. Furthermore, promotion of neuroinflammation at young ages in the R1.40 animals induces ectopic neuronal CCEs, while treatment with two commonly used non-steroidal anti-inflammatory drugs (NSAIDs) blocks both the alterations in brain microglia as well as neuronal CCEs. These independent findings suggest that inflammatory processes impact the induction of neuronal CCEs. 38 39 Figure 1.1: Processing of the Amyloid Precursor Protein APP, a type 1 transmembrane protein enriched in neuronal tissues containing the Aβ sequence, can be cleaved in one of two pathways. (A) α-secretase cleavage of APP generates a N-terminal fragment, sAPPα, and a membrane-associated C-terminal fragment, CTFα. This pathway is considered non-pathogenic because it precludes the formation of the Aβ peptide. (B) The alternate cleavage pathway of APP generates the secreted Aβ peptide of varying amino acid length. β-secretase cleavage at the N-terminus of the Aβ peptide generates a N-terminal fragment, sAPPβ, and a membrane-associated C-terminal fragment, CTFβ. Subsequent cleavage of CTFβ at the C-terminus of the Aβ sequence by βsecretase results in the production of the Aβ peptide. In addition to Aβ, γsecretase cleavage also releases AICD into the intracellular space. EOFAD mutations in APP, highlighted by arrows, influence this cleavage pathway. 40 Table 1.1 APP Transgenic Mouse Models Transgenic Line1 Tg2576 Genetic Promoter Background and Mutation Mixed Hamster Prion C57BL/6, (PrP)-APPswe SJL Mixed (Thy-1)C57BL/6, APPswe DBA/2 Congenic Human Maintained Genomic on C57BL/6 APPswe and DBA/2 C57BL/6 Human Genomic APPswe Onset of Aβ Deposition 9 to12 Months 7-9 Months References Hsaio, 1996 APP23 SturchlerPierrat, 1997 Lehman, 2003 R1.40 12 to14 Months N.R. (No Varvel, 2008 Detectable CTFβ Generation) 1 Transgenic mouse models overexpress a human APP cDNA under the promoters indicated with the exception of the R1.40 that utilizes endogenous human regulatory elements 2 R1.40;Bace1-/-2 R1.40 transgenic mouse maintained on a Bace1 null background. N.R.-Not Reported 41 Figure 1.2: Amyloid Cascade Hypothesis Diagram illustrating the factors associated with Aβ production and deposition in AD. APP can be cleaved by either α-secretase, which precludes the generation of Aβ. Alternatively, APP can be cleaved by β-secretase, which leads to the generation of Aβ peptides. The foundation of this hypothesis is the presence of genetic mutations in EOFAD families. Specifically, the Swedish FAD mutation at APP 670/671 preferentially increases β-secretase cleavage and leads to elevated levels of the 99 amino acid precursor, CTFβ. Mutations at APP 717 and PSEN1 and PSEN 2 alter γ-secretase cleavage and lead to increased production of the longer, more amyloidogenic Aβ1-42. 42 43 Figure 1.3: The Mitotic Cell Cycle The eukaryotic cell cycle is separated into four functionally distinct phases: growth 1 phase (G1), DNA synthesis phase (S), growth 2 phase (G2) and mitosis phase (M). G1, S and G2 are known as interphase; the period of time the cell takes to prepare for M phase and cytokinesis. In G1, the levels of cyclin D increase and bind to either cyclin-dependent kinase 4 (Cdk4) or 6 (Cdk6). This complex, in turn, phosphorylates the retinoblastoma protein, pRb, releasing the E2F protein. The E2F protein then acts as a transcription factor for genes needed for further cell cycle progression. In S phase the cell replicates the DNA so the new daughter cell can have a full complement of genes. In S phase, levels of cyclin A increase and bind to and activate Cdk2. In addition to cell cycle regulation of the cyclin-dependent kinases by the cyclins, cyclin-dependent inhibitors (CKIs) also control the kinase activity. 44 Chapter 2: Ectopic Cell Cycle Events Link Human Alzheimer’s Disease and Amyloid Precursor Protein Transgenic Mouse Models Yan Yang,1* Nicholas H. Varvel,2,4* Bruce T. Lamb2,3,4 and Karl Herrup1,2 1 2 Department of Neurology, University Hospitals of Cleveland, Departments of Neurosciences and 3Genetics, Case Western Reserve University, Cleveland, Ohio 44106, and 4Department of Neurosciences, Lerner Research Institute, The Cleveland Clinic Foundation, Cleveland, Ohio 44195 *Y.Y. and N.H.V. contributed equally to the work This manuscript was previously published: Journal of Neuroscience 2006 26(3):775-784. 45 Contributions of Authors Karl Herrup, Yang Yang, Bruce T. Lamb and Nicholas H. Varvel wrote the manuscript. The data was generated and analyzed by Yan Yang and Nicholas H. Varvel. Acknowledgements The authors thank Matthias Staufenbiel (Novartis Institute for Biomedical Research, Basal, Switzerland) for providing paraffin sections of the APP23 transgenic mice and Laura Kulnane for animal husbandry. This work was supported by grants from the National Institute on Aging and the National Institute of Neurological Disorders and Stroke (AG08012 and NS20591 to K.H., AG023012 to B.T.L.), the Alzheimer’s Association (K.H. and B.T.L.), an Anonymous Foundation, The Fidelity Foundation (B.T.L.) and by a gift from the Blanchette Hooker Rockefeller Fund. 46 Introduction Alzheimer’s disease (AD) is a late-onset human neurodegenerative disorder marked by a progressive dementia and a spectrum of behavioral abnormalities. Neuropathological investigation of the AD brain reveals plaques of β-amyloid peptide and tangles of hyperphosphorylated tau protein. Neuronal density (cell bodies and synapses) is reduced in the frontal, entorhinal, and hippocampal cortices. In addition, certain subcortical populations of neurons undergo substantial amounts of neurodegeneration. These include the locus ceruleus (Zweig et al., 1988; Zarow et al., 2003), the dorsal raphe (Zweig et al., 1988; Chen et al., 2000a), and the basal nucleus of Meynart (Whitehouse et al., 1982). Several transgenic mouse models have been generated that recreate the genetic changes found in familial AD (Lamb and Gearhart, 1995; Hsiao et al., 1996; Sturchler-Pierrat et al., 1997; Holcomb et al., 1998; Oddo et al., 2003). Transgenic mice expressing mutant human amyloid precursor protein (APP) genes exhibit an age-related development of diffuse and neuritic plaques, with plaque burdens often approaching those found in advanced cases of AD. This has proven to be a valuable resource in the exploration and design of disease therapies (Schenk, 2002). In addition, the AD mice show microglial activation, astrocytosis, and changes in neuronal cytoskeletal proteins including tau (Games et al., 1995; Hsiao et al., 1996; Holcomb et al., 1998; Stalder et al., 1999). Many of these model organisms have also been shown to have significant memory deficits (Hsiao et al., 1996; Holcomb et al., 1998; Oddo et al., 2003). Despite these parallels to the human disease state, however, none of the mouse models 47 has yet been shown to develop the typical neurofibrillary tangles or to suffer any significant loss of neuronal cell bodies (for review, see (Hock and Lamb, 2001). The reason for the discrepancy between the human and mouse neurodegenerative phenotype is unclear. It is conceivable that the models are inaccurate, yet the genetic mimicry is excellent. Recently, we and others have shown a close association between the neuronal cell death in AD and cellular processes that normally only occur during a mitotic cell cycle. Cell-cycle-related proteins are expressed in neurons that are “at risk” in AD but not in age-matched controls or in regions of the AD brain itself where degeneration is not prevalent. This ectopic re-expression of cell cycle markers is functional as shown by fluorescent in situ hybridization (FISH) (Yang et al., 2001). Because an aberrant neuronal cell cycle is closely related to the neuronal degeneration in human brain, we wanted to explore whether this phenotype was preserved in the neurons of the AD mouse model. We report here that cell-cycle processes have begun in three different models. These cell-cycle alterations are found before β-amyloid (Aβ) plaques in a pattern that recapitulates the selective neuronal vulnerability observed in AD. Thus, the fidelity of the mouse models of AD, although not perfect, may be better than had been appreciated previously. 48 Materials and Methods Transgenic Mouse Models of AD Four different transgenic mouse models of AD were used in the current studies. In each line, the APP-induced amyloid plaques develop at different ages. Detailed information about the mouse strains are summarized in Table 1. Animals (R1.40, Tg2576, and Tg2576/PSEN1) were genotyped by PCR and housed at Case Western Reserve University Medical School Animal Resource Center, a facility fully accredited by the Association for Assessment and Accreditation of Laboratory Animal Care. All procedures for animals were approved by the Institutional Animal Care and Use Committee of Case Western Reserve University. Paraffin-embedded, 10 µm sections of the APP23 mouse brain were a generous gift from Dr. M. Staufenbiel (Novartis Institute for Biomedical Research, Basel, Switzerland). Histology Animals were deeply anesthetized with Avertin (0.02 cc/mg body weight); they were perfused transcardially with PBS, followed by 4% paraformaldehyde in 0.1 M sodium phosphate buffer (PB). The brain was dissected, immediately removed from the cranium, and transferred to fresh 4% paraformaldehyde at 4°C overnight. The brains were then cryoprotected by sinking in 30% sucrose in 0.125 M PB at 4°C overnight. After bisecting along the midline, the brains were embedded in OCT compound. Then cryostat sections were cut and allowed to air dry on SuperPlus glass slides overnight. 49 Single and Double Immunohistochemistry The proliferating cell nuclear antigen (PCNA) mouse monoclonal antibody recognizing the PCNA p36 protein (Dako, High Wycombe, UK) was diluted 1:250 in 10% goat serum/PBS blocking buffer before use. The rabbit polyclonal cyclin A antibody (ab 7956; working dilution, 1:200; Abcam, Cambridge, UK) was raised against the C-terminal domain of cyclin A2. The mouse monoclonal NeuN antibody (dilution, 1:500; Chemicon, Temecula, CA) was used as a neuronal marker. The rat monoclonal CD45 antibody (catalog #MCA1388; working dilution, 1:500; Serotec, Raleigh, NC) was used as a microglial maker. To perform double fluorescence immunocytochemistry, sections were first rinsed in PBS, followed by pretreatment in citrate acid buffer (0.1 M citrate acid and 0.1 M sodium citrate, pH 7.4) for 6–8 min at 95°C. After the slides had cooled in buffer for 30 min at room temperature, they were rinsed in PBS. Sections were incubated for 1 h at room temperature in 10% goat serum in PBS to block nonspecific binding. All primary antibodies were diluted in PBS containing 0.4% Triton X-100 and 10% goat serum and were applied to sections and incubated overnight at 4°C. After rinsing in PBS, they were incubated for 2 h with a secondary antibody, which was conjugated with various fluorescent Alexa dyes (dilution, 1:500; Molecular Probes, Eugene, OR). The sections were then rinsed in PBS and reincubated in 10% goat serum blocking solution for 1 h, followed by the addition of the second primary antibody (raised in a different species from the first primary antibody) for a second overnight incubation at 4°C. Sections were then rinsed in PBS, and the second secondary antibody, 50 conjugated with a different fluorescent dye, was applied to the sections for 2 h at room temperature. After rinsing, all sections were mounted in PBS/glycerol under a glass coverslip. All paraffin-embedded APP23 mouse sections were deparaffinized in xylene and rehydrated through graded ethanols to water. For staining using HRP-conjugated secondary antibodies, the sections were pretreated in 0.3% hydrogen peroxide in methanol for 30 min to remove endogenous peroxidase activity, rinsed in Tris-buffered saline (TBS), and treated with 0.1 M citrate buffer in a microwave at sufficient power to keep the solution at 95–100°C for 10 min. Sections were cooled in the same buffer at room temperature for 30 min and rinsed in TBS. Slides were incubated in 10% goat serum in PBS blocking solution for 1 h at room temperature, after which a primary antibody was applied to the sections that were then incubated at 4°C overnight. The sections were washed three times in TBS before applying the secondary antibody (Vector Laboratories, Burlingame, CA), which was diluted in blocking solution at 1:300. The secondary antibody was applied for 1 h at room temperature. Afterward, sections were rinsed three times in TBS. Rinsed sections were then incubated in Vectastain ABC Elite reagent for 1 h and developed using diaminobenzidine (DAB), according to the protocol of the manufacturer. The sections were counterstained with hematoxylin, and after dehydration, all sections were mounted in permount under a glass coverslip. Control sections were subjected to the identical staining procedure, except for the omission of the primary antibody. 51 Flourescent in situ Hybridization (FISH) Three mouse-specific DNA probes were generated from bacterial artificial chromosomes (BACs), which carried individual specific mouse genomic DNA sequences. One of the DNA probes (480C6) was made from the region that encodes the Sim2 located on mouse chromosome 16. The other two probes were generated from overlapping BACs (170L21 and 566) containing the structural gene for aldolase C on mouse chromosome 11. Each of the three probes covers 100–300 kb of unique genomic sequence. They were labeled by standard nick translation protocols using digoxygenin-labeled dUTP. After labeling, probes were concentrated with mouse Cot-1 DNA (Invitrogen, San Diego, CA) to block hybridization to repetitive sequences. Before hybridization, all sections were rinsed in PBS and pretreated with 30% pretreatment powder (Oncor, Gaithersburg, MD) for 15 min at 45°C, followed by treatment with protease (0.25 mg/ml; Oncor) for 25 min at 45°C. After rinsing in 2 SSC [for details, see Sambrook et al. (1989)], the slides were dehydrated through graded alcohols and allowed to air dry. The labeled probe was applied to the individual sections, which were then covered with a glass coverslip and sealed with rubber cement. To denature DNA, slides were heated at 90–92°C on a heated block for 12 min and hybridized with probe overnight at 37°C. After rinsing in 50% formamide and 2 SSC at 37°C for 15 min, the slides were transferred to 0.1 SSC buffer for 30 min at 37°C and rinsed in PN buffer (0.5 M PB with 0.5% NP-40) at room temperature. To block nonspecific antibody binding, 10% goat serum in PBS was applied to the sections, followed by incubation in mouse 52 antidigoxygenin primary antibody (dilution, 1:200; Boehringer Mannheim, Indianapolis, IN) for 30 min at 37°C. After rinsing, a secondary antimouse antibody conjugated with Alexa 488 (dilution, 1:250) was applied to the sections for 30 min at 37°C. Slides were rinsed three times in PN buffer, and the sections were counterstained with either 4–6-diamidino-2-phenylindole (DAPI) or propidium iodide and covered with a coverslip. The number of spots of hybridization in each nucleus was determined at 1000x under fluorescent illumination. Images were captured on a Leitz (Wetzlar, Germany) research microscope equipped with a digital camera (Prog C14). Neurons were counterstained and identified on the basis of the size of their nucleus and their position either in the front cortex or hippocampus. Results Cell-cycle Events in R1.40 Animals We chose as our mouse model a line carrying the entire human APP gene on a yeast artificial chromosome. The transgene was engineered to mimic the double mutation known as the Swedish mutant (K670M/N671L), and the line of mice carrying the construct is known as R1.40. As reported previously, this line develops classic Aβ plaques in cortical regions beginning at 13 postnatal months. By 22 months of age, there are substantial numbers of 6E10 immunoreactive deposits in both the cortex and hippocampus. The density of these plaques is higher in the cortex than in the hippocampus, and antibody staining for the presence of hyperphosphorylated tau epitopes (AT8) is found around the plaques 53 (Kulnane and Lamb, 2001). R1.40 brain tissue was examined for the presence of cell-cycle proteins by immunocytochemistry. Figure 2.1 shows images from a 22-month old R1.40 homozygous transgenic mouse. Marked amyloid plaque pathology is found in both the hippocampus and cortex by this age (data not shown). Figure 2.1, A–F, shows a typical pattern of immunostaining of the PCNA in the frontal cortex (Figure 2.1, A–C) and hippocampus (Figure 2.1, D–F) of transgenic R1.40 animals. As indicated by the arrows, many neuronal nuclei stained positive for the presence of this DNA polymerase/replication fork subunit. Age-matched nontransgenic mice from the same genetic background (C57BL/6) had no or only an occasional PCNA-positive neuron in these regions, as illustrated here in the frontal cortex (Figure 2.1, G–I). A similar pattern of cell-cycle protein staining was found with the S-phase cyclin, cyclin A. Cyclin A is a regulatory subunit of Cdk2 and is normally elevated only during the S phase in dividing cells. We observed substantial numbers of cyclin A-positive cells in the R1.40 transgenic neocortex (Figure 2.1, J–L) and hippocampus (Figure 2.1, M–O) but not in nontransgenic, age-matched controls (Figure 2.1, P–R). Figure 2.1, J–L, taken at a higher magnification, clearly illustrates the neuronal morphology of the “cycling” cells. Cells located in cortical layers II/III and V were most frequently stained for cell-cycle proteins. In contrast to the images of PCNA-positive neurons in Figure 2.1, A–F, however, cyclin A protein was found localized to the neuronal cytoplasm of the cortex or hippocampus of transgenic R1.40 animals. To insure that the presence of both PCNA and cyclinA proteins was indicative of 54 neurons undergoing a true cell cycle, we used FISH on our material. Probing with a digoxygenin-labeled 300 kb BAC carrying unique sequences from mouse chromosome 11, we observed the situation illustrated in Figure 2.2. Many cells in the region where PCNA staining was found were labeled with more than two hybridization signals in their nuclei. This was true of neurons in both the neocortex (Figure 2.2, A and C) and hippocampus (Figure 2.2, B and D). No such cells were found in the aged-matched nontransgenic controls (Figure 2.2, E and F), and no hyperploid neuronal cells were found in the cerebellum (data not shown). Two different autosomal probes were used to achieve these images, one on chromosome 11 and a second on chromosome 16. The results from both probes were identical: substantial evidence of hyperploidy in cells of the R1.40 transgenic brain with a few examples of aneuploid neurons in comparable regions of nontransgenic, age-matched controls. Fields such as these are representative of the situation found in our material. Because of the relatively large areas that we routinely scan, we rely on a standard fluorescent microscope rather than a confocal microscope. The photographs of hyperploid cells taken on such a microscope will often give the impression that the spots of hybridization are actually coming from two overlapping nuclei rather than one. Part of this impression derives from the fact that the nuclei of the aneuploid cells are often misshapen. This is common experience in the field of cancer biology, in which the pathologist will use the deviation from spherical of the nuclear shape of a cell to obtain an estimate of the degree of aneuploidy in a tumor (Boone et al., 1992). For each field illustrated, however, the observer was careful to focus through the 55 entire depth of the section (at 1000x using an oil-immersion objective) to ensure that there was only one nucleus. Furthermore, reanalysis of the same sections on a confocal microscope resulted in the same conclusions. These images regularly reveal three (Figure 2.3A) and four (Figure 2.3B) hybridization spots in transgenic but not control animals. Thus, by both immunocytochemistry and FISH, many neurons in the 22 month R1.40 transgenic mouse brain show evidence of having re-entered a cell cycle. We wanted to determine whether the evidence indicated an active process of cell division or instead a situation more similar to the human AD brain in which the neurons enter the cycle only to stall at a point either near the end of S phase or during G2. Bromodeoxyuridine (BrdU) was injected into the transgenic mice 2 h before they were killed. If cycling were on-going, the modified DNA precursor should be taken up into the dividing cells and incorporated into their DNA. Immunocytochemical labeling of the CNS should then reveal the location of the actively dividing cells. Despite repeated attempts, and examination of thousands of neurons in dozens of sections, no BrdU-labeled neuronal nuclei were ever observed. The only exceptions were cells in the known neurogenic regions lining the lateral ventricle and in the inferior blade of the hippocampal dentate gyrus (data not shown). The size, cytological features, and position of the cycle-positive cells strongly implicates their identity as neuronal. We used a panel of antibodies to validate this impression. As a neuronal marker, we used the nuclear antigen NeuN. GFAP was used as an astrocyte marker. The non-neuronal (GFAP- 56 positive) cells in the transgenic brain were more often reactive than in controls (Figure 2.2, I and J). This is in keeping with the previously described reactive gliosis and inflammatory processes at work in these animals (Games et al., 1995; Hartlage-Rubsamen et al., 2003). Nonetheless, most of the cyclin A-positive nuclei were double labeled with NeuN antibody, indicating their identity as neurons (Figure 2.2, G and H). Other Mouse Models of AD To validate our findings in the R1.40 mouse, we chose to examine additional transgenic mouse models of AD. The Tg2576 mouse is a commonly used model in which a cDNA for human APP695, containing the Swedish mutation (K670M/N671L) is driven by the hamster prion promoter. The animals develop an early behavioral phenotype, and plaques appear by 9 postnatal months. Examination of the immunostained cortex and hippocampus of 12month-old Tg2576 mice revealed a substantial number of PCNA- or cyclin Apositive neurons in both the cortex (Figure 2.4A) and hippocampus (Figure 2.4B). Neurons from control mice were negative for cell-cycle proteins in these same regions (Figure 2.4, C and D). We were also able to obtain sections from APP23 mice. These animals carry a cDNA for human APP751 driven by the murine Thy-1 promoter (Bornemann and Staufenbiel, 2000). They normally develop plaques at 6 months of age and have 25% neuronal cell loss in the CA1 region of the hippocampus by 14 months of age. When we examined these animals for evidence of cell-cycle-related proteins, we found PCNA and cyclin A 57 staining in both the cortex (Figure 2.4E) and hippocampus (Figure 2.4F) by 1 year of age. Indeed, consistent with the more virulent nature of the pathology in these animals, the density of immunopositive cells in APP23 was greater than in any of the other models we examined. Wild-type littermates had no such staining (Figure 2.4, G and H). We note that Gartner et al. (2003) have previously examined the APP23 for cell-cycle protein immunoreactivity, finding no difference in staining between transgenic and age-matched controls at 21.5 months of age. Our findings differ from theirs primarily in that we are unable to find evidence for cell-cycle protein expression in 22-month-old C57BL/6 nontransgenic controls. The direct overlap between this study and ours is restricted to the expression of cyclin A, and we would suggest that any one of several points could explain the discrepancies in the two studies. The previous study used floating 30 µm sections as opposed to 10 µm paraffin sections in the current work. Our staining regimen used an antigen-retrieval protocol, whereas the previous work did not. Finally, (Gartner et al., 2003) used a polyclonal cyclin A antibody (Santa Cruz Biotechnology, Santa Cruz, CA) that would recognize both cyclin A1 and A2. The antibody used to obtain the results in Figure 4 was a monoclonal antibody raised against a cyclin A2-specific peptide. A high background of cyclin A1 might have obscured an increase in the mitotic cyclin A2 protein. Because the previous study provided no evidence for the presence or absence of DNA replication, we propose that in the aggregate, our data provide strong evidence that three of the current mouse models of AD each develop cell-cycle-positive neurons in the cortex and hippocampus. 58 Regional Variation The plaque pathology of the R1.40 mouse does not develop uniformly throughout the CNS. Rather, the neocortex is heavily involved with the hippocampus, and the olfactory bulb is also affected. Similarly, the presence of cell-cycle-positive neurons also varied substantially from region to region of the transgenic nervous system. As in AD, the R1.40 transgenic mouse cerebellar cortex is spared the effects of the disease. No cell evidence of neuronal cell cycling was found in Purkinje, granule, basket, or stellate cells (Figure 2.5O). Nearly one-third of the neurons of the deep nuclei, however, were brightly positive for both PCNA and cyclin A (data not shown). The neocortex was the site with the highest density of “dividing” neurons (Figure 2.1, A–C and J–L) although even here there was consistent variation among the regions of the neocortex, with frontal regions showing the highest density of cycle-positive cells, followed by occipital. Parietal regions had the lowest density of neurons. Subcortical structures were also examined carefully. The thalamus and hypothalamus were negative, as were most dorsal midbrain structures. We paid special attention to the cholinergic neurons in the basal forebrain as well as the neurons of the dorsal raphe and the locus ceruleus. The two brainstem nuclei were strongly immunoreactive for cell-cycle protein (Figure 2.5). Tyrosine hydroxylase (TH) immunoreactivity was used to identify the neurons of the locus ceruleus. Double immunostaining clearly shows the presence of cyclin A protein (Figure 2.5A) in these noradrenergic neurons (Figure 2.5B) in R1.40 animals but not in nontransgenic mice (Figure 2.5, D–F). The characteristic shape and 59 position of the raphe nuclei were used as the identifiers for the serotonergic neurons of the dorsal raphe. A significant number of neurons in these regions were positive for the cell-cycle marker cyclin A (Figure 2.5G) and tryptophan hydroxylase (Figure 2.5H), which is a marker of serotonergic neurons. Cell cycle markers were absent from nontransgenic controls (Figure 2.5, J–L). No evidence of neuronal cell cycling was found among the TH-positive neurons of the substantia nigra (Figure 2.5N) in any of the 22-month-old transgenic and wild-type animals (data not shown) we examined. This finding was especially significant because in the sagittal sections we examined, cells of the locus ceruleus (cell cycle positive) and substantia nigra (cell cycle negative) were often encountered in the same section. The basal nucleus of Meynart is the source of the forebrain cholinergic projection fibers to the hippocampus. The majority of these neurons are lost during the course of AD, and previous work from our laboratory has shown evidence for both cell-cycle protein reexpression and DNA replication in the human neurons (Yang et al., 2001). Curiously, none of the animals that we examined had any instances of cell-cycle proteins re-expressed in the ChAT-positive neurons of the basal forebrain (Figure 2.5M). Neuronal Cell-Cycles Initiate Before Plaques One value of a mouse model of a human disease is the opportunity it offers to perform precise longitudinal studies of genetically identical animals. Previous work has shown that the R1.40 mice develop their first dense plaque deposits at 13 months of age. We wanted to determine the relationship between 60 the timing of the appearance of these deposits with the initiation of the ectopic cell-cycle events (CCEs). To accomplish this, we killed animals at various ages (3, 6, and 10 months) and examined their CNS for signs of cell-cycle processes. As expected from previous studies, no evidence of either Aβ deposits or neurofibrillary tangles could be found in these younger brains (data not shown). In contrast, when 10-month-old R1.40 transgenic animals were examined for the presence of cell-cycle proteins, we found numerous examples of cycling neurons in both the neocortex (Figure 2.6I) and hippocampus (Figure 2.6K). At 3 months of age, we found no examples of CCEs in any of the neurons of the R1.40 mouse brain (Figure 2.6, A and C and Figure 2.7, A and B). At 6 months, however, we were reliably able to detect cell-cycle proteins in both the cortex and hippocampus (Figure 2.6, E and G). No evidence of cell-cycle proteins (Figure 2.6, B,D,F,H, J and L) or DNA replication (Figure 2.7, C,F and I ) were observed in the non-transgenic controls. In addition to this immunocytochemical evidence, the same relationship between cell-cycle proteins and DNA replication was found at this age. FISH with probes for loci on mouse chromosome 11 and chromosome 16 applied to adjacent sections demonstrated significant numbers of cells in the 6-month-old (Figure 2.7, D and E) and 10-month-old (Figure 2.7, G and H) R1.40 animals with three or four “spots” of hybridization in their nucleus. Thus, the neurons in the R1.40 transgenic mouse initiate a cell cycle before the appearance of the Aβ deposits form anywhere in the brain. 61 Reactive Microglia do not Associate with Locations of Neuronal Cell Cycles To examine the relationship between sites of the neuroinflammatory response and neuronal cell-cycle involvement, R1.40 animals were examined for activated microglia. We examined adjacent brain sections for cell-cycle markers and reactive microglial cells, using CD45 immunostaining as an indicator of the latter. In adult R1.40 transgenic mice, cyclin A- and PCNA-immunopositive cells were found at relatively high densities in the frontal cortex, with the greatest concentration located in cortical layers II and III. In addition to these Alzheimer’slike pathological features, when we examined 22-month-old R1.40 animals, CD45-immunoreactive microglia were observed throughout (Figure 2.8, A and B). However, this coincidence of microglial markers with the CCEs did not extend to other regions. The most extreme example of this was the brainstem nuclei in which, as shown in Figure 5, CCEs are easily detected in both the dorsal raphe and locus ceruleus. Examination of adjacent sections, stained for CD45 antigen, however, revealed no reactive microglial cells in either of these regions. This is illustrated by the absence of DAB reaction product in the R1.40 locus ceruleus shown in Figure 2.8, C. In addition to this spatial dissociation between the CCEs and the microglial cell response, there was also a significant temporal dissociation. The first CD45+ cells are observed at close to 1 year of age in the R1.40 cortex. Yet, as illustrated in Figures 2.6 and 2.7, the CCEs are apparent 6 months earlier. Thus, in both space and time, the inflammatory response in the R1.40 mouse model does not appear to predict or even coincide with the occurrence of the cell-cycle markers. 62 Discussion The results presented here document the initiation of a cell-cycle process in the neurons of several mouse models of familial AD. By both the expression of cell-cycle proteins and the documentation of DNA replication, we have shown that these normally postmitotic cells attempt a process that strongly resembles a mitotic cell division. There are a growing number of conditions in the mouse in which neuronal cell death is associated with re-entrance into a lethal cell cycle. These include the retinoblastoma-deficient mouse (Clarke et al., 1992; Jacks et al., 1992; Lee et al., 1992), cerebellar targetrelated cell death (Herrup and Busser, 1995), oncogene expres expression in maturing neurons (Feddersen et al., 1992) oxidative stress as suggested by the harlequin mouse (Klein et al., 2002), as well as models of stroke (Katchanov et al., 2001) and the superoxide dismutase-1 mouse model of amyotrophic lateral sclerosis (Ranganathan et al., 2001; Ranganathan and Bowser, 2003). The weight of this in vivo evidence, combined with elegant studies in cell culture (Farinelli and Greene, 1996; Giovanni et al., 1999; Greene et al., 2004) strongly implicates the initiation of cell cycling as a causative factor in the death of these neurons. A recent addition to this correlation between neuronal CCEs and cell death is the demonstration by our laboratory that in the mouse model of ataxia-telangiectasia (atm -/- ), Purkinje cells and striatal neurons also initiate a cell-cycle-like process (Yang and Herrup, 2005). The current report illustrates that CCEs are correlated with neuronal death in several different mouse models of human AD just as in the human condition itself. But viewed in conjunction with the previous work, it is clear that 63 the CCEs should not be interpreted as unique to Alzheimer’s disease or any other disease or disease model. Our findings also emphasize the unexpected conclusion that although the CCEs may be a necessary first step (as suggested by the cell-culture findings cited above), they are not an immediate cause of neuronal cell death, at least in mouse models. In the R1.40 mice, DNA replication leading to “hyperploid” cells is apparent as early as 6 months, yet cell death is not observed at any age. This means the initiation of the cell cycle, including DNA replication, can be followed by many months during which the aneuploid neurons persist in what we can assume is a near functional state [only mild behavioral abnormalities are reported (Hock and Lamb, 2001), and these can be resolved rapidly (Dodart et al., 2002)]. This is consistent with the calculations of Busser et al. (1998) and Yang et al. (2001) in human Alzheimer’s disease brains. Using different techniques, both studies reached nearly identical conclusions: the death of the neurons in the Alzheimer’s brain occurs months after the CCEs. There would seem to be two basic interpretations of these observations. The first is that the CCEs themselves are necessary but not sufficient to induce the death of adult CNS neurons. Perhaps, just as in cancer, a “second hit” is needed (Zhu et al., 2004). One such triggering event could be hypoxia–ischemia, as two recent studies implicate CCEs in the neuronal death after hypoxia–ischemia in rodents (Kuan et al., 2004; Wen et al., 2004). In addition, recent studies in transgenic mice producing wild type human tau but no endogenous mouse tau have documented the formation of neurofibrillary tangles and neuronal cell death associated with altered CCEs 64 (Andorfer et al., 2005). The suggestion is that different tau isoforms or tau expression patterns could be another potential triggering event. A final intriguing possibility is that, for unknown reasons, the CCEs we observe are actually protective responses of a neuron under stress and that much as in certain developmental situations (Claycomb et al., 2004) the neuron benefits from having multiple copies of each allele. The end result of a neuronal cell cycle is the death of the cells, but the long times required between initiation of the cycle and death suggests that in vivo there are other factors that must be involved in the death process. Putting aside the consequences of the CCEs, it is noteworthy that in a wide variety of different neurodegenerative conditions, these events are reliable and early markers of neuronal distress. Viewed through this lens, the R1.40 mouse model of AD becomes a more accurate model of the human disease than might have been expected. All extant mouse models have been viewed as compromised because they lack the severe behavioral and neurological phenotypes of the human disease. Furthermore, although the mimicry of the amyloid plaque pathology is excellent, it has been somewhat disappointing that neurofibrillary tangles and the neuronal cell death, both central to the human phenotype, are found only occasionally in the numerous mouse models of AD. If we take the cell-cycle abnormalities as surrogates for the early stages of cell death, however, the work reported here suggests that the R1.40 mouse is actually a significant and relatively accurate disease model. As has already been reported, the evolution of the plaque pathology, early tau phosphorylation events 65 and inflammatory markers, are both spatially and temporally correct in their expression (Kulnane and Lamb, 2001). What is remarkable about the CCEs is that they are similarly correct in their anatomical appearance. The markers appear most strongly in the hippocampal formation (including the entorhinal cortex) and in frontal cortical regions. Furthermore, just as in the human disease, the adrenergic neurons of the locus ceruleus and the serotonergic neurons of the dorsal raphe are also affected by the abnormalities in cell-cycle regulation. Equally important, the neurons of the substantia nigra show no evidence of CCEs. These neurons are spared in Alzheimer’s disease but represent a focal point of the neurodegeneration in Parkinson’s disease, and their normalcy in the R1.40 animals provides yet another indication of the anatomical specificity of the disease model. Standing in contrast to these human/mouse analogies are the cholinergic neurons of the basal forebrain. In humans, the basal nucleus of Meynert suffers substantial cell losses by the end stage of the disease (Whitehouse et al., 1982), and signs of distress are present in early stages (Chu et al., 2001; Mufson et al., 2002; Mesulam et al., 2004) including the presence of cell-cycle markers (Yang et al., 2003). In the mouse, however, we find no evidence of CCEs in the ChATpositive neurons of R1.40 transgenic mice at any age. One might want to dismiss the discordance as an example of the difficulties of modeling a complex human disorder in a mouse. A mouse, even with a perfect genetic reproduction of a human disease is, after all, still only a model. But the discordance might also suggest a somewhat different interpretation of the human situation. The basal 66 forebrain neurons have a chronic trophic dependency on the hippocampal pyramidal neurons, and it is possible that their dysfunction and death in Alzheimer’s disease represents not a primary disease event, but rather a secondary consequence of the hippocampal damage. The mouse hippocampus, spared the atrophy that is found in the human, can continue to support a full complement of basal forebrain cholinergic neurons. Because the above-cited human basal nucleus studies document biochemical changes in the neurons rather than cell death, this may yet prove to be the situation in early Alzheimer’s disease as well. A final consideration raised by our findings is the perspective it offers on the amyloid hypothesis of AD. Summarized broadly, the hypothesis is that abnormal processing of the APP protein leads to the accumulation of the highly insoluble Aβ peptide. The Aβ peptides form aggregates, in either micromolecular or macromolecular size, leading to the death of neurons and thus the clinical symptoms of Alzheimer’s disease. The findings of the current study both strengthen and weaken this linear view of the dementia. The finding that the CCEs precede Aβ plaque deposition by 6 months means that the plaques per se cannot be the immediate cause of the neuronal death. Small, micromolecular aggregates are still a plausible factor, however, and our findings are consistent with a growing consensus that these may be the truly toxic agents. Our findings strengthen this hypothesis in a different way as well. The strong anatomical reproduction of the sites of cell death in the human represented by the location of the CCEs in the mouse means that the overexpression of a single human 67 disease gene has closely reproduced a complex anatomical pattern of neuronal distress. This can hardly be a random finding and deepens the suggestion that imperfections in APP processing (though not necessarily Aβ) can produce the neurological problems of AD. 68 69 Figure 2.1: Appearance of cell-cycle proteins in the neurons of 22-monthold transgenic R1.40 mice. A-F, PCNA (green) was re-expressed in the nuclei of cortical (A-C) and hippocampal (D-F) neurons. G-I, No PCNA expression was found in the age-matched nontransgenic control cortex (G-I) or hippocampus (data not shown). J-O, Expression of cyclin A was also detected in the cytoplasm of cortical (J-L) and hippocampal CA1 pyramidal (M-O) neurons of the R1.40 mouse. P-R, There was no cyclin A found in comparable neuronal populations in the controls. Nuclei were counterstained with DAPI (blue; B, E, H, K, N, Q). The arrows indicate examples of cell-cycle-positive cells. Scale bar, 10 µm. 70 71 Figure 2.2: DNA replication in neurons of transgenic R1.40 mice. A, FISH with unique genomic sequences reveals four bright hybridization signals for mouse chromosome 11 (170L21) in the cortex. The arrows indicate the hybridization signals (green); nuclei are counterstained with propidium iodide (red). B, Hippocampal neurons show a similar pattern. The cell labeled 2 is shown with arrows to indicate the hybridization signals (green). In this image, the nuclei have been counterstained with DAPI (blue). C, D, A second BAC probe for sequences on mouse chromosome 16 (4806C) shows four hybridized signals (green) merged with propidium iodide (red) counter stain in the neuronal nuclei of the cortex (C; arrows) and hippocampus (D) of R1.40 mice. E, F, DAPI counterstain. Only two hybridized signals were found in the nuclei of agematched nontransgenic controls (arrows). G, H, Double immunostaining showed coexpression of cyclin A (red) with a neuronal marker, NeuN (green), in both the frontal cortex (G) and hippocampal pyramidal neurons (H). GFAP (red) as a marker for astrocytes shows that astrocyte activation (arrowheads) occurred in the neuropil surrounding the cell-cycle-positive neuronal cells (PCNAs; green) of R1.40 mice in both the cortex (I) and hippocampus (J). Only scattered GFAPpositive cells were also cell cycle positive (data not shown). Scale bar, 10 µm. 72 Figure 2.3: Confocal images of increased ploidy in some of the neurons of the adult R1.40 transgenic mouse brain. These images were taken with a Zeiss (Thornwood, NY) 510 confocal microscope of neurons in the frontal cortex of a 22-month-old R1.40 mouse. The cell nucleus is revealed with a propidium iodide (red) counterstain. A, B, The hyperploid DNA content of both neurons is illustrated by the three (A, arrows) and four (B, arrows) spots of hybridization of a BAC genomic probe complementary to sequences on mouse chromosome 16. Note that despite the elongated shape of the nucleus shown in A, the three hybridization signals are clearly contained within a single nuclear profile. 73 74 Figure 2.4: CCEs are observed in multiple AD transgenic mouse models. A, B, Cyclin A (red, arrows) is expressed in the cytoplasm of frontal cortical (A) and hippocampal (B) neurons of the Tg2576 AD transgenic mouse. The neuronal antigen NeuN (green) was used as a marker for neurons. C, D, No expression of PCNA (green) is found in the either cortical or hippocampal neurons of littermate animals from the same genetic background. The red fluorescence is a propidium iodide counterstain. Neuronal nuclei in the APP23 mouse, another AD transgenic mouse model, also exhibited CCEs. E-H, Immunostaining revealed PCNApositive neurons (arrows) in the frontal cortex (E) and hippocampus (F) in APP23 mice but not in the nontransgenic controls (G, H). Scale bars, 10 µm. 75 76 Figure 2.5: Expression of cell-cycle proteins in subcortical structures in 22month-old R1.40 mice. A-F, Cyclin A (green) was expressed in TH-positive (red) neurons of the locus ceruleus (A-C, arrows), whereas an aged-matched wild-type control showed only nonspecific cyclin A immunoreactivity (D-F). G-L, Cyclin A (red) was also expressed in the tryptophan hydroxylase-positive (green) neurons of the dorsal raphe (G-I, arrows), whereas an aged-matched wild-type control showed only background cyclin A immunoreactivity (J-L). M-O, No cellcycle expression was observed in the ChAT-positive (red) neurons of the basal nucleus (M), the TH-positive (red) neurons of the substantia nigra (N), or in the neurons of the cerebellar cortex (O). Cell nuclei counterstained with DAPI (blue) are shown throughout. Scale bars, 10 µm. GL, Granule cell layer; ML, molecular layer. 77 Figure 2.6: Expression of cell cycle proteins at various ages of R1.40 mice. A-D, At 3 months of age, no expression of cyclin A (data not shown) or PCNA (green) was found in any region of the R1.40 brain (A, frontal cortex; C, hippocampus) or in nontransgenic controls (B, frontal cortex; D, hippocampus). E-L, At 6 and 10 months of age, PCNA (green) appeared in the cortical (E, I; arrows) and hippocampal (G, K; arrows) neurons of R1.40 mice, but no immunoreactivity was found in controls (F, H, J, L). Nuclei were counterstained with propidium iodide (red; A-D, F-L) or DAPI (blue; E). Scale bar, 10 µm. 78 Figure 2.7: DNA replication in neurons at various ages in the R1.40 mouse model. A-C, At 3 months of age, only two hybridized signals (arrows) were found in the nuclei of cortical and hippocampal neurons of both R1.40 (A, B) and control mice (C). D, E, G, H, However, there were four bright hybridization signals (arrows) for mouse chromosome 11 (170L21) or 16 (480C6) at 6 months of age (D, cortex; E, hippocampus) and 10 months of age (G, cortex; H, hippocampus). F, I, Nontransgenic controls exhibited only two hybridization signals. Scale bar, 10 µm. 79 80 Figure 2.8: An inflammatory response is observed in the cortex of 22month-old R1.40 mice. A plaques (arrows) are surrounded by activated microglial cells. A, An antibody for CD45 reveals the presence of activated microglia in the frontal cortex. B, A higher-magnification image shows microglia with robust processes. C, The locus ceruleus remains devoid of CD45-positive microglia at this age. Scale bars: A, 100 µm; B, C, 10 µm. 81 Chapter 3: Aβ Oligomers Induce Neuronal Cell Cycle Events in Alzheimer’s Disease Nicholas H. Varvel1,2*, Kiran Bhaskar1*, Anita R. Patil1, Sanjay W. Pimplikar1, Karl Herrup3 and Bruce T. Lamb1,2,4 1 Lerner Research Institute, The Cleveland Clinic, Department of Neurosciences NC3-164, 9500 Euclid Avenue, NC30, Cleveland, OH 44195 2 Case Western Reserve University School of Medicine, Department of Neurosciences, 10900 Euclid Avenue, Cleveland, OH 44106 3 Rutgers, The State University of New Jersey, Department of Cell Biology and Neuroscience Nelson Biological Laboratories, Busch Campus, 604 Allison Road, Piscataway, NJ 08854 4 Case Western Reserve University School of Medicine, Department of Genetics, 10900 Euclid Avenue, Cleveland, OH 44106 *N.H.V. and K.B. contributed equally to the work This manuscript was previously published: Journal of Neuroscience 2008 28(43): 10786-10793. 82 Contributions of Authors Nicholas H. Varvel, Karl Herrup and Bruce T. Lamb wrote the manuscript. Anita R. Patil and Sanjay W. Pimplikar performed Western blot analysis of brain homogenates for amyloid precursor protein intracellular domain (AICD) and APP C-terminal fragments. Kiran Bhaskar performed in vitro Aβ oligomers experiments. Nicholas H. Varvel performed all other experiments and data interpretation with Karl Herrup and Bruce T. Lamb. Acknowledgements The authors thank R. Yan (Cleveland Clinic, Cleveland, OH) for Bace1-/- mice, G. Xu and N. Maphis for technical support and W.L. Kline and M.P Lambert (Northwestern University, Evanston , IL) for providing NU1 and NU2 antibodies. This work was supported in by the National Institutes of Health Grants (AG026146 to S.W.P., AG023012 to B.T.L. and AG024494 to K.H. and B.T.L.), the Alzheimer’s Association (B.T.L.) and an Anonymous Foundation. 83 Introduction Accumulating evidence suggests that neuronal cell cycle re-entry is the first step in a process that leads to the observed regional neuronal degeneration observed in Alzheimer’s disease (AD). Expression of cell cycle proteins and DNA synthesis is observed in neurons susceptible to death in AD (Arendt et al., 1996; Vincent et al., 1996; Yang et al., 2001). Importantly, cell cycle proteins and hyperploid neurons are seen at much lower levels in age-matched controls and in neuronal populations within the AD brain where degeneration is not prevalent. Furthermore, immunohistochemical analysis of brain tissue from individuals with mild cognitive impairment (MCI), believed by many to be of the clinical predecessor of AD (Petersen, 2000), reveals the presence of cell cycle events (CCEs) in brain regions that undergo substantial degeneration in AD (Yang et al., 2003). To better understand the pathogenesis of AD, we and others have used mouse models that express transgenes with mutations that cause familial earlyonset AD in humans (Lamb, 1995; Sturchler-Pierrat et al., 1997; Oddo et al., 2003). Aβ deposition is found in transgenic mouse models of AD, but little neuronal cell loss is encountered. Every model that has been examined, however, shows signs of ectopic neuronal CCEs (Yang et al., 2006). In particular, the genomic-based mouse model, R1.40, expressing the Swedish mutant form of human APP, on the C57BL/6 inbred genetic background (B6R1.40), recapitulates neuronal cell cycle re-entry in most of the same neuronal populations that exhibit DNA replication and degeneration in the AD brain. 84 Because the first ectopic cell cycle alterations are observed 6 to 8 months prior to the onset of Aβ deposition these data indicate that deposition is not itself the insult necessary for neuronal cell cycle re-entry. Recent experimental evidence has indicated that soluble aggregates of Aβ, termed Aβ oligomers, may play a causative role in AD pathogenesis. Oligomeric assemblies of Aβ have been isolated from post-mortem AD brains (Gong et al., 2003) as well as young, pre-depositing transgenic mouse models of AD (Lesne et al., 2006; Oddo et al., 2006; Cheng et al., 2007). These soluble Aβ aggregates have been implicated in the rapid interference of memory of learned behaviors (Cleary et al., 2005). Aβ oligomers can also inhibit long-term potentiation (Walsh et al., 2002) in nanomolar concentrations and they exhibit potent toxic effects, capable of inducing neuronal cell death in hippocampal slices (Lambert et al., 1998). Because, aberrant neuronal cell cycle re-entry is closely associated with sites of neuronal degeneration in human brain and mouse models of AD, we wanted to explore the involvement of Aβ in the formation of neuronal CCEs. We now provide direct genetic evidence that the onset of neuronal cell cycle alterations is dependent upon the amyloidogenic processing of APP. In addition, we provide evidence that in vitro preparations of Aβ oligomers can induce CCEs in primary cortical neurons. Our results suggest that neuronal cell cycle alterations represent a valuable biomarker for determine the effectiveness therapeutic strategies to reduce or eliminate Aβ production. 85 Materials and Methods Mice The R1.40 transgene is a full genomic copy of human APP (a 400 kb insert from a yeast artificial chromosome clone) carrying the Swedish (K670M/N671L) mutation associated with early-onset familial AD. Creation of the R1.40 transgenic mouse strain and subsequent backcrossing to inbred strains has been described previously (Lamb et al., 1993; Lamb et al., 1997; Lehman et al., 2003a). Age- and gender-matched non-transgenic C57BL/6J and DBA2/J animals served as controls in all analyses. Homozygous R1.40 animals, maintained on the C57BL/6J genetic background were also crossed to Bace1-/animals (Cai et al., 2001), also maintained on the C57BL/6J genetic background, to generate F1 R1.40/-;Bace1+/- animals. F1 animals were intercrossed to generate animals homozygous for the R1.40 transgene and homozygous for the Bace1 knockout allele as well as Bace1-/- animals, lacking the R1.40 transgene. Animals were housed at the Cleveland Clinic Biological Resources Unit, a facility fully accredited by the Association of Assessment and Accreditation of Laboratory Animal Care. All procedures were approved by the Institutional Animal Care and Use Committee of the Cleveland Clinic. Immunohistochemistry of tissue The rabbit polyclonal cyclin A antibody (ab 7956; Abcam, Cambridge, UK), specific for the C-terminal domain of cyclin A2 was diluted 1:200 in 10% goat serum/PBS containing 0.1% Triton X-100 blocking buffer before use. The mouse monoclonal cyclin D antibody (ab 31450; Abcam, Cambridge, UK) was raised 86 used as a marker of cell cycle antigens and diluted 1:200. The mouse monoclonal NeuN antibody (dilution, 1:500; Chemicon, Temecula, CA) was used as a neuronal-specific marker. To perform double fluorescent immunohistochemistry, sections were first rinsed in PBS containing 0.1% Triton X-100 (PBST). Sections were incubated for 1 h at room temperature in 10% goat serum in PBS to block non-specific binding. All primary antibodies were diluted in PBST and applied overnight at 4°C. After rinsing in PBS, the slides were incubated for 2 h with a secondary antibody, which was conjugated with various fluorescent Alexa dyes (dilution, 1:1000; Molecular Probes, Eugene, OR). The sections were then rinsed in PBS and reincubated in 10% goat serum blocking solution for 1 h, followed by the addition of the second primary antibody (raised in a different species from the first primary antibody) for a second overnight incubation at 4°C. Sections were then rinsed in PBS and the second secondary antibody, conjugated with a difference fluorescent dye, was applied to sections for 2 h at room temperature. After rinsing, all sections mounted in DAPI Hardest Reagent (Vector Laboratories, Burlingame, CA) under a glass coverslip. Histology Animals were prepared for histochemical analysis as described (Yang et al., 2006). Antibody concentrations used for immunohistochemistry were: rabbit anti-cyclin A2 (Abcam) 1:200, mouse anti-cyclin D (Abcam) 1:200 and mouse anti-NeuN (Chemicon) 1:500. Secondary antibodies (Molecular Probes) were used 1:1000. Tissues were mounted with DAPI Hardest Reagent (Vector 87 Laboratories, Burlingame, CA) under a glass coverslip. Fluorescent in situ hybridization was performed as described (Yang et al., 2006), using a mousespecific DNA probe (480C6, from the RPCI-22 BAC library) contains 150 kb of genomic sequence from the region that encodes the endogenous Sim2 gene located on mouse chromosome 16 (Kulnane et al., 2002). Neuronal cell counts For each of the genotypes we examined 5 animals at each age. For each animal, a total of 5 evenly spaced sections containing the frontal cortex were double stained for the neuronal marker, NeuN and cyclin A or cyclin D. The area located between 2.5 mm and 3.4 mm anterior to the Bregma was identified in each section analyzed. We scored NeuN-positive cells within cortical layers II/III or V/VI for the presence or absence of the cell cycle marker. Only cells with a discernable portion of their nucleus in the section were scored. For each of the five sections the percentage of NeuN+ cells exhibiting immunoreactivity for the cell cycle marker was tabulated, and the percentages for the 5 sections analyzed in each animal were averaged. For each age and genotype the percentages were then averaged over all 5 animals and expressed as mean+SEM. Adjacent sections that had undergone processing for fluorescent in situ hybridization (FISH) were tabulated in similar fashion where neurons were scored for the presence or absence of 3 or 4 spots of hybridization. All counts were performed in a blinded fashion and data were analyzed with the Student’s t test (GraphPad Prism, GraphPad Software, Inc. San Diego, CA). 88 Western blot of tissue homogenates Analysis of the steady-state levels of holo-APP and APP CTFs was performed on brain extracts from 28-day-old B6-R1.40 animals and B6R1.40;Bace1-/- animals as described previously (Ryan and Pimplikar, 2005). Mice were killed by cervical dislocation and their brains were removed, divided sagittally (after removing cerebellum), and snap frozen. Tissues were homogenized in 10 volumes of Tris-buffered saline (50 mM Tris; pH 7.4, 150 mM NaCl, 1 mM EDTA) with freshly added 1 mM PMSF and protease and phosphatase inhibitor cocktail (Sigma-Aldrich). Total brain homogenates were subsequently centrifuged to remove nuclei and cell debris at 1000 g for 15 minutes. These post-nuclear supernatants were carefully removed and saved in aliquots. Protein estimation was performed using Pierce BCA protein estimation kit. Equal amounts of protein (50 µg per lane) were added to the gel. Immunoblotting was performed using Novex NuPage, 4-12% Bis-Tris gel (Invitrogen). The blots were incubated with antibody 0443 (Calbiochem, #171610) against the C-terminus of APP. In vitro preparation of Aβ1-42 monomers and Aβ1-42 oligomers The preparation of synthetic Aβ1-42 monomers and Aβ1-42 oligomers followed established protocols (Stine et al., 2003). Briefly, HFIP-treated lyophilized Aβ1-42 peptide was carefully and completely resuspended to 5 mM in anhydrous dimethyl sulfoxide (D2650; catalog number D-2650; Sigma) by pipette mixing followed by brief sonication. The recombinant Aβ1-42 peptide was diluted to 100 µM in ice-cold cell culture medium (phenol red-free Ham’s F12; Caisson 89 Laboratories, North Logan, UT) immediately prior to the treatment for monomer preparations or incubated at 37ºC for 24 h to obtain Aβ1-42 oligomer preparations. Western blot analysis were performed according to the standard protocols as described previously (Stine et al., 2003) using monoclonal antibodies against Aβ oligomers (NU1 and NU2) (Lambert et al., 2007) or human Aβ (6E10; Covance Research Products, Denver, PA) . Primary cortical cultures and Aβ1-42 treatments Embryonic cortical neurons from E16.5 C57BL/6 mouse embryos were isolated by standard procedures as reported previously (Cicero and Herrup, 2005). All cultures were grown for a minimum of 7 days in vitro before any treatment. To assess the effect of monomeric and oligomeric Aβ1-42 on induction of neuronal cell cycle re-entry, the Aβ monomers, Aβ oligomers or Ham’s F12 vehicle were serially diluted in new NB-media containing 10 mM BrdU and cells treated for 24 h. To immunoneutralize the oligomers from the synthetic preparations of Aβ, oligomer-specific antibody NU2 antibody was added to the neuronal cultures at a final concentration of 100 nM, 30 min prior to exposure to 100 nM of the oligomeric Aβ preparations (De Felice et al., 2008). As a control, 100 nM of non-specific mouse IgG (Sigma) was exposed to the cultures in an identical manner. The treatments were performed on a minimum of three litters. Immunocytochemistry of cells For BrdU visualization on neuronal cultures, cells were treated with 2N HCl for 30min at 37°C, neutralized in 0.1M sodium borate (pH 8.6) for 10 min and washed 5 times in PBS. Cells were blocked with 5% normal goat serum in PBS 90 with 0.4% Triton X-100 for 1 h at room temperature, incubated overnight at 4ºC with primary antibodies (in blocking buffer), including a mouse monoclonal antibody against microtubule associated protein 2 (1:1000; Map2; Sigma, St. Louis, MO) and a rat monoclonal antibody against BrdU (1:1000; Abcam, Cambridge, MA). Following PBS washes, cells were incubated with secondary antibodies (1:1000; Invitrogen, Eugene, OR) for 1 h at room temperature. Cells were washed with PBS and coversliped with hard-set mounting media containing DAPI (Vector Laboratories, Burlingame, CA). Quantification of cells positive for Map2 and BrdU The number of cells positive for BrdU only, Map2 only or positive for both were quantified by scoring five random fields per treatment per each concentration in a blinded fashion. By assigning total number of Map2 positive cells per treatment as 100%, the percentage of total number of Map2 positive and BrdU positive cells were calculated and normalized and expressed as mean+SEM (n=3). Data was analyzed using the unpaired t-test (GraphPad Prism, GraphPad Software, Inc. San Diego, CA). Results We examined the levels of cell cycle proteins in brain sections of adult B6-R1.40 transgenic mice at a variety of ages by immunohistochemistry. Fluorescent in situ hybridization (FISH) was used to detect DNA replication. Consistent with our previous studies, six-month old B6-R1.40 transgenic mice exhibited CCEs in a large population of neurons in layers II/III of frontal cortex. These cells were 91 identified by co-immunostaining with the neuronal marker NeuN and cyclin A (Figure 3.1, D-F) as well as additional cell cycle proteins including cyclin D and proliferating cell nuclear antigen (PCNA) (data not shown). This ectopic cell cycle protein expression is accompanied by evidence of DNA replication as indicated by three or four FISH signals within a subset of these neuronal nuclei (Figure 3.1F-inset). Significantly, no evidence of cyclin A re-expression or DNA replication was observed either in the brains of four-month old B6-R1.40 transgenic mice (Figure 3.1, A-C, Figure 3.1C-inset) or in the brains of sixmonth old non-transgenic control mice (Figure 3.1, G-I, Figure 3.1I-inset). Taken together, these data indicate that the onset of the neuronal CCEs in cortical layers II/III in the B6-R1.40 transgenic mice is rapid and nearly synchronous, as all of the animals aged to four months of age displayed no evidence of CCEs, while all of the six-month old animals displayed a robust activation of the cell cycle. The layer II/III neurons of the frontal cortex are the first population of cells that exhibit CCEs in the B6-R1.40 transgenic mouse model of AD. Though synchronous in any one neuronal cell population there was nonetheless a pattern to the appearance of CCEs across different brain regions. We analyzed brain sections from B6-R1.40 animals at both 10 and 12 months of age with both immunohistochemistry and FISH. B6-R1.40 transgenic mice aged to 12 months of age had nearly identical densities of neuronal CCEs in cortical layers II/III as was observed in six-month old specimens (data not shown). In addition, in 12-month old brains, neuronal CCEs had progressed to include 92 cortical layers V/VI as evidenced by co-immunostaining for NeuN and cyclin D (Figure 3.2, D-F) and cyclin A (not shown). As elsewhere, this was accompanied by evidence for DNA replication as assessed by FISH (Figure 3.2F-inset). Neither 10-month old B6-R1.40 animals (Figure 3.2, A-C, Figure 3.2C-inset) nor 12-month old non-transgenic controls (Figure 3.2, G-I, Figure 3.2I-inset) exhibited either immunocytochemical or cytogenetic (FISH) evidence for CCEs in the same layer V/VI cells. This emphasizes the finding that within any one cell type the appearance of CCEs is rapid and nearly synchronous. We performed a quantitative analysis of cyclin A immunoreactivity and FISH signals to determine whether the percentages of neurons exhibiting CCEs in different brain regions remained constant or increased as the transgenic animals aged (and presumably the disease progressed). We quantified CCEs in frontal cortical layers II/III and V/VI separately, as these nerve cell populations exhibit distinct, temporal patterns of CCEs. As shown in Figure 1, many neurons in layers II/III of the frontal cortex show evidence of cell cycle re-entry at six months of age. Quantitative analysis revealed that ~44% of the neurons (NeuN positive cells) within these layers are positive for cyclin A (Figure 3.3A). This result was consistent across all test markers. Thus, ~45% of NeuN positive cells within cortical layers II/III were also positive for cyclin D (Figure 3.3B). By contrast <1% of the neurons exhibited evidence of cyclin A and D expression in cortical layers V/VI at six months of age. Age-matched non-transgenic controls had 0.5% and 1.7% of cyclin A and D-immunoreactive neurons, respectively, in cortical layers II/III (Figure 3.3A and 3.3B). 93 To quantify the number of cells undergoing DNA replication within the same brains we performed FISH and tabulated the percentages of neurons exhibiting three or four spots of hybridization. For these experiments we utilized a 150 kb BAC carrying genomic sequences from mouse chromosome 16 and determined the spots of hybridization within neuronal nuclei. Our analysis revealed that by 6 months of age ~9% of the neurons in cortical layers II/III had three or more spots of hybridization in the B6-R1.40 mice. Similar to the results from the cyclin A and D immunohistochemistry counts, <1% of neurons exhibit three of four spots of hybridization in non-transgenic controls at the same age (Figure 3.3C). We were surprised to find that the disease progresses with time between regions but not within them. The percentages of cyclin A and cyclin D immunoreactive neurons in layers II/III at 12 months of age remained unchanged when compared to six months of age in the R1.40 transgenic mice. Quantitative analysis of DNA replication with FISH revealed that, similar to the data obtained via immunohistochemistry, the number of neurons exhibiting three or four spots of hybridization did not change between six and 12 months of age in cortical layers II/III. (Figure 3.3A and 3.3B). At 12 months of age, nearly 45% of neurons in layers V/VI now exhibited cyclin A or cyclin D immunostaining as compared to <1% at six months of age (Figure 3.3A and 3.3B). Non-transgenic controls, exhibited <8% cyclin A and D immunoreactive neurons at the same age. (Figure 3.3A and 3.3B). Further, while six month old animals exhibited <1% of cells with increased FISH signal in cortical layers V/VI, this number increased to 94 11% by the age of 12 months. Non-transgenic controls at this age exhibited <1% of cells with increased FISH signal (Figure 3.3C). Together, these data suggest that within the specific neuronal populations impacted, CCEs occur rapidly and within a large percentage of cells that is stable over a prolonged period of time. Our studies indicate that neuronal CCEs are first evident at six months of age in cortical layers II/III and subsequently spread into cortical layers V/VI by 12 months. Thus, cortical CCEs appear approximately six to eight months prior to the onset of fibrillar Aβ deposition in the B6-R1.40 model. This suggests that fibrillar Aβ deposits are not responsible for the induction of neuronal CCEs and instead implicates either unique soluble Aβ species or particular APP processing products generated in the R1.40 transgenic mouse. To further examine the APP products(s) responsible for the induction of CCEs, we examined R1.40 mice in which the transgene had been transferred by repeated backcrossing to the DBA/2J mouse strain. D2-R1.40 APP transgenic mice exhibit similar expression levels of both holo-APP and APP CTFs to that observed in B6-R1.40 mice. However, the steady state levels of transgenederived Aβ are substantially reduced in the D2-R1.40 mice when compared to the B6-R1.40 mice (9.7 versus 12.3 pmole/g for Aβ1-40 and 4.0 versus 4.9 pmole/g for Aβ1-42). The result is a lack of Aβ deposition in the D2-R1.40 mouse model, even as late as 24 months of age, while B6-R1.40 mice exhibit Aβ deposition around 12 to 14 months of age. Unlike the B6-R1.40 strain, we found no evidence for neuronal CCEs in any brain region at either six (data not shown) or 10 months of age (Figure 3.4, 95 A-C) in the D2-R1.40 mouse strain. By 12 months of age, however, D2-R1.40 transgenic mice develop neuronal CCEs in cortical layers II/III, but not cortical layers V/VI as evidenced by immunohistochemistry for cyclin A (Figure 3.4, D-F) and cyclin D as well as FISH (data not shown). As in the C57BL/6 strain, nontransgenic controls at the same ages did not exhibit any evidence of neuronal CCEs (Figure 3.4, G-I). Thus, even APP transgenic mouse models that do not develop fibrillar Aβ deposits across their entire lifespan still develop neuronal CCEs in an anatomically appropriate fashion. These studies demonstrate that genetic reduction in steady state levels of Aβ delays the appearance of neuronal CCEs in all brain regions in the D2-R1.40 mouse model. The delay in neuronal CCEs in the D2-R1.40 mice, implicates Aβ as the causative factor in the induction of CCEs. To specifically test whether Aβ generation was necessary for the onset of CCEs, we generated B6-R1.40 animals that were also homozygous for a null allele in the β-secretase 1 (Bace1) gene. B6-R1.40 transgenic mice maintained on a Bace1-/- background fail to exhibit evidence of CTFβ or Aβ production, with corresponding increases in CTFα and full-length APP (Figure 3.5A) and no significant changes in the levels of the APP intracellular domain (AICD). While, B6-R1.40 mice exhibit neuronal CCEs in cortical layers II/II at 6 months of age (Figure 3.5B, 3.5D, and 3.5F), age-matched Bace1-/- (not shown) and B6-R1.40;Bace1-/- animals exhibit no evidence of neuronal CCEs in any brain region, including neurons residing in the frontal cortical layers II/III (Figure 3.5C, 3.5E, and 3.5G). Taken together with the delay in neuronal CCEs observed in 96 the D2-R1.40 mice, these results suggest that the production of the Aβ peptide itself, or a soluble Aβ aggregate is responsible for the induction of neuronal CCEs. To further test this hypothesis, we examined whether synthetic preparations of monomeric or oligomeric Aβ were sufficient to drive primary cortical neurons in culture into an aberrant cell cycle. Human Aβ1-42 peptides were treated by established protocols to generate both monomeric and oligomeric Aβ. Western blot analysis with antibody 6E10 revealed the predominance of Aβ monomers and low molecular weight oligomers (trimers and tetramers) in the monomeric preparations, while the oligomeric preparations also contained Aβ monomers and low molecular weight oligomers in addition to higher molecular weight oligomers ranging in size from 25 to 98 kDa (Figure 3.6). The higher molecular weight oligomers were also recognized by oligomer-specific antibodies NU1 and NU2 (data not shown). To determine whether soluble Aβ species are capable of inducing neuronal CCEs, we treated primary cortical neurons with varying concentrations of either monomeric or oligomeric preparations of Aβ as well as vehicle in the presence of bromodeoxyuridine (BrdU) for 24 hours. The cultures were then fixed and co-immunostained with antibodies to Map2 and BrdU. Exposure of neurons to increasing concentrations of oligomeric Aβ led Map2-immunoreactive neurons (green) to enter a cell cycle and incorporate BrdU (red) (Figure 3.7, GI). In contrast, Map2-positive neurons do not incorporate BrdU when exposed to monomeric Aβ (Figure 3.7, D-F) or vehicle (Figure 3.7, A-C). We observed a 97 basal level (5.7+1%) of Map2 positive cells displaying BrdU incorporation in vehicle treated groups (Figure 3.7J and 3.7K). Upon treatment with different concentrations of Aβ monomers, there was no statistically significant alteration in the percentage of BrdU positive cells (Figure 3.7J). However, upon exposure of neurons to the Aβ oligomeric preparations, we observed a two to five fold increase in the number of BrdU positive neurons compared to the vehicle control (Figure 3.7K). Importantly the effect of Aβ oligomers was observed at concentrations as low as 50 nM, which resulted in a two fold increase (5% versus 10%) in the Map2 positive neurons that displayed BrdU incorporation. Finally, to demonstrate that the effect of the synthetic Aβ oligomer preparations was due to the presence of specific oligomeric Aβ assemblies, we performed the same neuronal cell culture experiments in the presence of the NU2 monoclonal antibody, which was previously demonstrated to bind to Aβ oligomers and inhibit other downstream consequences of Aβ oligomer exposure to neurons (Lambert et al., 2007). Preincubation of the NU2 antibody with the 100 nM preparations of Aβ oligomers, resulted in 5 fold reduction in the percentage of Map2 positive cells incorporating BrdU, while preincubation with a non-specific mouse immunoglobulin had no discernible effect (Figure 3.7L). In summary, our in vitro data demonstrate that Aβ oligomers are sufficient to induce cell cycle re-entry in neurons. 98 Discussion The findings presented here offer substantial insights into the onset and progression of cell cycle events in post-mitotic neurons in the R1.40 mouse model of AD and by extension into the disease pathogenesis underlying AD. In human AD, neuronal CCEs are observed in neurons subject to neurodegeneration in patients early in the disease process as indicated by their presence in patients with mild cognitive impairment, coupled with their virtual absence in non-demented individuals and in brain regions where there is no neuronal cell loss (Busser et al., 1998; Yang et al., 2001; Yang et al., 2003). These and other data argue that neuronal CCEs represent an early marker of neuronal distress and disease pathogenesis. This is consistent with other evidence suggesting the re-entrance of neurons into the cell cycle is associated with neurodegeneration (al-Ubaidi et al., 1992; Klein et al., 2002; Kuan et al., 2004). We have taken advantage of our ability to do longitudinal studies in a genetically reproducible system by quantifying the CCEs in the R1.40 brain at multiple ages as well as genetic and biochemical perturbations designed to identify the mechanism behind the initiation of the CCEs. Our data document that CCEs do not develop within all disease-relevant neuronal populations at once. Rather, specific neuronal populations initiate CCEs during a relatively short period of time (i.e., two months or less), but in a precise sequence. Once initiated these events are subsequently stable for at least six months within the same neuronal populations. For example CCEs appear within a relatively large percentage of the neurons in frontal cortex layers 99 II/III at six months of age, and we previously reported that neuronal CCEs are observed within two subcortical populations, the locus ceruleus and dorsal raphe, by eight months of age (Yang et al., 2006). This is followed by the induction of CCEs in neurons of frontal cortical layers V/VI at 12 months of age. Between six and 12 months of age, however, CCEs remains constant in layers II/III. This bears striking but unexpected analogy to the findings in the Atm-/- (Yang and Herrup, 2005) and E2F1-/- (Wang et al., 2007) mouse brain. In both mutants, CCEs also appear synchronously. Closely spaced time points suggest the transition from normal to CCE-positive takes about a week. Our qualitative impression is that in the R1.40 the event is more spread out, but we could imagine that the process is equally rapid in this AD model. The nature of the signal that triggers this transition thus becomes a question of utmost importance. Neuronal CCEs are first observed approximately six to eight months prior to fibrillar Aβ deposition in the R1.40 transgenic mouse model of AD. In addition, neuronal CCEs are also observed in the locus ceruleus and dorsal raphe at eight months of age in the R1.40 mice, two brain regions in which no Aβ deposition is observed even at late ages. Interestingly, the locus ceruleus and dorsal raphe exhibit evidence of CCEs and are subject to substantial degeneration within the AD brain, even though there is limited AD-like pathology in these subcortical brain regions (Braak and Braak, 1997). Together, these results suggest that; 1) the CCEs present in the R1.40 mouse model of AD provide an accurate read out of the neuronal vulnerability observed in human AD that is likely reflective of the precise temporal regulation of the mutant human APP transgene, and 2) that 100 fibrillar Aβ is unlikely to be the triggering event responsible for neuronal CCEs. In addition, given that neuronal CCEs are not observed in age-matched, nontransgenic mice, this suggests that accumulation of either APP or its breakdown products (eg. Aβ) is likely responsible for the induction of CCEs. The current studies provide evidence that oligomeric Aβ species are both necessary and sufficient for the induction of neuronal CCEs. Genetic experiments using D2-R1.40 transgenic mice demonstrated that a reduction in steady state levels of Aβ, without significant alterations in holo-APP or APP CTFs, results in a six-month delay in neuronal CCEs. When compared to B6-R1.40 animals, D2-R1.40 animals exhibit lower levels of Aβ1-40 and Aβ1-42 and do not develop Aβ deposits throughout the lifetime of the animal. The biochemical differences are apparent as early as 28 days of age suggesting that altered APP processing and Aβ metabolism in young animals may have implications for later development of AD-like neuropathologies. Interestingly, CCEs first appear at 12 months of age in the D2-R1.40 mice in cortical layers II/III, suggesting that while delayed, the anatomical pattern and temporal progression of the CCEs is maintained. To more directly implicate Aβ production in the induction of neuronal CCEs, we examined B6-R1.40 mice lacking the primary β-secretase, Bace1. In B6-R1.40;Bace1-/- mice neuronal CCEs were completely blocked at 6 months of age, directly implicating the amyloidogenic processing of APP in the induction of CCEs. Taken together, this genetic data directly implicates the production of Aβ or its derivatives in initiating neuronal CCEs. 101 To determine the role of soluble Aβ species on the induction of neuronal CCEs we performed in vitro studies on primary cortical neurons. Significantly, primary cortical neurons exposed to in vitro preparations of Aβ oligomers, but not monomers, resulted in substantial incorporation of BrdU. The concentrations of Aβ oligomers sufficient to induce CCEs (50-1000 nM) was similar to other studies examining the neurotoxicity of oligomers that are capable of inhibiting long-term potentiation (LTP) in vivo (Walsh et al., 2002), and in hippocampal slices (Wang et al., 2002) decrease spine density (Lacor et al., 2007) and impair memory in animals models of AD independently of Aβ deposition and neuronal cell loss (Lesne et al., 2006). In addition, while previous studies from our group implicated Aβ fibrils in neuronal cell cycle alterations, this was observed at concentrations of 1 mM (Aβ25-35) after incubation for upwards of 72 hours (instead of 24 hours in the current study) (Wu et al., 2000). The studies leave unanswered the question of why discrete neuronal populations are impacted differently with age in the R1.40 mouse model and in AD. This could be due to 1) altered production of Aβ within specific brains regions, 2) altered generation of specific Aβ oligomers within these neuronal populations and/or 3) age-related alterations in neuronal selectivity to these insults. Previous data from our laboratory demonstrated that total levels of brain Aβ remain unchanged at the ages examined for neuronal CCEs in both the B6R1.40 and D2-R1.40 mouse models and that the highest steady state levels of Aβ are in the cerebellum, hippocampus and olfactory bulb (Lehman et al., 2003b). In addition, cell cycle events are not encountered within the Purkinje and 102 granule cells in the cerebellum as late as 22 months of age in B6-R1.40 animals (Yang et al., 2006). Together, these data suggest that the occurrence of neuronal CCEs is unlikely to be due to simply higher levels of Aβ peptides per se. Nevertheless, these studies clearly implicate the production of Aβ in the induction of neuronal CCEs and demonstrate that Aβ oligomers are capable of inducing CCEs, a finding that suggests CCEs represent an early and disease relevant marker of disease progression. Our future studies will be focused on identifying which species of Aβ oligomers are sufficient to induce neuronal CCEs in vitro and whether they exert their mitogenic effects through any of the pathways thus far identified underlying Aβ oligomer-based neurotoxicity, such as interactions with NMDA receptors (De Felice et al., 2007), insulin signaling (Zhao et al., 2008) as well as calcium dysregulation (Nimmrich et al., 2008). In addition, it will be critical to determine whether neuronal CCEs represent an upstream or downstream consequence of Aβ oligomer exposure. Finally, the identification and characterization of additional biochemical, morphological and physiological alterations will be required at the ages when neuronal CCEs first become evident in vivo. 103 104 Figure 3.1: Appearance of cell cycle proteins and DNA synthesis in frontal cortical layers II/III in B6-R1.40 mice at six months of age. A-C, No evidence of cyclin A (A, green) immunoreactivity was apparent in NeuN-positive cells (B, red) in transgenic mice aged to four months of age (C, merge). At this age neurons residing in frontal cortical layer II/III exhibit only two spots of hybridization (C-inset). Immunohistochemical profiles encountered at six months of age in B6-R1.40 animals reveal that cyclin A (D, green) is expressed in neurons (E, red). Overlaying the images reveals co-localization of both cyclin A and NeuN (F). FISH indicates that neuronal re-expression of cyclin A is accompanied by DNA synthesis as evidenced by three or four spots of hybridization (F-inset). G-I, There was no cyclin A (G, green) found in comparable neuronal populations (H, red) in age-matched non-transgenic controls. Nuclei were counterstained with DAPI (blue). The arrows indicate examples of cell cycle-positive neurons. Scale bar, 10 µm. 105 106 Figure 3.2: Expression of cell cycle proteins in frontal cortical layer V/VI in B6-R1.40 at 12 months of age. A-C, There was no evidence of cyclin D (A, green) observed in NeuN-positive cells (B, red) in 10-month old B6-R1.40 animals (C, merge). At this age neurons residing in frontal cortical layer II/III exhibit only two spots of hybridization (C-inset). D-F, Cyclin D (D, green) immunoreactivity was encountered in neurons (E, red) in R1.40 mice aged to 12 months of age. Overlaying the images reveals co-localization of both cyclin D and NeuN (F). FISH indicates that neuronal re-expression of cyclin D is accompanied by DNA synthesis as evidenced by four spots of hybridization (Finset). G-I, No evidence of cyclin D (G, green) was observed in NeuN+ cells (H, red) in age-matched non-transgenic controls. Cell nuclei counterstained with DAPI (blue) throughout. For each age and genotype a total of five animals were analyzed. Scale bar, 10 µm. 107 108 Figure 3.3: Quantification of neuronal cell cycle activity within cortical layers. Percentages of neurons exhibiting immunoreactivity for cell cycle reentry was tabulated in both male and female B6-R1.40 transgenic and nontransgenic mice aged to six and 12 months of age. Cell cycle re-entry was tabulated by scoring cyclin A (A) and cyclin D (B) immunoreactive neurons and polyploid neurons (C) in the frontal cortex. 109 110 Figure 3.4: Neuronal expression of cell cycle protein is delayed in D2-R1.40 animals. A-C, No evidence of cyclin A (green) immunoreactivity was apparent in NeuN-positive cells (red) in transgenic mice aged to 10 months of age. D-F, Cyclin A (green) was expressed in neurons (red) in 12-month old D2-R1.40 animals. Overlaying the images reveals co-localization of both cyclin D and NeuN (F). G-I, There was no cyclin A found in comparable neuronal populations in agematch non-transgenic control. Nuclei were counterstained with DAPI (blue). The arrows indicate examples of cell cycle-positive neurons. Scale bar, 10 µm. 111 112 Figure 3.5: B6-R1.40;Bace1-/- animals do not display neuronal cell cycle reentry at 6 months of age in frontal cortical layer II/III. A, Whole brain protein extracts were prepared from B6-R1.40 and B6-R1.40;Bace1-/- animals. Western blotting was performed using a C-terminal antibody. B, Cyclin A (green) is expressed in neurons (red) (D) in sic-month old B6-R1.40 animals. Overlaying the images reveals co-localization of both cyclin A and NeuN (F). E, Neurons (red) in six-month old B6-R1.40;Bace1-/- animals do not exhibit re-expression of cyclin A (green) (C). Nuclei were counterstained with DAPI (blue). The arrows indicate examples of cell cycle-positive neurons. Scale bar, 10 µm. 113 Figure 3.6: Western blot of monomer-(M) and oligomer (O)-rich Aβ1-42 in vitro preparations. Lane 1: Aβ1-42 incubated for 0 min shows mainly monomers and very low amounts of smaller oligomers. Lane 2: Aβ1-42 incubated for 24 h shows monomer, tri- and tetramers as well as large amount of higher oligomers with molecular weight between 49 and 100 kDa. Lane 1 and 2 were run on the same gel and probed with antibody 6E10. 114 115 Figure 3.7: Aβ oligomers induce neuronal BrdU incorporation in cortical neurons in vitro. A-I, cultured cortical neurons were treated with Ham’s F12 vehicle (A-C), 1000 nm of Aβ1-42 monomer-rich preparations (D-F), or 1000 nm Aβ1-42 oligomer-rich preparations (G-I) in the presence of BrdU for 24 h. Cells were fixed and co-immunostained with antibodies against Map2 (A, D, G) and BrdU (B, E, H), demonstrating the induction of BrdU incorporation in Map2 positive cells in the oligomer-rich preparations, but not the monomer-rich or vehicle control (merged images in C, F, I). Scale bar: 10 µM. Insert (G-I), higher magnification of the BrdU positive, Map2 positive cell in the oligomer-rich treatment group. J-K, Quantification of the percentage of BrdU positive/Map2 positive cells in Ab monomer-rich and oligomer-rich preparations. Cortical neurons were exposed to either vehicle or increasing concentrations (50-1000 nm) of either monomer-rich (J) or oligomer-rich (K) preparations for 24 h. Treatment with oligomer-rich preparations at concentrations greater than 100 nM resulted in a statistically significant increase in the percentage of BrdU positive cells (p<0.0001). (L) Immunoneutralization of Aβ oligomers with the addition of the Aβ oligomer-specific antibody NU2 (100 nM) resulted in a 5 fold reduction in BrdU incorporation (n=3; p=0.0325) in the neuronal cultures exposed to 100 nM of Aβ oligomer-rich preparations, to levels similar to the vehicle control (the same 100 nM control was utilized for experiments in K and L). At the same concentration, addition of non-specific mouse IgG did not have a statistically significant effect on BrdU incorporation (L). 116 Chapter 4: NSAIDs Prevent Neuronal Cell Cycle Re-Entry in Alzheimer’s Disease Mouse Models Nicholas H. Varvel1,2*, Maria Z. Kounnas3, Steven L. Wagner3, Yan Yang2, Bruce T. Lamb1,4 and Karl Herrup5* 1 Lerner Research Institute, The Cleveland Clinic, Department of Neurosciences NC3-164, 9500 Euclid Avenue, NC30, Cleveland, OH 44195 2 Case Western Reserve University School of Medicine, Department of Neurosciences, 10900 Euclid Avenue, Cleveland, OH 44106 3 Torrey Pines Therapeutics, Inc., La Jolla, CA 92037 4 Case Western Reserve University School of Medicine, Department of Genetics, 10900 Euclid Avenue, Cleveland, OH 44106 5 Rutgers, The State University of New Jersey, Department of Cell Biology and Neuroscience Nelson Biological Laboratories, Busch Campus, 604 Allison Road, Piscataway, NJ 08854 This manuscript will be submitted for publication. 117 Contributions of Authors Nicholas H. Varvel, Karl Herrup and Bruce T. Lamb wrote the manuscript. Yan Yang initiated and assisted in the design of experiments. Maria Z. Zounnas and Steven L. Wagner performed amyloid-beta ELISA. Experiments and data interpretation were performed by Nicholas H. Varvel with Karl Herrup and Bruce T. Lamb. Acknowledgements The authors thank R. Yan (Cleveland Clinic, Cleveland, OH) for Bace1-/- mice, Richard M. Ransohoff (Cleveland Clinic, Cleveland, OH) for Cx3cr1gfp/gfp mice and G. Xu and N. Maphis for technical support. This work was supported in by the National Institutes of Health Grants (AG026146 to S.W.P., AG023012 to B.T.L. and AG024494 to K.H. and B.T.L.), the Alzheimer’s Association (B.T.L.) and an Anonymous Foundation. 118 Introduction Alzheimer’s disease (AD), the most common dementing disorder of late life, is now the fourth major cause of death in the developed world after heart disease, cancer and stroke (Cummings and Cole, 2002). Increasing evidence suggests the progression of the disease is lengthy and there is currently no effective treatment. A definitive diagnosis of AD requires post-mortem examination of brain tissue for the presence of distinctive AD histopathology including neurofibrillary tangles, extracellular deposits of the β-amyloid peptide (Aβ) in senile plaques, activation of microglia and astrocytes, and induction of neuronal cell cycle alterations and accompanying cell loss. Understanding the relationship between the various neuropathological hallmarks of AD in the human brain has proven difficult, due to lack of accurate diagnostic markers, length of disease progression, and the considerable variation in the duration, severity, symptoms, age of onset and clinical/neuropathological correlations of AD. AD is one of many neurodegenerative conditions characterized by chronic neuroinflammatory processes. Microglia, the resident immune cells of the brain, are found in a highly activated state in close anatomical proximity to senile plaques within the AD brain, where they secrete numerous pro-inflammatory cytokines and chemokines (Akiyama et al., 2000; Wyss-Coray, 2006). Recent studies utilizing in vivo imaging have demonstrated that microglia rapidly migrate to newly formed Aβ deposits in mouse models of AD and are capable of removing Aβ fibrils (Bolmont et al., 2008; Meyer-Luehmann et al., 2008). However, it remains to be determined if neuroinflammatory alterations also 119 contribute to early steps in AD progression. Retrospective epidemiological studies indicate that chronic, long-term treatment with non-steroidal antiinflammatory drugs (NSAIDs) decrease the risk for developing AD, suggesting that neuroinflammation may play a pivotal role in early disease processes (McGeer et al., 1996; Stewart et al., 1997; Vlad et al., 2008). However, thus far prospective clinical trials with multiple different NSAIDs have failed to demonstrate significant beneficial effects in individuals with existing cognitive impairments characteristic of AD (Martin et al., 2008). At present, the biological mechanisms underlying the divergent results obtained in the retrospective and prospective NSAID studies remains unclear. NSAIDs may act via several pathways to influence AD pathogenesis. First, NSAIDs can reduce neuroinflammation via canonical anti-inflammatory pathways within the brain. Indeed, chronic administration of NSAIDs reduces neuroinflammation, AD-like brain pathology and behavioral impairments in transgenic mouse models of AD (Lim et al., 2000; Lim et al., 2001; Yan et al., 2003; Sung et al., 2004; Kukar et al., 2007). Second, NSAIDs can act as γsecretase modulators (GSMs). Acute administration of selective NSAIDs results in production of shorter, less amyloidogenic Aβ peptides both in vitro and in vivo, likely through interactions with the amyloid precursor protein (APP) that influences γ-secretase cleavage (Weggen et al., 2001; Eriksen et al., 2003; Kukar et al., 2008). Third, NSAIDs may also regulate the levels of β-secretase through a PPARγ-mediated pathway (Sastre et al., 2006). Finally, NSAIDs may act to 120 inhibit the formation of Aβ oligomers and Aβ deposits through direct interaction with the Aβ peptide (Kukar et al., 2008). Increasing evidence suggests that ectopic expression of cell cycle proteins and DNA synthesis identifies neuronal populations subject to degeneration in AD (Arendt et al., 1996; Vincent et al., 1996; McShea et al., 1997; Yang et al., 2001). Furthermore these cell cycle events (CCEs) are also observed in a similar pattern and extent in mild cognitive impairment (MCI), the clinical predecessor to AD (Petersen, 2000; Morris et al., 2001). Together, these results suggest the CCEs identify an early pathogenic process that ultimately results in the neuronal cell death characteristic of AD. In order to gain insights into the biological processes underlying the induction of neuronal CCEs we have focused on the genomic-based mouse model of AD, R1.40 (Lamb et al., 1993; Lamb et al., 1997; Lehman et al., 2003a). The R1.40 mouse model exhibits CCEs in a reliable, age-dependent pattern that identifies the identical neuronal populations subject to degenerate in human AD (Yang et al., 2006). Strikingly, neuronal CCEs occur approximately six months prior to the first appearance of Aβ deposits in this model. In addition, our previous studies demonstrated that lowering or eliminating Aβ production via genetic means in the R1.40 mouse model resulted in either a delay or complete block of neuronal CCEs, respectively (Varvel et al., 2008). The current studies focused on delineating the Aβ-dependent pathways responsible for induction of neuronal CCEs in the R1.40 mouse model and corresponding therapeutic strategies aimed at blocking CCEs. We demonstrate 121 that alterations in brain microglia are coincident with the first evidence of neuronal CCEs in the R1.40 model and that the microglial alterations are dependent on Aβ generation. This led us to hypothesize that Aβ-dependent inflammatory responses play a direct role in the induction of neuronal CCEs in AD mouse models. In support of this hypothesis, induction of systemic inflammation promoted the ectopic appearance of neuronal CCEs in young R1.40 animals, but not in non-transgenic controls. In addition, inhibition of neuroinflammation in young R1.40 animals through the chronic administration of two commonly used NSAIDs, ibuprofen and naproxen, blocked alterations in brain microglia as well as neuronal CCEs in the absence of detectable alterations in APP processing and Aβ metabolism. However, therapeutic NSAID treatment of older R1.40 mice, in which the induction of neuronal CCEs had already begun, demonstrated that while subsequent neuronal CCEs could be blocked, the presence of extant CCEs could not be reversed. Together, these results support the role of both Aβ and neuroinflammation in the induction of neuronal CCEs and provide a potential explanation for the relative successes and failures of the retrospective and prospective trials of NSAIDs in the treatment of human AD. 122 Materials and Methods Mice The R1.40 transgene is a full genomic copy of human APP (a 650 kb insert from a yeast artificial chromosome clone) carrying the Swedish (K670M/N671L) mutation associated with early-onset familial AD. Creation of the R1.40 transgenic mouse strain and subsequent backcrossing to inbred strains has been described previously (Lamb et al., 1993; Lamb et al., 1997; Lehman et al., 2003a). Age- and gender-matched non-transgenic C57BL/6J animals served as controls in all analyses. Homozygous R1.40 animals, maintained on the C57BL/6J genetic background were crossed to Bace1-/- animals (Cai et al., 2001), also maintained on the C57BL/6J genetic background, to generate F1 R1.40/-;Bace1+/- animals. F1 animals were intercrossed to generate animals homozygous for the R1.40 transgene and homozygous for the Bace1 knockout allele as well as Bace1-/- animals, lacking the R1.40 transgene. Homozygous R1.40 animals, maintained on the C57BL/6J genetic background were also crossed to Cx3cr1gfp/gfp animals (Geissmann et al., 2003), on the C57Bl/6J genetic background, to generate F1 R1.40/Cx3cr1+/gfp animals. F1 animals were intercrossed to generate animals homozygous for the R1.40 transgene and homozygous for the Cx3cr1 knockout allele as well as Cx3cr1gfp/gfp animals, lacking the R1.40 transgene. Non-steroidal Anti-inflammatory Drug Treatments Ibuprofen and naproxen were obtained from Sigma (St. Louis, MO). These compounds were formulated into standard, color-coded animal chow by 123 Research Diets (New Brunswick, NJ) at a final concentration of 375 parts per million. Three- and six-month old male and female R1.40 mice and age-matched non-transgenic controls were fed drug-supplemented or control chow ad libitum for either three or six months. During each trial the animals were weighted on a weekly basis. Mice were sacrificed following the experimental period and processed for either histological or biochemical analyses. Lipopolysaccaride Administration Two-month old male and female R1.40 mice and age-matched nontransgenic controls were injected with lipopolysaccaride (LPS, Sigma, L2880, 20 µg/animal) or PBS via intraperitoneal injection. Animals were subject to LPS or PBS once a day for four consecutive days and sacrificed four hours following the final injection (Cardona et al., 2006b). Antibodies Antibodies utilized for these studies include: rabbit polyclonal cyclin A antibody (ab 7956; Abcam, Cambridge, UK), specific for the C-terminal domain of cyclin A2; mouse monoclonal cyclin D antibody (ab 31450; Abcam, Cambridge, UK); mouse monoclonal NeuN antibody (Chemicon, Temecula, CA) was used as a neuronal-specific marker and CT-15, specific for the C-terminus of APP. Secondary antibodies were conjugated to various fluorescent Alexa dyes (Molecular Probes, Eugene, OR) Histology and Immunohistochemistry Animals were prepared for histological analysis as previously described (Yang et al., 2006). Animals were deeply anesthetized with Avertin (0.02 cc/mg 124 body weight); they were perfused transcardinally with 0.1 M sodium phosphate buffer (PB); pH 7.4, followed by 4% paraformaldehyde in 0.1 M (PB). The brain was dissected, immediately removed from the cranium and transferred to fresh 4% paraformaldehyde at 4°C overnight. To perform double fluorescent immunohistochemistry, sections were first rinsed in PBS containing 0.1% Triton X-100 (PBST). Sections were subsequently incubated for 1 h at room temperature in 10% goat serum in PBS to block non-specific binding. All primary antibodies were diluted in PBST and applied overnight at 4°C. After rinsing in PBS, the slides were incubated for 2 h with a secondary antibody, which was conjugated to various fluorescent Alexa dyes (dilution, 1:1000). The sections were then rinsed in PBS followed by incubation in the 10% goat serum blocking solution for 1 h and incubation with the second primary antibody (raised in a different species from the first primary antibody) overnight at 4°C. Sections were subsequently rinsed in PBS and the second secondary antibody, conjugated with a difference fluorescent dye, was applied to sections for 2 h at room temperature. After rinsing, all sections mounted in DAPI Hardset Reagent (Vector Laboratories, Burlingame, CA) under a glass coverslip. Antibody concentrations utilized for immunohistochemistry were: rabbit anti-cyclin A2 (Abcam) 1:200, mouse anti-cyclin D (Abcam) 1:200 and mouse anti-NeuN (Chemicon) 1:500 and fluorescently tagged secondary antibodies (Molecular Probes) 1:1000. Fluorescent in situ hybridization was performed as described (Kulnane et al., 2002), using a mouse-specific DNA probe (480C6, from the RPCI-22 BAC library) containing 150 kb of genomic sequence from the region that encodes the 125 endogenous Sim2 gene located on mouse chromosome 16 and a human-specific DNA probe (66H5, from the RPCI-11 BAC library) containing 170 kb of genomic sequence from the region that encodes the human APP gene located on human chromosome 21 and integrated into mouse chromosome 13 in the transgenic R1.40 animals. Neuronal cell counts For each of the treatment groups we examined five animals at each age. A total of five evenly spaced sections containing the frontal cortex were double stained for the neuronal marker, NeuN and cyclin A or cyclin D. The area located between 2.5 mm and 3.4 mm anterior to the Bregma was identified in each section analyzed. We scored NeuN-positive cells within cortical layers II/III or V/VI for the presence or absence of the cell cycle marker. Only cells with a discernable portion of their nucleus in the section were scored. For each of the five sections the percentage of NeuN+ cells exhibiting immunoreactivity for the cell cycle marker was tabulated, and the percentages for the five sections analyzed in each animal averaged. For each age and treatment group, the percentages were averaged over all 5 animals and expressed as mean + SEM. Adjacent sections that had undergone processing for fluorescent in situ hybridization (FISH) were tabulated in a similar fashion. Neurons were scored for the presence or absence of 3 or 4 spots of hybridization. All counts were performed in a blinded fashion and data were analyzed with the Student’s t test (GraphPad Prism, GraphPad Software, Inc. San Diego, CA). 126 Western blot of tissue homogenates Mice were killed by cervical dislocation and their brains were removed, divided sagittally (after removing cerebellum), and snap frozen. Tissues were subsequently homogenized in 10 volumes of Tris-buffered saline (50 mM Tris; pH 7.4, 150 mM NaCl, 1 mM EDTA, 0.1% Triton-X) with protease inhibitor cocktail (Sigma-Aldrich). Total brain homogenates were subsequently sonicated to shear DNA and centrifuged at 14,000 g for 30 min at 4°C to remove nuclei and cell debris. Total protein concentrations were determined using the Pierce bicinchoninic acid (BCA) Protein Assay Kit (Pierce). 30 µg of brain protein was run on a Novex NuPage, 4-12% Bis-Tris gel (Invitrogen), then transferred to a PVDF membrane. The Western blots were subsequently incubated with antibody CT-15 (1:5000, kindly provided by Edward H. Koo) against the Cterminus of APP (Martin et al., 1991). 127 Results Alterations in brain microglia in the R1.40 mouse model of AD To determine whether the induction of neuronal CCEs was accompanied by alterations in brain microglia, we utilized the genomic-based R1.40 transgenic mouse model of AD, in which neuronal CCEs are first observed at six months of age in the frontal cortex (Yang et al., 2006). Brain sections of adult R1.40 and control mice were examined for the microglial marker, Iba1, via immunohistochemistry at a variety of ages. Consistent with our previous studies R1.40 mice exhibit microglial activation and migration to sites of neocortical Aβ deposition beginning at about 12 to 14 months of age (data not shown). Unexpectedly, however, immunohistochemical analysis of microglial morphology in six-month old R1.40 animals demonstrated robust alterations in cortical microglia (Figure 4.1C and 4.1D). The microglia exhibited shorter, asymmetrically oriented processes as well as swollen cell bodies when compared to aged-matched, non-transgenic controls (Figure 4.1A and 4.1B). As expected, microglia in six-month old non-transgenic animals display a “resting” phenotype with numerous, thin, branching processes extending away from the small cell body of the microglial cells (Figure 4.1A and 4.1B). These alterations in brain microglia were also not observed at four months of age in the R1.40 or control mice (data not shown), suggesting that similar to induction of neuronal CCEs, alterations in brain microglia occur between four and six months of age. 128 In order to confirm our immunohistochemical data suggesting alterations in cortical microglia at six months of age, the R1.40 transgenic mice were crossed to a microglial reporter, in which the green fluorescent protein (GFP) gene is knocked into the fractalkine receptor (Cx3cr1) locus and specifically labels all brain microglial with GFP. Mice were generated that were heterozygous for the Cx3cr1 knock-in (Cx3cr1+/gfp) with and without the R1.40 transgene and brain sections were examined via fluorescent confocal microscopy. Similar to the immunohistochemical data, six-month old Cx3cr1+/gfp mice lacking the R1.40 transgene exhibit numerous “resting” microglia with numerous thin, branching processes (Figure 4.1G). However, Cx3cr1+/gfp mice with the R1.40 transgene exhibited GFP-expressing microglia with an activated phenotype, including shortened processes and enlarged cell bodies (Figure 4.1H). Similar to the immunohistochemical data, studies of younger animals suggested that these alterations in the brain microglia occurred between four and six months of age (data not shown). Finally, to directly test if Aβ generation from the R1.40 transgene is required for the alterations in brain microglia observed at six months of age, R1.40 transgenic mice were mated with animals lacking Bace1, the primary βsecretase required for the first step in the generation of Aβ from APP. Notably, Iba1 immunoreactivity demonstrated that cortical microglia in six-month old R1.40 transgenic mice lacking Bace1 exhibited a resting phenotype (Figure 4.1E and 4.1F) that resembled that observed in age matched, non-transgenic controls (Figure 4.1A and 4.1B) and was distinctly different from the microglial 129 morphology observed in the R1.40 transgenic mice (Figure 4.1C and 4.1D). Together with our previous data demonstrating that the induction of neuronal CCEs at six months of age is also dependent on the amyloidogenic processing of APP in the R1.40 mouse model, these results suggest that microglial activation could play a direct role in the Aβ dependent induction of neuronal CCEs. Induction of inflammation promotes microglial activation and neuronal CCEs Based on the correlative data linking microglial alterations and neuronal CCEs, we next examined whether induction of neuroinflammation was capable of inducing ectopic neuronal CCEs in young R1.40 animals, utilizing the environmental inflammatory stimulus, lipopolysaccaride (LPS). Two-month old non-transgenic and R1.40 mice were injected with either LPS, via standard protocol (20 µg/animal for four days) previously demonstrated to induce microglia activation (Cardona et al., 2006b) or with phosphate-buffered saline (PBS). As expected, Iba1 immunohistochemistry for microglia demonstrated that LPS exposure induced robust microgial activation in both R1.40 mice (Figure 4.2E) and non-transgenic controls (Figure 4.2A) when compared to R1.40 (Figure 4.2I) or non-transgenic control (data not shown) injected with PBS. Brain tissue in the LPS-injected and PBS-injected controls was subsequently examined for induction of neuronal CCEs via immunohistochemistry for cell cycle proteins and the neuronal marker NeuN. As expected from our previous studies, two-month old R1.40 animals injected with 130 PBS, did not exhibit any evidence of cyclin D or cyclin A (data not shown) positive neurons in frontal cortical layers II/III (Figure 4.2J-4.2L). By contrast, LPS-injected R1.40 animals exhibited numerous cyclin D and cyclin A (data not shown) positive neurons in the same brain regions (Figure 4.2F-4.2H). Notably, neither the LPS-injected (Figure 4.2B-4.2D) nor the PBS-injected non-transgenic controls exhibited evidence of neuronal CCEs. Taken together, these data suggest that the induction of neuronal CCEs is dependent on both the induction of neuroinflammatory processes as well as Aβ generation, as R1.40 animals, and not non-transgenic controls, exhibit ectopic neuronal CCEs after LPS stimulation. Prevention NSAID treatment inhibits neuroinflammatory responses and neuronal CCEs We next wanted to determine whether inhibition of the microglial alterations observed at six months of age in the R1.40 transgenic mice could block the induction of neuronal CCEs. To test this hypothesis, three-month old R1.40 and aged-matched, non-transgenic controls were placed on standard laboratory diets with or without ibuprofen or naproxen for three months in a prevention treatment paradigm. At six months of age, all mice were examined for the effect on both microglial alterations as well as neuronal CCEs. As, expected, Iba1 immunohistochemistry revealed that both ibuprofen (Figure 4.3C and 4.3D) and naproxen (Figure 4.3E and 4.3F) treatments reduced the activated microglial phenotype exhibited by R1.40 animals on the control diet (Figure 4.3A and 4.3B) to that resembling the “resting” phenotype exhibited by age-matched, 131 non-transgenic controls (Figure 4.1A and 4.1B). These results demonstrate that the Aβ dependent microglial alterations observed in the R1.40 mouse model of AD can be blocked via chronic NSAID treatment. Brain sections from the control and the NSAID treatment groups were examined for alterations in neuronal CCEs by both immunohistochemistry for cell cycle proteins and fluorescent in situ hybridization (FISH) to detect DNA synthesis. Consistent with our previous studies, R1.40 transgenic mice on a control diet lacking NSAIDs exhibited a substantial number of cyclin A and cyclin D (data not shown) positive neurons in layers II/III of frontal cortex (Yang et al., 2006; Varvel et al., 2008) (Figure 4.4A-4.4C). These neuronal populations also exhibit evidence of DNA replication as indicated by three or four spots of hybridization with a DNA FISH probe for mouse chromosome 16 (Figure 4.4Cinset) as well as the R1.40 transgene on mouse chromosome 13 (data not shown). Significantly, R1.40 mice on either ibuprofen (Figure 4.4D-4.4F) or naproxen (Figure 4.4G-4.4I) supplemented diets exhibited little evidence of cyclin A and cyclin D (data not shown) expression or DNA replication (Figure 4.4F and 4.4I, insets). Taken together, these data indicate that a three-month prevention treatment of young R1.40 mice with two different commonly utilized NSAIDs blocks both the microglial alterations and neuronal CCEs observed in this mouse model of AD. The effectiveness of the NSAID treatments in reducing neuronal CCEs was quantified by determining the percentage of neurons in frontal cortical layers II/III positive for cyclin A (Figure 4.5A) and cyclin D (Figure 4.5B) as well as the 132 percentage of neurons exhibiting three or four spots of hybridization with a DNA probe specific to mouse chromosome 16 (Figure 4.5C) or mouse chromosome 13 (Figure 4.5D). Similar to previously published results, quantitative analysis revealed that 43% of the neurons (NeuN positive cells) in frontal cortical layers II/III are positive for cyclin A (Figure 4.5A) in R1.40 transgenic mice at six months of age. Strikingly, the three month ibuprofen and naproxen treatments significantly decreased the percentage of cortical layer II/III neurons expressing cyclin A in R1.40 transgenic animals to ~4% and ~3%, respectively. Calculation of the percentage of cyclin D positive neurons yielded similar results (Figure 4.5B). R1.40 transgenic mice exhibited 47% cyclin D positive cortical layer II/III neurons. The ibuprofen and naproxen treatments reduced the percentage to 5% and 3%, respectively, while age-matched non-transgenic control exhibited 1.4% cyclin D positive neurons. Quantitative analysis of the percentage of neuronal nuclei with three or four spots of hybridization following FISH with a bacterial artificial chromosome (BAC) probe specific for mouse chromosome 16 revealed that R1.40 transgenic mice exhibit altered ploidy in 12% of neurons in frontal cortical layers II/III (Figure 4.5C). By contrast, the ibuprofen and naproxen treatments reduced the percentage of neuronal nuclei exhibiting three or four spots of hybridization to 0.6% and 0.4%, respectively, which was statistically indistinguishable from nontransgenic controls. Similar results were obtained with a BAC probe that recognizes the R1.40 transgene integration site on mouse chromosome 13 with upward of 9% of R1.40 neurons exhibiting altered ploidy that was reduced to 133 0.9% and 0.5% in the ibuprofen and naproxen groups, respectively (Figure 4.5D). Lack of effect of NSAIDs on APP Processing and Aβ Metabolism Considerable evidence suggests that NSAIDs can act as γ-secretase modulators (GSMs) in acute treatment paradigms both in vitro and in vivo. However, the potency of different NSAIDs as GSMs varies widely, with ibuprofen reported as one of the most effective GSMs, while naproxen lacks any apparent GSM activity (Weggen et al., 2001; Eriksen et al., 2003). We selected ibuprofen and naproxen for the current studies in an effort to discriminate between NSAIDs with and without substantial GSM activity. However, given that relatively few studies have examined the effects of chronic NSAID administration on Aβ metabolism and that our previous studies demonstrated the induction of both microglial alterations (Figure 4.1) and neuronal CCEs are dependent on Aβ generation (Varvel et al., 2008), we examined the effects of our NSAID treatment paradigm on APP processing and Aβ metabolism. First, to examine the effects of chronic NSAID administration on APP processing, brain extracts from six-month old R1.40 transgenic mice that were placed on ibuprofen-containing, naproxen-containing and control diets were analyzed by Western blot analysis for the levels of holo-APP and APP C-terminal fragments (CTFs). No significant differences in the steady state levels of holoAPP were observed in samples from either of the NSAID treatment groups when compared to controls (Figure 4.6A, top panel). Quantification of the levels of holo-APP via normalization to glyceraldehype 3-phosphate dehydrogenase 134 (GAPDH) levels as a protein loading control (Figure 4.6A, bottom panel), confirmed that the levels of holo-APP were unchanged between the control and NSAID treatment groups (Figure 4.6B). In addition, Western blot analysis revealed that the levels of the two primary APP CTFs, CTFα (data not shown) and CTFβ, the immediate precursor of Aβ, were also unchanged between the control and treatment groups (Figure 4.6a, middle panel). Second, we examined the effects of chronic NSAID administration on Aβ metabolism. The steady-state levels of the two major isoforms of Aβ (Aβ1-40 and Aβ1-42) were determined by enzyme-linked immunosorbent assays (ELISAs) from formic acid extracted brain extracts. Notably, neither ibuprofennor naproxen-treatment led to significant alterations in the steady state levels of either Aβ1-40 or Aβ1-42 or the ratio of Aβ1-42/Aβ1-40 when compared to control (Table 4.1). Taken together, our results suggest that while chronic administration of NSAIDs blocked the microglial alterations and neuronal CCEs observed in the R1.40 mouse model of AD, this is likely independent of the potential effect of NSAIDs in modulating APP processing and Aβ metabolism. Therapeutic NSAID treatment cannot reverse extant neuronal CCEs Neuronal CCEs proceed in a precise temporal and spatial pattern within the R1.40 transgenic mouse model of AD. For example, neurons residing in frontal cortical layers II/III first exhibit CCEs at 6 months of age, while neurons situated in cortical layers V/VI do not exhibit CCEs until 12 months of age (Figure 4.7A for a graphical timeline) (Varvel et al., 2008). Furthermore, once 135 formed within a specific brain region, neuronal CCEs are extremely stable over the lifespan of the animals. Given our findings that prevention NSAID administration could block the appearance of neuronal CCEs in cortical layers II/III, we next examined whether therapeutic administration of ibuprofen and naproxen at later ages could reverse the extant CCEs as well as block the subsequent neuronal CCEs. Six-month old R1.40 transgenic mice were placed on either control, ibuprofen- or naproxen-supplemented diets for six months. Brain sections from the 12-month old animals were subsequently examined for the presence of neuronal CCEs via immunohistochemistry for cell cycle proteins and FISH for DNA synthesis. To determine whether NSAID administration could reverse extant CCEs, we first examined neurons in frontal cortical layers II/III, as this neuronal population first exhibits CCEs by six months of age (Varvel et al., 2008). Notably, immunohistochemistry for cyclin D (Figure 4.7B, 4.7D and 4.7F) revealed the presence of numerous cyclin A (data not shown) and cyclin D (Figure 4.7B, 4.7D and 4.7F) positive neurons in both the control (Figure 4.7B and 4.7C), ibuprofen (Figure 4.7D and 4.7E) and naproxen (Figure 4.7F and 4.7G) treatment groups. This was supported by the FISH data, documenting the presence of neuronal nuclei with three or four spots of hybridization with a DNA FISH probe for mouse chromosome 13 (Figure 4.7C, 4.7E and 4.7G, insets) and mouse chromosome 16 (data not shown) in both control and NSAID treatment groups. 136 Quantification of the number of neuronal CCEs in frontal cortical layers II/III confirmed the lack of an effect on this neuronal population following a six month NSAID treatment. Similar to the results obtained at six months of age (Figure 4.5), ~45-50% of neurons within frontal cortical layers II/III were positive for cyclin A (Figure 4.8A) and cyclin D (Figure 4.8B) in 12-month old R1.40 transgenic mice. In addition, the number of neurons with three or four spots of hybridization in frontal cortical layers II/III remain unchanged between six and 12 months of age, with ~10-15% positive with DNA probes to mouse chromosomes 16 (Figure 4.8C) and the R1.40 transgene on mouse chromosome 13 (Figure 4.8D). Notably, the six month treatment with either ibuprofen or naproxen did not lead to any significant alterations in the percentage of cyclin A or cyclin D positive neurons (Figure 4.8A and 4.8B) or in the percentage of neuronal nuclei with three or four spots of hybridization (Figure 4.8C and 4.8D). This data suggests that therapeutic NSAID administration is incapable of reversing the extant neuronal CCEs observed in the R1.40 mouse model of AD. Therapeutic NSAID treatment can block subsequent neuronal CCEs Neuronal CCEs first appear in cortical layers V/VI at 12 months of age in the R1.40 mice (Figure 4.7H). To determine whether the therapeutic administration of ibuprofen or naproxen could block CCEs in this neuronal population, we next examined brain sections by both immunohistochemistry and FISH for CCEs. Unlike the results obtained for the existing CCEs in frontal cortex layers II/III (Figure 4.7B-4.7G), both ibuprofen (Figure 4.7J and 4.7K) 137 and naproxen (Figure 4.7L and 4.7M) lead to a dramatic reduction in the number of cyclin A (data not shown) and cyclin D (Figure 4.7J and 4.7L) positive neurons in layers V/VI at 12 months of age. FISH analysis with probes from mouse chromosome 13 (Figure 4.7I, 4.7K and 4.7M, insets) and 16 (data not shown) also revealed an apparent decrease in neuronal CCEs, with a decrease in the number of neuronal nuclei with three or four spots of hybridization. The effectiveness of the therapeutic NSAID treatments in blocking subsequent neuronal CCEs was quantified by determining the percentage of neurons in frontal cortex layers V/VI positive for cyclin A (Figure 4.8A) and cyclin D (Figure 4.8B) as well as the percentage of neurons exhibiting three or four spots of hybridization with a DNA probe specific to mouse chromosome 16 (Figure 4.8C) or the R1.40 transgene on mouse chromosome 13 (Figure 4.8D). Quantitative analysis revealed that ~50% of the neurons (NeuN positive cells) in cortical layers V/VI are positive for cyclin A (Figure 4.8A) and cyclin D (Figure 4.8B) in the R1.40 transgenic mice at 12 months of age. The six month ibuprofen and naproxen treatments significantly decreased the percentage of cortical layer V/VI neurons expressing cyclin A and cyclin D in the R1.40 transgenic animals to levels that were statistically indistinguishable from the percentage of cyclin A and cyclin D positive neurons in age-matched, nontransgenic controls. Quantitative analysis of the percentage of neuronal nuclei in layers V/VI with three or four spots of hybridization following FISH with DNA probes for mouse chromosome 16 (Figure 4.8C) and 13 (Figure 4.8D) also revealed a significant decrease after ibuprofen and naproxen treatments to levels 138 indistinguishable from non-transgenic controls. Taken together, our results suggest that therapeutic administration of NSAIDs is capable of blocking subsequent neuronal CCEs, but not able to reverse existing neuronal CCEs in the R1.40 mouse model of AD. 139 Discussion There is increasing evidence that the neurodegeneration observed in AD is the result of a pathogenic process that is likely initiated one to two decades prior to the onset of the cognitive symptoms associated with the disease. While biochemical, genetic and pathological studies clearly implicate disrupted Aβ homeostasis as being central to AD pathogenesis, the relationship between Aβ generation and deposition and the other features of the disease remains unclear. For example, longitudinal position emission tomography (PET) studies with the amyloid binding Pittsburgh compound B (PIB) have revealed that a number of aged, cognitively normal individuals have a substantial amount of amyloid deposition (Mintun et al., 2006; Rowe et al., 2007). This has direct implications for both the study of pathogenic mechanisms underlying AD, as well as the various prospective clinical trials being conducted in human AD. In light of this, we, as well as others, have focused on the identification of the earliest markers that identify neurons at risk in AD. Our previous studies have demonstrated that one of the most reliable indicators of neuronal populations at risk in AD is ectopic expression of cell cycle proteins as well as evidence of DNA synthesis in post-mitotic neurons. Significantly, neuronal CCEs identify neurons at risk, both in AD, as well as in MCI, the clinical predecessor to AD, suggesting that they indeed represent an early marker of neuronal vulnerability (Busser et al., 1998; Yang et al., 2001; Yang et al., 2003). Furthermore, we recently documented the presence of neuronal CCEs in a genomic-based transgenic mouse model of AD that first 140 occurs six to eight months prior to Aβ deposition and proceeds in a precise temporal and spatial pattern in the identical populations of neurons at risk in the human disease (Yang et al., 2006). Finally, genetic ablation of Bace1 in the R1.40 mice clearly demonstrated that the induction of neuronal CCEs was dependent on Aβ generation (Varvel et al., 2008). The current studies provide novel insights into the potential mechanisms underlying neuronal CCEs as well as therapeutic strategies aimed at reducing them using R1.40 mouse model of AD. First, we observed alterations in cortical microglia that occur between four and six months of age in the R1.40 mouse model of AD that was coincident with the first appearance of the neuronal CCEs in these animals. The microglial alterations were not observed in age matched, non-transgenic controls and was confirmed using a GFP reporter that specifically tags microglia within the brain. Most significantly, we demonstrated that the induction of the microglia alterations was dependent on Aβ generation in this model. While alterations in microglia are typically associated with the deposition of Aβ and subsequent migration to surround the deposits, several recent reports suggest that alterations in microglia as well as the production of cytokines, chemokines and reactive oxygen species may also occur early in disease progression in other mouse models of AD (Pratico et al., 2001; Tehranian et al., 2001; Janelsins et al., 2005). Second, to test whether microglial activation could play a role in the induction of neuronal CCEs, young R1.40 transgenic animals, prior to the first onset of neuronal CCEs, were subjected to a robust inflammatory challenge with 141 lipopolysaccharide (LPS). As expected, both non-transgenic controls and R1.40 mice exhibited robust microglial activation after LPS challenge. However, only LPS injected R1.40 transgenic mice, but not non-transgenic or PBS injected controls exhibited induction of ectopic neuronal CCEs. Third, to test whether anti-inflammatory treatments could block or reverse neuronal CCEs, R1.40 transgenic mice were placed on diets containing two commonly used NSAIDs, ibuprofen and naproxen, in a prevention as well as a therapeutic trial. The NSAID prevention trial was initiated three months prior to the first appearance of neuronal CCEs and continued to six months of age, when the neuronal CCEs first appear in frontal cortical layers II/III (Varvel et al., 2008). As expected, our results demonstrate that both ibuprofen and naproxen treatments were capable of reducing the microglial alterations observed at six months of age in the R1.40 mice. In addition, both the ibuprofen and naproxen treatment groups exhibited a dramatic reduction in the neuronal CCEs. Our biochemical analysis suggests that the effect of NSAIDs on neuronal CCEs occurs independent of any robust alterations in APP processing or Aβ metabolism within the brain. The NSAID therapeutic trial was initiated at six months of age and continued until 12 months of age, when neuronal CCEs first appear in frontal cortical layers V/VI. While both ibuprofen and naproxen treatments blocked the appearance of neuronal CCEs at 12 months of age, they were incapable of reversing the neuronal CCEs that first appeared at six months of age in cortical layers II/III. 142 There is considerable and confirming data regarding the efficacy of NSAIDs in the prevention and/or treatment of AD. Retrospective epidemiological studies suggest a wide variety of NSAIDs may provide protection from the subsequent development of AD (McGeer et al., 1996; in t' Veld et al., 2001; Etminan et al., 2003). Indeed, a recent study of nearly 250,000 individuals within the Veterans Administration system, suggested that a number of different NSAIDs, including ibuprofen and naproxen, reduced AD risk that was only significant after greater than four to five years of treatments, suggesting that NSAIDs may only prove efficacious after multiple years of continual treatment or at early states of disease progression (Vlad et al., 2008). On the other hand, prospective trials with NSAIDs in mild to moderate AD subjects have proven disappointing, with no detectable effect on cognitive decline in trials using naproxen, celecoxib or rofecoxib (Aisen et al., 2003; Martin et al., 2008). Indeed, a recent trial of more than 2,500 individuals reported no significant cognitive improvement after four years of treatment with either naproxen or celecoxib (Martin et al., 2008). In addition, a large phase III clinical trial of flurbiprofen was recently halted due to a lack of cognitive improvement. NSAIDs may act through a variety of different pathways to influence AD pathogenesis. First, NSAIDs may act to reduce inflammatory signalling mechanisms. Long-term use of NSAIDs has been positively correlated with a reduction in plaque-associated microglia in humans (Mackenzie and Munoz, 1998; Alafuzoff et al., 2000). Furthermore, mouse models of AD treated with NSAIDs exhibit reductions in numerous inflammatory markers, such as microglial 143 activation and expression of proinflammatory molecules (Lim et al., 2000; Jantzen et al., 2002; Yan et al., 2003; Heneka et al., 2005; Kotilinek et al., 2008). Second, selective NSAIDs act as γ-secretase modulators. Numerous studies have demonstrated that an acute administration of selective NSAIDs to AD mouse models results in decreased production of longer Aβ peptides, in favor or shorter less-amyloidogenic isoforms. Unlike numerous previous reports, we did not observe differences in steady state levels of Aβ1-40, Aβ1-42 or the ratio of Aβ1-42/Aβ1-40 peptides (Table 1) following chronic NSAID treatments. The differences in outcomes observed between our laboratories and others may be a reflection of differences in methodology, including the length of time each NSAID was administered. In addition, it is conceivable that the decreases in Aβ1-42 levels are extremely short-lived. Golde and colleagues sacrificed the AD mouse models two hours after the final administration of the NSAID (Weggen et al., 2001; Eriksen et al., 2003). Our studies recapitulated the manner in which humans are exposed to chronic NSAIDs. Third, it has been suggested that NSAIDs regulate Bace1 expression levels through a PPARγ-mediated pathway. Certain NSAIDs, including ibuprofen, are agonists for PPARγ (Lehmann et al., 1997). Activation of PPARγ with a selective agonist, pioglitazone, reduces Bace1 levels as well as steady state levels of CTFβ in a mouse model of AD (Sastre et al., 2006). However, the direct relationship between ibuprofen administration and suppression of Bace1 levels remains unresolved. In the current studies, we did not find any differences in CTFβ levels in the NSAID treatment groups, 144 confirming our conclusion that our treatment primarily targets inflammatory processes and not APP processing. In summary, neuronal cell cycle events are one of the earliest manifestations of Alzheimer’s disease pathogenesis. Here, we provide compelling data indicating that the induction of neuronal CCEs can be blocked by the chronic administration of two commonly use NSAIDs, ibuprofen and naproxen. We argue that neuronal CCEs therefore represent a viable disease relevant early biomarker for AD risk and progression. Our future studies will be focused on identifying the inflammatory molecule(s) that are responsible for neuronal cell cycle re-entry. 145 146 Figure 4.1: Aβ-dependant alterations in brain microglia in R1.40 transgenic mice. A and B, Neocortical microglia in six-month old non-transgenic mice exhibit extensive, fine processes with small cell bodies. C and D, Aged-matched R1.40 animals exhibit reactive neocoritical microglia displaying thick, asymmetrically oriented processes surrounding a swollen cell body. E and F, six-month old R1.40;Bace1-/- animals exhibit microglia with a resting morphology that was indistinguishable from non-transgenic controls (A and B). (G and H), Cx3cr1+/gfp mice lacking the R1.40 transgene (G) display GFP-expressing microglia morphologically similar to the Iba1 stained microglia observed in the non-transgenic controls (A and B). By contrast, Cx3cr1+/gfp mice transgenic mice with the R1.40 transgene exhibit microglia (H) with a reactive morphology similar to that observed in R1.40 transgenic mice at six months of age (C and D). Scale bars: (A, C, E)-50 µm, (B, D, F, G, H,)-10µm. 147 148 Figure 4.2: Lipopolysaccaride (LPS) administration provokes neuroinflammation and neuronal cell cycle events. A-D, Two-month old nontransgenic subject to LPS injections exhibit Iba1-immunoreactive neocortical microglia displaying an activated morphology (A) with no evidence of expression of cyclin D (B) in NeuN-positive neurons (C). E-H, Age-matched R1.40 transgenic animals injected with LPS exhibit Iba1-positive microglia with an activated morphology (E) as well as expression of cyclin D (F) in a subset of NeuN-positive cortical layers II/III neurons (G). I-K, Two-month old R1.40 animals injected with PBS exhibited Iba1-positive microglia with a resting morphology (I) and no evidence of expression of cyclin D (J) in NeuN positive neurons (K). Similar results were obtained with immunohistochemistry for the cell cycle protein cyclin A (data not shown). Nuclei were counterstained with DAPI (blue). D, H and L show the merged images. Arrows indicate cyclin Dpositive neurons. Scale bar, 10 µm. 149 150 Figure 4.3: Prevention trial of NSAIDs inhibits microglial alterations. A and B, Three-month old R1.40 transgenic mice placed on a control diet for three months exhibit Iba1-immunoreactive neocortical microglia with an activated phenotype, similar to R1.40 animals at six months of age (Figure 1C and 1D). (CF), R1.40 animals placed on a three month ibuprofen (C and D) or naproxen containing (E and F) diet exhibit Iba1-positive microglia with a resting phenotype that resembles that observed in six-month old non-transgenic controls (Figure 1A and 1B) and R1.40 animals lacking Bace1 (Figure 1E and 1F). Representative confocal images of Iba1-positive microglia stained with fluorescently tagged secondary antibodies are shown as insets. Scale bars: (A, C, E)-50 µm, (B, D, F)-10µm. 151 152 Figure 4.4: Prevention trial of NSAIDs inhibits neuronal CCEs. A-C, Threemonth old R1.40 transgenic mice placed on a control diet for three months exhibit expression of cyclin A (A) in numerous NeuN-positive (B) neurons on the frontal cortex layers II/III, similar to previously published results. D-I, R1.40 animals placed on the three month ibuprofen-(D-F) or naproxen-containing (G-I) diet exhibit expression of cyclin A (D and G) in a subset of NeuN-positive (E and H) neurons. Similar results were obtained with immunohistochemisty for the cell cycle protein cyclin D (data not shown). Nuclei were counterstained with DAPI (blue). C, F and I show merged images. The larger arrows indicate cyclin Apositive neurons. FISH with a DNA probe to mouse chromosome 13 demonstrated a subset of neurons in the R1.40 animals placed on the control diet with three or four spots of hybridization (C, inset), while the ibuprofen and naproxen treatment groups exhibited only two spots of hybridization (F and I, inset). The smaller arrowns indicate FISH signals in the neuronal nucleus. Scale bar, 10 µm. 153 Figure 4.5: Quantification of inhibition of neuronal CCEs in NSAIDs prevention trial. Percentages of NeuN-positive neurons in cortical layers II/III exhibiting expression of cyclin A (A) or cyclin D (B) as well as three or four spots of hybridization with FISH for DNA probes from mouse chromosome 16 (C) and 13 (D) was calculated in R1.40 transgenic mice placed on a control diet (white bar), ibuprofen- (IBU, grey bar) and naproxen-containing (NAP, checkered bar) diet as well as non-transgenic mice (black bar) placed on a control diet. Values are expressed as a mean plus or minus the standard error of the mean (n=5). The asterisks represent statistically significant alterations between R1.40 on the NSAID-containing diets and control diets with ** p<0.003 and ***p<0.001. 154 Figure 4.6: Lack of effect of NSAIDs on APP processing. A, Western blots of brain extracts from the R1.40 animals on control diets (C1-C3) as well as ibuprofen- (IBU, I1-13) and naproxen-containing (NAP, N1-N3) diets were probed with antibodies to the C-terminus of APP (top two panels) and subsequently stripped and re-probed with an antibody against GAPDH as a loading control. Shown on the right is the approximate size in kDa. B, Relative levels of holoAPP was quantified (n=3) from animals on the control diet (white bar) and the ibuprofen- (IBU, gray bar) and naproxen-containing (NAP, checkered bar) diets by normalizing the intensity values of APP to GAPDH. C, Relative levels of CTFβ was quantified similarly averaging the intensity values of APP CTFβ to GAPDH. No significant differences were observed in the relative levels of holoAPP or CTFβ between treatment groups. 155 Table 4.1: Chronic dosing with NSAIDs does not alter steady-state brain Aβ levels Treatment n Aβ1-40 (pmol g-1) Aβ1-42 (pmol g-1) Aβ1-42/Aβ1-40 Control 10 8.98 (1.86) 3.36 (0.71) 0.39 (0.11) Ibuprofen 10 9.00 (1.23) 3.09 (0.48) 0.35 (0.05) Naproxen 10 10.57 (2.97) 3.15 (0.71) 0.33 (0.11) R1.40 mice were dosed as described in text. Values are expressed as mean (s.d). 156 157 Figure 4.7 Therapeutic trial of NSAIDs inhibits subsequent, but not extant neuronal CCEs. A, Neuronal cell cycle events are first observed in frontal cortical layers II/III at six months of age and continue to persist for two or more years in the R1.40 animals. In contrast, neuronal cell cycle re-entry is not observed in deeper cortical layers V/VI until 12 months of age. Six-month old R1.40 transgenic mice placed on a control diet (B, C, H and I) for six months exhibit expression of cyclin D (B and H) in numerous NeuN-positive neurons in both frontal cortex layers II/III and layers V/VI, similar to previously published results. R1.40 animals placed on a six-month ibuprofen- (D, E, J, and K) or naproxen-containing (F, G, L and M) diet exhibit expression of cyclin D in a subset of NeuN-positive neurons in layers II/III (D and F) with minimal expression of cyclin D in layers V/VI (J and L). Sections were stained with NeuN (red) and nuclei were counterstained witih DAPI (blue) with merged images in C, E, G, I, K and M. Scale bar, 10 µm. 158 Figure 4.8. Quantification of inhibition of neuronal CCEs in NSAIDs therapeutic trial. Percentages of NueN-positive neurons in cortical layers II/III (left) and layers V/VI (right) exhibiting expression of cyclin A (A) or cyclin (B) as well as three or four spots of hybridization with FISH for DNA probes from mouse chromosome 16 (C) and 13 (D) was calculated in R1.40 transgenic mice placed on a control diet (white bar) and ibuprofen- (grey bar) and naproxen-containing (checkered bar) diet as well as non-transgenic mice (black bar) placed on a control diet. Values are expressed as a mean plus or minus the standard error of the mean (n=5). The asterisks represent statistically significant alterations between R1.40 mice on the NSAID-containing diets and control diets with *p<0.001. 159 Chapter 5: Thesis Objectives and Main Findings Accumulating evidence suggests that neuronal cell cycle re-entry is the first step in a process that leads to the observed regional neuronal degeneration observed in AD. Expression of cell cycle proteins and DNA synthesis is observed in neurons susceptible to death in AD (Vincent et al., 1996; McShea et al., 1997; Vincent et al., 1997; Busser et al., 1998; Yang et al., 2001). Importantly, cell cycle proteins and hyperploid neurons are seen at much lower levels in age-matched controls and in neuronal populations within the AD brain where degeneration is not prevalent. Furthermore, immunohistochemical analysis of brain tissue from individuals with mild cognitive impairment (MCI) reveals the presence of cell cycle events (CCEs) in brain region that undergo substantial degeneration in AD (Yang et al., 2003), suggesting that neuronal CCEs represent a viable biomarker for neuronal distress and disease progression. To examine the relationship between neuronal CCEs and the other pathologies associated with AD we utilized the R1.40 mouse model of AD (Lamb et al., 1993; Lamb et al., 1997; Lehman et al., 2003a). The main advantage of the R1.40 mouse model is that it is genomic-based and thus eliminates several confounding factors that may complicate our studies. First, the transgenic expression of human APP harboring an EOFAD mutation is under control of endogenous human regulatory elements, thus the spatial and temporal expression patterns encountered in the mouse recapitulate those observed in the human brain. In addition, the R1.40 transgene is maintained in a number of 160 inbred mouse genetic backgrounds by repeated backcrossing (Lehman et al., 2003a). Therefore, the R1.40 mouse model of AD represents a genetically defined and tractable model to study numerous AD phenotypes including ectopic neuronal cell cycle re-entry. Neuronal Cell Cycle Events and Alzheimer’s Disease Mouse Models An aberrant neuronal cell cycle is closely related to the neuronal degeneration encountered in specific populations within the AD brain (Vincent et al., 1996; McShea et al., 1997; Busser et al., 1998). Therefore, in chapter two we closely examined whether this phenotype was preserved in transgenic mouse models of AD. Even though the transgenic mouse models of AD do not exhibit significant neuronal cell loss we reasoned that they might exhibit neuronal CCEs, as these events occur early in the human disease and neurons can remain in this polyploidy state for an extended period of time (Yang et al., 2001; Yang et al., 2003). The AD mouse models examined differ with regard to the EOFAD mutation, promoter utilized as well as onset of Aβ deposition (Table 1.1). However, in the three different mouse models of AD examined, we encountered varying degrees of ectopic neuronal expression of cell cycle proteins as well as DNA synthesis by FISH, suggesting that neuronal CCEs were not unique to any one model of the disease (Yang et al., 2006). Remarkably, the genomic-based, R1.40 mouse model of AD exhibits neuronal CCEs in nearly all of the same neuronal populations that undergo neuronal cell death in the AD brain. For example, we routinely encountered 161 neuronal expression of numerous cell cycle antigens as well as evidence of DNA synthesis in neurons residing in the cortex and hippocampus (Figure 2.1 and Figure 2.2), noradrenergic nuclei (tyrosine hydroxylase-immunoreactive) of the locus ceruleus and serotoneric nuclei (tryptophan hydroxlyase-immunoreactive) of the dorsal raphe (Figure 2.5), neuronal populations that exhibit CCEs and cell death in the AD brain (Zweig et al., 1988; Chen et al., 2000a; Zarow et al., 2003). The specificity of the R1.40 model was confirmed by the absence of neuronal CCEs in the Purkinje cells and granule cells of the cerebellum as well as the neurons of the substantia nigra, cell types spared from degeneration in the AD brain (Figure 2.5). While all of the AD mouse models examined exhibit evidence of neuronal cell cycle re-entry, it should be noted that not all transgenic lines displayed the correct anatomical specificity encountered in the R1.40 animals. For example, in APPPS1-21 mice, designed using cDNA approaches and expressing mutant human APP and mutant PSEN1 (Radde et al., 2006), neuronal CCEs were routinely observed throughout the entire cortex as well as the striatum and neurons in the spinal cord (unpublished findings). This observation is in contrast to phenotypic specificity maintained in the R1.40 mice. These discrepancies are interesting for a number of reasons. First, we postulate that the disconnection between the APPPS-21 model and the R1.40 animals as well as human AD is attributed to the promoter utilized in the APPPS-21 model. The transgenes in the APPPS-21 mouse model are expressed off the Thy-1 promoter element, and therefore, exhibit robust expression mainly in post-mitotic neurons. Second, the 162 APPPS-21 mice begin to exhibit Aβ deposition, as well as other pathological hallmarks, as early as two months of age and in brain regions where no Aβ deposition is encountered in the R1.40 and, more importantly, in the human AD brain. Therefore, we conclude that the R1.40 mice more faithfully phenocopies the pathologies encountered in human AD in an age-dependent manner. The R1.40 animals represent a viable genetic model to identify the insults that induce neuronal CCEs in mouse models of AD and by extension the human condition. Aβ and Neuronal Cell Cycle Events in AD Mouse Models Numerous biochemical, genetic and neuropathological studies have provided strong evidence that the EOFAD forms of AD share common pathogenic mechanisms that involve alterations in Aβ metabolism. Detailed immunohistological examination of the natural history of the R1.40 mouse model of AD, maintained on the C57BL/6 inbred genetic background (B6-R1.40), indicates that neuronal cell cycle re-entry occurs at six months of age in frontal cortical layers II/III (Figure 3.1). This is six to eight months before fibrillar Aβ deposition in the B6-R1.40 animals, suggesting that Aβ deposits are not the trigger for neuronal CCEs. This conclusion is further supported by the observation that R1.40 animals maintained on the DBA/2 inbred genetic background (D2-R1.40) also exhibit neuronal CCEs (Figure 3.4); however, Aβ deposits are not encountered in D2-R1.40 animals even as late as 20 months of age (Lehman et al., 2003a). 163 In addition, our findings indicate that neuronal CCEs do not develop within all disease-relevant neuronal populations at once. Rather, specific neuronal populations initiate CCEs in an age-dependent manner. For example, in the B6R1.40 animals, neuronal CCEs are first observed in frontal cortical layers II/III at six months of age (Figure 3.1) and subsequently progress into deeper frontal cortical layers V/VI by 12 months of age (Figure 3.2). Our quantitative analyses indicate that once initiated neuronal CCEs are stable within a neuronal population (Figure 3.3). This finding, coupled with the absence of neuronal degeneration in the R1.40 mouse model of AD, indicates that neurons can survive in a polyploid state for many months after cell cycle re-entry. These findings are striking similar to studies in human AD (Yang et al., 2001) as well as MCI brain tissue (Yang et al., 2003), wherein neurons exhibiting mitotic entry are believed to survive for extended periods of time. Genetic experiments using the D2-R1.40 transgenic mice demonstrated that a reduction in steady-state levels of Aβ delay the onset of neuronal CCEs. The D2-R1.40 exhibit an ~25% reduction in levels of both Aβ1-40 and Aβ1-42 as early as 28 days of age when compared to B6-R1.40 mice (Lehman et al., 2003a). Importantly, the reduction in Aβ levels is not attributed to processing alterations as evidence by the absence of significant alterations in holo-APP expression or steady-state levels of APP C-terminal fragments (CTFs) when compared to B6-R1.40 mice. Interestingly, D2-R1.40 mice first exhibit neuronal CCEs at 12 months of age in frontal cortical layers II/III (Figure 3.4), suggesting that while delayed, the progression and anatomical specificity of the neuronal 164 CCEs is maintained in the D2-R1.40 mouse models of AD. In addition, these findings also suggest that accumulation of APP CTFs is the not the insult responsible for neuronal CCEs and implicates Aβ production in the induction of neuronal CCEs. Indeed, neuronal CCEs are completely absent in R1.40;Bace1-/mice aged to six months of age (Figure 3.5). Finally, to determine the role of soluble Aβ species on the induction of neuronal CCEs, we exposed primary neuronal cultures to our Aβ oligomer-rich and Aβ monomer-rich preparations (Figure 3.6). Importantly, our findings indicated that Aβ oligomers, and not monomers, were sufficient to induce neuronal BrdU incorporation in cultured cortical neurons (Figure 3.7). While our studies implicate Aβ generation in neuronal cell cycle re-entry it remains to be determined why specific neuronal populations exhibit CCEs in the R1.40 mouse model. Previous studies have determined that the R1.40 exhibits the highest levels of steady-state Aβ in the cerebellum and olfactory bulb, while lower levels are encountered in the cortex (Lehman et al., 2003b). These discrepancies suggest that cortical neurons are more susceptible to Aβ-mediated cell cycle re-entry and presumably cell death than other neuronal populations. Furthermore, we cannot rule out the possibility that subtle alterations in APP processing within specific neuronal populations occur in R1.40 animals. Finally, our in vitro studies suggest that small Aβ aggregates, termed Aβ oligomers, are sufficient to induce neuronal cell cycle re-entry in cultured cortical neurons. Therefore, it is possible that: 1) Aβ oligomers exhibit a greater propensity to form and persist in the frontal cortex as opposed to the cerebellum or olfactory bulb in 165 the R1.40 mouse model, or 2) cerebellar and olfactory neurons are immune to these cell cycle alterations mediated by Aβ oligomers. Thus, it would be extremely informative to expose cultured cerebellar granule cells to our Aβ oligomeric preparations to determine if cell cycle events are specific to cortical neurons or a general characteristic that applies to many neuronal cell types. Neuroinflammation and Neuronal Cell Cycle Events in AD Mouse Models Retrospective epidemiological studies indicate that chronic, long-term treatment with NSAIDs decrease the risk for developing AD, suggesting that neuroinflammation may play a pivotal role in early disease processes (in t' Veld et al., 2001; McGeer and McGeer, 2007; Vlad et al., 2008). However, prospective clinical trials with multiple different NSAIDs have failed to demonstrate significant behavioral improvements in individuals exhibiting cognitive impairments characteristic of AD (Martin et al., 2008). The discrepancies between these outcomes call into question the protective role of NSAIDs in AD pathogenesis. In chapter four we investigated the relationship between neuroinflammation and neuronal CCEs. Our studies indicated that the R1.40 mouse model of AD exhibits alterations in cortical microglia and neuronal CCEs at six months of age. Importantly, both the induction of neuronal CCEs (Figure 3.5) and microglial alterations (Figure 4.1) are dependent on Aβ generation because of their absence in in R1.40;Bace1-/- animals. This finding suggests that Aβ-mediated neuroinflammation may be the direct trigger for the induction of neuronal CCEs. 166 Indeed, young R1.40 animals subjected to a robust inflammatory challenge via LPS exhibit microglial activation and neuronal CCEs; however, only LPS injected R1.40 mice, and not non-transgenic controls or PBS injected R1.40 animals exhibited induction of ectopic neuronal CCEs (Figure 4.2). These data indicate that the induction of neuronal CCEs in the mouse models requires both neuroinflammatory processes and Aβ. Furthermore, our NSAID treatments provide valuable insights into the protective effects mediated by NSAIDs in human studies. First, a preventive NSAID treatment was protective against both alterations in cortical microglia (Figure 4.3) as well as neuronal CCEs (Figure 4.4). However, while therapeutic treatments were capable of inhibiting the progression of neuronal CCEs, the treatments failed to reverse extant neuronal CCEs (Figure 4.5). These observations provide an explanation for the discrepancies encountered in clinical drug trial. Efficacious NSAID treatments in human AD will require initiation at early stages of disease progression. These findings call into question two aspects of our original hypothesis, which stated that neuroinflammatory processes, initiated by soluble aggregates of Aβ, termed oligomers, induce neuronal CCEs in mouse models of the disease. First, our studies presented in chapter 3 provide compelling evidence that Aβ oligomeric preparations are sufficient, at least in vitro, to induce DNA synthesis in cultured neurons. These findings are strengthened by the observation that Aβ monomeric preparations were insufficient to induce neuronal CCEs and antibodymediated immunoneutralization of Aβ oligomers decreased the percentage of 167 neuronal CCEs. However, it remains to be determined if Aβ oligomers directly induce neuronal CCEs in vivo. Numerous groups have isolated Aβ oligomers from transgenic animals (Lesne et al., 2006; Oddo et al., 2006; Cheng et al., 2007); however, our attempts at isolating oligomeric species in the R1.40 have not been fruitful. Regardless of the downstream mechanisms, our findings definitely demonstrate that Aβ generation is necessary for neuronal cell cycle reentry in the R1.40 mouse model of AD because CCEs are blocked in the R1.40;Bace1-/- animals. Second, while LPS inducted neuroinflammation in both two-month old non-transgenic and R1.40 mice, neuronal CCEs were only encountered in the R1.40 animals. Therefore, the induction of neuroinflammation was not by itself sufficient to induce neuronal cell cycle re-entry, and it remains possible that the induction of neuronal cell cycle re-entry is dependent on both Aβ oligomers and activation of inflammatory processes. While the reasons for these conclusions are unresolved, it is important to note that elevated levels of Aβ are encountered in the R1.40 mouse as early as 28 days of age. Therefore, increases levels of Aβ or perhaps Aβ monomers may “prime” microglia to develop the capacity to induce CCEs, either with age or an environmental stress such as LPS. Alternatively, it may not be Aβ that is the “priming” factor. We cannot rule out that overexpression of mutant human APP is responsible for a “priming” effect and not Aβ. Therefore, a revealing experiment would be to expose R1.40;Bace1-/- and appropriate controls to LPS. If Aβ is the insult necessary for neuronal CCEs after LPS injection, then the LPS-injected R1.40;Bace1-/- animals 168 will not exhibit neuronal cell cycle re-entry; however, LPS-injected R1.40 animals will continue to exhibit neuronal CCEs. Future Directions The findings presented in this dissertation furthers our understanding of the biology of ectopic neuronal cell cycle re-entry in mouse models of AD and provides a mechanistic explanation for neuronal cell cycle re-entry in human AD. Moreover, our studies indicate that neuronal CCEs are a viable biomarker to ascertain the efficacy of a number of therapeutic interventions. Despite the strengths of this thesis work, there remain a number of outstanding questions surrounding the impact of neuronal CCEs on AD disease progression that can be addressed using the R1.40 mouse model of AD as well as other model systems. First, while the application of FISH indicates that DNA synthesis has indeed occurred in the human AD brain and the mouse models, it would be beneficial to have an additional independent outcome measure of DNA synthesis. For these studies, bromodeoxyuridine (BrdU) could be utilized to mark neurons undergoing DNA synthesis. It should be noted that we have attempted to label dividing cells with BrdU; however, despite our repeated attempts, we did not encounter any BrdU-labeled neurons. The absence of BrdU incorporation may be a subject of concern to our model. However, it should be noted that the induction of neuronal CCEs in a neuronal population seems to take place in a short time frame, as evidence by the lack of neuronal CCEs in R1.40 animals aged to four months of age and nearly ~40% of neurons exhibiting 169 CCEs at six months of age. Therefore, our BrdU injections may be ill timed and thus miss the substantial induction in neuronal cell cycle re-entry. To circumvent these timing issues it would be beneficial to expose the R1.40 animals to BrdU in their drinking water as this approach has been used successfully in previous studies to mark DNA synthesis in mature, post-mitotic neurons (Andorfer et al., 2005). This technique would allow continual exposure of the DNA analogue to the animals and hopefully result in BrdU-labeled neurons in the R1.40 mice. Our temporal and spatial characterization of neuronal CCEs in the R1.40 animals indicated that these events occur between four and six months of age. Therefore, R1.40 and aged-matched non-transgenic controls as well as R1.40;Bace1-/- could be subject to drinking water containing BrdU for two months beginning at four months of age. Second, studies in human AD as well as the described findings in the R1.40 mouse model provide substantial evidence that neuronal CCEs mark neuronal populations at-risk for death in the AD brain. However, it remains to be determined if these mitotic alterations are detrimental for neuronal function. Previous studies have determined the R1.40 mice begin to exhibit deficits in a battery of behavioral tests at 17 months of age when Aβ deposition is robust in the R1.40 mouse model (unpublished results). In addition to the R1.40 animals, numerous behavioral studies have been employed in other mouse models of AD to examine the effects of AD-like pathologies on specific attributes of learning and memory (King et al., 1999; Chen et al., 2000b; Kukar et al., 2007; Kotilinek et al., 2008). Therefore, to test if neuronal cell cycle re-entry is sufficient to induce 170 memory impairments it would be advantageous to subject six-month old R1.40 mice as well as age- and gender-matched control animals to a systems level behavioral analysis. We want to gain an appreciation for the R1.40 animals’ ability to utilize working memory by examining spontaneous alteration in the Y-maze. For these analyses we would begin our studies using animals aged to six months of age, as at this time point we encounter a robust induction of neuronal cell cycle reentry in frontal cortical layers II/III. These studies will be performed as described (King et al., 1999). Transgenic R1.40 animals, maintained on the C57BL/6 genetic background, and age- and gender-matched non-transgenic controls will be placed in one of the three arms of the maze and allowed free exploration of the Y-maze for a total of five minutes. Spontaneous alteration (SA) will be expressed as a percentage and calculated by dividing the number of arms entered that differ from the previous two by the total number of arms entered. In addition to SA, we will also determine the average total arms entered for each genotype to ensure the differences in SA are not attributed to alterations in overall activity. Our expectation is that six-month R1.40 animals will exhibit reductions in SA when compared to age-matched non-transgenic controls. This outcome would indicate a temporal correlation between working memory deficits and neuronal CCEs. Importantly, if deficits in SA persist in six-month old R1.40 animals it will be important to perform the same behavioral testing on animals aged to four months of age. The expectation is that if the induction of neuronal 171 CCEs is indeed causative for working memory behavioral deficits, then animals aged to four months of age will not exhibit memory impairments, as we encounter little evidence of neuronal cell cycle re-entry in R1.40 animals aged to four months of age. It is worth noting that a tight temporal correlation between the induction of neuronal CCEs and deficits in working memory in R1.40 animals can be interpreted as a cause and effect relationship between these two outcome measures, but it would not be proof. A recent report suggests that behavioral impairments are indeed encountered in other mouse models of AD at about six months of age. These studies also provide intriguing data suggesting that these impairments are a direct result of Aβ oligomers interfering with synaptic function (Lesne et al., 2006). In addition, our in vitro data described in chapter 3 indicates that Aβ oligomers, and not Aβ monomers, are sufficient to induce cell cycle reentry in cultured cortical neurons (Varvel et al., 2008). While it is conceivable that behavioral impairments in AD mouse models are a result of both synaptic interference and neuronal CCEs, it is also possible that Aβ oligomers can be inducing neuronal CCEs and memory impairments in two completely independent pathways. Third, this dissertation provides compelling evidence that neuronal CCEs are dependent on both Aβ as well as inflammatory processes. First, induction of neuroinflammation with a robust stimulus, LPS, resulted in microglial activation in young R1.40 transgenic animals as well as non-transgenic controls. However, neuronal CCEs were only encountered in the R1.40 and not in the non- 172 transgenic controls. Additionally, two commonly used NSAIDs were capable of inhibiting the induction of neuronal cell cycle re-entry. This protective effect was encountered in the absence in alterations in holo-APP expression, APP processing and steady-state Aβ levels. Therefore, it would be interesting to specifically target Aβ in a therapeutic paradigm and ascertain the response by observing by determining the extent of neuronal CCEs. Numerous studies have indicated that passive immunization with anti-Aβ antibodies clears preformed Aβ deposits (Bard et al., 2000; Bacskai et al., 2001) and substantially decreases brain Aβ levels (DeMattos et al., 2001). Interestingly, rapid removal of Aβ deposition with anti-Aβ antibodies was also encountered when the antibodies were applied directly to the exposed cortical surface. Furthermore, Aβ removal was only encountered in the area around antibody application in as little as four days after antibody application, suggesting the effects of this focal treatment was limited to a small area of the cortex (Bacskai et al., 2001). This therapeutic approach could also be utilized to determine the response of CCEs to reductions in Aβ levels. Our studies indicate that the induction of neuronal CCEs is also limited to a defined population of neurons near the surface of the brain in frontal cortical layers II/III at six months of age. Therefore, six-month old R1.40 animals can be subject to an application of anti-Aβ antibodies in the frontal cortex. To begin these studies, the animals will be anesthetized with 4% isoflurane; the skin and periosteum will be removed to expose the skull. After removal of the skull, the antibody 10D5 (Bacskai et al., 2001), specific for Aβ, will 173 be applied (10 µl of a 2 mg/ml solution) to the frontal cortex. In addition to antibody 10D5, we will also apply an unrelated antibody specific for human microtubule-associated protein tau as a control in our assays. After four days we will sacrifice the animals and perform immunohistochemical analysis to determine the extent of neuronal CCEs. Importantly, we are interested in determining if we can reverse the extant CCEs once they have occurred because we will have focally removed Aβ away from the microenvironment of “cycling” neurons. Fourth, one important aspect of my original hypothesis that was not directly tested was the ability of Aβ oligomers to activate microglia. Previous studies have characterized a cell surface receptor complex that mediates the binding of microglia to Aβ fibrils and subsequent activation of intracellular signaling pathways leading to a proinflammatory responses (Bamberger et al., 2003). However, it is unknown whether this complex also recognizes Aβ oligomers. To directly test if Aβ oligomers can activate microglia, we will expose primary microglia to our Aβ oligomer-rich and monomer-rich preparations (Figure 3.6). Primary microglial cultures will be obtained from postnatal day 1 to 3 mouse pup brain as described (Saura et al., 2003). We will then expose the microglial cultures to the preparations of oligomers and monomers. Similar to the neuronal experiments in described in chapter 3, we will first expose the cells at a concentration of 100 nM, as neuronal CCEs were encountered in this range. After 24 hours of exposure we will fix and stain the cells for Iba1 and lectin. We 174 will be interested in the morphology of the microglia may be altered after exposure to the Aβ oligomer-rich preparation. We anticipate that the cells will exhibit an activated morphology with shorted, thickened processes when compared to microglia subject to the monomer-rich preparation. Also, antibodies for activation markers, such for CD45 and Mac1, will be utilized to gain an appreciation of the levels of activation between the oligomer-rich and monomerrich preparation. Finally, our findings directly implicate neuroinflammatory processes in the induction of neuronal CCEs. Immunohistochemical profiles of six-month old R1.40 animals indicate that alterations in brain microglia occur coincidently with neuronal cell cycle re-entry, suggesting that inflammatory responses may be the trigger for neuronal CCEs. In addition, a three month exposure to either ibuprofen or naproxen diminishes microglial alterations as well as neuronal CCEs. Therefore, characterization of this inflammatory response will be critical for determining the inflammatory factor or factors inducing neuronal CCEs. One of the most sensitive measurements of increased expression of inflammatory molecules in young mouse models of AD is quantitative RT-PCR (Janelsins et al., 2005). Our characterization of neuronal CCEs in indicates that alterations in brain microglia are robust when the R1.40 animals are six month of age. Therefore, we will focus on six-month old R1.40 animals and age-matched non-transgenic controls for these studies. For analysis of various transcript levels, hemi-brains from six animals (three of each sex) from each genotype at the six month time point will be used to obtain brain total RNA and further purified 175 using RNeasy spin columns. Established, highly efficient TaqMan assays will be performed for transcript levels of pro- and anti-inflammatory molecules by comparing the experimental samples (R1.40 animals) to reference samples (nontransgenic controls). Samples will be analyzed and quantified relative to mouse housekeeping controls (18S rRNA and Gapdh) on an ABI Prism 7300 Sequence Detection System. For these studies we will initially focus on Tnfα and Il-1β, because they have been demonstrated to be increased in young mouse models of AD (Janelsins et al., 2005) and have been implicated in microglial-mediated neuronal death (Combs et al., 2001) (Cardona et al., 2006b). Quantitative RT-PCR is one of the most sensitive measures for identifying increased expression of inflammatory molecules. However, while our data indicates robust alterations in brain microglia, isolation of RNA from the whole brain may dilute the strong response elicited by the microglial cells. Therefore, we can also utilize Percoll gradients to purify microglial cells as described (Cardona et al., 2006a). After an enriched microglial cell population has been obtained, RNA can be directly isolated and analyzed for various inflammatory molecules. These methods will undoubtedly identify a number of inflammatory molecules that exhibit expression changes in the six-month old R1.40 animals when compared to aged-matched non-transgenic controls. However, these studies, while informative, will still only provide correlative data pertaining to the interactions between microglial cells and the induction of neuronal CCEs. Our data indicates that alterations in brain microglia are coincident with neuronal 176 CCEs, but we cannot rule out other cells types, such as astrocytes, may also be involved. Astrocytes are generally encountered near Aβ deposits in human and mouse brain. In addition, astrocytes may also participate in the phagocytosis of Aβ, either directly (Shaffer et al., 1995) or by regulating microglial activities (DeWitt et al., 1998). Therefore, it will be important to determine if microgliamediated inflammatory responses induce neuronal CCEs cell-autonomously. To begin these experiments we will identify six-month old R1.40;Cx3cr1+/gfp transgenic animals as well as age-matched non-transgenic Cx3cr1+/gfp mice. Again, we will isolate microglia from using the Percoll gradients and subsequently further purify the microglial cells by flow cytometry using the GFP reporter. The GFP+ microglial cells obtain from either transgenic R1.40 or non-transgenic mice will be injected into the frontal cortex of naïve six month old C57BL/6 mice using a 25-gauge needle. We will also include a mockinjected control. 36-48 hours after injection, brains will be removed and characterized for the presence of neuronal cell cycle re-events, focusing on sections at the level of the injection site as well as sections on either side of the injection site. A number of possible outcomes are certainly expected after these experiments. We expect that microglia obtained from six-month old R1.40 animals will be sufficient to induce neuronal CCEs in naïve C57BL/6 animals, while microglial cells obtained from non-transgenic mice will not be able to induce neuronal cell cycle re-entry. This outcome would suggest that microglia indeed act in a cell-autonomous fashion to induce neuronal CCEs. Importantly, this 177 would also indicate that the environment created by the R1.40 transgene, or more likely, elevated Aβ levels, primes microglia to induce these neuronal mitotic events. However, it is also possible that neuronal CCEs will not be observed in naïve C57BL/6 recipient mice regardless of the genotype of the donor animals. Therefore, it will be necessary to use R1.40 animals as the recipient of the microglia, as these animals will exhibit elevated levels of Aβ. While, it may be impossible to predict the outcome of these studies, we would anticipate that these experiments will provide additional insights into the biology surrounding neuroinflammation, Aβ and neuronal CCEs. Conclusion The findings reported in this dissertation highlight the complex relationship between the neuropathologies encountered in Alzheimer’s disease. In addition, these studies contribute substantial insights into insults that induce neuronal CCEs in AD mouse models and by extension the human disease. Our genetic studies provided compelling evidence that reductions in Aβ levels significantly delay the onset of neuronal CCEs. Furthermore, the importance of Aβ was confirmed by the absence of neuronal cell cycle re-entry in R1.40;Bace1-/animals. Finally, Aβ oligomers, and not monomers, induced neuronal CCEs in cultured cortical neurons. In addition, this dissertation work also provided evidence that neuroinflammation may mediate a pivotal role in early disease processes. Chronic administration of two commonly used NSAIDs prevented the induction of neuronal CCEs in young R1.40 mice. However, once initiated, 178 NSAID treatments were incapable of reversing extant CCEs, suggesting that efficacious AD therapies must be initiated early in the disease process. 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