Documents
Resources
Learning Center
Upload
Plans & pricing Sign in
Sign Out

ON THE ONTOLOGY OF DISEASE

VIEWS: 89 PAGES: 60

									                          ON THE ONTOLOGY OF DISEASE: part II




The Philosophy of Biology: Structure, Function, Evolution


Louis J. Goldberg
University at Buffalo
October 28, 2006



                                                                1
                    the complexity dilemma




mechanistic explanations cannot deal with the ever unfolding distributed
complexity of biological reality




                                                                       2
                    complexity equivalence



all levels of organization follow the same structural pattern in
biological networks (Song et al, 2005).



the base level has equivalent complexity to the level from which it
emerges, and the level which will emerge above




                                                                      3
                  networks
                     and

emergence

hierarchy

granularity

complexity

adaptability

the OBO Foundry

disease
                             4
the OBO foundry and the formation of a
       new network in biology




                                         5
biomedical theories of disease

          humoral


         miasmatic


            germ


         mechanistic


             ??
                                 6
            the humoral theory of disease



• biological basis: there are four bodily fluids, or humors;
  blood, phlegm, yellow bile, and black bile


• definition of disease: imbalance among the humors causes
  disease




                                                               7
            the miasmatic theory of disease


miasma: a poisonous vapor or mist filled with particles from
decomposed matter (miasmata)


disease: breathing miasma causes disease



be clean and avoid putrescence


                                                               8
                 the germ theory of disease
                   the modern era begins

biological basis: microorganisms exist in nature



definition of disease: microorganisms invade human bodies
and are the direct cause of infectious diseases




replaces the humoral and miasmatic theories of disease


                                                            9
       Year            Disease            Organism            Discoverer
1877               Anthrax            Bacillus anthra cis   Koch, R.
1878               Suppuration        Staphylococcus        Koch, R.
                                      Neisseria
1879               Gonorrhea                                Neisser, A.L.S.
                                      gonorrhoeae
1880               Typhoid fever      Salmo nella typhi     Eberth, C.J.
1881               Suppuration        Streptococcus         Ogston, A.
1882               Tuberculosis       Mycobacterium         Koch, R.
                                      tuberculosis
1883               Cholera            Vibrio cholerae       Koch, R.
1883               Diphthe ria        Corynebacterium       Klebs,T.A.E.
                                      diphthe riae          Loeffler, F.
1884               Tetanus            Clostridium tetani    Nicholaier, A.
1885               Diarrhea           Escherichia coli      Escherich, T.
                                      Streptococcus
1886               Pneumo nia         pneumo niae           Fraenkel, A.
                                      Neisseria             Weischselbaum,
1887               Meningitis
                                      meningitidis          A.
                                      Salmo nella
1888               Food poisoning                           Gaertner,A.A.H.
                                      enteritidis
1892               Gas gangrene       Clostridium           Welch, W.H.
                                      perfringens
                                                            Kitasato, S.,
1894               Plague             Yersinia pestis       Yersin, A.J.E.
                                      Clostridium           van Ermenge m,
1896               Botulism           botulinum             E.M.P.
1898               Dysentery          Shigella              Shiga, K.
                                      dysenteriae
1900               Paratyphoid        Salmo nella           Schottmuller, H.
                                      paratyphi
                                      Treponema              Schaudinn, F.R.,
1903               Syphilis
                                      pallidum              and Hoffmann, E.
                                                             Bordet, J., and
 1906              Whooping cough Bordtella pertussis Gengo u, O.
Table 4. The discoverers of the main bacterial pathoge ns. From Brock (1988), p.   10
290.
    modern biomedicine



the mechanistic theory of disease




                                    11
 in what do working biomedical scientists believe?
        is there a philosophy of biomedicine?

biomedical scientists believe:

       in cells and the cell doctrine




                                                     12
                        the cell doctrine
    (proposed in 1838 by Matthias Schleiden and by Theodor Schwann)


• cells are the fundamental structural and functional units of
  all organisms
•   all organisms are composed of one or more cells
• all cells come from preexisting cells
• all vital functions of an organism occur within cells
• cells contain the hereditary information necessary for
  regulating cell functions and for transmitting information
  to the next generation of cells


                                                                      13
 in what do working biomedical scientists believe?
       is there a philosophy of biomedicine?

biomedical scientists believe:

     in cells and the cell doctrine


    in mechanistic (scientific) explanations of intracellular
    function that are based on biochemical/molecular dynamics



    that functions and malfunctions at the organism level can
    be explained by biochemical dynamics at the
    cellular/molecular level
                                                           14
                  traditional biomedicine

 is thoroughly mechanism focused



is dominated by notions of molecular causality



molecular mechanisms (operations) at the biochemical
level lead “upward” to the understanding of health and
disease at the organism level


                                                         15
the complexity dilemma




                         16
                          restlessness in biomedicine

   “During the last fifty years the dominant stance in experimental
   biology has been reductionism.”


   “For the most part, research programs were based on the notion
   that genes were in 'the driver's seat' controlling the
   developmental program and determining normalcy and disease
   (genetic reductionism and genetic determinism).”


   “The optimism of molecular biologists, fueled by early success in
   tackling relatively simple problems, has now been tempered by
   the difficulties found when attempting to understand complex
   biological problems.”

Soto AM, Sonnenschein C. J Biosci 2005 Feb:30(1):103-18 Emergentism as a default: cancer as a problem
of tissue organization.                                                                                 17
                  the limitations of molecular mechanistic
                                explanations


     “Although molecular biology offers many spectacular
     successes, it is clear that the detailed inventory of genes,
     proteins, and metabolites is not sufficient to understand the
     cell's complexity.”




Zoltan and Barabasi, Systems biology: life’s complexity pyramid. Science (2002) 298: 763-764.
                                                                                                18
    a current trend in biomedical research


mechanistic biochemical explanation recedes into the
background



the foreground becomes occupied by newly discovered
components involved in unsuspected operations




                                                       19
MOVEMENT IN BIOMEDICINE TOWARDS A NEW
  PERSPECTIVE ON HEALTH AND DISEASE




                                        20
studies of mechanisms and mechanistic explanations at the
molecular level continue



a new omic entity comes into being




network theory is applied to the biomedical domain



                                                            21
                                         the omic entity

   out of the interactions of countless instances of particular types there
   emerges a larger entity that acts as a community of instances which
   forms new types at a “higher” level of organization




   “information storage and processing, and the execution of cell
   programs, is related to the distinct levels of omic organization, and
   not to the operations of biochemical pathways”




Zoltan and Barabasi, Systems biology: life’s complexity pyramid. Science (2002) 298: 763-764   22
                omic levels of organization

   ome                component parts            discipline

genome                    DNA                 genomics

transcriptome             RNA                 transcriptomics

proteome                  proteins            proteomics

metabolome                metabolites         metabolomics

microbiome                microorganisms      metagenomics

                                                         23
                                                                                                G

                                                                                                T

                                                                                                P




     this is foundational for all cells: eubacteria, prokaryotes, free-living
     eukaryotes and eukaryotes in metazoa


                                                                                                    24
Zoltan and Barabasi, Systems biology: life’s complexity pyramid. Science (2002) 298: 763-764.
    what does omic thinking add to biomedicine?

it moves from a one-at-a-time mechanistic, test tube view of
molecular chemistry, to a population view


it conceives of the type, genome, interacting with the type,
transcriptome, to produce the type, proteome



the interactome: the entire set of all omic level components
and operations of the cell


                                                               25
                         beyond omics: the network


  “…the distinctness of these (the omic) organizational
  levels has recently come under fire.”



   “…viewing the cell as a network of genes and proteins
   offers a viable strategy for addressing the complexity of
   living systems.”




Zoltan and Barabasi, Systems biology: life’s complexity pyramid. Science (2002) 298: 763-764.   26
                              intracellular organization


 “There is remarkable integration of the various layers both at
 the regulatory and the structural level. Insights into the logic
 of cellular organization can be achieved when we view the cell
 as a complex network in which the components are connected
 by functional links.”




Zoltan and Barabasi, Systems biology: life’s complexity pyramid. Science (2002) 298: 763-764.   27
NETWORKS IN BIOMEDICINE




                          28
  map of the C. elegans interaction network, or "interactome," links
  2,898 proteins (nodes) by 5,460 interactions (edges




                                                                                                     29
Li, S. A Map of the Interactome Network of the Metazoan C. elegans. Science (2004) 303: 540 - 543.
A Map of the Interactome Network of the Metazoan C. elegans. Science
(2004) 303: 540 - 543.



Li,1* Christopher M. Armstrong,1* Nicolas Bertin,1* Hui Ge,1* Stuart
Milstein,1* Mike Boxem,1* Pierre-Olivier Vidalain,1* Jing-Dong J. Han,1*
Alban Chesneau,1,2* Tong Hao,1 Debra S. Goldberg,3 Ning Li,1 Monica
Martinez,1 Jean-Fran腔is Rual,1,4 Philippe Lamesch,1,4 Lai Xu,5
Muneesh Tewari,1 Sharyl L. Wong,3 Lan V. Zhang,3 Gabriel F. Berriz,3
Laurent Jacotot,1 Philippe Vaglio,1 J Reboul,1 Tomoko Hirozane-
Kishikawa,1 Qianru Li,1 Harrison W. Gabel,1 Ahmed Elewa,1|| Bridget
Baumgartner,5 Debra J. Rose,6 Haiyuan Yu,7 Stephanie Bosak,8
Reynaldo Sequerra,8 Andrew Fraser,9 Susan E. Mango,10 William M.
Saxton,6 Susan Strome,6 Sander van den Heuvel,11 Fabio Piano,12 Jean
Vandenhaute,4 Claude Sardet,2 Mark Gerstein,7 Lynn Doucette-
Stamm,8 Kristin C. Gunsalus,12 J. Wade Harper,5 Michael E. Cusick,1
Frederick P. Roth,3 David E. Hill,1ヲ Marc Vidal1ヲ#



                                                                       30
      Graphical representation of a highly interconnected subnetwork




                                                                                                     31
Li, S. A Map of the Interactome Network of the Metazoan C. elegans. Science (2004) 303: 540 - 543.
         TWO EXAMPLES OF RECENT RESEARCH STUDIES
              EXEMPLIFYING THE NEW APPROACH:
        GOING FROM MOLECULES TO CELLS TO ORGANISMS



Sporns, O., Chialvo, D. R., Kaiser, M. and Hilgetag, C. C. (2004)
Organization, development and function of complex brain networks,
Trends Cogn Sci, 8, 418-25



Andrew J Pocklington, Mark Cumiskey, J Douglas Armstrong and Seth G N
Grant, (2006) The proteomes of neurotransmitter receptor complexes form
modular networks with distributed functionality underlying plasticity and
behaviour, Molecular Systems Biology 2. Published online: 17 January
2006
Article number: 2006.0023



                                                                      32
                             the universal nature of networks


    the general principles in the structural and functional
    organization of complex networks are shared by various
    natural, social and technological systems


    the interaction of architecture (the network's connection
    topology) and dynamics (the behavior of the individual
    network nodes), gives rise to global states [new continuants]
    and „emergent’ behaviors [new occurrents].”


Sporns, O., Chialvo, D. R., Kaiser, M. and Hilgetag, C. C. (2004) Organization, development and function of complex brain
networks, Trends Cogn Sci, 8, 418-25                                                                                        33
                                general network characteristics


      networks are sets of nodes linked by connections


     In many networks, clusters of nodes segregate into tightly coupled
     neighborhoods, but maintain very short DISTANCES among nodes across
     the entire network, giving rise to a small world within the network.


     The degree to which individual nodes are connected forms a distribution
     that, for many but not all networks, decays as a power law, producing a
     SCALE-FREE architecture characterized by the existence of highly
     connected nodes (hubs).



Sporns, O., Chialvo, D. R., Kaiser, M. and Hilgetag, C. C. (2004) Trends Cogn Sci, 8, 418-25.
                                                                                                34
is a physics-biology link on the horizon?




                                            35
                          Sporn asks


what is the structural substrate of neuroanatomy and how
does it relate to the more dynamic functional and effective
connectivity patterns that underlie human cognition?




Sporn believes that “network analysis offers new fundamental
insights into global and integrative aspects of brain function,
including the origin of flexible and coherent cognitive states
within the neural architecture.”                                  36
  Small-world and scale-free structural and functional brain networks.




                                                                                               37
Sporns, O., Chialvo, D. R., Kaiser, M. and Hilgetag, C. C. (2004) Trends Cogn Sci, 8, 418-25
          POSTSYNAPTIC DENSITY (PSD)


post synaptic density-electron dense cytoskeletal specialization located on
the post synaptic membrane at the site of synaptic contact.




                                                                        38
                               TEXTBOOK VIEW OF SYNAPSE




                                                          39
Nolte, Human Brain, Fig. 8.4
Ziff, Trends Neurosci. 2002 May;25(5):251.   40
                            the PSD

macromolecular complexes of neurotransmitter receptors

comprised of over 1000 proteins


perhaps the most complex molecular structures known in
mammals


proteins in these structures participate in information
processing in the brain, and also play roles in disease



                                                          41
                                 The Pocklington study

    determine the organization and function of the mammalian
    neurotransmitter receptor complex N-methyl-d-aspartate (NRC/MASC)
    using a systems biology approach.


    a) use synapse proteomic data to present a detailed analysis of the MASC
    complex using annotation, network and statistical approaches.


    b) develop a model to explain the structural and functional aspects of
    synapse molecular complexity




Pocklington et al., The proteomes of neurotransmitter receptor complexes form modular networks with
distributed functionality underlying plasticit an behaviour, Molecular Systems Biology 2. Published
                                                                                                    42
online: 17 January 2006
Article number: 2006.0023
                                                                                                                   reductionist
                                                                                                                     methods




                                                                                                              bioinformatics/
                                                                                                                 ontology




                                                                                                               graph theory
                                                                                                               and network
                                                                                                                 analysis




Fig. 1 Pocklington et al., The proteomes of neurotransmitter receptor complexes form modular networks with                 43
distributed functionality underlying plasticity and behaviour, Molecular Systems Biology 2. Published online: 17
January 2006
Article number: 2006.0023
               Modular structure and functional organization of the MASC
                       (N-methyl-d-aspartate receptor complex)
                                                                                               •    proteins are clustered
                                                                                                    into modules
                                                                                               •    individual modules play
                                                                                                    multiple functional roles
                                                                                               •    this permits distribution of
                                                                                                    information processing and
                                                                                                    regulation of effector
                                                                                                    pathways over multiple
                                                                                                    modules
                                                                                               •    there is a dynamical
                                                                                                    balance between multiple
                                                                                                    functional processes
                                                                                               •    synchronization of multiple
                                                                                                    cell-biological processes
                                                                                                    induces synaptic plasticity
                                                                                                    that is
                                                                                               •    manifested at a higher
                                                                                                    levels of neurological
                                                                                                    function through
                                                                                                    behavioural learning




Fig. 5 Pocklington et al., The proteomes of neurotransmitter receptor complexes form modular networks with
distributed functionality underlying plasticity and behaviour, Molecular Systems Biology 2. Published online: 17
                                                                                                                     44
January 2006
Article number: 2006.0023
Network cluster analysis. Clustering of the largest connected component of the
                   MASC network identified 13 clusters.




               50% of its proteins are essential to normal synaptic plasticity;
                 40% are implicated in schizophrenia; cognitive function




                               assimilates signals; co-ordinates
                                common effector mechanisms




                                                                                  45
                                             46
Ziff, Trends Neurosci. 2002 May;25(5):251.
                                             47
Ziff, Trends Neurosci. 2002 May;25(5):251.
                  HIPPOCAMPUS




                                48
Nolte Fig 32-15
                the behavioral level



cognitive processes




                                       49
            what makes biological complexity work?

high quality components (atoms and molecules)

formal language (physical chemistry)

common architecture (physical rules of network assembly)

stability of macro-assemblies (network physics)

because of the above, networks can stack (platform stability)

is there semantic interoperability in biological networks? a) at
a single level: the GTP? b) between levels: PSD and behavior?

                                                                   50
                 weakness in biological complexity?


network multiplication: large systems (the human organism) are composed
of multiple, semi-independent networks


it becomes difficult to maintain the coordination of marginally connected
networks (e.g. metagenomics: the interface between the microbial genome
and the organism‟s cell genome)


destructive competition between networks can occur




                                                                            51
                    the OBO foundry


a family of interoperable gold standard biomedical reference
ontologies to serve the annotation of inter alia
      scientific literature
      model organism databases
      clinical trial data




                                                               52
                       THE OBO FOUNDRY

undergoing reform
Gene Ontology (GO)
Chemical Ontology (ChEBI)
Cell Ontology (CL)
Foundational Model of Anatomy (FMA)
Phenotype Quality Ontology (PaTO)
Sequence Ontology (SO)

new
Common Anatomy Reference Ontology (CARO)
Clinical Trial Ontology (CTO)
Functional Genomics Investigation Ontology (FuGO)
Protein Ontology (PrO)
RNA Ontology (RnaO)
Relation Ontology (RO )

under consideration
disease ontology (DO)
biomedical image ontology (BIO)
upper biomedical ontology (OBO UBO)
environmental ontology (EnvO)
systems biology ontology (SBO)

                                                    53
                                 criteria
a common formal language


for any particular domain, there is community convergence on a single
controlled vocabulary.


the ontology has a clearly specified and clearly delineated content


common architecture: The ontology uses relations which are unambiguously
defined following the pattern of definitions laid down in the OBO Relation
Ontology


the developers of each ontology commit to its maintenance in light of
scientific advance: annotation
                                                                        54
                      disease ontology (DO)

does not belong in the OBO foundry

we do not now have a unified theory of disease

there can only be the category, ontologies of disease, under which are
listed the ontologies of specific diseases (e.g. multiple sclerosis MSO)


if the OBO foundry is constructed properly, then, as our understanding of
disease changes, old names can disappear (in ten years, there may not be a
disease we call MS) and new ones appear

permitting the foundry to persist


                                                                           55
    the structural organization of ontologies in the foundry


is nonexistent


which makes it all the more crucial that the criteria be met



the boundaries between ontologies will reconfigure (self-assemble) as our
understanding of biology changes




                                                                        56
tracking emerging organization and information flows within
                 the network of ontologies


will they conform to the principles of organization and function found in other
complex structures?




will we be able to identify nodes, modules, networks, etc?




                                                                         57
               complexity and the OBO foundry



is it appropriate to think of the suite of interoperable biomedical
ontologies currently being forged in the OBO foundry as an evolving
network?



will the network “give rise to global states and „emergent‟ behaviors” the
nature of which are unpredictable?




                                                                         58
               formation of a new network

will creation of massively interoperable biomedical ontologies that are
semantically interoperable with human minds be the equivalent of the
creation of a new network in nature not unlike those that currently
exist in biological organisms?


is semantic interoperability to be found in the interaction of the
human cognitive network with the computer-based foundry
network which it is constructing?


will the network “give rise to global states and „emergent‟
behaviors” the nature of which are unpredictable?


                                                                      59
                            human understanding
                                                     semantic interoperability


 biological reality                                Foundry network

                                                  computer systems

 biomedical science                                     ontology

biochemistry                                                   network analysis


           primary scientific lit                 annotation




                                                                            60

								
To top