Genetic Epidemiology - Science & Public Policy by SupremeLord

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									Genetic Epidemiology: The Interface
between Science and Public Policy

            Kathleen Ries Merikangas, Ph.D.

   Chief, Section on Developmental Genetic Epidemiology,
                Intramural Research Program
              National Institute of Mental Health
Epidemiology is more than counting
               The Epidemiologic Triangle
                     Age, Sex, Race, Religion, Customs,
                     Occupation, Genetic profile, Marital
                       status, Family background, Prior
                           diseases, Immune status


Environment                                                   Agent

 Temperature, Humidity, Altitude,             Biologic (bacteria, viruses),
Crowding, Housing, Neighborhood,           Chemical (poison, alcohol, smoke),
   Water, Milk, Food, Radiation,            Physical (trauma, radiation, fire),
       Noise, Air pollution                    Nutritional (lack, excess)
Taubes, G., Science, 169:164-169, 1995
Family history is an independent risk
factor for most chronic diseases of
public health significance
            Mendelian Disorders

 The gene loci are now known for nearly all of
  the Mendelian Disorders
 N of Mendelian disorders:
   40 cancer syndromes
   50 cardiovascular diseases
   29 diabetes subtypes
                                 Scheuner et al, 2004
Complex Disorders
     Status of Gene Identification for
           Complex Diseases

 Identification of genes for complex
  diseases has not been highly
  successful to date
 Most disease genes that have been
  identified are rare with high absolute
  risk but low population attributable risk
Complex patterns of disease transmission


Genetic Epidemiology
         Genetic Epidemiology

 to examine the distribution, risk factors
  & the inherited causes of disease, either
  through genes or culture, in groups of
 to identify the etiology of a disease and
  thereby prevent or intervene in the
  progression of the disorder
Application of Genetic Epidemiologic
           Study Designs

 to identify the mode of transmission
 to identify most heritable phenotypes
 to detect gene - environment interaction
   to establish population base rates of
    disease and genetic markers
Summary: Risk Ratios for Complex Disorders

                          Risk Ratios
Disorder           1 relative > 2 relatives
Asthma                2.3              3.9
Alzheimer’s (< 50)    2.8              4.3
  Breast              2.1              3.9
  Colorectal          1.7              4.9
  Prostate            3.2             11.0
Cardiovascular       2.0             3.4
Diabetes II          2.4             -----
                                             Yoon et al, 2002
The decrement in concordance rates between MZ
 and DZ twins is significantly different from 50%
           for most mental disorders

      Disorder                MZ     DZ
      Autism                  .60    .05
      Bipolar Disorder        .63    .12
      Schizophrenia           .58    .08
      Substance Abuse         .60    .40
      Tourette Syndrome       .53    .08
    BRCA Mutations & Breast Cancer

Family Group      N    BRCA1   BRCA2      Other
No Males         211    .55     .26        .19
Male Breast       26    .16     .76        .08
Breast/Ovarian    94    .81     .14        .05
Female Breast    117    .26     .32        .42

All Families     223    .52     .32        .16

                               Ford et al, 1998
 Association between Nicotine Use in
      Probands and Relatives

                      Adjusted Odds Ratios
              Parents Siblings Offspring Spouse
 Proband       n=74    n=131      n=56    n=123

Regular Use     0.9       1.2       0.7      1.6

Dependence      0.8       2.7       0.7      2.4
  How do we know that environmental
   factors are involved in a disease?

 > 50% decrement in the recurrence risk in
  families by degree of genetic relationship
 Increased prevalence of disease among non-
  biological relatives (eg., spouses)
 Change in disease prevalence among
  migrants to different environment
Type 2 Diabetes Pima Indians

          Gila River

                Type 2 Diabetes
    50%                           2%
                                       Schulz, 1996
        Human Diseases Result from
      Gene-Environment Interactions

 “If all factors that determine disease are
taken into account, then 100% of disease
 can be said to be inherited. Analogously,
  100% of any disease is environmentally
        Kenneth Rothman, Modern Epidemiology, 1986
   Value of Population-Based Samples

 Enhance generalizability (and reduce bias) of
  study findings
 Estimate gene frequencies and population
  risk parameters
 Collect comparable case and control groups
  to minimize confounding
 Obtain sufficient number of subjects to
  increase power to detect genes of small effect
    Genetic and Environmental Factors in
            Alzheimer’s Disease
      Genes                                  Environment
Susceptibility                            Susceptibility
     APOE-E 4                            Head trauma
                                          Vascular factors
                            Alzheimer’s   Total cholesterol
Probabilistic                 Disease     Hypertension
-amyloid precursor
Presenilin – 1
Presenilin – 2                            Protective
Slooter & Van Duijn, 1997                 Education
       Risk Factors and Impact of Selected Chronic Diseases
                                                  Specific Environmental
                                     Genes                                              Impact
              Phenotype                                   Factors
               Measure                Confirmed
                                       Loci
                                                        Known?        Malleable   Prevalence     DALY*

  Breast                               BRCA-1
                 Biopsy        1.8                1st   child > age   Possible       1.2%        0.4
  Cancer                               BRCA-2
                 Clinical,             PS1/PS2                                        5%
Alzheimer’s   Neurocognitive                       Head injury,
  Disease        Testing,      2.8       APP
                                                      Low             Possible
                                                                                    ( > age      0.8
               Post-mortem              APOE                                          65)
  Type 1         Markers,               HLA       Non-specific          No
 Diabetes        Glucose,      15.0     INS
                                                                                     0.4%        0.1
  Multiple      Clinical,                         Non-specific          No
 Sclerosis    Neuroimaging     20.0     HLA                                          0.2%        0.1
                                                         Obesity,                    6.1%
                                                        Physical        Yes
  Type 2        Glucose                                                           (> age 20)
 Diabetes      Metabolism      4.3     PPAR            Inactivity                               1.1
                                                                                  ( > age 60)
                               Merikangas & Risch, 2003
   Priorities for Genomics Research

 Biologically valid phenotype
 Knowledge regarding pathogenesis
 High genetic attributable risk
 Specific environmental factors have not
  been identified
 Severe impact or high prevalence
                        Merikangas & Risch, 2003
Priorities for Environmental Research

 Specific environmental exposure(s)
 Modifiable exposures
 Exposures with high attributable risk

                   Merikangas & Risch, 2003

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