1. Genetics of Complex Disease Bert Gold, Ph.D., F.A.C.M.G

2. Complex versus Mendelian Trait Complex trait suggests the involvement of: –Multiple loci and/or –Environmental effects

3. Characteristics of complex traits May be difficult to determine –May require measurements –Instruments –Phenotype details may be expensive to collect –Affected may be well defined, the unaffected may not

4. Mendelian trait suggests Single locus –May have some genetic heterogeneity –Or reduced penetrance but, –Strong genotype-phenotype correlation

5. Complex traits are common They may cluster in families, but not demonstrate an obvious Mendelian pattern Phenotypes may derive from multiple genes and environment acting in concert e.g. depression, schizophrenia, cardiovascular disease, dyslexia. Complex traits have substantial impact on public health. Mendelian traits are rare.

6. How do you know a complex phenotype is genetic? Mendelian disorders –Recognizable inheritance patterns –Phenotypic expression is highly correlated with genotype at the disease locus Complex disorders –Qualitative or Quantitative Traits –Qualitative Presence or Absence –Breast Cancer –Bipolar Disease

7. How do you know a complex phenotype is genetic? In complex traits, absence  unaffected Phenotypes are defined as above a threshold value Obesity => BMI 27 kg/m Diabetes=> Fasting plasma glucose > 126 mg Threshold for affection status may be somewhat arbitrary.

8. Quantitative Traits Measurements –Height, Weight, BMI –Fasting plasma glucose –Blood pressure Scales –Mini-mental status examination (MMSE) –Autism Diagnostic Interview – Revised (ADI-R) –Risk Scores –Evidence for a genetic component?

9. More about Complex Traits Usually have no distinct inheritance pattern High frequency in the general population complicates determining who carries the genetic liability within a family Phenotypic expression modified by the genotype of several loci and environmental factors.

10. Genetic Dissection of a complex disease Requires –Clinical definitions –Study design perspectives –Statistical approaches –Molecular approaches –Social, legal, and ethical issues discussions and clearances

11. The Literature Review How was the disease defined/diagnosed in previous studies? How does this compare with your clinical methods? Were individuals of all ages studied or only one age group? What races were studied? What environmental factors were considered? Significant deviations from your own definition of phenotype and study may necessitate you repeat these analyses.

12. Approaches to Determining the Genetic Component of a Disease First, establish evidence of a familial component Second, determine the cause of familial aggregation Third, identify the specific genetic factors involved

13. Methodology for Establishing the Genetic Component Segregation analysis –Computer/labor intensive statistical tool (SAGE, PAP) used to examine inheritance patterns for a disease. –By comparing different models, you can determine which inheritance model provides the “best fit” to your data

14. Segregation Model Advantages: –When successful, it provides a genetic model for linkage analysis. –Confirms that major gene is present before investing in expensive genomic screening. Simple example assuming autosomal dominant inheritance

15. Segregation Model Disadvantages: –Modeling is usually limited to 1-2 loci –Sensitive to ascertainment bias Examples of sensitivity to ascertainment bias –Sampling may include lost of “sporadic” families, not appropriate for linkage analysis –What do “negative” results imply? –Confounders can include heterogeneity, multilocus models

16. Familial clustering/recurrence risk to relatives Familial aggregation is the clustering of affected individuals within families. Methods for determining familial aggregation include: Family history approach (Khoury et al., 1993)

17. Family History Approach Specifically Ascertain the presence or absence of a family history of the disease in the study participants. Three variations depending on the level of detail of information obtained on the relatives: Abbreviated family history Detailed family history Family Study

18. Family History Approach 2x2 If you are performing a case-control study, you can treat family history as a “risk-factor” and use a standard 2x2 table to assess the significance If table is Odds ratio= (a*d)/(b*c) ab cd + - Family History Disease in study participant + -

19. Correlation coefficients Quantitative traits can be plotted using a trait value in one relative versus another. The slope of the line is the square of the correlation coefficient. If no correlation, then environmental factors predominate.

20. R 2 example Specifically, e.g. Mean Parental Height Mean Offspring height If you have a quantitative trait, you can polot the trait value in one relative versus the other The slope of the line is the square of the correlation coefficient. This graph suggests that mean offspring height is primarily a consequence of hereditary factors.

21. Recurrence Risk to relatives A measure of how “genetic” a trait or disease is. What is the rate of affection for relative of proband with the disease versus the frequency of the disease in the in the general population? (Risch, N. Am. J. Hum. Genet. (1990): 46: 222-253. Sibling Recurrence Risk: S

22. Interpretation of S Values > 1.0 are generally taken to indicate evidence in favor of a genetic component. In general, the higher the value, the stronger the genetic component. Values can be used to estimate the number of genes under different genetic models. Note that the magnitude of the estimate is very dependent on the frequency in the population. For example, a common disorder may have frequency estimates of 3-6% depending on how a given study was performed but this results in small lambda.

23. Twin and adoption studies Twins are special cases of siblings –MZ twins share 100% of their genetic material –DZ twins share 50% of their genetic material (same as other sibs).

24. Twin Studies Continued Comparisons of Disease concordance rates between MZ and DZ twins provide information regarding the involvement of genetics –Concordance rates with MZ>DZ are consistent with the involvement of genetics

25. First Twin Study Example Examples: One twin is affected, how often is the other affected? deviation from the expected frequencies may be due to incomplete penetrance MZDZ Type of Disease 90% Probably environment al 100%25% Mendelian recessive

26. Second Twin Example MZDZ Type of Disease 80%16%?? 72%35%?? 7% * *Especially may be the same as the population frequency; Therefore this may not be a good model for hereditary disease.

27. Twin Studies Twin studies are believed to control for many confounding environmental effects: –Age –Common familial environment Objection: Applicable for childhood, but not necessarily prenatal and rarely true for adult exposures

28. Cautions on Twin Studies Misclassification of zygosity Control for sex Diseases with variable age of onset PlacentaChorionAmnionDZ(%)MZ(%) 2225015 1225015 112-70 111-rare

29. Adoption Studies Like twin studies, adoption studies can be used to test for evidence of genetic versus common familial environmental factors in the etiology of a disease. Cases are ascertained and the frequency of the disease in the biological parents of the case is compared with than in the adoptive parents. Difficulties include: –Achieving the necessary sample size –Similarity of adoptive and biological parental environments

30. Adoptive Twin Approach Variation on Twin Studies, ‘Twins Reared Apart’. Should be very sensitive at teasing out environmental vs. hereditary causes of disease. Frequency of disease in biological parents Frequency of disease in adoptive parents Possible Etiology 85%4% Implies genetic etiology, frequency in adoptive parents may reflect general population risk 4%85% Implies common environment is the primary risk factor

31. Heritability A statistical measure of the degree to which a trait is genetically determined Conceptual defininition: the ratio of genetic variance to total variance Rigorous definition: The proportion of the total phenotypic variance (V) of a trait that is due to genetic variance (G). This is heritability in the “broad sense”. It is a form of Principal Components Analysis.

32. Heritability Approach: Compare variation among different classes of relatives to that predicted by simple genetic factors Variance can also be broken down into additive, dominant, and epistatic variance. Correlation coefficient revisited: heritability= fraction of genes shared via identity by descent times the r squared. This represents heritability in the narrow sense (additive variance). Heritability can be more rigorously defined in twin studies: h 2 =2(r MZ 2 -r DZ 2 )

33. Co-occurrence with other genetic conditions This occasionally occurs in a subset of patients and can provide very useful clues to the location of disease genes. –Examples: –Association between Trisomy 21 and Alzheimers disease led to the isolation of the APP gene. –Association between chromosome 15q11-q13 duplications and inversions with autistic disorder provides one of the most promising candidate regions for an autistic disorder locus.

34. Experimental systems Animal Models –The occurrence of a human disease trait in a model system can provide support for the genetic basis of human disease, and a method for investigating the genetic mechanisms. Example: –Over 40 mouse gene have been implicated in NTD (Harris and Juriloff, Teratology 56:177-187 (1997)).

35. Inheritance mode consideration (with statistical implications) Mendelian subsets? –Early onset? –More severe? –Clear-cut transmission allows parametric transmission analysis?

36. Consider Study Design Affected sibling pair –Easy to collect? Affected relative pair/extended pedigree –Better for fine mapping? –Allows consideration of different genetic models?

37. Family triads TDT or some variant? Assist with fine mapping? Include families not necessarily multiplex? Increase generality of results?

38. Case-control Easy to collect? Problems with establishing good control group?

39. The TDT As a test for linkage, can use singleton families, affected sib families, and extended families Looks only for informative familial relationships Has greater sensitivity than linkage analysis or affected sib pairs

40. A TDT example nontransmitting trans mittin g 1x 178 x46 79 parents heterozygous for Class I allele at insulin gene polymorphism (other alleles = X) Triad results: 24 transmitted class I, 10 transmitted X Affected Sib Pair Families: 15 transmitted class I to both children 24 transmitted class I to one child and X to the other 6 transmitted X to both children Evidence of linkage with the TDT Allele-sharing test is not significant For linkage (p-value=0.20)

41. Special populations Homogeneity? Generality?

42. Advantages and Disadvantages of the TDT Advantages –Can use singleton data –Can be more powerful than ASP tests (even when the same data are used) Disadvantage –Has little power to detect linkage unless there is also allelic association

43. Subject Recruitment –Researchers responsibility to subjects Maintaining IRB protocols ensuring adequate review and oversight of project Sharing results with subjects? Maintaining contact through –Newsletters? –Web site? –Phone access?

44. Sample Collection Blood for DNA Cell Lines Other tissue to allow extraction of tissue specific RNA –e.g., muscle biopsy for muscular dystrophy or tumor tissue for cancer research, FMRP through scalp hairlet bulbs.

45. Molecular Design Genomic Screen Candidate gene analysis –Candidate-by-function? –Candidate-by-location? –SSCP to screen or sequencing for more accurate gene assessment? Expression studies

46. Translation to Clinical Care DNA for presymptomatic and/or diagnostic testing? Develop prevention/treatment/cure? Phamacogenetics initiatives?