1. 1 Seminar 4: Applied Epidemiology Kaplan University School of Health Sciences

2. 2 Chapter 14: Molecular and Genetic Epidemiology  Introduction  Definitions and Distinctions: Molecular versus Genetic Epidemiology  Epidemiologic Evidence for Genetic Factors  Causes of Familial Aggregation  Shared Family Environment and Familial Aggregation

3. 3 Introduction  Mapping of the human genome and the subsequent advances in molecular biology forever changed epidemiologic research on disease etiology. Google Human Genome Project Google Human Genome ProjectHuman Genome ProjectHuman Genome Project  This chapter presents an overview of this rapidly growing area of epidemiology.

4. 4 Introduction  Exhibit 14-1 Basic Principle of Human Genetics. How many have a background in biology? How many have a background in biology? Please read this section to see if you can understand it. Please read this section to see if you can understand it.

5. 5 Definitions and Distinctions: Molecular versus Genetic Epidemiology  Genetic Epidemiology is devoted to the identification of inherited factors that influence disease, and how variation in the genetic material interacts with environmental factors to increase (or decrease) risk of disease.

6. 6 Genetic Epidemiology  Can be thought as a collection of methodologies designed to answer four questions (page 536):  1. Does the disease of interest cluster in families?  2. Is the clustering a reflection of shared lifestyle, common environment, or similar risk profiles?

7. 7 Genetic Epidemiology  3. Is the pattern of disease (or risk for a disease) within families consistent with the expectation under Mendelian transmision of a major gene?  4. Where is the chromosomal location of the putative gene?  Once the chromosomal region is narrowly defined, the torch is passed to molecular epidemiologists to identify appropriate genes

8. 8 Molecular Epidemiology  A greater precision in estimating exposure-disease associations can be made by using molecular biology to improve the measurement of exposures and disease.  Mole Epi has the possibility of providing early warnings for disease by flagging preclinical effects of exposure (page 537).

9. 9  Figure 14-2: Two strategies to identify human genes Functional cloning: Disease > Function > Gene > Map Functional cloning: Disease > Function > Gene > Map Position cloning: Disease > Map > Gene > Function. Position cloning: Disease > Map > Gene > Function.

10. 10 Molecular Epidemiology  Biomarkers from biologic specimens (e.g. blood, tissue, urine, and sputum) Recall of diet versus micronutrients in the blood. Recall of diet versus micronutrients in the blood. Colon cancer versus an intermediate marker (an accepted precursor lesion) Colon cancer versus an intermediate marker (an accepted precursor lesion) Smoking versus serum nicotine Smoking versus serum nicotine

11. 11 Molecular Epi versus Genetic Epi  Then gene is involved, there is an overlap between molecular and genetic epidemiology.  One distinction between the two is that molecular epidemiology does not involve studies of biologically related individuals.  Another distinction is that most molecular epidemiologic studies are conducted to evaluate the significance of variances in genes

12. 12 Molecular Epi versus Genetic Epi  Genetic epidemiology: concerned with inherited factors that influence risk of disease  Molecular epidemiology: uses molecular markers (in addition to genes) to establish exposure-disease association.

13. 13 Epidemiologic Evidence for Genetic Factors  If a disease has a genetic component, at the very least one might expect to observe the occurrence of the same disease among close family members because they have a certain probability of sharing the same gene that influences risk of disease.

14. 14 Epidemiologic Evidence for Genetic Factors  Positive family history A simple definition is the occurrence of the same disease or trait within a family. A simple definition is the occurrence of the same disease or trait within a family. A more precise definition would include the specific types of relatives that will be considered, for example first-degree relatives (parents, siblings, and offspring) or second-degree relatives (grandparents, aunts, and uncles, nieces and nephews, and grandchildren. A more precise definition would include the specific types of relatives that will be considered, for example first-degree relatives (parents, siblings, and offspring) or second-degree relatives (grandparents, aunts, and uncles, nieces and nephews, and grandchildren.

15. 15 Epidemiologic Evidence for Genetic Factors  Study designs to evaluate the association of family history with disease  A cross-sectional survey  Case-control study  Cohort study

16. 16 Causes of Familiar Aggregation  Although demonstration that a disease or trait clusters in families is certainly acceptable evidence that genetics may be important, several alternative explanations must be considered.  The explanations include the operation of chance and the influence of environmental factors.

17. 17 Shared Family Environment and Familial Aggregation  A difficulty in the interpretation of “family history” data is the inability to determine the influence of non-genetic risk factors on any observed familial clustering.  Measurement and evaluation of risk factors are necessary in order to answer the question, “Is the observed clustering, due to (shared) environmental factors?”

18. 18 Design of Case-Control Family Studies  A family study can be defined as one in which data on phenotype and risk factors are measured on individual members  A proband is the individual in a family who brings a disease of interest to the attention of the investigator.  In a case family, the proband is likely to be a person affected with the disease.  In a control family, the proband is the subject matched to the case.

19. 19 Design of Case-Control Family Studies  The definition of family also must be clearly stated: 3-generagion families or more are most valuable for elucidation of genetic mechanisms.  Two steps are required to establish the sampling frame for a case-control family study Ascertainment of cases (probands) and controls. Ascertainment of cases (probands) and controls. Enumeration of the relatives of the probands and controls. Enumeration of the relatives of the probands and controls.

20. 20 Gene Mappings: Segregation and Linkage Analysis  Segregation analysis is an approach to determine, from a sample of families, whether a particular disease or trait is inherited in Mendelian fashion.  By Mendelian, we mean the situation in which the mode of transmission of a disease or trait from parents to offspring is consistent with simple laws of inheritance.

21. 21 Modes of Inheritance  The mode of transmission refers to the association between number of mutated alleles at a locus and a given phenotype (disease or trait) and whether or not the locus is situated on one of the 22 autosomes or on a sex chromosome.  The example of B, b alleles in the textbook (page 546).

22. 22 Modes of Inheritance  Autosomal dominant refers to the situation in which only a single copy of an altered gene located on a non-sex chromosome is sufficient to cause an increased risk of disease.  Autosomal recessive Carriers: with one copy of recessive alleles. Carriers: with one copy of recessive alleles.  Sex-linked dominant: one mutated gene in male X chromosome may cause a disease.

23. 23 Determining the Mode of Inheritance  Is determined by comparing how well different hypotheses (genetic and non- genetic) fit the observed pattern of a disease in a collection of families.  Use computer programs to conduct segregation analysis  The goodness-of-fit is compared for various models to determine which one is the most likely explanation for the observed pattern of disease.

24. 24 LOD Score Linkage Analysis  Linkage analysis is an attempt to identify a DNA marker that co-segregates with the disease of interest and is considered strong evidence for the existence of a gene.  The basis for linkage analysis is that there are exceptions to Mendel’s law of independent assortment of traits.

25. 25 LOD Score Linkage Analysis  Specifically, genes that are in the close physical proximity to each other on the same chromosome tend to be linked (i.e. inherited together).  Two genes on different chromosomes are unlinked and will be inherited together roughly 50% of the time.  The probability of a recombination event is a function of the distance between two loci.

26. 26 LOD Score Linkage Analysis  In a given number of meioses, the proportion that yields a recombinant chromosome is defined as the recombination fraction (θ).  If the number of recombinants between two loci is estimated to be quite small (or zero), then the two loci are “linked” and physical location of the disease-causing gene possible has been identified.

27. 27 LOD Score Linkage Analysis  Whether two loci are linked is answered by comparing the value of the observed recombination fraction to the expected recombination fraction of 0.5 (under no linkage).  LOD (logarithm of the odds) is a ratio of the likelihood of the data under linkage at some specified recombination fraction to the likelihood of the data under a recombination fraction of 0.5.

28. 28 LOD Score Linkage Analysis  A LOD score of 3.0 is equivalent to a P- value of 1000 to 1; this evidence is commonly accepted for significance linkage.

29. 29 Nonparametric Linkage Analysis  A method that does not require specification of the parameters of the underlying genetic model.  Detailed description is on page 552.

30. 30 Genome-Wide Association Studies  Single nucleotide polymorphism (SNP) is a minor variation in genome.  Illustration of SNPs in Figure 14-4.  Exhibit 14-5 on page 554: Genome-Wide Association Studies of Breast Cancer

31. 31 Linkage Disequilibrium Revisited: Haplotypes  The combination of DNA markers along the chromosome is referred as to a haplotype.  The international HapMap Project: a collaboration to develop a haplotype map of the human genome and generate 200,00 to perhaps a million SNPs that would “tag” (represent) the most common hyplotypes in all human population.

32. 32 Application and Implications of the HapMap Project  The epidemiologic approach to the application of genetics to human disease is best described as one based on candidate genes.  There are several important issues to consider in genome-wide studies: The efficacy of this design is informed by power (true positive), sample, false positive, and cost.

33. 33 Application of Genes in Epidemiology. Genetics and Public Health  Please read the sections and discuss the application of genes in epidemiology and genetics and public health.  Discuss: What are the most important applications in public health and what applications are the most interesting to you?