Epidemiology 217Molecular and Genetic Epidemiology I John Witte Professor of Epidemiology & Biostatistics January 4, 2005
I. Details • Classes: 10 Tuesdays, 1:00-2:30 pm, MU 427 • Office hours: by appointment in MU 405E (John Witte’s office), or by appointment • Contact info: email@example.com 502-6882 • Course website: www.epibiostat.ucsf.edu/courses/schedule/mol_methodsi.html
Goals • Learn about: • common molecular and genetic measures available • genomics of infectious diseases • searching for disease-causing genes, and their interaction with environmental factors • pharmacogenomics; proteomics; and bioinformatics. • Main goal: develop a framework for interpreting, assessing, and incorporating molecular and genetic measures in your own research.
Homework Assignments • Count for 70% of grade (30% for final exam). • Weekly readings and / or brief problem sets. • Readings give important background information, and should be completed before the start of the corresponding lecture. • Problem sets are due at 8 pm on Mondays, so we can discuss the following day. • Late assignments are not accepted.
Web Resources • Video from UAB Short course on statistical genetics: http://www.soph.uab.edu/ssg_content.asp?id=1174 • Dorak’s notes on genetics: http://dorakmt.tripod.com/genetics/ • Strachan & Read’s Human Molecular Genetics: http://www.ncbi.nlm.nih.gov/books/bv.fcgi?rid=hmg
II. Introduction: how was lunch? ? Impact of folate, B12, and homocysteine on cognitive function?
How can we measure these factors? Problems?
Can we improve our measurements? Look at circulating levels in plasma
What else will impact these levels? • Methylene tetrahydrofolate reductase (MTHFR): e.g., catalyzes the last step in conversion of folic acid to its active form, 5-methyltetrahydrofolate (5MTHF).
MTHFR gene Locus 23 pairs of chrom, 1 sex • Single nucleotide polymorphisms (SNPs) in MTHFR: C677T (C and T are alleles; CC, CT, TT are genotypes) A1298C (A and C are alleles; AA, AC, CC are genotypes) • E.g., if an individual is homozygous for the 677TT SNP, MTHFR enzymatic activity can decrease by 50%. • This may in turn reduce cognitive function.
Notes on Human Genetics • 4 complementary nucleotide bases, A : T, G : C • 3-base sequences (codons) code for amino acids, and sequences of amino acids form proteins. • Genome ~ 3x109 base pairs, 25,000 genes • Hardy-Weinberg Equilibrium (HWE): If the frequencies of allele A and T (of a SNP) are p and q, then under random mating the expected genotype frequencies are: Prob (AA)=p2 Prob (AT)=2pq Prob (TT)=q2
Diet, plasma, & genotype interaction • Look at how these work in conjunction with each other to affect cognitive functioning!
III. Break: How about you? • Research interests? • Background / training in molecular / genetics? • Every used or considered using molecular or genetic measures in clinical research?
IV. Hints that disease is genetic? • Without yet looking at DNA… • Ecologic Studies (Migrant Studies) • Familial Aggregation: • Family Studies • Twin Studies • Segregation analyses
IV.1 Ecologic Studies (Migrant) Weeks, Population. 7th ed. London: Wadsworth Publishing Co 1999
Example: Cancer (SMRs) (MacMahon B, Pugh TF. Epidemiology: Principles and Methods. Boston: Little, Brown and Co, 1970:178.)
IV.2 Familial Aggregation • Does disease tend to run in families? • Example: Men who have a brother or father with prostate cancer have 2-3 times the risk than men without a family history. • Possible study designs: • Case-control: compare the family history between cases versus controls. • Cohort: view the family members of the cases and controls as two cohorts, one exposed (i.e., to a case), the other not exposed.
Twin Studies • Compare the disease concordance rates of MZ (identical) and DZ (fraternal) twins. Twin 1 Concordance = 2A/(2A+B+C) Twin 2 Then one can estimate heritability (the proportion of the variance of an underlying disease liability due to common genes), and environmentality.
Example of Twin Study: Prostate Cancer • Twin registry (Sweden, Denmark, and Finland) • 7,231 MZ and 13,769 DZ Twins (male) Heritability: 0.42 (0.29-0.50) Non-shared Environment: 0.58 (0.50-0.67) Lichtenstein et al NEJM 2000 13;343:78-85.
IV.3 Segregation Analysis • Evaluate whether the pattern of disease among relatives is compatible with a single major gene, polygenes, or simply shared environment. • Fit formal genetic models to data on disease phenotypes of family members. • The parameters of the model are generally fitted finding the values that maximize the probability (likelihood) of the observed data. • If there appears to be a single major gene, then one can estimate its dominance, penetrance, and allele frequency.
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Summary • Molecular measures can improve upon conventional questionnaire-based measurements. • Genetics can impact many exposures and diseases. • We can assess the heritability with studies of populations and families, including: • Migrant studies • Familial aggregation • Twin studies • Segregation analyses