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Understanding Genetic Terminology and Regression Analysis in Genetics

This discussion focuses on key genetic concepts and their application in regression analysis, particularly in the context of a study examining the link between genotype and the risk of myocardial infarction. Topics covered include basic genetic terminology (alleles, genotypes, haplotypes), interpretation of regression coefficients, and differences between various logistic regression models. A quiz is included to reinforce learning and practical application of these concepts.

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Understanding Genetic Terminology and Regression Analysis in Genetics

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  1. DISCUSSIONBIOST/EPI 536 Tuesday, December 8, 2009

  2. Outline • Review of genetic terminology • Weekly quiz • Interpretation of regression coefficients (HW 14)

  3. Genetic terms Allele 1 Homologous pair of chromosomes Locus Allele 2 • Genotype: A pair of alleles located at a specific location on homologous chromosomes, whose expression contributes to some observed trait • -- Homozygous: Same alleles (e.g., AA) • -- Heterozygous: Different alleles (e.g., Aa) One allele inherited from each parent

  4. Genetic terms Genotype aa Bb DD SNP 1 SNP 2 SNP 3 a B D a b D Haplotypes: (a,B,D) (a,b,D) Diplotype • Haplotype: A combination of alleles at multiple loci that are inherited together on the same chromosome • Diplotype: A pair of haplotypes from homologous chromosomes

  5. Genotype aa Bb DD Genotype 0 1 2 SNP 1 SNP 2 SNP 3 SNP 1 SNP 2 SNP 3 a B D 0 1 1 a b D 0 0 1 Haplotypes: (a,B,D) (a,b,D) Haplotypes: (0,1,1) (0,0,1) Diplotype Diplotype Counting alleles denoted in capital letters as those of interest…

  6. Week 10 Quiz • Dr. Austin was interested in whether genotype at a genetic locus on chromosome 4 was related to the risk of myocardial infarction. She conducted a case-control study among 60-65 year old men in the Seattle area. • Subject ascertainment methods were unbiased. • The study was adequately powered. • There was no matching. • At the genetic locus in question, one of five alleles exist: • A, B, C, D, and E.

  7. Week 10 Quiz She fit the following logistic model: logit p = -1.02 + 0.48xB + 0.54xC + 0.51xD + 0.52xE xB = # of B alleles in a subject’s genotype xC = # of C alleles in a subject’s genotype xD = # of D alleles in a subject’s genotype xE = # of E alleles in a subject’s genotype Based on the results of this model, one of Dr. Austin’s students concluded that each additional copy of allele B causes an increase in risk of MI among 60-65 year old men. Is this a correct interpretation? Why or why not?

  8. Week 10 Quiz Model: logit p = α + βBxB + βCxC + βDxD + βExE Consider the log odds of MI for each genotype Allele 2 Genotype comparisons for which log OR = βB?

  9. HW 14: Model A Letting xi = 1 if the haplotype is present, and 0 otherwise for i = 2, 3, or 4: logit p = α + β2x2 + β3x3 + β4x4 What is the interpretation of β2?

  10. HW 14: Model A Model A: logit p = α + β2x2 + β3x3 + β4x4 Consider the log odds of being a case for each diplotype 2nd Haplotype Diplotype comparisons for which log OR = β2?

  11. HW 14: Model B Letting xi = the number of ith haplotypes present in a subject’s diplotype (0, 1, 2) for i = 2, 3, or 4: logit p = α + β2x2 + β3x3 + β4x4 What is the interpretation of β2?

  12. HW 14: Model B Model B: logit p = α + β2x2 + β3x3 + β4x4 Consider the log odds of being a case for each diplotype 2nd Haplotype Diplotype comparisons for which log OR = β2?

  13. HW 14: Model C Letting diplotype 1 be the reference haplotype, and xi=1 if the ith diplotype is present and 0 otherwise for i = 2,…,10: logit p = α + β2x2 + … + β10x10 What is the interpretation of β4, β5, β8, and β9?

  14. HW 14: Differences in models • What constraints are imposed by each model? • Model A: • Model B: • Model C: • Are any of these reparameterizations of one another?

  15. HW 14: Differences in models How does the interpretation of β2 in models A and B differ? Is the interpretation of β2 in these two models comparable to the interpretation of β4, β5, β8, or β9 in model C?

  16. Revisiting some general principles • The interpretation of a regression coefficient depends on what other variables are included in the model. • The interpretation of a regression coefficient depends on how variables are coded in the model.

  17. Questions?

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