Regression-based approach for testing the association between multi-region haplotype configuration and complex trait

An Analytic Solution to the Computation of Power and Sample Size for Genetic Association Studies under a Pleiotropic Mode of Inheritance

Our motivation here is to calculate the power of 3 statistical tests used when there are genetic traits that operate under a pleiotropic mode of inheritance and when qualitative phenotypes are defined by use of thresholds for the multiple quantitative phenotypes. Specifically, we formulate a multivariate function that provides the probability that an individual has a vector of specific quantitative trait values conditional on having a risk locus genotype, and we apply thresholds to define qualitative phenotypes (affected, unaffected) and compute penetrances and conditional genotype frequencies based on the multivariate function. We extend the analytic power and minimum-sample-size-necessary (MSSN) formulas for 2 categorical data-based tests (genotype, linear trend test [LTT]) of genetic association to the pleiotropic model. We further compare the MSSN of the genotype test and the LTT with that of a multivariate ANOVA (Pillai). We approximate the MSSN for statistics by linear models using a factorial design and ANOVA. With ANOVA decomposition, we determine which factors most significantly change the power/MSSN for all statistics. Finally, we determine which test statistics have the smallest MSSN. In this work, MSSN calculations are for 2 traits (bivariate distributions) only (for illustrative purposes). We note that the calculations may be extended to address any number of traits. Our key findings are that the genotype test usually has lower MSSN requirements than the LTT. More inclusive thresholds (top/bottom 25% vs. top/bottom 10%) have higher sample size requirements. The Pillai test has a much larger MSSN than both the genotype test and the LTT, as a result of sample selection. With these formulas, researchers can specify how many subjects they must collect to localize genes for pleiotropic phenotypes.

Use of diplotypes - matched haplotype pairs from homologous chromosomes - in gene-disease association studies

Alleles, genotypes and haplotypes (combinations of alleles) have been widely used in gene-disease association studies. More recently, association studies using diplotypes (haplotype pairs on homologous chromosomes) have become increasingly common. This article reviews the rationale of the four types of association analyses and discusses the situations in which diplotype-based analyses are more powerful than the other types of association analyses. Haplotype-based association analyses are more powerful than allele-based association analyses, and diplotype-based association analyses are more powerful than genotype-based analyses. In circumstances where there are no interaction effects between markers and where the criteria for Hardy-Weinberg Equilibrium (HWE) are met, the larger sample size and smaller degrees of freedom of allele-based and haplotype-based association analyses make them more powerful than genotype-based and diplotype-based association analyses, respectively. However, under certain circumstances diplotype-based analyses are more powerful than haplotype-based analysis.