Genetic Analysis of Case/Control Data Using Estimated Haplotype Frequencies: Application to APOE Locus Variation and Alzheimer's Disease

Abstract

There is growing debate over the utility of multiple locus association analyses in the identification of genomic regions harboring sequence variants that influence common complex traits such as hypertension and diabetes. Much of this debate concerns the manner in which one can use the genotypic information from individuals gathered in simple sampling frameworks, such as the case/control designs, to actually assess the association between alleles in a particular genomic region and a trait. In this paper we describe methods for testing associations between estimated haplotype frequencies derived from multilocus genotype data and disease endpoints assuming a simple case/control sampling design. These proposed methods overcome the lack of phase information usually associated with samples of unrelated individuals and provide a comprehensive way of assessing the relationship between sequence or multiple-site variation and traits and diseases within populations. We applied the proposed methods in a study of the relationship between polymorphisms within the APOE gene region and Alzheimer's disease. Cases and controls for this study were collected from the United States and France. Our results confirm the known association between the APOE locus and Alzheimer's disease, even when the 4 polymorphism is not contained in the tested haplotypes. This suggests that, in certain situations, haplotype information and linkage disequilibrium-induced associations between polymorphic loci that neighbor loci harboring functional sequence variants can be exploited to identify disease-predisposing alleles in large, freely mixing populations via estimated haplotype frequency methods.

Improved use of SNP information to detect the role of genes

“…The etiological polymorphism can remain untyped or not included. Some studies [Akey et al, 2001;Fallin et al, 2001;Verpillat et al, 2001] showed that, under the hypothesis that the etiological marker is not among those typed, a haplotypebased test has better power than a single marker test. In this case, the role of the gene can only be detected through preferential association of the etiological allele with some haplotypes, and thus not taking into account the association of some alleles on the same haplotype (the linkage disequilibrium information) decreases the power to detect the effect of the gene.…”

High‐throughput single‐nucleotide polymorphism analysis of the IL1RN locus in patients with ankylosing spondylitis by matrix‐assisted laser desorption ionization‐time‐of‐flight mass spectrometry

“…Phenotype frequencies and odds ratios (ORs) were calculated with 95% confidence intervals (95% CIs). Haplotype inference was determined on data from individuals with a complete set of markers, using the SNPEM program (32,33), which implements an expectationmaximization algorithm method (34). A Markov chain Monte Carlo method (PHASE) was used to infer haplotype frequencies to determine whether they differed from those calculated using expectation-maximization (35).…”

On the advantage of haplotype analysis in the presence of multiple disease susceptibility alleles

“…For markers with two or more alleles and for haplotypes when haplotype phase was assumed known, the LRT statistic was computed using multinomial maximum likelihood estimates of marker allele or haplotype frequencies [Agresti, 1990]. When haplotype phase was assumed unknown, the LRT statistic was computed using an expectationmaximization algorithm to maximize a multinomial likelihood based on genotype frequencies under the assumption of Hardy-Weinberg equilibrium [Excoffier and Slatkin, 1995;Fallin et al, 2001]. We used a Newton-Raphson algorithm to maximize the complete-data likelihood and substituted the resulting maximum likelihood estimates into the observed-data likelihood, which has coupling and repulsion phase double heterozygotes confounded, to obtain the LRT statistic.…”