Contrasting Linkage-Disequilibrium Patterns between Cases and Controls as a Novel Association-Mapping Method

• Published in: American journal of human genetics Vol. 78; no. 5; pp. 737 - 746
• Main Authors: Zaykin, Dmitri V., Meng, Zhaoling, Ehm, Margaret G.
• Format: Journal Article
• Language: English
• Published: Chicago, IL Elsevier Inc 01.05.2006; University of Chicago Press; Cell Press; The American Society of Human Genetics
• Subjects: Biological and medical sciences; Case-Control Studies; Chromosome Mapping - methods; Computational Biology - methods; Computational Biology - statistics & numerical data; Computer Simulation; Cytochrome P-450 CYP2D6 - genetics; Cytochrome P-450 CYP2D6 - pharmacology; General aspects. Genetic counseling; Genetic linkage; Genetic Markers; Genetic Predisposition to Disease; Genetic Variation; Haplotypes; Humans; Linkage Disequilibrium; Medical genetics; Medical sciences; Methods; Models, Statistical; Polymorphism, Single Nucleotide; Quantitative Trait, Heritable; Samples; Studies; Tests; Genetic mapping; Case study; Human; Cartography; Association; Genetics; Method; Technique; Linkage equilibrium
• ISSN: 0002-9297; 1537-6605
• DOI: 10.1086/503710

Identification and description of genetic variation underlying disease susceptibility, efficacy, and adverse reactions to drugs remains a difficult problem. One of the important steps in the analysis of variation in a candidate region is the characterization of linkage disequilibrium (LD). In a region of genetic association, the extent of LD varies between the case and the control groups. Separate plots of pairwise standardized measures of LD (e.g., D′) for cases and controls are often presented for a candidate region, to graphically convey case-control differences in LD. However, the observed graphic differences lack statistical support. Therefore, we suggest the “LD contrast” test to compare whole matrices of disequilibrium between two samples. A common technique of assessing LD when the haplotype phase is unobserved is the expectation-maximization algorithm, with the likelihood incorporating the assumption of Hardy-Weinberg equilibrium (HWE). This approach presents a potential problem in that, in the region of genetic association, the HWE assumption may not hold when samples are selected on the basis of phenotypes. Here, we present a computationally feasible approach that does not assume HWE, along with graphic displays and a statistical comparison of pairwise matrices of LD between case and control samples. LD-contrast tests provide a useful addition to existing tools of finding and characterizing genetic associations. Although haplotype association tests are expected to provide superior power when susceptibilities are primarily determined by haplotypes, the LD-contrast tests demonstrate substantially higher power under certain haplotype-driven disease models.