domingo, 29 de marzo de 2015

A Statistical Approach for Rare-Variant Association Testing in Affected Sibships. - PubMed - NCBI

2015 Mar 18. pii: S0002-9297(15)00052-X. doi: 10.1016/j.ajhg.2015.01.020. [Epub ahead of print]

A Statistical Approach for Rare-Variant Association Testing in Affected Sibships.

Epstein MP1, Duncan R2, Ware EB3, Jhun MA3, Bielak LF3, Zhao W3, Smith JA3, Peyser PA3, Kardia SL3, Satten GA4.

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Abstract

Sequencing and exome-chip technologies have motivated development of novel statistical tests to identify rare genetic variation that influences complex diseases. Although many rare-variant association tests exist for case-control or cross-sectional studies, far fewer methods exist for testing association in families. This is unfortunate, because cosegregation of rare variation and disease status in families can amplify association signals for rare variants. Many researchers have begun sequencing (or genotyping via exome chips) familial samples that were either recently collected or previously collected for linkage studies. Because many linkage studies of complex diseases sampled affected sibships, we propose a strategy for association testing of rare variants for use in this study design. The logic behind our approach is that rare susceptibility variants should be found more often on regions shared identical by descent by affected sibling pairs than on regions not shared identical by descent. We propose both burden and variance-component tests of rare variation that are applicable to affected sibships of arbitrary size and that do not require genotype information from unaffected siblings or independent controls. Our approaches are robust to population stratification and produce analytic p values, thereby enabling our approach to scale easily to genome-wide studies of rare variation. We illustrate our methods by using simulated data and exome chip data from sibships ascertained for hypertension collected as part of the Genetic Epidemiology Network of Arteriopathy (GENOA) study.