On the validity of within-nuclear-family genetic association analysis in samples of extended families

Bureau Alexandre () and Duchesne Thierry
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Bureau Alexandre: Département de médecine sociale et préventive, Pavillon Vandry, room 2457, 1050 rue de la Médecine Université Laval, Québec, QC, G1V 0A6, Canada Centre de recherche de l’Institut Universitaire en Santé Mentale de Québec, Québec, QC, G1J 2G3, Canada
Duchesne Thierry: Département de mathématiques et de statistique, Pavillon Alexandre-Vachon, room 1056, 1045 av. de la Médecine Université Laval, Québec, QC, G1V 0A6, Canada

Statistical Applications in Genetics and Molecular Biology, 2015, vol. 14, issue 6, 533-549

Abstract: Splitting extended families into their component nuclear families to apply a genetic association method designed for nuclear families is a widespread practice in familial genetic studies. Dependence among genotypes and phenotypes of nuclear families from the same extended family arises because of genetic linkage of the tested marker with a risk variant or because of familial specificity of genetic effects due to gene-environment interaction. This raises concerns about the validity of inference conducted under the assumption of independence of the nuclear families. We indeed prove theoretically that, in a conditional logistic regression analysis applicable to disease cases and their genotyped parents, the naive model-based estimator of the variance of the coefficient estimates underestimates the true variance. However, simulations with realistic effect sizes of risk variants and variation of this effect from family to family reveal that the underestimation is negligible. The simulations also show the greater efficiency of the model-based variance estimator compared to a robust empirical estimator. Our recommendation is therefore, to use the model-based estimator of variance for inference on effects of genetic variants.

Keywords: conditional logistic regression; empirical variance estimation; genetic linkage; pseudo-controls; Wald test (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1515/sagmb-2015-0056

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