Adjusting heterogeneous ascertainment bias for genetic association analysis with extended families
Year: 2015
Type: article
Abstract: BACKGROUND: In family-based association analysis, each family is typically ascertained from a single proband, which renders the effects of ascertainment bias heterogeneous among family members. This is contrary to case-control studies, and may introduce sample or ascertainment bias. Statistical efficiency is affected by ascertainment bias, and careful adjustment can lead to substantial improvements in statistical power. However, genetic association analysis has often been conducted using family-based designs, without addressing the fact that each proband in a family has had a great influence on the probability for each family member to be affected. METHOD: We propose a powerful and efficient statistic for genetic association analysis that considered the heterogeneity of ascertainment bias among family members, under the assumption that both prevalence and heritability of disease are available. With extensive simulation studies, we showed that the proposed method performed better than the existing methods, particularly for diseases with large heritability. RESULTS: We applied the proposed method to the genome-wide association analysis of Alzheimer's disease. Four significant associations with the proposed method were found. CONCLUSION: Our significant findings illustrated the practical importance of this new analysis method.
Source: BMC Medical Genetics
Institutions: Soonchunhyang University, Korea National Institute of Health, Chung-Ang University, Seoul National University, Harvard University, German Center for Neurodegenerative Diseases, Massachusetts General Hospital, Max Planck Institute for Molecular Genetics, Imperial College London, University of Bonn
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,380
OpenAlex ID: W1941474075