Year: 2009
Type: article
Abstract: Genetic association studies of complex traits often rely on standardised quantitative phenotypes, such as percentage of predicted forced expiratory volume and body mass index to measure an underlying trait of interest (eg lung function, obesity). These phenotypes are appealing because they provide an easy mechanism for comparing subjects, although such standardisations may not be the best way to control for confounders and other covariates. We recommend adjusting raw or standardised phenotypes within the study population via regression. We illustrate through simulation that optimal power in both population- and family-based association tests is attained by using the residuals from within-study adjustment as the complex trait phenotype. An application of family-based association analysis of forced expiratory volume in one second, and obesity in the Childhood Asthma Management Program data, illustrates that power is maintained or increased when adjusted phenotype residuals are used instead of typical standardised quantitative phenotypes.
Source: Human Genomics
Institutions: Harvard University, Brigham and Women's Hospital
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,290
Awards: G116838145, G162555452, Pharmacogenetics of Asthma Treatment, G2772107177, Training Program in Psychiatric Genetics and Translational Research, G6512022131, Common Genetic Determinants of Asthma and COPD-PROGRAM PROJECT, G794209665, G821063702, G9000000934, G9000023607, G9000056548, G9000111170, G9000273487, G9000319496, SYSTEMS APPROACHES TO THE EPIDEMIOLOGY, GENETICS AND GENOMICS OF LUNG DISEASES
OpenAlex ID: W2138699833