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A pseudolikelihood approach for assessing genetic association in case-control studies with unmeasured population structure.
Chen, Yong; Liang, Kung-Yee; Tong, Pan; Beaty, Terri H; Barnes, Kathleen C; Linda Kao, W H.
Afiliação
  • Chen Y; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, USA.
  • Liang KY; National Health Research Institutes, Zhunan, Taiwan.
  • Tong P; Department of Bioinformatics & Computational Biology, University of Texas, Houston, USA.
  • Beaty TH; Department of Epidemiology, Johns Hopkins University, Baltimore, USA.
  • Barnes KC; University of Colorado Denver - Anschutz Medical Campus, Aurora, USA.
  • Linda Kao WH; Department of Epidemiology, Johns Hopkins University, Baltimore, USA.
Stat Methods Med Res ; 29(11): 3153-3165, 2020 11.
Article em En | MEDLINE | ID: mdl-32393154
The case-control study design is one of the main tools for detecting associations between genetic markers and diseases. It is well known that population substructure can lead to spurious association between disease status and a genetic marker if the prevalence of disease and the marker allele frequency vary across subpopulations. In this paper, we propose a novel statistical method to estimate the association in case-control studies with unmeasured population substructure. The proposed method takes two steps. First, the information on genomic markers and disease status is used to infer the population substructure; second, the association between the disease and the test marker adjusting for the population substructure is modeled and estimated parametrically through polytomous logistic regression. The performance of the proposed method, relative to the existing methods, on bias, coverage probability and computational time, is assessed through simulations. The method is applied to an end-stage renal disease study in African Americans population.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Marcadores Genéticos / Estudos de Casos e Controles Tipo de estudo: Observational_studies Limite: Humans Idioma: En Revista: Stat Methods Med Res Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Marcadores Genéticos / Estudos de Casos e Controles Tipo de estudo: Observational_studies Limite: Humans Idioma: En Revista: Stat Methods Med Res Ano de publicação: 2020 Tipo de documento: Article