語言:

On the adjustment for covariates in genetic association analysis: a novel, simple principle to infer direct causal effects

Vansteelandt, Stijn ; Goetgeluk, Sylvie ; Lutz, Sharon ; Waldman, Irwin ; Lyon, Helen ; Schadt, Eric E. ; Weiss, Scott T. ; Lange, Christoph

Genetic epidemiology, 2009-07, Vol.33 (5), p.394-405 [同儕審閱期刊]

可取得全文

引用被引用

傳送到

題名:
On the adjustment for covariates in genetic association analysis: a novel, simple principle to infer direct causal effects
著者: Vansteelandt, Stijn ; Goetgeluk, Sylvie ; Lutz, Sharon ; Waldman, Irwin ; Lyon, Helen ; Schadt, Eric E. ; Weiss, Scott T. ; Lange, Christoph
主題: causal diagram ; Cohort Studies ; Computer Simulation ; direct effect ; Gene Frequency ; genetic pathways ; Genetic Predisposition to Disease ; Genetic Variation ; Genome, Human ; Genome-Wide Association Study ; Genotype ; Heart Diseases - genetics ; Humans ; mediation ; Models, Genetic ; Models, Statistical ; Phenotype ; pleiotropy ; Polymorphism, Single Nucleotide ; Research Design
所屬期刊: Genetic epidemiology, 2009-07, Vol.33 (5), p.394-405
描述: In genetic association studies, different complex phenotypes are often associated with the same marker. Such associations can be indicative of pleiotropy (i.e. common genetic causes), of indirect genetic effects via one of these phenotypes, or can be solely attributable to non‐genetic/environmental links between the traits. To identify the phenotypes with the inducing genetic association, statistical methodology is needed that is able to distinguish between the different causes of the genetic associations. Here, we propose a simple, general adjustment principle that can be incorporated into many standard genetic association tests which are then able to infer whether an SNP has a direct biological influence on a given trait other than through the SNP's influence on another correlated phenotype. Using simulation studies, we show that, in the presence of a non‐marker related link between phenotypes, standard association tests without the proposed adjustment can be biased. In contrast to that, the proposed methodology remains unbiased. Its achieved power levels are identical to those of standard adjustment methods, making the adjustment principle universally applicable in genetic association studies. The principle is illustrated by an application to three genome‐wide association analyses. Genet. Epidemiol. 33:394–405, 2009. © 2009 Wiley‐Liss, Inc.
出版者: Hoboken: Wiley Subscription Services, Inc., A Wiley Company
語言: 英文
識別號: ISSN: 0741-0395
EISSN: 1098-2272
DOI: 10.1002/gepi.20393
PMID: 19219893
資源來源: Wiley Online Library All Journals
Wiley Online Library Full Collection 2020

連結

View this record in MEDLINE/PubMed

返回到檢索清單

On the adjustment for covariates in genetic association analysis: a novel, simple principle to infer direct causal effects

Vansteelandt, Stijn ; Goetgeluk, Sylvie ; Lutz, Sharon ; Waldman, Irwin ; Lyon, Helen ; Schadt, Eric E. ; Weiss, Scott T. ; Lange, Christoph

正在檢索遠程資料庫，請稍等