ArticleGenetic epidemiology2009
On the adjustment for covariates in genetic association analysis: a novel, simple principle to infer direct causal effects.
Article in Genetic epidemiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 52 citations in OpenAlex.
- Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies.Kidney international · 2022Pooled it
- Dissecting direct and indirect genetic effects on chronic obstructive pulmonary disease (COPD) susceptibility.Human genetics · 2013Trial
- Unveiling the causative role of promoter variant rs113823671 in MMP7 in gallbladder cancer susceptibility.Scientific reports · 2025Article
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- Examining the Association between Mitochondrial Genome Variation and Coronary Artery Disease.Genes · 2022Article
- Bias in two-sample Mendelian randomization when using heritable covariable-adjusted summary associations.International journal of epidemiology · 2021Article
- Impact of variant-level batch effects on identification of genetic risk factors in large sequencing studies.PloS one · 2021Article
- Ten years in: APOL1 reaches beyond the kidney.Current opinion in nephrology and hypertension · 2019Review
- Adjustment for covariates using summary statistics of genome-wide association studies.Genetic epidemiology · 2018Article
- Estimating and testing direct genetic effects in directed acyclic graphs using estimating equations.Genetic epidemiology · 2018Article
- A general approach to testing for pleiotropy with rare and common variants.Genetic epidemiology · 2017Article
- Statistical Methods for Testing Genetic Pleiotropy.Genetics · 2016Article
- Adjusting for heritable covariates can bias effect estimates in genome-wide association studies.American journal of human genetics · 2015Article
- Genome-wide association study of proneness to anger.PloS one · 2014Article
- Pleiotropy in complex traits: challenges and strategies.Nature reviews. Genetics · 2013Review
- Testing for direct genetic effects using a screening step in family-based association studies.Frontiers in genetics · 2013Article
- Causation and causal inference for genetic effects.Human genetics · 2012Review
- Methods for Analyzing Multivariate Phenotypes in Genetic Association Studies.Journal of probability and statistics · 2012Article
- Next generation analytic tools for large scale genetic epidemiology studies of complex diseases.Genetic epidemiology · 2012Article
Corrections and comments
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Authors and funding
8 authors at 5 institutions in 2 countries.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.