000 02494 am a22002293u 4500
042 _adc
100 1 0 _aGkatzionis, Apostolos
_eauthor
_92686
700 1 0 _aBurgess, Stephen
_eauthor
700 1 0 _aNewcombe, Paul J.
_eauthor
_92687
245 0 0 _aStatistical methods for cis‐Mendelian randomization with two‐sample summary‐level data
260 _bJohn Wiley and Sons Inc.,
_c2022-10-23.
500 _a/pmc/articles/PMC7614127/
500 _a/pubmed/36273411
520 _aMendelian randomization (MR) is the use of genetic variants to assess the existence of a causal relationship between a risk factor and an outcome of interest. Here, we focus on two‐sample summary‐data MR analyses with many correlated variants from a single gene region, particularly on cis‐MR studies which use protein expression as a risk factor. Such studies must rely on a small, curated set of variants from the studied region; using all variants in the region requires inverting an ill‐conditioned genetic correlation matrix and results in numerically unstable causal effect estimates. We review methods for variable selection and estimation in cis‐MR with summary‐level data, ranging from stepwise pruning and conditional analysis to principal components analysis, factor analysis, and Bayesian variable selection. In a simulation study, we show that the various methods have comparable performance in analyses with large sample sizes and strong genetic instruments. However, when weak instrument bias is suspected, factor analysis and Bayesian variable selection produce more reliable inferences than simple pruning approaches, which are often used in practice. We conclude by examining two case studies, assessing the effects of low‐density lipoprotein‐cholesterol and serum testosterone on coronary heart disease risk using variants in the HMGCR and SHBG gene regions, respectively.
540 _a© 2022 The Authors. Genetic Epidemiology published by Wiley Periodicals LLC.
540 _ahttps://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
546 _aen
690 _aResearch Articles
655 7 _aText
_2local
786 0 _nGenet Epidemiol
856 4 1 _uhttp://dx.doi.org/10.1002/gepi.22506
_zConnect to this object online.
999 _c2218
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