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Diagnostics for Pleiotropy in Mendelian Randomization Studies

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Diagnostics for Pleiotropy in Mendelian Randomization Studies. / Dai, James Y; Peters, Ulrike; Wang, Xiaoyu; Kocarnik, Jonathan; Chang-Claude, Jenny; Slattery, Martha L; Chan, Andrew; Lemire, Mathieu; Berndt, Sonja I; Casey, Graham; Song, Mingyang; Jenkins, Mark A; Brenner, Hermann; Thrift, Aaron P; White, Emily; Hsu, Li.

In: AM J EPIDEMIOL, Vol. 187, No. 12, 01.12.2018, p. 2672-2680.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Dai, JY, Peters, U, Wang, X, Kocarnik, J, Chang-Claude, J, Slattery, ML, Chan, A, Lemire, M, Berndt, SI, Casey, G, Song, M, Jenkins, MA, Brenner, H, Thrift, AP, White, E & Hsu, L 2018, 'Diagnostics for Pleiotropy in Mendelian Randomization Studies', AM J EPIDEMIOL, vol. 187, no. 12, pp. 2672-2680. https://doi.org/10.1093/aje/kwy177

APA

Dai, J. Y., Peters, U., Wang, X., Kocarnik, J., Chang-Claude, J., Slattery, M. L., Chan, A., Lemire, M., Berndt, S. I., Casey, G., Song, M., Jenkins, M. A., Brenner, H., Thrift, A. P., White, E., & Hsu, L. (2018). Diagnostics for Pleiotropy in Mendelian Randomization Studies. AM J EPIDEMIOL, 187(12), 2672-2680. https://doi.org/10.1093/aje/kwy177

Vancouver

Dai JY, Peters U, Wang X, Kocarnik J, Chang-Claude J, Slattery ML et al. Diagnostics for Pleiotropy in Mendelian Randomization Studies. AM J EPIDEMIOL. 2018 Dec 1;187(12):2672-2680. https://doi.org/10.1093/aje/kwy177

Bibtex

@article{3ea0dda8b45c47f7bec036244bdb1b19,
title = "Diagnostics for Pleiotropy in Mendelian Randomization Studies",
abstract = "Diagnosing pleiotropy is critical for assessing the validity of Mendelian randomization (MR) analyses. The popular MR-Egger method evaluates whether there is evidence of bias-generating pleiotropy among a set of candidate genetic instrumental variables. In this article, we propose a statistical method-global and individual tests for direct effects (GLIDE)-for systematically evaluating pleiotropy among the set of genetic variants (e.g., single nucleotide polymorphisms (SNPs)) used for MR. As a global test, simulation experiments suggest that GLIDE is nearly uniformly more powerful than the MR-Egger method. As a sensitivity analysis, GLIDE is capable of detecting outliers in individual variant-level pleiotropy, in order to obtain a refined set of genetic instrumental variables. We used GLIDE to analyze both body mass index and height for associations with colorectal cancer risk in data from the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colon Cancer Family Registry (multiple studies). Among the body mass index-associated SNPs and the height-associated SNPs, several individual variants showed evidence of pleiotropy. Removal of these potentially pleiotropic SNPs resulted in attenuation of respective estimates of the causal effects. In summary, the proposed GLIDE method is useful for sensitivity analyses and improves the validity of MR.",
keywords = "Journal Article",
author = "Dai, {James Y} and Ulrike Peters and Xiaoyu Wang and Jonathan Kocarnik and Jenny Chang-Claude and Slattery, {Martha L} and Andrew Chan and Mathieu Lemire and Berndt, {Sonja I} and Graham Casey and Mingyang Song and Jenkins, {Mark A} and Hermann Brenner and Thrift, {Aaron P} and Emily White and Li Hsu",
year = "2018",
month = dec,
day = "1",
doi = "10.1093/aje/kwy177",
language = "English",
volume = "187",
pages = "2672--2680",
journal = "AM J EPIDEMIOL",
issn = "0002-9262",
publisher = "Oxford University Press",
number = "12",

}

RIS

TY - JOUR

T1 - Diagnostics for Pleiotropy in Mendelian Randomization Studies

AU - Dai, James Y

AU - Peters, Ulrike

AU - Wang, Xiaoyu

AU - Kocarnik, Jonathan

AU - Chang-Claude, Jenny

AU - Slattery, Martha L

AU - Chan, Andrew

AU - Lemire, Mathieu

AU - Berndt, Sonja I

AU - Casey, Graham

AU - Song, Mingyang

AU - Jenkins, Mark A

AU - Brenner, Hermann

AU - Thrift, Aaron P

AU - White, Emily

AU - Hsu, Li

PY - 2018/12/1

Y1 - 2018/12/1

N2 - Diagnosing pleiotropy is critical for assessing the validity of Mendelian randomization (MR) analyses. The popular MR-Egger method evaluates whether there is evidence of bias-generating pleiotropy among a set of candidate genetic instrumental variables. In this article, we propose a statistical method-global and individual tests for direct effects (GLIDE)-for systematically evaluating pleiotropy among the set of genetic variants (e.g., single nucleotide polymorphisms (SNPs)) used for MR. As a global test, simulation experiments suggest that GLIDE is nearly uniformly more powerful than the MR-Egger method. As a sensitivity analysis, GLIDE is capable of detecting outliers in individual variant-level pleiotropy, in order to obtain a refined set of genetic instrumental variables. We used GLIDE to analyze both body mass index and height for associations with colorectal cancer risk in data from the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colon Cancer Family Registry (multiple studies). Among the body mass index-associated SNPs and the height-associated SNPs, several individual variants showed evidence of pleiotropy. Removal of these potentially pleiotropic SNPs resulted in attenuation of respective estimates of the causal effects. In summary, the proposed GLIDE method is useful for sensitivity analyses and improves the validity of MR.

AB - Diagnosing pleiotropy is critical for assessing the validity of Mendelian randomization (MR) analyses. The popular MR-Egger method evaluates whether there is evidence of bias-generating pleiotropy among a set of candidate genetic instrumental variables. In this article, we propose a statistical method-global and individual tests for direct effects (GLIDE)-for systematically evaluating pleiotropy among the set of genetic variants (e.g., single nucleotide polymorphisms (SNPs)) used for MR. As a global test, simulation experiments suggest that GLIDE is nearly uniformly more powerful than the MR-Egger method. As a sensitivity analysis, GLIDE is capable of detecting outliers in individual variant-level pleiotropy, in order to obtain a refined set of genetic instrumental variables. We used GLIDE to analyze both body mass index and height for associations with colorectal cancer risk in data from the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colon Cancer Family Registry (multiple studies). Among the body mass index-associated SNPs and the height-associated SNPs, several individual variants showed evidence of pleiotropy. Removal of these potentially pleiotropic SNPs resulted in attenuation of respective estimates of the causal effects. In summary, the proposed GLIDE method is useful for sensitivity analyses and improves the validity of MR.

KW - Journal Article

U2 - 10.1093/aje/kwy177

DO - 10.1093/aje/kwy177

M3 - SCORING: Journal article

C2 - 30188971

VL - 187

SP - 2672

EP - 2680

JO - AM J EPIDEMIOL

JF - AM J EPIDEMIOL

SN - 0002-9262

IS - 12

ER -