Sensitivity Analyses for Pleiotropy in Mendelian Randomization

Several sensitivity analyses were used to check and correct for the presence of pleiotropy in the causal estimates. Cochran’s Q was computed to quantify heterogeneity across the individual causal effects, with a P-value ≤ 0.05 indicating the presence of pleiotropy, and that consequently, a random effects IVW MR analysis should be used^{43 (link),48 (link)}. We also assessed the potential presence of horizontal pleiotropy using MR-Egger regression based on its intercept term, where deviation from zero denotes the presence of directional pleiotropy. Additionally, the slope of the MR-Egger regression provides valid MR estimates in the presence of horizontal pleiotropy when the pleiotropic effects of the genetic variants are independent from the genetic associations with the exposure^{49 (link),50 (link)}. We also computed OR estimates using the complementary weighted-median method that can give valid MR estimates under the presence of horizontal pleiotropy when up to 50% of the included instruments are invalid^{44 (link)}. The presence of pleiotropy was also assessed using the MR-PRESSO. In this, outlying SNPs are excluded from the accelerometer-measured physical activity instrument and the effect estimates are reassessed^{51 (link)}. For all of the aforementioned sensitivity analyses to identify possible pleiotropy, we considered the estimates from the extended 10 SNP instrument as the primary results due to unstable estimates from the 5 SNP instrument. A leave-one-SNP out analysis was also conducted to assess the influence of individual variants on the observed associations. We also examined the selected genetic instruments and their proxies (r² > 0.8) and their associations with secondary phenotypes (P-value < 5 × 10⁻⁸) in Phenoscanner (http://www.phenoscanner.medschl.cam.ac.uk/) and GWAS catalog (date checked April 2019).
For the extended 10 SNP instrument, we also conducted multivariable MR analyses to adjust for potential pleiotropy due to BMI because the initial GWAS on physical activity reported several strong associations (P-value < 10⁻⁵) between the identified SNPs and BMI^{52 (link)}. The new estimates correspond to the direct causal effect of physical activity with the BMI being fixed. The genetic data on BMI were obtained from a GWAS study published by The Genetic Investigation of ANthropometric Traits (GIANT) consortium^{53 (link)} (Supplementary Table 9). Additionally, for the extended 10 SNP instrument, we also conducted analyses with adiposity-related SNPs (i.e. those previously associated with BMI, waist circumference, weight, or body/trunk fat percentage in GWAS studies at P-value < 10⁻⁸) excluded (n = 5; rs34517439, rs6775319, rs11012732, rs1550435, rs59499656). Finally, we conducted two-sample MR analyses using BMI adjusted GWAS estimates for the 5 SNP accelerometer-measured physical activity instrument^{11 (link)}. However, the MR results using the BMI adjusted GWAS estimates should be interpreted cautiously due to the potential for collider bias^{11 (link)}.
All the analyses were conducted using the MendelianRandomisation^{54 (link)} and TwoSampleMR^{55 (link)} packages, and the R programming language.

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Papadimitriou N., Dimou N., Tsilidis K.K., Banbury B., Martin R.M., Lewis S.J., Kazmi N., Robinson T.M., Albanes D., Aleksandrova K., Berndt S.I., Timothy Bishop D., Brenner H., Buchanan D.D., Bueno-de-Mesquita B., Campbell P.T., Castellví-Bel S., Chan A.T., Chang-Claude J., Ellingjord-Dale M., Figueiredo J.C., Gallinger S.J., Giles G.G., Giovannucci E., Gruber S.B., Gsur A., Hampe J., Hampel H., Harlid S., Harrison T.A., Hoffmeister M., Hopper J.L., Hsu L., María Huerta J., Huyghe J.R., Jenkins M.A., Keku T.O., Kühn T., La Vecchia C., Le Marchand L., Li C.I., Li L., Lindblom A., Lindor N.M., Lynch B., Markowitz S.D., Masala G., May A.M., Milne R., Monninkhof E., Moreno L., Moreno V., Newcomb P.A., Offit K., Perduca V., Pharoah P.D., Platz E.A., Potter J.D., Rennert G., Riboli E., Sánchez M.J., Schmit S.L., Schoen R.E., Severi G., Sieri S., Slattery M.L., Song M., Tangen C.M., Thibodeau S.N., Travis R.C., Trichopoulou A., Ulrich C.M., van Duijnhoven F.J., Van Guelpen B., Vodicka P., White E., Wolk A., Woods M.O., Wu A.H., Peters U., Gunter M.J, & Murphy N. (2020). Physical activity and risks of breast and colorectal cancer: a Mendelian randomisation analysis. Nature Communications, 11, 597.

Publication 2020

Adiposity Body fat Fat body Genetic Genetic variants Gwas Heterogeneity Phenotypes Sensitivity Waist circumference

Corresponding Organization :

Other organizations : Centre International de Recherche sur le Cancer, University of Ioannina, Fred Hutch Cancer Center, University of Bristol, National Cancer Institute, National Institutes of Health, German Institute of Human Nutrition, University of Leeds, Heidelberg University, German Cancer Research Center, University of Melbourne, National Institute for Public Health and the Environment, American Cancer Society, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas, Universitat de Barcelona, Consorci Institut D'Investigacions Biomediques August Pi I Sunyer, Harvard University, Massachusetts General Hospital, Imperial College London, Cedars-Sinai Medical Center, Mount Sinai Hospital, University of Toronto, Lunenfeld-Tanenbaum Research Institute, University of Southern California, TU Dresden, The Ohio State University, Umeå University, Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública, University of North Carolina at Chapel Hill, Hellenic Health Foundation, University of Hawaiʻi at Mānoa, University of Hawaii System, Cancer Center of Hawaii, Karolinska University Hospital, Mayo Clinic in Arizona, University Hospitals of Cleveland, Case Western Reserve University, Piedmont Reference Center for Epidemiology and Cancer Prevention, Utrecht University, University Medical Center Utrecht, Cancer Council Victoria, Memorial Sloan Kettering Cancer Center, Université Paris-Saclay, Centre de recherche en Epidémiologie et Santé des Populations, Université de Versailles Saint-Quentin-en-Yvelines, Université Paris-Sud, University of Cambridge, Johns Hopkins University, Carmel Medical Center, University of Pittsburgh Medical Center, Fondazione IRCCS Istituto Nazionale dei Tumori, University of Utah, Mayo Clinic, University of Oxford, Huntsman Cancer Institute, Wageningen University & Research, Czech Academy of Sciences, Institute of Experimental Medicine, University of Washington, Karolinska Institutet, Memorial University of Newfoundland

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