Genome-wide association studies and Mendelian randomization analyses for leisure sedentary behaviours - Supplementary Data Files

Published: 10 March 2020| Version 1 | DOI: 10.17632/mxjj6czsrd.1
Contributors:
Yordi van de Vegte,
,
,
,

Description

Supplementary data files related to the article "Genome-wide association studies and Mendelian randomization analyses for leisure sedentary behaviours" by van de Vegte et al.

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Ascertainment of sedentary time During the first visit, participants were asked three questions, “In a typical DAY, how many hours do you spend watching TV?”, “In a typical DAY, how many hours do you spend using the computer? (Do not include using a computer at work)” and “In a typical DAY, how many hours do you spend driving?". Participants outside a 99.5% range on the right side of the normal distribution were excluded on a per-phenotype basis, since the sedentary phenotypes were right-skewed. Genotyping and imputation The Wellcome Trust Centre for Human Genetics performed genotyping, quality control before imputation and imputed to HRC v1.1 panel. Analysis has been restricted to variants that are in the HRC v1.1. Quality control of samples and variants, and imputation was performed by the Wellcome Trust Centre for Human Genetics. Minor Allele Frequency (MAF) of 0.5% and INFO-score of more than 0.3 was used in post-GWAS analysis. Genome-wide association study All three sedentary phenotypes were inverse rank normalized in order to obtain normally distributed data. Genome wide association analysis in UK Biobank was performed using BOLT-LMM v2.3beta2, employing a mixed linear model that corrects for population structure and cryptic relatedness. Leisure television watching, leisure computer use and driving were adjusted for age-squared, age, sex, age-sex interaction, the first 30 principal components (PCA’s) to correct for population stratification and genotyping array (Affymetrix UK Biobank Axiom array or Affymetrix UK BiLEVE Axiom array). Participants were excluded if they were of non-European ancestries (n=78,372) in order to reduce non-polygenetic signals. We used the PLINK clumping procedure for each sedentary phenotype separately to prune genetic variants at a stringent linkage disequilibrium (LD) of R2<0.005 within a five megabase window into a set of independently associated variants. Genetic loci were determined by assessing the highest associated variants in a one megabase region at either side of the independent variants. We combined all loci of the sedentary phenotypes and again searched within a one megabase region at either side to obtain the highest associated locus in order to receive a set of independent genetic loci associated with sedentary behaviour in general. Since the current study is the only population-based study of sedentary behaviours, independent cohorts that matched this study in size and availability of variables (specific questions assessing different subtypes of sedentary behaviour combined with genetics) were unavailable for replication purposes. Therefore, only loci that reached a stringent (two-sided) genome-wide significant threshold of P<1 × 10−8 were taken forward, in order to account for multiple independent traits in line with other multi phenotype studies.

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Genome Wide Association Study

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