Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use

CHD Exome+ Consortium, Consortium for Genetics of Smoking Behaviour, David M. Brazel, Yu Jiang, Jordan M. Hughey, Valérie Turcot, Xiaowei Zhan, Jian Gong, Chiara Batini, J. Dylan Weissenkampen, Meng Zhen Liu, Praveen Surendran, Robin Young, Daniel R. Barnes, Sune Fallgaard Nielsen, Asif Rasheed, Maria Samuel, Wei Zhao, Jukka Kontto, Markus PerolaMuriel Caslake, Anton J.M. de Craen, Stella Trompet, Maria Uria-Nickelsen, Anders Malarstig, Dermot F. Reily, Maarten Hoek, Thomas Vogt, J. Wouter Jukema, Naveed Sattar, Ian Ford, Chris J. Packard, Dewan S. Alam, Abdulla al Shafi Majumder, Emanuele Di Angelantonio, Rajiv Chowdhury, Philippe Amouyel, Dominique Arveiler, Stefan Blankenberg, Jean Ferrières, Frank Kee, Kari Kuulasmaa, Martina Müller-Nurasyid, Giovanni Veronesi, Jarmo Virtamo, Consortium EPIC-CVD Consortium, Philippe Frossard, Børge Grønne Nordestgaard, Danish Saleheen, John Danesh, Adam S. Butterworth, Dajiang Liu

Research output: Contribution to journalArticle

9 Scopus citations

Abstract

Background: Smoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences and to contribute to disease risk. Methods: We analyzed ∼250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack-years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-variant tests, and gene-based burden tests of nonsynonymous/loss-of-function coding variants. We performed a novel fine-mapping analysis to winnow the number of putative causal variants within associated loci. Results: Meta-analytic sample sizes ranged from 152,348 to 433,216, depending on the phenotype. Rare coding variation explained 1.1% to 2.2% of phenotypic variance, reflecting 11% to 18% of the total single nucleotide polymorphism heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between three and 10 variants for 65 loci. Twenty loci contained rare coding variants in the 95% credible intervals. Conclusions: Rare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine-mapping genome-wide association study loci identifies specific variants contributing to the biological etiology of substance use behavior.

Original languageEnglish (US)
Pages (from-to)946-955
Number of pages10
JournalBiological Psychiatry
Volume85
Issue number11
DOIs
StatePublished - Jun 1 2019

All Science Journal Classification (ASJC) codes

  • Biological Psychiatry

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    CHD Exome+ Consortium, Consortium for Genetics of Smoking Behaviour, Brazel, D. M., Jiang, Y., Hughey, J. M., Turcot, V., Zhan, X., Gong, J., Batini, C., Weissenkampen, J. D., Liu, M. Z., Surendran, P., Young, R., Barnes, D. R., Nielsen, S. F., Rasheed, A., Samuel, M., Zhao, W., Kontto, J., ... Liu, D. (2019). Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use. Biological Psychiatry, 85(11), 946-955. https://doi.org/10.1016/j.biopsych.2018.11.024