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 language | English (US) |
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Pages (from-to) | 946-955 |
Number of pages | 10 |
Journal | Biological psychiatry |
Volume | 85 |
Issue number | 11 |
DOIs | |
State | Published - Jun 1 2019 |
Bibliographical note
Funding Information:This research has been conducted using the UK Biobank Resource under Application Number 16651. This work was supported by the National Institute on Drug Abuse and the National Human Genome Research Institute of the National Institutes of Health Grant Nos. R01DA037904 (to SIV), R21DA040177 (to DJL), R01HG008983 (to DJL), R01GM126479 (to DJL), and 5T32DA017637-13 (to DMB); funding sources listed in the Supplementary Note; and a National Science Foundation Graduate Research Fellowship (to JMH). This material is based on work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE1255832 (to JMH). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s)and do not necessarily reflect the views of the National Science Foundation. The complete funding statements and acknowledgments for participating consortia are available in Supplement 1. GRA is an employee of Regeneron Pharmaceuticals. All other individually named authors report no biomedical financial interests or potential conflicts of interest. The members of the Consortium for Genetics of Smoking Behaviour report the following: Paul W. Franks has been a paid consultant for Eli Lilly and Sanofi Aventis and has received research support from several pharmaceutical companies as part of European Union Innovative Medicines Initiative (IMI)projects. Neil Poulter has received financial support from several pharmaceutical companies that manufacture either blood pressure lowering or lipid lowering agents or both and consultancy fees. Peter Sever has received research awards from Pfizer. Mark J. Caulfield is Chief Scientist for Genomics England, a UK government company.
Funding Information:
This research has been conducted using the UK Biobank Resource under Application Number 16651. This work was supported by the National Institute on Drug Abuse and the National Human Genome Research Institute of the National Institutes of Health Grant Nos. R01DA037904 (to SIV), R21DA040177 (to DJL), R01HG008983 (to DJL), R01GM126479 (to DJL), and 5T32DA017637-13 (to DMB); funding sources listed in the Supplementary Note; and a National Science Foundation Graduate Research Fellowship (to JMH).
Funding Information:
This research has been conducted using the UK Biobank Resource under Application Number 16651. This work was supported by the National Institute on Drug Abuse and the National Human Genome Research Institute of the National Institutes of Health Grant Nos. R01DA037904 (to SIV), R21DA040177 (to DJL), R01HG008983 (to DJL), R01GM126479 (to DJL), and 5T32DA017637-13 (to DMB); funding sources listed in the Supplementary Note; and a National Science Foundation Graduate Research Fellowship (to JMH).This material is based on work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE1255832 (to JMH). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.The members of the Consortium for Genetics of Smoking Behaviour report the following: Paul W. Franks has been a paid consultant for Eli Lilly and Sanofi Aventis and has received research support from several pharmaceutical companies as part of European Union Innovative Medicines Initiative (IMI) projects. Neil Poulter has received financial support from several pharmaceutical companies that manufacture either blood pressure lowering or lipid lowering agents or both and consultancy fees. Peter Sever has received research awards from Pfizer. Mark J. Caulfield is Chief Scientist for Genomics England, a UK government company.
Publisher Copyright:
© 2018 Society of Biological Psychiatry
Keywords
- Alcohol
- Behavioral genetics
- GWAS
- Heritability
- Nicotine
- Tobacco