Dataset Information

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

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.

SUBMITTER: Brazel DM

PROVIDER: S-EPMC6534468 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Publications

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

Brazel David M DM Jiang Yu Y Hughey Jordan M JM Turcot Valérie V Zhan Xiaowei X Gong Jian J Batini Chiara C Weissenkampen J Dylan JD Liu MengZhen M Barnes Daniel R DR Bertelsen Sarah S Chou Yi-Ling YL Erzurumluoglu A Mesut AM Faul Jessica D JD Haessler Jeff J Hammerschlag Anke R AR Hsu Chris C Kapoor Manav M Lai Dongbing D Le Nhung N de Leeuw Christiaan A CA Loukola Anu A Mangino Massimo M Melbourne Carl A CA Pistis Giorgio G Qaiser Beenish B Rohde Rebecca R Shao Yaming Y Stringham Heather H Wetherill Leah L Zhao Wei W Agrawal Arpana A Bierut Laura L Chen Chu C Eaton Charles B CB Goate Alison A Haiman Christopher C Heath Andrew A Iacono William G WG Martin Nicholas G NG Polderman Tinca J TJ Reiner Alex A Rice John J Schlessinger David D Scholte H Steven HS Smith Jennifer A JA Tardif Jean-Claude JC Tindle Hilary A HA van der Leij Andries R AR Boehnke Michael M Chang-Claude Jenny J Cucca Francesco F David Sean P SP Foroud Tatiana T Howson Joanna M M JMM Kardia Sharon L R SLR Kooperberg Charles C Laakso Markku M Lettre Guillaume G Madden Pamela P McGue Matt M North Kari K Posthuma Danielle D Spector Timothy T Stram Daniel D Tobin Martin D MD Weir David R DR Kaprio Jaakko J Abecasis Gonçalo R GR Liu Dajiang J DJ Vrieze Scott S

Biological psychiatry 20181206 11

<h4>Background</h4>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.<h4>Methods</h4>We analyzed ∼250,000 rare variants from 16 ...[more]

PMID: 30679032

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Project description:Background and Purpose- White matter hyperintensities (WMH) on brain magnetic resonance imaging are typical signs of cerebral small vessel disease and may indicate various preclinical, age-related neurological disorders, such as stroke. Though WMH are highly heritable, known common variants explain a small proportion of the WMH variance. The contribution of low-frequency/rare coding variants to WMH burden has not been explored. Methods- In the discovery sample we recruited 20?719 stroke/dementia-free adults from 13 population-based cohort studies within the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, among which 17?790 were of European ancestry and 2929 of African ancestry. We genotyped these participants at ?250?000 mostly exonic variants with Illumina HumanExome BeadChip arrays. We performed ethnicity-specific linear regression on rank-normalized WMH in each study separately, which were then combined in meta-analyses to test for association with single variants and genes aggregating the effects of putatively functional low-frequency/rare variants. We then sought replication of the top findings in 1192 adults (European ancestry) with whole exome/genome sequencing data from 2 independent studies. Results- At 17q25, we confirmed the association of multiple common variants in TRIM65, FBF1, and ACOX1 ( P<6×10-7). We also identified a novel association with 2 low-frequency nonsynonymous variants in MRPL38 (lead, rs34136221; PEA=4.5×10-8) partially independent of known common signal ( PEA(conditional)=1.4×10-3). We further identified a locus at 2q33 containing common variants in NBEAL1, CARF, and WDR12 (lead, rs2351524; Pall=1.9×10-10). Although our novel findings were not replicated because of limited power and possible differences in study design, meta-analysis of the discovery and replication samples yielded stronger association for the 2 low-frequency MRPL38 variants ( Prs34136221=2.8×10-8). Conclusions- Both common and low-frequency/rare functional variants influence WMH. Larger replication and experimental follow-up are essential to confirm our findings and uncover the biological causal mechanisms of age-related WMH.

Dataset Information

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

Publications

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

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