| Title: | Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use |
| Journal: | Biological Psychiatry |
| Published: | 6 Dec 2018 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/30679032/ |
| DOI: | https://doi.org/10.1016/j.biopsych.2018.11.024 |
| URL: | http://www.biologicalpsychiatryjournal.com/article/S0006322318320560/pdf |
| Citations: | 74 (21 in last 2 years) as of 8 Aug 2024 |
Publication 2694
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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.</p>
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.</p>
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.</p>
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.</p>
12 Keywords
- Alcohol Drinking
- Databases, Genetic
- Exome
- Genetic Predisposition to Disease
- Genetic Variation
- Genome-Wide Association Study
- Genotype
- Humans
- Oligonucleotide Array Sequence Analysis
- Phenotype
- Polymorphism, Single Nucleotide
- Smoking
188 Authors
- David M. Brazel
- Yu Jiang
- Jordan M. Hughey
- Valérie Turcot
- Xiaowei Zhan
- Jian Gong
- Chiara Batini
- J. Dylan Weissenkampen
- MengZhen Liu
- CHD Exome+ Consortium
- Praveen Surendran
- Robin Young
- Daniel R. Barnes
- Sune Fallgaard Nielsen
- Asif Rasheed
- Maria Samuel
- Wei Zhao
- Jukka Kontto
- Markus Perola
- Muriel 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
- EPIC-CVD Consortium
- Philippe Frossard
- Børge Grønne Nordestgaard
- Danish Saleheen
- John Danesh
- Adam S. Butterworth
- Joanna M.M. Howson
- Consortium for Genetics of Smoking Behaviour
- A. Mesut Erzurumluoglu
- Victoria E. Jackson
- Carl A. Melbourne
- Tibor V. Varga
- Helen R. Warren
- Vinicius Tragante
- Ioanna Tachmazidou
- Sarah E. Harris
- Evangelos Evangelou
- Jonathan Marten
- Weihua Zhang
- Elisabeth Altmaier
- Jian'an Luan
- Claudia Langenberg
- Robert A. Scott
- Hanieh Yaghootkar
- Kathleen Stirrups
- Stavroula Kanoni
- Eirini Marouli
- Fredrik Karpe
- Anna F. Dominiczak
- Peter Sever
- Neil Poulter
- Olov Rolandsson
- Clemens Baumbach
- Saima Afaq
- John C. Chambers
- Jaspal S. Kooner
- Nicholas J. Wareham
- Frida Renström
- Göran Hallmans
- Riccardo E. Marioni
- Janie Corley
- John M. Starr
- Niek Verweij
- Rudolf A. de Boer
- Peter van der Meer
- Ersin Yavas
- Ilonca Vaartjes
- Michiel L. Bots
- Folkert W. Asselbergs
- Hans J. Grabe
- Henry Völzke
- Matthias Nauck
- Stefan Weiss
- Paul D.P. Pharoah
- Alison M. Dunning
- Joe G. Dennis
- Deborah J. Thompson
- Kyriaki Michailidou
- Douglas F. Easton
- Antonis C. Antoniou
- Jessica Tyrrell
- Evelin Mihailov
- Nilesh J. Samani
- Kaixin Zhou
- Matthew J. Neville
- Andres Metspalu
- Colin N.A. Palmer
- Ian P. Hall
- David P. Strachan
- Ian J. Deary
- Tim M. Frayling
- Caroline Hayward
- Pim van der Harst
- Eleftheria Zeggini
- Understanding Society Scientific Group
- Patricia B. Munroe
- Jan-Håkan Jansson
- Paul W. Franks
- Panos Deloukas
- Mark J. Caulfield
- Louise V. Wain
- Martin D. Tobin
- Daniel R. Barnes
- Sarah Bertelsen
- Yi-Ling Chou
- A. Mesut Erzurumluoglu
- Jessica D. Faul
- Jeff Haessler
- Anke R. Hammerschlag
- Chris Hsu
- Manav Kapoor
- Dongbing Lai
- Nhung Le
- Christiaan A. de Leeuw
- Anu Loukola
- Massimo Mangino
- Carl A. Melbourne
- Giorgio Pistis
- Beenish Qaiser
- Rebecca Rohde
- Yaming Shao
- Heather Stringham
- Leah Wetherill
- Wei Zhao
- Arpana Agrawal
- Laura Bierut
- Chu Chen
- Charles B. Eaton
- Alison Goate
- Christopher Haiman
- Andrew Heath
- William G. Iacono
- Nicholas G. Martin
- Tinca J. Polderman
- Alex Reiner
- John Rice
- David Schlessinger
- H. Steven Scholte
- Jennifer A. Smith
- Jean-Claude Tardif
- Hilary A. Tindle
- Andries R. van der Leij
- Michael Boehnke
- Jenny Chang-Claude
- Francesco Cucca
- Sean P. David
- Tatiana Foroud
- Joanna M.M. Howson
- Sharon L.R. Kardia
- Charles Kooperberg
- Markku Laakso
- Guillaume Lettre
- Pamela Madden
- Matt McGue
- Kari North
- Danielle Posthuma
- Timothy Spector
- Daniel Stram
- Martin D. Tobin
- David R. Weir
- Jaakko Kaprio
- Gonçalo R. Abecasis
- Dajiang J. Liu
- Scott Vrieze
1 Application
| Application ID | Title |
|---|---|
| 16651 | Genetic architecture of disease and related anthropometric phenotypes |
Enabling scientific discoveries that improve human health