A Quantitative-Trait Genome-Wide Association Study of Alcoholism Risk in the Community: Findings and Implications
Background Given moderately strong genetic contributions to variation in alcoholism and heaviness of drinking (50% to 60% heritability) with high correlation of genetic influences, we have conducted a quantitative trait genome-wide association study (GWAS) for phenotypes related to alcohol use and d...
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creator | Heath, Andrew C Whitfield, John B Martin, Nicholas G Pergadia, Michele L Goate, Alison M Lind, Penelope A McEvoy, Brian P Schrage, Andrew J Grant, Julia D Chou, Yi-Ling Zhu, Rachel Henders, Anjali K Medland, Sarah E Gordon, Scott D Nelson, Elliot C Agrawal, Arpana Nyholt, Dale R Bucholz, Kathleen K Madden, Pamela A.F Montgomery, Grant W |
description | Background Given moderately strong genetic contributions to variation in alcoholism and heaviness of drinking (50% to 60% heritability) with high correlation of genetic influences, we have conducted a quantitative trait genome-wide association study (GWAS) for phenotypes related to alcohol use and dependence. Methods Diagnostic interview and blood/buccal samples were obtained from sibships ascertained through the Australian Twin Registry. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed with 8754 individuals (2062 alcohol-dependent cases) selected for informativeness for alcohol use disorder and associated quantitative traits. Family-based association tests were performed for alcohol dependence, dependence factor score, and heaviness of drinking factor score, with confirmatory case-population control comparisons using an unassessed population control series of 3393 Australians with genome-wide SNP data. Results No findings reached genome-wide significance ( p = 8.4 × 10−8 for this study), with lowest p value for primary phenotypes of 1.2 × 10−7 . Convergent findings for quantitative consumption and diagnostic and quantitative dependence measures suggest possible roles for a transmembrane protein gene ( TMEM108 ) and for ANKS1A . The major finding, however, was small effect sizes estimated for individual SNPs, suggesting that hundreds of genetic variants make modest contributions (1/4% of variance or less) to alcohol dependence risk. Conclusions We conclude that 1) meta-analyses of consumption data may contribute usefully to gene discovery; 2) translation of human alcoholism GWAS results to drug discovery or clinically useful prediction of risk will be challenging; and 3) through accumulation across studies, GWAS data may become valuable for improved genetic risk differentiation in research in biological psychiatry (e.g., prospective high-risk or resilience studies). |
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Methods Diagnostic interview and blood/buccal samples were obtained from sibships ascertained through the Australian Twin Registry. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed with 8754 individuals (2062 alcohol-dependent cases) selected for informativeness for alcohol use disorder and associated quantitative traits. Family-based association tests were performed for alcohol dependence, dependence factor score, and heaviness of drinking factor score, with confirmatory case-population control comparisons using an unassessed population control series of 3393 Australians with genome-wide SNP data. Results No findings reached genome-wide significance ( p = 8.4 × 10−8 for this study), with lowest p value for primary phenotypes of 1.2 × 10−7 . Convergent findings for quantitative consumption and diagnostic and quantitative dependence measures suggest possible roles for a transmembrane protein gene ( TMEM108 ) and for ANKS1A . The major finding, however, was small effect sizes estimated for individual SNPs, suggesting that hundreds of genetic variants make modest contributions (1/4% of variance or less) to alcohol dependence risk. Conclusions We conclude that 1) meta-analyses of consumption data may contribute usefully to gene discovery; 2) translation of human alcoholism GWAS results to drug discovery or clinically useful prediction of risk will be challenging; and 3) through accumulation across studies, GWAS data may become valuable for improved genetic risk differentiation in research in biological psychiatry (e.g., prospective high-risk or resilience studies).</description><identifier>ISSN: 0006-3223</identifier><identifier>EISSN: 1873-2402</identifier><identifier>DOI: 10.1016/j.biopsych.2011.02.028</identifier><identifier>PMID: 21529783</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Alcohol Drinking - genetics ; Alcoholism ; Alcoholism - diagnosis ; Alcoholism - genetics ; Case-Control Studies ; Genetic Predisposition to Disease - genetics ; genome-wide association ; Genome-Wide Association Study - statistics & numerical data ; Genotype ; Humans ; nonreplication ; Phenotype ; Polymorphism, Single Nucleotide ; Psychiatry ; quantitative trait ; Quantitative Trait Loci - genetics ; Residence Characteristics</subject><ispartof>Biological psychiatry (1969), 2011-09, Vol.70 (6), p.513-518</ispartof><rights>Society of Biological Psychiatry</rights><rights>2011 Society of Biological Psychiatry</rights><rights>Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.</rights><rights>2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved. 2011</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c525t-6b932ae4c490bd1adef4102ac297fbfb8cf10ef2723ef21b715793c451f281e73</citedby><cites>FETCH-LOGICAL-c525t-6b932ae4c490bd1adef4102ac297fbfb8cf10ef2723ef21b715793c451f281e73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0006322311002101$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,776,780,881,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21529783$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Heath, Andrew C</creatorcontrib><creatorcontrib>Whitfield, John B</creatorcontrib><creatorcontrib>Martin, Nicholas G</creatorcontrib><creatorcontrib>Pergadia, Michele L</creatorcontrib><creatorcontrib>Goate, Alison M</creatorcontrib><creatorcontrib>Lind, Penelope A</creatorcontrib><creatorcontrib>McEvoy, Brian P</creatorcontrib><creatorcontrib>Schrage, Andrew J</creatorcontrib><creatorcontrib>Grant, Julia D</creatorcontrib><creatorcontrib>Chou, Yi-Ling</creatorcontrib><creatorcontrib>Zhu, Rachel</creatorcontrib><creatorcontrib>Henders, Anjali K</creatorcontrib><creatorcontrib>Medland, Sarah E</creatorcontrib><creatorcontrib>Gordon, Scott D</creatorcontrib><creatorcontrib>Nelson, Elliot C</creatorcontrib><creatorcontrib>Agrawal, Arpana</creatorcontrib><creatorcontrib>Nyholt, Dale R</creatorcontrib><creatorcontrib>Bucholz, Kathleen K</creatorcontrib><creatorcontrib>Madden, Pamela A.F</creatorcontrib><creatorcontrib>Montgomery, Grant W</creatorcontrib><title>A Quantitative-Trait Genome-Wide Association Study of Alcoholism Risk in the Community: Findings and Implications</title><title>Biological psychiatry (1969)</title><addtitle>Biol Psychiatry</addtitle><description>Background Given moderately strong genetic contributions to variation in alcoholism and heaviness of drinking (50% to 60% heritability) with high correlation of genetic influences, we have conducted a quantitative trait genome-wide association study (GWAS) for phenotypes related to alcohol use and dependence. Methods Diagnostic interview and blood/buccal samples were obtained from sibships ascertained through the Australian Twin Registry. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed with 8754 individuals (2062 alcohol-dependent cases) selected for informativeness for alcohol use disorder and associated quantitative traits. Family-based association tests were performed for alcohol dependence, dependence factor score, and heaviness of drinking factor score, with confirmatory case-population control comparisons using an unassessed population control series of 3393 Australians with genome-wide SNP data. Results No findings reached genome-wide significance ( p = 8.4 × 10−8 for this study), with lowest p value for primary phenotypes of 1.2 × 10−7 . Convergent findings for quantitative consumption and diagnostic and quantitative dependence measures suggest possible roles for a transmembrane protein gene ( TMEM108 ) and for ANKS1A . The major finding, however, was small effect sizes estimated for individual SNPs, suggesting that hundreds of genetic variants make modest contributions (1/4% of variance or less) to alcohol dependence risk. Conclusions We conclude that 1) meta-analyses of consumption data may contribute usefully to gene discovery; 2) translation of human alcoholism GWAS results to drug discovery or clinically useful prediction of risk will be challenging; and 3) through accumulation across studies, GWAS data may become valuable for improved genetic risk differentiation in research in biological psychiatry (e.g., prospective high-risk or resilience studies).</description><subject>Alcohol Drinking - genetics</subject><subject>Alcoholism</subject><subject>Alcoholism - diagnosis</subject><subject>Alcoholism - genetics</subject><subject>Case-Control Studies</subject><subject>Genetic Predisposition to Disease - genetics</subject><subject>genome-wide association</subject><subject>Genome-Wide Association Study - statistics & numerical data</subject><subject>Genotype</subject><subject>Humans</subject><subject>nonreplication</subject><subject>Phenotype</subject><subject>Polymorphism, Single Nucleotide</subject><subject>Psychiatry</subject><subject>quantitative trait</subject><subject>Quantitative Trait Loci - genetics</subject><subject>Residence Characteristics</subject><issn>0006-3223</issn><issn>1873-2402</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFUttq3DAQNaWl2ab9haAf8FYj-dqH0GVJ0kCgtEnpo5DlcXY2trS15AX_fbXZJLR9KQwSYuac0ZwzSXIGfAkcio_bZUNu52ezWQoOsOQiRvUqWUBVylRkXLxOFpzzIpVCyJPknffb-CyFgLfJiYBc1GUlF8mvFfs2aRso6EB7TO9GTYFdoXUDpj-pRbby3hmKWWfZbZjambmOrXrjNq4nP7Dv5B8YWRY2yNZuGCZLYf7ELsm2ZO8907Zl18OuJ_PI4d8nbzrde_zwdJ8mPy4v7tZf0puvV9fr1U1qcpGHtGhqKTRmJqt504JuscuAC23ix7umayrTAcdOlELGE5oS8rKWJsuhExVgKU-T8yPvbmoGbA3aMOpe7UYa9Dgrp0n9nbG0Ufdur6QAXtRZJCiOBGZ03o_YvWCBq4MJaqueTVAHExQXMaoIPPuz8wvsWfVY8PlYgHH-PeGovCG0Blsa0QTVOvp_j_N_KExPNmrcP-CMfuum0UZ1FSgfAer2sAqHTQDgPM4H8jc3xrPr</recordid><startdate>20110915</startdate><enddate>20110915</enddate><creator>Heath, Andrew C</creator><creator>Whitfield, John B</creator><creator>Martin, Nicholas G</creator><creator>Pergadia, Michele L</creator><creator>Goate, Alison M</creator><creator>Lind, Penelope A</creator><creator>McEvoy, Brian P</creator><creator>Schrage, Andrew J</creator><creator>Grant, Julia D</creator><creator>Chou, Yi-Ling</creator><creator>Zhu, Rachel</creator><creator>Henders, Anjali K</creator><creator>Medland, Sarah E</creator><creator>Gordon, Scott D</creator><creator>Nelson, Elliot C</creator><creator>Agrawal, Arpana</creator><creator>Nyholt, Dale R</creator><creator>Bucholz, Kathleen K</creator><creator>Madden, Pamela A.F</creator><creator>Montgomery, Grant W</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>5PM</scope></search><sort><creationdate>20110915</creationdate><title>A Quantitative-Trait Genome-Wide Association Study of Alcoholism Risk in the Community: Findings and Implications</title><author>Heath, Andrew C ; Whitfield, John B ; Martin, Nicholas G ; Pergadia, Michele L ; Goate, Alison M ; Lind, Penelope A ; McEvoy, Brian P ; Schrage, Andrew J ; Grant, Julia D ; Chou, Yi-Ling ; Zhu, Rachel ; Henders, Anjali K ; Medland, Sarah E ; Gordon, Scott D ; Nelson, Elliot C ; Agrawal, Arpana ; Nyholt, Dale R ; Bucholz, Kathleen K ; Madden, Pamela A.F ; Montgomery, Grant W</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c525t-6b932ae4c490bd1adef4102ac297fbfb8cf10ef2723ef21b715793c451f281e73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Alcohol Drinking - genetics</topic><topic>Alcoholism</topic><topic>Alcoholism - diagnosis</topic><topic>Alcoholism - genetics</topic><topic>Case-Control Studies</topic><topic>Genetic Predisposition to Disease - genetics</topic><topic>genome-wide association</topic><topic>Genome-Wide Association Study - statistics & numerical data</topic><topic>Genotype</topic><topic>Humans</topic><topic>nonreplication</topic><topic>Phenotype</topic><topic>Polymorphism, Single Nucleotide</topic><topic>Psychiatry</topic><topic>quantitative trait</topic><topic>Quantitative Trait Loci - genetics</topic><topic>Residence Characteristics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Heath, Andrew C</creatorcontrib><creatorcontrib>Whitfield, John B</creatorcontrib><creatorcontrib>Martin, Nicholas G</creatorcontrib><creatorcontrib>Pergadia, Michele L</creatorcontrib><creatorcontrib>Goate, Alison M</creatorcontrib><creatorcontrib>Lind, Penelope A</creatorcontrib><creatorcontrib>McEvoy, Brian P</creatorcontrib><creatorcontrib>Schrage, Andrew J</creatorcontrib><creatorcontrib>Grant, Julia D</creatorcontrib><creatorcontrib>Chou, Yi-Ling</creatorcontrib><creatorcontrib>Zhu, Rachel</creatorcontrib><creatorcontrib>Henders, Anjali K</creatorcontrib><creatorcontrib>Medland, Sarah E</creatorcontrib><creatorcontrib>Gordon, Scott D</creatorcontrib><creatorcontrib>Nelson, Elliot C</creatorcontrib><creatorcontrib>Agrawal, Arpana</creatorcontrib><creatorcontrib>Nyholt, Dale R</creatorcontrib><creatorcontrib>Bucholz, Kathleen K</creatorcontrib><creatorcontrib>Madden, Pamela A.F</creatorcontrib><creatorcontrib>Montgomery, Grant W</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Biological psychiatry (1969)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Heath, Andrew C</au><au>Whitfield, John B</au><au>Martin, Nicholas G</au><au>Pergadia, Michele L</au><au>Goate, Alison M</au><au>Lind, Penelope A</au><au>McEvoy, Brian P</au><au>Schrage, Andrew J</au><au>Grant, Julia D</au><au>Chou, Yi-Ling</au><au>Zhu, Rachel</au><au>Henders, Anjali K</au><au>Medland, Sarah E</au><au>Gordon, Scott D</au><au>Nelson, Elliot C</au><au>Agrawal, Arpana</au><au>Nyholt, Dale R</au><au>Bucholz, Kathleen K</au><au>Madden, Pamela A.F</au><au>Montgomery, Grant W</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Quantitative-Trait Genome-Wide Association Study of Alcoholism Risk in the Community: Findings and Implications</atitle><jtitle>Biological psychiatry (1969)</jtitle><addtitle>Biol Psychiatry</addtitle><date>2011-09-15</date><risdate>2011</risdate><volume>70</volume><issue>6</issue><spage>513</spage><epage>518</epage><pages>513-518</pages><issn>0006-3223</issn><eissn>1873-2402</eissn><abstract>Background Given moderately strong genetic contributions to variation in alcoholism and heaviness of drinking (50% to 60% heritability) with high correlation of genetic influences, we have conducted a quantitative trait genome-wide association study (GWAS) for phenotypes related to alcohol use and dependence. Methods Diagnostic interview and blood/buccal samples were obtained from sibships ascertained through the Australian Twin Registry. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed with 8754 individuals (2062 alcohol-dependent cases) selected for informativeness for alcohol use disorder and associated quantitative traits. Family-based association tests were performed for alcohol dependence, dependence factor score, and heaviness of drinking factor score, with confirmatory case-population control comparisons using an unassessed population control series of 3393 Australians with genome-wide SNP data. Results No findings reached genome-wide significance ( p = 8.4 × 10−8 for this study), with lowest p value for primary phenotypes of 1.2 × 10−7 . Convergent findings for quantitative consumption and diagnostic and quantitative dependence measures suggest possible roles for a transmembrane protein gene ( TMEM108 ) and for ANKS1A . The major finding, however, was small effect sizes estimated for individual SNPs, suggesting that hundreds of genetic variants make modest contributions (1/4% of variance or less) to alcohol dependence risk. Conclusions We conclude that 1) meta-analyses of consumption data may contribute usefully to gene discovery; 2) translation of human alcoholism GWAS results to drug discovery or clinically useful prediction of risk will be challenging; and 3) through accumulation across studies, GWAS data may become valuable for improved genetic risk differentiation in research in biological psychiatry (e.g., prospective high-risk or resilience studies).</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>21529783</pmid><doi>10.1016/j.biopsych.2011.02.028</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Alcohol Drinking - genetics Alcoholism Alcoholism - diagnosis Alcoholism - genetics Case-Control Studies Genetic Predisposition to Disease - genetics genome-wide association Genome-Wide Association Study - statistics & numerical data Genotype Humans nonreplication Phenotype Polymorphism, Single Nucleotide Psychiatry quantitative trait Quantitative Trait Loci - genetics Residence Characteristics |
title | A Quantitative-Trait Genome-Wide Association Study of Alcoholism Risk in the Community: Findings and Implications |
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