Exploration of a Polygenic Risk Score for Alcohol Consumption: A Longitudinal Analysis from the ALSPAC Cohort.

<h4>Background</h4>Uncertainty remains about the true extent by which alcohol consumption causes a number of health outcomes. Genetic variants, or combinations of variants built into a polygenic risk score (PGRS), can be used in an instrumental variable framework to assess causality betw...

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Main Authors: Michelle Taylor, Andrew J Simpkin, Philip C Haycock, Frank Dudbridge, Luisa Zuccolo
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0167360
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spelling doaj-3651938dbcf84b6aa6ec74eb285833302021-03-04T12:31:34ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-011111e016736010.1371/journal.pone.0167360Exploration of a Polygenic Risk Score for Alcohol Consumption: A Longitudinal Analysis from the ALSPAC Cohort.Michelle TaylorAndrew J SimpkinPhilip C HaycockFrank DudbridgeLuisa Zuccolo<h4>Background</h4>Uncertainty remains about the true extent by which alcohol consumption causes a number of health outcomes. Genetic variants, or combinations of variants built into a polygenic risk score (PGRS), can be used in an instrumental variable framework to assess causality between a phenotype and disease outcome of interest, a method known as Mendelian randomisation (MR). We aimed to identify genetic variants involved in the aetiology of alcohol consumption, and develop a PGRS for alcohol.<h4>Methods</h4>Repeated measures of alcohol consumption from mothers and their offspring were collected as part of the Avon Longitudinal Study of Parents and Children. We tested the association between 89 SNPs (identified from either published GWAS data or from functional literature) and repeated measures of alcohol consumption, separately in mothers (from ages 28-48) and offspring (from ages 15-21) who had ever reported drinking. We modelled log units of alcohol using a linear mixed model and calculated beta coefficients for each SNP separately. Cross-validation was used to determine an allelic score for alcohol consumption, and the AVENGEME algorithm employed to estimate variance of the trait explained.<h4>Results</h4>Following correction for multiple testing, one SNP (rs1229984) showed evidence for association with alcohol consumption (β = -0.177, SE = 0.042, p = <0.0001) in the mothers. No SNPs showed evidence for association in the offspring after correcting for multiple testing. The optimal allelic score was generated using p-value cut offs of 0.5 and 0.05 for the mothers and offspring respectively. These scores explained 0.3% and 0.7% of the variance.<h4>Conclusion</h4>Our PGRS explains a modest amount of the variance in alcohol consumption and larger sample sizes would be required to use our PGRS in an MR framework.https://doi.org/10.1371/journal.pone.0167360
collection DOAJ
language English
format Article
sources DOAJ
author Michelle Taylor
Andrew J Simpkin
Philip C Haycock
Frank Dudbridge
Luisa Zuccolo
spellingShingle Michelle Taylor
Andrew J Simpkin
Philip C Haycock
Frank Dudbridge
Luisa Zuccolo
Exploration of a Polygenic Risk Score for Alcohol Consumption: A Longitudinal Analysis from the ALSPAC Cohort.
PLoS ONE
author_facet Michelle Taylor
Andrew J Simpkin
Philip C Haycock
Frank Dudbridge
Luisa Zuccolo
author_sort Michelle Taylor
title Exploration of a Polygenic Risk Score for Alcohol Consumption: A Longitudinal Analysis from the ALSPAC Cohort.
title_short Exploration of a Polygenic Risk Score for Alcohol Consumption: A Longitudinal Analysis from the ALSPAC Cohort.
title_full Exploration of a Polygenic Risk Score for Alcohol Consumption: A Longitudinal Analysis from the ALSPAC Cohort.
title_fullStr Exploration of a Polygenic Risk Score for Alcohol Consumption: A Longitudinal Analysis from the ALSPAC Cohort.
title_full_unstemmed Exploration of a Polygenic Risk Score for Alcohol Consumption: A Longitudinal Analysis from the ALSPAC Cohort.
title_sort exploration of a polygenic risk score for alcohol consumption: a longitudinal analysis from the alspac cohort.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2016-01-01
description <h4>Background</h4>Uncertainty remains about the true extent by which alcohol consumption causes a number of health outcomes. Genetic variants, or combinations of variants built into a polygenic risk score (PGRS), can be used in an instrumental variable framework to assess causality between a phenotype and disease outcome of interest, a method known as Mendelian randomisation (MR). We aimed to identify genetic variants involved in the aetiology of alcohol consumption, and develop a PGRS for alcohol.<h4>Methods</h4>Repeated measures of alcohol consumption from mothers and their offspring were collected as part of the Avon Longitudinal Study of Parents and Children. We tested the association between 89 SNPs (identified from either published GWAS data or from functional literature) and repeated measures of alcohol consumption, separately in mothers (from ages 28-48) and offspring (from ages 15-21) who had ever reported drinking. We modelled log units of alcohol using a linear mixed model and calculated beta coefficients for each SNP separately. Cross-validation was used to determine an allelic score for alcohol consumption, and the AVENGEME algorithm employed to estimate variance of the trait explained.<h4>Results</h4>Following correction for multiple testing, one SNP (rs1229984) showed evidence for association with alcohol consumption (β = -0.177, SE = 0.042, p = <0.0001) in the mothers. No SNPs showed evidence for association in the offspring after correcting for multiple testing. The optimal allelic score was generated using p-value cut offs of 0.5 and 0.05 for the mothers and offspring respectively. These scores explained 0.3% and 0.7% of the variance.<h4>Conclusion</h4>Our PGRS explains a modest amount of the variance in alcohol consumption and larger sample sizes would be required to use our PGRS in an MR framework.
url https://doi.org/10.1371/journal.pone.0167360
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