Exploration of a polygenic risk score for alcohol consumption: A longitudinal analysis from the ALSPAC cohort

Michelle Taylor, Andrew Simpkin, Philip Haycock, Frank Dudbridge, Luisa Zuccolo

Research output: Contribution to journalArticle (Academic Journal)peer-review

19 Citations (Scopus)
355 Downloads (Pure)


Background: 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. Methods: 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. Results: 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. Conclusion: 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.
Original languageEnglish
Article numbere0167360
Number of pages15
JournalPLoS ONE
Issue number11
Publication statusPublished - 30 Nov 2016


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