Dataset Information

Incorporating Functional Genomic Information to Enhance Polygenic Signal and Identify Variants Involved in Gene-by-Environment Interaction for Young Adult Alcohol Problems.

ABSTRACT: BACKGROUND:Characterizing aggregate genetic risk for alcohol misuse and identifying variants involved in gene-by-environment (G × E) interaction effects has so far been a major challenge. We hypothesized that functional genomic information could be used to enhance detection of polygenic signal underlying alcohol misuse and to prioritize identification of single nucleotide polymorphisms (SNPs) most likely to exhibit G × E effects. METHODS:We examined these questions in the young adult FinnTwin12 sample (n = 1,170). We used genomewide association estimates from an independent sample to derive 2 types of polygenic scores for alcohol problems in FinnTwin12. Genomewide polygenic scores included all SNPs surpassing a designated p-value threshold. DNase polygenic scores were a subset of the genomewide polygenic scores including only variants in DNase I hypersensitive sites (DHSs), which are open chromatin marks likely to index regions with a regulatory function. We conducted parallel analyses using height as a nonpsychiatric model phenotype to evaluate the consistency of effects. For the G × E analyses, we examined whether SNPs in DHSs were overrepresented among SNPs demonstrating significant G × E effects in an interaction between romantic relationship status and intoxication frequency. RESULTS:Contrary to our expectations, we found that DNase polygenic scores were not more strongly predictive of alcohol problems than conventional polygenic scores. However, variants in DNase polygenic scores had per-SNP effects that were up to 1.4 times larger than variants in conventional polygenic scores. This same pattern of effects was also observed in supplementary analyses with height. In G × E models, SNPs in DHSs were modestly overrepresented among SNPs with significant interaction effects for intoxication frequency. CONCLUSIONS:These findings highlight the potential utility of integrating functional genomic annotation information to increase the signal-to-noise ratio in polygenic scores and identify genetic variants that may be most susceptible to environmental modification.

SUBMITTER: Salvatore JE

PROVIDER: S-EPMC5785466 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Incorporating Functional Genomic Information to Enhance Polygenic Signal and Identify Variants Involved in Gene-by-Environment Interaction for Young Adult Alcohol Problems.

Salvatore Jessica E JE Savage Jeanne E JE Barr Peter P Wolen Aaron R AR Aliev Fazil F Vuoksimaa Eero E Latvala Antti A Pulkkinen Lea L Rose Richard J RJ Kaprio Jaakko J Dick Danielle M DM

Alcoholism, clinical and experimental research 20171219 2

<h4>Background</h4>Characterizing aggregate genetic risk for alcohol misuse and identifying variants involved in gene-by-environment (G × E) interaction effects has so far been a major challenge. We hypothesized that functional genomic information could be used to enhance detection of polygenic signal underlying alcohol misuse and to prioritize identification of single nucleotide polymorphisms (SNPs) most likely to exhibit G × E effects.<h4>Methods</h4>We examined these questions in the young ad ...[more]

PMID: 29121402

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Project description:Background and aimsMolecular genetic studies of alcohol and nicotine use have identified many genome-wide association study (GWAS) loci. We measured associations between drinking and smoking polygenic scores (PGS) and trajectories of alcohol and nicotine use outcomes from late childhood to early adulthood, substance-specific versus broader-liability PGS effects, and if PGS performance varied for consumption versus problematic substance use.Design, setting, participants and measurementsWe fitted latent growth curve models with structured residuals to scores on measures of alcohol and nicotine use and problems from ages 14 to 34 years. We then estimated associations between the intercept (initial status) and slope (rate of change) parameters and PGSs for drinks per week (DPW), problematic alcohol use (PAU), cigarettes per day (CPD) and ever being a regular smoker (SMK), controlling for sex and genetic principal components. All data were analyzed in the United States. PGSs were calculated for participants of the Minnesota Twin Family Study (n = 3225) using results from the largest GWAS of alcohol and nicotine consumption and problematic use to date.FindingsEach PGS was associated with trajectories of use for their respective substances [i.e. DPW (βmean = 0.08; βrange = 0.02-0.12) and PAU (βmean = 0.12; βrange = -0.02 to 0.31) for alcohol; CPD (βmean = 0.08; βrange = 0.04-0.14) and SMK (βmean = 0.18; βrange = 0.05-0.36) for nicotine]. The PAU and SMK PGSs also exhibited cross-substance associations (i.e. PAU for nicotine-specific intercepts and SMK for alcohol intercepts and slope). All identified SMK PGS effects remained as significant predictors of nicotine and alcohol trajectories (βmean = 0.15; βrange = 0.02-0.33), even after adjusting for the respective effects of all other PGSs.ConclusionsSubstance use-related polygenic scores (PGSs) vary in the strength and generality versus specificity of their associations with substance use and problems over time. The regular smoking PGS appears to be a robust predictor of substance use trajectories and seems to measure both nicotine-specific and non-specific genetic liability for substance use, and potentially externalizing problems in general.

Dataset Information

Incorporating Functional Genomic Information to Enhance Polygenic Signal and Identify Variants Involved in Gene-by-Environment Interaction for Young Adult Alcohol Problems.

Publications

Incorporating Functional Genomic Information to Enhance Polygenic Signal and Identify Variants Involved in Gene-by-Environment Interaction for Young Adult Alcohol Problems.

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