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

paper Cited Public

Authors: Salvatore, Jessica E; Savage, Jeanne E; Barr, Peter; Wolen, Aaron R; Aliev, Fazil; Vuoksimaa, Eero; Latvala, Antti; Pulkkinen, Lea; Rose, Richard J; Kaprio, Jaakko; Dick, Danielle M
Year: 2018
Journal: Alcoholism, clinical and experimental research
PMID: 29121402
DOI: 10.1111/acer.13551
PMCID: PMC5785466

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.

#	Section	Preview
40	Discussion — Limitations	Sixth, our environmental moderator (romantic relationship status) captures only one of many…
41	Discussion — Limitations	to detect interactions. On a more conceptual level, we note that previous analyses using the…
42	Discussion — Conclusions and Future Directions	These findings highlight the potential utility of integrating genomic annotation information in…

Name	Type
1000 Genomes Phase I (v3) reference panel local	cohort
1000 Genomes Project	cohort
additive genetic factor local	gene
ADsx	phenotype
ADsx criteria local	phenotype
age	phenotype
aggregate DHS score local	variant
aggregate GW score local	variant
alcohol	phenotype
Alcohol Dependence Symptoms	phenotype
alcohol intoxication	phenotype
Alcohol Problems	phenotype
alcohol problems factor score	phenotype
alcohol-related behaviors	phenotype
alcohol-related outcomes	phenotype
alcohol-related phenotypes	phenotype
Alcohol Use	phenotype
Alcohol Use Disorder	phenotype
ALSPAC	cohort
Avon Longitudinal Study of Parents and Children	cohort
brain tissue samples local	anatomy
complex diseases and traits local	phenotype
complex psychiatric disorders local	phenotype
complex traits	phenotype
cystic fibrosis	phenotype
DHS region variant local	variant
DHSs local	variant
DHS-scores local	cohort
DHS-scores local	drug
DHS SNP local	variant
DHS SNPs local	variant
DHS variants local	variant
discovery GWAS	cohort
DNase I	drug
DNase I-restricted polygenic scores local	drug
ENCODE Project Consortium local	cohort
environment	drug
environmental exposures	drug
environmental inputs local	drug
European ancestry	cohort
Finnish population	cohort
Finnish twins	cohort
Finntwin12	cohort
FinnTwin12 dataset local	cohort
FinnTwin12 study local	cohort
G×E effect local	phenotype
gene-by-environment interaction effects local	phenotype
gene expression	phenotype
genes	gene
genetic variants	cohort
GIANT consortium	cohort
GW-scores local	cohort
GW-scores local	drug
GW SNPs local	variant
HapMap2 CEU local	cohort
Health-related behaviors local	phenotype
height	phenotype
Human670-QuadCustom Illumina BeadChip	drug
Huntington’s disease	phenotype
inferred genotype local	variant
intoxication frequency	phenotype
Intoxication measures local	phenotype
lifetime alcohol use	phenotype
MAOA	gene
mixed European ancestry	cohort
non-DHS SNPs local	variant
non-DHS variants local	variant
phenotype	phenotype
polygenic risk score	cohort
psychiatric assessment at age 22 local	phenotype
regulatory region local	drug
Relationship duration ≥1 year local	phenotype
Relationship involvement local	phenotype
relationship status	phenotype
risky drinking	phenotype
RoadMap tissue lines local	cohort
schizophrenia	phenotype
sex	phenotype
significant G×E effects local	phenotype
SLC6A4	gene
SNP	cohort
The International Schizophrenia Consortium local	cohort
transcription factors	drug
Twin cohort	cohort

Citation	PMID	DOI	Status
Aliev, F et al., Behav Genet, 2014, Testing for measured gene-environment interaction: problems with the use of cross-product terms and a regression model reparameterization solution	24531874	10.1007/s10519-014-9642-1	Cited
Anttila, V et al., Analysis of shared heritability in common disorders of the brain	—	—	—
Barr, PB et al., J Stud Alcohol Drugs, Social relationships moderate genetic influences on heavy drinking in young adulthood	29087815	10.15288/jsad.2017.78.817	Cited
Bell, O et al., Nat Rev Genet, 2011, Determinants and dynamics of genome accessibility	21747402	10.1038/nrg3017	Cited
Bucholz, KK et al., J Stud Alcohol, 1994, A new, semi-structured psychiatric interview for use in genetic linkage studies: A report on the reliability of the SSAGA	8189735	10.15288/jsa.1994.55.149	Primary
Chang, CC et al., Gigascience, 2015, Second-generation PLINK: rising to the challenge of larger and richer datasets	25722852	10.1186/s13742-015-0047-8	Cited
Cockerill, PN, FEBS J, 2011, Structure and function of active chromatin and DNase I hypersensitive sites	—	—	—
Delaneau, O et al., Nat Methods, 2012, A linear complexity phasing method for thousands of genomes	22138821	10.1038/nmeth.1785	Cited
Dick, DM et al., Alcohol Clin Exp Res, 2011, Measures of current alcohol consumption and problems: two independent twin studies suggest a complex genetic architecture	21689117	10.1111/j.1530-0277.2011.01564.x	Cited
Dick, DM et al., J Abnorm Psychol, 2001, Exploring gene-environment interactions: Socioregional moderation of alcohol use	11727951	10.1037//0021-843x.110.4.625	Cited
Dick, DM et al., Perspect Psychol Sci, 2015, Candidate gene-environment interaction research: Reflections and recommendations	25620996	10.1177/1745691614556682	Primary
Dudbridge, F, PLoS Genet, 2013, Power and predictive accuracy of polygenic risk scores	23555274	10.1371/journal.pgen.1003348	Cited
Duncan, L et al., Am J Psychiat, 2011, A critical review of the first ten years of measured gene-by-environment interaction research in psychiatry	21890791	10.1176/appi.ajp.2011.11020191	Cited
Edwards, AC et al., Addiction, 2015, Genomic influences on alcohol problems in a population-based sample of young adults	25439982	10.1111/add.12822	Cited
Finucane, HK et al., Nat Genet, 2015, Partitioning heritability by functional annotation using genome-wide association summary statistics	26414678	10.1038/ng.3404	Cited
Fleming, CB et al., J Health Soc Behav, 2010, Romantic relationships and substance use in early adulthood: An examination of the influences of relationship type, partner substance use, and relationship quality	20617756	10.1177/0022146510368930	Cited
Frank, J et al., Addict Biol, 2012, Genome-wide significant association between alcohol dependence and a variant in the ADH gene cluster	22004471	10.1111/j.1369-1600.2011.00395.x	Cited
Gauderman, WJ, Stat Med, 2002, Sample size requirements for matched case-control studies of gene-environment interaction	11782049	10.1002/sim.973	Cited
Geschwind, DH et al., Science, 2015, Genetics and genomics of psychiatric disease	26404826	10.1126/science.aaa8954	Cited
Global Status Report on Alcohol and Health, 2014	—	—	—
Gusev, A et al., Am J Hum Genet, 2014, Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases	25439723	10.1016/j.ajhg.2014.10.004	Cited
Hart, AB et al., Alcohol Clin Exp Res, 2015, Alcohol dependence genetics: lessons learned from genome-wide association studies (GWAS) and post-GWAS analyses	26110981	10.1111/acer.12792	Cited
Heath, AC et al., J Stud Alcohol, 1989, Interactive effects of genotype and social-environment on alcohol-consumption in female twins	2927121	10.15288/jsa.1989.50.38	Cited
Hindorff, LA et al., Proc Natl Acad Sci U S A, 2009, Potential etiologic and functional implications of genome-wide association loci for human diseases and traits	19474294	10.1073/pnas.0903103106	Cited
Howie, BN et al., PLoS Genet, 2009, A flexible and accurate genotype imputation method for the next generation of genome-wide association studies	19543373	10.1371/journal.pgen.1000529	Cited
Jarnecke, AM et al., Alcohol Clin Exp Res, 2014, Genetic and environmental influences on alcohol use problems: Moderation by romantic partner support, but not family or friend support	24164253	10.1111/acer.12263	Cited
Kaprio, J et al., Twin Res, 2002, Genetic and environmental factors in health-related behaviors: Studies on Finnish twins and twin families	12537860	10.1375/136905202320906101	Cited
Kaprio, J, Twin Res Hum Genet, 2013, The Finnish Twin Cohort Study: an update	23298696	10.1017/thg.2012.142	Cited
Kos, MZ et al., Genes Brain Behav, 2013, Common biological networks underlie genetic risk for alcoholism in African- and European-American populations	23607416	10.1111/gbb.12043	Primary
Levey, DF et al., Transl Psychiatry, 2014, Genetic risk prediction and neurobiological understanding of alcoholism	24844177	10.1038/tp.2014.29	Cited
Liu, L et al., Curr Issues Mol Biol, 2008, Gene-environment interactions and epigenetic basis of human diseases	18525104	—	Cited
Lopez-Maury, L et al., Nat Rev Genet, 2008, Tuning gene expression to changing environments: from rapid responses to evolutionary adaptation	18591982	10.1038/nrg2398	Cited
Maher, BS, Curr Epidemiol Rep, 2015, Polygenic Scores in Epidemiology: Risk Prediction, Etiology, and Clinical Utility	26664818	10.1007/s40471-015-0055-3	Cited
Manolio, TA et al., Nature, 2009, Finding the missing heritability of complex diseases	19812666	10.1038/nature08494	Cited
Maurano, MT et al., Science, 2012, Systematic localization of common disease-associated variation in regulatory DNA	22955828	10.1126/science.1222794	Cited
Mbarek, H et al., Am J Med Genet B Neuropsychiatr Genet, 2015, The genetics of alcohol dependence: Twin and SNP-based heritability, and genome-wide association study based on AUDIT scores	26365420	10.1002/ajmg.b.32379	Cited
Meaney, MJ, Child Dev, 2010, Epigenetics and the biological definition of gene x environment interactions	20331654	10.1111/j.1467-8624.2009.01381.x	Cited
Meyers, J, ProQuest Dissertations & Theses Global Order No. 3523904, 2012, Elucidating genetic and environmental influences on alcohol-related phenotypes	—	—	—
Moore, SR et al., J Child Psychol Psychiatry, 2016, What is the biological reality of gene-environment interaction estimates? An assessment of bias in developmental models	27240973	10.1111/jcpp.12579	Cited
Nakagawa, S et al., Methods Ecol Evol, 2013, A general and simple method for obtaining R2 from generalized linear mixed-effects models	—	—	—
Nature, 2009, Common polygenic variation contributes to risk of schizophrenia and bipolar disorder	19571811	10.1038/nature08185	Cited
Nature, 2012, An integrated encyclopedia of DNA elements in the human genome	22955616	10.1038/nature11247	Cited
Pagan, JL et al., Behav Genet, 2006, Genetic and environmental influences on stages of alcohol use across adolescence and into young adulthood	16586152	10.1007/s10519-006-9062-y	Cited
Pickrell, JK, Am J Hum Genet, 2014, Joint analysis of functional genomic data and genome-wide association studies of 18 human traits	24702953	10.1016/j.ajhg.2014.03.004	Cited
Prescott, CA et al., J Stud Alcohol, 2001, Associations between marital status and alcohol consumption in a longitudinal study of female twins	11702798	10.15288/jsa.2001.62.589	Cited
Schork, AJ et al., PLoS Genet, 2013, All SNPs are not created equal: genome-wide association studies reveal a consistent pattern of enrichment among functionally annotated SNPs	23637621	10.1371/journal.pgen.1003449	Cited
Schumann, G et al., Proc Natl Acad Sci USA, 2016, KLB is associated with alcohol drinking, and its gene product beta-Klotho is necessary for FGF21 regulation of alcohol preference	27911795	10.1073/pnas.1611243113	Cited
Thomas, D, Nat Rev Genet, 2010, Gene-environment-wide association studies: Emerging approaches	20212493	10.1038/nrg2764	Cited
Thurman, RE et al., Nature, 2012, The accessible chromatin landscape of the human genome	22955617	10.1038/nature11232	Cited
Verhulst, B et al., Psychol Med, 2015, The heritability of alcohol use disorders: a meta-analysis of twin and adoption studies	25171596	10.1017/S0033291714002165	Cited
Vilhjalmsson, BJ et al., Am J Hum Genet, 2015, Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores	26430803	10.1016/j.ajhg.2015.09.001	Cited
Vrieze, SI et al., Behav Genet, 2013, Three mutually informative ways to understand the genetic relationships among behavioral disinhibition, alcohol use, drug use, nicotine use/dependence, and their co-occurrence: Twin biometry, GCTA, and genome-wide scoring	23362009	10.1007/s10519-013-9584-z	Cited
Wood, AR et al., Nat Genet, 2014, Defining the role of common variation in the genomic and biological architecture of adult human height	25282103	10.1038/ng.3097	Cited
Wray, NR et al., J Child Psychol Psychiatry, 2014, Research review: Polygenic methods and their application to psychiatric traits	25132410	10.1111/jcpp.12295	Cited
Yan, J et al., Addict Biol, 2014, Using genetic information from candidate gene and genome-wide association studies in risk prediction for alcohol dependence	23362995	10.1111/adb.12035	Primary
Yang, C et al., Hum Genet, 2014, Exploring the genetic architecture of alcohol dependence in African-Americans via analysis of a genomewide set of common variants	24297757	10.1007/s00439-013-1399-8	Cited
Young-Wolff, KC et al., Clin Psychol Rev, 2011, The influence of gene-environment interactions on alcohol consumption and alcohol use disorders: A comprehensive review	21530476	10.1016/j.cpr.2011.03.005	Cited

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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.

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