Incorporating Functional Genomic Information to Enhance Polygenic Signal and Identify Variants Involved in Gene-by-Environment Interaction for Young Adult Alcohol Problems.
- 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.
Schematic of DHS- and GW-polygenic score creation in the FinnTwin12 sample using an illustrative p-value of p < 0.01. The GW-score is the weighted linear combination of all SNPs meeting p < 0.01 in the discovery sample (ALSPAC) GWAS (Edwards et al., 2015). The DHS-score is the weighted linear combination of the subset of SNPs meeting p < 0.01 in the discovery sample GWAS that were also located in a DHS site. Abbreviations: DHS = DNase I hypersensitive site; GWAS = Genome-wide association study; LD = linkage disequilibrium; SNP = single nucleotide polymorphism.
| 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 |
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In this knowledge base
| Title | Year | PMID |
|---|---|---|
| Psychosocial moderation of polygenic risk for cannabis involvement: the role of trauma exposure and frequency of religious service attendance. | 2019 | 31636251 |
External
| Title | Authors | Journal | Year | Link |
|---|---|---|---|---|
| Polygenic Score for Smoking is associated with Externalizing Psychopathology and Disinhibited Personality Traits but not Internalizing Psychopathology in Adolescence. | Hicks BM et al. | — | 2021 | → |
| Polygenic scores for smoking and educational attainment have independent influences on academic success and adjustment in adolescence and educational attainment in adulthood. | Hicks BM et al. | — | 2021 | → |
| Using Genetic Marginal Effects to Study Gene-Environment Interactions with GWAS Data. | Verhulst B et al. | — | 2021 | → |
| Recent Efforts to Dissect the Genetic Basis of Alcohol Use and Abuse. | Sanchez-Roige S et al. | — | 2020 | → |
| FinnTwin12 Cohort: An Updated Review. | Rose RJ et al. | — | 2019 | → |
| Psychosocial moderation of polygenic risk for cannabis involvement: the role of trauma exposure and frequency of religious service attendance. | Meyers JL et al. | — | 2019 | → |
| Systematic Review of Polygenic Gene-Environment Interaction in Tobacco, Alcohol, and Cannabis Use. | Pasman JA et al. | — | 2019 | → |