Sibling comparisons elucidate the associations between educational attainment polygenic scores and alcohol, nicotine and cannabis.
paper
Primary
Public
- Authors
- Salvatore, Jessica E; Barr, Peter B; Stephenson, Mallory; Aliev, Fazil; Kuo, Sally I-Chun; Su, Jinni; Agrawal, Arpana; Almasy, Laura; Bierut, Laura; Bucholz, Kathleen; Chan, Grace; Edenberg, Howard J; Johnson, Emma C; McCutcheon, Vivia V; Meyers, Jacquelyn L; Schuckit, Marc; Tischfield, Jay; Wetherill, Leah; Dick, Danielle M
- Year
- 2020
- Journal
- Addiction (Abingdon, England)
- PMID
- 31659820
- DOI
- 10.1111/add.14815
- PMCID
- PMC7034661
BACKGROUND AND AIMS: The associations between low educational attainment and substance use disorders (SUDs) may be related to a common genetic vulnerability. We aimed to elucidate the associations between polygenic scores for educational attainment and clinical criterion counts for three SUDs (alcohol, nicotine and cannabis). DESIGN: Polygenic association and sibling comparison methods. The latter strengthens inferences in observational research by controlling for confounding factors that differ between families. SETTING: Six sites in the United States. PARTICIPANTS: European ancestry participants aged 25 years and older from the Collaborative Study on the Genetics of Alcoholism (COGA). Polygenic association analyses included 5582 (54% female) participants. Sibling comparisons included 3098 (52% female) participants from 1226 sibling groups nested within the overall sample. MEASUREMENTS: Outcomes included criterion counts for DSM-5 alcohol use disorder (AUDSX), Fagerström nicotine dependence (NDSX) and DSM-5 cannabis use disorder (CUDSX). We derived polygenic scores for educational attainment (EduYears-GPS) using summary statistics from a large (> 1 million) genome-wide association study of educational attainment. FINDINGS: In polygenic association analyses, higher EduYears-GPS predicted lower AUDSX, NDSX and CUDSX [P < 0.01, effect sizes (R ) ranging from 0.30 to 1.84%]. These effects were robust in sibling comparisons, where sibling differences in EduYears-GPS predicted all three SUDs (P < 0.05, R 0.13-0.20%). CONCLUSIONS: Individuals who carry more alleles associated with educational attainment tend to meet fewer clinical criteria for alcohol, nicotine and cannabis use disorders, and these effects are robust to rigorous controls for potentially confounding factors that differ between families (e.g. socio-economic status, urban-rural residency and parental education).
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| Name | Type |
|---|---|
| Age at last interview local | phenotype |
| alcohol | phenotype |
| alcohol dependence | phenotype |
| Alcohol Problems | phenotype |
| Alcohol Use Disorder | phenotype |
| attention deficit hyperactivity disorder | phenotype |
| AUD | phenotype |
| behavior problems | phenotype |
| cannabis use | phenotype |
| cannabis use disorder | phenotype |
| COGA European ancestry participants local | cohort |
| COGA (European ancestry subset) local | cohort |
| COGA sample | cohort |
| Cohort_1896-1930 local | cohort |
| Cohort_1930-1950 local | cohort |
| Cohort_1950-1970 local | cohort |
| Cohort_1970-2010 local | cohort |
| Collaborative Study on the Genetics of Alcoholism (COGA) | cohort |
| complex behavioral outcomes | phenotype |
| CUDsx | phenotype |
| educational attainment | phenotype |
| educational attainment polygenic score local | variant |
| educational attainment polygenic scores local | phenotype |
| Educational persistence local | phenotype |
| EduYears-deviation local | phenotype |
| EduYears-GPS local | drug |
| EduYears-GPS local | phenotype |
| EduYears-GPS local | variant |
| EduYears-GPS-deviation local | drug |
| EduYears-GPS-deviation local | phenotype |
| EduYears-GPS-deviation local | variant |
| EduYears-GPS-mean local | drug |
| EduYears-GPS-mean local | phenotype |
| EduYears-GPS-mean local | variant |
| EduYears-mean local | phenotype |
| European ancestry | cohort |
| European ancestry biological full siblings local | cohort |
| families | cohort |
| Family polygenic loading local | phenotype |
| full sample | cohort |
| Genetic ancestry PC1 local | phenotype |
| Genetic ancestry PC2 local | phenotype |
| Illumina Human1M array | drug |
| Illumina OmniExpress | drug |
| linear mixed model analyses local | cohort |
| living arrangements | phenotype |
| mediating phenotypes local | phenotype |
| NDSX local | phenotype |
| nicotine | drug |
| nicotine dependence | phenotype |
| non-European ancestry | cohort |
| personality traits | phenotype |
| Plink | drug |
| polygenic loading local | phenotype |
| polygenic risk score | cohort |
| sex | phenotype |
| sibling comparison analyses local | cohort |
| sibling data local | cohort |
| Sibling educational attainment differences local | phenotype |
| sibling GWAS sample local | cohort |
| sibling GWAS samples local | cohort |
| Sibling polygenic differences local | phenotype |
| siblings | cohort |
| sibling subsample local | cohort |
| Smokescreen local | drug |
| smoking | phenotype |
| SNP | cohort |
| SSAGA | cohort |
| SSGAC | cohort |
| study cohort | cohort |
| substance use | phenotype |
| SUD | phenotype |
| SUD criterion count local | phenotype |
| SUD criterion counts | phenotype |
| Twin cohort | cohort |
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