Genome‐wide association studies of alcohol dependence, DSM‐IV criterion count and individual criteria

Lai, Dongbing; Wetherill, Leah; Bertelsen, Sarah; Carey, Caitlin E.; Kamarajan, Chella; Kapoor, Manav; Meyers, Jacquelyn L.; Anokhin, Andrey P.; Bennett, David A.; Bucholz, Kathleen K.; Chang, Kai-Ting; Jager, Philip L. De; Dick, Danielle M.; Hesselbrock, Victor; Kramer, John; Kuperman, Samuel; Nürnberger, John I.; Raj, Towfique; Schuckit, Marc A.; Scott, Denise M.; Taylor, Robert E.; Tischfield, Jay A.; Hariri, Ahmad R.; Edenberg, Howard J.; Agrawal, Arpana; Bogdan, Ryan; Porjesz, Bernice; Goate, Alison; Foroud, Tatiana

doi:10.1111/gbb.12579

Cited by 63 publications

(85 citation statements)

References 93 publications

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“…The large meta-analysis of AUD GWAS summary statistics (N=48,545 AUD cases and 187,065 controls) from the Million Veterans Program (MVP) 19 , the Psychiatric Genetics consortium (PGC-SUD) 12 and the Collaborative Studies on Genetics of Alcoholism (COGA) 20 identified 1157 SNPs (31 independent lead SNPs) within or near 79 genes at 10 independent loci associated with AUD. We didn't include UKB-AUDIT-P in this meta-analysis to specifically focus on AUD.…”

Section: Results: Aud Meta-analysismentioning

confidence: 99%

Multi-omics integration analysis identifies novel genes for alcoholism with potential link to neurodegenerative diseases

Kapoor

Chao

Johnson³

et al. 2020

Preprint

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Significance: Identification of causal variants and genes underlying genome-wide association study (GWAS) loci is essential to understanding the biology of alcohol use disorder (AUD). Methods: Integration of multi-omics data is often necessary to nominate candidate causal variants and genes and prioritize them for follow up studies. Here, we used Mendelian randomization to integrate AUD and drinks per week (DPW) GWAS summary statistics with the gene expression and methylation quantitative trait loci (eQTLs and mQTLs) in the largest brain and myeloid datasets. We also used AUD-related single cell epigenetic data to nominate candidate causal variants and genes associated with DPW and AUD. Results: Our multi-omics integration analyses prioritized unique as well as shared genes and pathways among AUD and DPW. The GWAS variants associated with both AUD and DPW showed significant enrichment in the promoter regions of fetal and adult brains. The integration of GWAS SNPs with mQTLs from fetal brain prioritized variants on chromosome 11 in both AUD and DPW GWASs. The co-localized variants were found to be overlapping with promoter marks for SPI1, specifically in human microglia, the myeloid cells of the brain. The co-localized SNPs were also strongly associated with SPI1 mRNA expression in myeloid cells from peripheral blood. The prioritized variant at this locus is predicted to alter the binding site for a transcription factor, RXRA, a key player in the regulation of myeloid cell function. Our analysis also identified MAPT as a candidate causal gene specifically associated with DPW. mRNA expression of MAPT was also correlated with daily amounts of alcohol intake in post-mortem brains (frontal cortex) from alcoholics and controls (N = 92). Results may be queried and visualized in an online public resource of these integrative analysis (https://lcad.shinyapps.io/alc_multiomics/). These results highlight overlap between causal genes for neurodegenerative diseases, alcohol use disorder and alcohol consumption. In conclusion, integrating GWAS summary statistics with multi-omics datasets from multiple sources identified biological similarities and differences between typical alcohol intake and disordered drinking highlighting molecular heterogeneity that might inform future targeted functional and cross-species studies. Interestingly, overlap was also observed with causal genes for neurodegenerative diseases.

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Section: Results: Aud Meta-analysismentioning

confidence: 99%

Multi-omics integration analysis identifies novel genes for alcoholism with potential link to neurodegenerative diseases

Kapoor

Chao

Johnson³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

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“…Participants came from the Collaborative Study on the Genetics of Alcoholism (COGA) , whose objective is to identify genes involved in alcohol dependence and related disorders. Probands (i.e.…”

Section: Methodsmentioning

confidence: 99%

“…Quality control and imputation procedures are described in Lai et al . and in the Supporting information, section S1.…”

Section: Methodsmentioning

confidence: 99%

Sibling comparisons elucidate the associations between educational attainment polygenic scores and alcohol, nicotine and cannabis

et al. 2019

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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 2 ) 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 2 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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“…Animal models provide an opportunity to evaluate the role of newly identified genes (Table 1) at the molecular, cellular and circuit level. We may also be able to perform human genetic studies of specific components of AUD such as DSM-IV AD criterion count (67) and alcohol withdrawal (68). To date these traits have only been studied in smaller samples but this approach will be invaluable as sample sizes increase.…”

Section: Limitations and Future Directionsmentioning

confidence: 99%

Recent Efforts to Dissect the Genetic Basis of Alcohol Use and Abuse

Sanchez‐Roige

Palmer

Clarke

2020

Biological Psychiatry

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Alcohol use disorders (AUD) are defined by several symptom criteria, which can be further dissected at the genetic level. Over the past several years, our understanding of the genetic factors influencing alcohol use and abuse has progressed tremendously; hundreds of loci have now been implicated in different aspects of alcohol use. Previously known associations with alcohol metabolizing enzymes (ADH1B, ALDH2) have been definitively replicated. Additionally, novel associations with loci containing the genes KLB, GCKR, CRHR1 and CADM2 have been reported. Downstream analyses have leveraged these genetic findings to reveal important relationships between alcohol use behaviors and both physical and mental health. AUD and aspects of alcohol misuse have been shown to overlap strongly with psychiatric disorders, whereas aspects of alcohol consumption have shown stronger links to metabolism. These results demonstrate that the genetic architecture of alcohol consumption only partially overlaps with the genetics of clinically defined AUD. We discuss the limitations of using quantitative measures of alcohol use as proxy measures for AUD, and outline how future studies will require careful phenotype harmonization to properly capture the genetic liability to AUD.

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Genome‐wide association studies of alcohol dependence, DSM‐IV criterion count and individual criteria

Cited by 63 publications

References 93 publications

Multi-omics integration analysis identifies novel genes for alcoholism with potential link to neurodegenerative diseases

Multi-omics integration analysis identifies novel genes for alcoholism with potential link to neurodegenerative diseases

Sibling comparisons elucidate the associations between educational attainment polygenic scores and alcohol, nicotine and cannabis

Recent Efforts to Dissect the Genetic Basis of Alcohol Use and Abuse

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