Multi-omics integration analysis identifies novel genes for alcoholism with potential overlap with neurodegenerative diseases.
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Author
Kapoor, ManavChao, Michael J
Johnson, Emma C
Novikova, Gloriia
Lai, Dongbing
Meyers, Jacquelyn L
Schulman, Jessica
Nurnberger, John I
Porjesz, Bernice
Liu, Yunlong
Foroud, Tatiana
Edenberg, Howard J
Marcora, Edoardo
Agrawal, Arpana
Goate, Alison
Journal title
Nature communicationsDate Published
2021-08-20Publication Volume
12Publication Issue
1Publication Begin page
5071
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Show full item recordAbstract
Identification of causal variants and genes underlying genome-wide association study (GWAS) loci is essential to understand the biology of alcohol use disorder (AUD) and drinks per week (DPW). Multi-omics integration approaches have shown potential for fine mapping complex loci to obtain biological insights to disease mechanisms. In this study, we use multi-omics approaches, to fine-map AUD and DPW associations at single SNP resolution to demonstrate that rs56030824 on chromosome 11 significantly reduces SPI1 mRNA expression in myeloid cells and lowers risk for AUD and DPW. Our analysis also identifies MAPT as a candidate causal gene specifically associated with DPW. Genes prioritized in this study show overlap with causal genes associated with neurodegenerative disorders. Multi-omics integration analyses highlight, genetic similarities and differences between alcohol intake and disordered drinking, suggesting molecular heterogeneity that might inform future targeted functional and cross-species studies.Citation
Kapoor M, Chao MJ, Johnson EC, Novikova G, Lai D, Meyers JL, Schulman J, Nurnberger JI Jr, Porjesz B, Liu Y; Collaborative Study on the Genetics of Alcoholism (COGA), Foroud T, Edenberg HJ, Marcora E, Agrawal A, Goate A. Multi-omics integration analysis identifies novel genes for alcoholism with potential overlap with neurodegenerative diseases. Nat Commun. 2021 Aug 20;12(1):5071. doi: 10.1038/s41467-021-25392-y. PMID: 34417470; PMCID: PMC8379159.DOI
10.1038/s41467-021-25392-yae974a485f413a2113503eed53cd6c53
10.1038/s41467-021-25392-y
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- Creative Commons