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Alcohol use disorder and body mass index show genetic pleiotropy and shared neural associations

Abstract

Despite neurobiological overlap, alcohol use disorder (AUD) and body mass index (BMI) show minimal genetic correlation (rg), possibly due to mixed directions of shared variants. Here we applied MiXeR to investigate shared genetic architecture between AUD and BMI, conjunctional false discovery rate to detect shared loci and their directional effect, local analysis of (co)variant association for local rg, functional mapping and annotation to identify lead single-nucleotide polymorphisms, Genotype-Tissue Expression (GTEx) to examine tissue enrichment and BrainXcan to assess associations with brain phenotypes. MiXeR indicated 82.2% polygenic overlap, despite an rg of −0.03. The conjuctional false discovery rate method identified 132 shared lead single-nucleotide polymorphisms, with 53 novel, showing both concordant and discordant effects. GTEx analyses identified overexpression in multiple brain regions. Amygdala and caudate nucleus volumes were associated with AUD and BMI. Opposing variant effects explain the minimal rg between AUD and BMI, with implicated brain regions involved in executive function and reward, clarifying their polygenic overlap and neurobiological mechanisms.

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Fig. 1: MiXeR Venn diagrams showing the estimated number of shared causal variants in the thousands and genetic correlations (rg) of AUD and BMI with each other and psychiatric disorders.
Fig. 2: Manhattan plot of variants jointly associated with AUD and BMI.
Fig. 3: Significant upregulated differential gene expression in the frontal cortex (BA9), hypothalamus, cortex, anterior cingulate cortex (BA24), hippocampus and amygdala.
Fig. 4: Differential gene expression (DEG) in 54 GTEx tissue types for genes linked to lead SNPs in distinct loci significantly associated with AUD and BMI.
Fig. 5: Brain visualization of subcortical features significantly associated with AUD and BMI.

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Data availability

Full summary statistics from two genome-wide association studies are available at the following locations: GIANT Consortium website (https://portals.broadinstitute.org/collaboration/giant/index.php/GIANT_consortium_data_files) and the Gelernter Lab website without restriction (https://medicine.yale.edu/lab/gelernter/stats/) or dbGaP (accession number phs001672, under the ‘Addiction’ analysis; registration and approval are needed following dbGaP’s data accessing process). Researchers seeking access to the exact AUD summary statistics cohort used in this study should contact the original study authors for more information (Zhou et al., 2023 (ref. 23)). Replication summary statistics are available via the FinnGen website (https://www.finngen.fi/en/access_results). Annotations for the lead SNPs corresponding to VEP, CADD scores and nearest transcription start site were sourced from OpenTargets (https://genetics.opentargets.org/, v22.10). The presence of lead SNPs within genes was confirmed using dbGaP (https://www.ncbi.nlm.nih.gov/gap/). The TCRD and OpenTargets were accessed to integrate drug–protein interaction/druggability information (https://pharos.nih.gov/, v3.18.0; https://platform.opentargets.org/, v23.12).

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Acknowledgements

We thank all of the research participants who contributed their data to the data sources used in this study. This work was supported by funding from the National Institute on Alcohol Abuse and Alcoholism (R01 AA030041 to J.C.G., H.R.K. and C.T.R.; and R01 AA030056 to H.R.K.), the Department of Defense (HU0001-22-2-0066 to J.C.G., H.R.K. and C.T.R.) and the Veterans Integrated Service Network 4 Mental Illness Research, Education and Clinical Center of the Crescenz Veterans Affairs Medical Center (to H.R.K. and A.J.). L.L. is a federal employee and is supported by the National Institute on Drug Abuse and the National Institute on Alcohol Abuse and Alcoholism Intramural Research Programs. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the paper. The opinions and assertions herein are those of the authors and do not necessarily reflect the official views of the Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc. Moreover, the opinions and assertions herein do not necessarily reflect the official views of the Department of Defense, Uniformed Services University, the National Institute on Alcohol Abuse and Alcoholism or the US Government and do not imply endorsement by the Federal Government.

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Study concept and design: J.C.G. Analysis of data: Z.P., C.N.D., J.C.G. and H.Z. Drafting of the paper: S.G.M., J.C.G., M.R.S., C.N.D., S.T., H.R.K. and E.L.W. Critical revision of the paper for important intellectual content: C.N.D., S.G.M., J.C.G., H.R.K., C.T.R., L.L., S.T., H.Z., A.J. and J.G. Final approval of the paper: all.

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Correspondence to Joshua C. Gray.

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H.R.K. is a member of advisory boards for Altimmune, Clearmind Medicine, Dicerna Pharmaceuticals, Enthion Pharmaceuticals, Lilly Pharmaceuticals and Sophrosyne Pharmaceuticals; a consultant to Sobrera Pharmaceuticals and Altimmune; the recipient of research funding and medication supplies for an investigator-initiated study from Alkermes; and a member of the American Society of Clinical Psychopharmacology’s Alcohol Clinical Trials Initiative, which was supported in the past 3 years by Alkermes, Dicerna, Ethypharm, Imbrium, Indivior, Kinnov, Lilly, Otsuka and Pear. J.G. and H.R.K. hold US patent 10,900,082 titled ‘Genotype-guided dosing of opioid agonists’, issued 26 January 2021. J.G. is paid for editorial work for the journal Complex Psychiatry. The other authors declare no competing interests.

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Malone, S.G., Davis, C.N., Piserchia, Z. et al. Alcohol use disorder and body mass index show genetic pleiotropy and shared neural associations. Nat Hum Behav 9, 1056–1066 (2025). https://doi.org/10.1038/s41562-025-02148-y

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