Malone SG, Davis CN, Piserchia Z, Setzer MR, Toikumo S, Zhou H, Winterlind EL, Gelernter J, Justice A, Leggio L, Rentsch CT, Kranzler HR, Gray JC. Alcohol use disorder and body mass index show genetic pleiotropy and shared neural associations.
MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.03.24306773. [PMID:
38746260 PMCID:
PMC11092735 DOI:
10.1101/2024.05.03.24306773]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Background
The prevalence of co-occurring heavy alcohol consumption and obesity is increasing in the United States. Despite neurobiological overlap in the regulation of alcohol consumption and eating behavior, alcohol- and body mass index (BMI)-related phenotypes show no or minimal genetic correlation. We hypothesized that the lack of genetic correlation is due to mixed effect directions of variants shared by AUD and BMI.
Methods
We applied MiXeR, to investigate shared genetic architecture between AUD and BMI in individuals of European ancestry. We used conjunctional false discovery rate (conjFDR) analysis to detect loci associated with both phenotypes and their directional effect, Functional Mapping and Annotation (FUMA) to identify lead single nucleotide polymorphisms (SNPs), Genotype-Tissue Expression (GTEx) samples to examine gene expression enrichment across tissue types, and BrainXcan to evaluate the shared associations of AUD and BMI with brain image-derived phenotypes.
Results
MiXeR analysis indicated polygenic overlap of 80.9% between AUD and BMI, despite a genetic correlation (r g ) of -.03. ConjFDR analysis yielded 56 lead SNPs with the same effect direction and 76 with the opposite direction. Of the 132 shared lead SNPs, 53 were novel for both AUD and BMI. GTEx analyses identified significant overexpression in the frontal cortex (BA9), hypothalamus, cortex, anterior cingulate cortex (BA24), hippocampus, and amygdala. Amygdala and caudate nucleus gray matter volumes were significantly associated with both AUD and BMI in BrainXcan analyses.
Conclusions
More than half of variants significantly associated with AUD and BMI had opposite directions of effect for the traits, supporting our hypothesis that this is the basis for their lack of genetic correlation. Follow-up analyses identified brain regions implicated in executive functioning, reward, homeostasis, and food intake regulation. Together, these findings clarify the extensive polygenic overlap between AUD and BMI and elucidate several overlapping neurobiological mechanisms.
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