Alcohol use disorder (AUD) is known to have a significant genetic component, yet there remains a substantial gap between its heritability and findings from genome-wide association studies. One potential factor contributing to this gap may be genetic interactions, or epistasis, a largely unexplored aspect in the context of AUD. The aim of this study was to investigate the role of epistasis in AUD susceptibility and severity among American Indians, a population that exhibits the highest rates of AUD among all ethnic groups in the U.S. We began by identifying genes previously linked to alcohol dependence and AUD, then expanded this gene set through biological networks, ultimately comprising 3,736 genes and regulatory elements. The final gene set was mapped to over 476K variants in an American Indian cohort of 742 individuals. We performed a pairwise genetic interaction association analysis on the variant set, followed by a bi-clustering procedure to group the interacting SNP pairs into interacting intervals. A total of 114 interacting pairs of genes and regulatory elements were identified to be significantly associated with AUD severity. These genes were enriched for immune system, cell adhesion, neuronal, and disease pathways. Their expressions were particularly enriched in midbrain GABAergic neurons. Our study represents the first large-scale genetic interaction study of AUD in any population. Our findings suggest that epistasis may significantly contribute to the development and progression of AUD.

The authors have declared no competing interest.

This work was supported by the National Institutes of Health (NIH): National Institute on Alcohol Abuse and Alcoholism (NIAAA) T32AA007456 to Stanislav Listopad, and National Institute on Drug Abuse (NIDA) DP1DA054373 to Qian Peng.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The protocol for the study was approved by the Institutional Review Board (IRB) of TSRI, and the board of the Indian Health Council, a tribal review group overseeing health issues for the reservations where the recruitment was undertaken.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

The data that support the finding of this study are available by contacting the last author. However, data availability is subject to approval of the specific American Indian tribes participating. Code used to perform core gene set expansion, epistasis analysis, bi-clustering, and other miscellaneous tasks can be found in our GitHub repository [https://github.com/staslist/Biclustering_Epistasis]. The code in the repository contains ready to use bi-clustering functionality. REMMA (version 2021.6.17) can be downloaded from Python pip package installer.

https://github.com/staslist/Biclustering_Epistasis