Neurogenetic and multi-omic sources of overlap among sensation seeking, alcohol consumption, and alcohol use disorder

Abstract

Sensation seeking is bidirectionally associated with levels of alcohol consumption in both adult and adolescent samples and shared neurobiological and genetic influences may in part explain this association. Links between sensation seeking and alcohol use disorder (AUD) may primarily manifest via increased alcohol consumption rather than through direct effects on increasing problems and consequences. Here the overlap between sensation seeking, alcohol consumption, and AUD was examined using multivariate modeling approaches for genome-wide association study (GWAS) summary statistics in conjunction with neurobiologically-informed analyses at multiple levels of investigation. Meta-analytic and genomic structural equation modeling (GenomicSEM) approaches were used to conduct GWAS of sensation seeking, alcohol consumption, and AUD. Resulting summary statistics were used in downstream analyses to examine shared brain tissue enrichment of heritability and genome-wide evidence of overlap (e.g., stratified GenomicSEM, RRHO, genetic correlations with neuroimaging phenotypes) and to identify genomic regions likely contributing to observed genetic overlap across traits (e.g., H-MAGMA, LAVA). Across approaches, results supported shared neurogenetic architecture between sensation seeking and alcohol consumption characterized by overlapping enrichment of genes expressed in midbrain and striatal tissues and variants associated with increased cortical surface area. Alcohol consumption and AUD evidenced overlap in relation to variants associated with decreased frontocortical thickness. Finally, genetic mediation models provided evidence of alcohol consumption mediating associations between sensation seeking and AUD. This study extends previous research by examining critical sources of neurogenetic and multi-omic overlap among sensation seeking, alcohol consumption, and AUD which may underlie observed phenotypic associations.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

Investigator effort was supported by the National Institutes of Health (APM, F31AA027957, T32DA015035).

Author Declarations

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:

All secondary data analysis of GWAS summary statistics and reference panels were considered exempt by the Institutional Review Board at the University of Missouri.

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).

Yes

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

Data Availability

The full GWAS summary statistics for the 23andMe discovery data set will be made available through 23andMe to qualified researchers under an agreement with 23andMe that protects the privacy of the 23andMe participants. Please visit https://research.23andme.com/collaborate/#dataset-access/ for more information and to apply to access the data. GWAS summary statistics for risk taking in the UKB cohort along with ten smaller replication samples were obtained from https://thessgac.com/. GWAS summary statistics for drinks per week were obtained from https://conservancy.umn.edu/handle/11299/201564. Meta-analytic GWAS summary statistics (AlcGen, CHARGE +, and UKB) for grams of alcohol consumed per day were obtained through author request and the European Molecular Biology Laboratory's European Bioinformatics Institute website (http://ftp.ebi.ac.uk/). PGC alcohol dependence and UKB GWAS summary statistics for AUDIT-C were obtained from the PGC website (https://www.med.unc.edu/pgc/). Million Veteran Program GWAS summary statistics were obtained through the Database for Genotypes and Phenotypes (dbGaP; Study Accession: phs001672). FinnGenR6 ICD-based AUD GWAS data were obtained from https://r6.finngen.fi/pheno/AUD. For more information, visit https://finngen.gitbook.io/documentation/. GWAS summary statistics from UKB cortical regional volume neuroimaging phenotypes were obtained using the Oxford Brain Imaging Genetics (BIG40) web server (https://open.win.ox.ac.uk/ukbiobank/big40/). ENIGMA and UKB GWAS summary statistics for cortical thickness and surface area and CHARGE, ENIGMA, and UKB GWAS summary statistics for subcortical structural volume were obtained by request at http://enigma.ini.usc.edu/. GWAS summary statistics from UKB rs-fMRI phenotypes were obtained using the Brain Imaging Genetics Knowledge Portal (BIG-KP; https://bigkp.org). GTEx v8 RNA-seq read counts and transcripts per million normalized gene expression data were obtained from https://gtexportal.org/home/datasets. 1000 Genomes Project Phase 3 BaselineLD v2.2 and Roadmap Epigenomics Consortium annotation datasets for LDSC-SEG and stratified GenomicSEM were obtained from https://alkesgroup.broadinstitute.org/LDSCORE/. Hi-C datasets were obtained from the Won Lab GitHub repository (https://github.com/thewonlab/H-MAGMA). The locus file used for LAVA analyses was accessed at https://github.com/josefin-werme/LAVA/tree/main/support_data. 1000 Genomes Project Phase 3 LD reference panel data for LDSC-SEG, MAGMA, and GenomicSEM/stratified GenomicSEM were obtained from https://alkesgroup.broadinstitute.org/LDSCORE/, https://ctg.cncr.nl/software/magma, and https://github.com/GenomicSEM/GenomicSEM, respectively.

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