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Genome-wide association study of traumatic brain injury in U.S. military veterans enrolled in the VA million veteran program

Molecular Psychiatry (2023)Cite this article

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Abstract

Large-scale genetic studies of traumatic brain injury (TBI) are lacking; thus, our understanding of the influence of genetic factors on TBI risk and recovery is incomplete. This study aimed to conduct a genome-wide association study (GWAS) of TBI in VA Million Veteran Program (MVP) enrollees. Participants included a multi-ancestry cohort (European, African, and Hispanic ancestries; N = 304,485; 111,494 TBI cases, 192,991 controls). TBI was assessed using MVP survey data and International Classification of Diseases (ICD) codes from the Veterans Health Administration’s electronic health record. GWAS was performed using logistic regression in PLINK, and meta-analyzed in METAL. FUMA was used for post-GWAS analysis. Genomic structural equation modeling (gSEM) was conducted to investigate underlying genetic associations with TBI, and bivariate MiXeR was used to estimate phenotype specific and shared polygenicity. SNP-based heritability was 0.060 (SE = 0.004, p = 7.83×10-66). GWAS analysis identified 15 genome-wide significant (GWS) loci at p < 5×10-8. Gene-based analyses revealed 14 gene-wide significant genes; top genes included NCAM1, APOE, FTO, and FOXP2. Gene tissue expression analysis identified the brain as significantly enriched, particularly in the frontal cortex, anterior cingulate cortex, and nucleus accumbens. Genetic correlations with TBI were significant for risk-taking behaviors and psychiatric disorders, but generally not significant for the neurocognitive variables investigated. gSEM analysis revealed stronger associations with risk-taking traits than with psychiatric traits. Finally, the genetic architecture of TBI was similar to polygenic psychiatric disorders. Neurodegenerative disorders including Alzheimer’s and Parkinson’s disease showed much less polygenicity, however, the proportion of shared variance with TBI was high. This first well-powered GWAS of TBI identified 15 loci including genes relevant to TBI biology, and showed that TBI is a heritable trait with comparable genetic architecture and high genetic correlation with psychiatric traits. Our findings set the stage for future TBI GWASs that focus on injury severity and diversity and chronicity of symptom sequelae.

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Fig. 1: Manhattan plot of TBI for the multi-ancestry cohort.
Fig. 2: Gene tissue expression in the multi-ancestry cohort.
Fig. 3: Genetic correlation between TBI and other phenotypes.
Fig. 4: Genomic structural equation modeling (gSEM) results.
Fig. 5: Multiple regression results.

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Data availability

The data underlying this publication are accessible to researchers with Million Veteran Program (MVP) data access. MVP is currently only accessible to researchers who have a funded MVP project, either through a VA Merit Award or a VA Career Development Award. See https://www.research.va.gov/funding/Guidance-MVP-Data-Access-Merit-Award.pdf for more details. Summary statistics will be made publicly available on dbGAP.

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Acknowledgements

The authors sincerely thank the Veterans who volunteered to participate in the Million Veteran Program. This research is based on data from the Million Veteran Program (Project MVP026), Office of Research and Development, Veterans Health Administration. This publication does not represent the views of the Department of Veteran Affairs or the United States Government.

Funding

This work was supported by a Career Development Award awarded to Dr. Merritt from the VA Clinical Science Research & Development Service (IK2 CX001952).

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Authors and Affiliations

  1. VA San Diego Healthcare System (VASDHS), San Diego, CA, USA

    Victoria C. Merritt, Adam X. Maihofer, Marianna Gasperi, Murray B. Stein, Matthew S. Panizzon, Richard L. Hauger, Lisa Delano-Wood & Caroline M. Nievergelt

  2. Department of Psychiatry, University of California San Diego, La Jolla, CA, USA

    Victoria C. Merritt, Adam X. Maihofer, Marianna Gasperi, Murray B. Stein, Matthew S. Panizzon, Richard L. Hauger, Lisa Delano-Wood & Caroline M. Nievergelt

  3. Center of Excellence for Stress and Mental Health, VASDHS, San Diego, CA, USA

    Victoria C. Merritt, Marianna Gasperi, Richard L. Hauger, Lisa Delano-Wood & Caroline M. Nievergelt

  4. VA Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Health Care System, Salt Lake City, UT, USA

    Catherine Chanfreau-Coffinier

  5. School of Public Health, University of California San Diego, La Jolla, CA, USA

    Murray B. Stein

  6. Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA

    Matthew S. Panizzon & Richard L. Hauger

  7. National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, MA, USA

    Mark W. Logue

  8. Boston University Chobanian & Avedisian School of Medicine, Department of Psychiatry, Boston, MA, USA

    Mark W. Logue

  9. Boston University Chobanian & Avedisian School of Medicine, Biomedical Genetics, Boston, MA, USA

    Mark W. Logue

  10. Boston University School of Public Health, Department of Biostatistics, Boston, MA, USA

    Mark W. Logue

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  1. Victoria C. Merritt
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Contributions

Overall study coordination: VCM, CMN. Study concept and design: VCM, CMN, AXM, LDW. Data curation: CCC. Phenotype analysis: CCC (lead), VCM, LDW. Statistical analysis: AXM (lead), MG. Data interpretation: AXM, MG, CMN, MBS, MSP, RLH, MWL, VCM. Writing: VCM (lead), AXM, CMN. All authors provided edits, feedback, and approved the final version of the paper for submission.

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Correspondence to Victoria C. Merritt.

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Merritt, V.C., Maihofer, A.X., Gasperi, M. et al. Genome-wide association study of traumatic brain injury in U.S. military veterans enrolled in the VA million veteran program. Mol Psychiatry (2023). https://doi.org/10.1038/s41380-023-02304-8

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