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Using Patterns of Genetic Association to Elucidate Shared Genetic Etiologies Across Psychiatric Disorders

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Abstract

Twin studies indicate that latent genetic factors overlap across comorbid psychiatric disorders. In this study, we used a novel approach to elucidate shared genetic factors across psychiatric outcomes by clustering single nucleotide polymorphisms based on their genome-wide association patterns. We applied latent profile analysis (LPA) to p-values resulting from genome-wide association studies across three phenotypes: symptom counts of alcohol dependence (AD), antisocial personality disorder (ASP), and major depression (MD), using the European–American case-control genome-wide association study subsample of the collaborative study on the genetics of alcoholism (N = 1399). In the 3-class model, classes were characterized by overall low associations (85.6% of SNPs), relatively stronger association only with MD (6.8%), and stronger associations with AD and ASP but not with MD (7.6%), respectively. These results parallel the genetic factor structure identified in twin studies. The findings suggest that applying LPA to association results across multiple disorders may be a promising approach to identify the specific genetic etiologies underlying shared genetic variance.

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Acknowledgements

We thank our collaborators of Collaborative Study on the Genetics of Alcoholism (COGA) for sharing their valuable ideas and feedback that helped complete this study.

Funding

Funding support for GWAS genotyping performed at the Johns Hopkins University Center for Inherited Disease Research was provided by the National Institute on Alcohol Abuse and Alcoholism, the NIH GEI (U01HG004438), and the NIH contract “High throughput genotyping for studying the genetic contributions to human disease” (HHSN268200782096C). GWAS genotyping was also performed at the Genome Technology Access Center in the Department of Genetics at Washington University School of Medicine which is partially supported by NCI Cancer Center Support Grant #P30 CA91842 to the Siteman Cancer Center and by ICTS/CTSA Grant# UL1RR024992 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research.

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Authors and Affiliations

  1. Department of Psychology, Virginia Commonwealth University, PO Box 842018, 817W. Franklin Street, Richmond, VA, 23284-2018, USA

    Seung Bin Cho, Fazil Aliev, Amy E. Adkins & Danielle M. Dick

  2. College Behavioral and Emotional Health Institute, Virginia Commonwealth University, Richmond, VA, USA

    Seung Bin Cho, Fazil Aliev, Amy E. Adkins & Danielle M. Dick

  3. Faculty of Business, Karabuk University, Karabuk, Turkey

    Fazil Aliev

  4. Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, Richmond, VA, USA

    Shaunna L. Clark

  5. Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA

    Howard J. Edenberg

  6. Department of Psychiatry, Washington University, Saint Louis, MO, USA

    Kathleen K. Bucholz

  7. Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn, NY, USA

    Bernice Porjesz

  8. Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA

    Danielle M. Dick

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  1. Seung Bin Cho
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Correspondence to Seung Bin Cho.

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Conflict of interest

Seung Bin Cho, Fazil Aliev, Shaunna L. Clark, Amy E. Adkins, Howard J. Edenberg, Kathleen K. Bucholz, Bernice Porjesz and Danielle M. Dick declares that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all individual participants included in this study.

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Edited by Gitta Lubke.

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Cho, S.B., Aliev, F., Clark, S.L. et al. Using Patterns of Genetic Association to Elucidate Shared Genetic Etiologies Across Psychiatric Disorders. Behav Genet 47, 405–415 (2017). https://doi.org/10.1007/s10519-017-9844-4

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