TY - JOUR
T1 - Exploring the genetic overlap of suicide-related behaviors and substance use disorders
AU - Colbert, Sarah M.C.
AU - Hatoum, Alexander S.
AU - Shabalin, Andrey
AU - Li, Qingqin S.
AU - Coon, Hilary
AU - Nelson, Elliot C.
AU - Agrawal, Arpana
AU - Docherty, Anna R.
AU - Johnson, Emma C.
N1 - Funding Information:
This work was supported by grant YIG‐0‐064‐18 from the American Foundation for Suicide Prevention. The authors thank all investigators and participants who have contributed to the publicly available GWAS data used in this study. The authors thank Million Veteran Program (MVP) staff, researchers, and volunteers, who have contributed to MVP, and especially participants who previously served their country in the military and now generously agreed to enroll in the study. (See https://www.research.va.gov/mvp/ for more details.) The citation for MVP is Gaziano, J.M. et al. Million Veteran Program: A mega‐biobank to study genetic influences on health and disease. 70, 214–23 (2016). This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, and was supported by the Veterans Administration Cooperative Studies Program Award #G002. Sarah M. C. Colbert, Elliot C. Nelson, and Arpana Agrawal acknowledge support from MH109532. Emma C. Johnson acknowledges support through grant YIG‐0‐064‐18 from the American Foundation for Suicide Prevention. The content is solely the responsibility of the authors and does not necessarily represent the official views of the American Foundation for Suicide Prevention. Arpana Agrawal acknowledges K02DA032573. Alexander S. Hatoum receives support from DA007261‐17. Support was provided by National Institute of Mental Health R01 MH123619 to Anna R. Docherty, R01 MH123489 and R01 MH122412 to Hilary Coon, a Simons Foundation/SFARI award to Anna R. Docherty and Hilary Coon, and a Brain & Behavior Research Foundation Young Investigator award to Andrey Shabalin. Journal of Clinical Epidemiology
Funding Information:
American Foundation for Suicide Prevention, Grant/Award Number: YIG‐0‐064‐18; Brain and Behavior Research Foundation; National Institute of Mental Health, Grant/Award Numbers: MH109532, R01 MH122412, R01 MH123489, R01 MH123619; National Institute on Drug Abuse, Grant/Award Numbers: DA007261‐17, K02DA032573; Simons Foundation Autism Research Initiative; Veterans Administration Cooperative Studies Program Award #G002 Funding information
Funding Information:
This work was supported by grant YIG-0-064-18 from the American Foundation for Suicide Prevention. The authors thank all investigators and participants who have contributed to the publicly available GWAS data used in this study. The authors thank Million Veteran Program (MVP) staff, researchers, and volunteers, who have contributed to MVP, and especially participants who previously served their country in the military and now generously agreed to enroll in the study. (See https://www.research.va.gov/mvp/ for more details.) The citation for MVP is Gaziano, J.M. et al. Million Veteran Program: A mega-biobank to study genetic influences on health and disease. Journal of Clinical Epidemiology 70, 214?23 (2016). This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, and was supported by the Veterans Administration Cooperative Studies Program Award #G002. Sarah M. C. Colbert, Elliot C. Nelson, and Arpana Agrawal acknowledge support from MH109532. Emma C. Johnson acknowledges support through grant YIG-0-064-18 from the American Foundation for Suicide Prevention. The content is solely the responsibility of the authors and does not necessarily represent the official views of the American Foundation for Suicide Prevention. Arpana Agrawal acknowledges K02DA032573. Alexander S. Hatoum receives support from DA007261-17. Support was provided by National Institute of Mental Health R01 MH123619 to Anna R. Docherty, R01 MH123489 and R01 MH122412 to Hilary Coon, a Simons Foundation/SFARI award to Anna R. Docherty and Hilary Coon, and a Brain & Behavior Research Foundation Young Investigator award to Andrey Shabalin.
Publisher Copyright:
© 2021 Wiley Periodicals LLC.
PY - 2021/12
Y1 - 2021/12
N2 - Suicide-related behaviors are heterogeneous and transdiagnostic, and may demonstrate varying levels of genetic overlap with different substance use disorders (SUDs). We used linkage disequilibrium score regression, genomic structural equation models, and Mendelian randomization to examine the genetic relationships between several SUDs and suicide-related behaviors. Our analyses incorporated summary statistics from the largest genome-wide association studies (GWAS) of problematic alcohol use, the Fagerström test for nicotine dependence, cannabis use disorder, and opioid use disorder (Ns ranging from 46,213–435,563) and GWAS of ever self-harmed, suicide attempt, and suicide death (Ns ranging from 18,223–117,733). We also accounted for genetic liability to depression (N = 500,199) and risk tolerance (N = 315,894). Suicide-related behaviors were significantly genetically correlated with each other and each SUD, but there was little evidence of causal relationships between the traits. Simultaneously correlating a common SUD factor with each specific suicide indicator while controlling for depression and risk tolerance revealed significant, positive genetic correlations between the SUD factor and suicide-related behaviors (rg = 0.26–0.45, SE = 0.08–0.09). In the model, depression's association with suicide death (β = 0.42, SE = 0.06) was weaker compared to ever-self harmed and suicide attempt (β = 0.58, SE = 0.05 and β = 0.50, SE = 0.06, respectively). We identify a general level of genetic overlap between SUDs and suicide-related behaviors, which is independent of depression and risk tolerance. Additionally, our findings suggest that genetic and behavioral contributions to suicide death may somewhat differ from nonlethal suicide-related behaviors.
AB - Suicide-related behaviors are heterogeneous and transdiagnostic, and may demonstrate varying levels of genetic overlap with different substance use disorders (SUDs). We used linkage disequilibrium score regression, genomic structural equation models, and Mendelian randomization to examine the genetic relationships between several SUDs and suicide-related behaviors. Our analyses incorporated summary statistics from the largest genome-wide association studies (GWAS) of problematic alcohol use, the Fagerström test for nicotine dependence, cannabis use disorder, and opioid use disorder (Ns ranging from 46,213–435,563) and GWAS of ever self-harmed, suicide attempt, and suicide death (Ns ranging from 18,223–117,733). We also accounted for genetic liability to depression (N = 500,199) and risk tolerance (N = 315,894). Suicide-related behaviors were significantly genetically correlated with each other and each SUD, but there was little evidence of causal relationships between the traits. Simultaneously correlating a common SUD factor with each specific suicide indicator while controlling for depression and risk tolerance revealed significant, positive genetic correlations between the SUD factor and suicide-related behaviors (rg = 0.26–0.45, SE = 0.08–0.09). In the model, depression's association with suicide death (β = 0.42, SE = 0.06) was weaker compared to ever-self harmed and suicide attempt (β = 0.58, SE = 0.05 and β = 0.50, SE = 0.06, respectively). We identify a general level of genetic overlap between SUDs and suicide-related behaviors, which is independent of depression and risk tolerance. Additionally, our findings suggest that genetic and behavioral contributions to suicide death may somewhat differ from nonlethal suicide-related behaviors.
KW - genetic overlap
KW - genome-wide association studies
KW - genomic structural equation models
KW - substance use disorders
KW - suicide
UR - http://www.scopus.com/inward/record.url?scp=85120634804&partnerID=8YFLogxK
U2 - 10.1002/ajmg.b.32880
DO - 10.1002/ajmg.b.32880
M3 - Article
C2 - 34821019
AN - SCOPUS:85120634804
SN - 1552-4841
VL - 186
SP - 445
EP - 455
JO - American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics
JF - American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics
IS - 8
ER -