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Abstract

Objective:

Despite substantial progress in identifying genomic variation associated with major depression, the mechanisms by which genomic and environmental factors jointly influence depression risk remain unclear. Genomically conferred sensitivity to the social environment may be one mechanism linking genomic variation and depressive symptoms. The authors assessed whether social support affects the likelihood of depression development differently across the spectrum of genomic risk in two samples that experienced substantial life stress: 1,011 first-year training physicians (interns) in the Intern Health Study (IHS) and 435 recently widowed Health and Retirement Study (HRS) participants.

Methods:

Participants’ depressive symptoms and social support were assessed with questionnaires that were administered before and after the life stressor. Polygenic risk scores (PRSs) for major depressive disorder were calculated for both samples.

Results:

Depressive symptom scores increased by 126% after the start of internship in the IHS sample and by 34% after widowing in the HRS sample. There was an interaction between depression PRS and change in social support in the prediction of depressive symptoms in both the IHS sample (incidence rate ratio [IRR]=0.96, 95% CI=0.93, 0.98) and the HRS sample (IRR=0.78, 95% CI=0.66, 0.92), with higher depression PRS associated with greater sensitivity to changes in social support. Johnson-Neyman intervals indicated a crossover effect, with losses and gains in social support moderating the effect of PRS on depressive symptoms. (Johnson-Neyman interval in the IHS sample, −0.02, 0.71; in the HRS sample, −0.49, 1.92).

Conclusions:

The study findings suggest that individuals with high genomic risk for developing increased depressive symptoms under adverse social conditions also benefit more from nurturing social environments.

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Information & Authors

Information

Published In

Go to American Journal of Psychiatry
Go to American Journal of Psychiatry
American Journal of Psychiatry
Pages: 139 - 145
PubMed: 36628515

History

Received: 5 November 2021
Revision received: 15 April 2022
Revision received: 12 July 2022
Accepted: 4 August 2022
Published online: 11 January 2023
Published in print: February 01, 2023

Keywords

  1. Depressive Disorders
  2. Major Depressive Disorder
  3. Genetics/Genomics
  4. Development
  5. Stress

Authors

Details

Jennifer L. Cleary, M.S. [email protected]
Department of Psychology (Cleary, Zahodne), Molecular and Behavioral Neuroscience Institute (Cleary, Fang, Burmeister, Sen), VA Center for Clinical Management Research (Bohnert), and Department of Anesthesiology (Bohnert), University of Michigan, Ann Arbor; Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor (Burmeister).
Yu Fang, M.S.E.
Department of Psychology (Cleary, Zahodne), Molecular and Behavioral Neuroscience Institute (Cleary, Fang, Burmeister, Sen), VA Center for Clinical Management Research (Bohnert), and Department of Anesthesiology (Bohnert), University of Michigan, Ann Arbor; Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor (Burmeister).
Laura B. Zahodne, Ph.D.
Department of Psychology (Cleary, Zahodne), Molecular and Behavioral Neuroscience Institute (Cleary, Fang, Burmeister, Sen), VA Center for Clinical Management Research (Bohnert), and Department of Anesthesiology (Bohnert), University of Michigan, Ann Arbor; Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor (Burmeister).
Amy S.B. Bohnert, Ph.D.
Department of Psychology (Cleary, Zahodne), Molecular and Behavioral Neuroscience Institute (Cleary, Fang, Burmeister, Sen), VA Center for Clinical Management Research (Bohnert), and Department of Anesthesiology (Bohnert), University of Michigan, Ann Arbor; Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor (Burmeister).
Margit Burmeister, Ph.D.
Department of Psychology (Cleary, Zahodne), Molecular and Behavioral Neuroscience Institute (Cleary, Fang, Burmeister, Sen), VA Center for Clinical Management Research (Bohnert), and Department of Anesthesiology (Bohnert), University of Michigan, Ann Arbor; Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor (Burmeister).
Srijan Sen, M.D., Ph.D.
Department of Psychology (Cleary, Zahodne), Molecular and Behavioral Neuroscience Institute (Cleary, Fang, Burmeister, Sen), VA Center for Clinical Management Research (Bohnert), and Department of Anesthesiology (Bohnert), University of Michigan, Ann Arbor; Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor (Burmeister).

Notes

Send correspondence to Ms. Cleary ([email protected]).

Funding Information

Supported by NIMH grant R01MH101459.Dr. Bohnert has received funding from the Illinois Health and Hospital Association for speaking and has provided consultation services related to opioid medications.The other authors report no financial relationships with commercial interests.

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