Depression does not come from one gene, one life event, or one personality trait. That's what makes it so hard to predict, prevent or treat effectively.
But new research suggests that a tool that uses a range of genetic information to predict a person's chance of developing depression when they're under intense stress. The findings might lead to a better understanding of the pathways that lead to depression.
While the tool is far from ready to use for individuals, it does suggest the potential for personalized depression prevention, and identification of those who may be most vulnerable to stress or most resilient.
The study was done in a population of more than 5,200 people in the most stressful year of training for a medical career, called the intern year of residency. In a new paper Nature Human Behavior by a team from the University of Michigan.
A score based on many genetic factors
The team used a genetic risk-assessment tool called polygenic risk score. They construct a polygenic risk score for major depressive disorder, or MDD-PRS, from widely available consortium and biobank data on the known associations between a person's risk of depression, and variations throughout a person's genome.
While genetics and stress are known to play a role in depression, the new research helps reveal the way these factors interact.
The interns who had higher-than-average MDD-PRS scores were slightly more likely to be among the 3% of interns who showed signs of depression before their intern year started. But by the end of the year, these high PRS subjects had more than 33% of interns who had developed depression.
The MDD-PRS scores were the most likely to be used to identify the most likely to be used.
Interns as a model of depression and stress
The research team tested the predictive power of MDD-PRS by young doctors taking part in the Intern Health Study, which is led by Srijan Sen, M.D., Ph.D., the senior author of the new paper. The Intern Health Study enrolls thousands of new physicians across the United States. high demands.
You and the study's first author, Yu Fang, UM research specialist, combined data across millions of sites within the human genomes to construct the MDD-PRS, and looked at how well a person's "score" on this tool predicted with their scores on standard surveys of depressive symptoms. They also evaluate whether MDD-PRS worked through known mechanisms and depression, such as personal and family history, childhood experience or general temperament.
The result: MDD-PRS.
"Interestingly, we found evidence that MDD-PRS and depression were stronger in the presence of MDD-PRS. says You, who holds the Eisenberg Professorship in Depression and Neurosciences at U-M and is part of the U-M Department of Psychiatry, the Molecular and Behavioral Neuroscience Institute and the Depression Center. "These findings further emphasize our understanding of how genomics and stress responds."
Notes of caution
The major limitation of the study is based on genetic information. Because MDD-PRS has been used in the study of the genetics of depression.
In fact, the tool failed to predict the symptoms of depression.
Also, the group of interns in the study was young, with an average age of 27, and had already been accepted into a residency training program, making them not representative of the general population.
Despite these limitations, this test of the MDD-PRS suggests its potential use.
"We are optimistic that these findings will be transferred to other ethnic groups with improving multi-ethnic analysis techniques and more data collected from these populations," says Fang. She also notes the predictive power of the MDD-PRS score to predict resilience. "We hope that this tool will be easy to discriminate against at-risk individuals."
More about the study
You, Fang and their colleagues used genetic linkages for depression identified through three major pools of DNA data: the Psychiatric Genomics Consortium, the UK Biobank and the commercial genetics company 23andMe.
Symptoms of a traumas, depression and symptoms of depression. Symptoms of a traumas, depression and symptoms of depression.
MDD-PRS worked through these three established risk factors.
However, while the overall predictive power of MDD-PRS increased significantly under the stress of the year, the predictive power of the three established factors remained the same.
This suggests that as-yet-undiscovered factors accounted for the greater link between MDD-PRS and depression.
Srijan Sen, M.D., Ph.D., senior author of the new paper
Margit Burmeister, Ph.D., a UM professor of human genetics and psychiatry who is a co-author of the new paper, says, "The MDD-PRS may be useful to discover such unknown environmental factors, for example by searching for resiliency behaviors in people who are at high risk, but unexpectedly did not become depressed during their internship. " Burmeister is part of the U-M Molecular and Behavioral Neuroscience Institute, the Department of Computational Medicine & Bioinformatics and the Depression Center.
The The ability of a better predictor to prevent depression, allow you concludes. "Studying individuals with a genomic protection against depression under stress can help us understand resilience"
University of Michigan
Fang, Y., et al. (2019) Genomic prediction of depression risk and resilience under stress. Nature Human Behavior. doi.org/10.1038/s41562-019-0759-3.