More Risk Factors Predict Future Depression

August 17, 2020
Kenny Walter

A number of new modifiable risk factors for depression were identified including confiding in others, time spent watching television, and daytime napping.

Researchers might soon be adding to the list of risk factors for depression.

A team, led by Karmel W. Choi, PhD, used phenotypic and genomic data from over 100,000 UK Biobank participants to systematically screen and validate a wide range of potential modifiable factors for depression.

Depression is currently the leading cause of disability worldwide. However, efforts to prevent depression have only focused on a limited number of candidate factors.

The investigators extracted baseline data for 106 modifiable risk factors depression including lifestyle measures such as exercise, sleep, media, and diet, social factors including support and engagement, and environmental variable such as green space and pollution.

The researchers defined incident depression as minimal depressive symptoms at baseline and clinically significant depression at follow-up and at risk individuals for incident depression were identified by either polygenic risk scores or reported traumatic life events.

Each patient underwent an exposure-wide association scan to identify factors linked with incident depression in the full sample and among at-risk individuals. The researchers used a two-sample Mendelian randomization to validate potentially causal relationships between identified factors and depression.

Overall, there were several factors across social, sleep, media, dietary, and exercise-related domains prospectively linked to depression, even among at-risk individuals.

However, only a subset of factors was supported when the investigators used Mendelian randomization evidence, including confiding in others (OR, 0.76; 95% CI, 0.67-0.86), time spent watching television (OR, 1.09; 95% CI, 1.05-1.13), and daytime napping (OR, 1.34; 95% CI, 1.17-1.53).

“Using a two-stage approach, this study validates several actionable targets for preventing depression,” the authors wrote. “It also demonstrates that not all factors associated with depression in observational research may translate into robust targets for prevention. A large-scale exposure-wide approach combined with genetically informed methods for causal inference may help prioritize strategies for multimodal prevention in psychiatry.”

Recently, investigators tested the effects of vitamin D3 supplementation on late-life depression risk and mood scores.

In the randomized clinical trial dubbed the VITAL-DEP (Vitamin D and Omega-3 Trial-Depression Endpoint Prevention), the investigators examined 18,353 individuals older than 50.

The investigators found the risk of depression or clinically relevant depressive symptoms was not significantly different between the vitamin D3 group (609 depression or clinically relevant depressive symptom events; 12.9/1000 person-years) and the placebo group (625 depression or clinically relevant depressive symptom events; 13.3/ 1000 person-years) (HR, 0.97; 95% CI, 0.87-1.09; P = 0.62).

The researchers did not find significant differences between groups in depression incidence or recurrence or between treatment groups for changes in mood scores over time. The mean change in PHQ-8 score was not significantly different from zero (mean difference for change in mood scores, 0.01 points; 95% CI, -0.04 to 0.05 points).

The study, “An Exposure-Wide and Mendelian Randomization Approach to Identifying Modifiable Factors for the Prevention of Depression,” was published online in The American Journal of Psychiatry.


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