Sex Differences in Mood Disorders: Personalizing Treatment

Summary: Researchers review progress since the 2016 National Institutes of Health (NIH) policy requiring basic research to include sex as a biological variable. Their analysis highlights important advances in understanding sex differences in mood disorders and points toward priorities for future, more inclusive research that can inform personalized treatment approaches.

The review emphasizes several consistent findings: women face a greater lifetime risk of depression and anxiety, men are at risk of underdiagnosis because symptoms often present differently, and brain cell types show both baseline and stress-induced sex differences that may contribute to divergent disease mechanisms. The authors call for research that goes beyond identifying whether sex differences exist to determining why they arise and how this knowledge can be used to improve diagnostics and therapeutics for all people, including transgender and intersex populations.

Key Facts:

  1. Women have approximately twice the risk of developing depression and anxiety disorders, often experience their first episode at a younger age, and tend to have more cumulative episodes during their lifetime.
  2. Men may be underdiagnosed for major depressive disorder because their symptoms frequently present as externalizing behaviors—such as anger, aggression, or substance use—which can obscure underlying depression.
  3. Multiple brain cell types, including microglia (the central nervous system’s resident immune cells), display sex-specific patterns at baseline and in response to stress. These cellular differences may help explain sex-based disparities in psychiatric disorders.

Source: Virginia Tech

Background: In 2016 the NIH revised its policy for basic research to require investigators to consider sex as a biological variable. This policy change responded to a long-standing bias in preclinical research that favored male animals and left critical gaps in knowledge about female physiology and disease biology. That mismatch contributed to translational failures—drugs developed and tested primarily in male animals sometimes performed differently or posed unrecognized risks in women.

“A strong, unbiased evidence base is essential to identify sex-specific biomarkers for depression onset and to develop more effective, targeted treatments,” said Georgia Hodes, an assistant professor in the School of Neuroscience at Virginia Tech’s College of Science. Hodes and co-author Dawson Kropp, a Ph.D. student in neuroscience, synthesized recent discoveries and emerging themes in a Review published in the journal Nature Mental Health.

Their review highlights several notable observations from the recent literature:

  • Women have a higher prevalence of depression and anxiety, earlier onset, and a greater burden of recurrent episodes across the lifespan compared with men.
  • Diagnostic patterns differ by sex: men frequently show externalizing symptoms and higher rates of co-occurring substance use disorders, patterns that can lead to missed or delayed depression diagnoses.
  • Cellular and developmental differences matter. For example, microglia and other brain cells show sex-specific traits across development and into adulthood, which may shape vulnerability to psychiatric conditions.
  • Timing of vulnerability differs: evidence suggests males may be more susceptible to prenatal or early-life stress, with physiological and behavioral changes appearing in childhood, whereas equivalent behavioral effects in females often emerge after puberty.
  • Some animal models reveal sex-specific timelines for stress-induced behavioral changes. In certain mouse studies, chronic variable stress produced behavioral alterations in females after only six days, while comparable changes in males required a longer duration—around 21 days—to appear.

The authors also stress that depression is heterogeneous and that drug developers must recognize this complexity. Historically, many medications caused disproportionately higher adverse effects in women; public attention to this issue intensified after analyses showed that several drugs withdrawn from the market from 1997–2001 posed greater risks to women. That history underscores the need to account for sex in every stage of drug development and testing.

Hodes and Kropp advocate shifting research questions beyond the binary existence of sex differences to address mechanisms and clinical translation: why do sex differences arise, what are their biological functions, and how can that information guide development of sex-informed or sex-specific treatments? They also emphasize the ethical and scientific imperative to include transgender and intersex individuals in research, so that findings reflect the full diversity of human biology and experience and so clinicians can provide better-informed care to everyone.

About this depression research news

Author: Steven Mackay
Source: Virginia Tech
Contact: Steven Mackay – Virginia Tech
Image: The image is credited to Neuroscience News

Original Research: Open access. “Sex as a biological variable in stress and mood disorder research” by Georgia Hodes et al., published in Nature Mental Health.


Abstract

Sex as a biological variable in stress and mood disorder research

The 2016 policy change requiring sex to be included as a biological variable corrected a long-standing imbalance in basic research that had favored male subjects. That imbalance created a disconnect between the sex distribution of preclinical models used in drug discovery and the diverse populations enrolled in clinical trials, limiting the translational success of new therapeutics for mood disorders.

Now that sex differences are well documented across many domains of neuroscience and psychiatry, the field must advance to the next phase: explaining why these differences exist, determining their functional consequences, and translating those insights into precision approaches for prevention, diagnosis, and treatment. This Review summarizes what has been learned from incorporating sex as a biological variable and outlines how those data can be used to reduce sex-based disparities in mental health care.