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Progress Toward Genetic Signature for Depression

One in six Americans experience a depressive episode during their lifetime, and the incidence of depression has risen every year since the early 20th century.

New research into the genetic basis of the disorder has focused on how to assess an individual’s risk of depression improve treatment.

Classically, psychiatric disorders have been described by subjective descriptions of the experience of being depressed and the use of rating scales that quantify depressive symptoms.

Over the past two decades, research has developed other strategies for describing the biological underpinnings of depression, including volumetric brain measurements using magnetic resonance imaging (MRI) and the patterns of gene expression in white blood cells.

At the same time, researchers have sought to characterize the genes that cause depression. The genetic relationship has been confirmed by use of rating scales of mood states, alterations in brain structure and function as measured by MRI, and gene expression patterns in postmortem brain tissue from people who suffered from depression.

In as new study, investigators led by David Glahn, Ph.D., of Yale University sought to lay out a “big picture” of the genetic contribution to depression by combining disparate, yet relevant types of genetic information.

“They have provided a very exciting strategy for uniting the various types of data that we collect in clinical research in studies attempting to identify risk genes,” said Dr. John Krystal, Editor of Biological Psychiatry.

Their work localized a gene, called RNF123, which may play a role in major depression.

Researchers set out with two clear goals: to describe a new method for ranking measures of brain structure and function on their genetic importance for an illness, and then to localize a candidate gene for major depression.

“We were trying to come up with a way that could generally be used to link biological measurements to (psychiatric) disease risk,” said geneticist John Blangero, Ph.D., director of the AT&T Genomics Computing Center at the Texas Biomedical Research Institute. “And in our first application of this, in relation to major depressive disorder, we’ve actually come up with something quite exciting.”

While RNF123 hasn’t previously been linked to depression, it has been shown to affect a part of the brain called the hippocampus, which is altered in people with major depression.

“We assume that the biological measures are closer mechanistically to the underlying disease processes in the brain. Yet, ultimately we are interested in the subjective experiences and functional impairment associated with mental illness,” added Krystal.

“The approach employed in this study may help to make use of all of this information, hopefully increasing our ability to identify genes that cause depression or might be targeted for its treatment.”

Glahn said, “We still have more work before we truly believe this is a home-run gene, but we’ve got a really good candidate. Even that has been tough to do in depression.”

Source: Elsevier

Progress Toward Genetic Signature for Depression

Rick Nauert PhD

Rick Nauert, PhDDr. Rick Nauert has over 25 years experience in clinical, administrative and academic healthcare. He is currently an associate professor for Rocky Mountain University of Health Professionals doctoral program in health promotion and wellness. Dr. Nauert began his career as a clinical physical therapist and served as a regional manager for a publicly traded multidisciplinary rehabilitation agency for 12 years. He has masters degrees in health-fitness management and healthcare administration and a doctoral degree from The University of Texas at Austin focused on health care informatics, health administration, health education and health policy. His research efforts included the area of telehealth with a specialty in disease management.

APA Reference
Nauert PhD, R. (2018). Progress Toward Genetic Signature for Depression. Psych Central. Retrieved on December 4, 2020, from
Scientifically Reviewed
Last updated: 8 Aug 2018 (Originally: 5 Jan 2012)
Last reviewed: By a member of our scientific advisory board on 8 Aug 2018
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