Metabolism may play a role in recurrent major depression

The researchers found that the metabolites – the small molecules produced by cellular activities – seemed to predict the risk of recurrence of depression and could be a new diagnostic tool.

Researchers at the University of California San Diego School of Medicine, in collaboration with Dutch scientists, have found that certain metabolites – small molecules produced by metabolism – may be predictive markers for people at risk of developing recurrent major depressive disorder.

The results were published in the January 11, 2021, online issue of Translational Psychiatry.

Chief researcher Robert K. Navio, MD, professor of medicine, paediatrics and pathology at the University of California, San Diego School of Medicine: “This is evidence of a mitochondrial link at the heart of depression.” “It’s a small study, but it is the first to show the potential for metabolic markers to be used as clinical indicators that are predictive of patients at higher risk of recurring episodes of major depressive symptoms – and with fewer risks.”

Recurrent major depressive disorder (usually, clinical depression) is a mood disorder characterized by multiple symptoms combined: feeling sad or hopeless, anger or frustration, loss of interest, sleep disturbances, anxiety, slowed down or difficulty thinking, suicidal thoughts and unexplained physical problems. Like back pain or a headache.

Major depressive disorder (MDD) is among the most common mental illnesses in the United States, with an estimated lifetime prevalence of 20.6 percent, meaning that one in five Americans will experience at least one episode during their lifetime. For patients with recurrent MDD (rMDD), the risk of recurrence for five years is as high as 80 percent.

For their study, Naviaux and colleagues in the Netherlands recruited 68 subjects (45 female, 23 male) with rMDD who were in remission free of antidepressants and 59 age- and gender-matched controls. After blood was collected from patients who were in remission, the patients were prospectively followed for two and a half years.

The results showed that the metabolic signature found when patients were otherwise healthy could predict which patients are most likely to relapse for two and a half years in the future. The accuracy of this prediction was over 90 percent. The analysis of the most predictive chemicals found that they belong to specific types of lipids (lipids that include eicosanoids and sphingolipids) and purines.

Purines are made from molecules, such as ATP and ADP – the main chemicals used to store energy in cells, but they also play a role in the connections that cells use under stress, known as purinic signaling.

The researchers found that in people with RMD, changes in specific metabolites in six specific metabolic pathways led to fundamental changes in important cellular activities.

“The results revealed an underlying biochemical signature in the switched rMDD that distinguishes diagnosed patients away from healthy controls,” Naviaux said. “These differences are not visible through normal clinical evaluation, but they suggest that the use of the metabolites – the biological study of metabolites – could be a new tool to predict which patients are most likely to have recurrences of depressive symptoms.”

The authors note that their preliminary results require validation in a larger study of at least 198 females and 198 males (99 cases and 99 control groups each).


The co-authors are: Roel JT Mocking, Caroline A. Figueroa and Johanna Assies, University of Amsterdam, the Netherlands; Jin C. Navio, Keving Lee, Lin Wang, Jonathan M. Monk, and A. Taylor Bright, University of California, San Diego; Art H. Sheen, University of Radboud Medical Center, Netherlands; And Henricus G. Ruhe, University of Amsterdam and University of Radboud Medical Center, The Netherlands.

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