Recurrent major depressive disorder (rMDD) is a relapsing-remitting disease with high morbidity and a 5-year risk of recurrence of up to 80%. A research recently found that certain metabolites -- small molecules produced by the process of metabolism -- may be predictive indicators for persons at risk for recurrent major depressive disorder. 

Targeted broad-spectrum LC-MS/MS-metabolomics of 399 plasma metabolites was used to study recurrent major depressive disorder in remission (rrMDD), and the time to recurrence, in 126 cases and controls. Lipid abnormalities dominated rrMDD’s metabolic signature. The most powerful statistical inferences came from the 2.5-year prospective study of subjects at risk for recurrence. Stratification of rrMDD subjects using metabolomics was able to predict recurrence risk with >90% accuracy in both males and females. Nearly 80% of the metabolites with greatest predictive accuracy for recurrence risk belonged to just six pathways: phospholipids, sphingomyelins, glycosphingolipids, eicosanoids, microbiome, and purines.

This research revealed an underlying biochemical signature in remitted recurrent major depressive disorder (rrMDD). this is the first report to show that broad-spectrum targeted metabolomics can predict future recurrence risk of rMDD.

link https://www.nature.com/articles/s41398-020-01182-w

source : Translational Psychiatry