Identifying Baseline Predictors of Relapse and Stratifying Immune Composition in Major Depressive Disorder

Abstract

A major challenge in the treatment of major depressive disorder (MDD) is relapse, which is defined as the return of depressive symptoms during a period of remission. Relapse rates in MDD are high, with approximately 50% of individuals relapsing following treatment of their first depressive episode, therefore early intervention to prevent relapse is crucial. Evidence suggests that immune dysregulation may be linked to longitudinal changes in depressive severity. However, it is currently unknown whether inflammation can predict future relapse in MDD. The objective of this project was to identify potential immune predictors of relapse in participants that responded to a treatment or a combination of treatments for MDD. A secondary objective was to investigate immune composition in efforts to stratify MDD individuals into more homogenous groups and further explore these groups in relation to clinical symptoms. This project is part of the Wellness Monitoring for Major Depressive Disorder longitudinal study (NCT02934334) of responders to antidepressant treatment conducted at 6 clinical sites across Canada. Montgomery Asberg Depression Rating Scale (MADRS) scores were used to assess depression severity and to categorize participants into ultrastable, unstable, and relapse groups. Plasma immune profiles were generated using the LEGENDplex Human Th Cytokine Panel immunoassay. Principal Component Analysis and Kruskal-Wallis tests of individual immune cytokines did not show differences between ultrastable, unstable, or relapse groups. Principal Component Analysis did reveal two cytokine clusters. Hierarchical Clustering analysis identified three distinct immune biotypes characterized by differing levels of Th cytokines and validated the presence of the cytokine clusters. Neither of these outcomes was predictive of relapse in this cohort. Our findings have shown that immune composition may serve as an important factor in parsing heterogeneity that is observed in this disorder through identification of distinct immune biotypes and highly interconnected cytokine subnetworks in major depression. The potential for immune biotypes for optimizing treatment regimens and relapse prevention necessitates further investigation and replication.