A proteomic feasibility study connecting metabolic and synaptic pathway alterations in serum and extracellular vesicles to characterize treatment-resistant depression

Authors

Ramsay, O. B., Burnap, S. A., Dobbs, M. F., Struwe, W. B., Russo, S., Murrough, J. W., Robinson, C. V., El-Baba, T. J.

Abstract

Treatment-resistant depression (TRD) remains a major clinical challenge, yet the biological processes distinguishing TRD from non-treatment-resistant depression (nTRD) are incompletely defined. While circulating serum proteomes reflect broad systemic alterations associated with depression, extracellular vesicles (EVs) could provide a more selective representation of intercellular signaling relevant to treatment resistance. Here, we carried out a pilot study to evaluate the extent that parallel proteomic profiling of serum and serum-derived EVs could distinguish healthy controls (CON), nTRD, and TRD individuals. In this exploratory and hypothesis-generating study, serum proteomes exhibited robust global differences between depression groups and controls, largely reflecting shared systemic biology across nTRD and TRD. In contrast, EV proteomes showed limited global separation but revealed subtype-associated pathway differences. Relative to controls, nTRD EVs were enriched for immune and inflammatory pathways. By contrast, TRD EVs were characterized by enrichment of mitochondrial metabolism, oxidative phosphorylation, translational initiation, and MYC-regulated pathways, together with depletion of synaptic signalling, membrane trafficking, and cytoskeletal pathways. Comparative analysis of pathways significant in both contrasts revealed that these bioenergetic and translational signatures were selectively amplified in TRD relative to nTRD. Our exploratory analyses identified that the circulating EV cargo may reflect a treatment-resistance-specific reorganization of biological pathways not apparent in bulk serum proteomics. This study highlights parallel serum and EV proteomics as a complementary approach for molecular stratification in antidepressant resistance.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 25 Aug 2026.

Stats

1-terrible, 9-excellent. How would you rate this preprint? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.