Plasma proteomics reveal heterogeneous subtypes of depression linked to inflammation and aging

Authors

Lian, Z., Palaniyappan, L., Liu, Z., Kuang, N., Liu, Y., Jiang, Y., Sahakian, B. J., Robbins, T. W., Feng, J., Becker, B., Cheng, W., Wu, X., Zhang, J., Bullmore, E.

Abstract

The clinical heterogeneity of depression has defied biological classification, limiting personalized treatment. Previous neuroimaging- or symptom-based subtyping of depression failed to clarify the underlying pathoetiology, while plasma proteins which integrates signals from multiple organ systems, offers a promising way to define biologically grounded subtypes. Using plasma proteomics from 2,127 incident depression cases in a cohort of 53000 individuals, we identified three biologically distinct subtypes differing in inflammation, aging, and metabolic profiles. The most prevalent subtype (inflammation/aging) was characterized by aging-related inflammation, poorest prognosis with hippocampal atrophy and highest suicide risk, mediated by age-related amygdalar atrophy; this subtype had highest anhedonia burden. A distinct inflammation/energy dysregulation group had metabolic pathway enrichment with high inflammation and lifestyle risk factors (smoking) but no aging trend, predominantly physical/psychomotor symptoms and decreased thalamic volume. In contrast, the inflammation-resilient group had the lowest inflammatory proteomic loading, lowest depression severity, more resilient lifestyle and increased hippocampal volume. These proteomic signatures, detectable years before symptom onset, enable risk stratification and suggest subtype-specific targeted physical and lifestyle interventions.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 16 Jan 2026.

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