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Exploratory Longitudinal Pilot Study of Proteomic and Metabolomic Profiling Suggests a Hypothesized
Weidi Wang1, Yueyang Li1, Rubai Zhou1
1Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Current Neuropharmacology
|August 11, 2026
Summary
This study identifies potential immune-metabolic biomarkers, like PIAS4, in Atypical Depression (AFD). These dynamic changes suggest a link between lipid metabolism and innate immunity, potentially impacting mood instability.
Area of Science:
- Neuroscience
- Immunology
- Metabolomics
Background:
- Atypical Depression (AFD) presents with affective instability and metabolic-immune abnormalities.
- Objective biomarkers for AFD are currently lacking.
- Understanding these underlying mechanisms is crucial for developing effective treatments.
Purpose of the Study:
- To explore plasma proteomic and metabolomic profiles in AFD.
- To nominate candidate immune-metabolic signatures associated with AFD.
- To investigate dynamic changes over time using a longitudinal design.
Main Methods:
- Longitudinal pilot study with 5 female AFD patients and 5 healthy controls.
- Plasma samples analyzed using SomaScan® proteomics and UHPLC-QTOF-MS metabolomics.
- Multi-omics integration techniques (EFS, WGCNA, O2PLS) applied.
Main Results:
- Candidate proteins (e.g., PIAS4, IFN-λ1) and metabolites (e.g., stearic acid, glutamic acid) identified.
- Immune/inflammatory pathways were enriched in proteomic modules.
- An inverse correlation between stearic acid and a PIAS4-centered immune module was observed.
Conclusions:
- AFD may involve dynamic immune-metabolic alterations over time.
- PIAS4-centered immuno-metabolic signals are nominated as candidate AFD biomarkers.
- Longitudinal multi-omics approaches can map dynamic biomarker networks in affective disorders.