Proteomic profiles of cytokines and chemokines in moderate to severe depression: Implications for comorbidities and biomarker discovery.

Biomarkers Chemokines Cytokines Inflammation Major depressive disorder Proteomics

Journal

Brain, behavior, & immunity - health
ISSN: 2666-3546
Titre abrégé: Brain Behav Immun Health
Pays: United States
ID NLM: 101759062

Informations de publication

Date de publication:
Mar 2024
Historique:
received: 01 12 2023
revised: 22 01 2024
accepted: 25 01 2024
medline: 4 3 2024
pubmed: 4 3 2024
entrez: 4 3 2024
Statut: epublish

Résumé

This study assessed the proteomic profiles of cytokines and chemokines in individuals with moderate to severe depression, with or without comorbid medical disorders, compared to healthy controls. Two proteomic multiplex platforms were employed for this purpose. An immunofluorescent multiplex platform and an aptamer-based method were used to evaluate 32 protein analytes from 153 individuals with moderate to severe major depressive disorder (MDD) and healthy controls (HCs). The study focused on determining the level of agreement between the two platforms and evaluating the ability of individual analytes and principal components (PCs) to differentiate between the MDD and HC groups. Additionally, the study investigated the relationship between PCs consisting of chemokines and cytokines and comorbid inflammatory and cardiometabolic diseases. Analysis revealed a small or moderate correlation between 47% of the analytes measured by the two platforms. Two proteomic profiles were identified that differentiated individuals with moderate to severe MDD from HCs. High eotaxin, age, BMI, IP-10, or IL-10 characterized profile 1. This profile was associated with several cardiometabolic risk factors, including hypertension, hyperlipidemia, and type 2 diabetes. Profile 2 is characterized by higher age, BMI, interleukins, and a strong negative loading for eotaxin. This profile was associated with inflammation but not cardiometabolic risk factors. This study provides further evidence that proteomic profiles can be used to identify potential biomarkers and pathways associated with MDD and comorbidities. Our findings suggest that MDD is associated with distinct profiles of proteins that are also associated with cardiometabolic risk factors, inflammation, and obesity. In particular, the chemokines eotaxin and IP-10 appear to play a role in the relationship between MDD and cardiometabolic risk factors. These findings suggest that a focus on the interplay between MDD and comorbidities may be useful in identifying potential targets for intervention and improving overall health outcomes.

Identifiants

pubmed: 38435722
doi: 10.1016/j.bbih.2024.100731
pii: S2666-3546(24)00009-7
pmc: PMC10906146
doi:

Types de publication

Journal Article

Langues

eng

Pagination

100731

Informations de copyright

© 2024 The Authors.

Déclaration de conflit d'intérêts

There is no conflict of interest among all the authors with either Luminex or Somalogic.BL and IK are a full-time employees of the biopharmaceutical company Alkahest, Inc.

Auteurs

Kathleen T Watson (KT)

Department of Psychiatry and Behavioral Health, Stanford School of Medicine, Stanford, CA, USA.

Jennifer Keller (J)

Department of Psychiatry and Behavioral Health, Stanford School of Medicine, Stanford, CA, USA.

Caleb M Spiro (CM)

Department of Psychiatry and Behavioral Health, Stanford School of Medicine, Stanford, CA, USA.

Isaac B Satz (IB)

Department of Psychiatry and Behavioral Health, Stanford School of Medicine, Stanford, CA, USA.

Samantha V Goncalves (SV)

Department of Psychiatry and Behavioral Health, Stanford School of Medicine, Stanford, CA, USA.

Heather Pankow (H)

Department of Psychiatry and Behavioral Health, Stanford School of Medicine, Stanford, CA, USA.

Idit Kosti (I)

Alkahest Inc, San Carlos, CA, USA.

Benoit Lehallier (B)

Alkahest Inc, San Carlos, CA, USA.

Adolfo Sequeira (A)

Department of Psychiatry & Human Behavior, University of California, Irvine, CA, USA.
School of Medicine, Irvine, CA, USA.

William E Bunney (WE)

Department of Psychiatry & Human Behavior, University of California, Irvine, CA, USA.
School of Medicine, Irvine, CA, USA.

Natalie L Rasgon (NL)

Department of Psychiatry and Behavioral Health, Stanford School of Medicine, Stanford, CA, USA.

Alan F Schatzberg (AF)

Department of Psychiatry and Behavioral Health, Stanford School of Medicine, Stanford, CA, USA.

Classifications MeSH