Serum proteomics analysis of drug-naïve patients with generalised anxiety disorder: Tandem mass tags and multiple reaction monitoring

Abstract

Objectives

The prevalence of generalised anxiety disorder (GAD) is high. However, the underlying mechanisms remain elusive. Proteomics techniques can be employed to assess the pathological mechanisms involved in GAD.

Methods

Twenty-two drug-naive GAD patients were recruited, their serum samples were used for protein quantification and identified using Tandem Mass Tag and Multiple Reaction Monitoring (MRM). Machine learning models were employed to construct predictive models for disease occurrence by using clinical scores and target proteins as input variables.

Results

A total of 991 proteins were differentially expressed between GAD and healthy participants. Gene Ontology analysis revealed that these proteins were significantly associated with stress response and biological regulation, suggesting a significant implication in anxiety disorders. MRM validation revealed evident disparities in 12 specific proteins. The machine learning model found a set of five proteins accurately predicting the occurrence of the disease at a rate of 87.5%, such as alpha 1B-glycoprotein, complement component 4 A, transferrin, V3-3, and defensin alpha 1. These proteins had a functional association with immune inflammation.

Conclusions

The development of generalised anxiety disorder might be closely linked to the immune inflammatory stress response.

Keywords:

• Immune inflammation
• drug-naive
• tandem mass tags
• multiple reaction monitoring
• machine learning

Acknowledgements

Additional thanks to the Beijing Biobank of Clinical Resources-Mental Disorders (BBCR-MD) for their excellent assistance with sample collection, storage preparation, processing, and to provide healthy control samples.

Authors contributions

Conception- H.J. and H.Z; Design- H.J.; Supervision- H.J.; Data collection and/or processing- L.Z., X.L., Z.F., G.Z., Y.D., and L.M.; Analysis and/or interpretation- S.Z. Literature review- X.L.; Writing- X.L. and H.Z; Critical review- H.J.

Statement of interest

All authors have read the journal’s policy on disclosure of potential conflicts of interest. All authors have disclosed any financial or personal relationship with organisations that could potentially be perceived as influencing the described research.

Data availability statement

In response to reasonable requests, the corresponding author Jia Hongxiao is willing to provide the data supporting this study’s findings.

Additional information

Funding

This study was supported by Beijing Hospitals Authority Clinical Medicine Development of Special Funding (ZYLX202129), Beijing Hospitals Authority’s Ascent Plan (DFL20191901) and Beijing Chinese Medicine Science and Technology Development Fund Projects (BJZYQN-2023-32). The funding agencies were not involved in the study design, data collection, analysis, and interpretation, in writing the report, or in the publication decision. All authors have read and agreed to the published version of the manuscript.