The conventional differentiation of affective disorders into major depressive disorder (MDD) and bipolar disorder (BD) has insufficient biological evidence. Utilizing multiple proteins quantified in plasma may provide critical insight into these limitations. In this study, the plasma proteomes of 299 patients with MDD or BD (aged 19–65 years old) were quantified using multiple reaction monitoring. Based on 420 protein expression levels, a weighted correlation network analysis was performed. Significant clinical traits with protein modules were determined using correlation analysis. Top hub proteins were determined using intermodular connectivity, and significant functional pathways were identified. Weighted correlation network analysis revealed six protein modules. The eigenprotein of a protein module with 68 proteins, including complement components as hub proteins, was associated with the total Childhood Trauma Questionnaire score (r = −0.15, p = 0.009). Another eigenprotein of a protein module of 100 proteins, including apolipoproteins as hub proteins, was associated with the overeating item of the Symptom Checklist-90-Revised (r = 0.16, p = 0.006). Functional analysis revealed immune responses and lipid metabolism as significant pathways for each module, respectively. No significant protein module was associated with the differentiation between MDD and BD. In conclusion, childhood trauma and overeating symptoms were significantly associated with plasma protein networks and should be considered important endophenotypes in affective disorders.

Introduction

The conventional differentiation of affective disorders into major depressive disorder (MDD) and bipolar disorder (BD) is based on the history of (hypo)manic symptoms [1]. As treatment regimens and outcomes differ between these disorders, there has been considerable effort to differentiate these disorders, including the use of biological correlates [2, 3]. Top-down biological approaches have expanded our knowledge to facilitate the differentiation of these disorders. However, there are limitations with regard to inconsistency and modest accuracy [4, 5]. Understanding affective disorders based on biological correlates with a transdiagnostic bottom-up approach may explain these limitations and deepen our knowledge of the pathophysiology of these disorders.

Proteomics-based research has received growing interest as proteomes reflect biological functions [6]. Recent technological advances have enabled researchers to simultaneously quantify multiple proteins [7]. While previous studies relied on few markers, multiplexing now permits the construction of networks between multiple proteins [8]. These approaches have focused on comparing specific diseases with healthy controls. For instance, a study from the NESDA (Netherlands Study of Depression and Anxiety) constructed networks with 171 blood proteomes to explain the differentiation between MDD and healthy controls [9]. However, to our knowledge, no study to date has applied this approach trans-diagnostically in individuals with affective disorders.

In this study, we implemented weighted correlation network analysis to identify biologically meaningful modules of interconnected proteins in plasma samples from individuals with affective disorders, including both MDD and BD. Further analysis was performed to determine meaningful traits associated with these modules and to identify hub proteins from these modules.

Materials and methods

Clinical samples
The initial study population comprised 169 patients with MDD and 141 patients with BD from our previous study [10]. In total, 26 patients with BD with a Young Mania Rating Scale (YMRS) total score >12 had been excluded to rule out those with current (hypo)manic symptoms, and 8 patients additionally had been excluded due to missing data of covariates. Patients were enrolled between August 2018 and December 2020 from 6 hospitals, including Seoul National University Hospital (SNUH); Nowon Eulji Medical Center, Eulji University; Seoul Metropolitan Government Seoul National University Boramae Medical Center; Hanyang University Hospital; Inha University Hospital; and Cha University Bundang Medical Center. The diagnosis was based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) and was confirmed with the Mini-International Neuropsychiatric Interview (MINI). Only patients with Clinical Global Index—Severity (CGI-S) ≥ 3 were included.

Patients were excluded if they had taken any anti-inflammatory analgesic within the 2 preceding weeks; had a history of neurosurgery, central nervous system (CNS) diseases, cancer, and tuberculosis; had a substance use disorder other than alcohol, caffeine, and nicotine; were currently lactating or pregnant; and/or were predicted to have an intellectual disability or difficulty in understanding Korean. These exclusions were predominantly based on previous evidence of known associations between these conditions and protein expression [11,12,13,14,15,16,17,18,–19]. Patients with a history of neuromodulation or intensive psychotherapy for the past 2 months were also excluded to confine the effect of treatment to psychotropic medications.

Plasma samples from each individual were collected in a 6-mL ethylenediaminetetraacetic acid (EDTA) tube (ref. 367863, Becton, Dickinson and Company, Trenton, NJ) and centrifuged at 1100–1300g for 10–15 min at 4 °C or room temperature. The collected supernatant was stored in Eppendorf tubes at ≤−70 °C until usage.

The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. Informed consent for each participant was obtained. The study was reviewed by the Institutional Review Boards of Seoul National University Hospital (IRB No. 1806-1065-951) and all other participating hospitals.

PMID 37296094