Dissecting depression symptoms: multi-omics clustering uncovers immune-related subgroups and cell-type specific dysregulation

• DOI: 10.1101/2024.03.07.24303916
• Publication Date: 2024-03-08T22:45:12Z
• Authors: Jonas Hagenberg; ; ; Tanja M. Brückl; Mira Erhart; Johannes Kopf-Beck; Maik Ködel; Ghalia Rehawi; Simone Röh-Karami...; Susann Sauer; Natan Yusupov; Monika Rex-Haffner; Victor I. Spoormaker; Philipp Sämann; Elisabeth Binder; Janine Knauer-Arloth
• Keywords: Immune Dysregulation; Depression

Abstract In a subset of patients with mental disorders, such as depression, low-grade inflammation and altered immune marker concentrations are observed. However, these alterations often assessed by only one data type small panels. Here, we used transdiagnostic approach combined from two cohorts to define subgroups depression symptoms across the diagnostic spectrum through large-scale multi-omics clustering in 237 individuals. The method incorporated age, body mass index (BMI), 43 plasma markers RNA-seq peripheral mononuclear blood cells (PBMCs). Our initial revealed four clusters, including immune-related symptom clusters characterized elevated BMI, higher severity levels interleukin-1 receptor antagonist (IL-1RA), C-reactive protein (CRP) C-C motif chemokine 2 (CCL2 or MCP-1). contrast, mostly differentiated cluster low severity, enriched brain related gene sets. This was also distinguished electrocardiography data, while structural imaging differences ventricle volumes clusters. Incorporating predicted cell proportions into resulted three showing concentrations. proportion genes types were most pronounced an intermediate cluster, suggesting that measure different aspects dysregulation. Lastly, found dysregulation SERPINF1 /VEGF-A pathway specific dendritic integrating data. shows advantages combining modalities highlights possible for further stratification research symptoms.