Dataset Information

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

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

ORGANISM(S): Homo sapiens

PROVIDER: GSE260603 | GEO | 2024/03/05

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:Purpose: The goal of the study is to determine the phenotypic and functional states of glioma cells induce in response to a standard glioblastoma therapy, ionizing radiation. Methods: We performed single-cell RNA-sequencing on a patient-derived gliomasphere line isolated from a primary glioblastoma tumor. Cells were exposed to a single dose of radiation ( 8 Gy) for 2- and 7-days to elaborate their gene expression profile. Single cell suspensions and cDNA library preparation was done using 10x Genomics Chromium single cell reagent kit v3 according to manufacturer's protocol. cDNA samples were sequenced on 1 lane of NovaSeq 6000 S2 flowcell. Reads were mapped to HumanGRCh38 genome using Cell Ranger v.3.0.2. More than 600 million reads were obtained for each sample. Average number of genes detected was 5875 (SE±357). Confident read mapping rates were 81.2-87.4% with over 86.8% of reads in cells. Seurat package v3.1.1 was used for integrated analysis by Canonical correlation analysis method with 75 dimensions . PCA was used for dimensional reduction, and Cell clustering was performed using shared nearest neighbor method. Each cell cluster was annotated by a combination of the following methods 1) canonical marker expression 2) Gene Set Enrichment Analysis (GSEA) of cluster specific markers determined by Find Markers function in Seurat and 3) Co-expression modules obtained by Louvain community detection clustering method. Trajectory analysis was done with monocle 3 (version 0.2.1.3) by converting Seurat object to monocle. Results: We identified 14 distinct clusters in all samples, and found dynamic alterations in frequency and size of clusters between non-radiated and radiated cells. Louvian community detection and co-expressed gene module analysis revealed that clusters expressing mitotic and DNA repair modules were diminshed, whereas clusters expressing stemness, mesenchymal and vasculogenesis modules increased post-radiation. Conclusion: Radiation therapy induces diverse functional states in glioma cells.

Dataset Information

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure