Comprehensive analysis of single-cell transcriptome and bulk transcriptome sequencing identifies B cell-related biomarkers in obesity

Abstract

Abstract Background: Obesity represents a significant public health concern，B cells residing in adipose tissue have been found to be closely associated with weight gain, metabolic dysfunction, and inflammation in individuals with obesity. Nevertheless, the precise contribution of B cells to the development of obesity remains uncertain. In this study, RNA-seq and single-cell RNA sequencing (scRNA-seq) data were combined to explore the molecular mechanisms of B cell involvement in obesity and identify B cell-related biomarkers. Methods: Obesity scRNA-seq and Bulk sequences were downloaded from the GEO database. The scRNA-seq data processing was performed using the R software package "Seurat" and downscaling and cluster identification were performed using UMAP. The FindAllMarkers function is used to identify the marker genes for each cluster. B cell clusters in the dataset were further clustered by PCA, UMAP, and SNN. GO and KEGG analyzed the differential genes of four B cell subtypes. iTALK is used to analyze communication molecules between B cell subsets. Obesity-related differentially expressed genes (DEGs) were obtained by limma software package. Further, LASSO and CytoHubba were used to identify B cell-related biomarkers in obesity. The expression of B cell-related biomarkers was confirmed by RT-PCR in the animal model induced by high-fat diet. Results:Analysis of scRNA-seq data identified 28 cell subpopulations and 9 core cell types. B cells were significantly down-regulated in the obese group compared to the control group. At the same time B cells re-clustered into 10 clusters and they eventually clustered into 4 types, namely Exhausted B cells, Naive B cells, Non-switched memory B cells, and Plasmablasts. We identified 790 B-cell differentially expressed genes from the scRNA-seq dataset and 928 obesity-related differentially expressed genes from the Bulk RNA-seq dataset, and after cross-analysis, CytoHubba and LASSO analysis, we obtained 3 B cell-related biomarkers (GAPDH, AHNAK, HEXIM1). Animal experiments confirmed the expression of three B cell-related biomarkers in obesity. Conclusions: This study revealed the pathogenesis of B cells in obesity and also suggest that 3 B cell-related biomarkers (GAPDH, AHNAK, and HEXIM1) may be promising therapeutic targets in the future obesity therapeutic field.