Single-cell analysis of human PBMCs in healthy and type 2 diabetes populations: dysregulated immune networks in type 2 diabetes unveiled through single-cell profiling

  • Doeon Gu
  • , Jinyeong Lim
  • , Kyung Yeon Han
  • , In Ho Seo
  • , Jae Hwan Jee
  • , Soo Jin Cho
  • , Yoon Ho Choi
  • , Sung Chul Choi
  • , Jang Hyun Koh
  • , Jin Young Lee
  • , Mira Kang
  • , Dong Hyuk Jung
  • , Woong Yang Park

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Abnormalities in glucose metabolism that precede the onset of type 2 diabetes (T2D) activate immune cells, leading to elevated inflammatory factors and chronic inflammation. However, no single-cell RNA sequencing (scRNA-seq) studies have characterized the properties and networks of individual immune cells in T2D. Here, we analyzed peripheral blood mononuclear cells (PBMCs) from non-diabetes and T2D patients by scRNA-seq. We found that CD14 monocytes in T2D patients were in a pro-inflammatory state and intermediate monocytes expressed more MHC class II genes. In T2D patients, cytotoxic CD4 T cells, effector memory CD8 T cells, and γδ T cells have increased cytotoxicity and clonal expansion. B cells were characterized by increased differentiation into intermediate B cells, plasma cells, and isotype class switching with increased expression of soluble antibody genes. These results suggest that monocytes, T cells, and B cells could interact to induce chronic inflammation in T2D patients with pro-inflammatory characteristics.

Original languageEnglish
Article number1397661
JournalFrontiers in Endocrinology
Volume15
DOIs
StatePublished - 2024

Keywords

  • cell interaction
  • monocyte
  • pro-inflammatory characteristics
  • single-cell RNA sequencing
  • T cell
  • type 2 diabetes

Fingerprint

Dive into the research topics of 'Single-cell analysis of human PBMCs in healthy and type 2 diabetes populations: dysregulated immune networks in type 2 diabetes unveiled through single-cell profiling'. Together they form a unique fingerprint.

Cite this