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Discovery of cellular and genetic signatures of immune tolerance in kidney transplant recipients through single cell RNA sequencing analysis

ABSTRACT: The objective of this study was to uncover distinct cellular and genetic signatures of transplant operational tolerance (TOT) in kidney transplant recipients (KTRs) through single cell RNA sequencing (scRNA-seq) using peripheral blood mononuclear cells (PBMCs). PBMCs were isolated from 12 KTRs, including those with TOT (TOT, n = 4), stable allograft function on maintenance immunosuppression (STA, n = 4) and biopsy-proven allograft rejection (BPAR, n = 4). ScRNA-seq of PBMCs was analyzed using 20 cell surface marker antibody sequencing to annotate clusters and 399 immune response panel to identify gene expression. Differences in cellular distribution and gene expression were compared among the three groups. Heatmap hierarchical clustering showed that overall cellular distribution pattern was distinct in TOT in comparison with those in the other two groups, with the proportion of B cells being higher in TOT, attributed to immature B cell fraction (TOT vs. STA vs. BPAR: 4.61% vs. 1.27% vs. 2.53%, p = 0.011). Transcript analysis of B cells revealed that genes involved in allo-immune pathway were downregulated in TOT. In T cell subset analysis, the proportion of regulatory T cells (Tregs) was increased. In transcript analysis, genes associated with inflammation were decreased, while expression levels of CCR6 in Tregs were increased in TOT. Proportions of NKT and NK cells were increased in TOT than in the other two groups. This study showed that TOT has distinct cellular and genetic signatures such as increases of immature B cells and Tregs and high expression levels of CCR6 in Tregs.

ORGANISM(S): Homo sapiens

PROVIDER: GSE224445 | GEO | 2023/04/12

REPOSITORIES: GEO

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Project description:This study corresponds to a re-analysis and meta-analysis of the five transcriptomic studies related to spontaneous tolerance to renal allograft in human. It examines the transcriptome of peripheral blood samples from six distinct clinical groups: healthy volunteers (HV); tolerant patients (TOL); stable patients on minimal immunosuppression (MIS) or maintained on classical immunosuppressive therapy (STA); patients showing either signs of chronic rejection (CR) or acute rejection (AR). The initial studies are the following: -Study 1 from Braud C. et al. (J Cell Biochem., 2008) published under GEO accession number GSE47755 and comprising 250 unique samples (8 HV; 21 TOL; 190 STA; 31 CR). -Study 2 from Brouard S. et al. (Proc Natl Acad Sci U S A., 2007) published under GEO accession number GSE47683 and comprising 67 unique samples (8 HV; 12 TOL; 10 MIS; 12 STA; 11 CR; 14 AR). - Study 3 from Lozano JJ. et al. (Am J Transplant., 2011) published under GEO accession number GSE22707 and comprising 42 unique samples (6 HV; 12 TOL; 12 STA; 12 CR). - Study 4 from Newell KA. et al. (J Clin Invest., 2010) published under GEO accession number GSE22229 and comprising 58 unique samples (12 HV; 19 TOL; 27 STA). - Study 5 from Sagoo P. et al. (J Clin Invest. 2010) published under GEO accession number GSE14655 and comprising two distinct cohorts of patients. The IOT (“Indices of Tolerance”) cohort (5a) corresponds to a European group of patients and totalizes 74 unique samples (8 HV; 10 TOL; 11 MIS; 36 STA; 9 CR). The ITN (“Immune Tolerance in Transplantation”) cohort (5b) corresponds to an American group of patients and totalizes 105 unique samples (20 HV; 22 TOL; 11 MIS; 34 STA; 18 CR). The final data matrix corresponds to the combination of the data from the five independent studies and examines the expression of 1846 meta-genes (MG) across 596 unique blood samples. The 1846 meta-genes correspond to the genes being measured across the five datasets and form a virtual microarray platform (TOL-HUMAN-G1846). The 596 examined samples can be divided into 62 HV, 96 TOL, 32 MIS, 311 STA, 81 CR, and 14 AR.

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Discovery of cellular and genetic signatures of immune tolerance in kidney transplant recipients through single cell RNA sequencing analysis

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