| Literature DB >> 32107344 |
Rajasree Menon1, Edgar A Otto1, Paul Hoover2, Sean Eddy1, Laura Mariani1, Bradley Godfrey1, Celine C Berthier1, Felix Eichinger1, Lalita Subramanian1, Jennifer Harder1, Wenjun Ju1, Viji Nair1, Maria Larkina1, Abhijit S Naik1, Jinghui Luo1, Sanjay Jain3, Rachel Sealfon4, Olga Troyanskaya4, Nir Hacohen2, Jeffrey B Hodgin1, Matthias Kretzler1, Kidney Precision Medicine Project Kpmp5.
Abstract
To define cellular mechanisms underlying kidney function and failure, the KPMP analyzes biopsy tissue in a multicenter research network to build cell-level process maps of the kidney. This study aimed to establish a single cell RNA sequencing strategy to use cell-level transcriptional profiles from kidney biopsies in KPMP to define molecular subtypes in glomerular diseases. Using multiple sources of adult human kidney reference tissue samples, 22,268 single cell profiles passed KPMP quality control parameters. Unbiased clustering resulted in 31 distinct cell clusters that were linked to kidney and immune cell types using specific cell markers. Focusing on endothelial cell phenotypes, in silico and in situ hybridization methods assigned 3 discrete endothelial cell clusters to distinct renal vascular beds. Transcripts defining glomerular endothelial cells (GEC) were evaluated in biopsies from patients with 10 different glomerular diseases in the NEPTUNE and European Renal cDNA Bank (ERCB) cohort studies. Highest GEC scores were observed in patients with focal segmental glomerulosclerosis (FSGS). Molecular endothelial signatures suggested 2 distinct FSGS patient subgroups with α-2 macroglobulin (A2M) as a key downstream mediator of the endothelial cell phenotype. Finally, glomerular A2M transcript levels associated with lower proteinuria remission rates, linking endothelial function with long-term outcome in FSGS.Entities:
Keywords: Bioinformatics; Cell Biology; Chronic kidney disease; Nephrology; endothelial cells
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Year: 2020 PMID: 32107344 PMCID: PMC7213795 DOI: 10.1172/jci.insight.133267
Source DB: PubMed Journal: JCI Insight ISSN: 2379-3708