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Multi-omics Analyses Identify AKR1A1 as a Biomarker for Diabetic Kidney Disease
Diabetes ( IF 7.7 ) Pub Date : 2024-02-23 , DOI: 10.2337/db23-0540 DengFeng Li 1 , Fang-Chi Hsu 1 , Nicholette D. Palmer 2 , Liang Liu 3 , Young A Choi 4 , Mariana Murea 4 , John S. Parks 5 , Donald W. Bowden 2 , Barry I. Freedman 4 , Lijun Ma 4
Diabetes ( IF 7.7 ) Pub Date : 2024-02-23 , DOI: 10.2337/db23-0540 DengFeng Li 1 , Fang-Chi Hsu 1 , Nicholette D. Palmer 2 , Liang Liu 3 , Young A Choi 4 , Mariana Murea 4 , John S. Parks 5 , Donald W. Bowden 2 , Barry I. Freedman 4 , Lijun Ma 4
Affiliation
Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease. As many genes associate with DKD, multi-omics approaches were employed to narrow the list of functional genes, gene products and related pathways providing insights into the pathophysiological mechanisms of DKD. The Kidney Precision Medicine Project human kidney single-cell RNA-sequencing (scRNAseq) dataset and Mendeley Data on human kidney cortex biopsy proteomics were utilized. R package Seurat was used to analyze scRNAseq and subset proximal tubule cells. PathfindR was applied for pathway analysis in cell type-specific differentially expressed genes and R limma package was used to analyze differential protein expression in kidney cortex. A total of 790 differentially expressed genes were identified in proximal tubule cells, including 530 upregulated and 260 downregulated transcripts. Compared with differentially expressed proteins, 24 genes/proteins were in common. An integrated analysis combining protein quantitative trait loci (pQTL), GWAS hits (estimated glomerular filtration rate) and a plasma metabolomics analysis was performed using baseline metabolites predictive of DKD progression in our longitudinal Diabetes Heart Study samples. Aldo-keto reductase family 1 member A1 gene (AKR1A1) was revealed as a potential molecular hub for DKD cellular dysfunction in several cross-linked pathways featured by deficiency of this enzyme.
更新日期：2024-02-23
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