A non-invasive urinary diagnostic signature for diabetic kidney disease revealed by machine learning and single-cell analysis

This study identifies a three-gene biomarker panel (PDK4, RHCG, FBP1) as a promising non-invasive diagnostic tool for DKD. While demonstrating excellent diagnostic performance. It represents a tubular injury-associated gene signature that is detectable in urinary cells and shows strong association with DKD in transcriptomic datasets, presenting a promising candidate for a non-invasive diagnostic assay.

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Publication Details

Journal
PLoS ONE
Published
2026-01-02
DOI
https://doi.org/10.1371/journal.pone.0340096
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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0.00
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article

A non-invasive urinary diagnostic signature for diabetic kidney disease revealed by machine learning and single-cell analysis

Jintai Luo, Bo Chen, Xiaomei Jiang, Xiaobing Liu et al.
PLoS ONE
Single-cell and spatial transcriptomics
article

A non-invasive urinary diagnostic signature for diabetic kidney disease revealed by machine learning and single-cell analysis

Jintai Luo, Bo Chen, Xiaomei Jiang, Xiaobing Liu, Yingying Zheng, Zixiang Yang
article en

Abstract

This study identifies a three-gene biomarker panel (PDK4, RHCG, FBP1) as a promising non-invasive diagnostic tool for DKD. While demonstrating excellent diagnostic performance. It represents a tubular injury-associated gene signature that is detectable in urinary cells and shows strong association with DKD in transcriptomic datasets, presenting a promising candidate for a non-invasive diagnostic assay.

PLoS ONEVol. 21(1)
First Affiliated Hospital of Guangzhou Medical University (CN), The First Affiliated Hospital of Guangxi University of Traditional Chinese Medicine (CN), Guangxi University of Chinese Medicine (CN), Loudi Central Hospital (CN), Guangzhou Medical University (CN)
Openalex Percentile: Top 99%
Single-cell and spatial transcriptomics
DOIOpen Access PDFOpenAlex
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A non-invasive urinary diagnostic signature for diabetic kidney disease revealed by machine learning and single-cell analysis — Jintai Luo, Bo Chen, et al. · PLoS ONE (2026) | TGRS Research Map | TGRS