Integrated transcriptomics identifies key genes and pathways driving CKD to ESRD progression: implications for diagnosis and prognosis
- 1Shaanxi University of Chinese Medicine
Abstract
BackgroundChronic kidney disease (CKD) may progress to stage 5 CKD (end-stage renal disease, ESRD), but stage-associated molecular alterations remain incompletely characterized. This study aimed to identify candidate biomarkers associated with CKD and ESRD.
MethodsTwo discovery datasets comparing CKD or ESRD with healthy controls were analyzed using differential expression analysis and weighted gene co-expression network analysis. Candidate genes were identified by intersecting differentially expressed genes with key co-expression modules, followed by protein-protein interaction network analysis using Degree, Closeness, and Maximal Clique Centrality algorithms. Candidate genes were evaluated in independent GEO validation datasets and further examined by quantitative real-time PCR and western blotting using clinical blood samples.
ResultsTen hub genes were identified, among which EPB42, KLF1, and H3F3A were prioritized for further evaluation. EPB42 showed decreased expression in CKD but increased expression in ESRD, indicating an opposite-direction pattern between the two disease states. KLF1 showed no significant difference between healthy controls and CKD but was increased in ESRD, whereas H3F3A was increased in CKD and further increased in ESRD. Functional enrichment analysis highlighted processes related to oxygen transport, mitochondrial function, muscle-associated processes, and inflammation, suggesting possible involvement of hypoxia-associated oxidative injury and ferroptosis-related processes.
ConclusionsIntegrated transcriptomic and experimental analyses identified EPB42, KLF1, and H3F3A as candidate stage-associated biomarkers in CKD and ESRD. In particular, the opposite-direction expression pattern of EPB42 may provide additional molecular information for distinguishing CKD from ESRD.
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BibTeX
@misc{zhang2026integrated,
title = {{Integrated transcriptomics identifies key genes and pathways driving CKD to ESRD progression: implications for diagnosis and prognosis}},
author = {X. Zhang and Y. Xie and H. Cao and F. Ping and H. Yang and K. Qu and X. Shen},
howpublished = {medRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.14.26365574},
url = {https://www.medrxiv.org/content/10.64898/2026.10.14.26365574v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Integrated transcriptomics identifies key genes and pathways driving CKD to ESRD progression: implications for diagnosis and prognosis
AU - X. Zhang
AU - Y. Xie
AU - H. Cao
AU - F. Ping
AU - H. Yang
AU - K. Qu
AU - X. Shen
PY - 2026
DA - 2026/10/14
PB - medRxiv
DO - 10.64898/2026.10.14.26365574
UR - https://www.medrxiv.org/content/10.64898/2026.10.14.26365574v1
AB - BackgroundChronic kidney disease (CKD) may progress to stage 5 CKD (end-stage renal disease, ESRD), but stage-associated molecular alterations remain incompletely characterized. This study aimed to identify candidate biomarkers associated with CKD and ESRD. MethodsTwo discovery datasets comparing CKD or ESRD with healthy controls were analyzed using differential expression analysis and weighted gene co-expression network analysis. Candidate genes were identified by intersecting differentially expressed genes with key co-expression modules, followed by protein-protein interaction network analysis using Degree, Closeness, and Maximal Clique Centrality algorithms. Candidate genes were evaluated in independent GEO validation datasets and further examined by quantitative real-time PCR and western blotting using clinical blood samples. ResultsTen hub genes were identified, among which EPB42, KLF1, and H3F3A were prioritized for further evaluation. EPB42 showed decreased expression in CKD but increased expression in ESRD, indicating an opposite-direction pattern between the two disease states. KLF1 showed no significant difference between healthy controls and CKD but was increased in ESRD, whereas H3F3A was increased in CKD and further increased in ESRD. Functional enrichment analysis highlighted processes related to oxygen transport, mitochondrial function, muscle-associated processes, and inflammation, suggesting possible involvement of hypoxia-associated oxidative injury and ferroptosis-related processes. ConclusionsIntegrated transcriptomic and experimental analyses identified EPB42, KLF1, and H3F3A as candidate stage-associated biomarkers in CKD and ESRD. In particular, the opposite-direction expression pattern of EPB42 may provide additional molecular information for distinguishing CKD from ESRD.
ER -