Evidence map›Paper›PMID 42227533›Full record

ArticleCurrent medicinal chemistry2026

Uncovering Shared Diagnostic Genes and Mechanisms in Chronic Kidney Disease and Atherosclerosis: A Bioinformatics Approach.

Hua Li, Jinfeng Guo, Hao Luo, Rui Huang, Hongwei Su

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Article in Current medicinal chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 authors.

Hua LiCollege of Integrated Traditional and Western Medicine, Southwest Medical University, Luzhou, 646000, China.
Jinfeng GuoCollege of Integrated Traditional and Western Medicine, Southwest Medical University, Luzhou, 646000, China.
Hao LuoCollege of Integrated Traditional and Western Medicine, Southwest Medical University, Luzhou, 646000, China.
Rui HuangCollege of Integrated Traditional and Western Medicine, Southwest Medical University, Luzhou, 646000, China.
Hongwei SuDepartment of Urology, The Affiliated Traditional Medicine Hospital, Southwest Medical University, Luzhou, 646000, China.

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6 · The paper itself

Abstract

objectiveThe purpose of this study was to screen for common diagnostic genes and identify possible molecular mechanisms underlying CKD combined with AS using bioinformatic methods.

methodsWe retrieved the gene expression profiles of CKD and AS from the Gene Expression Omnibus (GEO). Using differential expression combined with WGCNA, we identified hub genes shared by CKD and AS. GO and KEGG enrichment analyses were conducted. To screen the diagnostic biomarker, we constructed PPI networks and applied three ML methods: least absolute shrinkage and selection operator (ASSO), random forest (RF), and Support Vector Machine-Recursive Feature Elimination (SVM-RFE). The diagnostic performance for the candidate gene was assessed by a receiver operating characteristic curve (ROC) on the training set and the external validation dataset. CIBERSORT is used to evaluate immune cell infiltration the DGIdb database predicts possible drugs for treatment.

resultsWe found a total of 119 common genes highly correlated between CKD and AS. The enrichment results showed that these genes are mainly related to the cytoskeleton in the muscle cell, vascular smooth muscle contraction, cGMP-PKG signaling pathway and NF-kappa B signaling pathway. By the integrative PPI and ML analysis, TAGLN was selected as the hub common gene. TAGLN had good diagnostic efficiency (AUC > 0.70) across the training and validation cohorts. Immune infiltration analysis showed significant dysregulation of several immune cells for both diseases. Moreover, two candidate drugs acting on TAGLN were found. DISCUSSION: In this research, we have revealed that TAGLN was an effective diagnostic indicator in CKD-AS comorbidity. The multi-algorithms confirmed TAGLN's outstanding diagnostic ability among six independent samples. Mechanistically, cytoskeletal dysregulation seems to be the key connection of the two diseases, and there is a strong correlation between TAGLN expression and immune cell infiltration. Recombinant transforming growth factor-β1 and azacitidine could possibly function by modulating TAGLN. Our study not only reveals the molecular basis of CKD-AS comorbidity but also provides some useful targets for developing novel diagnostic or therapeutic strategies.

conclusionWe believe our results provide clues to the possibility of using TAGLN as an ideal common diagnostic marker for CKD and AS, and point out some common molecular mechanisms and possible treatment targets between the two diseases that will provide new clues to future research on their pathogenesis, diagnosis, and therapy.

Indexed as

AtherosclerosisComputational BiologyRenal Insufficiency, ChronicBiomarkersGene Expression ProfilingHumansMicrofilament ProteinsMuscle ProteinsBiomarkersMicrofilament ProteinsMuscle ProteinstransgelinatherosclerosisbioinformaticsChronic kidney diseaseGene Expression Omnibus (GEO)machine learningNF-kappa B

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