Evidence map›Paper›PMID 41582386›Full record

ArticleEndocrine, metabolic & immune disorders drug targets2026

Decoding Diabetes: Hub Genes as Pivotal Players in Cardiomyopathy and Kidney Disease.

Jiarong Liu, Wen Chen, Yun Zou, Jixiong Xu

Abstract read
In one paragraph

Article in Endocrine, metabolic & immune disorders drug targets, 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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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Jiarong LiuDepartment of Endocrine and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, People's Republic of China.
Wen ChenDepartment of Endocrine and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, People's Republic of China.
Yun ZouDepartment of Endocrine and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, People's Republic of China.
Jixiong XuDepartment of Endocrine and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionDiabetes mellitus (DM) induces systemic vascular dysfunction and leads to life-threatening complications, including diabetic cardiomyopathy (DCM) and diabetic kidney disease (DKD), whose shared mechanisms remain elusive. In this study, we performed an indepth bioinformatics analysis to identify shared therapeutic targets and key molecular players in DKD and DCM.

methodsIntegrated computational and experimental approaches were employed. Bioinformatics analysis of GEO datasets (GSE30122 and GSE197850) identified differentially expressed genes (DEGs). Hub genes were extracted via protein-protein interaction networks and functional enrichment.

resultsWe identified 48 common DEGs ( DISCUSSION: Our study is one of the first to simultaneously investigate the molecular underpinnings of DKD and DCM by integrating bioinformatics data with experimental validation. Meanwhile, the relatively small sample sizes may limit the statistical power and generalizability of the identified DEGs.

conclusionThis study uncovers novel shared mechanisms between DCM and DKD, providing a framework for dual-organ protective therapies to advance the management of diabetic complications.

Indexed as

Diabetes Mellitus, ExperimentalDiabetic CardiomyopathiesDiabetic NephropathiesAnimalsComputational BiologyGene Expression ProfilingGene Regulatory NetworksHumansMaleMyocytes, CardiacPodocytesProtein Interaction MapsRatsbioinformatics analysisdiabetic cardiomyopathyDiabetic kidney diseasedifferentially expressed geneshyperglycemiain vivo/in vitro experiments

Identifiers

PMID41582386
PMCPMC13662719

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.