Evidence map›Paper›PMID 42633340›Full record

ArticleMetabolism open2026

Transcriptomic and genetic evidence highlights EHHADH in a FUNDC1-associated mitochondrial network in diabetic nephropathy.

Yuzhi Chen, Demei Ying, Xuli Guo, Shaozhe Wang, Wenjing Liu, Siwen Wang, Na Kuang, Jiahan Li, Nan Chen

Abstract read
In one paragraph

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

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Yuzhi ChenHebei Key Laboratory of Medical Data Science, School of Medicine, Hebei University of Engineering, Handan, Hebei Province, 056038, China.
Demei YingDepartment of Obstetrics and Gynecology, Xinqiao Hospital, Second Clinical Medical College of Army Medical University, Chongqing, 400037, China.
Xuli GuoHebei Key Laboratory of Medical Data Science, School of Medicine, Hebei University of Engineering, Handan, Hebei Province, 056038, China.
Shaozhe WangHebei Key Laboratory of Medical Data Science, School of Medicine, Hebei University of Engineering, Handan, Hebei Province, 056038, China.
Wenjing LiuDepartment of Pathology, The First Affiliated Hospital of Hebei University of Chinese Medicine, Shijiazhuang, 050011, China.
Siwen WangHebei Key Laboratory of Medical Data Science, School of Medicine, Hebei University of Engineering, Handan, Hebei Province, 056038, China.
Na KuangDepartment of Obstetrics and Gynecology, Xinqiao Hospital, Second Clinical Medical College of Army Medical University, Chongqing, 400037, China.
Jiahan LiHebei Key Laboratory of Medical Data Science, School of Medicine, Hebei University of Engineering, Handan, Hebei Province, 056038, China.
Nan ChenHebei Key Laboratory of Medical Data Science, School of Medicine, Hebei University of Engineering, Handan, Hebei Province, 056038, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Diabetic nephropathy (DN) is a major microvascular complication of diabetes and the leading cause of end-stage renal disease. Glomerular and tubular injury, mitochondrial dysfunction, and impaired mitophagy are core factors driving the progression of DN. Recent studies have identified FUNDC1 as a crucial mitophagy receptor; however, its regulatory mechanism in DN remains poorly elucidated. Methods: This study integrated compartmental transcriptomics, gene interaction network analysis, and summary-data-based Mendelian randomization (SMR) for systematic research. Differentially expressed genes (DEGs) were extracted from the glomerular dataset GSE96804 and the tubular dataset GSE294519. The intersecting genes of these DEGs with FUNDC1-interacting genes and mitochondrial dysfunction-related genes were obtained to screen core hub genes. Combined with renal expression quantitative trait locus (eQTL) data and DN genome-wide association study (GWAS) data, SMR analysis was performed. Functional enrichment analysis, gene set enrichment analysis (GSEA), and upstream transcription factor prediction were further conducted. Results: A total of 5560 DEGs were screened based on adjusted P values (Padj), including 2625 glomerular DEGs, 3199 tubular DEGs, and 264 common DEGs. Twenty FUNDC1-related core hub genes were finally identified, which were mainly enriched in mitophagy and mitochondrial energy metabolism pathways. After correction and screening via the HEIDI test, Transcriptomic and genetic evidence highlights EHHADH in a FUNDC1-associated mitochondrial network in diabetic nephropathy, and its expression was downregulated in DN lesional tissues. FUNDC1 and EHHADH were both associated with mitochondrial metabolic pathways, and E2F4 was predicted to be their common upstream regulatory factor. Conclusions: Multi-dimensional results suggest that EHHADH may represent a candidate gene within a FUNDC1-associated mitochondrial regulatory network in DN. The coordinated expression patterns of FUNDC1 and EHHADH suggest their potential involvement in mitochondrial homeostasis-related processes during DN progression.

Indexed as

Diabetic nephropathyEHHADHFUNDC1Mendelian randomizationMitochondrial dysfunction

Identifiers

PMID42633340
PMCPMC13499379

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.