Evidence map›Paper›PMID 42591226›Full record

ArticleFrontiers in endocrinology2026

A novel continuous-progression CKM model combined with multi-omics data integration identifies lipid metabolic drivers of disease progression.

Hai-Lun Ye, Ya-Ni Wang, Gang-Ao Li, Xing-Hui Jin, Yang Li, Ying-Hua Jin

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 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

6 authors.

Hai-Lun YeKey Laboratory for Molecular Enzymology and Engineering of the Ministry of Education, School of Life Sciences, Jilin University, Changchun, China.
Ya-Ni WangKey Laboratory for Molecular Enzymology and Engineering of the Ministry of Education, School of Life Sciences, Jilin University, Changchun, China.
Gang-Ao LiKey Laboratory for Molecular Enzymology and Engineering of the Ministry of Education, School of Life Sciences, Jilin University, Changchun, China.
Xing-Hui JinKey Laboratory for Molecular Enzymology and Engineering of the Ministry of Education, School of Life Sciences, Jilin University, Changchun, China.
Yang LiKey Laboratory for Molecular Enzymology and Engineering of the Ministry of Education, School of Life Sciences, Jilin University, Changchun, China.
Ying-Hua JinKey Laboratory for Molecular Enzymology and Engineering of the Ministry of Education, School of Life Sciences, Jilin University, Changchun, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Cardiovascular-kidney-metabolic (CKM) syndrome represents an emerging systemic disorder characterized by intertwined metabolic dysfunction, chronic kidney disease, and cardiovascular injury, yet robust preclinical models and mechanistic insights remain limited. Methods: Here, we established a progressive rat model of CKM syndrome by combining high-fat/high-sucrose exposure with adenine-induced renal stress, capturing temporal changes from early metabolic dysregulation to advanced multi-organ injury. Integrative multi-omics analyses incorporating network toxicology, single-cell RNA sequencing, and spatial transcriptomics were performed to investigate molecular features associated with CKM progression. Finally, AI-assisted virtual screening coupled with molecular docking was conducted to identify potential multi-target therapeutic candidates. Results: Longitudinal phenotyping revealed a temporal pattern in which early metabolic abnormalities preceded more prominent renal and cardiovascular impairment. Integrative multi-omics analyses incorporating network toxicology, single-cell RNA sequencing, and spatial transcriptomics consistently converged on lipid metabolic dysregulation as a prominent molecular feature associated with CKM progression. PPARγ, ESR1, and FASN were identified as candidate regulatory nodes associated with CKM-related lipid remodeling. Single-cell analyses revealed enrichment of lipid metabolic programs in renal epithelial compartments, particularly proximal tubular cells, suggesting their potential involvement in CKM-associated renal metabolic remodeling. Spatial transcriptomics further revealed patterns consistent with ectopic adipocyte infiltration, lipid-associated niche remodeling, increased PPARγ/FASN expression, and reduced ESR1 expression in diseased kidneys. AI-assisted virtual screening coupled with molecular docking identified BRD-K26818574 as a potential multi-target therapeutic candidate. Discussion: Collectively, this study establishes a translational CKM model and highlights renal lipotoxic remodeling as a potential therapeutic target in CKM progression.

Indexed as

Cardiovascular DiseasesKidney DiseasesLipid MetabolismMetabolic SyndromeAnimalsDisease Models, AnimalDisease ProgressionMaleMolecular Docking SimulationMultiomicsRatsSpatial Transcriptomicsanimal modelcardiovascular–kidney–metabolic (CKM)single-cell transcriptomicspatial transcriptomicsvirtual drug screening

Identifiers

PMID42591226
PMCPMC13461501

What Socratic 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 Socratic graph.