Evidence map›Paper›PMID 39900554›Full record

ArticleJournal of cellular and molecular medicine2025

Single-Cell Transcriptomic Reveals the Involvement of Cell-Cell Junctions in the Early Development of Hypertrophic Cardiomyopathy.

Dingchen Wang, Miao Lin, Ruobing Wang, Xiaoran Huang, Yaowen Liang, Xiran Wang, Yuge Chen, Yunfei Gao, Huiming Guo, Huiying Liang and 1 more

Abstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

11 authors.

Dingchen WangSchool of Medicine, South China University of Technology, Guangzhou, Guangdong Province, China.
Miao LinGuangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong Province, China.
Ruobing WangGuangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong Province, China.
Xiaoran HuangDepartment of Emergency Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province, China.
Yaowen LiangDepartment of Emergency Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province, China.
Xiran WangGuangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong Province, China.
Yuge ChenDepartment of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Yunfei GaoZhuhai Precision Medical Center, Zhuhai People's Hospital (Zhuhai Hospital Affiliated with Jinan University), Jinan University, Zhuhai, Guangdong Province, China.
Huiming GuoGuangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong Province, China.
Huiying LiangGuangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong Province, China.
Xin LiSchool of Medicine, South China University of Technology, Guangzhou, Guangdong Province, China.ORCID 0000-0003-0469-5121

Funding

Basic and Applied Basic Research Foundation ofGuangdong Province 2024A1515012697National key research and development program intergovernmental key projects 2023YFE0114300National Science Foundation of China 82272246:82122036:82204396Science and Technology Program of Guangzhou 202206010044The Joint Funds of the Natural Science Foundation of China U24A20652
6 · The paper itself

Abstract

The relationship between the changes in endothelial cell-cell junctions and microvascular abnormalities in the progression of hypertrophic cardiomyopathy (HCM), as well as their potential as early biomarkers, remains unclear. Here, we analysed single-nucleus RNA-sequencing data from the left ventricles of 44 health donors and HCM patients. First, we observed that endothelial cell-cell junctions were significantly altered in HCM vascular endothelial cells (ECs), including tight junctions, gap junctions and adherens junctions, especially in capillary ECs. The proposed pseudo-timing analysis predicted that endothelial cell-cell junctions abnormalities occurred in the early stages of HCM. Second, we verified that endothelial cell-cell junctions disorders occur at early stages of HCM disease progression in two time-series single-nucleus datasets of mice. The expression of eight cell-cell junction genes showed an initial increase in the early stage, followed by a slight decrease in the middle stage, and a sharp increase in the later stage. Subsequently, cell communication and transcription factor analysis were used to explore the underlying mechanisms. Furthermore, an early HCM prediction model was developed and independently validated using three mRNA datasets comprising 204 health individuals and HCM patients for the eight genes panel, the accuracy was 0.81 [0.63-0.98]. Finally, we validated this panel in HCM tissues. This study demonstrated in humans and mice that eight cell-cell junction genes were significantly elevated in the early stages of HCM and may be potential biomarkers for the early diagnosis of HCM.

Indexed as

Cardiomyopathy, HypertrophicIntercellular JunctionsSingle-Cell AnalysisTranscriptomeAnimalsBiomarkersCell CommunicationDisease ProgressionEndothelial CellsFemaleGene Expression ProfilingHumansMaleMiceMiddle AgedBiomarkerscell–cell junctionendothelial cellshypertrophic cardiomyopathysnRNA‐seq

Identifiers

PMID39900554
PMCPMC11790354

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.