Evidence map›Paper›PMID 40344498›Full record

ArticleJournal of cellular and molecular medicine2025

Characterising Shared and Specific Cell-Cell Communication in Cardiomyopathy Subtypes From Single-Cell Transcriptomics Data.

Wenqi Tao, Miao Gong, Zunping Ke

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

3 authors.

Wenqi TaoDepartment of Cardiology, Jing'an District Centre Hospital of Shanghai, Fudan University, Shanghai, China.
Miao GongDepartment of Geriatrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China.
Zunping KeDepartment of Geriatrics, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China.ORCID 0000-0003-0274-5543

Funding

Natural Science Foundation of Minhang District, Shanghai, China 2024MHZ015
6 · The paper itself

Abstract

Cardiomyopathy encompasses a diverse range of conditions characterised by extensive molecular heterogeneity, particularly the variations in cell-cell communication events such as ligand-receptor interactions and downstream signalling. Understanding the common and unique features of these intercellular interactions is crucial for advancing targeted treatments. We analysed single-cell RNA sequencing datasets from the ventricular regions of patients with arrhythmogenic cardiomyopathy (ACM), dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM) and healthy donors (HD), as well as ischemic cardiomyopathy (ICM). Our analyses focused on cell type-specific disease preferences, differential gene expression, pathway enrichment and particularly cell-cell communication. We observed that inflammatory, autoimmune, angiogenesis, lymphangiogenesis and fibrotic extracellular matrix deposition are consistently enriched across all four disease subtypes, highlighting their universal significance in disease progression through intercellular interactions. Additionally, we identified subtype-specific pathways that reflect distinct intercellular communication patterns unique to each disease subtype: arrhythmia-associated pathways in ACM, chronic inflammation-related pathways in DCM, ECM remodelling pathways in HCM and ischaemic injury and recovery pathways in ICM.

Indexed as

CardiomyopathiesCell CommunicationSingle-Cell AnalysisTranscriptomeCardiomyopathy, DilatedGene Expression ProfilingHumansSignal Transductioncell–cell communicationsdiease specific intercellular interactionsmolecular pathwayssingle nucleus RNA sequencing

Identifiers

PMID40344498
PMCPMC12061637

What OpenQuestion holds

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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.