Evidence map›Paper›PMID 41751630›Full record

ArticleGenes2026

Integrated Transcriptomic Analysis Identifies Novel Candidate Genes Associated with Calcific Aortic Valve Disease.

Jing Chen, Shichao Guo, Junming Zhu, Haiou Hu, Bing Tang, Lingchen Huang, Chenhan Zhang, Suwei Chen, Sanbao Chai, Zhiyu Qiao and 1 more

Abstract read
In one paragraph

Article in Genes, 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
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0citing papers in PubMed
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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

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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

11 authors.

Jing ChenBeijing Anzhen Hospital of Capital Medical University and Beijing Institute of Heart Lung and Blood Vessel Diseases, Beijing 101118, China.ORCID 0000-0002-0172-0873
Shichao GuoCenter for Aortic Surgery, Beijing Anzhen Hospital of Capital Medical University, Beijing 101118, China.
Junming ZhuCenter for Aortic Surgery, Beijing Anzhen Hospital of Capital Medical University, Beijing 101118, China.
Haiou HuCenter for Aortic Surgery, Beijing Anzhen Hospital of Capital Medical University, Beijing 101118, China.
Bing TangCenter for Aortic Surgery, Beijing Anzhen Hospital of Capital Medical University, Beijing 101118, China.
Lingchen HuangCenter for Aortic Surgery, Beijing Anzhen Hospital of Capital Medical University, Beijing 101118, China.ORCID 0000-0001-7620-9554
Chenhan ZhangCenter for Aortic Surgery, Beijing Anzhen Hospital of Capital Medical University, Beijing 101118, China.
Suwei ChenCenter for Aortic Surgery, Beijing Anzhen Hospital of Capital Medical University, Beijing 101118, China.ORCID 0000-0003-2549-103X
Sanbao ChaiDepartment of Endocrinology and Metabolism, Peking University International Hospital, Beijing 102206, China.
Zhiyu QiaoCenter for Aortic Surgery, Beijing Anzhen Hospital of Capital Medical University, Beijing 101118, China.
Hongfeng JiangBeijing Anzhen Hospital of Capital Medical University and Beijing Institute of Heart Lung and Blood Vessel Diseases, Beijing 101118, China.

Funding

National Natural Science Foundation of China 81970392
6 · The paper itself

Abstract

backgroundCalcified aortic valve disease (CAVD) is a prevalent valvular disorder in the elderly and a major cause of aortic stenosis. Surgical and transcatheter aortic valve replacement remain the primary treatments for advanced CAVD; however, effective pharmacological therapies to prevent or slow disease progression are lacking. Therefore, there is an urgent need to explore potential novel candidate biomarkers and therapeutic targets.

methodsIn this study, transcriptomic data from multiple independent datasets were integrated to comprehensively characterize the transcriptional profile of CAVD. Feature genes were identified using complementary machine learning approaches, followed by functional pathway enrichment and protein-protein interaction (PPI) network analyses to uncover novel candidate genes associated with CAVD. Single-cell RNA sequencing (sc-RNA-Seq) data were further analyzed using pseudotime trajectory analysis to explore transcriptional dynamics during valve interstitial cells' (VICs) osteogenic progression. Quantitative PCR and Western blot analyses of human calcified aortic valve tissues were used for validation.

resultsA total of 119 CAVD-associated genes were identified, primarily involved in ossification, extracellular matrix organization, and cell-substrate adhesion. Among these, the ossification-associated genes BAMBI, HAND2, and MYOC exhibited potential discriminatory power between CAVD and control samples, with notable downregulation in calcified valves. Pseudotime analysis showed that the expression of these genes gradually decreased along the transcriptional trajectory associated with osteogenic differentiation. In addition, the analysis of relative immune signatures revealed negative correlations between these genes and multiple immune signatures.

conclusionsThis study identifies novel candidate genes underlying CAVD pathogenesis and highlights BAMBI, HAND2, and MYOC as potential biomarkers and therapeutic targets, providing new insights into disease mechanisms and opportunities for novel interventions.

Indexed as

Aortic ValveAortic Valve StenosisCalcinosisTranscriptomeGene Expression ProfilingHumansOsteogenesisProtein Interaction MapsBAMBIcalcified aortic valve disease (CAVD)HAND2machine learningMYOCosteogenesissingle-cell RNA sequencing

Identifiers

PMID41751630
PMCPMC12941080

What Socratic holds

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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 Socratic graph.