Evidence map›Paper›PMID 42581084›Full record

ArticleMammalian genome : official journal of the International Mammalian Genome Society2026

Screening for candidate genes and cell populations associated with atherosclerotic calcification using single-cell RNA sequencing.

Huai Wu Yuan, Weiye Wang, Wei Cheng, Hongzhe Wang, Boyan Song, Tian Xiang Chen, Guo Ping Peng

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Article in Mammalian genome : official journal of the International Mammalian Genome Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Huai Wu YuanThe First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Weiye WangThe First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Wei ChengDepartment of neurology, Shengzhou People's Hospital, Shengzhou, China.
Hongzhe WangThe First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Boyan SongThe First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Tian Xiang ChenHangzhou Lianchuan biotechnology Co., Ltd, Shengzhou, China.
Guo Ping PengThe First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China. guopingpeng@zju.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Calcification often occurs as a characteristic pathological manifestation in the progression of atherosclerosis (AS) plaques, but its mechanism is not fully understood yet. The purpose of this research was to supplement the exploration of key candidate genes and key cells involved in the calcification process of AS, building on existing insights into its underlying mechanisms. Through the examination of our internally generated single‑cell RNA sequencing (scRNA-seq) dataset derived from human carotid plaque samples, pivotal cellular populations associated with AS calcification were successfully identified. Following this identification, a comprehensive analytical approach was employed, incorporating differential gene expression profiling alongside the establishment of protein-protein interaction (PPI) networks, thereby enabling the extraction of critical genetic markers within these cellular subsets. Furthermore, a molecular regulatory framework was assembled, aiming to elucidate the mechanistic pathways through which these genetic determinants contribute to the calcification phenomena in AS pathology. Moreover, analysis of cell communication was applied to explore the interactions among cells. Pseudo-time analysis was employed to explore the expression of key candidate genes during the differentiation of key cells. Finally, monocytes were identified as key cells. WARS1, IFITM1, ANXA1, ADGRE2, and S100P were identified as key candidate genes. Moreover, 115 transcription factors such as THRB and 118 miRNAs such as hsa-miR-196a-5p were predicted to be associated with the key candidate genes. Across both calcified and non-calcified control specimens, the cellular communication between endothelial cells and natural killer (NK) T cell populations was consistently orchestrated via the PPBP-CXCR2 signaling axis. During monocytic differentiation trajectories, ADGRE2 expression exhibited a biphasic pattern characterized by initial gradual elevation followed by subsequent decline. Conversely, both ANXA1 and S100P demonstrated progressive upregulation throughout the differentiation process. The expression of IFITM1 and WARS1 first decreased, then increased, and finally decreased again. The present investigation successfully pinpointed five critical genes alongside one key cellular population, collectively providing potential molecular insights and candidate targets for further investigation into AS calcification.

Indexed as

AtherosclerosisCalcinosisSingle-Cell AnalysisAntigens, DifferentiationCell DifferentiationGene Expression ProfilingGene Expression RegulationGene Regulatory NetworksHumansMonocytesPlaque, AtheroscleroticProtein Interaction MapsSequence Analysis, RNASingle-Cell Gene Expression AnalysisAntigens, Differentiationleu-13 antigen

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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 OpenQuestion graph.