Evidence map›Paper›PMID 41188916›Full record

ArticleBMC medical genomics2025

The molecular complexity of deep vein thrombosis was preliminarily explored based on the ceRNA network, scRNA-seq and AlphaFold 2.

Bao-Ze Pan, Qing-Yu Luo, Ming-Jun Jiang, Dan Ning, Li-Ming Deng, Xian-Peng Dai, Zi-Xuan Wu, Zhi-He Deng, Dong-Yang Luo, Yang-Yi-Jing Wang and 3 more

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In one paragraph

Article in BMC medical genomics, 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. 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

13 authors.

Bao-Ze Pan *Department of Vascular Surgery, The Second Affiliated Hospital, Hengyang Medical School, University of South China, No.35, Jiefang Road, Hengyang, Hunan Province, 421001, People's Republic of China.
Qing-Yu Luo *Department of Vascular Surgery, The Second Affiliated Hospital, Hengyang Medical School, University of South China, No.35, Jiefang Road, Hengyang, Hunan Province, 421001, People's Republic of China.
Ming-Jun JiangDepartment of Vascular Surgery, The Second Affiliated Hospital, Hengyang Medical School, University of South China, No.35, Jiefang Road, Hengyang, Hunan Province, 421001, People's Republic of China.
Dan NingDepartment of Vascular Surgery, The Second Affiliated Hospital, Hengyang Medical School, University of South China, No.35, Jiefang Road, Hengyang, Hunan Province, 421001, People's Republic of China.
Li-Ming DengDepartment of Vascular Surgery, The Second Affiliated Hospital, Hengyang Medical School, University of South China, No.35, Jiefang Road, Hengyang, Hunan Province, 421001, People's Republic of China.
Xian-Peng DaiDepartment of Vascular Surgery, The Second Affiliated Hospital, Hengyang Medical School, University of South China, No.35, Jiefang Road, Hengyang, Hunan Province, 421001, People's Republic of China.
Zi-Xuan WuDepartment of Vascular Surgery, The Second Affiliated Hospital, Hengyang Medical School, University of South China, No.35, Jiefang Road, Hengyang, Hunan Province, 421001, People's Republic of China.
Zhi-He DengDepartment of Vascular Surgery, The Second Affiliated Hospital, Hengyang Medical School, University of South China, No.35, Jiefang Road, Hengyang, Hunan Province, 421001, People's Republic of China.
Dong-Yang LuoDepartment of Vascular Surgery, The Second Affiliated Hospital, Hengyang Medical School, University of South China, No.35, Jiefang Road, Hengyang, Hunan Province, 421001, People's Republic of China.
Yang-Yi-Jing WangDepartment of Vascular Surgery, The Second Affiliated Hospital, Hengyang Medical School, University of South China, No.35, Jiefang Road, Hengyang, Hunan Province, 421001, People's Republic of China.
Jie ChenDepartment of Vascular Surgery, The Second Affiliated Hospital, Hengyang Medical School, University of South China, No.35, Jiefang Road, Hengyang, Hunan Province, 421001, People's Republic of China. 1454420262@qq.com.
Guo-Zuo XiongDepartment of Vascular Surgery, The Second Affiliated Hospital, Hengyang Medical School, University of South China, No.35, Jiefang Road, Hengyang, Hunan Province, 421001, People's Republic of China. 55752528@qq.com.
Guo-Shan BiDepartment of Vascular Surgery, The Second Affiliated Hospital, Hengyang Medical School, University of South China, No.35, Jiefang Road, Hengyang, Hunan Province, 421001, People's Republic of China. doctorbi2020@163.com.

Funding

Hengyang science and technology innovation Project 20330046498Hunan Clinical Medical Research Center for thrombotic diseases 2023SK4041Hunan Province Clinical Medical Technology Innovation Guidance Project 2021SK51713Hunan Provincial Innovation Foundation For Postgraduate LXBZZ2024256Hunan Provincial Natural Science Foundation 2024JJ9390Hunan Provincial Natural Science Foundation 2025JJ81026Hunan Provincial Natural Science Foundation of Youth Project 2022JJ40385Science and Technology Plan Project of Hengyang 202222035728University of South China Clinical Research 4310 Program 20224310NHYCG08
6 · The paper itself

Abstract

backgroundDeep vein thrombosis (DVT) is a prevalent peripheral vascular disease that is frequently accompanied by significant complications. However, the complexity and diversity of its pathogenesis have resulted in a lack of in-depth understanding of relevant regulatory targets. The objective of this study was to identify the highly distinctive genes associated with DVT, and to investigate their intricacies.

methodsIn this study, a comprehensive transcriptomic analysis was conducted on blood samples from 4 DVT patients and 6 healthy subjects from an internal test set, employing established standard procedures. Differential (diff) circular RNAs (circRNAs), diff microRNAs (miRNAs) and diff messenger RNAs (mRNAs) associated with DVT were identified to construct a competing endogenous RNA (ceRNA) network model, and node mRNAs were identified in an external validation set (n = 14). Furthermore, a topological analysis was conducted by using 7 protein-protein interaction (PPI) network algorithms. Concurrently, AlphaFold 2 was employed for three-dimensional prediction and assessment of the molecular structure. The comparative toxicology genomics database (CTD) was employed to assess the interconnectivity between these genes. Subsequently, single-cell RNA sequencing (scRNA-seq) was conducted on blood samples from 3 DVT patients and 3 healthy subjects, following the standard protocol, to ascertain the cellular localization of gene expression and the role of core pathways.

resultsA whole-transcriptome analysis identified a total of 406 diff circRNAs, 29 diff miRNAs and 154 diff mRNAs. Concurrently, a total of 6 circRNAs, 5 miRNAs and 16 mRNAs were incorporated into the ceRNA network models (a total of 6 node mRNAs were identified differentially). A total of 5 hub genes (including JAK2, CD36, TNFSF13B, TLR7 and PARP9) were identified by 7 PPI network algorithms. The structure and function of the above genes are adequately described by the AlphaFold 2 and CTD interference scores. A total of 7 cell types were identified by scRNA-seq, and there were obvious differences in the localization of genes and the role of core pathways in different cells.

conclusionsJAK2, CD36, TNFSF13B, TLR7 and PARP9 were identified as potential regulatory target genes for the pathophysiological process of DVT. Additionally, hsa_circ_0095124/hsa-miR-3074-5p/TNFSF13B is a potential regulatory pathway for DVT.

Indexed as

Gene Regulatory NetworksVenous ThrombosisCase-Control StudiesFemaleGene Expression ProfilingHumansMaleMicroRNAsMiddle AgedProtein Interaction MapsRNA, CircularRNA, Competitive EndogenousRNA, MessengerRNA-SeqSequence Analysis, RNASingle-Cell Gene Expression AnalysisMicroRNAsRNA, CircularRNA, Competitive EndogenousRNA, MessengerAlphaFold 2CeRNA networkDeep venous thrombosisPPISingle-cell analysisVascular disease

Identifiers

PMID41188916
PMCPMC12584523

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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.