Evidence map›Paper›PMID 40540299›Full record

ArticleFASEB journal : official publication of the Federation of American Societies for Experimental Biology2025

Deciphering the Regulatory Networks of the Migrasome-Associated Cell Subpopulation in Heterotopic Ossification via Multi-Omics Analysis.

Guanzhi Li, Xiao Deng, Tong Li, Yuchen Liu, Lei Tan, Kairui Zhang, Bin Yu

Abstract read
In one paragraph

Article in FASEB journal : official publication of the Federation of American Societies for Experimental Biology, 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. Deciphering the Regulatory Networks of the Migrasome-Associated Cell Subpopulation in Heterotopic Ossification via Multi-Omics Analysis.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2025
    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

7 authors.

Guanzhi LiDivision of Orthopaedics and Traumatology, Department of Orthopaedics, Nanfang Hospital, Southern Medical University, Guangzhou, China.ORCID https://orcid.org/0000-0001-5366-348X
Xiao DengDivision of Orthopaedics and Traumatology, Department of Orthopaedics, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Tong LiDivision of Orthopaedics and Traumatology, Department of Orthopaedics, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Yuchen LiuDivision of Orthopaedics and Traumatology, Department of Orthopaedics, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Lei TanDivision of Orthopaedics and Traumatology, Department of Orthopaedics, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Kairui ZhangDivision of Orthopaedics and Traumatology, Department of Orthopaedics, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Bin YuDivision of Orthopaedics and Traumatology, Department of Orthopaedics, Nanfang Hospital, Southern Medical University, Guangzhou, China.

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2021B1515230004National Key Research and Development Program of China 2022YFC2504305National Natural Science Foundation of China 82072430
6 · The paper itself

Abstract

Heterotopic ossification (HO) is a pathological process where bone forms in extraskeletal tissues, often occurring as a complication of tissue repair following injury. This condition can lead to movement limitations, pain, and functional impairment. However, the underlying pathomechanisms remain poorly understood. This study aims to elucidate key biomolecular networks involved in HO through a comprehensive multi-omics analysis. Single-cell, bulk, and spatial transcriptome datasets were obtained from the Gene Expression Omnibus (GEO) database. Migrasome score analysis identified a critical cell subtype associated with HO. Key genes were identified through high-dimensional weighted gene co-expression network analysis (hdWGCNA), machine learning, and dataset validation from clinical samples. Then we analyzed immune infiltration, microRNA (miRNA) networks, co-expression networks, transcription factor (TF) regulatory networks, and signaling pathways to investigate potential regulatory mechanisms of HO. Spatial transcriptomics revealed the spatial patterns of cell subpopulation distribution and key molecule expression. Experimental validation further confirmed the expression patterns of key molecules in HO. As a result, we identified mesenchymal lineage cells (MLin) as the key migrasome-associated cell subtype and determined peptidylprolyl isomerase B (Ppib) and transgelin (Tagln) as the key molecules. We constructed a regulatory network of these biomolecules and clarified their spatial distribution. Notably, the expression of Ppib and Tagln is temporally correlated with HO progression. Collectively, the identification of Ppib and Tagln, along with the construction of key biomolecular networks, facilitates the discovery of novel biomarkers for HO, offering promising potential for the development of preventive and therapeutic strategies.

Indexed as

Gene Regulatory NetworksOssification, HeterotopicGene Expression ProfilingHumansMesenchymal Stem CellsMicroRNAsMultiomicsTranscriptomeMicroRNAshdWGCNAheterotopic ossificationmachine learningmigrasomesingle‐cell RNA sequencingspatial transcriptomics

Identifiers

PMID40540299
PMCPMC12180572

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.