Evidence map›Paper›PMID 42477605›Full record

ArticleBMC pregnancy and childbirth2026

Mitochondria-localized protein-encoding genes and programmed cell death-related genes reveal potential molecular perturbations underlying spontaneous preterm birth.

Luguang Zuo, Qingsong Huai, Mingming Zhang, Xin Liu, Xiaoling Shang

Abstract read
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Article in BMC pregnancy and childbirth, 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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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Luguang ZuoThe First Affiliated Hospital of Hebei North University, Zhangjiakou, China.ORCID http://orcid.org/0000-0003-1994-1954
Qingsong HuaiShenzhou Hospital, Shenzhou, China.
Mingming ZhangHebei Key Laboratory of Metabolic Diseases & Clinical Medicine Research Center, Hebei General Hospital, Shijiazhuang, China. zhangmm197612@hebmu.edu.cn.
Xin LiuHebei Key Laboratory of Metabolic Diseases & Clinical Medicine Research Center, Hebei General Hospital, Shijiazhuang, China.
Xiaoling ShangThe First Affiliated Hospital of Hebei North University, Zhangjiakou, China.

Funding

Hebei Natural Science Foundation Project H2024405001
6 · The paper itself

Abstract

backgroundMultiple programmed cell death (PCD) modalities, including apoptosis, autophagy, and ferroptosis, are closely implicated in spontaneous preterm birth (SPTB). Mitochondria serve as central regulators of various PCD pathways, playing a critical role in cellular stress responses and homeostasis. However, comprehensive studies integrating mitochondria-localized protein-encoding genes and PCD-related genes to explore the molecular mechanisms underlying SPTB remain limited.

methodsTwo gene expression datasets from the Gene Expression Omnibus (GEO) were analyzed. Mitochondria-localized protein-encoding genes from MitoCarta3.0 and curated PCD-related gene sets were combined to define a mitochondrial PCD-related gene set (mtPCD-RGs). Differentially expressed genes (DEGs) between SPTB and control samples were identified, and their intersection with mtPCD-RGs was obtained. A protein-protein interaction (PPI) network was constructed, followed by least absolute shrinkage and selection operator (LASSO) regression, random forest (RF) modeling to identify hub genes. External validation of gene expression was performed. Subsequent analyses included gene set enrichment analysis (GSEA), immune infiltration analysis, and the construction of competing endogenous RNA (ceRNA) network.

resultsA total of 63 intersecting genes were identified, and 46 genes were retained after PPI network filtering. BST2 and TRIM22 were eventually identified as key hub genes for SPTB, and their incorporation into a nomogram enabled individualized risk prediction for clinical application. Immunological analysis revealed significant differences in naïve CD4 + T cells, resting NK cells, monocytes, and eosinophils in SPTB peripheral blood samples compared to the control group. BST2 and TRIM22 showed positive correlations with monocyte abundance and negative correlations with naïve CD4 + T cells and resting NK cells.

conclusionBST2 and TRIM22 are identified as pivotal genes in SPTB, potentially reflecting different outcomes of pregnancy, respectively. These genes may serve as potential biomarkers and provide mechanistic insights into SPTB, highlighting promising targets for future therapeutic interventions.

Indexed as

ApoptosisMitochondriaMitochondrial ProteinsPremature BirthFemaleGene Expression ProfilingHumansPregnancyProtein Interaction MapsMitochondrial ProteinsBST2Machine learningMitochondria-localized protein-encoding genesProgrammed cell deathSpontaneous preterm birthTRIM22

Identifiers

PMID42477605
PMCPMC13663287

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