ArticleFrontiers in immunology2023
Identification and verification of diagnostic biomarkers based on mitochondria-related genes related to immune microenvironment for preeclampsia using machine learning algorithms.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Identifying mitochondrial genes and potential biological functions in pre-eclampsia: bioinformatics and experimental insights.Frontiers in genetics · 2026Article
- Review
- ACO1 OGDH axis drives mitochondrial immune crosstalk in preeclampsia through systems biology enabling dual target therapy.Scientific reports · 2025Article
- AttBiomarker: unveiling preeclampsia biomarkers and molecular pathways through two-stage gene selection techniques and attention-based CNN with gene regulatory network analysis.Briefings in bioinformatics · 2025Article
- Multiple analytical perspectives of mitochondrial genes in the context of preeclampsia: potential diagnostic markers.Frontiers in immunology · 2025Article
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
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Abstract
Preeclampsia is one of the leading causes of maternal and fetal morbidity and mortality worldwide. Preeclampsia is linked to mitochondrial dysfunction as a contributing factor in its progression. This study aimed to develop a novel diagnostic model based on mitochondria-related genes(MRGs) for preeclampsia using machine learning and further investigate the association of the MRGs and immune infiltration landscape in preeclampsia. In this research, we analyzed GSE75010 database and screened 552 DE-MRGs between preeclampsia samples and normal samples. Enrichment assays indicated that 552 DE-MRGs were mainly related to energy metabolism pathway and several different diseases. Then, we performed LASSO and SVM-RFE and identified three critical diagnostic genes for preeclampsia, including CPOX, DEGS1 and SH3BP5. In addition, we developed a novel diagnostic model using the above three genes and its diagnostic value was confirmed in GSE44711, GSE75010 datasets and our cohorts. Importantly, the results of RT-PCR confirmed the expressions of CPOX, DEGS1 and SH3BP5 were distinctly increased in preeclampsia samples compared with normal samples. The results of the CIBERSORT algorithm revealed a striking dissimilarity between the immune cells found in preeclampsia samples and those found in normal samples. In addition, we found that the levels of SH3BP5 were closely associated with several immune cells, highlighting its potential involved in immune microenvironment of preeclampsia. Overall, this study has provided a novel diagnostic model and diagnostic genes for preeclampsia while also revealing the association between MRGs and immune infiltration. These findings offer valuable insights for further research and treatment of preeclampsia.
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