Back

SERPINA3 and NDRG1 are critical diagnostic immune genes associated with macrophages in preeclampsia

Wu, Z.; Chen, s.; Chen, w.; Xie, Y.; Zhou, Z.; Huang, L.; Sheng, L.; wang, y.; Chen, b.; Yang, c.; Ke, Y.

2026-02-10 immunology
10.64898/2026.02.09.704892 bioRxiv
Show abstract

ObjectiveThe immune system plays a role in the occurrence and progression of numerous pregnancy complications, particularly preeclampsia (PE). This study aims to identify critical immune biomarkers via machine learning and assess their predictive ability. MethodsGene expression data were retrieved from the GEO database, while immune-related genes were obtained from the ImmPort repository. Differential expression analysis was then conducted to identify immune genes associated with PE. Different immune-related genes (DIRGs) were subjected to functional and pathway enrichment analysis. We adopted protein-protein interaction (PPI) networks for exploring the connections among various DIRGs and integrated two machine-learning to pinpoint candidate biomarkers in PE. Diagnostic performance was assessed via ROC curve analysis, with predictive accuracy further quantified using nomogram calibration. Findings were validated through integrated computational and experimental analyses. In silico validation utilized additional GEO datasets, while experimental confirmation involved qRT-PCR and IHC assessment of placental tissues. We developed a nomogram to predict PE utilizing two immune-related genes. Cellular composition was inferred from transcriptomic data using CIBERSORT deconvolution.. ResultsWe identified 66 differentially expressed genes (DEGs) and 10 DIRGs between PE pregnancies and normotensive pregnancies. The GO analyses revealed that the DIRGs were enriched in gonadotropin secretion, the regulation of gonadotropin secretion, and the regulation of endocrine processes. Functional annotation revealed enrichment in cytokine and neuroactive ligand-receptor pathways. SERPINA3 and NDRG1 emerged as top-performing biomarkers (training AUCs: 0.812 and 0.866; external validation: 0.795 and 0.781), with overexpression validated in clinical specimens. Both genes inversely regulated M2 macrophage abundance (P < 0.05). ConclusionPE is fundamentally an immune-mediated disorder. SERPINA3 and NDRG1 can be identified as key immune genes associated with M2 macrophages, and these findings provide novel perspectives for the diagnosis and pathogenesis of PE.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Placenta
18 papers in training set
Top 0.1%
20.5%
2
Frontiers in Pediatrics
29 papers in training set
Top 0.1%
8.9%
3
PLOS ONE
4510 papers in training set
Top 23%
7.5%
4
Frontiers in Immunology
586 papers in training set
Top 2%
4.2%
5
Scientific Reports
3102 papers in training set
Top 30%
4.1%
6
BMC Medicine
163 papers in training set
Top 1%
3.8%
7
Frontiers in Physiology
93 papers in training set
Top 1%
3.8%
50% of probability mass above
8
The Journal of Clinical Endocrinology & Metabolism
35 papers in training set
Top 0.4%
2.9%
9
Frontiers in Cardiovascular Medicine
49 papers in training set
Top 1%
2.2%
10
Endocrinology
38 papers in training set
Top 0.2%
1.8%
11
BMC Pregnancy and Childbirth
20 papers in training set
Top 0.4%
1.7%
12
International Journal of Molecular Sciences
453 papers in training set
Top 9%
1.4%
13
Frontiers in Genetics
197 papers in training set
Top 6%
1.3%
14
Cell Communication and Signaling
35 papers in training set
Top 0.6%
1.3%
15
Animals
20 papers in training set
Top 0.6%
1.0%
16
Immunology
29 papers in training set
Top 0.7%
1.0%
17
Computational and Structural Biotechnology Journal
216 papers in training set
Top 7%
0.9%
18
Frontiers in Endocrinology
53 papers in training set
Top 2%
0.9%
19
Clinical & Translational Immunology
22 papers in training set
Top 0.2%
0.9%
20
Acta Neuropsychiatrica
12 papers in training set
Top 0.7%
0.9%
21
Journal of Clinical Investigation
164 papers in training set
Top 6%
0.8%
22
Genetics in Medicine
69 papers in training set
Top 0.9%
0.8%
23
BMJ Open
554 papers in training set
Top 12%
0.8%
24
Computational Biology and Chemistry
23 papers in training set
Top 0.4%
0.8%
25
Frontiers in Microbiology
375 papers in training set
Top 8%
0.8%
26
Physiological Genomics
15 papers in training set
Top 0.3%
0.8%
27
Communications Biology
886 papers in training set
Top 20%
0.8%
28
Frontiers in Cell and Developmental Biology
218 papers in training set
Top 8%
0.8%
29
Journal of the American Heart Association
119 papers in training set
Top 4%
0.8%
30
Cells
232 papers in training set
Top 7%
0.7%