Transcriptomics-guided serum podoplanin and interpretable machine learning for early risk stratification of necrotizing enterocolitis in preterm infants
- 1Department of Neonatology, Children’s Hospital of Soochow University
- 2Suzhou Medical College, Soochow University
Abstract
Background: To evaluate podoplanin (PDPN) as a circulating biomarker for early necrotizing enterocolitis (NEC) risk stratification and to determine whether an interpretable machine-learning framework integrating PDPN with prediagnostic clinical and inflammatory variables could improve individualized risk estimation.
Methods: PDPN expression was examined in two public NEC intestinal transcriptomic datasets. Serum PDPN was then measured by enzyme-linked immunosorbent assay in a nested case-control cohort of 132 preterm infants (66 with NEC and 66 gestational-age- and birth-weight-matched controls). All candidate predictors were obtained before NEC onset in cases and before the matched reference time in controls. Restricted cubic spline, receiver operating characteristic, precision-recall, LASSO, multivariable logistic regression, 11 machine-learning algorithms, SHAP, and nomogram analyses were performed.
Results: PDPN was upregulated in NEC intestinal tissue. Serum concentrations were higher in infants who developed NEC than in controls (48.36 ± 22.89 vs 19.75 ± 6.26 ng/mL, P < 0.001) and in Bell stage III than in Bell stage II NEC [69.43 (58.91–77.95) vs 30.59 (24.06–42.79) ng/mL, P < 0.001]. PDPN correlated weakly with the C-reactive protein-to-albumin ratio and high-sensitivity C-reactive protein, achieved an area under the receiver operating characteristic curve of 0.905 and an area under the precision-recall curve of 0.925, and remained independently associated with NEC after multivariable adjustment. CatBoost showed the most favorable internal performance among 11 models, with PDPN as the leading SHAP contributor. The nomogram achieved an internally assessed area under the curve of 0.974.
Conclusions: Prediagnostic serum PDPN, particularly when combined with routinely available variables, may support early individualized NEC risk stratification. Prospective multicenter validation and mechanistic studies are warranted.
Related
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- Necrotizing enterocolitis as a disorder of neonatal mucosal immune ecology: from dysbiosis and barrier failure to regulated cell death and precision prevention
- Pharmacokinetics and Efficacy of the FimH Inhibitor Sibofimloc in Preventing Necrotizing Enterocolitis in Preterm Piglets
- Divergent Pontine and Cerebellar Pathology in Preterm Infants With Necrotizing Enterocolitis
- SpCAST enables scalable and interpretable integration of single-cell RNA sequencing and single-cell-resolved spatial transcriptomics
BibTeX
@article{peng2026transcriptomicsguided,
title = {{Transcriptomics-guided serum podoplanin and interpretable machine learning for early risk stratification of necrotizing enterocolitis in preterm infants}},
author = {Hanghang Peng and Xue Liu and Yihui Li and Minqian Zhou and Jingtao Bian and Yuhan Huang and Zengxue Hu and Wenqiang Sun and Xueping Zhu},
journal = {Frontiers in Immunology},
year = {2026},
month = oct,
doi = {10.3389/fimmu.2026.1973760},
url = {https://www.frontiersin.org/articles/10.3389/fimmu.2026.1973760/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Transcriptomics-guided serum podoplanin and interpretable machine learning for early risk stratification of necrotizing enterocolitis in preterm infants
AU - Hanghang Peng
AU - Xue Liu
AU - Yihui Li
AU - Minqian Zhou
AU - Jingtao Bian
AU - Yuhan Huang
AU - Zengxue Hu
AU - Wenqiang Sun
AU - Xueping Zhu
PY - 2026
DA - 2026/10/06
JO - Frontiers in Immunology
DO - 10.3389/fimmu.2026.1973760
UR - https://www.frontiersin.org/articles/10.3389/fimmu.2026.1973760/full
AB - Background: To evaluate podoplanin (PDPN) as a circulating biomarker for early necrotizing enterocolitis (NEC) risk stratification and to determine whether an interpretable machine-learning framework integrating PDPN with prediagnostic clinical and inflammatory variables could improve individualized risk estimation. Methods: PDPN expression was examined in two public NEC intestinal transcriptomic datasets. Serum PDPN was then measured by enzyme-linked immunosorbent assay in a nested case-control cohort of 132 preterm infants (66 with NEC and 66 gestational-age- and birth-weight-matched controls). All candidate predictors were obtained before NEC onset in cases and before the matched reference time in controls. Restricted cubic spline, receiver operating characteristic, precision-recall, LASSO, multivariable logistic regression, 11 machine-learning algorithms, SHAP, and nomogram analyses were performed. Results: PDPN was upregulated in NEC intestinal tissue. Serum concentrations were higher in infants who developed NEC than in controls (48.36 ± 22.89 vs 19.75 ± 6.26 ng/mL, P < 0.001) and in Bell stage III than in Bell stage II NEC [69.43 (58.91–77.95) vs 30.59 (24.06–42.79) ng/mL, P < 0.001]. PDPN correlated weakly with the C-reactive protein-to-albumin ratio and high-sensitivity C-reactive protein, achieved an area under the receiver operating characteristic curve of 0.905 and an area under the precision-recall curve of 0.925, and remained independently associated with NEC after multivariable adjustment. CatBoost showed the most favorable internal performance among 11 models, with PDPN as the leading SHAP contributor. The nomogram achieved an internally assessed area under the curve of 0.974. Conclusions: Prediagnostic serum PDPN, particularly when combined with routinely available variables, may support early individualized NEC risk stratification. Prospective multicenter validation and mechanistic studies are warranted.
SN - 1664-3224
ER -