Development and validation of multi-modal transformer models for preeclampsia using clinical, metabolomic, and laboratory data
Year: 2026
Type: article
Abstract: Preeclampsia (PE) constitutes a major contributor to maternal–fetal morbidity and mortality, yet prospective identification remains challenging due to limited predictive accuracy of conventional screening modalities. To address this gap, we developed multi-modal transformer models for PE subtypes. This retrospective multicenter cohort study enrolled 491 PE cases and 1,162 normotensive controls across six hospitals in China. Plasma metabolomics, placental growth factor (PlGF), and 40 routine early-gestation laboratory parameters were measured. Subtype-specific models for early-onset PE (EPE) and late-onset PE (LPE) were built using multi-modal transformer models. Distinctive metabolic signatures were identified, comprising 5 and 7 differentially expressed metabolites for EPE and LPE, respectively. On external validation, the multi-modal fusion model achieved an AUC of 0.915 (95% CI 0.862–0.968) for EPE. At a 90% specificity threshold, it yielded sensitivity of 72.2% and a negative predictive value of 97.2%. The clinical factors, metabolomics model attained an AUC of 0.832 (95% CI 0.75–0.914), yielding 57.7% sensitivity with 90% specificity. The multi-modal transformer model showed robust external performance for EPE, supporting its potential to complement current screening. In contrast, LPE performance was modest and requires further improvement. Given the retrospective design, prospective validation is essential before clinical implementation.
Authors: Rui Zhang, Jia Li, Xiao Zhang, Guixue Hou, Zhiguang Zhao, Wenqiu Xu, Wudong He, Ruyun Gao, Zhixu Qiu, Songchang Chen, Suihua Feng, Gefei Xiao, Jie Qin, Shang Huang, Xin Wang, Lanlan Zhang, Xu Han, Liang Lin, Haiquan Hou, Shaohan Cheng, Sufen Zhang, Jianguo Zhang, Lijian Zhao, Qiang Zhao, Fengxiang Wei, Shuyuan Li
Institutions: BGI Group (China), BGI Genomics, Harbin Institute of Technology, Guangdong Medical College, Hebei Medical University, Fudan University, Obstetrics and Gynecology Hospital of Fudan University, Jiangmen Central Hospital, Shenzhen Maternity and Child Healthcare Hospital, Shantou University Medical College, Suzhou Municipal Hospital, Nanjing Medical University, Shanghai Jiao Tong University, International Peace Maternity & Child Health Hospital, Zhuhai Hospital of Integrated Traditional Chinese and Western Medicine, University of Chinese Academy of Sciences
Language: English
Subfield: Obstetrics and Gynecology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,190
OpenAlex ID: W7225797132
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