Construction of a diagnostic model for preeclampsia based on differentially expressed lactylation-related genes and the immune infiltration analysis

Preeclampsia is a complex pregnancy complication marked by hypertension and organ dysfunction, posing considerable risks to maternal and fetal health. This study aimed to explore the role of lactylation, a posttranslational modification associated with multiple disease processes, in the pathophysiology of preeclampsia. Comprehensive bioinformatics analyses identified 99 differentially expressed genes (DEGs), among which two lactylation-related DEGs (LRDEGs)-EAF1 and PFKP were significantly up-regulated in preeclampsia. Pathway enrichment analysis revealed that these LRDEGs were strongly associated with the Glycolysis/Gluconeogenesis pathway. A logistic regression model based on the LRDEGs achieved 81.7% accuracy in predicting preeclampsia, validated on the GSE54618 dataset, which achieved 91% accuracy. Immune cell infiltration analysis using CIBERSORT revealed significant differences between the preeclampsia and control cohorts. Additionally, nonnegative matrix factorization classified preeclampsia samples into two subtypes, with distinct immune infiltration profiles. Single-cell RNA sequencing analysis further revealed cell-type-specific expression of the identified diagnostic genes, highlighting heterogeneity within the placental microenvironment. The expression levels of EAF1 and PFKP were significantly increased in placental tissues from individuals with preeclampsia. Collectively, these results suggest that EAF1 and PFKP may represent potential diagnostic biomarkers for preeclampsia and may influence its onset and progression through the Glycolysis/Gluconeogenesis pathway in specific cell types.