Jing Wang, Yixin Gong, Tong Yue, Xianming Li, Qin Wang, Tian Wei, Likun Yang, Xueying Zheng, Sihui Luo, Yu Ding, Hongbo Chen, Jianping Weng, Yujie Liu
Large-for-gestational-age (LGA) births occur in many pregnancies with an apparently metabolically healthy phenotype, limiting risk identification based on conventional clinical characteristics alone. We explored the association between second-trimester maternal serum lipidomic profiles and LGA risk in this apparently healthy population using a nested case-control design within an ongoing prospective pregnancy cohort. The study included a derivation cohort of 135 participants and an independent temporal validation cohort of 66 participants. Lipidomic profiles were analyzed by using liquid chromatography and high-resolution mass spectrometry. Multivariate modeling identified 11 circulating lipid biomarkers (seven glycerophospholipids, two glycerolipids, and two sphingolipids) associated with LGA risk. Integrating these lipid biomarkers with routine clinical factors substantially improved predictive performance compared with clinical variables alone. These findings suggest that metabolic alterations are detectable before clinical manifestations become apparent and support serum lipidomic profiling as a complementary approach for early risk stratification in pregnancies traditionally considered low risk.