Small-for-gestational age (SGA) neonates exhibit increased perinatal morbidity and mortality, and a greater risk of developing chronic diseases in adulthood. Currently, no effective maternal blood-based screening methods for determining SGA risk are available. We used a high-resolution MS/MS^ALL shotgun lipidomic approach to explore the lipid profiles of small extracellular vesicles (sEV) released from the placenta into the circulation of pregnant individuals. Samples were acquired from 195 normal and 41 SGA pregnancies. Lipid profiles were determined serially across pregnancy. We identified specific lipid signatures of placental sEVs that define the trajectory of a normal pregnancy and their changes occurring in relation to maternal characteristics (parity and ethnicity) and birthweight centile. We constructed a multivariate model demonstrating that specific lipid features of circulating placental sEVs, particularly during early gestation, are highly predictive of SGA infants. Lipidomic-based biomarker development promises to improve the early detection of pregnancies at risk of developing SGA, an unmet clinical need in obstetrics.

中文翻译：

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怀孕期间循环胎盘细胞外囊泡的脂质谱可识别胎儿生长受限的风险

小于胎龄（SGA）新生儿的围产期发病率和死亡率增加，成年后患慢性疾病的风险更大。目前，尚无有效的基于母血的筛查方法来确定 SGA 风险。我们使用高分辨率 MS/MS ^ALL鸟枪脂质组学方法来探索从胎盘释放到怀孕个体循环中的小细胞外囊泡 (sEV) 的脂质谱。样本取自 195 例正常妊娠和 41 例 SGA 妊娠。在整个怀孕期间连续测定脂质谱。我们确定了胎盘 sEV 的特定脂质特征，这些特征定义了正常妊娠的轨迹及其与母亲特征（胎次和种族）和出生体重百分位数相关的变化。我们构建了一个多变量模型，证明循环胎盘 sEV 的特定脂质特征，特别是在妊娠早期，可以高度预测 SGA 婴儿。基于脂质组学的生物标志物开发有望改善对有 SGA 风险的妊娠的早期检测，这是产科尚未满足的临床需求。