V.I. Kulakov National Medical Research Center for Obstetrics Gynecology and Perinatology, Ministry of Healthcare of Russian Federation, 117997 Moscow, Russia.
Moscow Center for Advanced Studies, 123592 Moscow, Russia.
Int J Mol Sci. 2024 Oct 3;25(19):10653. doi: 10.3390/ijms251910653.
Preeclampsia (PE) is a complex and multifaceted obstetric syndrome characterized by several distinct molecular subtypes. It complicates up to 5% of pregnancies and significantly contributes to maternal and newborn morbidity, thereby diminishing the long-term quality of life for affected women. Due to the widespread dissatisfaction with the effectiveness of existing approaches for assessing PE risk, there is a pressing need for ongoing research to identify newer, more accurate predictors. This study aimed to investigate early changes in the maternal serum proteome and associated signaling pathways. The levels of 125 maternal serum proteins at 11-13 weeks of gestation were quantified using liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM MS) with the BAK-125 kit. Ten serum proteins emerged as potential early markers for PE: Apolipoprotein M (APOM), Complement C1q subcomponent subunit B (C1QB), Lysozyme (LYZ), Prothrombin (F2), Albumin (ALB), Zinc-alpha-2-glycoprotein (AZGP1), Tenascin-X (TNXB), Alpha-1-antitrypsin (SERPINA1), Attractin (ATRN), and Apolipoprotein A-IV (APOA4). Notably, nine of these proteins have previously been associated with PE in prior research, underscoring the consistency and reliability of our findings. These proteins play key roles in critical molecular processes, including complement and coagulation cascades, platelet activation, and insulin-like growth factor pathways. To improve the early prediction of PE, a highly effective Support Vector Machine (SVM) model was developed, analyzing 19 maternal serum proteins from the first trimester. This model achieved an area under the curve (AUC) of 0.91, with 87% sensitivity and 95% specificity, and a hazard ratio (HR) of 13.5 (4.6-40.8) with < 0.001. These findings demonstrate that serum protein-based SVM models possess significantly higher predictive power compared to the routine first-trimester screening test, highlighting their superior utility in the early detection and risk stratification of PE.
子痫前期（PE）是一种复杂且多方面的产科综合征，其特征是存在几种不同的分子亚型。它影响多达 5%的妊娠，并显著导致母婴发病率增加，从而降低受影响妇女的长期生活质量。由于人们普遍对评估 PE 风险的现有方法的有效性不满意，因此迫切需要开展研究来确定更新、更准确的预测指标。本研究旨在探讨母体血清蛋白质组及其相关信号通路的早期变化。使用 BAK-125 试剂盒，通过液相色谱-多重反应监测质谱法（LC-MRM MS）对 11-13 周妊娠的 125 种母体血清蛋白的水平进行了定量分析。十种血清蛋白被确定为 PE 的潜在早期标志物：载脂蛋白 M（APOM）、补体 C1q 亚成分亚基 B（C1QB）、溶菌酶（LYZ）、凝血酶原（F2）、白蛋白（ALB）、锌-α-2-糖蛋白（AZGP1）、腱糖蛋白-X（TNXB）、α-1-抗胰蛋白酶（SERPINA1）、吸引素（ATRN）和载脂蛋白 A-IV（APOA4）。值得注意的是，其中九种蛋白在之前的研究中与 PE 相关，这突显了我们研究结果的一致性和可靠性。这些蛋白在关键的分子过程中发挥着关键作用，包括补体和凝血级联、血小板激活和胰岛素样生长因子途径。为了提高 PE 的早期预测效果，我们开发了一个高效的支持向量机（SVM）模型，分析了来自第一孕期的 19 种母体血清蛋白。该模型的曲线下面积（AUC）为 0.91，灵敏度为 87%，特异性为 95%，风险比（HR）为 13.5（4.6-40.8），P 值＜0.001。这些发现表明，基于血清蛋白的 SVM 模型与常规的第一孕期筛查试验相比具有显著更高的预测能力，突出了它们在 PE 的早期检测和风险分层中的优势。
