Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA, 02115, USA.
Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Sci Rep. 2020 Oct 21;10(1):17353. doi: 10.1038/s41598-020-74078-w.
We hypothesize that first trimester circulating micro particle (CMP) proteins will define preeclampsia risk while identifying clusters of disease subtypes among cases. We performed a nested case-control analysis among women with and without preeclampsia. Cases diagnosed < 34 weeks' gestation were matched to controls. Plasma CMPs were isolated via size exclusion chromatography and analyzed using global proteome profiling based on HRAM mass spectrometry. Logistic models then determined feature selection with best performing models determined by cross-validation. K-means clustering examined cases for phenotypic subtypes and biological pathway enrichment was examined. Our results indicated that the proteins distinguishing cases from controls were enriched in biological pathways involved in blood coagulation, hemostasis and tissue repair. A panel consisting of C1RL, GP1BA, VTNC, and ZA2G demonstrated the best distinguishing performance (AUC of 0.79). Among the cases of preeclampsia, two phenotypic sub clusters distinguished cases; one enriched for platelet degranulation and blood coagulation pathways and the other for complement and immune response-associated pathways (corrected p < 0.001). Significantly, the second of the two clusters demonstrated lower gestational age at delivery (p = 0.049), increased protein excretion (p = 0.01), more extreme laboratory derangement (p < 0.0001) and marginally increased diastolic pressure (p = 0.09). We conclude that CMP-associated proteins at 12 weeks' gestation predict the overall risk of developing early preeclampsia and indicate distinct subtypes of pathophysiology and clinical morbidity.
我们假设,在确定子痫前期风险的同时,第一孕期循环微粒(CMP)蛋白将识别病例中的疾病亚型簇。我们在有和没有子痫前期的妇女中进行了嵌套病例对照分析。<34 周妊娠的病例与对照相匹配。通过尺寸排阻色谱法分离血浆 CMP,并使用基于 HRAM 质谱的全局蛋白质组分析进行分析。然后,逻辑模型通过交叉验证确定特征选择,最佳性能模型确定。K-均值聚类检查病例的表型亚型,并检查生物途径富集。我们的结果表明,将病例与对照区分开来的蛋白质在涉及血液凝固、止血和组织修复的生物学途径中富集。由 C1RL、GP1BA、VTNC 和 ZA2G 组成的面板表现出最佳的区分性能(AUC 为 0.79)。在子痫前期病例中,两个表型亚群区分了病例;一个富含血小板脱颗粒和血液凝固途径,另一个富含补体和免疫反应相关途径(校正后 p<0.001)。重要的是,这两个亚群中的第二个显示出较低的分娩时胎龄(p=0.049)、增加的蛋白质排泄(p=0.01)、更极端的实验室紊乱(p<0.0001)和舒张压略有增加(p=0.09)。我们得出结论,妊娠 12 周时与 CMP 相关的蛋白质可预测发生早期子痫前期的总体风险,并表明病理生理学和临床发病率存在不同的亚型。