PDF(Pubmed)
Abstract：
OBJECTIVE: The heterogeneous nature of preeclampsia is a major obstacle to early screening and prevention, and a molecular taxonomy of disease is needed. We have previously identified four subclasses of preeclampsia based on first-trimester plasma proteomic profiles. Herein, we expanded this approach by using a more comprehensive panel of proteins profiled in longitudinal samples.
METHODS: Proteomic data collected longitudinally from plasma samples of women who developed preeclampsia (n=109) and of controls (n=90) were available from our previous report on 1,125 proteins. Consensus clustering was performed to identify subgroups of patients with preeclampsia based on data from five gestational-age intervals by using select interval-specific features. Demographic, clinical, and proteomic differences among clusters were determined. Differentially abundant proteins were used to identify cluster-specific perturbed KEGG pathways.
RESULTS: Four molecular clusters with different clinical phenotypes were discovered by longitudinal proteomic profiling. Cluster 1 involves metabolic and prothrombotic changes with high rates of early-onset preeclampsia and small-for-gestational-age neonates; Cluster 2 includes maternal anti-fetal rejection mechanisms and recurrent preeclampsia cases; Cluster 3 is associated with extracellular matrix regulation and comprises cases of mostly mild, late-onset preeclampsia; and Cluster 4 is characterized by angiogenic imbalance and a high prevalence of early-onset disease.
CONCLUSIONS: This study is an independent validation and further refining of molecular subclasses of preeclampsia identified by a different proteomic platform and study population. The results lay the groundwork for novel diagnostic and personalized tools of prevention.
METHODS: Proteomic data collected longitudinally from plasma samples of women who developed preeclampsia (n=109) and of controls (n=90) were available from our previous report on 1,125 proteins. Consensus clustering was performed to identify subgroups of patients with preeclampsia based on data from five gestational-age intervals by using select interval-specific features. Demographic, clinical, and proteomic differences among clusters were determined. Differentially abundant proteins were used to identify cluster-specific perturbed KEGG pathways.
RESULTS: Four molecular clusters with different clinical phenotypes were discovered by longitudinal proteomic profiling. Cluster 1 involves metabolic and prothrombotic changes with high rates of early-onset preeclampsia and small-for-gestational-age neonates; Cluster 2 includes maternal anti-fetal rejection mechanisms and recurrent preeclampsia cases; Cluster 3 is associated with extracellular matrix regulation and comprises cases of mostly mild, late-onset preeclampsia; and Cluster 4 is characterized by angiogenic imbalance and a high prevalence of early-onset disease.
CONCLUSIONS: This study is an independent validation and further refining of molecular subclasses of preeclampsia identified by a different proteomic platform and study population. The results lay the groundwork for novel diagnostic and personalized tools of prevention.
摘要：
目的：子痫前期的异质性是早期筛查和预防的主要障碍，需要疾病的分子分类学。我们先前已经根据孕早期血浆蛋白质组学图谱鉴定了先兆子痫的四个亚类。在这里，我们通过在纵向样本中使用更全面的一组蛋白质来扩展这种方法。
方法：从发生先兆子痫的妇女（n=109）和对照组（n=90）的血浆样本中纵向收集的蛋白质组数据可从我们先前的1,125种蛋白质的报告中获得。通过使用选择的间隔特异性特征，基于来自五个胎龄间隔的数据，进行共识聚类以识别先兆子痫患者的亚组。人口统计,临床,并确定了簇之间的蛋白质组差异。差异丰富的蛋白质用于鉴定簇特异性扰动的KEGG途径。
结果：通过纵向蛋白质组学分析发现了四种具有不同临床表型的分子簇。第1组涉及代谢和血栓形成改变，早发型先兆子痫和小于胎龄新生儿的发生率高；第2组包括母体抗胎儿排斥机制和复发性先兆子痫病例；第3组与细胞外基质调节相关，包括大多数轻度，晚发型先兆子痫;第4类以血管生成失衡和早发型疾病的高患病率为特征。
结论：本研究是通过不同蛋白质组平台和研究人群鉴定的先兆子痫分子亚类的独立验证和进一步完善。结果为新型诊断和个性化预防工具奠定了基础。
方法：从发生先兆子痫的妇女（n=109）和对照组（n=90）的血浆样本中纵向收集的蛋白质组数据可从我们先前的1,125种蛋白质的报告中获得。通过使用选择的间隔特异性特征，基于来自五个胎龄间隔的数据，进行共识聚类以识别先兆子痫患者的亚组。人口统计,临床,并确定了簇之间的蛋白质组差异。差异丰富的蛋白质用于鉴定簇特异性扰动的KEGG途径。
结果：通过纵向蛋白质组学分析发现了四种具有不同临床表型的分子簇。第1组涉及代谢和血栓形成改变，早发型先兆子痫和小于胎龄新生儿的发生率高；第2组包括母体抗胎儿排斥机制和复发性先兆子痫病例；第3组与细胞外基质调节相关，包括大多数轻度，晚发型先兆子痫;第4类以血管生成失衡和早发型疾病的高患病率为特征。
结论：本研究是通过不同蛋白质组平台和研究人群鉴定的先兆子痫分子亚类的独立验证和进一步完善。结果为新型诊断和个性化预防工具奠定了基础。
