Human Plasma Proteome During Normal Pregnancy,Journal of Proteome Research

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Human Plasma Proteome During Normal Pregnancy
Journal of Proteome Research ( IF 3.8 ) Pub Date : 2022-09-26 , DOI: 10.1021/acs.jproteome.2c00391
Adi L Tarca _{1,

2,

3} , Roberto Romero _{1,

4,

5,

6,

7} , Gaurav Bhatti _{1,

2} , Francesca Gotsch _{1,

2} , Bogdan Done _{1,

2} , Dereje W Gudicha _{1,

2} , Dahiana M Gallo _{1,

2,

8} , Eunjung Jung _{1,

2} , Roger Pique-Regi _{1,

6} , Stanley M Berry _{1,

2} , Tinnakorn Chaiworapongsa _{1,

2} , Nardhy Gomez-Lopez _{1,

2,

9}

Affiliation

Perinatology Research Branch, Division of Obstetrics and Maternal-Fetal Medicine, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, U.S. Department of Health and Human Services, Bethesda, MD, and, Detroit, Michigan48201, United States.
Department of Obstetrics and Gynecology, Wayne State University School of Medicine, Detroit, Michigan48201, United States.
Department of Computer Science, Wayne State University College of Engineering, Detroit, Michigan48202, United States.
Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, Michigan48103, United States.
Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, Michigan48824, United States.
Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan48202, United States.
Detroit Medical Center, Detroit, Michigan48201, United States.
Department of Obstetrics and Gynecology, University of Valle 13, Cali, Valle del Cauca100-00, Colombia.
Department of Biochemistry, Microbiology and Immunology, Wayne State University School of Medicine, Detroit, Michigan48201, United States.

The human plasma proteome is underexplored despite its potential value for monitoring health and disease. Herein, using a recently developed aptamer-based platform, we profiled 7288 proteins in 528 plasma samples from 91 normal pregnancies (Gene Expression Omnibus identifier GSE206454). The coefficient of variation was <20% for 93% of analytes (median 7%), and a cross-platform correlation for selected key angiogenic and anti-angiogenic proteins was significant. Gestational age was associated with changes in 953 proteins, including highly modulated placenta- and decidua-specific proteins, and they were enriched in biological processes including regulation of growth, angiogenesis, immunity, and inflammation. The abundance of proteins corresponding to RNAs specific to populations of cells previously described by single-cell RNA-Seq analysis of the placenta was highly modulated throughout gestation. Furthermore, machine learning-based prediction of gestational age and of time from sampling to term delivery compared favorably with transcriptomic models (mean absolute error of 2 weeks). These results suggested that the plasma proteome may provide a non-invasive readout of placental cellular dynamics and serve as a blueprint for investigating obstetrical disease.

中文翻译：

正常妊娠期间的人类血浆蛋白质组

尽管人类血浆蛋白质组在监测健康和疾病方面具有潜在价值，但其研究尚未充分。在此，使用最近开发的基于适配体的平台，我们分析了来自 91 个正常妊娠的 528 个血浆样本中的 7288 个蛋白质（基因表达综合标识符 GSE206454）。93% 的分析物（中位数 7%）的变异系数 <20%，并且选定的关键血管生成蛋白和抗血管生成蛋白的跨平台相关性显着。胎龄与 953 种蛋白质的变化相关，包括高度调节的胎盘和蜕膜特异性蛋白质，它们在生长调节、血管生成、免疫和炎症等生物过程中丰富。先前通过胎盘单细胞 RNA-Seq 分析描述的与特定细胞群 RNA 相对应的蛋白质丰度在整个妊娠过程中受到高度调节。此外，基于机器学习的胎龄和从采样到足月分娩时间的预测与转录组模型相比更有利（平均绝对误差为 2 周）。这些结果表明，血浆蛋白质组可以提供胎盘细胞动力学的非侵入性读数，并作为研究产科疾病的蓝图。

更新日期：2022-09-26

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