Suppr超能文献

健康妊娠中胎盘来源蛋白的变化——评估胎盘功能的新方法?

Placenta-derived proteins across gestation in healthy pregnancies-a novel approach to assess placental function?

机构信息

Department of Obstetrics, Division of Obstetrics and Gynecology, Oslo University Hospital Rikshospitalet, Oslo, Norway.

Department of Biostatistics, Oslo Centre for Biostatistics and Epidemiology, University of Oslo, Oslo, Norway.

出版信息

BMC Med. 2022 Jul 1;20(1):227. doi: 10.1186/s12916-022-02415-z.

Abstract

BACKGROUND

Placenta-derived proteins in the systemic maternal circulation are suggested as potential biomarkers for placental function. However, the identity and longitudinal patterns of such proteins are largely unknown due to the inaccessibility of the human placenta and limitations in assay technologies. We aimed to identify proteins derived from and taken up by the placenta in the maternal circulation. Furthermore, we aimed to describe the longitudinal patterns across gestation of placenta-derived proteins as well as identify placenta-derived proteins that can serve as reference curves for placental function.

METHODS

We analyzed proteins in plasma samples collected in two cohorts using the Somalogic 5000-plex platform. Antecubital vein samples were collected at three time points (gestational weeks 14-16, 22-24, and 30-32) across gestation in 70 healthy pregnancies in the longitudinal STORK cohort. In the cross sectional 4-vessel cohort, blood samples were collected simultaneously from the maternal antecubital vein (AV), radial artery (RA), and uterine vein (UV) during cesarean section in 75 healthy pregnancies. Placenta-derived proteins and proteins taken up by the placenta were identified using venoarterial differences (UV-RA). Placenta-derived proteins were defined as placenta-specific by comparison to the venoarterial difference in the antecubital vein-radial artery (AV-RA). These proteins were described longitudinally based on the STORK cohort samples using a linear mixed effects model per protein. Using a machine learning algorithm, we identified placenta-derived proteins that could predict gestational age, meaning that they closely tracked gestation, and were potential read-outs of placental function.

RESULTS

Among the nearly 5000 measured proteins, we identified 256 placenta-derived proteins and 101 proteins taken up by the placenta (FDR < 0.05). Among the 256 placenta-derived proteins released to maternal circulation, 101 proteins were defined as placenta-specific. These proteins formed two clusters with distinct developmental patterns across gestation. We identified five placenta-derived proteins that closely tracked gestational age when measured in the systemic maternal circulation, termed a "placental proteomic clock."

CONCLUSIONS

Together, these data may serve as a first step towards a reference for the healthy placenta-derived proteome that can be measured in the systemic maternal circulation and potentially serve as biomarkers of placental function. The "placental proteomic clock" represents a novel concept that warrants further investigation. Deviations in the proteomic pattern across gestation of such proteomic clock proteins may serve as an indication of placental dysfunction.

摘要

背景

循环系统中的胎盘衍生蛋白被认为是胎盘功能的潜在生物标志物。然而,由于人类胎盘无法获取以及检测技术的限制,这些蛋白的特性和纵向变化模式在很大程度上仍不为人知。本研究旨在鉴定在母体循环中来源于胎盘并被胎盘摄取的蛋白。此外,我们还旨在描述这些胎盘衍生蛋白在妊娠期间的纵向变化模式,并确定可作为胎盘功能参考曲线的胎盘衍生蛋白。

方法

我们使用 Somalogic 5000-plex 平台分析了两个队列的血浆样本中的蛋白。在 STORK 纵向队列中,70 例健康妊娠女性分别于妊娠 14-16 周、22-24 周和 30-32 周时采集肘前静脉样本。在 4 血管横断面队列中,75 例健康妊娠女性行剖宫产术时同时采集肘前静脉(AV)、桡动脉(RA)和子宫静脉(UV)血样。通过静脉-动脉差值(UV-RA)鉴定胎盘衍生蛋白和胎盘摄取蛋白。将与肘前静脉-桡动脉静脉-动脉差值(AV-RA)比较具有胎盘特异性的蛋白定义为胎盘衍生蛋白。我们对每个蛋白使用线性混合效应模型,基于 STORK 队列样本进行纵向描述。通过机器学习算法,我们鉴定了可预测妊娠年龄的胎盘衍生蛋白,这些蛋白与妊娠密切相关,可能是胎盘功能的潜在检测指标。

结果

在近 5000 种测量蛋白中,我们鉴定了 256 种胎盘衍生蛋白和 101 种被胎盘摄取的蛋白(FDR<0.05)。在释放到母循环中的 256 种胎盘衍生蛋白中,有 101 种被定义为胎盘特异性蛋白。这些蛋白在整个妊娠期间形成了两个具有不同发育模式的簇。我们鉴定了 5 种在系统母血循环中与妊娠年龄密切相关的胎盘衍生蛋白,称为“胎盘蛋白质组钟”。

结论

总之,这些数据可能是健康胎盘衍生蛋白质组在系统母血循环中可测量的参考标准的第一步,并且可能作为胎盘功能的生物标志物。“胎盘蛋白质组钟”是一个新的概念,值得进一步研究。这些蛋白质组钟蛋白的妊娠期间蛋白质组模式的偏差可能表明胎盘功能障碍。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/840f/9248112/43e69d102df1/12916_2022_2415_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验