无胎盘谱(PAS)中血浆外泌体微RNA通路的激活:病理生理学与检测

Jessian L. Munoz MD, PhD, MPH , Brett D. Einerson MD , Robert M. Silver MD , Sureshkumar Mulampurath PhD , Lauren S. Sherman PhD , Pranela Rameshwar PhD , Egle Bytautiene Prewit PhD , Patrick S. Ramsey MD, MSPH
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引用次数: 0

摘要

背景胎盘早剥谱系病是一系列复杂的胎盘病变,与重大的孕产妇发病率和死亡率相关。胎盘早剥的诊断依赖于超声波检查结果,但其阳性预测值并不高。外泌体microRNA是一种小RNA分子,可反映起源组织的细胞过程。研究设计本研究是对2011年至2022年期间在2所学术机构前瞻性收集的样本进行生物标记分析。血浆标本采集自疑似胎盘早剥谱系、前置胎盘或再次剖宫产的患者。通过纳米颗粒追踪分析和免疫印迹法对外泌体进行定量和定性。通过聚合酶链反应阵列和靶向单体定量评估微RNA。使用 Ingenuity Pathway Analyses 软件进行微RNA通路分析。从所有组别中提取胎盘活检组织,并通过聚合酶链反应和全细胞酶联免疫吸附试验进行分析。对使用微RNA预测胎盘早剥谱进行了接收者操作特征曲线单变量分析。结果共分析了 120 例受试者的血浆标本(60 例谱性胎盘、30 例前置胎盘和 30 例对照)。分离出的血浆外泌体平均大小为 71.5 nm,是频谱胎盘标本的 10 倍(20 个颗粒/帧 vs 2 个颗粒/帧)。外泌体的蛋白表达呈阳性,包括细胞内粘附分子 1、绒毛蛋白、附件蛋白和 CD9。微RNA分析显示,在胎盘早剥患者中,3种微RNA(mir-92、-103和-192)的检出率增加。通路相互作用评估显示,在胎盘早剥谱系中,p53 信号的调控不同,而在对照标本中,红细胞癌基因 B2 或人类表皮生长因子 2 的调控不同。这些发现随后在胎盘蛋白分析中得到证实。胎盘微RNA与血浆外泌体微RNA的表达相平行。胎盘早剥谱系特征 microRNA 的生物标记物评估的接收者操作特征曲线下面积为 0.81(P< .001;95% 置信区间,0.73-0.89),灵敏度和特异性分别为 89.2% 和 80%。
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Serum exosomal microRNA pathway activation in placenta accreta spectrum: pathophysiology and detection

BACKGROUND

Placenta accreta spectrum disorders are a complex range of placental pathologies that are associated with significant maternal morbidity and mortality. A diagnosis of placenta accreta spectrum relies on ultrasonographic findings with modest positive predictive value. Exosomal microRNAs are small RNA molecules that reflect the cellular processes of the origin tissues.

OBJECTIVE

We aimed to explore exosomal microRNA expression to understand placenta accreta spectrum pathology and clinical use for placenta accreta spectrum detection.

STUDY DESIGN

This study was a biomarker analysis of prospectively collected samples at 2 academic institutions from 2011 to 2022. Plasma specimens were collected from patients with suspected placenta accreta spectrum, placenta previa, or repeat cesarean deliveries. Exosomes were quantified and characterized by nanoparticle tracking analysis and western blotting. MicroRNA were assessed by polymerase chain reaction array and targeted single quantification. MicroRNA pathway analysis was performed using the Ingenuity Pathway Analyses software. Placental biopsies were taken from all groups and analyzed by polymerase chain reaction and whole cell enzyme-linked immunosorbent assay. Receiver operating characteristic curve univariate analysis was performed for the use of microRNA in the prediction of placenta accreta spectrum. Clinically relevant outcomes were collected from abstracted medical records.

RESULTS

Plasma specimens were analyzed from a total of 120 subjects (60 placenta accreta spectrum, 30 placenta previa, and 30 control). Isolated plasma exosomes had a mean size of 71.5 nm and were 10 times greater in placenta accreta spectrum specimens (20 vs 2 particles/frame). Protein expression of exosomes was positive for intracellular adhesion molecule 1, flotilin, annexin, and CD9. MicroRNA analysis showed increased detection of 3 microRNAs (mir-92, -103, and -192) in patients with placenta accreta spectrum. Pathway interaction assessment revealed differential regulation of p53 signaling in placenta accreta spectrum and of erythroblastic oncogene B2 or human epidermal growth factor 2 in control specimens. These findings were subsequently confirmed in placental protein analysis. Placental microRNA paralleled plasma exosomal microRNA expression. Biomarker assessment of placenta accreta spectrum signature microRNA had an area under the receiver operating characteristic curve of 0.81 (P<.001; 95% confidence interval, 0.73–0.89) with a sensitivity and specificity of 89.2% and 80%, respectively.

CONCLUSION

In this large cohort, plasma exosomal microRNA assessment revealed differentially expressed pathways in placenta accreta spectrum, and these microRNAs are potential biomarkers for the detection of placenta accreta spectrum.

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来源期刊
AJOG global reports
AJOG global reports Endocrinology, Diabetes and Metabolism, Obstetrics, Gynecology and Women's Health, Perinatology, Pediatrics and Child Health, Urology
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