Hromadnikova Ilona, Kotlabova Katerina, Krofta Ladislav
Department of Molecular Biology and Cell Pathology, Third Faculty of Medicine, Charles University, Prague, Czechia.
Institute for the Care of the Mother and Child, Third Faculty of Medicine, Charles University, Prague, Czechia.
Front Cell Dev Biol. 2024 Sep 4;12:1461547. doi: 10.3389/fcell.2024.1461547. eCollection 2024.
This study aimed to establish efficient, cost-effective, and early predictive models for adverse pregnancy outcomes based on the combinations of a minimum number of miRNA biomarkers, whose altered expression was observed in specific pregnancy-related complications and selected maternal clinical characteristics.
This retrospective study included singleton pregnancies with gestational hypertension (GH, n = 83), preeclampsia (PE, n = 66), HELLP syndrome (n = 14), fetal growth restriction (FGR, n = 82), small for gestational age (SGA, n = 37), gestational diabetes mellitus (GDM, n = 121), preterm birth in the absence of other complications (n = 106), late miscarriage (n = 34), stillbirth (n = 24), and 80 normal term pregnancies. MiRNA gene expression profiling was performed on the whole peripheral venous blood samples collected between 10 and 13 weeks of gestation using real-time reverse transcription polymerase chain reaction RT-PCR).
Most pregnancies with adverse outcomes were identified using the proposed approach (the combinations of selected miRNAs and appropriate maternal clinical characteristics) (GH, 69.88%; PE, 83.33%; HELLP, 92.86%; FGR, 73.17%; SGA, 81.08%; GDM on therapy, 89.47%; and late miscarriage, 84.85%). In the case of stillbirth, no addition of maternal clinical characteristics to the predictive model was necessary because a high detection rate was achieved by a combination of miRNA biomarkers only [91.67% cases at 10.0% false positive rate (FPR)].
The proposed models based on the combinations of selected cardiovascular disease-associated miRNAs and maternal clinical variables have a high predictive potential for identifying women at increased risk of adverse pregnancy outcomes; this can be incorporated into routine first-trimester screening programs. Preventive programs can be initiated based on these models to lower cardiovascular risk and prevent the development of metabolic/cardiovascular/cerebrovascular diseases because timely implementation of beneficial lifestyle strategies may reverse the dysregulation of miRNAs maintaining and controlling the cardiovascular system.
本研究旨在基于最少数量的miRNA生物标志物组合，建立高效、经济且早期的不良妊娠结局预测模型，这些miRNA生物标志物在特定的妊娠相关并发症及选定的孕产妇临床特征中表达发生改变。
这项回顾性研究纳入了单胎妊娠，包括妊娠期高血压（GH，n = 83）、子痫前期（PE，n = 66）、HELLP综合征（n = 14）、胎儿生长受限（FGR，n = 82）、小于胎龄儿（SGA，n = 37）、妊娠期糖尿病（GDM，n = 121）、无其他并发症的早产（n = 106）、晚期流产（n = 34）、死产（n = 24）以及80例正常足月妊娠。在妊娠10至13周期间采集的全外周静脉血样本上，使用实时逆转录聚合酶链反应（RT-PCR）进行miRNA基因表达谱分析。
使用所提出的方法（选定的miRNA与适当的孕产妇临床特征组合）可识别出大多数不良结局妊娠（GH，69.88%；PE，83.33%；HELLP，92.86%；FGR，73.17%；SGA，81.08%；接受治疗的GDM，89.47%；晚期流产，84.85%）。对于死产情况，预测模型无需添加孕产妇临床特征，因为仅通过miRNA生物标志物组合就能实现高检出率[在假阳性率（FPR）为10.0%时，检出率为91.67%]。
所提出的基于选定的心血管疾病相关miRNA与孕产妇临床变量组合的模型，在识别不良妊娠结局风险增加的女性方面具有很高的预测潜力；可将其纳入常规的孕早期筛查项目。基于这些模型可启动预防项目以降低心血管风险并预防代谢/心血管/脑血管疾病的发生，因为及时实施有益的生活方式策略可能会逆转维持和控制心血管系统的miRNA失调。
