Hromadnikova Ilona, Kotlabova Katerina, Krofta Ladislav
Department of Molecular Biology and Cell Pathology, Third Faculty of Medicine, Charles University, 10000 Prague, Czech Republic.
Institute for the Care of the Mother and Child, Third Faculty of Medicine, Charles University, 14700 Prague, Czech Republic.
Biomedicines. 2022 Oct 15;10(10):2591. doi: 10.3390/biomedicines10102591.
The goal of the study was to establish an efficient first-trimester predictive model for any type of preterm birth before 37 gestational weeks (spontaneous preterm birth (PTB) or preterm prelabor rupture of membranes (PPROM)) in the absence of other pregnancy-related complications, such as gestational hypertension, preeclampsia, fetal growth restriction, or small for gestational age. The retrospective study was performed in the period from 11/2012 to 3/2020. Peripheral blood samples were collected from 6440 Caucasian individuals involving 41 PTB and 65 PPROM singleton pregnancies. A control group with 80 singleton term pregnancies was selected on the basis of equal sample-storage time. A combination of only six microRNAs (miR-16-5p, miR-21-5p, miR-24-3p, miR-133a-3p, miR-155-5p, and miR-210-3p; AUC 0.812, p < 0.001, 70.75% sensitivity, 78.75% specificity, cut-off > 0.652) could predict preterm delivery before 37 gestational weeks in early stages of gestation in 52.83% of pregnancies with a 10.0% FPR. This predictive model for preterm birth based on aberrant microRNA expression profile was further improved via implementation of maternal clinical characteristics (maternal age and BMI at early stages of gestation, infertility treatment with assisted reproductive technology, occurrence of preterm delivery before 37 gestational weeks in previous pregnancy(ies), and presence of any kind of autoimmune disease (rheumatoid arthritis, systemic lupus erythematosus, antiphospholipid syndrome, type 1 diabetes mellitus, or other autoimmune disease)). With this model, 69.81% of pregnancies destined to deliver before 37 gestational weeks were identified with a 10.0% FPR at early stages of gestation. When other clinical variables as well as those mentioned above—such as positive first-trimester screening for early preeclampsia with onset before 34 gestational weeks and/or fetal growth restriction with onset before 37 gestational weeks using the Fetal Medicine Foundation algorithm, as well as positive first-trimester screening for spontaneous preterm birth with onset before 34 gestational weeks using the Fetal Medicine Foundation algorithm—were added to the predictive model for preterm birth, the predictive power was even slightly increased to 71.70% with a 10.0% FPR. Nevertheless, we prefer to keep the first-trimester screening for any type of preterm birth occurring before 37 gestational weeks in the absence of other pregnancy-related complications as simple as possible.
本研究的目的是建立一种有效的孕早期预测模型，用于预测在无其他妊娠相关并发症（如妊娠高血压、子痫前期、胎儿生长受限或小于胎龄儿）的情况下，任何类型的孕37周前早产（自发性早产（PTB）或胎膜早破（PPROM））。这项回顾性研究于2012年11月至2020年3月期间进行。收集了6440名白种人的外周血样本，其中包括41例PTB单胎妊娠和65例PPROM单胎妊娠。根据样本储存时间相同的原则，选择了80例单胎足月妊娠作为对照组。仅六种微小RNA（miR-16-5p、miR-21-5p、miR-24-3p、miR-133a-3p、miR-155-5p和miR-210-3p；AUC 0.812，p<0.001，敏感性70.75%，特异性78.75%，临界值>0.652）的组合能够在孕早期预测52.83%的妊娠在孕37周前早产，假阳性率为10.0%。基于异常微小RNA表达谱的早产预测模型通过纳入孕妇临床特征（孕早期的孕妇年龄和BMI、辅助生殖技术的不孕治疗、既往妊娠中孕37周前早产的发生情况以及任何自身免疫性疾病（类风湿关节炎、系统性红斑狼疮、抗磷脂综合征、1型糖尿病或其他自身免疫性疾病））得到了进一步改善。使用该模型，在孕早期能够识别出注定在孕37周前分娩的69.81%的妊娠，假阳性率为10.0%。当将其他临床变量以及上述变量（如使用胎儿医学基金会算法在孕34周前发病的早发型子痫前期和/或在孕37周前发病的胎儿生长受限的孕早期筛查阳性，以及使用胎儿医学基金会算法在孕34周前发病的自发性早产的孕早期筛查阳性）添加到早产预测模型中时，预测能力甚至略有提高，假阳性率为10.0%时预测能力达到71.70%。然而，我们更倾向于在无其他妊娠相关并发症的情况下，尽可能简化对孕37周前任何类型早产的孕早期筛查。
