First trimester prediction models for small-for- gestational age and fetal growth restricted fetuses without the presence of preeclampsia

Abstract

We established efficient first trimester prediction models for small-for-gestational age (SGA) and fetal growth restriction (FGR) without the presence of preeclampsia (PE) regardless of the gestational age of the onset of the disease [early FGR occurring before 32 gestational week or late FGR occurring after 32 gestational week]. The retrospective study was performed on singleton Caucasian pregnancies (n = 6440) during the period 11/2012–3/2020. Finally, 4469 out of 6440 pregnancies had complete medical records since they delivered in the Institute for the Care of Mother and Child, Prague, Czech Republic. The study included all cases diagnosed with SGA (n = 37) or FGR (n = 82) without PE, and 80 selected normal pregnancies. Four microRNAs (miR-1-3p, miR-20a-5p, miR-146a-5p, and miR-181a-5p) identified 75.68 % SGA cases at 10.0 % false positive rate (FPR). Eight microRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-126-3p, miR-130b-3p, miR-146a-5p, miR-181a-5p, and miR-499a-5p) identified 83.80 % SGA cases at 10.0 % FPR. The prediction model for SGA based on microRNAs was further improved via implementation of maternal clinical characteristics [maternal age and BMI, an infertility treatment by assisted reproductive technology (ART), first trimester screening for PE and/or FGR and for spontaneous preterm, both by FMF algorithm]. Then 81.08 % and 89.19 % pregnancies developing SGA were identified at 10.0 % FPR in case of utilization of 4 microRNA and 8 microRNA biomarkers. Simplified prediction model for SGA based on limited number of maternal clinical characteristics (maternal age and BMI, an infertility treatment by ART, and 4 microRNAs) does not improve the detection rate of SGA (70.27 % SGA cases at 10.0 % FPR) when compared with prediction model for SGA based just on the expression profile of 4 or 8 microRNAs biomarkers. Seven microRNAs only (miR-16-5p, miR-20a-5p, miR-145-5p, miR-146a-5p, miR-181a-5p, miR-342-3p, and miR-574-3p) identified 42.68 % FGR cases at 10.0 % FPR (AUC 0.725). However, the combination of 10 microRNAs only (miR-16-5p, miR-20a-5p, miR-100-5p, miR-143-3p, miR-145-5p, miR-146a-5p, miR-181a-5p, miR-195-5p, miR-342-3p, and miR-574-3p) reached a higher discrimination power (AUC 0.774). It identified 40.24 % FGR cases at 10.0 % FPR. The prediction model for any subtype of FGR based on microRNAs was further improved via implementation of maternal clinical characteristics [maternal age and BMI, an infertility treatment by ART, the parity (nulliparity), the occurrence of SGA or FGR in previous gestation, and the occurrence of any autoimmune disorder, and the presence of chronic hypertension]. Then 64.63 % and 65.85 % pregnancies destinated to develop FGR were identified at 10.0 % FPR in case of utilization of 7 microRNA biomarkers or 10 microRNA biomarkers. When other clinical variables next to those ones mentioned above such as first trimester screening for PE and/or FGR and for spontaneous preterm, both by FMF algorithm, were added to the prediction model for FGR, the detection power was even increased to 74.39 % cases and 78.05 % cases at 10.0 % FPR.