Most cited article - PubMed ID 36982251
First-Trimester Screening for HELLP Syndrome-Prediction Model Based on MicroRNA Biomarkers and Maternal Clinical Characteristics
BACKGROUND: Placenta previa is the abnormal implantation of the placenta into the lower segment of the uterus, is associated with adverse maternal and fetal outcomes such as placenta accreta spectrum disorders, antepartum and postpartum hemorrhage, fetal growth restriction, prematurity, stillbirth and neonatal death, thrombophlebitis, and septicemia. The aim of the study was to assess retrospectively how the later onset of placenta previa affects the microRNA expression profile in the whole peripheral blood during the first trimester of gestation. METHODS: Regarding the occurrence of the association between aberrant microRNA expression profiles at early stages of gestation and later onset of various pregnancy-related complications, we selected for the study pregnancies developing placenta previa as the only pregnancy-related disorder. In total, 24 singleton pregnancies diagnosed with placenta previa that underwent first-trimester prenatal screening and delivered on-site within the period November 2012-May 2018 were included in the study. Overall, 80 normal pregnancies that delivered appropriate-for-gestational age newborns after completing 37 weeks of gestation were selected as the control group based on the equality of the length of biological sample storage. RESULTS: Downregulation of multiple microRNAs (miR-20b-5p, miR-24-3p, miR-26a-5p, miR-92a-3p, miR-103a-3p, miR-130b-3p, miR-133a-3p, miR-145-5p, miR-146a-5p, miR-155-5p, miR-181a-5p, miR-195-5p, miR-210-3p, miR-342-3p, and miR-574-3p) was observed in pregnancies destined to develop placenta previa. The combination of seven microRNAs (miR-130b-3p, miR-145-5p, miR-155-5p, miR-181a-5p, miR-210-3p, miR-342-3p, and miR-574-3p) showed the highest accuracy (AUC 0.937, p < 0.001, 100.0% sensitivity, 83.75% specificity) to differentiate, at early stages of gestation, between pregnancies with a normal course of gestation and those with placenta previa diagnosed in the second half of pregnancy. Overall, 75% of pregnancies destined to develop placenta previa were correctly identified at 10.0% FPR. CONCLUSION: Consecutive large-scale analyses must be performed to verify the reliability of the proposed novel early predictive model for placenta previa occurring as the only pregnancy-related disorder.
- Keywords
- first trimester screening, gene expression, microRNAs, placenta previa, prediction, whole peripheral venous blood,
- Publication type
- Journal Article MeSH
INTRODUCTION: 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. METHODS: 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). RESULTS: 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)]. CONCLUSION: 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.
- Keywords
- cardiovascular risk, first-trimester screening, miRNA, predictive models, preventive program, risk factors,
- Publication type
- Journal Article MeSH
This Special Issue mainly focuses on preeclampsia (PE), haemolysis, elevated liver enzymes, and low platelet count (HELLP) syndrome, gestational diabetes mellitus (GDM), foetal growth restriction (FGR), small-for-gestational-age foetuses (SGA), miscarriage, stillbirth, first-episode psychosis (FEP) during pregnancy, and pregnancy-related acute kidney injury (PR-AKI) [...].
- MeSH
- Diabetes, Gestational * MeSH
- Pregnancy Complications * MeSH
- Humans MeSH
- Stillbirth MeSH
- Pre-Eclampsia * MeSH
- Fetal Growth Retardation MeSH
- Pregnancy MeSH
- Check Tag
- Humans MeSH
- Pregnancy MeSH
- Female MeSH
- Publication type
- Editorial MeSH
We evaluated the potential of cardiovascular-disease-associated microRNAs to predict in the early stages of gestation (from 10 to 13 gestational weeks) the occurrence of a miscarriage or stillbirth. The gene expressions of 29 microRNAs were studied retrospectively in peripheral venous blood samples derived from singleton Caucasian pregnancies diagnosed with miscarriage (n = 77 cases; early onset, n = 43 cases; late onset, n = 34 cases) or stillbirth (n = 24 cases; early onset, n = 13 cases; late onset, n = 8 cases; term onset, n = 3 cases) and 80 selected gestational-age-matched controls (normal term pregnancies) using real-time RT-PCR. Altered expressions of nine microRNAs (upregulation of miR-1-3p, miR-16-5p, miR-17-5p, miR-26a-5p, miR-146a-5p, and miR-181a-5p and downregulation of miR-130b-3p, miR-342-3p, and miR-574-3p) were observed in pregnancies with the occurrence of a miscarriage or stillbirth. The screening based on the combination of these nine microRNA biomarkers revealed 99.01% cases at a 10.0% false positive rate (FPR). The predictive model for miscarriage only was based on the altered gene expressions of eight microRNA biomarkers (upregulation of miR-1-3p, miR-16-5p, miR-17-5p, miR-26a-5p, miR-146a-5p, and miR-181a-5p and downregulation of miR-130b-3p and miR-195-5p). It was able to identify 80.52% cases at a 10.0% FPR. Highly efficient early identification of later occurrences of stillbirth was achieved via the combination of eleven microRNA biomarkers (upregulation of miR-1-3p, miR-16-5p, miR-17-5p, miR-20a-5p, miR-146a-5p, and miR-181a-5p and downregulation of miR-130b-3p, miR-145-5p, miR-210-3p, miR-342-3p, and miR-574-3p) or, alternatively, by the combination of just two upregulated microRNA biomarkers (miR-1-3p and miR-181a-5p). The predictive power achieved 95.83% cases at a 10.0% FPR and, alternatively, 91.67% cases at a 10.0% FPR. The models based on the combination of selected cardiovascular-disease-associated microRNAs had very high predictive potential for miscarriages or stillbirths and may be implemented in routine first-trimester screening programs.
- Keywords
- cardiovascular diseases, first-trimester screening, gene expression, microRNA, miscarriage, prediction, stillbirth, whole peripheral venous blood,
- MeSH
- Biomarkers MeSH
- Cardiovascular Diseases * genetics MeSH
- Humans MeSH
- MicroRNAs * metabolism MeSH
- Stillbirth MeSH
- Pregnancy Trimester, First MeSH
- Retrospective Studies MeSH
- Abortion, Spontaneous * genetics MeSH
- Pregnancy MeSH
- Check Tag
- Humans MeSH
- Pregnancy MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Biomarkers MeSH
- MicroRNAs * MeSH
- MIRN145 microRNA, human MeSH Browser