Fetal growth restriction and stillbirth: Biomarkers for identifying at risk fetuses

Assessment of fetal growth trajectory identifies infants at high risk of perinatal mortality

OBJECTIVE

To analyze perinatal risks associated with three distinct scenarios of fetal growth trajectory in the latter half of pregnancy compared with a reference group.

METHODS

This cohort study included women with a singleton pregnancy that delivered between 32 + 0 and 41 + 6 weeks' gestation and had two or more ultrasound scans, at least 4 weeks apart, from 18 + 0 weeks. We evaluated three different scenarios of fetal growth against a reference group, which comprised appropriate-for-gestational-age fetuses with appropriate forward-growth trajectory. The comparator growth trajectories were categorized as: Group 1, small-for-gestational-age (SGA) fetuses (estimated fetal weight (EFW) or abdominal circumference (AC) persistently < 10th centile) with appropriate forward growth; Group 2, fetuses with decreased growth trajectory (decrease of ≥ 50 centiles) and EFW or AC ≥ 10th centile (i.e. non-SGA) at their final ultrasound scan; and Group 3, fetuses with decreased growth trajectory and EFW or AC < 10th centile (i.e. SGA) at their final scan. The primary outcome was overall perinatal mortality (stillbirth or neonatal death). Secondary outcomes included stillbirth, delivery of a SGA infant, preterm birth, emergency Cesarean section for non-reassuring fetal status and composite severe neonatal morbidity. Associations were analyzed using logistic regression.

RESULTS

The final study cohort comprised 5319 pregnancies. Compared to the reference group, the adjusted odds of perinatal mortality were increased significantly in Group 2 (adjusted odds ratio (aOR), 4.00 (95% CI, 1.36-11.22)) and Group 3 (aOR, 7.71 (95% CI, 2.39-24.91)). Only Group 3 had increased odds of stillbirth (aOR, 5.69 (95% CI, 1.55-20.93)). In contrast, infants in Group 1 did not have significantly increased odds of demise. The odds of a SGA infant at birth were increased in all three groups compared with the reference group, but was highest in Group 1 (aOR, 111.86 (95% CI, 62.58-199.95)) and Group 3 (aOR, 40.63 (95% CI, 29.01-56.92)). In both groups, more than 80% of infants were born SGA and nearly half had a birth weight < 3rd centile. Likewise, the odds of preterm birth were increased in all three groups compared with the reference group, being highest in Group 3, with an aOR of 4.27 (95% CI, 3.23-5.64). Lastly, the odds of composite severe neonatal morbidity were increased in Groups 1 and 3, whereas the odds of emergency Cesarean section for non-reassuring fetal status were increased only in Group 3.

CONCLUSION

Assessing the fetal growth trajectory in the latter half of pregnancy can help identify infants at increased risk of perinatal mortality and birth weight < 3rd centile for gestation. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.

Fetal heart rate spectral analysis in raw signals and PRSA-derived curve: normal and pathological fetuses discrimination

Cardiotocography (CTG) is the most common technique for electronic fetal monitoring and consists of the simultaneous recording of fetal heart rate (FHR) and uterine contractions. In analogy with the adult case, spectral analysis of the FHR signal can be used to assess the functionality of the autonomic nervous system. To do so, several methods can be employed, each of which has its strengths and limitations. This paper aims at performing a methodological investigation on FHR spectral analysis adopting 4 different spectrum estimators and a novel PRSA-based spectral method. The performances have been evaluated in terms of the ability of the various methods to detect changes in the FHR in two common pregnancy complications: intrauterine growth restriction (IUGR) and gestational diabetes. A balanced dataset containing 2178 recordings distributed between the 32nd and 38th week of gestation was used. The results show that the spectral method derived from the PRSA better differentiates high-risk pregnancies vs. controls compared to the others. Specifically, it more robustly detects an increase in power percentage within the movement frequency band and a decrease in high frequency between pregnancies at high risk in comparison to those at low risk.

Biomarker screening in fetal growth restriction based on multiple RNA-seq studies

Objective

Fetal growth restriction (FGR) is a severe pathological complication associated with compromised fetal development. The early diagnosis and prediction for FGR are still unclear. Sequencing technologies present a huge opportunity to identify novel biomarkers. However, limitation of individual studies (e.g., long lists of dysregulated genes, small sample size and conflicting results) hinders the selection of the best-matched ones.

Study design

A multi-step bioinformatics analysis was performed. We separately reanalyzed data from four public RNA-seq studies, followed by a combined analysis of individual results. The differentially expressed genes (DEGs) were identified based on DESeq2. Then, function enrichment analyses and protein-protein interaction network (PPI) were conducted to screen for hub genes. The results were further verified by using external microarray data.

Results

A total of 65 dysregulated genes (50 down and 15 upregulated) were identified in FGR compared to controls. Function enrichment and PPI analysis revealed ten hub genes closely related to FGR. Validation analysis found four downregulated candidate biomarkers (CEACAM6, SCUBE2, DEFA4, and MPO) for FGR.

Conclusions

The use of omics tools to explore mechanism of pregnancies disorders contributes to improvements in obstetric clinical practice.

Quantitative Proteomics of Maternal Blood Plasma in Isolated Intrauterine Growth Restriction

Intrauterine growth restriction (IUGR) remains a significant concern in modern obstetrics, linked to high neonatal health problems and even death, as well as childhood disability, affecting adult quality of life. The role of maternal and fetus adaptation during adverse pregnancy is still not completely understood. This study aimed to investigate the disturbance in biological processes associated with isolated IUGR via blood plasma proteomics. The levels of 125 maternal plasma proteins were quantified by liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM MS) with corresponding stable isotope-labeled peptide standards (SIS). Thirteen potential markers of IUGR (Gelsolin, Alpha-2-macroglobulin, Apolipoprotein A-IV, Apolipoprotein B-100, Apolipoprotein(a), Adiponectin, Complement C5, Apolipoprotein D, Alpha-1B-glycoprotein, Serum albumin, Fibronectin, Glutathione peroxidase 3, Lipopolysaccharide-binding protein) were found to be inter-connected in a protein-protein network. These proteins are involved in plasma lipoprotein assembly, remodeling, and clearance; lipid metabolism, especially cholesterol and phospholipids; hemostasis, including platelet degranulation; and immune system regulation. Additionally, 18 proteins were specific to a particular type of IUGR (early or late). Distinct patterns in the coagulation and fibrinolysis systems were observed between isolated early- and late-onset IUGR. Our findings highlight the complex interplay of immune and coagulation factors in IUGR and the differences between early- and late-onset IUGR and other placenta-related conditions like PE. Understanding these mechanisms is crucial for developing targeted interventions and improving outcomes for pregnancies affected by IUGR.

Maternal Cardiovascular Responses to Position Change in Pregnancy

The maternal cardiovascular-circulatory system undergoes profound changes almost from the conception of a pregnancy until the postpartum period to support the maternal adaptions required for pregnancy and lactation. Maintenance of cardiovascular homeostasis requires changes in the cardiovascular autonomic responses. Here, we present a longitudinal study of the maternal cardiovascular autonomic responses to pregnancy and maternal position. Over a normal gestation, in the left lateral position there are significant changes in both time and frequency domain parameters reflecting heart rate variability. We show that cardiovascular autonomic responses to physiological stressors (standing and supine positions in late pregnancy) became significantly different with advancing gestation. In the third trimester, 60% of the subjects had an unstable heart rate response on standing, and these subjects had a significantly reduced sample entropy evident in their heart rate variability data. By 6 weeks, postpartum function returned to near the non-pregnant state, but there were consistent differences in high-frequency power when compared to nulligravid cases. Finally, we review complementary evidence, in particular from magnetic resonance imaging, that provides insights into the maternal and fetal impacts of positioning in pregnancy. This demonstrates a clear relationship between supine position and maternal hemodynamic parameters, which relates to compression of the inferior vena cava (p = 0.05). Together, these studies demonstrate new understanding of the physiology of physiological stressors related to position.

From Molecules to Imaging: Assessment of Placental Hypoxia Biomarkers in Placental Insufficiency Syndromes

Placental hypoxia poses significant risks to both the developing fetus and the mother during pregnancy, underscoring the importance of early detection and monitoring. Effectively identifying placental hypoxia and evaluating the deterioration in placental function requires reliable biomarkers. Molecular biomarkers in placental tissue can only be determined post-delivery and while maternal blood biomarkers can be measured over time, they can merely serve as proxies for placental function. Therefore, there is an increasing demand for non-invasive imaging techniques capable of directly assessing the placental condition over time. Recent advancements in imaging technologies, including photoacoustic and magnetic resonance imaging, offer promising tools for detecting and monitoring placental hypoxia. Integrating molecular and imaging biomarkers may revolutionize the detection and monitoring of placental hypoxia, improving pregnancy outcomes and reducing long-term health complications. This review describes current research on molecular and imaging biomarkers of placental hypoxia both in human and animal studies and aims to explore the benefits of an integrated approach throughout gestation.

Hyperglycosylated-hCG: Its Role in Trophoblast Invasion and Intrauterine Growth Restriction

Human chorionic gonadotropin (hCG) is produced by the placenta and its roles have been studied for over a century, being the first known pregnancy-related protein. Although its main role is to stimulate the production of progesterone by corpus luteal cells, hCG does not represent just one biologically active molecule, but a group of at least five variants, produced by different cells and each with different functions. The hyperglycosylated variant of hCG (H-hCG) plays a key role in trophoblast invasion, placental development and fetal growth. During trophoblast invasion, H-hCG promotes extravillous cytotrophoblast cells to infiltrate the decidua, and also to colonize and remodel the spiral arteries in to low resistance, larger-diameter vessels. As fetal growth is heavily reliant on nutrient availability, impaired trophoblast invasion and remodeling of the uterine arteries, leads to a defective perfusion of the placenta and fetal growth restriction. Understanding the function of H-hCG in the evolution of the placenta might unveil new ways to manage and treat fetal growth restriction.

Fetal Growth Restriction Is Associated with Pregnancy Associated Plasma Protein A and Uterine Artery Doppler in First Trimester

Fetal growth restriction (FGR) is a major cause of stillbirth and poor neurodevelopmental outcomes. The early prediction may be important to establish treatment options and improve neonatal outcomes. The aim of this study was to assess the association of parameters used in first-trimester screening, uterine artery Doppler pulsatility index and the development of FGR. In this retrospective cohort study, 1930 singleton pregnancies prenatally diagnosed with an estimated fetal weight under the third percentile were included. All women underwent first-trimester screening assessing maternal serum pregnancy-associated plasma protein A (PAPP-A), free beta-human chorionic gonadotrophin levels, fetal nuchal translucency and uterine artery Doppler pulsatility index (PI). We constructed a Receiver Operating Characteristics curve to calculate the sensitivity and specificity of early diagnosis of FGR. In pregnancies with FGR, PAPP-A was significantly lower, and uterine artery Doppler pulsatility index was significantly higher compared with the normal birth weight group (0.79 ± 0.38 vs. 1.15 ± 0.59, p < 0.001 and 1.82 ± 0.7 vs. 1.55 ± 0.47, p = 0.01). Multivariate logistic regression analyses demonstrated that PAPP-A levels and uterine artery Doppler pulsatility index were significantly associated with FGR (p = 0.009 and p = 0.01, respectively). To conclude, these two parameters can predict FGR < 3rd percentile.

Multi-centre deep learning for placenta segmentation in obstetric ultrasound with multi-observer and cross-country generalization

The placenta is crucial to fetal well-being and it plays a significant role in the pathogenesis of hypertensive pregnancy disorders. Moreover, a timely diagnosis of placenta previa may save lives. Ultrasound is the primary imaging modality in pregnancy, but high-quality imaging depends on the access to equipment and staff, which is not possible in all settings. Convolutional neural networks may help standardize the acquisition of images for fetal diagnostics. Our aim was to develop a deep learning based model for classification and segmentation of the placenta in ultrasound images. We trained a model based on manual annotations of 7,500 ultrasound images to identify and segment the placenta. The model's performance was compared to annotations made by 25 clinicians (experts, trainees, midwives). The overall image classification accuracy was 81%. The average intersection over union score (IoU) reached 0.78. The model's accuracy was lower than experts' and trainees', but it outperformed all clinicians at delineating the placenta, IoU = 0.75 vs 0.69, 0.66, 0.59. The model was cross validated on 100 2nd trimester images from Barcelona, yielding an accuracy of 76%, IoU 0.68. In conclusion, we developed a model for automatic classification and segmentation of the placenta with consistent performance across different patient populations. It may be used for automated detection of placenta previa and enable future deep learning research in placental dysfunction.