Maternal Acylcarnitine Disruption as a Potential Predictor of Preterm Birth in Primigravida: A Preliminary Investigation.

Preterm birth, defined as any birth before 37 weeks of completed gestation, poses adverse health risks to both mothers and infants. Despite preterm birth being associated with several risk factors, its relationship to maternal metabolism remains unclear, especially in first-time mothers. Aims of the present study were to identify maternal metabolic disruptions associated with preterm birth and to evaluate their predictive potentials. Blood was collected, and the serum harvested from the mothers of 24 preterm and 42 term births at 28-32 weeks gestation (onset of the 3rd trimester). Serum samples were assayed by untargeted metabolomic analyses via liquid chromatography/mass spectrometry (QTOF-LC/MS). Metabolites were annotated by inputting the observed mass-to-charge ratio into the Human Metabolome Database (HMDB). Analysis of 181 identified metabolites by PLS-DA modeling using SIMCA (v17) showed reasonable separation between the two groups (CV-ANOVA, p = 0.02). Further statistical analysis revealed lower serum levels of various acyl carnitines and amino acid metabolites in preterm mothers. Butenylcarnitine (C4:1), a short-chain acylcarnitine, was found to be the most predictive of preterm birth (AUROC = 0.73, [CI] 0.60-0.86). These observations, in conjuncture with past literature, reveal disruptions in fatty acid oxidation and energy metabolism in preterm primigravida. While these findings require validation, they reflect altered metabolic pathways that may be predictive of preterm delivery in primigravida.

Potential molecular and cellular mechanisms for adverse placental outcomes in pregnancies complicated by SARS-CoV-2 infection-A scoping review.

BACKGROUND: Emerging evidence suggests that SARS-CoV-2 infection during pregnancy can result in placental damage and poor placental outcomes. However, the mechanisms by which SARS-CoV-2 infection leads to placental damage are not well understood. With a rapid expansion of literature on this topic, it is critical to assess the quality and synthesize the current state of literature. The objective of this scoping review is to highlight underlying mechanisms of SARS-CoV-2 mediated placental pathology in pregnant individuals and identify literature gaps regarding molecular and cellular mechanisms of poor placental outcomes. METHODS: The review was conducted and reported following the recommendations of the PRISMA extension for Scoping Reviews. The study protocol was registered with Open Science Framework (https://osf.io/p563s/). Five databases (MEDLINE, EMBASE, Scopus, CINAHL, PubMed) were searched for studies published between September 2019 until April 2022. Studies assessing placental outcomes with respect to SARS-CoV-2 infection in pregnancy were eligible for inclusion. Outcomes of interest included histopathology, and molecular or cellular analysis. All records were uploaded into Covidence and extracted using the Joanna Briggs Institute method. Studies were assessed for risk of bias using the Newcastle Ottawa scale and a narrative synthesis of results was generated. RESULTS: Twenty-seven studies reporting on molecular and/or cellular mechanisms of SARS-CoV-2 mediated placental outcomes were included in this review. SARS-CoV-2 infection was associated with perturbations in the ACE2 pathway, inflammatory mediators and immune cell populations and mitochondrial function in placentas. CONCLUSIONS: Our findings suggest that changes in the ACE2 pathway, mitochondrial dysfunction, and/or inflammatory processes may lead to placental damage observed in SARS-CoV-2 infection during pregnancy. More research is needed to understand the role of these pathways further, in addition to data collection related to trimester, severity, and strain.

Is there a maternal blood biomarker that can predict spontaneous preterm birth prior to labour onset? A systematic review.

INTRODUCTION: The ability to predict spontaneous preterm birth (sPTB) prior to labour onset is a challenge, and it is currently unclear which biomarker(s), may be potentially predictive of sPTB, and whether their predictive power has any utility. A systematic review was conducted to identify maternal blood biomarkers of sPTB. METHODS: This study was conducted according to PRISMA protocol for systematic reviews. Four databases (MEDLINE, EMBASE, CINAHL, Scopus) were searched up to September 2021 using search terms: "preterm labor", "biomarker" and "blood OR serum OR plasma". Studies assessing blood biomarkers prior to labour onset against the outcome sPTB were eligible for inclusion. Risk of bias was assessed based on the Newcastle Ottawa scale. Increased odds of sPTB associated with maternal blood biomarkers, as reported by odds ratios (OR), or predictive scores were synthesized. This review was not prospectively registered. RESULTS: Seventy-seven primary research articles met the inclusion criteria, reporting 278 unique markers significantly associated with and/or predictive of sPTB in at least one study. The most frequently investigated biomarkers were those measured during maternal serum screen tests for aneuploidy, or inflammatory cytokines, though no single biomarker was clearly predictive of sPTB based on the synthesized evidence. Immune and signaling pathways were enriched within the set of biomarkers and both at the level of protein and gene expression. CONCLUSION: There is currently no known predictive biomarker for sPTB. Inflammatory and immune biomarkers show promise, but positive reporting bias limits the utility of results. The biomarkers identified may be more predictive in multi-marker models instead of as single predictors. Omics-style studies provide promising avenues for the identification of novel (and multiple) biomarkers. This will require larger studies with adequate power, with consideration of gestational age and the heterogeneity of sPTB to identify a set of biomarkers predictive of sPTB.

Prostaglandins in biofluids in pregnancy and labour: A systematic review.

Prostaglandins are thought to be important mediators in the initiation of human labour, however the evidence supporting this is not entirely clear. Determining how, and which, prostaglandins change during pregnancy and labour may provide insight into mechanisms governing labour initiation and the potential to predict timing of labour onset. The current study systematically searched the existing scientific literature to determine how biofluid levels of prostaglandins change throughout pregnancy before and during labour, and whether prostaglandins and/or their metabolites may be useful for prediction of labour. The databases EMBASE and MEDLINE were searched for English-language articles on prostaglandins measured in plasma, serum, amniotic fluid, or urine during pregnancy and/or spontaneous labour. Studies were assessed for quality and risk of bias and a qualitative summary of included studies was generated. Our review identified 83 studies published between 1968-2021 that met the inclusion criteria. As measured in amniotic fluid, levels of PGE2, along with PGF2α and its metabolite 13,14-dihydro-15-keto-PGF2α were reported higher in labour compared to non-labour. In blood, only 13,14-dihydro-15-keto-PGF2α was reported higher in labour. Additionally, PGF2α, PGF1α, and PGE2 were reported to increase in amniotic fluid as pregnancy progressed, though this pattern was not consistent in plasma. Overall, the evidence supporting changes in prostaglandin levels in these biofluids remains unclear. An important limitation is the lack of data on the complexity of the prostaglandin pathway outside of the PGE and PGF families. Future studies using new methodologies capable of co-assessing multiple prostaglandins and metabolites, in large, well-defined populations, will help provide more insight as to the identification of exactly which prostaglandins and/or metabolites consistently change with labour. Revisiting and revising our understanding of the prostaglandins may provide better targets for clinical monitoring of pregnancies. This study was supported by the Canadian Institutes of Health Research.

Quality assessment of RNA in long-term storage: The All Our Families biorepository.

BACKGROUND: The All Our Families (AOF) cohort study is a longitudinal population-based study which collected biological samples from 1948 pregnant women between May 2008 and December 2010. As the quality of samples can decline over time, the objective of the current study was to assess the association between storage time and RNA (ribonucleic acid) yield and purity, and confirm the quality of these samples after 7-10 years in long-term storage. METHODS: Maternal whole blood samples were previously collected by trained phlebotomists and stored in four separate PAXgene Blood RNA Tubes (PreAnalytiX) between 2008 and 2011. RNA was isolated in 2011 and 2018 using PAXgene Blood RNA Kits (PreAnalytiX) as per the manufacturer's instruction. RNA purity (260/280), as well as RNA yield, were measured using a Nanodrop. The RNA integrity number (RIN) was also assessed from 5-25 and 111-130 months of storage using RNA 6000 Nano Kit and Agilent 2100 BioAnalyzer. Descriptive statistics, paired t-test, and response feature analysis using linear regression were used to assess the association between various predictor variables and quality of the RNA isolated. RESULTS: Overall, RNA purity and yield of the samples did not decline over time. RNA purity of samples isolated in 2011 (2.08, 95% CI: 2.08-2.09) were statistically lower (p<0.000) than samples isolated in 2018 (2.101, 95% CI: 2.097, 2.104), and there was no statistical difference between the 2011 (13.08 µg /tube, 95% CI: 12.27-13.89) and 2018 (12.64 µg /tube, 95% CI: 11.83-13.46) RNA yield (p = 0.2964). For every month of storage, the change in RNA purity is -0.01(260/280), and the change in RNA yield between 2011 and 2018 is -0.90 µ g / tube. The mean RIN was 8.49 (95% CI:8.44-8.54), and it ranged from 7.2 to 9.5. The rate of change in expected RIN per month of storage is 0.003 (95% CI 0.002-0.004), so while statistically significant, these results are not relevant. CONCLUSIONS: RNA quality does not decrease over time, and the methods used to collect and store samples, within a population-based study are robust to inherent operational factors which may degrade sample quality over time.