Use of metabolomics for predicting spontaneous preterm birth in asymptomatic pregnant women: protocol for a systematic review and meta-analysis

Utilizing Amniotic Fluid Metabolomics to Monitor Fetal Well-Being: A Narrative Review of the Literature

Fetal and perinatal periods are critical phases for long-term development. Early diagnosis of maternal complications is challenging due to the great complexity of these conditions. In recent years, amniotic fluid has risen in a prominent position in the latest efforts to describe and characterize prenatal development. Amniotic fluid may provide real-time information on fetal development and metabolism throughout pregnancy as substances from the placenta, fetal skin, lungs, gastric fluid, and urine are transferred between the mother and the fetus. Applying metabolomics to monitor fetal well-being, in such a context, could help in the understanding, diagnosis, and treatment of these conditions and is a promising area of research. This review shines a spotlight on recent amniotic fluid metabolomics studies and their methods as an interesting tool for the assessment of many conditions and the identification of biomarkers. Platforms in use, such as proton nuclear magnetic resonance (¹H NMR) and ultra-high-performance liquid chromatography (UHPLC), have different merits, and a combinatorial approach could be valuable. Metabolomics may also be used in the quest for habitual diet-induced metabolic signals in amniotic fluid. Finally, analysis of amniotic fluid can provide information on exposure to exogenous substances by detecting the exact levels of metabolites carried to the fetus and associated metabolic effects.

Are newborn outcomes different for term babies who were exposed to antenatal corticosteroids?

BACKGROUND

Antenatal corticosteroids improve newborn outcomes for preterm infants. However, predicting which women presenting for threatened preterm labor will have preterm infants is inaccurate, and many women receive antenatal corticosteroids but then go on to deliver at term.

OBJECTIVE

This study aimed to compare the short-term outcomes of infants born at term to women who received betamethasone for threatened preterm labor with infants who were not exposed to betamethasone in utero.

STUDY DESIGN

We performed a retrospective cohort study of infants born at or after 37 weeks' gestational age to mothers diagnosed as having threatened preterm labor during pregnancy. The primary neonatal outcomes of interest included transient tachypnea of the newborn, neonatal intensive care unit admission, and small for gestational age and were evaluated for their association with betamethasone exposure while adjusting for covariates using multiple logistic regression.

RESULTS

Of 5330 women, 1459 women (27.5%) received betamethasone at a mean gestational age of 32.2±3.3 weeks. The mean age of women was 27±5.9 years and the mean gestational age at delivery was 38.9±1.1 weeks. Women receiving betamethasone had higher rates of maternal comorbidities (P<.001 for diabetes mellitus, asthma, and hypertensive disorder) and were more likely to self-identify as White (P=.022). Betamethasone-exposed neonates had increased rates of transient tachypnea of the newborn, neonatal intensive care unit admission, small for gestational age, hyperbilirubinemia, and hypoglycemia (all, P<.05). Controlling for maternal characteristics and gestational age at delivery, betamethasone exposure was not associated with a diagnosis of transient tachypnea of the newborn (adjusted odds ratio, 1.10; 95% confidence interval, 0.80-1.51), although it was associated with more neonatal intensive care unit admissions (adjusted odds ratio, 1.49; 95% confidence interval, 1.19-1.86) and higher odds of the baby being small for gestational age (adjusted odds ratio, 1.78; 95% confidence interval, 1.48-2.14).

CONCLUSION

Compared with women evaluated for preterm labor who did not receive betamethasone, women receiving betamethasone had infants with higher rates of neonatal intensive care unit admission and small for gestational age. Although the benefits of betamethasone to infants born preterm are clear, there may be negative impacts for infants delivered at term.

Metabolite-Investigator: an integrated user-friendly workflow for metabolomics multi-study analysis

Motivation

Many diseases have a metabolic background, which is increasingly investigated due to improved measurement techniques allowing high-throughput assessment of metabolic features in several body fluids. Integrating data from multiple cohorts is of high importance to obtain robust and reproducible results. However, considerable variability across studies due to differences in sampling, measurement techniques and study populations needs to be accounted for.

Results

We present Metabolite-Investigator, a scalable analysis workflow for quantitative metabolomics data from multiple studies. Our tool supports all aspects of data pre-processing including data integration, cleaning, transformation, batch analysis as well as multiple analysis methods including uni- and multivariable factor-metabolite associations, network analysis and factor prioritization in one or more cohorts. Moreover, it allows identifying critical interactions between cohorts and factors affecting metabolite levels and inferring a common covariate model, all via a graphical user interface.

Availability and implementation

We constructed Metabolite-Investigator as a free and open web-tool and stand-alone Shiny-app. It is hosted at https://apps.health-atlas.de/metabolite-investigator/, the source code is freely available at https://github.com/cfbeuchel/Metabolite-Investigator.

Supplementary information

Supplementary data are available at Bioinformatics online.

How could metabolomics change pediatric health?

In the last years, 'omics' technologies, and especially metabolomics, emerged as expanding scientific disciplines and promising technologies in the characterization of several pathophysiological processes.In detail, metabolomics, able to detect in a dynamic way the whole set of molecules of low molecular weight in cells, tissues, organs, and biological fluids, can provide a detailed phenotypic portray, representing a metabolic "snapshot."Thanks to its numerous strength points, metabolomics could become a fundamental tool in human health, allowing the exact evaluation of individual metabolic responses to pathophysiological stimuli including drugs, environmental changes, lifestyle, a great number of diseases and other epigenetics factors.Moreover, if current metabolomics data will be confirmed on larger samples, such technology could become useful in the early diagnosis of diseases, maybe even before the clinical onset, allowing a clinical monitoring of disease progression and helping in performing the best therapeutic approach, potentially predicting the therapy response and avoiding overtreatments. Moreover, the application of metabolomics in nutrition could provide significant information on the best nutrition regimen, optimal infantile growth and even in the characterization and improvement of commercial products' composition.These are only some of the fields in which metabolomics was applied, in the perspective of a precision-based, personalized care of human health.In this review, we discuss the available literature on such topic and provide some evidence regarding clinical application of metabolomics in heart diseases, auditory disturbance, nephrouropathies, adult and pediatric cancer, obstetrics, perinatal conditions like asphyxia, neonatal nutrition, neonatal sepsis and even some neuropsychiatric disorders, including autism.Our research group has been interested in metabolomics since several years, performing a wide spectrum of experimental and clinical studies, including the first metabolomics analysis of human breast milk. In the future, it is reasonable to predict that the current knowledge could be applied in daily clinical practice, and that sensible metabolomics biomarkers could be easily detected through cheap and accurate sticks, evaluating biofluids at the patient's bed, improving diagnosis, management and prognosis of sick patients and allowing a personalized medicine. A dream? May be I am a dreamer, but I am not the only one.