Untargeted Metabolomic Biomarker Discovery for the Detection of Ectopic Pregnancy.

Ectopic pregnancy (EP) is the leading cause of maternal morbidity and mortality in the first trimester. Using an untargeted metabolomic approach, we sought to identify putative plasma biomarkers using tandem liquid chromatography-mass spectrometry for the detection of tubal EP. This case-control study included the prospective recruitment of 50 tubal EP cases and 50 early intrauterine pregnancy controls.

Metabolomic prediction of severe maternal and newborn complications in preeclampsia.

Introduction: Preeclampsia (PreE) remains a major source of maternal and newborn complications. Prenatal prediction of these complications could significantly improve pregnancy management.

Objectives: Using metabolomic analysis we investigated the prenatal prediction of maternal and newborn complications in early and late PreE and investigated the pathogenesis of such complications.

Metabolomics: An Emerging "Omics" Platform for Systems Biology and Its Implications for Huntington Disease Research.

Huntington's disease (HD) is a progressive, fatal neurodegenerative disease characterized by motor, cognitive, and psychiatric symptoms. The precise mechanisms of HD progression are poorly understood; however, it is known that there is an expansion of the trinucleotide cytosine-adenine-guanine (CAG) repeat in the Huntingtin gene. Important new strategies are of paramount importance to identify early biomarkers with predictive value for intervening in disease progression at a stage when cellular dysfunction has not progressed irreversibly.

Neurocutaneous Disorders in Pregnancy.

Importance: Neurocutaneous disorders have significant implications for care of the pregnant patient. As neurocutaneous disorders are uncommon, obstetricians may be unfamiliar with these disorders and with recommendations for appropriate care of this population.

Objective: This review aims to summarize existing literature on the interaction between neurocutaneous disorders and pregnancy and to provide a guide for physicians caring for an affected patient.

Precision oncology: Artificial intelligence, circulating cell-free DNA, and the minimally invasive detection of pancreatic cancer-A pilot study.

Background: Pancreatic cancer (PC) is among the most lethal cancers. The lack of effective tools for early detection results in late tumor detection and, consequently, high mortality rate. Precision oncology aims to develop targeted individual treatments based on advanced computational approaches of omics data.

Evaluation During Postpartum Hemorrhage.

Postpartum hemorrhage is an obstetric emergency that is the leading and the most preventable cause of maternal death that occurs on the day of birth. The treatment of postpartum hemorrhage in a timely fashion is crucial to prevent morbidity and mortality. The accurate assessment of blood loss during delivery and the postpartum period remains a major challenge.

Fetal effects of mild maternal COVID-19 infection: metabolomic profiling of cord blood.

Introduction: The impact of maternal coronavirus disease 2019 (COVID-19) infection on fetal health remains to be precisely characterized.

Objectives: Using metabolomic profiling of newborn umbilical cord blood, we aimed to investigate the potential fetal biological consequences of maternal COVID-19 infection.

Methods: Cord blood plasma samples from 23 mild COVID-19 cases (mother infected/newborn negative) and 23 gestational age-matched controls were analyzed using nuclear magnetic spectroscopy and liquid chromatography coupled with mass spectrometry.

Alzheimer's Precision Neurology: Epigenetics of Cytochrome P450 Genes in Circulating Cell-Free DNA for Disease Prediction and Mechanism.

Precision neurology combines high-throughput technologies and statistical modeling to identify novel disease pathways and predictive biomarkers in Alzheimer's disease (AD). Brain cytochrome P450 (CYP) genes are major regulators of cholesterol, sex hormone, and xenobiotic metabolism, and they could play important roles in neurodegenerative disorders. Increasing evidence suggests that epigenetic factors contribute to AD development.

Does Maternal SARS-CoV-2 Infection or SARS-CoV-2 Vaccination Trigger an Inflammatory Response in the Fetus? A Prospective Cohort Study.

Objectives: SARS-CoV-2 infection triggers a significant maternal inflammatory response. There is a dearth of information regarding whether maternal SARS-CoV-2 infection at admission for delivery or SARS-CoV-2 vaccination triggers an inflammatory response in the fetus. This study aims at evaluating fetal inflammatory response to maternal SARS-CoV-2 infection or SARS-CoV-2 vaccination compared to control group.

Urine metabolomic biomarkers for prediction of isolated fetal congenital heart defect.

Objective: To identify maternal second and third trimester urine metabolomic biomarkers for the detection of fetal congenital heart defects (CHDs).

Study Design: This was a prospective study. Metabolomic analysis of randomly collected maternal urine was performed, comparing pregnancies with isolated, non-syndromic CHDs versus unaffected controls.

Targeted metabolomics highlights perturbed metabolism in the brain of autism spectrum disorder sufferers.

Introduction: Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders characterized by deficiencies in social interactions and communication, combined with restricted and repetitive behavioral issues.

Objectives: As little is known about the etiopathophysiology of ASD and early diagnosis is relatively subjective, we aim to employ a targeted, fully quantitative metabolomics approach to biochemically profile post-mortem human brain with the overall goal of identifying metabolic pathways that may have been perturbed as a result of the disease while uncovering potential central diagnostic biomarkers.

Methods: Using a combination of H NMR and DI/LC-MS/MS we quantitatively profiled the metabolome of the posterolateral cerebellum from post-mortem human brain harvested from people who suffered with ASD (n = 11) and compared them with age-matched controls (n = 10).

Metabolomic identification of placental alterations in fetal growth restriction.

Introduction: Fetal growth restriction (FGR), viz., birth weight <10th percentile is a common pregnancy complication which increases the risk of adverse fetal and newborn outcomes. The placenta is the key organ for fetal growth as it controls oxygen and nutrient availability.

Metabolomic identification of novel diagnostic biomarkers in ectopic pregnancy.

Introduction: Ectopic pregnancy (EP) is a potentially life-threatening condition and early diagnosis still remains a challenge, causing a delay in management leading to tubal rupture.

Objectives: To identify putative plasma biomarkers for the detection of tubal EP and elucidate altered biochemical pathways in EP compared to intrauterine pregnancies.

Methods: This case-control study included prospective recruitment of 39 tubal EP cases and 89 early intrauterine pregnancy controls.

Artificial Intelligence and the detection of pediatric concussion using epigenomic analysis.

Concussion, also referred to as mild traumatic brain injury (mTBI) is the most common type of traumatic brain injury. Currently concussion is an area ofintensescientific interest to better understand the biological mechanisms and for biomarker development. We evaluated whole genome-wide blood DNA cytosine ('CpG') methylation in 17 pediatric concussion isolated cases and 18 unaffected controls using Illumina Infinium MethylationEPIC assay.

Artificial intelligence and the analysis of multi-platform metabolomics data for the detection of intrauterine growth restriction.

Objective: To interrogate the pathogenesis of intrauterine growth restriction (IUGR) and apply Artificial Intelligence (AI) techniques to multi-platform i.e. nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) based metabolomic analysis for the prediction of IUGR.

Targeted metabolomic profiling of low and high grade serous epithelial ovarian cancer tissues: a pilot study.

Introduction: Epithelial ovarian cancer (EOC) remains the leading cause of death from gynecologic malignancies and has an alarming global fatality rate. Besides the differences in underlying pathogenesis, distinguishing between high grade (HG) and low grade (LG) EOC is imperative for the prediction of disease progression and responsiveness to chemotherapy.

Objectives: The aim of this study was to investigate, the tissue metabolome associated with HG and LG serous epithelial ovarian cancer.

First-trimester metabolomic prediction of stillbirth.

Stillbirth remains a major problem in both developing and developed countries. Omics evaluation of stillbirth has been highlighted as a top research priority. To identify new putative first-trimester biomarkers in maternal serum for stillbirth prediction using metabolomics-based approach.

Diminished ovarian reserve in patients with psoriasis.

Objective: Psoriasis is a multi-systemic chronic inflammatory skin disease. Previous data suggests that women with some chronic inflammatory diseases have diminished ovarian reserve. This study explores ovarian reserve in patients with psoriasis.

Metabolomic prediction of endometrial cancer.

Introduction: Endometrial cancer (EC) is associated with metabolic disturbances including obesity, diabetes and metabolic syndrome. Identifying metabolite biomarkers for EC detection has a crucial role in reducing morbidity and mortality.

Objective: To determine whether metabolomic based biomarkers can detect EC overall and early-stage EC.

Integrated Proteomic and Metabolomic prediction of Term Preeclampsia.

Term preeclampsia (tPE), ≥37 weeks, is the most common form of PE and the most difficult to predict. Little is known about its pathogenesis. This study aims to elucidate the pathogenesis and assess early prediction of tPE using serial integrated metabolomic and proteomic systems biology approaches.

Targeted Metabolic Profiling of Post-Mortem Brain from Infants Who Died from Sudden Infant Death Syndrome.

Currently little is known about the underlying pathophysiology associated with SIDS, and no objective biomarkers exist for the accurate identification of those at greatest risk of dying from SIDS. Using targeted metabolomics, we aim to profile the medulla oblongata of infants who have died from SIDS (n = 16) and directly compare their biochemical profile with age matched controls. Combining data acquired using H NMR and targeted DI-LC-MS/MS, we have identified fatty acid oxidation as a pivotal biochemical pathway perturbed in the brains of those infants who have from SIDS (p = 0.

Metabolomic determination of pathogenesis of late-onset preeclampsia.

Objective: Our primary objective was to apply metabolomic pathway analysis of first trimester maternal serum to provide an insight into the pathogenesis of late-onset preeclampsia (late-PE) and thereby identify plausible therapeutic targets for PE.

Methods: NMR-based metabolomics analysis was performed on 29 cases of late-PE and 55 unaffected controls. In order to achieve sufficient statistical power to perform the pathway analysis, these cases were combined with a group of previously analyzed specimens, 30 late-PE cases and 60 unaffected controls.

Genome-Wide DNA Methylation Analysis and Epigenetic Variations Associated with Congenital Aortic Valve Stenosis (AVS).

Congenital heart defect (CHD) is the most common cause of death from congenital anomaly. Among several candidate epigenetic mechanisms, DNA methylation may play an important role in the etiology of CHDs. We conducted a genome-wide DNA methylation analysis using an Illumina Infinium 450k human methylation assay in a cohort of 24 newborns who had aortic valve stenosis (AVS), with gestational-age matched controls.

Metabolomics of biomarker discovery in ovarian cancer: a systematic review of the current literature.

Introduction: Metabolomics is the emerging member of "omics" sciences advancing the understanding, diagnosis and treatment of many cancers, including ovarian cancer (OC).

Objectives: To systematically identify the metabolomic abnormalities in OC detection, and the dominant metabolic pathways associated with the observed alterations.

Methods: An electronic literature search was performed, up to and including January 15th 2016, for studies evaluating the metabolomic profile of patients with OC compared to controls.