Untargeted metabolomics: an overview of its usefulness and future potential in prenatal diagnosis

ABSTRACT

Introduction: Metabolomics opens up new avenues for biomarker discovery in different branches of medicine, including perinatology. Chromosomal aberration, preterm delivery (PTD), congenital heart defects, spina bifida, chorioamnionitis, and low birth weight are the main perinatal pathologies. Investigations using untargeted metabolomics have found the candidate metabolites for diagnostic biomarkers.

Areas covered: This review describes areas of prenatal diagnosis in which untargeted metabolomics has been used. Data on the disease, type of sample, techniques used, number of samples used in the study, and metabolites obtained including the sign of their regulation are summarized.

Expert commentary: Untargeted metabolomics is a powerful tool which can shed a new light on prenatal diagnostics. It helps to discover affected metabolic pathways what may help to reveal disease pathogenesis and propose potential biomarkers. Among others, glycerol and 2- and 3-hydroxybutyrate were proposed as markers of chromosomal aberration. Serum metabolic signature of PTD was characterized by increased lipids and decreased levels of hypoxanthine, tryptophane, and pyroglutamic acid. Lower level lipids and vitamin D3 metabolites together with increased bilirubin level in maternal serum were associated with macrosomia. However, to give a real value to those assays and allow their clinical application multicenter, large cohort validation studies are necessary.     

Performance and environmental accounting of nutrient cycling models to estimate nitrogen emissions in agriculture and their sensitivity in life cycle assessment

Purpose

Several models are available in the literature to estimate agricultural emissions. From life cycle assessment (LCA) perspective, there is no standardized procedure for estimating emissions of nitrogen or other nutrients. This article aims to compare four agricultural models (PEF, SALCA, Daisy and Animo) with different complexity levels and test their suitability and sensitivity in LCA.

Methods

Required input data, obtained outputs, and main characteristics of the models are presented. Then, the performance of the models was evaluated according to their potential feasibility to be used in estimating nitrogen emissions in LCA using an adapted version of the criteria proposed by the United Nations Framework Convention on Climate Change (UNFCCC), and other relevant studies, to judge their suitability in LCA. Finally, nitrogen emissions from a case study of irrigated maize in Spain were estimated using the selected models and were tested in a full LCA to characterize the impacts.

Results and discussion

According to the set of criteria, the models scored, from best to worst: Daisy (77%), SALCA (74%), Animo (72%) and PEF (70%), being Daisy the most suitable model to LCA framework. Regarding the case study, the estimated emissions agreed to literature data for the irrigated corn crop in Spain and the Mediterranean, except N₂O emissions. The impact characterization showed differences of up to 56% for the most relevant impact categories when considering nitrogen emissions. Additionally, an overview of the models used to estimate nitrogen emissions in LCA studies showed that many models have been used, but not always in a suitable or justified manner.

Conclusions

Although mechanistic models are more laborious, mainly due to the amount of input data required, this study shows that Daisy could be a suitable model to estimate emissions when fertilizer application is relevant for the environmental study. In addition, and due to LCA urgently needing a solid methodology to estimate nitrogen emissions, mechanistic models such as Daisy could be used to estimate default values for different archetype scenarios.

     

Exposure to tobacco smoke and low birth weight: from epidemiology to metabolomics

Introduction: The exposure to tobacco smoke during pregnancy is one of the leading causes of perinatal adverse outcomes such as stillbirth, intrauterine growth restriction (IUGR), and low birth weight, but the underlying biological mechanisms are still unclear. The incidence of this phenomenon maybe largely underestimated since the evaluation is made mainly by self-assessment questionnaires rather than measuring nicotine metabolites (such as cotinine) in biological fluids. In this context metabolomics may be useful to assess the actual number of pregnant women and to highlight the pathophysiological mechanisms that lead to the abovementioned adverse outcomes.

Areas covered: The aims of this review are to analyze the literature and the application of the omics sciences, such as genomics and metabolomics concerning the negative effects of smoking during pregnancy in order to give a comprehensive picture of all the study made so far and to point out the potential of metabolomics as an investigative, predictive, and diagnostic tool.

Expert commentary: Metabolomics in recent years has proved an excellent tool to try to understand the problems in perinatal medicine. With the increase in the number of studies we are convinced that it can be a useful instrument of investigation in this field.     

Quality will determine the future of mass spectrometry imaging in clinical laboratories: the need for standardization

Introduction: Mass Spectrometry Imaging (MSI) provides information about the spatial distributions of different analytes on tissue sections and requires no homogenization techniques or labeling. It has a wide spectrum of applications ranging from biomarker discovery to drug response studies. MSI can be adapted to the clinical settings due to its ability to combine mass spectrometry and histological data.

Areas covered: The major obstacle to adapt MSI into clinical settings arises from the limited standardization in MSI experiments. We aimed to review the multi-site studies in MSI specifically focusing on reproducibility. Additionally, we emphasized the necessity of quality assessments in MSI for its potential usage in clinical settings.

Expert opinion: We discuss how important it is to follow optimized and standardized workflows in MSI and conduct potential quality assessments at important stages in order to adapt MSI into clinical applications.     

A Systematic Review and Meta-Analysis of the Effect of Short Birth Interval on Infant Mortality in Ethiopia

IntroductionEven though Ethiopia has been celebrating the achievements of MDG 4, still one in every 17 Ethiopian children dies before their first birthday. This is the biggest of the African regional average. Short birth interval is inconsistently reported as a risk factor by limited and independent studies in Ethiopia. Therefore, the purpose of this meta-analysis was to determine the pooled effect size of the preceding birth interval length on infant mortality.MethodsStudies were accessed through the electronic web-based search mechanism from PUBMED, Advanced Google Scholar, WHO databases and journals: PLOS ONE, and BMC, using independent and combinations of key terms. Comprehensive meta-analysis version 2 was used to analyze the data. An I² test was used to assess heterogeneity. Funnel plot and statistical significance by Egger’s test of the intercept was used to check publication bias. The final estimate was determined in the form of odds ratio by applying Duval and Tweedie’s trim and fill analysis in the Random-effects model.Results872 studies were identified on the reviewed topic. During screening, forty-five studies were found to be relevant for data abstraction. However, only five studies fulfilled the inclusion criteria and were included in the analysis. In all of the studies included in the analysis, the preceding birth interval had a significant association with under-one mortality. The final pooled estimate in the form of the odds ratio for infant mortality with a preceding birth interval of less than 24 months was found to be 2.03 (95% CI: 1.52, 2.70, random effect (five studies, n=43,909), I²=70%, P<0.05).ConclusionIn Ethiopia, promoting the length of birth interval to at least two years lowered under-one mortality by 50% (95% CI: 35%, 63%).     

Proteomic analysis of red blood cells and the potential for the clinic: what have we learned so far?

Introduction: Red blood cells (RBC) are the most abundant host cells in the human body. Mature erythrocytes are devoid of nuclei and organelles and have always been regarded as circulating ‘bags of hemoglobin’. The advent of proteomics has challenged this assumption, revealing unanticipated complexity and novel roles for RBCs not just in gas transport, but also in systemic metabolic homeostasis in health and disease.

Areas covered: In this review we will summarize the main advancements in the field of discovery mode and redox/quantitative proteomics with respect to RBC biology. We thus focus on translational/clinical applications, such as transfusion medicine, hematology (e.g. hemoglobinopathies) and personalized medicine. Synergy of omics technologies – especially proteomics and metabolomics – are highlighted as a hallmark of clinical metabolomics applications for the foreseeable future.

Expert commentary: The introduction of advanced proteomics technologies, especially quantitative and redox proteomics, and the integration of proteomics data with omics information gathered through orthogonal technologies (especially metabolomics) promise to revolutionize many biomedical areas, from hematology and transfusion medicine to personalized medicine and clinical biochemistry.     

Correcting observer effect bias in estimates of nesting success of a coastal bird,the White-fronted Plover Charadrius marginatus

Capsule A recently developed observer-effects model gives better estimates than the survival model.

Aims To compare the performance of the traditional survival model with that of an observer-effects model in estimating nesting success.

Methods We used survival data from 654 nests in a covariate-dependent extension of a maximum-likelihood estimator model to simultaneously estimate daily survival rate and observer effect on nesting success in four different sectors of a study site. Standard likelihood-ratio tests and Akaike's information criterion differences were used to compare model performances.

Results A significant (negative) observer effect was detected in one of four sectors of the study area, and was probably attributable to small mammal predators. Despite significantly higher predation risk during the laying period, there was a significant positive observer effect during the laying period, contrasting with a weak negative effect during the incubation period, suggesting that an observer's tracks around unattended nests reduced predation risk. Likelihood-ratio tests indicated a significantly better fit using the observer effects model versus the Mayfield survival model in four of six scenarios.

Conclusion The observer-effects model accounts for bias in estimates of nest survival rates, and is preferred over the survival model because the inclusion of observer effect as a variable does not over-parameterize the model.     

Preterm or Not – An Evaluation of Estimates of Gestational Age in a Cohort of Women from Rural Papua New Guinea

BackgroundKnowledge of accurate gestational age is required for comprehensive pregnancy care and is an essential component of research evaluating causes of preterm birth. In industrialised countries gestational age is determined with the help of fetal biometry in early pregnancy. Lack of ultrasound and late presentation to antenatal clinic limits this practice in low-resource settings. Instead, clinical estimators of gestational age are used, but their accuracy remains a matter of debate.MethodsIn a cohort of 688 singleton pregnancies from rural Papua New Guinea, delivery gestational age was calculated from Ballard score, last menstrual period, symphysis-pubis fundal height at first visit and quickening as well as mid- and late pregnancy fetal biometry. Published models using sequential fundal height measurements and corrected last menstrual period to estimate gestational age were also tested. Novel linear models that combined clinical measurements for gestational age estimation were developed. Predictions were compared with the reference early pregnancy ultrasound (<25 gestational weeks) using correlation, regression and Bland-Altman analyses and ranked for their capability to predict preterm birth using the harmonic mean of recall and precision (F-measure).ResultsAverage bias between reference ultrasound and clinical methods ranged from 0–11 days (95% confidence levels: 14–42 days). Preterm birth was best predicted by mid-pregnancy ultrasound (F-measure: 0.72), and neuromuscular Ballard score provided the least reliable preterm birth prediction (F-measure: 0.17). The best clinical methods to predict gestational age and preterm birth were last menstrual period and fundal height (F-measures 0.35). A linear model combining both measures improved prediction of preterm birth (F-measure: 0.58).ConclusionsEstimation of gestational age without ultrasound is prone to significant error. In the absence of ultrasound facilities, last menstrual period and fundal height are among the more reliable clinical measures. This study underlines the importance of strengthening ultrasound facilities and developing novel ways to estimate gestational age.     

Prediction of VLCAD deficiency phenotype by a metabolic fingerprint in newborn screening bloodspots

PurposeNewborns who test positive for very long-chain acyl-CoA dehydrogenase deficiency (VLCADD) in newborn screening may have a severe phenotype with early onset of life-threatening symptoms but may also have an attenuated phenotype and never become symptomatic. The objective of this study is to investigate whether metabolomic profiles in dried bloodspots (DBS) of newborns allow early phenotypic prediction, permitting tailored treatment and follow-up.MethodsA metabolic fingerprint was generated by direct infusion high resolution mass spectrometry in DBS of VLCADD patients (n = 15) and matched controls. Multivariate analysis of the metabolomic profiles was applied to differentiate subgroups.ResultsConcentration of six acylcarnitine species differed significantly between patients and controls. The concentration of C18:2- and C20:0-carnitine, 13,14-dihydroretinol and deoxycytidine monophosphate allowed separation between mild and severe patients. Two patients who could not be prognosticated on early clinical symptoms, were correctly fitted for severity in the score plot based on the untargeted metabolomics.ConclusionDistinctive metabolomic profiles in DBS of newborns with VLCADD may allow phenotypic prognostication. The full potential of this approach as well as the underlying biochemical mechanisms need further investigation.     

网络化管理对降低秦皇岛地区出生人口缺陷率的价值分析

目的:探讨网络化管理对降低秦皇岛地区出生人口缺陷率的应用价值。方法:选取2011年-2016年秦皇岛地区214404例新生儿两病(苯丙酮尿症和先天性甲状腺功能低下症)筛查的统计资料,并统计2011年至2016年每年及6年的筛查率和两病的筛查发病率,并与秦皇岛地区前6年两病的发生率进行对比。结果:秦皇岛地区6年内总筛查率为98.0010%,确诊苯丙酮尿症27例,先天性甲状腺功能低下症79例,两病的筛查疾病发病率分别为1/7782和1/2660。与前6年相比,2011至2016年两病的发生率均明显下降(P0.05)。结论:网络化管理通过及时预知并召回可疑患儿,对其采取行预防措施或者一定的治疗手段,降低了秦皇岛地区出生人口缺陷率,同时使新生儿筛查真实、完整、准确,效率较高,较易查询。     

Ambient and household PM2.5 pollution and adverse perinatal outcomes: A meta-regression and analysis of attributable global burden for 204 countries and territories

BackgroundParticulate matter <2.5 micrometer (PM_2.5) is associated with adverse perinatal outcomes, but the impact on disease burden mediated by this pathway has not previously been included in the Global Burden of Disease (GBD), Mortality, Injuries, and Risk Factors studies. We estimated the global burden of low birth weight (LBW) and preterm birth (PTB) and impacts on reduced birth weight and gestational age (GA), attributable to ambient and household PM_2.5 pollution in 2019.Methods and findingsWe searched PubMed, Embase, and Web of Science for peer-reviewed articles in English. Study quality was assessed using 2 tools: (1) Agency for Healthcare Research and Quality checklist; and (2) National Institute of Environmental Health Sciences (NIEHS) risk of bias questions. We conducted a meta-regression (MR) to quantify the risk of PM_2.5 on birth weight and GA. The MR, based on a systematic review (SR) of articles published through April 4, 2021, and resulting uncertainty intervals (UIs) accounted for unexplained between-study heterogeneity. Separate nonlinear relationships relating exposure to risk were generated for each outcome and applied in the burden estimation.The MR included 44, 40, and 40 birth weight, LBW, and PTB studies, respectively. Majority of the studies were of retrospective cohort design and primarily from North America, Europe, and Australia. A few recent studies were from China, India, sub-Saharan Africa, and South America. Pooled estimates indicated 22 grams (95% UI: 12, 32) lower birth weight, 11% greater risk of LBW (1.11, 95% UI: 1.07, 1.16), and 12% greater risk of PTB (1.12, 95% UI: 1.06, 1.19), per 10 μg/m³ increment in ambient PM_2.5. We estimated a global population–weighted mean lowering of 89 grams (95% UI: 88, 89) of birth weight and 3.4 weeks (95% UI: 3.4, 3.4) of GA in 2019, attributable to total PM_2.5. Globally, an estimated 15.6% (95% UI: 15.6, 15.7) of all LBW and 35.7% (95% UI: 35.6, 35.9) of all PTB infants were attributable to total PM_2.5, equivalent to 2,761,720 (95% UI: 2,746,713 to 2,776,722) and 5,870,103 (95% UI: 5,848,046 to 5,892,166) infants in 2019, respectively. About one-third of the total PM_2.5 burden for LBW and PTB could be attributable to ambient exposure, with household air pollution (HAP) dominating in low-income countries. The findings should be viewed in light of some limitations such as heterogeneity between studies including size, exposure levels, exposure assessment method, and adjustment for confounding. Furthermore, studies did not separate the direct effect of PM_2.5 on birth weight from that mediated through GA. As a consequence, the pooled risk estimates in the MR and likewise the global burden may have been underestimated.ConclusionsAmbient and household PM_2.5 were associated with reduced birth weight and GA, which are, in turn, associated with neonatal and infant mortality, particularly in low- and middle-income countries.

Rakesh Ghosh and co-workers report on associations between particulate matter air pollution and adverse perinatal health outcomes.     

Cetti's Warbler Cettia cetti: analysis of an expanding population

Capsule Productivity in the UK Cetti's Warbler population is constant, but overwinter survival has become increasingly dependent on winter temperatures.

Aims To demonstrate how constant effort (CE) ringing can be used to estimate productivity of breeding populations, using the expanding Cetti's Warbler population as an example.

Methods A logistic generalized linear model is developed from an established method of estimating abundance to generate an annual index of productivity from CE catches. Dispersal of birds from ring–recapture data is modelled using a simple exponential model of dispersal.

Results The number of Cetti's Warblers on CE sites has increased markedly, particularly since 1998, but productivity has remained largely constant. The rate of population increase has slowed in recent years, in part because of an increasing sensitivity of the population to cold winters. Juveniles disperse further than adults, and the distance over which they disperse has increased.

Conclusions CE catching provides a way of easily measuring whole-season productivity. The future of Cetti's Warblers in Britain looks secure, but the population may be approaching its maximum size under current conditions.     

The Undiagnosed Chronically-Infected HCV Population in France. Implications for Expanded Testing Recommendations in 2014

BackgroundRecent HCV therapeutic advances make effective screening crucial for potential HCV eradication. To identify the target population for a possible population-based screening strategy to complement current risk-based testing in France, we aimed to estimate the number of adults with undiagnosed chronic HCV infection and age and gender distribution at two time points: 2004 and 2014.MethodsA model taking into account mortality, HCV incidence and diagnosis rates was applied to the 2004 national seroprevalence survey.ResultsIn 2014, an estimated 74,102 individuals aged 18 to 80 were undiagnosed for chronic HCV infection (plausible interval: 64,920-83,283) compared with 100,868 [95%CI: 58,534-143,202] in 2004. Men aged 18-59 represented approximately half of the undiagnosed population in 2014. The proportion of undiagnosed individuals in 2004 (43%) varied from 21.9% to 74.1% in the 1945-1965 and 1924-1944 birth cohorts. Consequently, age and gender distributions between the chronically-infected (diagnosed and undiagnosed) and undiagnosed HCV populations were different, the 1945-1965 birth cohort representing 48.9% and 24.7%, respectively.ConclusionsMany individuals were still undiagnosed in 2014 despite a marked reduction with respect to 2004. The present work contributed to the 2014 recommendation of a new French complementary screening strategy, consisting in one-time simultaneous HCV, HBV and HIV testing in men aged 18-60. Further studies are needed to assess the cost-effectiveness and feasibility of such a strategy. We also demonstrated that data on the undiagnosed HCV population are crucial to help adapt testing strategies, as the features of the chronically-infected HCV population are very distinct.     

The metabolomics and lipidomics window into thyroid cancer research

Context: Thyroid carcinoma is the most common endocrine system malignancy with a fast rising incidence in the last decade for unknown reasons. Fine needle aspiration (FNA) biopsy, the gold standard in thyroid cancer (TC) screening has still its own challenges and in some cases needs a proceeding surgery.

Objective: This review highlights the role of the two most recent “omics” approaches, “metabolomics” and “lipidomics”, in the field of TC research.

Methods: All the previous studies have been extracted from the literature and major concepts were detailed in the field of TC metabolomics and lipidomics.

Results: Metabolomics and lipidomics, have potential in finding biomarkers related to thyroid carcinoma. Among the previous studies, the most important introduced altered tissue metabolites and lipids included glucose and galactose, lactate, Scyllo- and Myo inositol, hypoxanthine, citrate, cholesterol and choline.

Conclusion: Metabolomics methods have been widely used in the field of biomarker discovery in TC and attempts are still in progress to use these methods to find a reliable biomarker panel besides current diagnostic tools.     

出生早期母婴分离对新生小鼠神经元细胞凋亡的影响

目的:探讨出生早期母婴分离对新生儿神经系统的影响及其相关机制。方法:随机选择2015年1月~2015年9月出生的新生小鼠120例作为本次研究的对象,其中新生小鼠出生后实施母婴分离的作为观察组(60只),出生后不实施母婴分离的作为对照组(60只)。比较两组新生小鼠的神经系统、神经细胞的变化。结果:观察组新生小鼠在母婴分离第7天、14天、21天的神经元细胞的凋亡率显著高于对照组新生(P值均0.05),神经元胱天蛋白酶-3(Caspase-3)蛋白表达均明显高于对照组(P值均0.05)。观察组新生小鼠的母婴分离14天、21天的神经胶质细胞小窝蛋白-1(Caveo-1)蛋白的表达,与对照组新生小鼠的神经胶质细胞Caveo-1蛋白的表达进行比较,(P值均0.05),具有统计学意义。结论:出生早期实施母婴分离,对新生儿的神经系统会产生较大的影响,影响新生儿发育中神经系统的表达,进而会影响新生儿成年后的行为发育异常。     

Serum metabolomics identifies metabolite panels that differentiate lame dairy cows from healthy ones

Background

Metabolomics provides measurement of numerous metabolites in human samples, which can be a useful tool in clinical research. Blood and urine are regarded as preferred subjects of study because of their minimally invasive collection and simple preprocessing methods. Adhering to standard operating procedures is an essential factor in ensuring excellent sample quality and reliable results.

Aim of review

In this review, we summarize the studies about the impacts of various preprocessing factors on metabolomics studies involving clinical blood and urine samples in order to provide guidance for sample collection and preprocessing.

Key scientific concepts of review

Clinical information is important for sample grouping and data analysis which deserves attention before sample collection. Plasma and serum as well as urine samples are appropriate for metabolomics analysis. Collection tubes, hemolysis, delay at room temperature, and freeze–thaw cycles may affect metabolic profiles of blood samples. Collection time, time between sampling and examination, contamination, normalization strategies, and storage conditions may alter analysis results of urine samples. Taking these collection and preprocessing factors into account, this review provides suggestions of standard sample preprocessing.

     

The choice of amniotic fluid in metabolomics for the monitoring of fetus health - update

Introduction: In recent years, several studies have highlighted the promising role of metabolomics in the analysis of amniotic fluid (AF), to describe and characterize the interactions occurring between the mother and the fetus during prenatal development.

Among the available biological fluids, AF represents an ideal substrate to provide dynamic information regarding fetal organogenesis and metabolism through pregnancy, since it originates from both maternal and fetal tissues and contains substances derived from placenta, fetal skin, lungs, gastric fluid, and fetal urine.

Areas covered: In this paper, we provide an update reporting the most recent results on AF metabolomics in the assessment of feto-maternal health, regarding physiological pregnancies but even fields such as prematurity, bronchopulmonary dysplasia, fetal malformations, chromosomopathies, maternal diseases, placental inflammation or infections, maternal diet or exposure to exogenous substances, according to the literature found on MEDLINE since 2015.

Expert opinion: Metabolomics shows a promising role in describing both physiology and disease; the goal would be the identification of biomarkers able to precociously and efficaciously detect pathological conditions, allowing the identification of complicated pregnancy and improving their management. However, this field is under development and its reliability still needs to be clarified, especially through more numerous and accurate studies.     

Metabolic phenotyping to monitor chronic enteritis canceration

Introduction

Untargeted metabolomics intends to objectively analyze a wide variety of compounds. Their diverse physicochemical properties make it difficult to choose an appropriate reconstitution solvent after sample evaporation without influencing the chromatography or hamper column sorbent integrity.

Objectives

The study aimed to identify the most appropriate reconstitution solvent for blood plasma samples in terms of feature recovery, four endogenous compounds, and one selected internal standard.

Methods

We investigated several reconstitution solvent mixtures containing acetonitrile and methanol to resolve human plasma extract and evaluated them concerning the peak areas of tryptophan-d₅, glucose, creatinine, palmitic acid, and the phophatidylcholine PC(P-16:0/P-16:0), as well as the total feature count

Results

Results indicated that acetonitrile containing 30% methanol was best suited to match all tested criteria at least for human blood plasma samples.

Conclusion

Despite identifying the mixture of acetonitrile and methanol being suitable as solvent for human blood plasma extracts, we recommend to systematically test for an appropriate reconstitution solvent for each analyzed biomatrix.