The Urinary Metabolome of Healthy Newborns

Metabolic maturation in the infant urine during the first 3 months of life

The infant urine metabolome provides a body metabolic snapshot, and the sample collection can be done without stressing the fragile infant. 424 infant urine samples from 157 infants were sampled longitudinally at 1-, 2-, and 3 months of age. 49 metabolites were detected using proton nuclear magnetic resonance spectroscopy. Data were analyzed with multi- and univariate statistical methods to detect differences related to infant age-stage, gestational age, mother's pre-pregnancy BMI, C-section, infant birth weight, and infant sex. Significant differences were identified between age-stage (pbonferoni < 0.05) in 30% (15/49) of the detected metabolites. Urine creatinine increased significantly from 1 to 3 months. In addition, myo-inositol, taurine, methionine, and glucose seem to have conserved levels within the individual over time. We calculated a urine metabolic maturation age and found that the metabolic age at 3 months is negatively correlated to weight at 1 year. These results demonstrate that the metabolic maturation can be observed in urine metabolome with implications on infant growth and specifically suggesting that the systematic age effect on creatinine promotes caution in using this as normalization of other urine metabolites.

The Urinary Metabolome of Newborns with Perinatal Complications

Maternal pathological conditions such as infections and chronic diseases, along with unexpected events during labor, can lead to life-threatening perinatal outcomes. These outcomes can have irreversible consequences throughout an individual's entire life. Urinary metabolomics can provide valuable insights into early physiological adaptations in healthy newborns, as well as metabolic disturbances in premature infants or infants with birth complications. In the present study, we measured 180 metabolites and metabolite ratios in the urine of 13 healthy (hospital-discharged) and 38 critically ill newborns (admitted to the neonatal intensive care unit (NICU)). We used an in-house-developed targeted tandem mass spectrometry (MS/MS)-based metabolomic assay (TMIC Mega) combining liquid chromatography (LC-MS/MS) and flow injection analysis (FIA-MS/MS) to quantitatively analyze up to 26 classes of compounds. Average urinary concentrations (and ranges) for 167 different metabolites from 38 critically ill NICU newborns during their first 24 h of life were determined. Similar sets of urinary values were determined for the 13 healthy newborns. These reference data have been uploaded to the Human Metabolome Database. Urinary concentrations and ranges of 37 metabolites are reported for the first time for newborns. Significant differences were found in the urinary levels of 44 metabolites between healthy newborns and those admitted at the NICU. Metabolites such as acylcarnitines, amino acids and derivatives, biogenic amines, sugars, and organic acids are dysregulated in newborns with bronchopulmonary dysplasia (BPD), asphyxia, or newborns exposed to SARS-CoV-2 during the intrauterine period. Urine can serve as a valuable source of information for understanding metabolic alterations associated with life-threatening perinatal outcomes.

Association of Maternal Age and Blood Markers for Metabolic Disease in Newborns

Pregnancy at an advanced maternal age is considered a risk factor for adverse maternal, fetal, and neonatal outcomes. Here we investigated whether maternal age could be associated with differences in the blood levels of newborn screening (NBS) markers for inborn metabolic disorders on the Recommended Universal Screening Panel (RUSP). Population-level NBS data from screen-negative singleton infants were examined, which included blood metabolic markers and covariates such as age at blood collection, birth weight, gestational age, infant sex, parent-reported ethnicity, and maternal age at delivery. Marker levels were compared between maternal age groups (age range: 1544 years) using effect size analyses, which controlled for differences in group sizes and potential confounding from other covariates. We found that 13% of the markers had maternal age-related differences, including newborn metabolites with either increased (Tetradecanoylcarnitine [C14], Palmitoylcarnitine [C16], Stearoylcarnitine [C18], Oleoylcarnitine [C18:1], Malonylcarnitine [C3DC]) or decreased (3-Hydroxyisovalerylcarnitine [C5OH]) levels at an advanced maternal age (≥35 years, absolute Cohen's d > 0.2). The increased C3DC levels in this group correlated with a higher false-positive rate in newborn screening for malonic acidemia (p-value < 0.001), while no significant difference in screening performance was seen for the other markers. Maternal age is associated with inborn metabolic differences and should be considered together with other clinical variables in genetic disease screening.

The Urinary Metabolomic Fingerprint in Extremely Preterm Infants on Total Parenteral Nutrition vs. Enteral Feeds

Total Parenteral Nutrition (TPN), which uses intravenous administration of nutrients, minerals and vitamins, is essential for sustaining premature infants until they transition to enteral feeds, but there is limited information on metabolomic differences between infants on TPN and enteral feeds. We performed untargeted global metabolomics on urine samples collected between 23-30 days of life from 314 infants born <29 weeks gestational age from the TOLSURF and PROP cohorts. Principal component analysis across all metabolites showed a separation of infants solely on TPN compared to infants who had transitioned to enteral feeds, indicating global metabolomic differences between infants based on feeding status. Among 913 metabolites that passed quality control filters, 609 varied in abundance between infants on TPN vs. enteral feeds at p < 0.05. Of these, 88% were in the direction of higher abundance in the urine of infants on enteral feeds. In a subset of infants in a longitudinal analysis, both concurrent and delayed changes in metabolite levels were observed with the initiation of enteral feeds. These infants had higher concentrations of essential amino acids, lipids, and vitamins, which are necessary for growth and development, suggesting the nutritional benefit of an enteral feeding regimen.

Ketogenic diet in action: Metabolic profiling of pyruvate dehydrogenase deficiency

The pyruvate dehydrogenase complex serves as the main connection between cytosolic glycolysis and the tricarboxylic acid cycle within mitochondria. An infant with pyruvate dehydrogenase complex deficiency was treated with vitamin B1 supplementation and a ketogenic diet. These dietary modifications resolved the renal tubular reabsorption, central apnea, and transfusion-dependent anemia. A concurrent metabolome analysis demonstrated the resolution of the amino aciduria and an increased total amount of substrates in the tricarboxylic acid cycle, reflecting the improved mitochondrial energetics. Glutamate was first detected in the cerebrospinal fluid, accompanied by a clinical improvement, after the ketogenic ratio was increased to 3:1; thus, glutamate levels in cerebrospinal fluid may represent a biomarker for neuronal recovery. Metabolomic analyses of body fluids are useful for monitoring therapeutic effects in infants with inborn errors of carbohydrate metabolism.

Ex vivo proton spectroscopy (1 H-NMR) analysis of inborn errors of metabolism: Automatic and computer-assisted analyses

There are about 1500 genetic metabolic diseases. A small number of treatable diseases are diagnosed by newborn screening programs, which are continually being developed. However, most diseases can only be diagnosed based on clinical symptoms or metabolic findings. The main biological fluids used are urine, plasma and, in special situations, cerebrospinal fluid. In contrast to commonly used methods such as gas chromatography and high performance liquid chromatography mass spectrometry, ex vivo proton spectroscopy (¹ H-NMR) is not yet used in routine clinical practice, although it has been recommended for more than 30 years. Automatic analysis and improved NMR technology have also expanded the applications used for the diagnosis of inborn errors of metabolism. We provide a mini-overview of typical applications, especially in urine but also in plasma, used to diagnose common but also rare genetic metabolic diseases with ¹ H-NMR. The use of computer-assisted diagnostic suggestions can facilitate interpretation of the profiles. In a proof of principle, to date, 182 reports of 59 different diseases and 500 reports of healthy children are stored. The percentage of correct automatic diagnoses was 74%. Using the same ¹ H-NMR profile-targeted analysis, it is possible to apply an untargeted approach that distinguishes profile differences from healthy individuals. Thus, additional conditions such as lysosomal storage diseases or drug interferences are detectable. Furthermore, because ¹ H-NMR is highly reproducible and can detect a variety of different substance categories, the metabolomic approach is suitable for monitoring patient treatment and revealing additional factors such as nutrition and microbiome metabolism. Besides the progress in analytical techniques, a multiomics approach is most effective to combine metabolomics with, for example, whole exome sequencing, to also diagnose patients with nondetectable metabolic abnormalities in biological fluids. In this mini review we also provide our own data to demonstrate the role of NMR in a multiomics platform in the field of inborn errors of metabolism.

Urine Metabolomic Profile of Breast- versus Formula-Fed Neonates Using a Synbiotic-Enriched Formula

The aim of this study was to compare the urine metabolic fingerprint of healthy neonates exclusively breastfed with that of neonates fed with a synbiotic-enriched formula (Rontamil^® Complete 1) at four time points (the 3rd and 15th days of life and the 2nd and 3rd months). The determination of urine metabolic fingerprint was performed using NMR metabolomics. Multivariate data analyses were performed with SIMCA-P 15.0 software and R language. Non-distinct profiles for both groups (breastfeeding and synbiotic formula) for the two first time points (3rd and 15th days of life) were detected, whereas after the 2nd month of life, a discrimination trend was observed between the two groups, which was further confirmed at the 3rd month of life. A clear discrimination of the synbiotic formula samples was evident when comparing the metabolites taken in the first days of life (3rd day) with those taken in the 2nd and 3rd months of life. In both cases, OPLS-DA models explained more than 75% of the metabolic variance. Non-distinct metabolomic profiles were obtained between breastfed and synbiotic-formula-fed neonates up to the 15th day of life. Discrimination trends were observed only after the 2nd month of the study, which could be attributed to breastfeeding variations and the consequent dynamic profile of urine metabolites compared to the stable ingredients of the synbiotic formula.

Associations of Diet with Urinary Trimethylamine-N-Oxide (TMAO) and Its Precursors among Free-Living 10-Year-Old Children: Data from SMBCS

Trimethylamine-N-oxide (TMAO), a diet-derived cometabolite linked to cardiometabolic disease, has been associated with elevated dietary status, particularly in people with kidney failure and adults with dietary modulations. However, the influence of the current diet on TMAO levels in free-living children has not been adequately described. This study was to explore associations of food compositions and dietary diversity with urinary TMAO and its precursor concentrations. Urinary TMAO and its precursor concentrations of 474 healthy children from the Sheyang Mini Birth Cohort were quantified by ultra-performance liquid chromatography−Q Exactive high-resolution mass spectrometer (UPLC-Q Exactive HRMS). Individual food compositions from 24 h dietary recall data were classified into 20 groups and diversity scores were calculated according to the guidelines of the Food and Agriculture Organization of the United Nations (FAO). Associations of urinary TMAO and its precursors with food compositions and dietary diversity scores were assessed by generalized linear regression models. In models adjusted for potential confounders, urinary TMAO was significantly associated with intakes of fish (β, regression coefficient = 0.155, p < 0.05) and vegetables (β = 0.120, p < 0.05). Eggs intake showed positive associations with TMAO’s precursors (trimethylamine: β = 0.179, p < 0.05; choline: β = 0.181, p < 0.05). No association between meat intake and TMAO was observed, whereas meat and poultry intakes were related to the levels of acetyl-L-carnitine and L-carnitine (β: 0.134 to 0.293, p < 0.05). The indicators of dietary diversity were positively correlated to TMAO concentration (β: 0.027 to 0.091, p < 0.05). In this free-living children-based study, dietary factors were related to urinary TMAO and its precursors, especially fish, meat, and eggs. As such, dietary diversity was positively related to the level of TMAO.

Urinary Metabolomic Study in a Healthy Children Population and Metabolic Biomarker Discovery of Attention-Deficit/Hyperactivity Disorder (ADHD)

Objectives

Knowledge of the urinary metabolomic profiles of healthy children and adolescents plays a promising role in the field of pediatrics. Metabolomics has also been used to diagnose disease, discover novel biomarkers, and elucidate pathophysiological pathways. Attention-deficit/hyperactivity disorder (ADHD) is one of the most common psychiatric disorders in childhood. However, large-sample urinary metabolomic studies in children with ADHD are relatively rare. In this study, we aimed to identify specific biomarkers for ADHD diagnosis in children and adolescents by urinary metabolomic profiling.

Methods

We explored the urine metabolome in 363 healthy children aged 1-18 years and 76 patients with ADHD using high-resolution mass spectrometry.

Results

Metabolic pathways, such as arachidonic acid metabolism, steroid hormone biosynthesis, and catecholamine biosynthesis, were found to be related to sex and age in healthy children. The urinary metabolites displaying the largest differences between patients with ADHD and healthy controls belonged to the tyrosine, leucine, and fatty acid metabolic pathways. A metabolite panel consisting of FAPy-adenine, 3-methylazelaic acid, and phenylacetylglutamine was discovered to have good predictive ability for ADHD, with a receiver operating characteristic area under the curve (ROC-AUC) of 0.918. A panel of FAPy-adenine, N-acetylaspartylglutamic acid, dopamine 4-sulfate, aminocaproic acid, and asparaginyl-leucine was used to establish a robust model for ADHD comorbid tic disorders and controls with an AUC of 0.918.

A rapid LC-MS/MS assay for detection and monitoring of underivatized branched-chain amino acids in maple syrup urine disease

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Branched chain amino acid (BCAA) testing is crucial in the diagnosis and monitoring of maple syrup urine disease (MSUD).

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Mixed mode chromatography can be applied to separate BCAAs without requiring sample derivatization.

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A rapid, clinically validated LC-MS/MS-based assay for analysis of underivatized BCAA in human plasma was developed.

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The assay involves minimal sample preparation without derivatization, rapid chromatographic separation, and requires only 20 µL of sample.

Introduction

Quantitation of the isomeric branched-chain amino acids (BCAA; valine, alloisoleucine, isoleucine, leucine) is a challenging task that typically requires derivatization steps or long runtimes if a traditional chromatographic method involving a ninhydrin ion pairing reagent is used.

Objectives

To develop and perform clinical validation of a rapid, LC-MS/MS-based targeted metabolomics assay for detection and monitoring of underivatized BCAA in human plasma.

Methods:

Various columns and modes of chromatography were tested. The final optimized method utilized mixed mode chromatography with an Intrada column under isocratic condition. Sample preparation utilized the 96-well format. Briefly, extraction solvent containing the internal standard is added to 20 uL of sample, followed by shaking and positive pressure filtering, and the resulting extracted sample is analyzed. The assay was validated based on accepted quality standards (e.g., CLIA and CLSI) for clinical assays.

Results

The method is linear over a wide range of concentrations, 2.0–1500 µM, with LOD of 0.60 µM and LOQ of 2.0 µM. The precision of the assay was 4–10% across analytes. The method was also validated against reference laboratories via blinded split-sample analysis and demonstrated good agreement with accuracy: 89–95% relative to the external group mean.

Conclusion

We have developed a method that is accurate, rapid, and reliable for routine clinical testing of patient sample BCAA, which is used in the diagnosis and management of maple syrup urine disease (MSUD). The assay also has desirable characteristics, such as short run time, small sample volume requirement, simple sample preparation without the need for derivatization, and high throughput.

A Longitudinal 1H NMR-Based Metabolic Profile Analysis of Urine from Hospitalized Premature Newborns Receiving Enteral and Parenteral Nutrition

Preterm newborns are extremely vulnerable to morbidities, complications, and death. Preterm birth is a global public health problem due to its socioeconomic burden. Nurturing preterm newborns is a critical medical issue because they have limited nutrient stores and it is difficult to establish enteral feeding, which leads to inadequate growth frequently associated with poor neurodevelopmental outcomes. Parenteral nutrition (PN) provides nutrients to preterm newborns, but its biochemical effects are not completely known. To study the effect of PN treatment on preterm newborns, an untargeted metabolomic ¹H nuclear magnetic resonance (NMR) assay was performed on 107 urine samples from 34 hospitalized patients. Multivariate data (Principal Component Analysis, PCA, Orthogonal partial least squares discriminant analysis OPLS-DA, parallel factor analysis PARAFAC-2) and univariate analyses were used to identify the association of specific spectral data with different nutritional types (NTs) and gestational ages. Our results revealed changes in the metabolic profile related to the NT, with the tricarboxylic acid cycle and galactose metabolic pathways being the most impacted pathways. Low citrate and succinate levels, despite higher glucose relative urinary concentrations, seem to constitute the metabolic profile found in the studied critically ill preterm newborns who received PN, indicating an energetic dysfunction that must be taken into account for better nutritional management.

A Comparison of Mother’s Milk and the Neonatal Urine Metabolome: A Unique Fingerprinting for Different Nutritional Phenotypes

The ability of metabolomics to provide a snapshot of an individual’s metabolic state makes it a very useful technique in neonatology for investigating the complex relationship between nutrition and the state of health of the newborn. Through an ¹H-NMR metabolomics analysis, we aimed to investigate the metabolic profile of newborns by analyzing both urine and milk samples in relation to the birth weight of neonates classified as AGA (adequate for the gestational age, n = 51), IUGR (intrauterine growth restriction, n = 14), and LGA (large for gestational age, n = 15). Samples were collected at 7 ± 2 days after delivery. Of these infants, 42 were exclusively breastfed, while 38 received mixed feeding with a variable amount of commercial infant formula (less than 40%) in addition to breast milk. We observed a urinary spectral pattern for oligosaccharides very close to that of the corresponding mother’s milk in the case of exclusively breastfed infants, thus mirroring the maternal phenotype. The absence of this good match between the infant urine and human milk spectra in the case of mixed-fed infants could be reasonably ascribed to the use of a variable amount of commercial infant formulas (under 40%) added to breast milk. Furthermore, our findings did not evidence any significant differences in the spectral profiles in terms of the neonatal customize centile, i.e., AGA (adequate for gestational age), LGA (large for gestational age), or IGUR (intrauterine growth restriction). It is reasonable to assume that maternal human milk oligosaccharide (HMO) production is not or is only minimally influenced by the fetal growth conditions for unknown reasons. This hypothesis may be supported by our metabolomics-based results, confirming once again the importance of this approach in the neonatal field.

HMDB 5.0: the Human Metabolome Database for 2022

The Human Metabolome Database or HMDB (https://hmdb.ca) has been providing comprehensive reference information about human metabolites and their associated biological, physiological and chemical properties since 2007. Over the past 15 years, the HMDB has grown and evolved significantly to meet the needs of the metabolomics community and respond to continuing changes in internet and computing technology. This year's update, HMDB 5.0, brings a number of important improvements and upgrades to the database. These should make the HMDB more useful and more appealing to a larger cross-section of users. In particular, these improvements include: (i) a significant increase in the number of metabolite entries (from 114 100 to 217 920 compounds); (ii) enhancements to the quality and depth of metabolite descriptions; (iii) the addition of new structure, spectral and pathway visualization tools; (iv) the inclusion of many new and much more accurately predicted spectral data sets, including predicted NMR spectra, more accurately predicted MS spectra, predicted retention indices and predicted collision cross section data and (v) enhancements to the HMDB's search functions to facilitate better compound identification. Many other minor improvements and updates to the content, the interface, and general performance of the HMDB website have also been made. Overall, we believe these upgrades and updates should greatly enhance the HMDB's ease of use and its potential applications not only in human metabolomics but also in exposomics, lipidomics, nutritional science, biochemistry and clinical chemistry.

Exploring functional metabolites in preterm infants

AIM

Metabolomics is the study of small molecules that represent the functional end points of cellular reactions that can impact health. Necrotising enterocolitis (NEC) and late onset sepsis (LOS) are the main cause of death in preterm infants surviving the initial days of life.

METHODS

This review will explore and summarise the current literature exploring metabolomics in preterm infants.

RESULTS

There are a relatively limited number of studies investigating metabolomics in preterm infants with NEC and/or LOS and matched controls. Nonetheless, it is evident across longitudinally age-related metabolomic studies that there are significant changes in metabolite profiles post-partum and over the first year of life. Existing studies have reported associations between the metabolite profiles of serum, urine and stool in health and disease in preterm infants. Although some studies have found selected metabolites are associated with disease, the specific metabolites vary from study to study, and larger studies are required. Excitingly, recent work has also begun to untangle how microbially produced metabolites can impact immunoregulation of the infant.

CONCLUSION

Metabolic exploration is an emerging research area with huge potential for developing novel biomarkers and better understanding disease processes in preterm infants.

Urinary Metabolomic Profile of Neonates Born to Women with Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is one of the most frequent pregnancy complications with potential adverse outcomes for mothers and newborns. Its effects on the newborn appear during the neonatal period or early childhood. Therefore, an early diagnosis is crucial to prevent the development of chronic diseases later in adult life. In this study, the urinary metabolome of babies born to GDM mothers was characterized. In total, 144 neonatal and maternal (second and third trimesters of pregnancy) urinary samples were analyzed using targeted metabolomics, combining liquid chromatographic mass spectrometry (LC-MS/MS) and flow injection analysis mass spectrometry (FIA-MS/MS) techniques. We provide here the neonatal urinary concentration values of 101 metabolites for 26 newborns born to GDM mothers and 22 newborns born to healthy mothers. The univariate analysis of these metabolites revealed statistical differences in 11 metabolites. Multivariate analyses revealed a differential metabolic profile in newborns of GDM mothers characterized by dysregulation of acylcarnitines, amino acids, and polyamine metabolism. Levels of hexadecenoylcarnitine (C16:1) and spermine were also higher in newborns of GDM mothers. The maternal urinary metabolome revealed significant differences in butyric, isobutyric, and uric acid in the second and third trimesters of pregnancy. These metabolic alterations point to the impact of GDM in the neonatal period.

Complexity of skeletal muscle degeneration: multi-systems pathophysiology and organ crosstalk in dystrophinopathy

Duchenne muscular dystrophy is a highly progressive muscle wasting disorder due to primary abnormalities in one of the largest genes in the human genome, the DMD gene, which encodes various tissue-specific isoforms of the protein dystrophin. Although dystrophinopathies are classified as primary neuromuscular disorders, the body-wide abnormalities that are associated with this disorder and the occurrence of organ crosstalk suggest that a multi-systems pathophysiological view should be taken for a better overall understanding of the complex aetiology of X-linked muscular dystrophy. This article reviews the molecular and cellular effects of deficiency in dystrophin isoforms in relation to voluntary striated muscles, the cardio-respiratory system, the kidney, the liver, the gastrointestinal tract, the nervous system and the immune system. Based on the establishment of comprehensive biomarker signatures of X-linked muscular dystrophy using large-scale screening of both patient specimens and genetic animal models, this article also discusses the potential usefulness of novel disease markers for more inclusive approaches to differential diagnosis, prognosis and therapy monitoring that also take into account multi-systems aspects of dystrophinopathy. Current therapeutic approaches to combat muscular dystrophy are summarised.

Sex Affects Human Premature Neonates' Blood Metabolome According to Gestational Age, Parenteral Nutrition, and Caffeine Treatment

Prematurity is the leading cause of neonatal deaths and high economic costs; it depends on numerous biological and social factors, and is highly prevalent in males. Several factors can affect the metabolome of premature infants. Accordingly, the aim of the present study was to analyze the role played by gestational age (GA), parenteral nutrition (PN), and caffeine treatment in sex-related differences of blood metabolome of premature neonates through a MS/MS-based targeted metabolomic approach for the detection of amino acids and acylcarnitines in dried blood spots. GA affected the blood metabolome of premature neonates: male and female very premature infants (VPI) diverged in amino acids but not in acylcarnitines, whereas the opposite was observed in moderate or late preterm infants (MLPI). Moreover, an important reduction of metabolites was observed in female VPI fed with PN, suggesting that PN might not satisfy an infant's nutritional needs. Caffeine showed the highest significant impact on metabolite levels of male MLPI. This study proves the presence of a sex-dependent metabolome in premature infants, which is affected by GA and pharmacological treatment (e.g., caffeine). Furthermore, it describes an integrated relationship among several features of physiology and health.

Monitoring Methylmalonic Aciduria by NMR Urinomics

The paper reports on monitoring methylmalonic aciduria (MMA)-specific and non-specific metabolites via NMR urinomics. Five patients have been monitored over periods of time; things involved were diet, medication and occasional episodes of failing to comply with prescribed diets. An extended dataset of targeted metabolites is presented, and correlations with the type of MMA are underlined. A survey of previous NMR studies on MMA is also presented.

Emerging Biomarkers for Prediction and Early Diagnosis of Necrotizing Enterocolitis in the Era of Metabolomics and Proteomics

Necrotizing Enterocolitis (NEC) is a catastrophic disease affecting predominantly premature infants and is characterized by high mortality and serious long-term consequences. Traditionally, diagnosis of NEC is based on clinical and radiological findings, which, however, are non-specific for NEC, thus confusing differential diagnosis of other conditions such as neonatal sepsis and spontaneous intestinal perforation. In addition, by the time clinical and radiological findings become apparent, NEC has already progressed to an advanced stage. During the last three decades, a lot of research has focused on the discovery of biomarkers, which could accurately predict and make an early diagnosis of NEC. Biomarkers used thus far in clinical practice include acute phase proteins, inflammation mediators, and molecules involved in the immune response. However, none has been proven accurate enough to predict and make an early diagnosis of NEC or discriminate clinical from surgical NEC or other non-NEC gastrointestinal diseases. Complexity of mechanisms involved in NEC pathogenesis, which remains largely poorly elucidated, could partly explain the unsatisfactory diagnostic performance of the existing NEC biomarkers. More recently applied technics can provide important insight into the pathophysiological mechanisms underlying NEC but can also aid the detection of potentially predictive, early diagnostic, and prognostic biomarkers. Progress in omics technology has allowed for the simultaneous measurement of a large number of proteins, metabolic products, lipids, and genes, using serum/plasma, urine, feces, tissues, and other biological specimens. This review is an update of current data on emerging NEC biomarkers detected using proteomics and metabolomics, further discussing limitations and future perspectives in prediction and early diagnosis of NEC.