Background: The incidence of chronic kidney disease (CKD) and end-stage kidney disease (ESKD) is increasing worldwide. Hemodialysis (HD) is the mainstay of renal replacement therapy for patients with ESKD. Risk factors associated with late arteriovenous fistula (AVF) failure in HD patients are poorly investigated. Therefore, the aim of this study was to identify factors associated with late AVF failure in HD patients. Methods: Patients with end-stage renal disease (ESRD) who underwent forearm or upper arm AVF angioplasty at Second Affiliated Hospital of Chongqing Medical University between September 2009 and August 2018 were included. Patients were followed up for 36 months. Baseline characteristics were collected using electronic medical records (EMRs). Variables associated with late AVF failure were identified using Cox proportional hazards models. Results: There were 137 patients (64% male, 36% female) included in this study, with 50 (36.5%) experiencing AVF failure. Univariable log-rank analysis showed that age, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), intact parathyroid hormone (iPTH), albumin (ALB), and AVF patency rate were significantly different between patients who did and did not experience AVF failure. Cox regression analysis showed that CRP [P=0.002, hazard ratio (HR) =2.719, 95% confidence interval (CI) for HR: 1.432-5.164], ESR (P=0.030, HR =2.431, 95% CI: 1.088-5.434), iPTH (P=0.013, HR =0.325, 95% CI: 0.133-0.793), and ALB (P=0.040, HR =0.539, 95% CI: 0.299-0.972) were independently associated with AVF failure. Kaplan-Meier survival analysis showed that the cumulative patency rates of AVF at 6, 12, 18, 24, 30, and 36 months were 84%, 74%, 69%, 64%, 64%, and 64%, respectively. Conclusions: CRP, ESR, iPTH, and ALB were associated with AVF failure and should be used as reference in clinical practice.
Benign paroxysmal positional vertigo (BPPV) represents the most frequent cause of peripheral vertigo. In most cases, it is successfully treated using the canalith repositioning procedure, but it is often followed by continuous lightheadedness in the absence of vertigo or nystagmus (residual dizziness, RD). Our aim is to describe the clinical effectiveness and the urine metabolomics profile of treating these patients with polyphenol compound supplementation. We enrolled 30 patients reporting RD after BPPV of the posterior semicircular canal (PSC) successfully treated using the Semont maneuver. Supplementation with a polyphenol compound was administered for 60 days, and patients were evaluated after 30 and 60 days of treatment using self-administered questionnaires (Visual Analog Scales for Dizziness and Nausea, Dizziness Handicap Inventory, DHI) and urine metabolomics analysis performed using 1H-NMR spectroscopy and multivariate followed by univariate analysis. Most patients reported excellent or good efficacy in the treatment of RD with a significant decrease in VAS and DHI values. The metabolomics analysis identified six significant metabolites related to the treatment, namely 1-methylnicotinamide, anserine, hippurate, lysine, methyl succinate and urea, indicating the inflammatory activities and antioxidant properties of the polyphenol compound. These preliminary data suggest that supplementation with a polyphenol compound could induce some metabolic changes that can help in recovery from RD. However, future steps will require confirmation with a more significant cohort of patients and an extension of the metabolomics evaluation to other problems concerning the different clinical aspects of BPPV, such as the high rate of relapse.
Background: Neonatal hypoxic-ischemic brain damage (HIBD) is a clinical syndrome causing brain injury in newborns with obscure etiology. Increasing evidence suggests that ferroptosis plays a role in HIBD. This study aimed to clarify the key ferroptosis-related genes (FRGs) of HIBD, construct a long non-coding RNA-microRNA-messenger RNA (lncRNA-miRNA-mRNA) network, and further investigate the pathogenesis of HIBD. Methods: Gene expression data were downloaded from the Gene Expression Omnibus and FerrDb databases. The differentially expressed lncRNAs and FRGs were screened, and the related miRNAs and mRNAs were predicted. The obtained mRNA was intersected with the differentially expressed FRGs (DE-FRGs) to identify the key DE-FRGs. Cell-type Identification by Estimating Relative Subsets of RNA Transcripts method was applied to analyze the immune cell infiltration level and the relationship between key genes and immune cells. Results: Gene differential expression analysis revealed that 1,178 lncRNAs, 207 miRNAs, and 647 mRNAs were differentially expressed in the blood of HIBD patients in comparison to healthy controls. The correlations of the lncRNAs, miRNAs, and mRNAs lead to the establishment of a competing endogenous RNA (ceRNA) network associated with ferroptosis in HIBD. Further validation using an external dataset and quantitative real-time polymerase chain reaction (PCR) analysis of brain tissues from hypoxic-ischemic encephalopathy rats confirmed the expression patterns of three key genes, including HMOX1, MYCN, and QSOX1. Meanwhile, the three key genes were closely correlated with the infiltration of multiple immune cells and might affect the function of HIBD regulatory genes such as CPT2 and GCK. In addition, drug prediction suggested that four drugs, including cephaeline, emetine, mestranol, and sulmazole, might alleviate HIBD. Conclusions: Our study established a ceRNA network, identified three key genes, and predicted four drugs that are associated with ferroptosis in HIBD, which provides new ideas for the investigation of the disease mechanisms and might facilitate the diagnosis and treatment of the disease.
BACKGROUND: Measurement of serum amino acid (AA) concentrations is important in particular for the diagnosis and monitoring of inborn errors of AA metabolism. To ensure optimal clinical interpretation of AAs, reliable biological variation (BV) data are essential. In the present study, we derived BV data for 22 non-essential, conditionally essential, and essential AAs and assessed differences in BV of AAs related to sex. METHODS: Morning blood samples were drawn from 66 subjects (31 males and 35 females) once a week for 10 consecutive weeks. All samples were analyzed in duplicate using liquid chromatography-tandem mass-spectrometry. The data were assessed for outliers, trends, normality and variance homogeneity analysis prior to estimating within-subject (CVI) and between-subject (CVG) BV. RESULTS: CVI estimates ranged from 9.0 % for histidine (male) to 33.0 % for taurine (male). CVI estimates in males and females were significantly different for all AAs except for aspartic acid, citrulline and phenylalanine, in most cases higher in females than in males. Apart from for arginine, CVG estimates in males and females were similar. CONCLUSIONS: In this highly powered BV study, we provide updated BV estimates for 22 AAs and demonstrate that for most AAs, CVI estimates differ between males and females, with implications for interpretation and use of AAs in clinical practice.
Amino Acids , Sex Characteristics , Female , Humans , Male , Amino Acids/blood
Autism spectrum disorder (ASD) is a neurodevelopmental disorder evolving over the lifetime of individuals. The oral and gut microbial ecosystems are closely connected to each other and the brain and are potentially involved in neurodevelopmental diseases. This narrative review aims to identify all the available evidence emerging from observational studies focused on the role of the oral microbiome in ASD. A literature search was conducted using PubMed and the Cochrane Library for relevant studies published over the last ten years. Overall, in autistic children, the oral microbiota is marked by the abundance of several microbial species belonging to the Proteobacteria phylum and by the depletion of species belonging to the Bacteroidetes phylum. In mouse models, the oral microbiota is marked by the abundance of the Bacteroidetes phylum. Oral dysbiosis in ASD induces changes in the human metabolome, with the overexpression of metabolites closely related to the pathogenesis of ASD, such as acetate, propionate, and indoles, together with the underexpression of butyrate, confirming the central role of tryptophan metabolism. The analysis of the literature evidences the close relationship between oral dysbiosis and autistic core symptoms; the rebuilding of the oral and gut ecosystems by probiotics may significantly contribute to mitigating the severity of ASD symptoms.
Precision medicine is imminent, and metabolomics is one of the main actors on stage. We summarize and discuss the current literature on the clinical application of metabolomic techniques as a possible tool to improve early diagnosis of autism spectrum disorder (ASD), to define clinical phenotypes and to identify co-occurring medical conditions. A review of the current literature was carried out after PubMed, Medline and Google Scholar were consulted. A total of 37 articles published in the period 2010-2022 was included. Selected studies involve as a whole 2079 individuals diagnosed with ASD (1625 males, 394 females; mean age of 10, 9 years), 51 with other psychiatric comorbidities (developmental delays), 182 at-risk individuals (siblings, those with genetic conditions) and 1530 healthy controls (TD). Metabolomics, reflecting the interplay between genetics and environment, represents an innovative and promising technique to approach ASD. The metabotype may mirror the clinical heterogeneity of an autistic condition; several metabolites can be expressions of dysregulated metabolic pathways thus liable of leading to clinical profiles. However, the employment of metabolomic analyses in clinical practice is far from being introduced, which means there is a need for further studies for the full transition of metabolomics from clinical research to clinical diagnostic routine.
Autism Spectrum Disorder , Autistic Disorder , Female , Male , Humans , Autism Spectrum Disorder/diagnosis , Employment , Metabolomics , Phenotype
Importance: Neonatal seizures pose a significant challenge in critical care, and continuous video electroencephalography (cEEG) monitoring holds promise for early detection of seizures. However, large-scale data on the incidence of neonatal seizures and monitoring systems in China are lacking. Objectives: To determine the incidence of neonatal seizures in infants with high risk in China. Design, Setting, and Participants: A large, cross-sectional multicenter study was conducted from January 2017 to December 2018 in the neonatal intensive care units (NICUs) of 7 tertiary medical centers in China. Neonates with high risk were included, and cEEG monitoring was conducted. Data were collected between January 1, 2017, and January 31, 2020. The data were analyzed between January 2021 and January 2022. Main Outcomes and Measures: The incidence of neonatal seizures, categorized by etiology, and seizure burden. Results: A total of 20â¯310 neonates with high risk were included (10â¯495 [51.7%] male; mean [SD] postmenstrual age, 37.7 [3.7] weeks), and seizures were observed in 3423 infants (16.9%). The highest proportion of seizures was attributed to acute neonatal encephalopathy (1448 [42.3%]). The incidence of seizures decreased with postmenstrual age and birth weight, with the highest occurrence observed in neonates with postmenstrual age of less than 28 weeks (237 of 879 [27.0%]) or birth weight of less than 1.0 kg (269 of 914 [29.4%]). Preterm infants had a higher proportion of moderate and severe seizure burdens compared with full-term infants (moderate severity: 248 of 1199 [20.7%] vs 454 of 2224 [20.4%]), but no significant differences were observed in etiology. Seizure burden was highest with genetic syndromes (49 of 188 [26.1%]), central nervous system malformations (33 of 127 [26.0%]), and inborn errors of metabolism (27 of 113 [23.9%]). During hospitalization, 7.8% of neonates with seizures died (267 neonates), with 81.3% of these cases having a moderate or severe seizure burden (217 neonates). Mortality was generally higher in preterm vs full-term infants (98 of 1199 [8.2%] vs 169 of 2224 [7.6%]) and increased with the severity of seizure burden (217 of 267 neonates with moderate or severe burden [81.3%]). Conclusions and Relevance: This cross-sectional study of neonatal seizures underscores the substantial burden seizures pose to high-risk infants with brain injury in China, particularly those who are born prematurely or who have congenital conditions.
Brain Injuries , Epilepsy , Infant, Newborn, Diseases , Infant , Infant, Newborn , Male , Humans , Adult , Female , Cross-Sectional Studies , Infant, Premature , Birth Weight , Incidence , Seizures/diagnosis , Seizures/epidemiology , Seizures/etiology , Brain Injuries/complications , Electroencephalography
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by heterogeneous cognitive, behavioral and communication impairments. Disruption of the gut-brain axis (GBA) has been implicated in ASD although with limited reproducibility across studies. In this study, we developed a Bayesian differential ranking algorithm to identify ASD-associated molecular and taxa profiles across 10 cross-sectional microbiome datasets and 15 other datasets, including dietary patterns, metabolomics, cytokine profiles and human brain gene expression profiles. We found a functional architecture along the GBA that correlates with heterogeneity of ASD phenotypes, and it is characterized by ASD-associated amino acid, carbohydrate and lipid profiles predominantly encoded by microbial species in the genera Prevotella, Bifidobacterium, Desulfovibrio and Bacteroides and correlates with brain gene expression changes, restrictive dietary patterns and pro-inflammatory cytokine profiles. The functional architecture revealed in age-matched and sex-matched cohorts is not present in sibling-matched cohorts. We also show a strong association between temporal changes in microbiome composition and ASD phenotypes. In summary, we propose a framework to leverage multi-omic datasets from well-defined cohorts and investigate how the GBA influences ASD.
Autism Spectrum Disorder , Gastrointestinal Microbiome , Humans , Gastrointestinal Microbiome/genetics , Brain-Gut Axis , Autism Spectrum Disorder/genetics , Autism Spectrum Disorder/metabolism , Cross-Sectional Studies , Bayes Theorem , Reproducibility of Results , Cytokines
Albuminuria standardization is a key issue to produce reliable and equivalent results between laboratories. We investigated whether official recommendations on albuminuria harmonization are followed in the literature. The PubMed database was searched from June 1 to September 26, 2021. The search terms included urine albumin, urine albumin-to-creatinine ratio (uACR), and albuminuria. A total of 159 articles were considered eligible; 50.9â¯% reported the type of urine collection. Specifically, 58.1â¯% collected a random spot urine specimen, 21â¯% collected a first morning void, and 6.2â¯% collected a 24-h specimen. Overall, 15â¯% of articles reported data on sample shipping, storage, and centrifugation and 13.3â¯% mentioned the preanalytical phase without any data on albuminuria. The method for albuminuria was properly described in 31.4â¯% of articles; of these, 54.9â¯% used immunological methods, and 8.9â¯% contained errors or missing data. Most articles (76.7â¯%) expressed test results as albuminuria-to-creatininuria ratio. Different decision levels were utilized in 130 articles; of these, 36â¯% used a decision level of ≤30â¯mg/g creatininuria and 23.7â¯% used three decision levels (≤30, 30-300, and ≥300â¯mg/g). The failure to follow guidelines on albuminuria harmonization was mainly found in the preanalytical phase. The poor awareness of the importance of preanalytical steps on test result may be a possible explanation.
Albuminuria , Urinalysis , Humans , Albuminuria/diagnosis , Albuminuria/urine , Urinalysis/methods , Urine Specimen Collection , Laboratories , Albumins , Creatinine/urine
The inborn errors of metabolism (IEMs or Inherited Metabolic Disorders) are a heterogeneous group of diseases caused by a deficit of some specific metabolic pathways. IEMs may present with multiple overlapping symptoms, sometimes difficult delayed diagnosis and postponed therapies. Additionally, many IEMs are not covered in newborn screening and the diagnostic profiling in the metabolic laboratory is indispensable to reach a correct diagnosis. In recent years, Metabolomics helped to obtain a better understanding of pathogenesis and pathophysiology of IEMs, by validating diagnostic biomarkers, discovering new specific metabolic patterns and new IEMs itself. The expansion of Metabolomics in clinical biochemistry and laboratory medicine has brought these approaches in clinical practice as part of newborn screenings, as an exam for differential diagnosis between IEMs, and evaluation of metabolites in follow up as markers of severity or therapies efficacy. Lastly, several research groups are trying to profile metabolomics data in platforms to have a holistic vision of the metabolic, proteomic and genomic pathways of every single patient. In 2018 this team has made a review of literature to understand the value of Metabolomics in IEMs. Our review offers an update on use and perspectives of metabolomics in IEMs, with an overview of the studies available from 2018 to 2022.
Perinatal nutrition is a key factor related to the Developmental Origin of Health and Disease hypothesis, which states that each and every event that happens during the periconceptional period and pregnancy can affect the health status of an individual. Metabolomics can be a very useful tool for gathering information about the effect of perinatal nutrition on both mothers and newborn infants. This non-systematic review focuses on the main metabolites detected by this technique, with regard to gestational diabetes, intrauterine growth restriction and breast milk. Conclusion. Nutrition, metabolome and microbiome interactions are gaining interest in the scientific community.
Diabetes, Gestational , Metabolomics , Infant, Newborn , Infant , Pregnancy , Female , Humans , Milk, Human/metabolism , Metabolome , Mothers
Microbial secondary infections can contribute to an increase in the risk of mortality in COVID-19 patients, particularly in case of severe diseases. In this study, we collected and evaluated the clinical, laboratory and microbiological data of COVID-19 critical ill patients requiring intensive care (ICU) to evaluate the significance and the prognostic value of these parameters. One hundred seventy-eight ICU patients with severe COVID-19, hospitalized at the S. Francesco Hospital of Nuoro (Italy) in the period from March 2020 to May 2021, were enrolled in this study. Clinical data and microbiological results were collected. Blood chemistry parameters, relative to three different time points, were analyzed through multivariate and univariate statistical approaches. Seventy-four percent of the ICU COVID-19 patients had a negative outcome, while 26% had a favorable prognosis. A correlation between the laboratory parameters and days of hospitalization of the patients was observed with significant differences between the two groups. Moreover, Staphylococcus aureus, Enterococcus faecalis, Candida spp, Pseudomonas aeruginosa and Klebsiella pneumoniae were the most frequently isolated microorganisms from all clinical specimens. Secondary infections play an important role in the clinical outcome. The analysis of the blood chemistry tests was found useful in monitoring the progression of COVID-19.
COVID-19 , Coinfection , Humans , SARS-CoV-2 , Pandemics , Intensive Care Units
Otorhinolaryngology (Ear, Nose and Throat-ENT) focuses on inflammatory, immunological, infectious, and neoplastic disorders of the head and neck and on their medical and surgical therapy. The fields of interest of this discipline are the ear, the nose and its paranasal sinuses, the oral cavity, the pharynx, the larynx, and the neck. Besides surgery, there are many other diagnostic aspects of ENT such as audiology and Vestibology, laryngology, phoniatrics, and rhinology. A new advanced technology, named metabolomics, is significantly impacting the field of ENT. All the "omics" sciences, such as genomics, transcriptomics, and proteomics, converge at the level of metabolomics, which is considered the integration of all "omics." Its application will change the way several of ENT disorders are diagnosed and treated. This review highlights the power of metabolomics, including its pitfalls and promise, and several of its most relevant applications in ENT to provide a basic understanding of the metabolites associated with these districts. In particular, the attention has been focused on different heterogeneous diseases, from head and neck cancer to allergic rhinitis, hearing loss, obstructive sleep apnea, noise trauma, sinusitis, and Meniere's disease. In conclusion, metabolomics study indicates a "fil rouge" that links these pathologies to improve three aspects of patient care: diagnostics, prognostics, and therapeutics, which in one word is defined as precision medicine.
This Special Issue aimed to collect studies based on clinical applications of metabolomics in human disease [...].
The integrity of the gastrointestinal tract structure and function is seriously compromised by two pathological conditions sharing, at least in part, several pathogenetic mechanisms: inflammatory bowel diseases (IBD) and coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. IBD and COVID-19 are marked by gut inflammation, intestinal barrier breakdown, resulting in mucosal hyperpermeability, gut bacterial overgrowth, and dysbiosis together with perturbations in microbial and human metabolic pathways originating changes in the blood and fecal metabolome. This review compared the most relevant metabolic and microbial alterations reported from the literature in patients with IBD with those in patients with COVID-19. In both diseases, gut dysbiosis is marked by the prevalence of pro-inflammatory bacterial species and the shortfall of anti-inflammatory species; most studies reported the decrease in Firmicutes, with a specific decrease in obligately anaerobic producers short-chain fatty acids (SCFAs), such as Faecalibacterium prausnitzii. In addition, Escherichia coli overgrowth has been observed in IBD and COVID-19, while Akkermansia muciniphila is depleted in IBD and overexpressed in COVID-19. In patients with COVID-19, gut dysbiosis continues after the clearance of the viral RNA from the upper respiratory tract and the resolution of clinical symptoms. Finally, we presented and discussed the impact of gut dysbiosis, inflammation, oxidative stress, and increased energy demand on metabolic pathways involving key metabolites, such as tryptophan, phenylalanine, histidine, glutamine, succinate, citrate, and lipids.
Chronic pain affects almost 20% of the European adult population and it significantly reduces patients' quality of life. Chronic pain is considered a multidimensional experience determined by the interaction of several genetic and environmental factors. The effect of specific genetic contributions is often unclear, and the interpretation of the results from studies focused on genetic influences on pain has been complicated by the existence of multiple pain phenotypes. A step forward from genetics could be given by the application of metabolomics and microbiomics tools. Metabolomics is a powerful approach for hypothesis generation in biology, and it aims to analyze low molecular weight compounds, either metabolic intermediates or metabolic end-products, resulting from human or microbial metabolism. Microbiomics is a fast-growing field in which all the microbes are examined together, and as a result, its perturbation may indicate the development of chronic diseases. By applying these methodologies for the study of chronic pain, several differences have been identified. The alteration of the choline-PAF pathway is an intriguing finding recognized by several groups. In our opinion, metabolomics and microbiomics techniques will allow significant progress into the medical field. Patients may benefit from the possibility of being stratified and classified based on their metabolic and microbial profile, which, in the next future, may lead to personalized therapy.
Several metabolomics-based studies have provided evidence that autistic subjects might share metabolic abnormalities with gut microbiota dysbiosis and alterations in gut mucosal permeability. Our aims were to explore the most relevant metabolic perturbations in a group of autistic children, compared with their healthy siblings, and to investigate whether the increased intestinal permeability may be mirrored by specific metabolic perturbations. We enrolled 13 autistic children and 14 unaffected siblings aged 2-12 years; the evaluation of the intestinal permeability was estimated by the lactulose:mannitol test. The urine metabolome was investigated by proton nuclear magnetic resonance (1H-NMR) spectroscopy. The lactulose:mannitol test unveiled two autistic children with altered intestinal permeability. Nine metabolites significantly discriminated the urine metabolome of autistic children from that of their unaffected siblings; however, in the autistic children with increased permeability, four additional metabolites-namely, fucose, phenylacetylglycine, nicotinurate, and 1-methyl-nicotinamide, strongly discriminated their urine metabolome from that of the remaining autistic children. Our preliminary data suggest the presence of a specific urine metabolic profile associated with the increase in intestinal permeability.
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.
Necrotizing enterocolitis (NEC) is among the most relevant gastrointestinal diseases affecting mostly prematurely born infants with low birth weight. While intestinal dysbiosis has been proposed as one of the possible factors involved in NEC pathogenesis, the role of the gut microbiota remains poorly understood. In this study, the gut microbiota of preterm infants was explored to highlight differences in the composition between infants affected by NEC and infants prior to NEC development. A large-scale gut microbiome analysis was performed, including 47 shotgun sequencing data sets generated in the framework of this study, along with 124 retrieved from publicly available repositories. Meta-analysis led to the identification of preterm community state types (PT-CSTs), which recur in healthy controls and NEC infants. Such analyses revealed an overgrowth of a range of opportunistic microbial species accompanying the loss of gut microbial biodiversity in NEC subjects. Moreover, longitudinal insights into preterm infants prior to NEC development indicated Clostridium neonatale and Clostridium perfringens species as potential biomarkers for predictive early diagnosis of this disease. Furthermore, functional investigation of the enzymatic reaction profiles associated with pre-NEC condition suggested DL-lactate as a putative metabolic biomarker for early detection of NEC onset. IMPORTANCE Necrotizing enterocolitis (NEC) is a severe gastrointestinal disease occurring predominantly in premature infants whose etiology is still not fully understood. In this study, the analysis of infant fecal samples through shotgun metagenomics approaches revealed a marked reduction of the intestinal (bio)diversity and an overgrowth of (opportunistic) pathogens associated with the NEC development. In particular, dissection of the infant's gut microbiome before NEC diagnosis highlighted the potential involvement of Clostridium genus members in the progression of NEC. Remarkably, our analyses highlighted a gastrointestinal DL-lactate accumulation among NEC patients that might represent a novel potential functional biomarker for the early diagnosis of NEC.
Clostridium perfringens/isolation & purification , Clostridium/isolation & purification , Dysbiosis/microbiology , Enterocolitis, Necrotizing/microbiology , Gastrointestinal Microbiome/physiology , Infant, Premature, Diseases/microbiology , Biomarkers/analysis , Clostridium/genetics , Clostridium perfringens/genetics , Enterocolitis, Necrotizing/pathology , Feces/microbiology , Humans , Infant, Low Birth Weight/metabolism , Infant, Newborn , Infant, Premature , Intestines/microbiology , Lactic Acid/analysis , Metagenome/genetics
Objective: To investigate changes in the urine metabolome of very low birth weight preterm newborns with necrotizing enterocolitis (NEC) and feed intolerance, we conducted a longitudinal study over the first 2 months of life. The metabolome of NEC newborns was compared with two control groups that did not develop NEC: the first one included preterm babies with feed intolerance, while the second one preterm babies with good feed tolerance. Methods: Newborns developing NEC within the 3 weeks of life were identified as early onset NEC, while the remaining as late onset NEC. Case-control matching was done according to the gestational age (±1 week), birth weight (± 200 g), and postnatal age. A total of 96 urine samples were collected and analyzed. In newborns with NEC, samples were collected before, during and after the diagnosis over the first 2 months of life, while in controls samples were collected as close as possible to the postnatal age of newborns with NEC. Proton nuclear magnetic resonance (1H NMR) spectroscopy was used for metabolomic analysis. Data were analyzed by univariate and multivariate statistical analysis. Results: In all the preterm newborns, urine levels of betaine, glycine, succinate, and citrate positively correlated with postnatal age. Suberate and lactate correlated with postnatal age in preterms with NEC and in controls with food intolerance, while N,N-dimethylglycine (N,N-DMG) correlated only in controls with good digestive tolerance. Preterm controls with feed intolerance showed a progressive significant decrease of N-methylnicotinamide and carnitine. Lactate, betaine, myo-inositol, urea, creatinine, and N,N-dimethylglycine discriminated late-onset NEC from controls with good feed tolerance. Conclusion: Our findings are discussed in terms of contributions from nutritional and clinical managements of patients and gut microbiota.
