Metabolic network analysis of pre-ASD newborns and 5-year-old children with autism spectrum disorder.

Classical metabolomic and new metabolic network methods were used to study the developmental features of autism spectrum disorder (ASD) in newborns (n = 205) and 5-year-old children (n = 53). Eighty percent of the metabolic impact in ASD was caused by 14 shared biochemical pathways that led to decreased anti-inflammatory and antioxidant defenses, and to increased physiologic stress molecules like lactate, glycerol, cholesterol, and ceramides. CIRCOS plots and a new metabolic network parameter, V ° net, revealed differences in both the kind and degree of network connectivity. Of 50 biochemical pathways and 450 polar and lipid metabolites examined, the developmental regulation of the purine network was most changed. Purine network hub analysis revealed a 17-fold reversal in typically developing children. This purine network reversal did not occur in ASD. These results revealed previously unknown metabolic phenotypes, identified new developmental states of the metabolic correlation network, and underscored the role of mitochondrial functional changes, purine metabolism, and purinergic signaling in autism spectrum disorder.

Metabolic Connectome and Its Role in the Prediction, Diagnosis, and Treatment of Complex Diseases.

The interconnectivity of advanced biological systems is essential for their proper functioning. In modern connectomics, biological entities such as proteins, genes, RNA, DNA, and metabolites are often represented as nodes, while the physical, biochemical, or functional interactions between them are represented as edges. Among these entities, metabolites are particularly significant as they exhibit a closer relationship to an organism's phenotype compared to genes or proteins. Moreover, the metabolome has the ability to amplify small proteomic and transcriptomic changes, even those from minor genomic changes. Metabolic networks, which consist of complex systems comprising hundreds of metabolites and their interactions, play a critical role in biological research by mediating energy conversion and chemical reactions within cells. This review provides an introduction to common metabolic network models and their construction methods. It also explores the diverse applications of metabolic networks in elucidating disease mechanisms, predicting and diagnosing diseases, and facilitating drug development. Additionally, it discusses potential future directions for research in metabolic networks. Ultimately, this review serves as a valuable reference for researchers interested in metabolic network modeling, analysis, and their applications.

Metabolic features of treatment-refractory major depressive disorder with suicidal ideation.

Peripheral blood metabolomics was used to gain chemical insight into the biology of treatment-refractory Major Depressive Disorder with suicidal ideation, and to identify individualized differences for personalized care. The study cohort consisted of 99 patients with treatment-refractory major depressive disorder and suicidal ideation (trMDD-SI n = 52 females and 47 males) and 94 age- and sex-matched healthy controls (n = 48 females and 46 males). The median age was 29 years (IQR 22-42). Targeted, broad-spectrum metabolomics measured 448 metabolites. Fibroblast growth factor 21 (FGF21) and growth differentiation factor 15 (GDF15) were measured as biomarkers of mitochondrial dysfunction. The diagnostic accuracy of plasma metabolomics was over 90% (95%CI: 0.80-1.0) by area under the receiver operator characteristic (AUROC) curve analysis. Over 55% of the metabolic impact in males and 75% in females came from abnormalities in lipids. Modified purines and pyrimidines from tRNA, rRNA, and mRNA turnover were increased in the trMDD-SI group. FGF21 was increased in both males and females. Increased lactate, glutamate, and saccharopine, and decreased cystine provided evidence of reductive stress. Seventy-five percent of the metabolomic abnormalities found were individualized. Personalized deficiencies in CoQ10, flavin adenine dinucleotide (FAD), citrulline, lutein, carnitine, or folate were found. Pathways regulated by mitochondrial function dominated the metabolic signature. Peripheral blood metabolomics identified mitochondrial dysfunction and reductive stress as common denominators in suicidal ideation associated with treatment-refractory major depressive disorder. Individualized metabolic differences were found that may help with personalized management.

LC-MS/MS Analysis of Reaction Products of Arginine/Methylarginines with Methylglyoxal/Glyoxal.

Methylglyoxal (MGO) and glyoxal (GO) are toxic α-dicarbonyl compounds that undergo reactions with amine containing molecules such as proteins and amino acids and result in the formation of advanced glycation end products (AGEs). This study aimed at investigating the reactivity of arginine (Arg) or dimethylarginine (SDMA or ADMA) with MGO or GO. The solutions of arginine and MGO or GO were prepared in PBS buffer (pH 7.4) and incubated at 37 °C. Direct electrospray ionization-high-resolution mass spectrometry (ESI-HRMS) analysis of the reaction mixture of Arg and MGO revealed the formation of Arg-MGO (1:1) and Arg-2MGO (1:2) products and their corresponding dehydrated products. Further liquid chromatography (LC)-MS analyses revealed the presence of isomeric products in each 1:1 and 1:2 product. The [M + H]+ of each isomeric product was subjected to MS/MS experiments for structural elucidation. The MS/MS spectra of some of the products showed a distinct structure indicative fragment ions, while others showed similar data. The types of products formed by the arginines with GO were also found to be similar to that of MGO. The importance of the guanidine group in the formation of the AGEs was reflected in similar incubation experiments with ADMA and SDMA. The structures of the products were proposed based on the comparison of the retention times and HRMS and MS/MS data interpretation, and some of them were confirmed by drawing analogy to the data reported in the literature.

Assessment of uremic toxins in advanced chronic kidney disease patients on maintenance hemodialysis by LC-ESI-MS/MS.

INTRODUCTION: In the advanced stage of chronic kidney disease (CKD), electrolytes, fluids, and metabolic wastes including various uremic toxins, accumulate at high concentrations in the patients' blood. Hemodialysis (HD) is the conventional procedure used worldwide to remove metabolic wastes. The creatinine and urea levels have been routinely monitored to estimate kidney function and effectiveness of the HD process. This study, first from in Indian perspective, aimed at the identification and quantification of major uremic toxins in CKD patients on maintenance HD (PRE-HD), and compared with the healthy controls (HC) as well as after HD (POST-HD). OBJECTIVES: The study mainly focused on the identification of major uremic toxins in Indian perspective and the quantitative analysis of indoxyl sulfate and p-cresol sulfate (routinely targeted uremic toxins), and phenyl sulfate, catechol sulfate, and guaiacol sulfate (targeted for the first time), apart from creatinine and urea in PRE-HD, POST-HD, and HC groups. METHODS: Blood samples were collected from 90 HD patients (both PRE-HD and POST-HD), and 74 HCs. The plasma samples were subjected to direct ESI-HRMS and LC/HRMS for untargeted metabolomics and LC-MS/MS for quantitative analysis. RESULTS: Various known uremic toxins, and a few new and unknown peaks were detected in PRE-HD patients. The p-cresol sulfate and indoxyl sulfate were dominant in PRE-HD, the concentrations of phenyl sulfate, catechol sulfate, and guaiacol sulfate were about 50% of that of indoxyl sulfate. Statistical evaluation on the levels of targeted uremic toxins in PRE-HD, POST-HD, and HC groups showed a significant difference among the three groups. The dialytic clearance of indoxyl sulfate and p-cresol sulfate was found to be < 35%, while that of the other three sulfates was 50-58%. CONCLUSION: LC-MS/MS method was developed and validated to evaluate five major uremic toxins in CKD patients on HD. The levels of the targeted uremic toxins could be used to assess kidney function and the effectiveness of HD.

Historical biomonitoring of pollution trends in the North Pacific using archived samples from the Continuous Plankton Recorder Survey.

First started in 1931, the Continuous Plankton Recorder (CPR) Survey is the longest-running and most geographically extensive marine plankton sampling program in the world. This pilot study investigates the feasibility of biomonitoring the spatiotemporal trends of marine pollution using archived CPR samples from the North Pacific. We selected specimens collected from three different locations (British Columbia Shelf, Northern Gulf of Alaska, and Aleutian Shelf) in the North Pacific between 2002 and 2020. Comprehensive profiling of the plankton chemical exposome was conducted using liquid and gas chromatography coupled with tandem mass spectrometry (LC-MS/MS and GC-MS/MS). Our results show that phthalates, plasticizers, persistent organic pollutants (POPs), pesticides, pharmaceuticals, and personal care products were present in the plankton exposome, and that many of these pollutants have decreased in amount over the last two decades, which was most pronounced for tri-n-butyl phosphate. In addition, the plankton exposome differed significantly by regional human activities, with the most polluted samples coming from the nearshore area. Exposome-wide association analysis revealed that bioaccumulation of environmental pollutants was highly correlated with the biomass of different plankton taxa. Overall, this study demonstrates that exposomic analysis of archived samples from the CPR Survey is effective for long-term biomonitoring of the spatial and temporal trends of environmental pollutants in the marine environment.

Metabolomic and exposomic biomarkers of risk of future neurodevelopmental delay in human milk.

BACKGROUND: The chemical composition of human milk has long-lasting effects on brain development. We examined the prognostic value of the human milk metabolome and exposome in children with the risk of neurodevelopmental delay (NDD). METHODS: This retrospective cohort study included 82 mother-infant pairs (40 male and 42 female infants). A total of 59 milk samples were from mothers with typically developing children and 23 samples were from mothers of children at risk. Milk samples were collected before 9 months of age (4.6 ± 2.5 months, mean ± SD). Neurocognitive development was assessed by maternal report at 14.2 ± 3.1 months using the Ages and Stages Questionnaires-2. RESULTS: Metabolome and exposome profiling identified 453 metabolites and 61 environmental chemicals in milk. Machine learning tools identified changes in deoxysphingolipids, phospholipids, glycosphingolipids, plasmalogens, and acylcarnitines in the milk of mothers with children at risk for future delay. A predictive classifier had a diagnostic accuracy of 0.81 (95% CI: 0.66-0.96) for females and 0.79 (95% CI: 0.62-0.94) for males. CONCLUSIONS: Once validated in larger studies, the chemical analysis of human milk might be added as an option in well-baby checks to help identify children at risk of NDD before the first symptoms appear. IMPACT: Maternal milk for infants sampled before 9 months of age contained sex-specific differences in deoxysphingolipids, sphingomyelins, plasmalogens, phospholipids, and acylcarnitines that predicted the risk of neurodevelopmental delay at 14.2 months of age. Once validated, this early biosignature in human milk might be incorporated into well-baby checks and help to identify infants at risk so early interventions might be instituted before the first symptoms appear.