1H NMR-based metabolite profiling for biomarker identification

Silva, Ruan A.; Pereira, Táyla C.S.; Souza, Alzenir R.; Ribeiro, Paulo R.

doi:10.1016/j.cca.2019.11.015

Cited by 42 publications

(19 citation statements)

References 94 publications

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“…The inherent limitation of NMR is the low sensitivity compared to MS but there are emerging new NMR technologies that suggest a huge improvement in the NMR spectroscopy [21]. In order to highlight one of the NMR-approaches, quantitative proton 1 H-NMR is the most useful NMR-based platform for metabolomics and has been successfully applied to early diagnostic and prognostic purposes [22,23]. The most popular biological fluids used in metabolomics are plasma, serum, urine and feces, while other fluids and tissues are not yet well explored.…”

Section: Introductionmentioning

confidence: 99%

Detection of Early Disease Risk Factors Associated with Metabolic Syndrome: A New Era with the NMR Metabolomics Assessment

et al. 2020

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The metabolic syndrome is a multifactorial disease developed due to accumulation and chronification of several risk factors associated with disrupted metabolism. The early detection of the biomarkers by NMR spectroscopy could be helpful to prevent multifactorial diseases. The exposure of each risk factor can be detected by traditional molecular markers but the current biomarkers have not been enough precise to detect the primary stages of disease. Thus, there is a need to obtain novel molecular markers of pre-disease stages. A promising source of new molecular markers are metabolomics standing out the research of biomarkers in NMR approaches. An increasing number of nutritionists integrate metabolomics into their study design, making nutrimetabolomics one of the most promising avenues for improving personalized nutrition. This review highlight the major five risk factors associated with metabolic syndrome and related diseases including carbohydrate dysfunction, dyslipidemia, oxidative stress, inflammation, and gut microbiota dysbiosis. Together, it is proposed a profile of metabolites of each risk factor obtained from NMR approaches to target them using personalized nutrition, which will improve the quality of life for these patients.

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Section: Introductionmentioning

confidence: 99%

Detection of Early Disease Risk Factors Associated with Metabolic Syndrome: A New Era with the NMR Metabolomics Assessment

et al. 2020

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“…Complex aetiologies and atypical symptoms pose very large challenges to the early diagnosis of ASD. Urinary 1 H-NMR analysis provides a fast and comprehensive assessment to detect potential biomarkers of ASD [28]. Our study was based on the 1 H-NMR analysis of urine samples from ASD and control groups to identify candidate metabolites and associated pathogenic mechanisms.…”

Section: Discussionmentioning

confidence: 99%

Differential Metabolites in Chinese Autistic Children: A Multi-Centre Study Based on Urinary 1H-NMR Metabolomics Analysis

Zhou

et al. 2020

Preprint

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Background: Autism spectrum disorder (ASD) is a group of early-onset neurodevelopmental disorders. However, there is no valuable biomarker for the early diagnosis of ASD. Our large-scale and multi-centre study aims to identify metabolic variations between ASD and healthy children and to investigate differential metabolites and associated pathogenic mechanisms.Methods: 117 autistic children and 119 healthy children were recruited from research centres of 7 cities. Urine samples were assayed by 1H-NMR metabolomics analysis to detect metabolic variations. Multivariate statistical analysis, including principal component analysis (PCA) and orthogonal projection to latent structure discriminant analysis (OPLS-DA), as well as univariate analysis were used to assess differential metabolites between the ASD and control groups. The differential metabolites were further analysed by receiver operating characteristics (ROC) curve analysis and metabolic pathways analysis.Results: Compared with the control group, the ASD group showed higher levels of glycine, guanidinoacetic acid, creatine, hydroxyphenylacetylglycine, phenylacetylglycine and formate and lower levels of 3-aminoisobutanoic acid, alanine, taurine, creatinine, hypoxanthine and N-methylnicotinamide. ROC curve showed relatively significant diagnostic values for hypoxanthine (area under the curve (AUC) = 0.657, 95% CI 0.588 to 0.726), creatinine (AUC = 0.639, 95% CI 0.569 to 0.709), creatine (AUC = 0.623, 95% CI 0.552 to 0.694), N-methylnicotinamide (AUC = 0.595, 95% CI 0.523 to 0.668) and guanidinoacetic acid (AUC = 0.574, 95% CI 0.501 to 0.647) in the ASD group. Combining the metabolites creatine, creatinine and hypoxanthine, the AUC of the ROC curve reached 0.720 (95% CI 0.659 to 0.777). Significantly altered metabolite pathways associated with differential metabolites were glycine, serine and threonine metabolism, arginine and proline metabolism, and taurine and hypotaurine metabolism.Limitations: Due to the restriction of research centres, inconsistent urine collection times may have affected the quality of metabolic analyses. Moreover, it is necessary to compare metabolite levels that vary with ASD severity to better clarify the pathogenesis of ASD.Conclusions: Urinary amino acid metabolites significantly altered in children with ASD. Amino acid metabolic pathways might play important roles in the pathogenic mechanisms of ASD.Clinical Trial registration: National Study on Autism Spectrum Disorder in China (NCT02200679). Registered July 24, 2014. https://www.clinicaltrials.gov/ct2/show/NCT02200679

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“…With appropriate application of qualitative analysis the molecular structure of unknown compound can be unambiguously determinate. Spectral libraries for comparison with known molecules are also available 12 . The most common NMR technique used in metabolomic analysis is based on measuring of proton ( 1 H) and carbon ( 13 C) NMR spectra.…”

Section: Nuclear Magnetic Resonance Spectroscopymentioning

confidence: 99%

Metabolomic analysis in ophthalmology

Nazifova-Tasinova

Radeva

Galunska

et al. 2020

Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub

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Modern science takes into account phenotype complexity and establishes approaches to track changes on every possible level. Many "omics" studies have been developed over the last decade. Metabolomic analysis enables dynamic measurement of the metabolic response of a living system to a variety of stimuli or genetic modifications. Important targets of metabolomics is biomarker development and translation to the clinic for personalized diagnosis and a greater understanding of disease pathogenesis. The current review highlights the major aspects of metabolomic analysis and its applications for the identification of relevant predictive, diagnostic and prognostic biomarkers for some ocular diseases including dry eye, keratoconus, retinal diseases, macular degeneration, and glaucoma. To date, possible biomarker candidates for dry eye disease are lipid metabolites and androgens, for keratoconus cytokeratins, urea, citrate cycle, and oxidative stress metabolites. Palmitoylcarnitine, sphingolipids, vitamin D related metabolites, and steroid precursors may be used for distinguishing glaucoma patients from healthy controls. Dysregulation of amino acid and carnitine metabolism is critical in the development and progression of diabetic retinopathy. Further work is needed to discover and validate metabolic biomarkers as a powerful tool for understanding the molecular mechanisms of ocular diseases, to provide knowledge on their etiology and pathophysiology and opportunities for personalized clinical intervention at an early stage.

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1H NMR-based metabolite profiling for biomarker identification

Cited by 42 publications

References 94 publications

Detection of Early Disease Risk Factors Associated with Metabolic Syndrome: A New Era with the NMR Metabolomics Assessment

Detection of Early Disease Risk Factors Associated with Metabolic Syndrome: A New Era with the NMR Metabolomics Assessment

Differential Metabolites in Chinese Autistic Children: A Multi-Centre Study Based on Urinary 1H-NMR Metabolomics Analysis

Metabolomic analysis in ophthalmology

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