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Free-amino acid metabolic profiling of visceral adipose tissue from obese subjects.
Piro, MC, Tesauro, M, Lena, AM, Gentileschi, P, Sica, G, Rodia, G, Annicchiarico-Petruzzelli, M, Rovella, V, Cardillo, C, Melino, G, et al
Amino acids. 2020;(8):1125-1137
Abstract
Interest in adipose tissue pathophysiology and biochemistry have expanded considerably in the past two decades due to the ever increasing and alarming rates of global obesity and its critical outcome defined as metabolic syndrome (MS). This obesity-linked systemic dysfunction generates high risk factors of developing perilous diseases like type 2 diabetes, cardiovascular disease or cancer. Amino acids could play a crucial role in the pathophysiology of the MS onset. Focus of this study was to fully characterize amino acids metabolome modulations in visceral adipose tissues (VAT) from three adult cohorts: (i) obese patients (BMI 43-48) with metabolic syndrome (PO), (ii) obese subjects metabolically well (O), and (iii) non obese individuals (H). 128 metabolites identified as 20 protein amino acids, 85 related compounds and 13 dipeptides were measured by ultrahigh performance liquid chromatography-tandem mass spectroscopy (UPLC-MS/MS) and gas chromatography-/mass spectrometry GC/MS, in visceral fat samples from a total of 53 patients. Our analysis indicates a probable enhanced BCAA (leucine, isoleucine, valine) degradation in both VAT from O and PO subjects, while levels of their oxidation products are increased. Also PO and O VAT samples were characterized by: elevated levels of kynurenine, a catabolic product of tryptophan and precursor of diabetogenic substances, a significant increase of cysteine sulfinic acid levels, a decrease of 1-methylhistidine, and an up regulating trend of 3-methylhistidine levels. We hope this profiling can aid in novel clinical strategies development against the progression from obesity to metabolic syndrome.
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Detection of Early Disease Risk Factors Associated with Metabolic Syndrome: A New Era with the NMR Metabolomics Assessment.
Hernandez-Baixauli, J, Quesada-Vázquez, S, Mariné-Casadó, R, Gil Cardoso, K, Caimari, A, Del Bas, JM, Escoté, X, Baselga-Escudero, L
Nutrients. 2020;(3)
Abstract
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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Identification of the metabolic fingerprints in women with polycystic ovary syndrome using the multiplatform metabolomics technique.
Buszewska-Forajta, M, Rachoń, D, Stefaniak, A, Wawrzyniak, R, Konieczna, A, Kowalewska, A, Markuszewski, MJ
The Journal of steroid biochemistry and molecular biology. 2019;:176-184
Abstract
In addition to chronic anovulation and clinical signs of hyperandrogenism women with polycystic ovary syndrome (PCOS) are insulin resistant and therefore, develop central obesity with its long term consequences such as dyslipidaemia, hypertension, atherosclerosis and type 2 diabetes mellitus (T2DM), which all lead to the development of cardiovascular disease (CVD). Due to the polysymptomatic nature of this syndrome and lack of consensus on its diagnostic criteria there is a strong need of finding a reliable biochemical or molecular marker, which would facilitate making the accurate diagnosis of PCOS. Therefore, the aim of our study was to perform a metabolomics analysis with the use of two complementary techniques: gas chromatography and liquid chromatography coupled with mass spectrometry, of the serum samples from women with PCOS (n = 30) and to compare them with healthy age and BMI matched controls (n = 30). Obtained results were subjected to one-dimensional statistical analysis (student's t-test or its non-parametric equivalent U Mann-Whitney test) and multivariate statistical analysis (the principal component analysis [PCA], variable importance into projection [VIP] and selectivity ratio [SR]). The results of our study showed that women with PCOS are characterised by metabolic disorders of the amino acids, carbohydrates, steroid hormones, lipids and purines. Compared to control subjects, women with PCOS had increased serum levels of phospholipids, aromatic amino acids, organic acids, hormones and sphinganine and decreased total cholesterol. Among the identified compounds, total cholesterol, phenylalanine and dehydroepiandrosterone sulfate, uric and lactic acid were the compounds with the strongest discriminating power.
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Linking of metabolomic biomarkers with cardiometabolic health in Chinese population.
Sun, L, Li, H, Lin, X
Journal of diabetes. 2019;(4):280-291
Abstract
Due to rapid nutrition transitions, the prevalence of cardiometabolic diseases, such as metabolic syndrome, type 2 diabetes, and cardiovascular diseases, has been increasing at an alarming rate in the Chinese population. Moreover, Asians, including Chinese, have been hypothesized to have a higher susceptibility to cardiometabolic diseases than Caucasians. Early prediction and prevention are key to controlling this epidemic trend; to this end, the identification of novel biomarkers is critical to reflect environmental exposure, as well as to reveal endogenous metabolic and pathophysiologic mechanisms. The emerging "omics" technologies, especially metabolomics, offer a unique opportunity to provide novel signatures or fingerprints to understand the effects of genetic and non-genetic factors on cardiometabolic health. During the past two decades, metabolomic approaches have been increasingly used in various epidemiological studies, primarily in Western populations. Although the field is still in its early stages, some studies have tried to identify novel compounds or confirm their metabolites and associations with cardiometabolic diseases in Chinese populations, including amino acids, fatty acids, acylcarnitines and other metabolites. Despite major efforts to discover novel biomarkers for disease prediction or intervention, the limits in current study design, analytical platforms, and data processing approaches are challenges in metabolomic research worldwide. Therefore, future research with more advanced technologies, rigorous study designs, standardized detection and analytic approaches, and integrated data from multiomics approaches are essential to evaluate the feasibility of using metabolomics in clinical settings. Finally, the functional roles and underlying biological mechanisms of metabolomic biomarkers should be elucidated by future mechanistic research.
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Nutrigenomics: Opportunities & challenges for public health nutrition.
Reddy, VS, Palika, R, Ismail, A, Pullakhandam, R, Reddy, GB
The Indian journal of medical research. 2018;(5):632-641
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Abstract
The hierarchical information flow through DNA-RNA-protein-metabolite collectively referred to as 'molecular fingerprint' defines both health and disease. Environment and food (quality and quantity) are the key factors known to affect the health of an individual. The fundamental concepts are that the transition from a healthy condition to a disease phenotype must occur by concurrent alterations in the genome expression or by differences in protein synthesis, function and metabolites. In other words, the dietary components directly or indirectly modulate the molecular fingerprint and understanding of which is dealt with nutrigenomics. Although the fundamental principles of nutrigenomics remain similar to that of traditional research, a collection of comprehensive targeted/untargeted data sets in the context of nutrition offers the unique advantage of understanding complex metabolic networks to provide a mechanistic understanding of data from epidemiological and intervention studies. In this review the challenges and opportunities of nutrigenomic tools in addressing the nutritional problems of public health importance are discussed. The application of nutrigenomic tools provided numerous leads on biomarkers of nutrient intake, undernutrition, metabolic syndrome and its complications. Importantly, nutrigenomic studies also led to the discovery of the association of multiple genetic polymorphisms in relation to the variability of micronutrient absorption and metabolism, providing a potential opportunity for further research toward setting personalized dietary recommendations for individuals and population subgroups.
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Study of the metabolomics characteristics of patients with metabolic syndrome based on liquid chromatography quadrupole time-of-flight mass spectrometry.
Wu, N, Wang, W, Yi, M, Cheng, S, Wang, D
Annales d'endocrinologie. 2018;(1):37-44
Abstract
BACKGROUND Metabolic syndrome (MS) is a disease with complex pathophysiology and pathogenesis involving multiple systems of the human body. This study aimed to identify serum metabolites that are relevant to MS. MATERIAL AND METHODS This study involved 40 patients with MS and 28 healthy adults, and the following data were statistically analyzed: basic clinical data, blood lipids, fasting blood glucose, blood pressure, waist circumference, and visceral fat coefficient. Serum samples from both groups were collected and analyzed by liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF/MS); multivariate and univariate statistical methods were used to identify potential MS biomarkers and MS-related metabolic pathways. In addition, leucine and valine levels in serum from MS patients and normal subjects were measured using enzyme-linked immunosorbent assays (ELISAs). RESULTS In this study, 23 potential biomarkers were identified in the plasma of MS patients. These biomarkers were mainly related to metabolism; the tricarboxylic acid cycle; galactose metabolism; arachidonic acid metabolism; valine, leucine, and isoleucine degradation; and valine, leucine, and isoleucine biosynthesis. ELISAs were utilized to verify serum leucine and valine levels, and the results supported the experimental metabolomics results. CONCLUSIONS In total, 23 MS-related metabolites were identified in the serum; these differential metabolites were mainly associated with lipid metabolism, amino acid metabolism, glucose metabolism, purine metabolism, and other related metabolic pathways. This study shows that LC/MS-based metabolomics methods can be used to investigate the pathological changes in MS patients and identify biomarkers for the early diagnosis of MS.