-
1.
Could metabolomics drive the fate of COVID-19 pandemic? A narrative review on lights and shadows.
Mussap, M, Fanos, V
Clinical chemistry and laboratory medicine. 2021;(12):1891-1905
Abstract
Human Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) infection activates a complex interaction host/virus, leading to the reprogramming of the host metabolism aimed at the energy supply for viral replication. Alterations of the host metabolic homeostasis strongly influence the immune response to SARS-CoV-2, forming the basis of a wide range of outcomes, from the asymptomatic infection to the onset of COVID-19 and up to life-threatening acute respiratory distress syndrome, vascular dysfunction, multiple organ failure, and death. Deciphering the molecular mechanisms associated with the individual susceptibility to SARS-CoV-2 infection calls for a system biology approach; this strategy can address multiple goals, including which patients will respond effectively to the therapeutic treatment. The power of metabolomics lies in the ability to recognize endogenous and exogenous metabolites within a biological sample, measuring their concentration, and identifying perturbations of biochemical pathways associated with qualitative and quantitative metabolic changes. Over the last year, a limited number of metabolomics- and lipidomics-based clinical studies in COVID-19 patients have been published and are discussed in this review. Remarkable alterations in the lipid and amino acid metabolism depict the molecular phenotype of subjects infected by SARS-CoV-2; notably, structural and functional data on the lipids-virus interaction may open new perspectives on targeted therapeutic interventions. Several limitations affect most metabolomics-based studies, slowing the routine application of metabolomics. However, moving metabolomics from bench to bedside cannot imply the mere determination of a given metabolite panel; rather, slotting metabolomics into clinical practice requires the conversion of metabolic patient-specific data into actionable clinical applications.
-
2.
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.
-
3.
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.
-
4.
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.
-
5.
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.
-
6.
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
-
-
Free full text
-
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.
-
7.
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.
-
8.
Metabolic Fingerprints of Circulating IGF-1 and the IGF-1/IGFBP-3 Ratio: A Multifluid Metabolomics Study.
Knacke, H, Pietzner, M, Do, KT, Römisch-Margl, W, Kastenmüller, G, Völker, U, Völzke, H, Krumsiek, J, Artati, A, Wallaschofski, H, et al
The Journal of clinical endocrinology and metabolism. 2016;(12):4730-4742
Abstract
OBJECTIVE IGF-1 is known for its various physiological and severe pathophysiological effects on human metabolism; however, underlying molecular mechanisms still remain unsolved. To reveal possible molecular mechanisms mediating these effects, for the first time, we associated serum IGF-1 levels with multifluid untargeted metabolomics data. METHODS Plasma/urine samples of 995 nondiabetic participants of the Study of Health in Pomerania were characterized by mass spectrometry. Sex-specific linear regression analyses were performed to assess the association of IGF-1 and IGF-1/IGF binding protein 3 ratio with metabolites. Additionally, the predictive ability of the plasma and urine metabolome for IGF-1 was assessed by orthogonal partial least squares analyses. RESULTS AND CONCLUSIONS We revealed a multifaceted image of associated metabolites with large sex differences. Confirming previous reports, we detected relations between IGF-1 and steroid hormones or related intermediates. Furthermore, various associated metabolites were previously mentioned regarding IGF-1-associated diseases, eg, betaine and cortisol in cardiovascular disease and metabolic syndrome, lipid disorders, and diabetes, or have previously been found to associate with differentiation and proliferation or mitochondrial functionality, eg, phospholipids. bradykinin, fatty acid derivatives, and cortisol, which were inversely associated with IGF-1, might establish a link of IGF-1 with inflammation. For the first time, we showed an association between IGF-1 and pipecolate, a metabolite linked to amino acid metabolism. Our study demonstrates that IGF-1 action on metabolism is tractable, even in healthy subjects, and that the findings provide a solid basis for further experimental/clinical investigation, eg, searching for inflammatory or cardiovascular disease- or metabolic syndrome-associated biomarkers and therapeutic targets.
-
9.
Quantitative serum nuclear magnetic resonance metabolomics in cardiovascular epidemiology and genetics.
Soininen, P, Kangas, AJ, Würtz, P, Suna, T, Ala-Korpela, M
Circulation. Cardiovascular genetics. 2015;(1):192-206
Abstract
Metabolomics is becoming common in epidemiology due to recent developments in quantitative profiling technologies and appealing results from their applications for understanding health and disease. Our team has developed an automated high-throughput serum NMR metabolomics platform that provides quantitative molecular data on 14 lipoprotein subclasses, their lipid concentrations and composition, apolipoprotein A-I and B, multiple cholesterol and triglyceride measures, albumin, various fatty acids as well as on numerous low-molecular-weight metabolites, including amino acids, glycolysis related measures and ketone bodies. The molar concentrations of these measures are obtained from a single serum sample with costs comparable to standard lipid measurements. We have analyzed almost 250 000 samples from around 100 epidemiological cohorts and biobanks and the new international set-up of multiple platforms will allow an annual throughput of more than 250 000 samples. The molecular data have been used to study type 1 and type 2 diabetes etiology as well as to characterize the molecular reflections of the metabolic syndrome, long-term physical activity, diet and lipoprotein metabolism. The results have revealed new biomarkers for early atherosclerosis, type 2 diabetes, diabetic nephropathy, cardiovascular disease and all-cause mortality. We have also combined genomics and metabolomics in diverse studies. We envision that quantitative high-throughput NMR metabolomics will be incorporated as a routine in large biobanks; this would make perfect sense both from the biological research and cost point of view - the standard output of over 200 molecular measures would vastly extend the relevance of the sample collections and make many separate clinical chemistry assays redundant.
-
10.
Clinical application of metabolomics in neonatology.
Fanos, V, Antonucci, R, Barberini, L, Noto, A, Atzori, L
The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians. 2012;:104-9
Abstract
The youngest and more rapidly increasing "omic" discipline, called metabolomics, is the process of describing the phenotype of a cell, tissue or organism through the full complement of metabolites present. Metabolomics measure global sets of low molecular weight metabolites (including amino acids, organic acids, sugars, fatty acids, lipids, steroids, small peptides, vitamins, etc.), thus providing a "snapshot" of the metabolic status of a cell, tissue or organism in relation to genetic variations or external stimuli. The use of metabolomics appears to be a promising tool in neonatology. The management of sick newborns might improve if more information on perinatal/neonatal maturational processes and their metabolic background were available. Urine ("a window on the organism") is a biofluid particularly suitable for metabolomic analysis in neonatology because it may be collected by using simple, noninvasive techniques and because it may provide valuable diagnostic information. In this review, the authors report the few literature data on neonatal metabolomics, including their personal experience, in the following fields: intrauterine growth restriction, perinatal transition, asphyxia, brain injury and hypothermia, maternal milk evaluation, postnatal maturation, bronchiolitis, sepsis, patent ductus arteriosus, respiratory distress syndrome, nephrouropathies, metabolic diseases, antibiotic treatment, perinatal programming and long-term outcome in extremely low birth-weight infants.