scholarly journals Metabolic profiling in diabetes

2014 ◽  
Vol 221 (3) ◽  
pp. R75-R85 ◽  
Author(s):  
Karsten Suhre
Keyword(s):  
Metabolic Profiling ◽  
Metabolic Pathways ◽  
Genetic Variance ◽  
Biomarker Discovery ◽  
Drug Efficacy ◽  
Diabetes Research ◽  
Metabolic Markers ◽  
Mature Science ◽  
Target Effects

Metabolic profiling, or metabolomics, has developed into a mature science in recent years. It has major applications in the study of metabolic disorders. This review addresses issues relevant to the choice of the metabolomics platform, study design and data analysis in diabetes research, and presents recent advances using metabolomics in the identification of markers for altered metabolic pathways, biomarker discovery, challenge studies, metabolic markers of drug efficacy and off-target effects. The role of genetic variance and intermediate metabolic phenotypes and its relevance to diabetes research is also addressed.

scholarly journals Comparative analysis unveils novel changes in serum metabolites and metabolomic networks of retinopathy of prematurity infants

2021 ◽  
Author(s):  
Yuhang Yang ◽  
Qian Yang ◽  
Yinsheng Zhang ◽  
Chaohui Lian ◽  
Honghui He ◽  
...  
Keyword(s):  
Retinopathy Of Prematurity ◽  
Metabolic Profiling ◽  
Metabolic Pathways ◽  
Redox Homeostasis ◽  
Serum Samples ◽  
Retrospective Case ◽  
Machine Leaning ◽  
Liquid Chromatography Tandem Mass ◽  
Ultrahigh Performance Liquid Chromatography

AbstractBackgroundAdvances in mass spectrometry are providing new insights into the role of metabolomics in the aetiology of many diseases. Studies in retinopathy of prematurity (ROP), for instance, overlooked the role of metabolic alterations in disease development. Here, we employed comprehensive metabolic profiling and gold-standard metabolic analysis to explore major metabolites and metabolic pathways significantly affected in early stages of pathogenesis toward ROP.MethodsThis is a multicentre, retrospective case-control study. We collected serums from 57 ROP cases and 57 strictly baseline matched non-ROP controls. Non-targeted ultrahigh performance liquid chromatography-tandem mass spectroscopy (UPLC-MS/MS) from Metabolon, Inc. was used to detect the metabolites in serum samples. Machine learning was used to unravel most affected metabolites and pathways in ROP development.ResultsCompared to non-ROP controls, we found a significant metabolic perturbation in the ROP serums, featured with an increase in lipid, nucleotide, carbohydrate metabolites and a lower level of peptides. Machine leaning helped to distinguish a cluster of metabolic pathways (glycometabolism, redox homeostasis, lipid metabolism and arginine pathway) that were strongly related to the development of ROP. In addition, we found that the severity of ROP was related to the level of creatinine and ribitol.ConclusionIn the current study, our results suggested a strong link between metabolic profiling and retinal neovascularization during ROP pathogenesis. These findings provided an insight into identifying novel metabolic biomarkers for ROP diagnosis and prevention.

scholarly journals The Ability of Metabolomics to Discriminate Non-Small-Cell Lung Cancer Subtypes Depends on the Stage of the Disease and the Type of Material Studied

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3314
Author(s):  
Tomasz Kowalczyk ◽  
Joanna Kisluk ◽  
Karolina Pietrowska ◽  
Joanna Godzien ◽  
Miroslaw Kozlowski ◽  
...  
Keyword(s):  
Metabolic Pathways ◽  
Early Stage ◽  
Chronic Obstructive ◽  
Liquid Chromatography Mass Spectrometry ◽  
Obstructive Pulmonary Disease ◽  
Cell Lung Carcinoma ◽  
Cancer Subtypes ◽  
Inflammatory State ◽  
Nsclc Patients

Identification of the NSCLC subtype at an early stage is still quite sophisticated. Metabolomics analysis of tissue and plasma of NSCLC patients may indicate new, and yet unknown, metabolic pathways active in the NSCLC. Our research characterized the metabolomics profile of tissue and plasma of patients with early and advanced NSCLC stage. Samples were subjected to thorough metabolomics analyses using liquid chromatography-mass spectrometry (LC-MS) technique. Tissue and/or plasma samples from 137 NSCLC patients were analyzed. Based on the early stage tissue analysis, more than 200 metabolites differentiating adenocarcinoma (ADC) and squamous cell lung carcinoma (SCC) subtypes as well as normal tissue, were identified. Most of the identified metabolites were amino acids, fatty acids, carnitines, lysoglycerophospholipids, sphingomyelins, plasmalogens and glycerophospholipids. Moreover, metabolites related to N-acyl ethanolamine (NAE) biosynthesis, namely glycerophospho (N-acyl) ethanolamines (GP-NAE), which discriminated early-stage SCC from ADC, have also been identified. On the other hand, the analysis of plasma of chronic obstructive pulmonary disease (COPD) and NSCLC patients allowed exclusion of the metabolites related to the inflammatory state in lungs and the identification of compounds (lysoglycerophospholipids, glycerophospholipids and sphingomyelins) truly characteristic to cancer. Our results, among already known, showed novel, thus far not described, metabolites discriminating NSCLC subtypes, especially in the early stage of cancer. Moreover, the presented results also indicated the activity of new metabolic pathways in NSCLC. Further investigations on the role of NAE biosynthesis pathways in the early stage of NSCLC may reveal new prognostic and diagnostic targets.

scholarly journals The Role of Cell Metabolism in Innate Immune Memory

2020 ◽  
pp. 1-9
Author(s):  
Anaisa Valido Ferreira ◽  
Jorge Domiguéz-Andrés ◽  
Mihai Gheorghe Netea
Keyword(s):  
Metabolic Pathways ◽  
Tricarboxylic Acid Cycle ◽  
Cell Metabolism ◽  
Innate Immune ◽  
Immune Memory ◽  
Functional Changes ◽  
Trained Immunity ◽  
Health And Disease

Immunological memory is classically attributed to adaptive immune responses, but recent studies have shown that challenged innate immune cells can display long-term functional changes that increase nonspecific responsiveness to subsequent infections. This phenomenon, coined <i>trained immunity</i> or <i>innate immune memory</i>, is based on the epigenetic reprogramming and the rewiring of intracellular metabolic pathways. Here, we review the different metabolic pathways that are modulated in trained immunity. Glycolysis, oxidative phosphorylation, the tricarboxylic acid cycle, amino acid, and lipid metabolism are interplaying pathways that are crucial for the establishment of innate immune memory. Unraveling this metabolic wiring allows for a better understanding of innate immune contribution to health and disease. These insights may open avenues for the development of future therapies that aim to harness or dampen the power of the innate immune response.

scholarly journals Mitochondrial Sirtuins in Reproduction

Antioxidants ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1047
Author(s):  
Giovanna Di Emidio ◽  
Stefano Falone ◽  
Paolo Giovanni Artini ◽  
Fernanda Amicarelli ◽  
Anna Maria D’Alessandro ◽  
...  
Keyword(s):  
Stress Responses ◽  
Metabolic Pathways ◽  
Redox Balance ◽  
Antioxidant Defenses ◽  
Metabolic Abnormalities ◽  
Female Reproduction ◽  
Mitochondrial Dysfunctions ◽  
Early Embryos ◽  
The Relationship

Mitochondria act as hubs of numerous metabolic pathways. Mitochondrial dysfunctions contribute to altering the redox balance and predispose to aging and metabolic alterations. The sirtuin family is composed of seven members and three of them, SIRT3-5, are housed in mitochondria. They catalyze NAD+-dependent deacylation and the ADP-ribosylation of mitochondrial proteins, thereby modulating gene expression and activities of enzymes involved in oxidative metabolism and stress responses. In this context, mitochondrial sirtuins (mtSIRTs) act in synergistic or antagonistic manners to protect from aging and aging-related metabolic abnormalities. In this review, we focus on the role of mtSIRTs in the biological competence of reproductive cells, organs, and embryos. Most studies are focused on SIRT3 in female reproduction, providing evidence that SIRT3 improves the competence of oocytes in humans and animal models. Moreover, SIRT3 protects oocytes, early embryos, and ovaries against stress conditions. The relationship between derangement of SIRT3 signaling and the imbalance of ROS and antioxidant defenses in testes has also been demonstrated. Very little is known about SIRT4 and SIRT5 functions in the reproductive system. The final goal of this work is to understand whether sirtuin-based signaling may be taken into account as potential targets for therapeutic applications in female and male infertility.

scholarly journals Utilizing the Food–Pathogen Metabolome to Putatively Identify Biomarkers for the Detection of Shiga Toxin-Producing E. coli (STEC) from Spinach

Metabolites ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 67
Author(s):  
Snehal R. Jadhav ◽  
Rohan M. Shah ◽  
Avinash V. Karpe ◽  
Robert S. Barlow ◽  
Kate E. McMillan ◽  
...  
Keyword(s):  
Shiga Toxin ◽  
Metabolic Profiling ◽  
Biomarker Discovery ◽  
Risk Groups ◽  
Proof Of Concept ◽  
Rapid Methods ◽  
E Coli ◽  
Leafy Greens ◽  
Food Pathogen ◽  
Genomic Similarity

Shiga toxigenic E. coli (STEC) are an important cause of foodborne disease globally with many outbreaks linked to the consumption of contaminated foods such as leafy greens. Existing methods for STEC detection and isolation are time-consuming. Rapid methods may assist in preventing contaminated products from reaching consumers. This proof-of-concept study aimed to determine if a metabolomics approach could be used to detect STEC contamination in spinach. Using untargeted metabolic profiling, the bacterial pellets and supernatants arising from bacterial and inoculated spinach enrichments were investigated for the presence of unique metabolites that enabled categorization of three E. coli risk groups. A total of 109 and 471 metabolite features were identified in bacterial and inoculated spinach enrichments, respectively. Supervised OPLS-DA analysis demonstrated clear discrimination between bacterial enrichments containing different risk groups. Further analysis of the spinach enrichments determined that pathogen risk groups 1 and 2 could be easily discriminated from the other groups, though some clustering of risk groups 1 and 2 was observed, likely representing their genomic similarity. Biomarker discovery identified metabolites that were significantly associated with risk groups and may be appropriate targets for potential biosensor development. This study has confirmed that metabolomics can be used to identify the presence of pathogenic E. coli likely to be implicated in human disease.

scholarly journals The Pleiotropic Function of Human Sirtuins as Modulators of Metabolic Pathways and Viral Infections

Cells ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 460
Author(s):  
Mohammed Hamed Alqarni ◽  
Ahmed Ibrahim Foudah ◽  
Magdy Mohamed Muharram ◽  
Nikolaos E. Labrou
Keyword(s):  
Metabolic Pathways ◽  
Histone Deacetylases ◽  
Viral Infections ◽  
Cell Physiology ◽  
Functional Roles ◽  
Regulatory Processes ◽  
Complex Functions ◽  
Natural Polyphenol ◽  
Antiviral Targets

Sirtuins (SIRTs) are nicotinamide adenine dinucleotide-dependent histone deacetylases that incorporate complex functions in the mechanisms of cell physiology. Mammals have seven distinct members of the SIRT family (SIRT1-7), which play an important role in a well-maintained network of metabolic pathways that control and adapt the cell to the environment, energy availability and cellular stress. Until recently, very few studies investigated the role of SIRTs in modulating viral infection and progeny. Recent studies have demonstrated that SIRT1 and SIRT2 are promising antiviral targets because of their specific connection to numerous metabolic and regulatory processes affected during infection. In the present review, we summarize some of the recent progress in SIRTs biochemistry and their emerging function as antiviral targets. We also discuss the potential of natural polyphenol-based SIRT modulators to control their functional roles in several diseases including viral infections.

scholarly journals Metabolomics for Biomarker Discovery: Key Signatory Metabolic Profiles for the Identification and Discrimination of Oat Cultivars

Metabolites ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 165
Author(s):  
Chanel J. Pretorius ◽  
Fidele Tugizimana ◽  
Paul A. Steenkamp ◽  
Lizelle A. Piater ◽  
Ian A. Dubery
Keyword(s):  
High Performance ◽  
Biomarker Discovery ◽  
Cultivar Identification ◽  
Principal Component ◽  
Rapid Identification ◽  
Maturity Stage ◽  
Metabolic Profiles ◽  
High Definition ◽  
Metabolic Markers ◽  
Leaves And Roots

The first step in crop introduction—or breeding programmes—requires cultivar identification and characterisation. Rapid identification methods would therefore greatly improve registration, breeding, seed, trade and inspection processes. Metabolomics has proven to be indispensable in interrogating cellular biochemistry and phenotyping. Furthermore, metabolic fingerprints are chemical maps that can provide detailed insights into the molecular composition of a biological system under consideration. Here, metabolomics was applied to unravel differential metabolic profiles of various oat (Avena sativa) cultivars (Magnifico, Dunnart, Pallinup, Overberg and SWK001) and to identify signatory biomarkers for cultivar identification. The respective cultivars were grown under controlled conditions up to the 3-week maturity stage, and leaves and roots were harvested for each cultivar. Metabolites were extracted using 80% methanol, and extracts were analysed on an ultra-high performance liquid chromatography (UHPLC) system coupled to a quadrupole time-of-flight (qTOF) high-definition mass spectrometer analytical platform. The generated data were processed and analysed using multivariate statistical methods. Principal component analysis (PCA) models were computed for both leaf and root data, with PCA score plots indicating cultivar-related clustering of the samples and pointing to underlying differential metabolic profiles of these cultivars. Further multivariate analyses were performed to profile differential signatory markers, which included carboxylic acids, amino acids, fatty acids, phenolic compounds (hydroxycinnamic and hydroxybenzoic acids, and associated derivatives) and flavonoids, among the respective cultivars. Based on the key signatory metabolic markers, the cultivars were successfully distinguished from one another in profiles derived from both leaves and roots. The study demonstrates that metabolomics can be used as a rapid phenotyping tool for cultivar differentiation.

scholarly journals The Constantly Evolving Role of Medical Image Processing in Oncology: From Traditional Medical Image Processing to Imaging Biomarkers and Radiomics

2021 ◽  
Vol 7 (8) ◽  
pp. 124
Author(s):  
Kostas Marias
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Medical Image ◽  
Biomarker Discovery ◽  
Medical Image Processing ◽  
Machine Learning Techniques ◽  
Imaging Biomarker ◽  
Imaging Biomarkers ◽  
Precision Oncology

The role of medical image computing in oncology is growing stronger, not least due to the unprecedented advancement of computational AI techniques, providing a technological bridge between radiology and oncology, which could significantly accelerate the advancement of precision medicine throughout the cancer care continuum. Medical image processing has been an active field of research for more than three decades, focusing initially on traditional image analysis tasks such as registration segmentation, fusion, and contrast optimization. However, with the advancement of model-based medical image processing, the field of imaging biomarker discovery has focused on transforming functional imaging data into meaningful biomarkers that are able to provide insight into a tumor’s pathophysiology. More recently, the advancement of high-performance computing, in conjunction with the availability of large medical imaging datasets, has enabled the deployment of sophisticated machine learning techniques in the context of radiomics and deep learning modeling. This paper reviews and discusses the evolving role of image analysis and processing through the lens of the abovementioned developments, which hold promise for accelerating precision oncology, in the sense of improved diagnosis, prognosis, and treatment planning of cancer.

scholarly journals Placental 13C-DHA metabolism and relationship with maternal BMI, glycemia and birthweight

2021 ◽  
Vol 27 (1) ◽  
Author(s):  
Oliver C. Watkins ◽  
Preben Selvam ◽  
Reshma Appukuttan Pillai ◽  
Victoria K. B. Cracknell-Hazra ◽  
Hannah E. J. Yong ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Liquid Chromatography ◽  
Lipid Metabolism ◽  
Metabolic Pathways ◽  
Liquid Chromatography Mass Spectrometry ◽  
Fasting Glycemia ◽  
Glucose Treatment ◽  
Maternal Bmi

Abstract Background Fetal docosahexaenoic acid (DHA) supply relies on preferential transplacental transfer, which is regulated by placental DHA lipid metabolism. Maternal hyperglycemia and obesity associate with higher birthweight and fetal DHA insufficiency but the role of placental DHA metabolism is unclear. Methods Explants from 17 term placenta were incubated with 13C-labeled DHA for 48 h, at 5 or 10 mmol/L glucose treatment, and the production of 17 individual newly synthesized 13C-DHA labeled lipids quantified by liquid chromatography mass spectrometry. Results Maternal BMI positively associated with 13C-DHA-labeled diacylglycerols, triacylglycerols, lysophospholipids, phosphatidylcholine and phosphatidylethanolamine plasmalogens, while maternal fasting glycemia positively associated with five 13C-DHA triacylglycerols. In turn, 13C-DHA-labeled phospholipids and triacylglycerols positively associated with birthweight centile. In-vitro glucose treatment increased most 13C-DHA-lipids, but decreased 13C-DHA phosphatidylethanolamine plasmalogens. However, with increasing maternal BMI, the magnitude of the glucose treatment induced increase in 13C-DHA phosphatidylcholine and 13C-DHA lysophospholipids was curtailed, with further decline in 13C-DHA phosphatidylethanolamine plasmalogens. Conversely, with increasing birthweight centile glucose treatment induced increases in 13C-DHA triacylglycerols were exaggerated, while glucose treatment induced decreases in 13C-DHA phosphatidylethanolamine plasmalogens were diminished. Conclusions Maternal BMI and glycemia increased the production of different placental DHA lipids implying impact on different metabolic pathways. Glucose-induced elevation in placental DHA metabolism is moderated with higher maternal BMI. In turn, findings of associations between many DHA lipids with birthweight suggest that BMI and glycemia promote fetal growth partly through changes in placental DHA metabolism.

scholarly journals PD-L1/PD-1 Axis in Multiple Myeloma Microenvironment and a Possible Link with CD38-Mediated Immune-Suppression

Cancers ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 164
Author(s):  
Federica Costa ◽  
Valentina Marchica ◽  
Paola Storti ◽  
Fabio Malavasi ◽  
Nicola Giuliani
Keyword(s):  
Multiple Myeloma ◽  
Bone Marrow ◽  
Cell Survival ◽  
Immune Suppression ◽  
Metabolic Pathways ◽  
Therapeutic Strategy ◽  
Myeloma Cell ◽  
Immune Microenvironment ◽  
Potential Use

The emerging role of the PD-1/PD-L1 axis in MM immune-microenvironment has been highlighted by several studies. However, discordant data have been reported on PD-1/PD-L1 distribution within the bone marrow (BM) microenvironment of patients with monoclonal gammopathies. In addition, the efficacy of PD-1/PD-L1 blockade as a therapeutic strategy to reverse myeloma immune suppression and inhibit myeloma cell survival still remains unknown. Recent data suggest that, among the potential mechanisms behind the lack of responsiveness or resistance to anti-PD-L1/PD-1 antibodies, the CD38 metabolic pathways involving the immune-suppressive factor, adenosine, could play an important role. This review summarizes the available data on PD-1/PD-L1 expression in patients with MM, reporting the main mechanisms of regulation of PD-1/PD-L1 axis. The possible link between the CD38 and PD-1/PD-L1 pathways is also reported, highlighting the rationale for the potential use of a combined therapeutic approach with CD38 blocking agents and anti-PD-1/PD-L1 antibodies in order to improve their anti-tumoral effect in MM patients.

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