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Metabolites
Special Issues
Metabolomic Analysis for Biomarker Discovery
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Metabolomic Analysis for Biomarker Discovery

A special issue of Metabolites (ISSN 2218-1989).

Deadline for manuscript submissions: closed (15 March 2022) | Viewed by 12755

Special Issue Editors

Prof. Dr. Georgios Theodoridis

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Guest Editor
1. Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
2. Biomic_AUTh, Center for Interdisciplinary Research and Innovation (CIRI-AUTH), Balkan Center, 10th km Thessaloniki-Thermi Rd, 57001 Thessaloniki, Greece
Interests: metabonomic/metabolomic analysis for biomarker discovery; bioanalysis and biological mass spectrometry (LC-MS, GC-MS); exploitation of molecular recognition mechanisms in analytical separations (immunoaffinity chromatography, molecular imprinting); novel sample pretreatment techniques (solid phase extraction-microextraction, chromatographic techniques in bioanalysis, pharmaceutical-toxicological analysis)
Special Issues, Collections and Topics in MDPI journals
Dr. Olga - Angeliki Begou

E-Mail Website
Guest Editor
1. School of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
2. Biomic_AUTh, Center for Interdisciplinary Research and Innovation (CIRI-AUTH), Balkan Center, B1.4, 57001 Thermi, Greece
Interests: mass spectrometry; validation; analytical chemistry; high-performance liquid chromatography (HPLC); gas chromatography; analytical method development; quality control of chemicals, foods, and pharmaceuticals; metabonomic/metabolomic analysis for biomarker discovery; novel sample pretreatment techniques
Special Issues, Collections and Topics in MDPI journals
Dr. Olga Deda

E-Mail Website
Guest Editor
1. School of Medicine, Aristotle University of Thessaloniki, University Campus, 54124 Thessaloniki, Greece
2. Greece & Biomic_AUTh, Center for Interdisciplinary Research and Innovation (CIRI-AUTH), Balkan Center, 10th km Thessaloniki-Thermi Rd, 57001 Thessaloniki, Greece
Interests: LC-MS/MS; GC-MS and NMR metabolic profiling; biochemical interpretation of metabolomics data; designing and carrying out procedures on rodents
Dr. Christina Virgiliou

E-Mail Website
Guest Editor
1. Department of Chemistry, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
2. Biomic_AUTh, Center for Interdisciplinary Research and Innovation (CIRI-AUTH), Balkan Center, 10th km Thessaloniki-Thermi Rd, 57001 Thessaloniki, Greece
Interests: metabolomics based method development; LC-HRMS; GC-MS; targeted metabolomics LC-MS/MS; foodomics; bioanalysis

Special Issue Information

Dear Colleagues,

A wide range of applications of metabolomics-based technologies is used to enlighten the pathophysiological mechanism of a plethora of diseases and holds promise in discovering novel and reliable biomarkers for disease stratification, management, and therapeutic interventions. The potential and the advantage that metabolomics brings to the field emanates from the simultaneous determination of hundreds of compounds that may have diverge physiochemical properties but are nevertheless assayed by this holistic approach: amino acids, lipids, sugars, bile acids, vitamins, nucleotides, and other primary endogenous metabolites. Metabolomics field aspires to expand and overcome current limitations of clinical markers, and to generate tools and biomarker panels for accurate diagnostic assessment of public health. Biomarker discovery remains challenging, since metabolic profile could be influenced by many factors, as genetic, nutritional, environmental.

This Special Issue aims to include, but not be limited to, articles and reviews regarding complex and high prevalent diseases, elucidation of their responsible mechanisms, novel metabolomics derived therapeutic intervention, as well as innovative methodologies in bioanalysis.

Thank you for your time, considering this invitation.

Prof. Dr. Georgios Theodoridis
Dr. Olga Angeliki Begou
Dr. Olga Deda
Dr. Christina Virgiliou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • metabolomics/metabonomics
  • disease biomarker discovery
  • mass spectrometry
  • metabolic profiling
  • hyphenated techniques

Published Papers (4 papers)

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Research

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16 pages, 1148 KiB  
Article
Novel Plasma Metabolomic Markers Associated with Diabetes Progression in Older Puerto Ricans
by Sona Rivas-Tumanyan, Lorena S. Pacheco, Danielle E. Haslam, Liming Liang, Katherine L. Tucker, Kaumudi J. Joshipura and Shilpa N. Bhupathiraju
Metabolites 2022, 12(6), 513; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo12060513 - 02 Jun 2022
Cited by 2 | Viewed by 2099
Abstract
We assessed longitudinal associations between plasma metabolites, their network-derived clusters, and type 2 diabetes (T2D) progression in Puerto Rican adults, a high-risk Hispanic subgroup with established health disparities. We used data from 1221 participants free of T2D and aged 40–75 years at baseline [...] Read more.
We assessed longitudinal associations between plasma metabolites, their network-derived clusters, and type 2 diabetes (T2D) progression in Puerto Rican adults, a high-risk Hispanic subgroup with established health disparities. We used data from 1221 participants free of T2D and aged 40–75 years at baseline in the Boston Puerto Rican Health and San Juan Overweight Adult Longitudinal Studies. We used multivariable Poisson regression models to examine associations between baseline concentrations of metabolites and incident T2D and prediabetes. Cohort-specific estimates were combined using inverse-variance weighted fixed-effects meta-analyses. A cluster of 13 metabolites of branched chain amino acids (BCAA), and aromatic amino acid metabolism (pooled IRR = 1.87, 95% CI: 1.28; 2.73), and a cell membrane component metabolite cluster (pooled IRR = 1.54, 95% CI: 1.04; 2.27) were associated with a higher risk of incident T2D. When the metabolites were tested individually, in combined analysis, 5 metabolites involved in BCAA metabolism were associated with incident T2D. These findings highlight potential prognostic biomarkers to identify Puerto Rican adults who may be at high risk for diabetes. Future studies should examine whether diet and lifestyle can modify the associations between these metabolites and progression to T2D. Full article
(This article belongs to the Special Issue Metabolomic Analysis for Biomarker Discovery)
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14 pages, 1828 KiB  
Article
Plasma Lipidomic and Metabolomic Profiling after Birth in Neonates Born to SARS-CoV-19 Infected and Non-Infected Mothers at Delivery: Preliminary Results
by Aggeliki Kontou, Christina Virgiliou, Thomai Mouskeftara, Olga Begou, Thomas Meikopoulos, Agathi Thomaidou, Eleni Agakidou, Helen Gika, Georgios Theodoridis and Kosmas Sarafidis
Metabolites 2021, 11(12), 830; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo11120830 - 30 Nov 2021
Cited by 5 | Viewed by 2727
Abstract
Pregnant women are among the high-risk populations for COVID-19, whereas the risk of vertical transmission to the fetus is very low. Nevertheless, metabolic alternations described in COVID-19 patients may also occur in pregnant women and their offspring. We prospectively evaluated the plasma lipidomic [...] Read more.
Pregnant women are among the high-risk populations for COVID-19, whereas the risk of vertical transmission to the fetus is very low. Nevertheless, metabolic alternations described in COVID-19 patients may also occur in pregnant women and their offspring. We prospectively evaluated the plasma lipidomic and metabolomic profiles, soon after birth, in neonates born to infected mothers (cases, n = 10) and in the offspring of uninfected ones at delivery (controls, n = 10). All cases had two negative tests for SARS-CoV-2 (nasopharyngeal swabs) performed 72 h apart. Blood samples were obtained within the first hours after birth. Liquid chromatography-high resolution mass spectrometry (UHPLC-TOF/MS) and gas chromatography-mass spectrometry (GC-MS) were applied for the analyses. Multivariate statistical analysis was performed for data evaluation. Changes in several plasma lipid species-classes (long-chain fatty acids phosphatidylcholines, triglycerides), and amino-acids were identified that allowed for clear discrimination between the study groups. The results of this preliminary investigation suggest that neonates born to Sars-Cov-19 positive mothers, without evidence of viral infection at birth, have a distinct plasma lipidomic and metabolomic profile compared to those of uninfected mothers. Whether these findings are reflective of maternal metabolic alternations due to the virus or a metabolic response following an unidentified neonatal infection warrants further investigation. Full article
(This article belongs to the Special Issue Metabolomic Analysis for Biomarker Discovery)
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18 pages, 3064 KiB  
Article
PRM-MS Quantitative Analysis of Isomeric N-Glycopeptides Derived from Human Serum Haptoglobin of Patients with Cirrhosis and Hepatocellular Carcinoma
by Cristian D. Gutierrez Reyes, Yifan Huang, Mojgan Atashi, Jie Zhang, Jianhui Zhu, Suyu Liu, Neehar D. Parikh, Amit G. Singal, Jianliang Dai, David M. Lubman and Yehia Mechref
Metabolites 2021, 11(8), 563; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo11080563 - 23 Aug 2021
Cited by 20 | Viewed by 2896
Abstract
Currently, surveillance strategies have inadequate performance for cirrhosis and early detection of hepatocellular carcinoma (HCC). The glycosylation of serum haptoglobin has shown to have significant differences between cirrhosis and HCC, thus can be used for diagnosis. We performed a comprehensive liquid chromatography—parallel reaction [...] Read more.
Currently, surveillance strategies have inadequate performance for cirrhosis and early detection of hepatocellular carcinoma (HCC). The glycosylation of serum haptoglobin has shown to have significant differences between cirrhosis and HCC, thus can be used for diagnosis. We performed a comprehensive liquid chromatography—parallel reaction monitoring—mass spectrometry (LC-PRM-MS) approach, where a targeted parallel reaction monitoring (PRM) strategy was coupled to a powerful LC system, to study the site-specific isomerism of haptoglobin (Hp) extracted from cirrhosis and HCC patients. We found that our strategy was able to identify a large number of isomeric N-glycopeptides, mainly located in the Hp glycosylation site Asn207. Four N-glycopeptides were found to have significant changes in abundance between cirrhosis and HCC samples (p < 0.05). Strategic combinations of the significant N-glycopeptides, either with alpha-fetoprotein (AFP) or themselves, better estimate the areas under the curve (AUC) of their respective receiver operating characteristic (ROC) curves with respect to AFP. The combination of AFP with the isomeric sialylated fucosylated N-glycopeptides Asn207 + 5-6-1-2 and Asn207 + 5-6-1-3, resulted with an AUC value of 0.98, while the AUC value for AFP alone was 0.85. When comparing cirrhosis vs. early HCC, the isomeric N-glycopeptide Asn207 + 5-6-0-1 better estimated AUC with respect to AFP (AUCAFP = 0.81, and AUCAsn207 + 5-6-0-1 = 0.88, respectively). Full article
(This article belongs to the Special Issue Metabolomic Analysis for Biomarker Discovery)
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Review

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22 pages, 2792 KiB  
Review
A Review of Metabolomic Profiling in Rheumatoid Arthritis: Bringing New Insights in Disease Pathogenesis, Treatment and Comorbidities
by Bárbara Jonson Bartikoski, Marianne Schrader De Oliveira, Rafaela Cavalheiro Do Espírito Santo, Leonardo Peterson Dos Santos, Natália Garcia Dos Santos and Ricardo Machado Xavier
Metabolites 2022, 12(5), 394; https://0-doi-org.brum.beds.ac.uk/10.3390/metabo12050394 - 27 Apr 2022
Cited by 8 | Viewed by 3757
Abstract
Metabolomic analysis provides a wealth of information that can be predictive of distinctive phenotypes of pathogenic processes and has been applied to better understand disease development. Rheumatoid arthritis (RA) is an autoimmune disease with the establishment of chronic synovial inflammation that affects joints [...] Read more.
Metabolomic analysis provides a wealth of information that can be predictive of distinctive phenotypes of pathogenic processes and has been applied to better understand disease development. Rheumatoid arthritis (RA) is an autoimmune disease with the establishment of chronic synovial inflammation that affects joints and peripheral tissues such as skeletal muscle and bone. There is a lack of useful disease biomarkers to track disease activity, drug response and follow-up in RA. In this review, we describe potential metabolic biomarkers that might be helpful in the study of RA pathogenesis, drug response and risk of comorbidities. TMAO (choline and trimethylamine oxide) and TCA (tricarboxylic acid) cycle products have been suggested to modulate metabolic profiles during the early stages of RA and are present systemically, which is a relevant characteristic for biomarkers. Moreover, the analysis of lipids such as cholesterol, FFAs and PUFAs may provide important information before disease onset to predict disease activity and treatment response. Regarding therapeutics, TNF inhibitors may increase the levels of tryptophan, valine, lysine, creatinine and alanine, whereas JAK/STAT inhibitors may modulate exclusively fatty acids. These observations indicate that different disease modifying antirheumatic drugs have specific metabolic profiles and can reveal differences between responders and non-responders. In terms of comorbidities, physical impairment represented by higher fatigue scores and muscle wasting has been associated with an increase in urea cycle, FFAs, tocopherols and BCAAs. In conclusion, synovial fluid, blood and urine samples from RA patients seem to provide critical information about the metabolic profile related to drug response, disease activity and comorbidities. Full article
(This article belongs to the Special Issue Metabolomic Analysis for Biomarker Discovery)
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