Literature DB >> 27061322

Integration of metabolomics and proteomics in multiple sclerosis: From biomarkers discovery to personalized medicine.

Piero Del Boccio1,2, Claudia Rossi1,2, Maria di Ioia2,3, Ilaria Cicalini1,2, Paolo Sacchetta1,2, Damiana Pieragostino1,2.   

Abstract

Personalized medicine is the science of individualized prevention and therapy. In the last decade, advances in high-throughput approaches allowed the development of proteomic and metabolomic studies in evaluating the association of genetic and phenotypic variability with disease sensitivity and analgesic response. These considerations have more value in case of multiple sclerosis (MuS), a multifactorial disease with high heterogeneity in clinical course and treatment response. In this review, we reported and updated about proteomic and metabolomic studies for the research of new candidate biomarkers in MuS, and difficulties in their clinical applications. We focused especially on the description of both "omics" approaches that, once integrated, may synergically describe pathophysiology conditions. To prove this assumption, we rebuilt interaction between proteins and metabolites described in the literature as potential biomarkers for MuS, and a pathway analysis of these molecules was performed. The result of such speculation demonstrated a strong convergence of proteomic and metabolomic results in this field, showing also a poorness of available tools for incorporating "omics" approaches. In conclusion, the integration of Metabolomics and Proteomics may allow a more complete characterization of such a heterogeneous disease, providing further insights into personalized healthcare.
© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Biomarkers; Metabolomics; Multiple sclerosis; Personalized medicine; Proteomics

Mesh:

Substances:

Year:  2016        PMID: 27061322     DOI: 10.1002/prca.201500083

Source DB:  PubMed          Journal:  Proteomics Clin Appl        ISSN: 1862-8346            Impact factor:   3.494


  9 in total

1.  Metabolomic and proteomic profiling in bipolar disorder patients revealed potential molecular signatures related to hemostasis.

Authors:  Henrique Caracho Ribeiro; Partho Sen; Alex Dickens; Elisa Castañeda Santa Cruz; Matej Orešič; Alessandra Sussulini
Journal:  Metabolomics       Date:  2022-08-03       Impact factor: 4.747

2.  Integrated Proteomic and Metabolomic prediction of Term Preeclampsia.

Authors:  Ray Bahado-Singh; Liona C Poon; Ali Yilmaz; Argyro Syngelaki; Onur Turkoglu; Praveen Kumar; Joseph Kirma; Matthew Allos; Veronica Accurti; Jiansheng Li; Peng Zhao; Stewart F Graham; David R Cool; Kypros Nicolaides
Journal:  Sci Rep       Date:  2017-11-23       Impact factor: 4.379

Review 3.  A Primer on Data Analytics in Functional Genomics: How to Move from Data to Insight?

Authors:  Piotr Grabowski; Juri Rappsilber
Journal:  Trends Biochem Sci       Date:  2018-12-03       Impact factor: 13.807

Review 4.  An emerging potential of metabolomics in multiple sclerosis: a comprehensive overview.

Authors:  Insha Zahoor; Bin Rui; Junaid Khan; Indrani Datta; Shailendra Giri
Journal:  Cell Mol Life Sci       Date:  2021-01-15       Impact factor: 9.261

Review 5.  Contribution of Metabolomics to Multiple Sclerosis Diagnosis, Prognosis and Treatment.

Authors:  Marianna Gabriella Rispoli; Silvia Valentinuzzi; Giovanna De Luca; Piero Del Boccio; Luca Federici; Maria Di Ioia; Anna Digiovanni; Eleonora Agata Grasso; Valeria Pozzilli; Alessandro Villani; Antonio Maria Chiarelli; Marco Onofrj; Richard G Wise; Damiana Pieragostino; Valentina Tomassini
Journal:  Int J Mol Sci       Date:  2021-10-15       Impact factor: 5.923

Review 6.  Breast cancer in the era of integrating "Omics" approaches.

Authors:  Claudia Rossi; Ilaria Cicalini; Maria Concetta Cufaro; Ada Consalvo; Prabin Upadhyaya; Gianluca Sala; Ivana Antonucci; Piero Del Boccio; Liborio Stuppia; Vincenzo De Laurenzi
Journal:  Oncogenesis       Date:  2022-04-14       Impact factor: 6.524

7.  Machine-learning based lipid mediator serum concentration patterns allow identification of multiple sclerosis patients with high accuracy.

Authors:  Jörn Lötsch; Susanne Schiffmann; Katja Schmitz; Robert Brunkhorst; Florian Lerch; Nerea Ferreiros; Sabine Wicker; Irmgard Tegeder; Gerd Geisslinger; Alfred Ultsch
Journal:  Sci Rep       Date:  2018-10-05       Impact factor: 4.379

Review 8.  Advances in High Throughput Proteomics Profiling in Establishing Potential Biomarkers for Gastrointestinal Cancer.

Authors:  Md Zahirul Islam Khan; Shing Yau Tam; Helen Ka Wai Law
Journal:  Cells       Date:  2022-03-11       Impact factor: 6.600

Review 9.  Metabolomics as a promising tool for improving understanding of multiple sclerosis: A review of recent advances.

Authors:  Zhicheng Liu; Jeffrey Waters; Bin Rui
Journal:  Biomed J       Date:  2022-01-15       Impact factor: 7.892

  9 in total

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