Advances in Mass Spectrometry-Based Blood Metabolomics Profiling for Non-Cancer Diseases: A Comprehensive Review

Author:

Demicheva Ekaterina12ORCID,Dordiuk Vladislav1ORCID,Polanco Espino Fernando1ORCID,Ushenin Konstantin13ORCID,Aboushanab Saied4ORCID,Shevyrin Vadim4ORCID,Buhler Aleksey1ORCID,Mukhlynina Elena12ORCID,Solovyova Olga12ORCID,Danilova Irina12ORCID,Kovaleva Elena4ORCID

Affiliation:

1. Institute of Natural Sciences and Mathematics, Ural Federal University, Ekaterinburg 620075, Russia

2. Institute of Immunology and Physiology of the Ural Branch of the Russian Academy of Sciences, Ekaterinburg 620049, Russia

3. Autonomous Non-Profit Organization Artificial Intelligence Research Institute (AIRI), Moscow 105064, Russia

4. Institute of Chemical Engineering, Ural Federal University, Ekaterinburg 620002, Russia

Abstract

Blood metabolomics profiling using mass spectrometry has emerged as a powerful approach for investigating non-cancer diseases and understanding their underlying metabolic alterations. Blood, as a readily accessible physiological fluid, contains a diverse repertoire of metabolites derived from various physiological systems. Mass spectrometry offers a universal and precise analytical platform for the comprehensive analysis of blood metabolites, encompassing proteins, lipids, peptides, glycans, and immunoglobulins. In this comprehensive review, we present an overview of the research landscape in mass spectrometry-based blood metabolomics profiling. While the field of metabolomics research is primarily focused on cancer, this review specifically highlights studies related to non-cancer diseases, aiming to bring attention to valuable research that often remains overshadowed. Employing natural language processing methods, we processed 507 articles to provide insights into the application of metabolomic studies for specific diseases and physiological systems. The review encompasses a wide range of non-cancer diseases, with emphasis on cardiovascular disease, reproductive disease, diabetes, inflammation, and immunodeficiency states. By analyzing blood samples, researchers gain valuable insights into the metabolic perturbations associated with these diseases, potentially leading to the identification of novel biomarkers and the development of personalized therapeutic approaches. Furthermore, we provide a comprehensive overview of various mass spectrometry approaches utilized in blood metabolomics research, including GC-MS, LC-MS, and others discussing their advantages and limitations. To enhance the scope, we propose including recent review articles supporting the applicability of GC×GC-MS for metabolomics-based studies. This addition will contribute to a more exhaustive understanding of the available analytical techniques. The Integration of mass spectrometry-based blood profiling into clinical practice holds promise for improving disease diagnosis, treatment monitoring, and patient outcomes. By unraveling the complex metabolic alterations associated with non-cancer diseases, researchers and healthcare professionals can pave the way for precision medicine and personalized therapeutic interventions. Continuous advancements in mass spectrometry technology and data analysis methods will further enhance the potential of blood metabolomics profiling in non-cancer diseases, facilitating its translation from the laboratory to routine clinical application.

Funder

Ministry of Science and Higher Education of the Russian Federation

Publisher

MDPI AG

Subject

Molecular Biology,Biochemistry,Endocrinology, Diabetes and Metabolism

Reference306 articles.

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4. Bird, S., Klein, E., and Loper, E. (2009). Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit, O’Reilly Media, Inc.

5. Text mining: Use of TF-IDF to examine the relevance of words to documents;Qaiser;Int. J. Comput. Appl.,2018

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