Related Experiment Video
Updated: Jun 21, 2025
Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
Published on: November 29, 2024
Metabolomic biomarkers of multiple myeloma: A systematic review
Valeria G Varzieva1, Natalia V Mesonzhnik2, Irina S Ilgisonis3
1Department of Pharmacology, Sechenov First Moscow State Medical University (Sechenov University), Vernadskogo pr., 96, 119571 Moscow, Russia; Centre of Biopharmaceutical Analysis and Metabolomics, Institute of Translational Medicine and Biotechnology, Sechenov First Moscow State Medical University (Sechenov University), Nakhimovsky pr., 45, 117418 Moscow, Russia.
Abstract:
Multiple myeloma (MM) is an incurable malignancy of clonal plasma cells. Various diagnostic methods are used in parallel to accurately determine stage and severity of the disease. Identifying a biomarker or a panel of biomarkers could enhance the quality of medical care that patients receive by adopting a more personalized approach. Metabolomics utilizes high-throughput analytical platforms to examine the levels and quantities of biochemical compounds in biosamples. The aim of this review was to conduct a systematic literature search for potential metabolic biomarkers that may aid in the diagnosis and prognosis of MM. The review was conducted in accordance with PRISMA recommendations and was registered in PROSPERO. The systematic search was performed in PubMed, CINAHL, SciFinder, Scopus, The Cochrane Library and Google Scholar. Studies were limited to those involving people with clinically diagnosed MM and healthy controls as comparators. Articles had to be published in English and had no restrictions on publication date or sample type. The quality of articles was assessed according to QUADOMICS criteria. A total of 709 articles were collected during the literature search. Of these, 436 were excluded based on their abstract, with 26 more removed after a thorough review of the full text. Finally, 16 articles were deemed relevant and were subjected to further analysis of their data. A number of promising candidate biomarkers was discovered. Follow-up studies with large sample sizes are needed to determine their suitability for clinical applications.
