Personalized and Precision Medicine Journal
Where Innovations Meets Personalized and Precision Medicine

Innovative Functions of Metabolomics in Individualized Health Care: A Review Study in the Field of Metabolomics

Document Type : Review Article

Authors

Sara Saremi Nouri 1
Mehrsa Emami 2
Hamidreza Kabiri 3
Negin Rajaei 4

1 Department of Biology, Faculty of Basic Sciences, Azarbaijan Branch, Azarbaijan Shahid Madani University, Azarbaijan, Iran.

2 Department of Biology, Faculty of Basic Sciences, East-Tehran Branch, Islamic Azad University, Tehran, Iran.

3 Young Researchers and Elite Club, Shahrekord Branch, Islamic Azad University, Shahrekord, Iran.

4 3Young Researchers and Elite Club, Shahrekord Branch, Islamic Azad University, 8816954615 Shahrekord, Iran 4Sina Borna Aria (SABA) Co., Ltd., Research and Development Center for Biotechnology, 8815943157 Shahrekord, Iran 5Parsian Bioproducers

https://doi.org/10.22034/pmj.2024.2024193.1033
Abstract
Variability in medication reactions and illness susceptibility among individuals is often seen in clinical settings. Personalized medicine is now highly esteemed for its focus on prescribing the appropriate medication to each patient. Metabolomics is a developing field that thoroughly assesses all metabolite and low-molecular-weight compounds in a biological sample. Metabolic profiling offers a quick overview of a cell's physiology, making the technique a direct indicator of an organism's physiological condition. Quantifiable correlations exist between the metabolome and other cellular components such as the genome, transcriptome, proteome, and lipidome. These correlations can be utilized to forecast metabolite levels in biological samples based on mRNA levels. One of the key problems in systems biology is to incorporate metabolomics with other -omics data to enhance comprehension of cellular biology. Metabolomics is used to assess the effectiveness of clinical substances by analyzing the metabolic characteristics of patients before treatment to predict their responses (pharmacometabolomic) and to identify individuals at risk of developing diseases (patient stratification). The rapid progress in metabolomics technique highlights its significant potential for use in customized treatment. We reviewed the unique benefits of metabolomics, including instances in assessing medication treatment and individual stratification, and emphasized metabolomics' promise in personalized medicine.

Keywords

Personalized medicine
Metabolomics
Health Care
Drug Sensitivity

Subjects

  1. Oyesola OO, Souza CO. The Influence of Genetic and Environmental Factors and Their Interactions on Immune Response to Helminth Infections. Frontiers in Immunology. 2022 Apr 29;13:869163.
  2. Lightbody G, Haberland V, Browne F, Taggart L, Zheng H, Parkes E, Blayney JK. Review of applications of high-throughput sequencing in personalized medicine: barriers and facilitators of future progress in research and clinical application. Briefings in bioinformatics. 2019 Sep;20(5):1795-811.
  3. Piri-Gharaghie T. Polycystic ovary syndrome and genetic factors influencing its development: A review article. Personalized Medicine Journal. 2021 Dec 1;6(23):25-9.
  4. Pirmohamed M. Personalized pharmacogenomics: predicting efficacy and adverse drug reactions. Annual review of genomics and human genetics. 2014 Aug 31;15:349-70.
  5. Dhurjad P, Dhavaliker C, Gupta K, Sonti R. Exploring drug metabolism by the gut microbiota: modes of metabolism and experimental approaches. Drug Metabolism and Disposition. 2022 Mar 1;50(3):224-34.
  6. Klassen A, Faccio AT, Canuto GA, da Cruz PL, Ribeiro HC, Tavares MF, Sussulini A. Metabolomics: definitions and significance in systems biology. Metabolomics: from fundamentals to clinical applications. 2017:3-17.
  7. Everett JR. Pharmacometabonomics: The prediction of drug effects using metabolic profiling. Concepts and Principles of Pharmacology: 100 Years of the Handbook of Experimental Pharmacology. 2019:263-99.
  8. Beger RD, Schmidt MA, Kaddurah-Daouk R. Current concepts in pharmacometabolomics, biomarker discovery, and precision medicine. Metabolites. 2020 Mar 27;10(4):129.
  9. Beger RD, Dunn W, Schmidt MA, Gross SS, Kirwan JA, Cascante M, Brennan L, Wishart DS, Oresic M, Hankemeier T, Broadhurst DI. Metabolomics enables precision medicine:“a white paper, community perspective”. Metabolomics. 2016 Sep;12:1-5.
  10. Pinu FR, Beale DJ, Paten AM, Kouremenos K, Swarup S, Schirra HJ, Wishart D. Systems biology and multi-omics integration: viewpoints from the metabolomics research community. Metabolites. 2019 Apr 18;9(4):76.
  11. Wishart DS. Emerging applications of metabolomics in drug discovery and precision medicine. Nature reviews Drug discovery. 2016 Jul;15(7):473-84.
  12. Zodda D, Giammona R, Schifilliti S. Treatment strategy for dyslipidemia in cardiovascular disease prevention: focus on old and new drugs. Pharmacy. 2018 Jan 21;6(1):10.
  13. Ridker PM. The JUPITER trial: results, controversies, and implications for prevention. Circulation: Cardiovascular Quality and Outcomes. 2009 May;2(3):279-85.
  14. Kaddurah-Daouk R, Baillie RA, Zhu H, Zeng ZB, Wiest MM, Nguyen UT, Watkins SM, Krauss RM. Lipidomic analysis of variation in response to simvastatin in the Cholesterol and Pharmacogenetics Study. Metabolomics. 2010 Jun;6:191-201.
  15. Li B, He X, Jia W, Li H. Novel applications of metabolomics in personalized medicine: a mini-review. Molecules. 2017 Jul 13;22(7):1173.
  16. He X, Zheng N, He J, Liu C, Feng J, Jia W, Li H. Gut microbiota modulation attenuated the hypolipidemic effect of simvastatin in high-fat/cholesterol-diet fed mice. Journal of proteome research. 2017 May 5;16(5):1900-10.
  17. Al-Hamadiny SQ, Salman RI, Najman SK, Dilfy SH, Qurabiy HE. Clinical Evaluation of Aspirin Effects on Gastrointestinal Tract and Circulatory System. NVEO-NATURAL VOLATILES & ESSENTIAL OILS Journal| NVEO. 2021 Nov 15:5328-43.
  18. Mason PJ, Jacobs AK, Freedman JE. Aspirin resistance and atherothrombotic disease. Journal of the American College of Cardiology. 2005 Sep 20;46(6):986-93.
  19. Yerges‐Armstrong LM, Ellero‐Simatos S, Georgiades A, Zhu H, Lewis JP, Horenstein RB, Beitelshees AL, Dane A, Reijmers T, Hankemeier T, Fiehn O. Purine pathway implicated in mechanism of resistance to aspirin therapy: pharmacometabolomics‐informed pharmacogenomics. Clinical pharmacology & Therapeutics. 2013 Oct;94(4):525-32.
  20. Hinton DJ, Vázquez MS, Geske JR, Hitschfeld MJ, Ho AM, Karpyak VM, Biernacka JM, Choi DS. Metabolomics biomarkers to predict acamprosate treatment response in alcohol-dependent subjects. Scientific reports. 2017 May 31;7(1):2496.
  21. Nam HW, Karpyak VM, Hinton DJ, Geske JR, Ho AM, Prieto ML, Biernacka JM, Frye MA, Weinshilboum RM, Choi DS. Elevated baseline serum glutamate as a pharmacometabolomic biomarker for acamprosate treatment outcome in alcohol-dependent subjects. Translational psychiatry. 2015 Aug;5(8):e621-.
  22. Asadipour E, Asgari M, Mousavi P, Piri‐Gharaghie T, Ghajari G, Mirzaie A. Nano‐Biotechnology and Challenges of Drug Delivery System in Cancer Treatment Pathway. Chemistry & Biodiversity. 2023 Mar 1:e202201072.
  23. Bell JA, Kivimaki M, Hamer M. Metabolically healthy obesity and risk of incident type 2 diabetes: a meta‐analysis of prospective cohort studies. Obesity reviews. 2014 Jun;15(6):504-15.
  24. Doosti A, Amini-Bavil-Olyaee S, Tajbakhsh E, Adeli A, Mahboudi F. Prevalence of viral hepatitis and molecular analysis of HBV among voluntary blood donors in west Iran. The new microbiologica. 2009 Apr 1;32(2):193.
  25. Piri Gharaghie T, Doosti A, Mirzaei SA. Detection of T6SS secretory system and membrane purine involved in antibiotic resistance in multidrug-resistant Acinetobacter baumannii isolates. Journal of Microbial World. 2021 May 22;14(1):47-58.
  26. Wang TJ, Larson MG, Vasan RS, Cheng S, Rhee EP, McCabe E, Lewis GD, Fox CS, Jacques PF, Fernandez C, O'donnell CJ. Metabolite profiles and the risk of developing diabetes. Nature medicine. 2011 Apr;17(4):448-53.
  27. Hashemzehi R, Doosti A, Kargar M, Jaafarinia M. Cloning and expression of nlpA gene as DNA vaccine candidate against Acinetobacter baumannii. Molecular biology reports. 2018 Aug;45:395-401.

 

 

Personalized and Precision Medicine Journal
Volume 9, Issue 32 - Serial Number 32
Original article
Winter 2024
Pages 23-28

  • Receive Date 05 December 2023
  • Revise Date 27 January 2024
  • Accept Date 26 February 2024

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