Integrating metabolomics into obesity care: towards biomarker guided pharmacy practice
Main Article Content
Keywords
Obesity, Overweight, Metabolomics, Metabolites, Metabolic pathways
Abstract
Background: Obesity is a complex and prevalent global health issue strongly associated with chronic diseases. Early diagnosis and precise monitoring remain challenging due to the complex metabolic dysregulation underlying obesity. Metabolomics provides a powerful tool to investigate biochemical changes and discover novel diagnostic biomarkers. Objectives: This study used untargeted metabolomics of human plasma samples to identify distinct plasma metabolite profiles and altered metabolic pathways in overweight and obese individuals. The ultimate goal is to improve obesity management through early diagnosis and personalized treatments. Methods: A total of 74 Jordanian participants were recruited and categorized into normal-weight (n=29), overweight (n=17), and obese (n=28) groups based on BMI and metabolic parameters. Plasma samples were analyzed using ultra-high-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). Data processing and statistical analysis were performed using MetaboScape and MetaboAnalyst 5.0. Group comparisons were evaluated using t-tests, ANOVA, and multivariate models, and pathway enrichment analysis was conducted to determine altered metabolic pathways. Results: A total of 82 metabolites were identified, with 26 showing significant differences between groups. In the overweight group, pantothenic acid and L-proline were elevated, while phenylacetaldehyde and glycerophosphocholine were decreased. The obese group exhibited increased levels of L-leucine, L-tryptophan, phenylalanine, and tyrosine, and reduced levels of 2,3-diaminopropionic acid and phenylacetaldehyde. Key altered pathways included pantothenate and CoA biosynthesis, beta-alanine metabolism, phenylalanine and tyrosine metabolism, and beta-oxidation of long-chain fatty acids. Conclusions: The study revealed significant novel metabolic disturbances associated with overweight and obesity, highlighting potential diagnostic biomarkers and perturbed metabolic pathways. These findings provide valuable insights into the molecular underpinnings of obesity, underscore the potential of metabolomics in advancing personalized approaches for managing obesity, and warrant further validation in larger, diverse populations to assess their diagnostic and clinical relevance.
References
2. Kelly T, Yang W, Chen CS, Reynolds K, He J. Global burden of obesity in 2005 and projections to 2030. Int J Obes (Lond). 2008;32(9):1431-1437.
3. Stein CJ, Colditz GA. The epidemic of obesity. J Clin Endocrinol Metab. 2004;89(6):2522-2525.
4. Afshin A, Forouzanfar MH, Reitsma MB, Sur P, Estep K, Lee A, et al. Health effects of overweight and obesity in 195 countries over 25 years. N Engl J Med. 2017;377(1):13-27.
5. Abufares HI, Zenati RA, Soares NC, El-Huneidi W, Dahabiyeh LA, Al-Hroub HM, et al. A non-targeted metabolomics comparative study on plasma of Pfizer and Sinopharm COVID-19 vaccinated individuals assessed by TIMS-QTOF mass spectrometry. Heliyon. 2024;10(15):e35443.
6. Kim DH, Kim YS, Son NI, Kang CK, Kim AR. Recent omics technologies and their emerging applications for personalised medicine. IET Syst Biol. 2017;11(3):87-98.
7. Qi S, Wu Q, Chen Z, Zhang W, Zhou Y, Mao K, et al. High-resolution metabolomic biomarkers for lung cancer diagnosis and prognosis. Sci Rep. 2021;11(1):1-10.
8. Alsoud LO, Soares NC, Al-Hroub HM, Mousa M, Kasabri V, Bulatova N, et al. Identification of insulin resistance biomarkers in metabolic syndrome detected by UHPLC-ESI-QTOF-MS. Metabolites. 2022;12(6).
9. Wishart DS. Metabolomics for investigating physiological and pathophysiological processes. Physiol Rev. 2019;99(4):1819-1875.
10. Alberti KGMM, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome. Circulation. 2009;120(16):1640-1645.
11. Zenati RA, Giddey AD, Al-Hroub HM, Hagyousif YA, El-Huneidi W, Bustanji Y, et al. Evaluation of two simultaneous metabolomic and proteomic extraction protocols assessed by UHPLC-MS/MS. Int J Mol Sci. 2023;24(2).
12. Sharaf BM, Giddey AD, Alniss H, Al-Hroub HM, El-Awady R, Mousa M, et al. Untargeted metabolomics of breast cancer cells MCF-7 and SkBr3 treated with tamoxifen/trastuzumab. Cancer Genomics Proteomics. 2022;19(1):79-93.
13. Jové M, Mauri-Capdevila G, Suárez I, Cambray S, Sanahuja J, Quílez A, et al. Metabolomics predicts stroke recurrence after transient ischemic attack. Neurology. 2015;84(1):36-45.
14. Syme C, Czajkowski S, Shin J, Abrahamowicz M, Leonard G, Perron M, et al. Glycerophosphocholine metabolites and cardiovascular disease risk factors in adolescents. Circulation. 2016;134(21):1629-1636.
15. Singh A, Kinnebrew G, Hsu PC, Weng DY, Song MA, Reisinger SA, et al. Untargeted metabolomics and body mass in adolescents: a cross-sectional and longitudinal analysis. Metabolites. 2023;13(8).
16. Liu Z, Jeppesen PB, Gregersen S, Bach Larsen L, Hermansen K. Chronic exposure to proline causes aminoacidotoxicity and impaired beta-cell function. Rev Diabet Stud. 2016;13(1):66-78.
17. Vettore LA, Westbrook RL, Tennant DA. Proline metabolism and redox: maintaining a balance in health and disease. Amino Acids. 2021;53(12):1779-1788.
18. Moran-Ramos S, Ocampo-Medina E, Gutierrez-Aguilar R, Macías-Kauffer L, Villamil-Ramírez H, López-Contreras BE, et al. An amino acid signature associated with obesity predicts risk of hypertriglyceridemia in children. Sci Rep. 2017;7:5607.
19. Ho JE, Larson MG, Ghorbani A, Cheng S, Chen MH, Keyes M, et al. Metabolomic profiles of body mass index in the Framingham Heart Study. PLoS One. 2016;11(2):e0148361.
20. Li Q, Gu W, Ma X, Liu Y, Jiang L, Feng R, et al. Amino acid and biogenic amine profile deviations in oral glucose tolerance tests. Nutrients. 2016;8(6).
21. Libert DM, Nowacki AS, Natowicz MR. Metabolomic analysis of obesity, metabolic syndrome, and type 2 diabetes. PeerJ. 2018;6:e5410.
22. Adams SH. Emerging perspectives on essential amino acid metabolism in obesity and insulin resistance. Adv Nutr. 2011;2(6):445-456.
23. Fernstrom JD. Branched-chain amino acids and brain function. J Nutr. 2005;135(6 Suppl):1539S-1546S.
24. Liao C, Wang B, Gao W, Cao W, Lv J, Yu C, et al. Associations of obesity measurements with serum metabolomic profile. Twin Res Hum Genet. 2021;24(1):14-21.
25. Chen HH, Tseng YJ, Wang SY, Tsai YS, Chang CS, Kuo TC, et al. Metabolome profiling in metabolic healthy and abnormal obesity. Int J Obes. 2015;39(8):1241-1248.
26. Caballero B. Humans against obesity: who will win? Adv Nutr. 2019;10(Suppl 1):S4-S9.
27. Piening BD, Zhou W, Contrepois K, Röst H, Gu Urban GJ, Mishra T, et al. Integrative personal omics profiles during weight gain and loss. Cell Syst. 2018;6(2):157-170.
28. Komoda T, Matsunaga T. Metabolic pathways in the human body. In: Biochemistry for Medical Professionals. Boston: Academic Press; 2015. p.25-63.
29. Zouhal H, Lemoine-Morel S, Mathieu ME, Casazza GA, Jabbour G. Catecholamines and obesity: effects of exercise and training. Sports Med. 2013;43(7):591-600.
30. Miller GD. Appetite regulation: hormones, peptides, and neurotransmitters and their role in obesity. Am J Lifestyle Med. 2019;13(6):586-601.
31. Yu E, Papandreou C, Ruiz-Canela M, Guasch-Ferre M, Clish CB, Dennis C, et al. Association of tryptophan metabolites with incident type 2 diabetes. Clin Chem. 2018;64(8):1211-1220.
32. Favennec M, Hennart B, Caiazzo R, Leloire A, Yengo L, Verbanck M, et al. The kynurenine pathway is activated in human obesity. Obesity (Silver Spring). 2015;23(10):2066-2074.
33. Munipally PK, Agraharm SG, Valavala VK, Gundae S, Turlapati NR. Evaluation of indoleamine 2,3-dioxygenase expression and kynurenine metabolites in diabetic retinopathy. Arch Physiol Biochem. 2011;117(5):254-258.
34. Huang T, Song J, Gao J, Cheng J, Xie H, Zhang L, et al. Adipocyte-derived kynurenine promotes obesity and insulin resistance. Nat Commun. 2022;13(1):3489.
35. Dadvar S, Ferreira DMS, Cervenka I, Ruas JL. Kynurenine metabolites in obesity and exercise. J Intern Med. 2018;284(5):519-533.
36. Rangel-Huerta OD, Pastor-Villaescusa B, Gil A. Metabolomic signature of human obesity: a systematic review. Metabolomics. 2019;15(6):93.
37. Mking. Amino acid derivatives: neurotransmitters, nitric oxide, and more. The Medical Biochemistry Page. 2023.
38. Fanet H, Capuron L, Castanon N, Calon F, Vancassel S. Tetrahydrobiopterin pathway: from metabolism to neuropsychiatry. Curr Neuropharmacol. 2021;19(5):591-609.
39. Zhang L, Ussher JR, Oka T, Cadete VJJ, Wagg C, Lopaschuk GD. Cardiac diacylglycerol accumulation in high fat-fed mice. Cardiovasc Res. 2011;89(1):148-156.
40. Peterson LR, Herrero P, Schechtman KB, Racette SB, Waggoner AD, Kisrieva-Ware Z, et al. Effect of obesity and insulin resistance on myocardial substrate metabolism. Circulation. 2004;109(18):2191-2196.
41. Herrero P, Peterson LR, McGill JB, Matthew S, Lesniak D, Dence C, et al. Increased myocardial fatty acid metabolism in type 1 diabetes. J Am Coll Cardiol. 2006;47(3):598-604.
42. Ding S, Chen M, Liao Y, Chen Q, Lin X, Chen S, et al. Serum metabolic profiles of Chinese women with perimenopausal obesity. Front Endocrinol. 2021;12:637317.
43. Wu ZP, Wei W, Cheng Y, Chen JY, Liu Y, Liu S, et al. Altered adolescent obesity metabolism associated with hypertension. Front Endocrinol. 2023;14:1172290.
44. Ferrandez A, Prieto MA, Garcia JL, Diaz E. Molecular characterization of PadA from Escherichia coli. FEBS Lett. 1997;406(1-2):23-27.
45. Guo Z, Hu B, Zhu L, Yang Y, Liu C, Liu F, et al. Microbiome-metabolomics insights into high-fat diet mice feces. Food Res Int. 2022;156:111024.
46. Clements JN, Albanese NP, D’Souza JJ, Misher A, Reece S, Trujillo J, et al. Role of clinical pharmacists in obesity management. J Am Coll Clin Pharm. 2021;4(11):1469-1484.
47. Yan L, Reese T, Nelson SD. Clinical decision support for inpatient clinical pharmacists. Appl Clin Inform. 2021;12(2):199-207.
48. Francis BR, Challen LM. Impact of a clinical pharmacist in an interdisciplinary weight loss service. Innovations in Pharmacy. 2021;12(4).
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