CLINICAL AND METABOLIC FEATURES OF THE KAZAKH POPULATION: SEARCH FOR BIOMARKERS OF THE AGE-ASSOCIATED PATHOLOGY BASED ON MULTIOMICS DATA
Introduction: The determination of variations in various metabolites can be used to predict disease risk and diagnosis, to understand molecular pathophysiology, to interpret an understanding of the effects of the environment and lifestyle, as well as to develop and evaluate drug efficacy, toxicity, and adverse reactions.
Purpose: in this work, we evaluated the clinical and metabolic features among the adult population living in Kazakhstan to identify and characterize metabolic biomarkers of age-associated pathology based on the analysis of multi-mix data.
Materials and methods: A one-stage trans-sectional study of healthy Kazakhs over 18 years old was performed. Plasma metabolome study in 60 individuals of Kazakh nationality on a platform using the tandem technology of ultrahigh liquid chromatography and mass spectroscopy (Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectroscopy (UPLC-MS / MS)) was conducted. Clinical and biochemical parameters in these individuals were also determined. The necessary logarithmic transformation and ANOVA analysis of variance, two-sample Welch t-test for determining bio compounds, which differed significantly between the experimental groups, were carried out.
Results: Metabolic changes estimated depending on age and the presence or absence of obesity. 692 different biochemical indicators of the main pathways of the metabolism of amino acids, peptides, nucleotides, carbohydrates, cofactors and vitamins, xenobiotics, lipid and energy metabolism were determined. Changes in several known metabolites and metabolic pathways were found in a group older than 45 years compared with a group of young individuals (metabolites associated with the exchange of fatty acids, steroidogenesis (biosynthesis of steroid hormones), with inflammation and oxidative stress.
Conclusions: Thus, the analysis of the metabolic profile of the blood allows one to take into account the influence of both internal (endogenous) and external (exogenous) factors affecting the body, for example, xenobiotics, drugs, etc., which makes it a universal and promising source of age-related clinical biomarkers associated pathology.
Ainur R. Akilzhanova1, http://orcid.org/0000-0001-6161-8355
Ulan A. Kozhamkulov1, http://orcid.org/0000-0002-9782-7631
Saule Е. Rakhimova1, http://orcid.org/0000-0002-8245-2400
Ulykbek Е. Kairov1, http://orcid.org/ 0000-0001-8511-8064
Dauren А. Yerezhepov1, http://orcid.org/ 0000-0002-4161-1348
Sholpan N. Askarova2, http://orcid.org/0000-0001-6161-1671
Almagul R. Kushugulova3, orcid.org/0000-0001-9479-0899
1 Laboratory of Genomic and Personalized Medicine, Center for Life Sciences, National Laboratory Astana, Nazarbayev University, Nur-Sultan city, Republic of Kazakhstan;
2 Laboratory of Bioengineering and Regenerative Medicine, Center for Life Sciences,
National Laboratory Astana, Nazarbayev University, Nur-Sultan city, Republic of Kazakhstan;
3 Laboratory of Human Microbiome and Longevity, Center for Life Sciences, National Laboratory Astana, Nazarbayev University, Nur-Sultan city, Republic of Kazakhstan.
1. Adamski J., Suhre K. Metabolomics platforms for genome wide association studies – linking the genome to the metabolome // Current opinion in biotechnology. – 2013. V.24. P. 39-47.
2. Akanov A.A., Tulebaev K.A., Eshmanova A.K., Chaĭkovskaia V.V., Abikulova A.K., Kalmakhanov S.B., Mansharipova A.T. Analysis of condition and prospects in geriatric care of population of Kazakhstan // Adv Gerontol. 2014. V.27(3). P.589-95
3. Dharuri H., Demirkan A., Klinken J., Mook-Kanamori D., Duijin C., Hoen P., Dijk K. Genetics of the human metabolome, what is next? // Biochimica et Biophysica Acta 1842. 2014. P. 1923 – 1931.
4. Dunn W., LinW, Broadhurst D., Begley P., Brown M., Zelena E., Vaughan A. Molecular phenotyping of a UK population: defining the human serum metabolome // Metabolomics. 2015. V11. P. 9 – 26.
5. Guo L., Milburn M., Ryals J., Lonergan S., Mitchell M., Wulf J., Alexander A., Evans A., Bridgewater B., Miller L., Gonzalez-Garay M., Caskey T. Plasma metabolomics profiles enhance precision medicine for volunteers of normal health // PNAS. 2015 P. 4901–4910.
6. Jordan K.W., Nordenstam J., Lauwers G.Y., Rothenberger D.A., Alavi K., Garwood M., Cheng L.L. «Metabolomic characterization of human rectal adenocarcinoma with intact tissue magnetic resonance spectroscopy» // Diseases of the Colon & Rectum. 2009. 52(3). P.520–5.
7. Oshakbayev K.P., Kenneth Alibek, Ponomarev I.O., Dukenbayeva B.A., Uderbayev N.N., Oshakbayev P., Mustafin H. The heating value of a different location of human body lipids // Global Journal of Medical Research. 2014. Vol.13(7). P.19-23.
8. Oshakbayev K.P., Kenneth Alibek, Ponomarev I.O., Uderbayev N.N., Dukenbayeva B.A., Gazaliyeva M., Oshakbayev P., Kaliyeva Sh. Body fats accumulate metabolic products: physical and chemical analysis in vitro // American Journal of Medical and Biological Research. 2014. V.2(1). P.5-11.
9. Suhre K., Raffler J., Kastenmuller G. Biochemical insights from population studies with genetics and metabolomics // Archives of biochemistry and biophysics. 2016. V.589. P.168-176.
10. Yan W., Yang X., Zheng Y., Ge D., Zhang Y., Shan Z., Simu H., Sukerobai M., Wang R. The metabolic syndrome in Uygur and Kazak populations // Diabetes Care. 2005. V.28(10). P. 2554-5.
11. Wishart D.S., Tzur D., Knox C., et al. HMDB: the Human Metabolome Database // Nucleic Acids Research 35. 2006. (Database issue): D521–6.
12. Wishart D.S., Knox C., Guo A.C., Eisner R., Young N., Gautam B., Hau D.D., Psychogios N. et al. HMDB: a knowledgebase for the human metabolome // Nucleic Acids Research 37. 2007. (Database issue): D603.
13. WHO. Highlights on health in Kazakhstan. 1999. 120 p.
14. Zalesin K.C., Franklin B.A., Miller W.M., Peterson E.D., Mc Cullough P.A. Impact of obesity on cardiovascular disease // The Medical clinics of North America. 2011. V.95(5). P.919-937.
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Akilzhanova A.R., Kozhamkulov U.A., Rakhimova S.Е., Kairov U.Е., Yerezhepov D.А., Askarova Sh.N., Kushugulova A.R. Clinical and metabolic features of the kazakh population: search for biomarkers of the age-associated pathology based on multiomics data // Nauka i Zdravookhranenie [Science & Healthcare]. 2019, (Vol.21) 5, pp. 53-67.Related publications:
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