Search for metabolomic markers of hypertensive conditions of different genesis: Experimental study

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Abstract

A personalized approach to the diagnosis and treatment of arterial hypertension requires a comprehensive analysis of the pathogenetic mechanisms underlying the disease. To determine specific metabolomic markers of various hypertensive conditions, four groups of experimental animals were studied: WAG rats (normotensive control); ISIAH rats with inherited stress-induced arterial hypertension (AH); L-NAME-treated rats with hypertension induced by endothelial dysfunction; rats with hypertension caused by DOCA administration in combination with the salt loading. Rat blood serum samples were analyzed by NMR spectroscopy. The metabolomic analysis differentiated the hypertensive conditions of various origins using group-specific blood serum metabolomic biomarkers. Rats with DOCA-salt hypertension are characterized by increased concentration of choline. Hypertension associated with endothelial dysfunction induced by L-NAME administration was accompanied by a decrease in the levels of tyrosine, serine and glycine. Distinctive features of ISIAH rats are increased concentrations of ornithine (urea and nitric oxide cycle), valine, leucine, isoleucine, myo-inositol, glutamate, glutamine (glucose metabolism).

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About the authors

А. А. Seryapina

Federal Research Center Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences

Author for correspondence.
Email: seryapina@bionet.nsc.ru
Russian Federation, Novosibirsk

А. А. Sorokoumova

Federal Research Center Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences

Email: seryapina@bionet.nsc.ru
Russian Federation, Novosibirsk

Yu. К. Polityko

Federal Research Center Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences; Federal State Budgetary Scientific Institution “Research Institute of Neuroscience and Medicine”

Email: seryapina@bionet.nsc.ru
Russian Federation, Novosibirsk; Novosibirsk

L. V. Yanshole

Institute “International Tomographic Center”, Siberian Branch of the Russian Academy of Sciences

Email: seryapina@bionet.nsc.ru
Russian Federation, Novosibirsk

Yu. P. Tsentalovich

Institute “International Tomographic Center”, Siberian Branch of the Russian Academy of Sciences

Email: seryapina@bionet.nsc.ru
Russian Federation, Novosibirsk

М. А. Gilinsky

Federal State Budgetary Scientific Institution “Research Institute of Neuroscience and Medicine”

Email: seryapina@bionet.nsc.ru
Russian Federation, Novosibirsk

А. L. Markel

Federal Research Center Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences; Novosibirsk State University

Email: seryapina@bionet.nsc.ru
Russian Federation, Novosibirsk; Novosibirsk

References

  1. Byrd JB (2016) Personalized medicine and treatment approaches in hypertension: current perspectives. Integr Blood Press Contr 9: 59–67. https://doi.org/10.2147/IBPC.S74
  2. De Jong W, Birkenhäger WH, Reid JL (Eds) (2013) Experimental and Genetic Models of Hypertension. Handbook of Hypertension, Elsevier.
  3. Schenk J, McNeill JH (1992) The pathogenesis of DOCA-salt hypertension. J Pharmacol Toxicol Meth 27(3): 161–170. https://doi.org/10.1016/1056-8719(92)90036-Z
  4. Küng CF, Moreau P, Takase H, Lüscher TF (1995) L-NAME hypertension alters endothelial and smooth muscle function in rat aorta: prevention by trandolapril and verapamil. Hypertension 26(5): 744–751. https://doi.org/10.1161/01.HYP.26.5.744
  5. Markel AL (1992) Development of a new strain of rats with inherited stress-induced arterial hypertension. In Genetic Hypertension. (Ed.J. Sassard), Colloque INSERM John Libbey Eurotext Ltd 218: 405–407.
  6. Redina OE, Markel AL (2018) Stress, genes, and hypertension. Contribution of the ISIAH rat strain study. Curr Hyperten Rep 20: 1–10. https://doi.org/10.1007/s11906-018-0870-2
  7. Kulkarni S, O’Farrell I, Erasi M, Kochar MS (1998) Stress and hypertension. Wisconsin Med J 97(11): 34–38.
  8. Hudzinski LG, Frohlich ED, Holloway RD (1988) Hypertension and stress. Clin Cardiol 11(9): 622–626. https://doi.org/10.1002/clc.4960110906
  9. Freeman ZS (1990) Stress and hypertension – critical review. Med J Austral 153(10): 621–625. https://doi.org/10.5694/j.1326-5377.1990.tb126276.x
  10. Fürstenau CR, da Silva Trentin D, Gossenheimer AN, Ramos DB, Casali EA, Barreto-Chaves MLM, Sarkis JJF (2008) Ectonucleotidase activities are altered in serum and platelets of L-NAME-treated rats. Blood Cell Mol Diseas 41(2): 223–229. https://doi.org/10.1016/j.bcmd.2008.04.009
  11. Chan V, Hoey A, Brown L (2006) Improved cardiovascular function with aminoguanidine in DOCA‐salt hypertensive rats. British J Pharmacol 148(7): 902–908. https://doi.org/10.1038/sj.bjp.0706801
  12. Snytnikova OA, Khlichkina AA, Sagdeev RZ, Tsentalovich YP (2019) Evaluation of sample preparation protocols for quantitative NMR-based metabolomics. Metabolomics 15: 1–9. https://doi.org/10.1007/s11306-019-1545-y
  13. Zelentsova EA, Yanshole LV, Snytnikova OA, Yanshole VV, Tsentalovich YP, Sagdeev RZ (2016) Post-mortem changes in the metabolomic compositions of rabbit blood, aqueous and vitreous humors. Metabolomics 12: 1–11. https://doi.org/10.1007/s11306-016-1118-2
  14. Hollenbeck CB (2012) An introduction to the nutrition and metabolism of choline. Central Nervous Syst Agent Med Chem 12(2): 100–113. https://doi.org/10.2174/187152412800792689
  15. Corbin KD, Zeisel SH (2012) Choline metabolism provides novel insights into non-alcoholic fatty liver disease and its progression. Curr Opin Gastroenterol 28(2): 159. https://doi.org/10.1097/MOG.0b013e32834e7b4b
  16. Morris AJ, Frohman MA, Engebrecht J (1997) Measurement of phospholipase D activity. Analyt Biochem 252(1): 1–9. https://doi.org/10.1006/abio.1997.2299
  17. O’Brien KD, Pineda C, Chiu WS, Bowen R, Deeg MA (1999) Glycosylphosphatidylinositol-specific phospholipase D is expressed by macrophages in human atherosclerosis and colocalizes with oxidation epitopes. Circulation 99(22): 2876–2882. https://doi.org/10.1161/01.CIR.99.22.2876
  18. Danne O, Möckel M, Lueders C, Mügge C, Zschunke GA, Lufft H, Müller C, Frei U (2003) Prognostic implications of elevated whole blood choline levels in acute coronary syndromes. American J Cardiol 91(9): 1060–1067. https://doi.org/10.1016/s0002-9149(03)00149-8
  19. Kwiatkowska I, Hermanowicz JM, Mysliwiec M, Pawlak D (2020) Oxidative storm induced by tryptophan metabolites: missing link between atherosclerosis and chronic kidney disease. Oxidat Med Cell Longevity ID6656033. https://doi.org/10.1155/2020/6656033
  20. Konje VC, Rajendiran TM, Bellovich K, Gadegbeku CA, Gipson DS, Afshinnia F, Mathew AV (2021) Tryptophan levels associate with incident cardiovascular disease in chronic kidney disease. Clin Kidney J 14(4): 1097–1105. https://doi.org/10.1093/ckj/sfaa031
  21. Saito K, Fujigaki S, Heyes MP, Shibata K, Takemura M, Fujii H, Wada H, Noma A, Seishima M (2000) Mechanism of increases in L-kynurenine and quinolinic acid in renal insufficiency. Am J Physiol-Renal Physiol 279(3): F565–F572. https://doi.org/10.1152/ajprenal.2000.279.3.F565
  22. Roager HM, Licht TR (2018) Microbial tryptophan catabolites in health and disease. Nat Communicat 9(1): 3294. https://doi.org/10.1038/s41467-018-05470-4
  23. Wilck N, Matus MG, Kearney SM, Olesen SW, Forslund K, Bartolomaeus H, Müller DN (2017) Salt-responsive gut commensal modulates TH17 axis and disease. Nature 551(7682): 585–589. https://doi.org/10.1038/nature24628
  24. Guimarães S, Moura D (2001) Vascular adrenoceptors: an update. Pharmacological reviews 53(2): 319–356.
  25. Missale C, Nash SR, Robinson SW, Jaber M, Caron MG (1998) Dopamine receptors: from structure to function. Physiol Rev 78(1): 189–225. https://doi.org/10.1152/physrev.1998.78.1.189
  26. De Koning TJ, Klomp LW (2004) Serine-deficiency syndromes. Curr Opin Neurol 17(2): 197–204. https://doi.org/10.1097/00019052-200404000-00019
  27. Brawley L, Torrens C, Anthony FW, Itoh S, Wheeler T, Jackson AA, Clough GF, Poston L, Hanson MA (2004) Glycine rectifies vascular dysfunction induced by dietary protein imbalance during pregnancy. J Physiol 554(2): 497–504. https://doi.org/10.1113/jphysiol.2003.052068
  28. Le Maistre JL, Sanders SA, Stobart MJ, Lu L, Knox JD, Anderson HD, Anderson CM (2012) Coactivation of NMDA receptors by glutamate and D-serine induces dilation of isolated middle cerebral arteries. J Cerebr Blood Flow Metabol 32(3): 537–547. https://doi.org/10.1038/jcbfm.2011.161
  29. Sadagopan N, Li W, Roberds SL, Major T, Preston GM, Yu Y, Tones MA (2007) Circulating succinate is elevated in rodent models of hypertension and metabolic disease. Am J Hypertens 20(11): 1209–1215. https://doi.org/10.1016/j.amjhyper.2007.05.010
  30. Akira K, Masu S, Imachi M, Mitome H, Hashimoto M, Hashimoto T (2008) 1H NMR-based metabonomic analysis of urine from young spontaneously hypertensive rats. J Pharmaceut Biomed Analys 46(3): 550–556. https://doi.org/10.1016/j.jpba.2007.11.017
  31. Lucas PA, Lacour B, McCarron DA, Drüeke T (1987) Disturbance of acid-base balance in the young spontaneously hypertensive rat. Clin Sci 73(2): 211–215. https://doi.org/10.1042/cs0730211
  32. Carrero JJ, Grimble RF (2006) Does nutrition have a role in peripheral vascular disease? British J Nutrit 95(2): 217–229. https://doi.org/10.1079/BJN20051616
  33. Pluznick JL (2017) Microbial short-chain fatty acids and blood pressure regulation. Current hypertension reports 19: 1–5. https://doi.org/ 10.1007/s11906-017-0722-5
  34. Chen XF, Chen X, Tang X (2020) Short-chain fatty acid, acylation and cardiovascular diseases. Clin Sci 134(6): 657–676. https://doi.org/0.1042/CS20200128
  35. Gstraunthaler G, Holcomb T, Feifel E, Liu W, Spitaler N, Curthoys NP (2000) Differential expression and acid-base regulation of glutaminase mRNAs in gluconeogenic LLC-PK(1)-FBPase(+) cells. Am J Physiol 278: F227–F237. https://doi.org/10.1152/ajprenal.2000.278.2.F227
  36. Huang XT, Li C, Peng XP, Guo J, Yue SJ, Liu W, Zhao FY, Han JZ, Huang YH, Li Y, Cheng QM, Zhou ZG, Chen C, Feng DD, Luo ZQ (2017) An excessive increase in glutamate contributes to glucose-toxicity in β-cells via activation of pancreatic NMDA receptors in rodent diabetes. Scientif rep 7(1): 44120. https://doi.org/10.1038/srep44120
  37. Liu X, Zheng Y, Guasch-Ferré M, Ruiz-Canela M, Toledo E, Clish C, Liang L, Razquin C, Corella D, Estruch R, Fito M, Gómez-Gracia E, Arós F, Ros E, Lapetra J, Fiol M, Serra-Majem L, Papandreou C, Martínez-González MA, Hu FB, Salas-Salvadó J (2019) High plasma glutamate and low glutamine-to-glutamate ratio are associated with type 2 diabetes: case-cohort study within the PREDIMED trial. Nutrit Metabol Cardiovascul Diseas 29(10): 1040–1049. https://doi.org/10.1016/j.numecd.2019.06.005
  38. Yoshizawa F (2012) New therapeutic strategy for amino acid medicine: notable functions of branched chain amino acids as biological regulators. J Pharmacol Sci 118(2): 149–155. https://doi.org/10.1254/jphs.11R05FM
  39. Yoon MS (2016) The emerging role of branched-chain amino acids in insulin resistance and metabolism. Nutrients 8(7): 405. https://doi.org/10.3390/nu8070405
  40. Arrieta-Cruz I, Su Y, Gutiérrez-Juárez R (2016) Suppression of endogenous glucose production by isoleucine and valine and impact of diet composition. Nutrients 8(2): 79. https://doi.org/10.3390/nu8020079
  41. Croze ML, Soulage CO (2013) Potential role and therapeutic interests of myo-inositol in metabolic diseases. Biochimie 95(10): 1811–1827. https://doi.org/10.1016/j.biochi.2013.05.011
  42. Abou-Saleh H, Pathan AR, Daalis A, Hubrack S, Abou-Jassoum H, Al-Naeimi H, Rusch NJ, Machaca K (2013) Inositol 1,4,5-trisphosphate (IP3) receptor up-regulation in hypertension is associated with sensitization of Ca2+ release and vascular smooth muscle contractility. J Biol Chem 288(46): 32941–32951. https://doi.org/10.1074/jbc.M113.496802
  43. Snider SA, Margison KD, Ghorbani P, LeBlond ND, O’Dwyer C, Nunes JR, Xu H, Bennett S, Fullerton MD (2018) Choline transport links macrophage phospholipid metabolism and inflammation. J Biol Chem 293(29): 11600–11611. https://doi.org/10.1074/jbc.RA118.003180
  44. Kagitani S, Ueno H, Hirade S, Takahashi T, Takata M, Inoue H (2004) Tranilast attenuates myocardial fibrosis in association with suppression of monocyte/macrophage infiltration in DOCA/salt hypertensive rats. J Hypertens 22(5): 1007–1015.
  45. Ishimaru K, Ueno H, Kagitani S, Takabayashi D, Takata M, Inoue H (2007) Fasudil attenuates myocardial fibrosis in association with inhibition of monocyte/macrophage infiltration in the heart of DOCA/salt hypertensive rats. J Cardiovascul Pharmacol 50(2): 187–194. https://doi.org/10.1097/FJC.0b013e318064f150
  46. Kubo T, Fukumori R, Kobayashi M, Yamaguchi H (1996) Enhanced cholinergic activity in the medulla oblongata of DOCA-salt hypertensive and renal hypertensive rats. Hypertens Res 19(3): 213–219. https://doi.org/10.1291/hypres.19.213
  47. Kvetňanský R, Pacák K, Tokarev D, Jeloková J, Ježová D, Rusnák M (1997) Chronic blockade of nitric oxide synthesis elevates plasma levels of catecholamines and their metabolites at rest and during stress in rats. Neurochem Res 22: 995–1001. https://doi.org/10.1023/A:1022426910111
  48. Mishra RC, Tripathy S, Quest D, Desai KM, Akhtar J, Dattani ID, Gopalakrishnan V (2008) L-Serine lowers while glycine increases blood pressure in chronic L-NAME-treated and spontaneously hypertensive rats. J Hypertens 26(12): 2339–2348. https://doi.org/ 10.1097/HJH.0b013e328312c8a3
  49. Gilinsky MA, Polityko YK, Markel AL, Latysheva TV, Samson AO, Polis B, Naumenko SE (2020) Norvaline reduces blood pressure and induces diuresis in rats with inherited stress-induced arterial hypertension. BioMed Res Internat 2020: 4935386. https://doi.org/10.1155/2020/4935386
  50. Shorin IP, Markel AL, Seliatitskaia VG, Pal’chikova NA, Grinberg PM, Amstislavskii SI (1990) Endocrine-metabolic relations in rats with inherited stress-induced arterial hypertension. Bull Exp Biol Med 109(6): 768–770. https://doi.org/10.1007/BF00841441

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2. Fig. 1. Intergroup differences (ISIAH, L-NAME, DOCA vs WAG) in concentrations of metabolites associated with choline metabolism (choline, betaine), renal function (tryptophan), and tyrosine metabolism (phenylalanine, tyrosine). The Mann–Whitney criterion, * – p < 0.05, ** – p < 0.01, *** – p < 0.001.

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3. Fig. 2. Intergroup differences (ISIAH, L-NAME, DOCA vs WAG) in concentrations of metabolites associated with glycine metabolism (glycine, serine), Krebs cycle (citrate, succinate), and oxidative metabolism (carnitine, acetylcarnitine ). The Mann–Whitney criterion, * – p < 0.05, ** – p < 0.01, *** – p < 0.001.

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4. Fig. 3. Intergroup differences (ISIAH, L-NAME, DOCA vs WAG) in concentrations of metabolites associated with the activity of the intestinal microbiota (isobutyrate, formate, 3-methyl‑2-oxovalerate, 3-hydroxybutyrate, 2- hydroxyisobutyrate, 3-hydroxyisobutyrate, acetate, acetoacetate, acetone). The Mann–Whitney criterion, * – p < 0.05, ** – p < 0.01, *** – p < 0.001.

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5. Fig. 4. Intergroup differences (ISIAH, L-NAME, DOCA vs WAG) in concentrations of metabolites associated with the cycle of urea and nitric oxide (ornithine), as well as glutamate and glutamine. The Mann–Whitney criterion, * – p < 0.05, ** – p < 0.01, *** – p < 0.001.

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6. Fig. 5. Intergroup differences (ISIAH, L-NAME, DOCA vs WAG) in concentrations of metabolites associated with glucose metabolism (valine, leucine, isoleucine, glucose, glycerol, myo-inositol). The Mann–Whitney criterion, * – p < 0.05, ** – p < 0.01, *** – p < 0.001.

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