Preliminary study of metabonomic changes during the progression of atherosclerosis in miniature pigs

Abstract

Background: To explore potential biomarkers for early diagnosis of atherosclerosis (AS) and provide basic data for further research on AS, the characteristics of serum metabolomics during the progression of AS in mini-pigs were observed dynamically.

Methods: An AS model in Bama miniature pigs was established by a high-cholesterol and high-fat diet. Fasting serum samples were collected monthly for metabolomics and serum lipid detection. At the end of the treatment period, pathological analysis of the abdominal aorta and coronary artery was performed to evaluate the lesions of AS, thereby distinguishing the susceptibility of mini-pigs to AS. The metabolomics was detected using a high-resolution untargeted metabolomic approach. Statistical analysis was used to identify metabolites associated with AS susceptibility.

Results: Based on pathological analysis, mini-pigs were divided into two groups: a susceptible group (n = 3) and a non-susceptible group (n = 6). A total of 1318 metabolites were identified, with significant shifting of metabolic profiles over time in both groups. Dynamic monitoring analysis highlighted 57 metabolites that exhibited an obvious trend of differential changes between two groups with the advance of time. The KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis indicated significant disorders in cholesterol metabolism, primary bile acid metabolism, histidine metabolism, as well as taurine and hypotaurine metabolism.

Conclusions: During the progression of AS in mini-pigs induced by high-cholesterol/high-fat diet, the alterations in serum metabolic profile exhibited a time-dependent pattern, accompanied by notable disturbances in lipid metabolism, cholesterol metabolism, and amino acid metabolism. These metabolites may become potential biomarkers for early diagnosis of AS.

Keywords

atherosclerosis / metabolomics / miniature pig / susceptibility

References

[1] LibbyP, BuringJE, BadimonL, et al. Atherosclerosis. Nat Rev Dis Prim. 2019;5(1):56.

[2] Di CesareM, PerelP, TaylorS, et al. The heart of the world. Glob Heart. 2024;19(1):11.

[3] VaduganathanM, MensahGA, TurcoJV, Fuster V, RothGA. The global burden of cardiovascular diseases and risk: a compass for future health. J Am Coll Cardiol. 2022;80(25):2361-2371.

[4] LechnerK, von Schacky C, McKenzieAL, et al. Lifestyle factors and high-risk atherosclerosis: pathways and mechanisms beyond traditional risk factors. Eur J Prev Cardiol. 2020;27(4):394-406.

[5] AboonabiA, MeyerRR, SinghI. The association between metabolic syndrome components and the development of atherosclerosis. J Hum Hypertens. 2019;33(12):844-855.

[6] LusisAJ. Atherosclerosis. Nature. 2000;407(6801):233-241.

[7] SchombergDT, TellezA, MeudtJJ, et al. Miniature swine for preclinical modeling of complexities of human disease for translational scientific discovery and accelerated development of therapies and medical devices. Toxicol Pathol. 2016;44(3):299-314.

[8] ShimJ, Al-Mashhadi RH, SorensenCB, BentzonJF. Large animal models of atherosclerosis—new tools for persistent problems in cardiovascular medicine. J Pathol. 2016;238(2):257-266.

[9] HamamdzicD, Wilensky RL. Porcine models of accelerated coronary atherosclerosis: role of diabetes mellitus and hypercholesterolemia. J Diabetes Res. 2013;2013:761415.

[10] GranadaJF, KaluzaGL, WilenskyRL, Biedermann BC, SchwartzRS, FalkE. Porcine models of coronary atherosclerosis and vulnerable plaque for imaging and interventional research. EuroIntervention. 2009;5(1):140-148.

[11] RennerS, Dobenecker B, BlutkeA, et al. Comparative aspects of rodent and nonrodent animal models for mechanistic and translational diabetes research. Theriogenology. 2016;86(1):406-421.

[12] BährA, WolfE. Domestic animal models for biomedical research. Reprod Domest Anim. 2012;47(Suppl 4):59-71.

[13] PriyadharsiniRP. Animal models to evaluate anti-atherosclerotic drugs. Fundam Clin Pharmacol. 2015;29(4):329-340.

[14] KnuutiJ, WijnsW, SarasteA, et al. ESC guidelines for the diagnosis and management of chronic coronary syndromes. Eur Heart J. 2019;41(3):407-477.

[15] BhattDL, LopesRD, HarringtonRA. Diagnosis and treatment of acute coronary syndromes: a review. JAMA. 2022;327(7):662-675.

[16] HoeferIE, Steffens S, Ala-KorpelaM, et al. Novel methodologies for biomarker discovery in atherosclerosis. Eur Heart J. 2015;36(39):2635-2642.

[17] MengH, RuanJ, YanZ, et al. New progress in early diagnosis of atherosclerosis. Int J Mol Sci. 2022;23(16):8939.

[18] WuDJ, ZhuBJ, WangXD. Metabonomics-based omics study and atherosclerosis. J Clin Bioinforma. 2011;1(1):30.

[19] MüllerJ, Bertsch T, VolkeJ, et al. Narrative review of metabolomics in cardiovascular disease. J Thorac Dis. 2021;13(4):2532-2550.

[20] ChandranM, Sudhina S, ChandranA, JaleelA, Plakkal Ayyappan J. Defining atherosclerotic plaque biology by mass spectrometry-based omics approaches. Mol Omics. 2023;19(1):6-26.

[21] FineKS, Wilkins JT, SawickiKT. Clinical metabolomic landscape of cardiovascular physiology and disease. J Am Heart Assoc. 2023;12(6):e027725.

[22] StaryHC, Blankenhorn DH, ChandlerAB, et al. A definition of the intima of human arteries and of its atherosclerosis-prone regions. A report from the committee on vascular lesions of the council on arteriosclerosis, American Heart Association. Arterioscler Thromb. 1992;12(1):120-134.

[23] StaryHC, Chandler AB, GlagovS, et al. A definition of initial, fatty streak, and intermediate lesions of atherosclerosis. A report from the committee on vascular lesions of the council on arteriosclerosis, American Heart Association. Arterioscler Thromb. 1994;14(5):840-856.

[24] StaryHC, Chandler AB, DinsmoreRE, et al. A definition of advanced types of atherosclerotic lesions and a histological classification of atherosclerosis. A report from the committee on vascular lesions of the council on arteriosclerosis, American Heart Association. Arterioscler Thromb Vasc Biol. 1995;15(9):1512-1531.

[25] PezzattiJ, Boccard J, CodesidoS, et al. Implementation of liquid chromatography-high resolution mass spectrometry methods for untargeted metabolomic analyses of biological samples: a tutorial. Anal Chim Acta. 2020;1105:28-44.

[26] ZhangJ, MaL, LiB, ChenX, WangD, Zhang A. Identification of biomarkers for risk assessment of arsenicosis based on untargeted metabolomics and machine learning algorithms. Sci Total Environ. 2023;870:161861.

[27] ZhaoJ, YangQ, LiuZ, et al. The impact of subchronic ozone exposure on serum metabolome and the mechanisms of abnormal bile acid and arachidonic acid metabolisms in the liver. Ecotoxicol Environ Saf. 2023;252:114573.

[28] BlaženovićI, KindT, JiJ, FiehnO. Software tools and approaches for compound identification of LC-MS/MS data in metabolomics. Meta. 2018;8(2):31.

[29] MarenbergME, RischN, BerkmanLF, Floderus B, de FaireU. Genetic susceptibility to death from coronary heart disease in a study of twins. N Engl J Med. 1994;330(15):1041-1046.

[30] ZdravkovicS, WienkeA, PedersenNL, Marenberg ME, YashinAI, De FaireU. Heritability of death from coronary heart disease: a 36-year follow-up of 20 966 Swedish twins. J Intern Med Sep 2002;252(3):247–254.

[31] WonHH, Natarajan P, DobbynA, et al. Disproportionate Contributions of select genomic compartments and cell types to genetic risk for coronary artery disease. PLoS Genet. 2015;11(10):e1005622.

[32] ZhaoY, XiangL, LiuY, NiuM, YuanJ, Chen H. Atherosclerosis induced by a high-cholesterol and high-fat diet in the inbred strain of the Wuzhishan miniature pig. Anim Biotechnol. 2018;29(2):110-118.

[33] ZhaW, JiyeA, WangG, et al. Metabonomic characterization of early atherosclerosis in hamsters with induced cholesterol. Biomarkers. 2009;14(6):372-380.

[34] YangY, LiuY, ZhengL, et al. Serum metabonomic analysis of apoE(−/−) mice reveals progression axes for atherosclerosis based on NMR spectroscopy. Mol BioSyst. 2014;10(12):3170-3178.

[35] LiD, ZhangL, DongF, et al. Metabonomic changes associated with atherosclerosis progression for LDLR(−/−) mice. J Proteome Res. 2015;14(5):2237-2254.

[36] LiB, LuX, WangJ, et al. The metabonomics study of P-selectin glycoprotein ligand-1 (PSGL-1) deficiency inhibiting the progression of atherosclerosis in LDLR(−/−) mice. Int J Biol Sci. 2018;14(1):36-46.

[37] IzidoroMA, Cecconi A, PanaderoMI, et al. Plasma metabolic signature of atherosclerosis progression and colchicine treatment in rabbits. Sci Rep. 2020;10(1):7072.

[38] WangF, ZhaoC, TianG, et al. Naringin alleviates atherosclerosis in ApoE(−/−) mice by regulating cholesterol metabolism involved in gut microbiota remodeling. J Agric Food Chem. 2020;68(45):12651-12660.

[39] MaY, LiD, LiuW, et al. Resveratrol on the metabolic reprogramming in liver: implications for advanced atherosclerosis. Front Pharmacol. 2021;12:747625.

[40] WangX, ChenQ, WangX, Cong P, XuJ, XueC. Lipidomics approach in high-fat-diet-induced atherosclerosis dyslipidemia hamsters: alleviation using ether-phospholipids in sea urchin. J Agric Food Chem. 2021;69(32):9167-9177.

[41] WuDN, GuanL, JiangYX, et al. Microbiome and metabonomics study of quercetin for the treatment of atherosclerosis. Cardiovasc Diagn Ther. 2019;9(6):545-560.

[42] SongT, WangP, LiC, et al. Salidroside simultaneously reduces de novo lipogenesis and cholesterol biosynthesis to attenuate atherosclerosis in mice. Biomed Pharmacother. 2021;134:111137.

[43] KongXL, LyuQ, ZhangYQ, et al. Effect of astragaloside IV and salvianolic acid B on antioxidant stress and vascular endothelial protection in the treatment of atherosclerosis based on metabonomics. Chin J Nat Med. 2022;20(8):601-613.

[44] TzoulakiI, Castagné R, BoulangéCL, et al. Serum metabolic signatures of coronary and carotid atherosclerosis and subsequent cardiovascular disease. Eur Heart J. 2019;40(34):2883-2896.

[45] WangZ, ZhuC, NambiV, et al. Metabolomic pattern predicts incident coronary heart disease. Arterioscler Thromb Vasc Biol. 2019;39(7):1475-1482.

[46] SongL, ZhangZ, QiuZ, JiangT. Serum metabonomic study of patients with acute coronary syndrome using ultra-performance liquid chromatography orbitrap mass spectrometer. Front Cardiovasc Med. 2021;8:637621.

[47] FanY, LiY, ChenY, et al. Comprehensive metabolomic characterization of coronary artery diseases. J Am Coll Cardiol. 2016;68(12):1281-1293.

[48] WangX, ZhangL, SunW, et al. Changes of metabolites in acute ischemic stroke and its subtypes. Front Neurosci. 2020;14:580929.

[49] LiuH, ChenX, HuX, et al. Alterations in the gut microbiome and metabolism with coronary artery disease severity. Microbiome. 2019;7(1):68.

[50] SuJ, ZhaoQ, ZhaoA, et al. Serum metabolic signatures of subclinical atherosclerosis in patients with type 2 diabetes mellitus: a preliminary study. Acta Diabetol. 2021;58(9):1217-1224.

[51] ChenX, LiuL, PalaciosG, et al. Plasma metabolomics reveals biomarkers of the atherosclerosis. J Sep Sci. 2010;33(17–18):2776-2783.

[52] RomO, LiuY, FinneyAC, et al. Induction of glutathione biosynthesis by glycine-based treatment mitigates atherosclerosis. Redox Biol. 2022;52:102313.

[53] ZhouX, JinM, LiuL, YuZ, LuX, ZhangH. Trimethylamine N-oxide and cardiovascular outcomes in patients with chronic heart failure after myocardial infarction. ESC Heart Fail. 2020;7(1):188-193.

[54] TangWH, WangZ, LevisonBS, et al. Intestinal microbial metabolism of phosphatidylcholine and cardiovascular risk. N Engl J Med. 2013;368(17):1575-1584.

[55] AntoL, BlessoCN. Interplay between diet, the gut microbiome, and atherosclerosis: role of dysbiosis and microbial metabolites on inflammation and disordered lipid metabolism. J Nutr Biochem. 2022;105:108991.

[56] VourakisM, MayerG, RousseauG. The role of gut microbiota on cholesterol metabolism in atherosclerosis. Int J Mol Sci. 2021;22(15):8074.

RIGHTS & PERMISSIONS

2024 The Author(s). Animal Models and Experimental Medicine published by John Wiley & Sons Australia, Ltd on behalf of The Chinese Association for Laboratory Animal Sciences.