Analysis of ischemic stroke biomarkers based on non-targeted metabolomics

doi:10.3724/SP.J.1123.2024.02015

Abstract

Abstract:

Biomarkers for ischemic stroke (IS) are yet to fulfill clinical requirements. This study used non-targeted metabolomics to investigate differential metabolites and metabolic pathways in plasma and brain tissue following IS, with the aim of identifying new potential biomarkers and therapeutic targets. Twelve Tibetan miniature pigs were randomly assigned to a model- or sham-operation group. An electrocoagulation-based anterior temporal approach was employed to occlude the middle cerebral artery, thereby creating a model for IS. Plasma and brain tissue samples were collected 36 h post-surgery and analyzed using liquid chromatography-mass spectrometry. Principal component and partial least squares discriminant analyses were used to screen for differential metabolites and exclude exogenous metabolites at p<0.05. Compounds were classified according to the HMDB (Human Metabolome Database), and subjected to KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and VIP (variable importance in projection) analyses. Plasma metabolomics revealed that 86 metabolites were upregulated while 149 were downregulated, with (Z)-3-oxo-2-(2-pentenyl)-1-cyclopentylacetic acid, trans-cinnamic acid and cinnamoylglycine determined to be significant metabolites. Fifty-eight differential metabolites were upregulated in brain tissue and 53 were downregulated, with 2,3-dihydroflavon-3-ol, guanidinoacetic acid (GAA), N-acetyl-D-tryptophan, oxidized glutathione, 2-hydroxyquinoline, and N-acetyl-L-aspartate (NAA) identified as significant metabolites. Organic acids and derivatives, lipids and lipid-like molecules, organoheterocyclic compounds, and organic oxygen compounds were found to be common compound categories among the top five types of compound in both plasma and brain tissue. Common metabolic pathways in plasma and brain tissue include amino acid metabolism, digestive system, cancer overview, and lipid metabolism pathways, with the (Z)-3-oxo-2-(2-pentenyl)-1-cyclopentylacetic acid, GAA, oxidized glutathione, and NAA metabolites serving as potential biomarkers. This study provides a theoretical foundation for the early screening and development of clinical treatment strategies for IS.

Key words: ischemic stroke (IS), non-target metabolomics, biomarkers, plasma, brain tissue

CLC Number:

O658

XU Fei, LIU Tianping, GUAN Yajin, HAO Weichao, WEN Dingsheng, XIE Shuilin, BIE Yanan. Analysis of ischemic stroke biomarkers based on non-targeted metabolomics[J]. Chinese Journal of Chromatography, 2025, 43(2): 139-147.

Figures/Tables 6

Fig. 1 Gross anatomical observation and hematoxylin-eosin (HE) staining of the right hemisphere in the MCAO and Sham groups a. gross anatomical observation of the brain; b. HE staining of ischaemic stroke injury. Sham: the sham operation group; MCAO: the middle cerebral artery occlusion model group.

Fig. 2 Analysis of PCA and PLS-DA of MCAO and Sham groups a. PCA score plot for plasma; b. PLS-DA analysis for plasma; c. permutation testing for plasma, where the horizontal axis shows the permutation retention of the test (the dashed line parallel to the horizontal axis indicates the zero scale line), and the vertical axis displays the values of the R2 and Q2 permutation tests, and the two dashed lines represent the regression lines of R2 and Q2, respectively (excluding those outside the zero scale line); d. PLS-DA analysis for brain tissue; e. permutation testing for brain tissue. MCAOR: the right hemisphere of the MCAO group; ShamR: the right hemisphere of the Sham group.

Fig. 3 Volcano plots of differential metabolism in MCAO and Sham groups a. plasma; b. bain tissue. up: upregulated; nosig: not significantly different; down: downregulated.

Fig. 4 HMDB compound classification at the super class level a. plasma; b. brain tissue.

Fig. 5 KEGG functional pathway of differential metabolites a. plasma; b. brain tissue.

Fig. 6 Differential metabolite clustering heat maps and VIP bar charts a. plasma; b. brain tissue. C: Sham group; M: MCAO group. C19H37N5O5: N-(R)-(2-(hydroxyaminocarbonyl)methyl)-4-methylpentanoyl-L-t-butyl-alanyl-L-alanine, 2-aminoethyl amide; C21H18O11: (2S,3S,4S,5R)-3,4,5-trihydroxy-6-(5-hydroxy-3-(4-hydroxyphenyl)-4-oxochromen-7-yl)oxyoxane-2-carboxylic acid; C16H29N3O4: ethyl-3-((5-methyl-4-oxo-1,5-diazacycloundecane-1-carbonyl)amino)propanoate; C25H20Cl2N2O3: (4-chlorophenyl) (1R)-6-chloro-1-(4-methoxyphenyl)-1,3,4,9-tetrahydropyrido(3,4-b)indole-2-carboxylate.

References

[1]	Patel D, Wairkar S. Eur J Pharmacol, 2021, 913: 174638
[2]	Lindsay M P, Norrving B, Sacco R L, et al. Int J Stroke, 2019, 14(8): 806
[3]	Wang L D, Peng B, Zhang H Q, et al. Chinese Journal of Cerebrovascular Diseases, 2022, 19(2): 136
[3]	王陇德, 彭斌, 张鸿祺, 等. 中国脑血管病杂志, 2022, 19(2): 136
[4]	Johnson C O, Nguyen M, Roth G A, et al. Lancet Neurol, 2019, 18(5): 439
[5]	Yoshimura S, Sakai N, Yamagami H, et al. N Engl J Med, 2022, 386(14): 1303
[6]	Esposito E, Li W, Mandeville E T, et al. Nature, 2020, 582(7812): 395
[7]	Lees K R, Bluhmki E, von Kummer R, et al. Lancet, 2010, 375(9727): 1695
[8]	Sauleau P, Lapouble E, Val-Laillet D, et al. Animal, 2009, 3(8): 1138
[9]	White E, Woolley M, Bienemann A, et al. J Neurosci Methods, 2011, 195(1): 78
[10]	Song Y Y, Qi Z H, Cai Z W. Chinese Journal of Chromatography, 2024, 42(2): 120
[10]	宋媛媛, 祁增华, 蔡宗苇. 色谱, 2024, 42(2): 120
[11]	Imai H, Konno K, Nakamura M, et al. J Cereb Blood Flow Metab, 2006, 104(2): 123
[12]	Kondoh T, Kameishi M, Mallick H N, et al. Front Integr Neurosci, 2010, 4: 18
[13]	Lee Y, Khan A, Hong S, et al. Mol Biosyst, 2017, 13(6): 1109
[14]	Kamal F Z, Lefter R, Jaber H, et al. Int J Mol Sci, 2023, 24(7): 6389
[15]	Brosnan J T, Brosnan M E. Annu Rev Nutr, 2007, 27(1): 241
[16]	Ostojic S M, Niess B, Stojanovic M, et al. Int J Med Sci, 2013, 10(2): 141
[17]	Ostojic S M. J Bioenerg Biomembr, 2015, 47(5): 369
[18]	Schulze A. Mol Cell Biochem, 2003, 244(1/2): 143
[19]	Neu A, Neuhoff H, Trube G, et al. Neurobiol Dis, 2002, 11(2): 298
[20]	Moffett J R, Ross B, Arun P, et al. Prog Neurobiol, 2007, 81(2): 89
[21]	Bogner-Strauss J G. Front Endocrinol, 2017, 8: 240
[22]	Bhakoo K K, Craig T, Pearce D. Adv Exp Med Biol, 2006, 576: 27
[23]	Wild J M, Wardlaw J M, Marshall I, et al. Stroke, 2000, (12): 31
[24]	Pereira A C, Saunders D E, Doyle V L, et al. Stroke, 1999, 30(8): 1577
[25]	Hasseldam H, Rasmussen R S, El Ali H H, et al. Heliyon, 2024, 10(2): e24233