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Metabolomics and metabolites in ischemic stroke

  • Maria S. Chumachenko , Tatsiana V. Waseem and Sergei V. Fedorovich EMAIL logo
Published/Copyright: July 1, 2021
Become an author with De Gruyter Brill

Abstract

Stroke is a major reason for disability and the second highest cause of death in the world. When a patient is admitted to a hospital, it is necessary to identify the type of stroke, and the likelihood for development of a recurrent stroke, vascular dementia, and depression. These factors could be determined using different biomarkers. Metabolomics is a very promising strategy for identification of biomarkers. The advantage of metabolomics, in contrast to other analytical techniques, resides in providing low molecular weight metabolite profiles, rather than individual molecule profiles. Technically, this approach is based on mass spectrometry and nuclear magnetic resonance. Furthermore, variations in metabolite concentrations during brain ischemia could alter the principal neuronal functions. Different markers associated with ischemic stroke in the brain have been identified including those contributing to risk, acute onset, and severity of this pathology. In the brain, experimental studies using the ischemia/reperfusion model (IRI) have shown an impaired energy and amino acid metabolism and confirmed their principal roles. Literature data provide a good basis for identifying markers of ischemic stroke and hemorrhagic stroke and understanding metabolic mechanisms of these diseases. This opens an avenue for the successful use of identified markers along with metabolomics technologies to develop fast and reliable diagnostic tools for ischemic and hemorrhagic stroke.


Corresponding author: Sergei V. Fedorovich, Department of Biochemistry, Faculty of Biology, Belarusian State University, Kurchatova St., 10, Minsk 220030, Belarus, E-mail:

Award Identifier / Grant number: B19-001

Acknowledgments

We thank Mr. Randal Petlock, B.Sc., B.Ed. (Canada) and Ms. Natalla Liubetskaya for English language editing to improve the manuscript.

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This work was supported by the Belorussian Republican Foundation of Basic Investigation (grant B19-001).

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

References

Adachi, N., Liu, K., and Arai, T. (2005). Prevention of brain infarction by postischemic administration of histidine in rats. Brain Res. 1039: 220–223, https://doi.org/10.1016/j.brainres.2005.01.061.Search in Google Scholar PubMed

Alexander, J.J., Snyder, A., and Tonsgard, J.H. (1998). Omega-oxidation of monocarboxylic acids in rat brain. Neurochem. Res. 23: 227–233, https://doi.org/10.1023/a:1022441211177.10.1023/A:1022441211177Search in Google Scholar

Araníbar, N., Ott, K.H., Roongta, V., and Mueller, L. (2006). Metabolomic analysis using optimized NMR and statistical methods. Anal. Biochem. 355: 62–70, https://doi.org/10.1016/j.ab.2006.04.014.Search in Google Scholar PubMed

Armstead, W.M., Ganguly, K., Kiessling, J.W., Riley, J., Chen, X.H., Smith, D.H., Higazi, A.A., Cines, D.B., Bdeir, K., Zaitsev, S., et al.. (2010). Signaling, delivery and age as emerging issues in the benefit/risk ratio outcome of tPA for treatment of CNS ischemic disorders. J. Neurochem. 113: 303–312, https://doi.org/10.1111/j.1471-4159.2010.06613.x.Search in Google Scholar PubMed PubMed Central

Au, A. (2018). Metabolomics and lipidomics of ischemic stroke. Adv. Clin. Chem. 85: 31–69, https://doi.org/10.1016/bs.acc.2018.02.002.Search in Google Scholar PubMed

Balan, V., Mihai, C.T., Cojocaru, F.D., Uritu, C.M., Dodi, G., Botezat, D., and Gardikiotis, I. (2019). Vibrational spectroscopy fingerprinting in medicine: from molecular to clinical practice. Materials 12: 2884, https://doi.org/10.3390/ma12182884.Search in Google Scholar PubMed PubMed Central

Bar-Tana, J., Ben-Shoshan, S., Blum, J., Migron, Y., Hertz, R., Pill, J., Rose-Khan, G., and Pill, J. (1989). Synthesis and hypolipidemic and antidiabetogenic activities of β,β,β′,β′-tetrasubstituted, long-chain dioic acids. J. Med. Chem. 32: 2072–2084, https://doi.org/10.1021/jm00129a010.Search in Google Scholar PubMed

Barker, M. and Rayens, W. (2003). Partial least squares for discrimination. J. Chemom. 17: 166–173, https://doi.org/10.1002/cem.785.Search in Google Scholar

Baranovicova, E., Grendar, M., Kalenska, D., Tomascova, A., Cierny, D., and Lehotsky, J. (2018). NMR metabolomic study of blood plasma in ischemic and ischemically preconditioned rats: an increased level of ketone bodies and decreased content of glycolytic products 24 h after global cerebral ischemia. J. Physiol. Biochem. 74: 417–429.10.1007/s13105-018-0632-2Search in Google Scholar PubMed

Barsotti, C. and Ipata, P.L. (2004). Metabolic regulation of ATP breakdown and of adenosine production in rat brain extracts. Int. J. Biochem. Cell Biol. 36: 2214–2225, https://doi.org/10.1016/j.biocel.2004.04.015.Search in Google Scholar PubMed

Batch, B.C., Hyland, K., and Svetkey, L.P. (2014). Branch chain amino acids: biomarkers of health and disease. Curr. Opin. Clin. Nutr. Metab. Care 17: 86–89, https://doi.org/10.1097/MCO.0000000000000010.Search in Google Scholar PubMed

Belgardt, B.F. and Brüning, J.C. (2010). CNS leptin and insulin action in the control of energy homeostasis. Ann. N. Y. Acad. Sci. 1212: 97–113, https://doi.org/10.1111/j.1749-6632.2010.05799.x.Search in Google Scholar PubMed

Berger, C., Schmid, P.C., Schabitz, W.R., Wolf, M., Schwab, S., and Schmidt, H.H.O. (2004). Massive accumulation of N-acylethanolamines after stroke. Cell signalling in acute cerebral ischemia? J. Neurochem. 88: 1159–1167, https://doi.org/10.1046/j.1471-4159.2003.02244.x.Search in Google Scholar PubMed

Berkhemer, O.A., Fransen, P.S.S., Beumer, D., van den Berg, L.A., Lingsma, H.F., Yoo, A.J., Schonewille, W.J., Vos, J.A., Nederkoorn, P.J., Wermer, M.J., et al.. (2015). A randomized trial of intraarterial treatment for acute ischemic stroke. N. Engl. J. Med. 372: 11–20, https://doi.org/10.1056/NEJMoa1411587.Search in Google Scholar PubMed

Berthet, C., Lei, H., Thevenet, J., Gruetter, R., Magistretti, P.J., and Hirt, L. (2009). Neuroprotective role of lactate after cerebral ischemia. J. Cerebr. Blood Flow Metabol. 29: 1780–1790, https://doi.org/10.1038/jcbfm.2009.97.Search in Google Scholar PubMed

Bie, X., Chen, Y., Han, J., Dai, H., Wan, H.W., and Zhao, T. (2007). Effects of gastrodin on amino acids after cerebral ischemia-reperfusion injury in rat striatum. Asia Pac. J. Clin. Nutr. 16: 305–308.Search in Google Scholar

Blad, C.C., Tang, C., and Offermanns, S. (2012). G protein-coupled receptors for energy metabolites as new therapeutic targets. Nat. Rev. Drug Discov. 11: 603–619, https://doi.org/10.1038/nrd3777.Search in Google Scholar PubMed

Blat, A., Dybas, J., Chrabaszcz, K., Bulat, K., Jasztal, A., Kaczmarska, M., Pulyk, R., Popiela, T., Slowik, A., Malek, K., et al.. (2019). FTIR, Raman and AFM characterization of the clinically valid biochemical parameters of the thrombi in acute ischemic stroke. Sci. Rep. 9: 1–10, https://doi.org/10.1038/s41598-019-51932-0.Search in Google Scholar PubMed PubMed Central

Boehme, A.K., Esenwa, C., and Elkind, M.S.V. (2017). Stroke risk factors, genetics and prevention. Circ. Res. 120: 472–495, https://doi.org/10.1161/circresaha.116.308398.Search in Google Scholar

Bordone, M.P., Salman, M.M., Titus, H.E., Amini, E., Andersen, J.V., Chakraborti, B., Diuba, A.V., Dubouskaya, T.G., Ehrke, E., Espindola de Freitas, A., et al.. (2019). The energetic brain – a review from students to students. J. Neurochem. 151: 139–165, https://doi.org/10.1111/jnc.14829.Search in Google Scholar PubMed

Botros, L., Sakkas, D., and Seli, E. (2008). Metabolomics and its application for non-invasive embryo assessment in IVF. Mol. Hum. Reprod. 14: 679–690, https://doi.org/10.1093/molehr/gan066.Search in Google Scholar PubMed PubMed Central

Brooks, C.J.W., Horning, E.C., and Young, J.S. (1968). Characterization of sterols by gas chromatography-mass spectrometry of the trimethylsilyl ethers. Lipids 3: 391–402, https://doi.org/10.1007/bf02531277.Search in Google Scholar

Bruce, S.J., Tavazzi, I., Parisod, V., Rezzi, S., Kochhar, S., and Guy, P.A. (2009). Investigation of human blood plasma sample preparation for performing metabolomics using ultrahigh performance liquid chromatography/mass spectrometry. Anal. Chem. 81: 3285–3296, https://doi.org/10.1021/ac8024569.Search in Google Scholar

Cacciapuoti, F. (2013). Lowering homocysteine levels with folic acid and B-vitamins do not reduce early atherosclerosis, but could interfere with cognitive decline and Alzheimer’s disease. J. Thromb. Thrombolysis 36: 258–262, https://doi.org/10.1007/s11239-012-0856-x.Search in Google Scholar

Campbell, B.C.V. and Khatri, P. (2020). Stroke. Lancet 396: 129–142, https://doi.org/10.1016/s0140-6736(20)31179-x.Search in Google Scholar

Cao, D.S., Wang, B., Zeng, M.M., Liang, Y.Z., Xu, Q.S., Zhang, L.X., Li, H.D., and Hu, Q.N. (2011). A new strategy of exploring metabolomics data using Monte Carlo tree. Analyst 136: 947–954, https://doi.org/10.1039/c0an00383b.Search in Google Scholar

Castillo, J., Dávalos, A., and Noya, M. (1997). Progression of ischemic stroke and excitotoxic aminoacids. Lancet 349: 79–82, https://doi.org/10.1016/s0140-6736(96)04453-4.Search in Google Scholar

Chamorro, Á., Meisel, A., Planas, A.M., Urra, X., Van De Beek, D., and Veltkamp, R. (2012). The immunology of acute stroke. Nat. Rev. Neurol. 8: 401–410, https://doi.org/10.1038/nrneurol.2012.98.Search in Google Scholar

Chamorro, Á., Dirnagl, U., Urra, X., and Planas, A.M. (2016). Neuroprotection in acute stroke: targeting excitotoxicity, oxidative and nitrosative stress, and inflammation. Lancet Neurol. 15: 869–881, https://doi.org/10.1016/s1474-4422(16)00114-9.Search in Google Scholar

Chei, C.L., Yamagishi, K., Kitamura, A., Kiyama, M., Imano, H., Ohira, T., Cui, R., Tanigawa, T., Sankai, T., Ishikawa, Y., et al.. (2013). High-density lipoprotein subclasses and risk of stroke and its subtypes in Japanese population: the circulatory risk in communities study. Stroke 44: 327–333, https://doi.org/10.1161/strokeaha.112.674812.Search in Google Scholar

Cheng, Y., Xie, G., Chen, T., Qiu, Y., Zou, X., Zheng, M., Tan, B., Feng, B., Dong, T., He, P., et al.. (2012). Distinct urinary metabolic profile of human colorectal cancer. J. Proteome Res. 11: 1354–1363, https://doi.org/10.1021/pr201001a.Search in Google Scholar PubMed

Choi, J.Y., Kim, J.S., Kim, J.H., Oh, K., Koh, S.B., and Seo, W.K. (2014). High free fatty acid level is associated with recurrent stroke in cardioembolic stroke patients. Neurology 82: 1142–1148, https://doi.org/10.1212/wnl.0000000000000264.Search in Google Scholar

Choi, D.W. (2020). Excitotoxicity: still hammering the ischemic brain in 2020. Front. Neurosci. 14: 5759953, https://doi.org/10.3389/fnins.2020.579953.Search in Google Scholar

Chouchani, E.T., Pell, V.R., Gaude, E., Aksentijevic, D., Sundier, S.Y., Robb, E.L., Logan, A., Nadtochiy, S.M., Ord, E.N.J., Smith, A.C., et al.. (2014). Ischemic accumulation of succinate controls reperfusion injury through mitochondrial ROS. Nature 515: 431–435, https://doi.org/10.1038/nature13909.Search in Google Scholar

Connelly, M.A., Gruppen, E.G., Otvos, J.D., and Dullaart, R.P.F. (2016). Inflammatory glycoproteins in cardiometabolic disorders, autoimmune diseases and cancer. Clin. Chim. Acta 459: 177–186, https://doi.org/10.1016/j.cca.2016.06.012.Search in Google Scholar

Corbyn, Z. (2014). Statistics: a growing global burden. Nature 510: S2–S3, https://doi.org/10.1038/510s2a.Search in Google Scholar

Correia, S.C. and Moreira, P.I. (2010). Hypoxia-inducible factor1: a new hope to counteract neurodegeneration? J. Neurochem. 122: 1–12, https://doi.org/10.1111/j.1471-4159.2009.06443.x.Search in Google Scholar

Coste, J., Mccauley, R., and Hall, J. (2004). Glutamine: metabolism and application in nutrition support. Asia Pac. J. Clin. Nutr. 13: 25–31, https://doi.org/10.3917/imin.013.0117.Search in Google Scholar

Cunningham, T.J., Yao, L., and Lucena, A. (2008). Product inhibition of secreted phospholipase A2 may explain lysophosphatidylcholines’ unexpected therapeutic properties. J. Inflamm. 5: 17, https://doi.org/10.1186/1476-9255-5-17.Search in Google Scholar

Darabi, M. and Kontush, A. (2016). Can phosphatidylserine enhance atheroprotective activities of high-density lipoprotein? Biochimie 120: 81–86, https://doi.org/10.1016/j.biochi.2015.06.022.Search in Google Scholar

Dear, G.J., Plumb, R.S., Sweatman, B.C., Parry, P.S., Roberts, A.D., Lindon, J.C., Nicholson, J.K., and Ismail, I.M. (2000). Use of directly coupled ion-exchange liquid chromatography-mass spectrometry and liquid chromatography-nuclear magnetic resonance spectroscopy as a strategy for polar metabolite identification. J. Chromatogr. B Biomed. Sci. Appl. 748: 295–309, https://doi.org/10.1016/s0378-4347(00)00401-1.Search in Google Scholar

Ding, H., Cui, G., Zhang, L., Xu, Y., Bao, X., Tu, Y., Wu, B., Wang, Q., Hui, R., Wang, W., et al.. (2010). Association of common variants of CYP4A11 and CYP4F2 with stroke in the Han Chinese population. Pharmacogenetics Genom. 20: 187–194, https://doi.org/10.1097/fpc.0b013e328336eefe.Search in Google Scholar

Ding, X., Liu, R., Li, W., Ni, H., Liu, Y., Wu, D., Yang, S., Liu, J., Xiao, B., and Liu, S. (2016). A metabonomic investigation on the biochemical perturbation in post-stroke patients with depressive disorder (PSD). Metab. Brain Dis. 31: 279–287, https://doi.org/10.1007/s11011-015-9748-z.Search in Google Scholar PubMed

Djukovic, D., Rafteri, D., and Gowda, N. (2020). Mass spectrometry and NMR spectroscopy-based quantitative metabolomics. In: Isaak, H.J. and Veenstra, T.D. (Eds.), Proteomic and metabolomic approaches to biomarker discovery. Academic Press, San Diego, pp. 289–311.10.1016/B978-0-12-818607-7.00016-5Search in Google Scholar

Doyle, K.P., Simon, R.P., and Stenzel-Poore, M.P. (2008). Mechanisms of ischemic brain damage. Neuropharmacology 55: 310–318, https://doi.org/10.1016/j.neuropharm.2008.01.005.Search in Google Scholar PubMed PubMed Central

Duan, X.X., Zhang, G.P., Wang, X.B., Yu, H., Wu, J.L., Liu, K.Z., Wang, L., and Long, X. (2017). Elevated serum and cerebrospinal fluid free fatty acid levels are associated with unfavorable functional outcome in subjects with acute ischemic stroke. Mol. Neurobiol. 54: 1677–1683, https://doi.org/10.1007/s12035-016-9756-y.Search in Google Scholar PubMed

Dubouskaya, T.G., Hrynevich, S.V., Waseem, T.V., and Fedorovich, S.V. (2018). Calcium release from intracellular stores is involved in mitochondria depolarization after lowering extracellular pH in rat brain synaptosomes. Acta Neurobiol. Exp. 78: 343–351, https://doi.org/10.21307/ane-2018-033.Search in Google Scholar

Dunn, W.B., Broadhurst, D.I., Atherton, H.J., Goodacre, R., and Griffin, J.L. (2011a). Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy. Chem. Soc. Rev. 40: 387–426, https://doi.org/10.1039/b906712b.Search in Google Scholar PubMed

Dunn, W.B., Broadhurst, D.I., Atherton, H.J., Goodacre, R., and Griffin, J.L. (2011b). Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy. Chem. Soc. Rev. 40: 387–426, https://doi.org/10.1039/b906712b.Search in Google Scholar

El-Aneed, A., Cohen, A., and Banoub, J. (2009). Mass spectrometry, review of the basics: electrospray, MALDI, and commonly used mass analyzers. Appl. Spectrosc. Rev. 44: 210–230, https://doi.org/10.1080/05704920902717872.Search in Google Scholar

Ellis, D.I., Cowcher, D.P., Ashton, L., O’Hagan, S., and Goodacre, R. (2013). Illuminating disease and enlightening biomedicine: Raman spectroscopy as a diagnostic tool. Analyst 138: 3871–3884, https://doi.org/10.1039/c3an00698k.Search in Google Scholar PubMed

Emwas, A.H., Roy, R., McKay, R.T., Tenori, L., Saccenti, E., Gowda, N.A.G., Raftery, D., Alahmari, F., Jaremko, L., Jaremko, M., and Wishart, D.S. (2019). NMR spectroscopy for metabolomics research. Metabolites 9: 123, https://doi.org/10.3390/metabo9070123.Search in Google Scholar

Epstein, F.H., Moncada, S., and Higgs, A. (1993). The L-arginine-nitric oxide pathway. N. Engl. J. Med. 329: 2002–2012, https://doi.org/10.1056/nejm199312303292706.Search in Google Scholar

Esposito, E., Cordaro, M., and Cuzzocrea, S. (2014). Roles of fatty acid ethanolamides (FAE) in traumatic and ischemic brain injury. Pharmacol. Res. 86: 26–31, https://doi.org/10.1016/j.phrs.2014.05.009.Search in Google Scholar

Fedorovich, S.V. and Waseem, T.V. (2018). Metabolic regulation of synaptic activity. Rev. Neurosci. 29: 825–835, https://doi.org/10.1515/revneuro-2017-0090.Search in Google Scholar

Fedorovich, S.V., Voronina, P.P., and Waseem, T.V. (2018). Ketogenic diet versus ketoacidosis: what determines the influence of ketone bodies on neurons? Neural Regen. Res. 13: 2060–2063, https://doi.org/10.4103/1673-5374.241442.Search in Google Scholar

Fedorovich, S.V., Dubouskaya, T.G., and Waseem, T.V. (2020). Synaptic receptors for low pH in extracellular space: metabotropic receptors are an underestimated factor in stroke. Neural Regen. Res. 15: 2033–2034, https://doi.org/10.4103/1673-5374.282249.Search in Google Scholar

Fiehn, O. (2016). Metabolomics by gas chromatography-mass spectrometry: combined targeted and untargeted profiling. Curr. Protoc. Mol. Biol. 114: 30.4.1–30.4.32, https://doi.org/10.1002/0471142727.mb3004s114.Search in Google Scholar

Floegel, A., Stefan, N., Yu, Z., Mühlenbruch, K., Drogan, D., Joost, H.G., Fritsche, A., Haring, H.-U., Hrabe de Angelis, M., Peters, A., et al.. (2013). Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach. Diabetes 62: 639–648, https://doi.org/10.2337/db12-0495.Search in Google Scholar

Floegel, A., Kühn, T., Sookthai, D., Johnson, T., Prehn, C., Rolle-Kampczyk, U., Otto, W., Weikert, C., Illig, T., von Bergen, M., et al.. (2018). Serum metabolites and risk of myocardial infarction and ischemic stroke: a targeted metabolomic approach in two German prospective cohorts. Eur. J. Epidemiol. 33: 55–66, https://doi.org/10.1007/s10654-017-0333-0.Search in Google Scholar

Folbergrov, J., Ljunggren, B., Norberg, K., and Siesjo, B.K. (1974). Influence of complete ischemia on glycolytic metabolites, citric acid cycle intermediates, and associated amino acids in the rat cerebral cortex. Brain Res. 80: 265–279, https://doi.org/10.1016/0006-8993(74)90690-8.Search in Google Scholar

Fonarow, G.C., Smith, E.E., Saver, J.L., Reeves, M.J., Bhatt, D.L., Grau-Sepulveda, M.V., Olsson, D.M.W., Hernandez, A.F., Petersen, E.D., and Schwamm, L.H. (2011). Timeliness of tissue-type plasminogen activator therapy in acute ischemic stroke: patient characteristics, hospital factors, and outcomes associated with door-to-needle times within 60 minutes. Circulation 123: 750–758, https://doi.org/10.1161/circulationaha.110.974675.Search in Google Scholar PubMed

Fonteh, A.N., Harrington, R.J., Tsai, A., Liao, P., and Harrington, M.G. (2007). Free amino acid and dipeptide changes in the body fluids from Alzheimer’s disease subjects. Amino Acids 32: 213–224, https://doi.org/10.1007/s00726-006-0409-8.Search in Google Scholar PubMed

Fretts, A.M., Mozaffarian, D., Siscovick, D.S., Sitlani, C., Psaty, B.M., Rimm, E.B., Song, X., McKnight, B., Spiegelman, D., King, I.B., et al.. (2014). Plasma phospholipid and dietary α-linolenic acid, mortality, CHD and stroke: the Cardiovascular Health Study. Br. J. Nutr. 112: 1206–1213, https://doi.org/10.1017/s0007114514001925.Search in Google Scholar

Frisardi, V., Panza, F., Seripa, D., Farooqui, T., and Farooqui, A.A. (2011). Glycerophospho-lipids and glycerophospholipid-derived lipid mediators: a complex meshwork in Alzheimer’s disease pathology. Prog. Lipid Res. 50: 313–330, https://doi.org/10.1016/j.plipres.2011.06.001.Search in Google Scholar PubMed

Fu, X., Wang, J., Liao, S., Lv, Y., Xu, D., Yang, M., and Kong, L. (2019). 1H NMR-based metabolomics reveals refined-Huang-lian-jie-du-decoction (BBG) as a potential ischemic stroke treatment drug with efficacy and a favorable therapeutic window. Front. Pharmacol. 10: 337, https://doi.org/10.3389/fphar.2019.00337.Search in Google Scholar PubMed PubMed Central

Gao, J., Yang, H., Chen, J., Fang, J., Chen, C., Liang, R., Yang, G., Wu, H., Wu, C., and Li, S. (2013). Analysis of serum metabolites for the discovery of amino acid biomarkers and the effect of galangin on cerebral ischemia. Mol. BioSyst. 9: 2311–2321, https://doi.org/10.1039/c3mb70040b.Search in Google Scholar PubMed

Geng, H.H., Wang, X.W., Fu, R.L., Jing, M.J., Huang, L.L., Zhang, Q., Wang, X.X., and Wang, P.X. (2016). The relationship between C-reactive protein level and discharge outcome in patients with acute ischemic stroke. Int. J. Environ. Res. Publ. Health 13: 636, https://doi.org/10.3390/ijerph13070636.Search in Google Scholar PubMed PubMed Central

Ghosh, S., Castillo, E., Frias, E.S., and Swanson, R.A. (2018). Bioenergetic regulation of microglia. Glia 66: 1200–1212, https://doi.org/10.1002/glia.23271.Search in Google Scholar PubMed PubMed Central

Gibson, C.L., Murphy, A.N., and Murphy, S.P. (2012). Stroke outcome in the ketogenic state – a systematic review of the animal data. J. Neurochem. 123: 52–57, https://doi.org/10.1111/j.1471-4159.2012.07943.x.Search in Google Scholar PubMed PubMed Central

Gowda, G.A. and Djukovic, D. (2014). Overview of mass spectrometry-based metabolomics: opportunities and challenges. Methods Mol. Biol. 1198: 3–12, https://doi.org/10.1007/978-1-4939-1258-2_1.Search in Google Scholar PubMed PubMed Central

Gowda, G.N., Zhang, S., Gu, H., Asiago, V., Shanaiah, N., and Raftery, D. (2008). Metabolomics-based methods for early disease diagnostics. Expert Rev. Mol. Diagn. 8: 617–633, https://doi.org/10.1586/14737159.8.5.617.Search in Google Scholar PubMed PubMed Central

Gray, L.R., Tompkins, S.C., and Taylor, E.B. (2014). Regulation of pyruvate metabolism and human disease. Cell. Mol. Life Sci. 71: 2577–2604, https://doi.org/10.1007/s00018-013-1539-2.Search in Google Scholar PubMed PubMed Central

Gromski, P.S., Muhamadali, H., Ellis, D.I., Xu, Y., Correa, E., Turner, M.L., and Goodacre, R. (2015). A tutorial review: metabolomics and partial least squares-discriminant analysis – a marriage of convenience or a shotgun wedding. Anal. Chim. Acta 879: 10–23, https://doi.org/10.1016/j.aca.2015.02.012.Search in Google Scholar PubMed

Gu, X., Al Dubayee, M., Alshahrani, A., Masood, A., Benabdelkamel, H., Zahra, M., Li, L., Rahman, A.M.A., and Aljada, A. (2020). Distinctive metabolomics patterns associated with insulin resistance and type 2 diabetes mellitus. Front. Mol. Biosci. 7: 609806, https://doi.org/10.3389/fmolb.2020.609806.Search in Google Scholar PubMed PubMed Central

Guasch-Ferré, M., Zheng, Y., Ruiz-Canela, M., Hruby, A., Martínez-González, M.A., Clish, C.B., Corella, D., Estruch, R., Ros, E., Fito, M., et al.. (2016). Plasma acylcarnitines and risk of cardiovascular disease: effect of Mediterranean diet interventions. Am. J. Clin. Nutr. 103: 1408–1416, https://doi.org/10.3945/ajcn.116.130492.Search in Google Scholar PubMed PubMed Central

Guijas, C., Montenegro-Burke, J.R., Domingo-Almenara, X., Palermo, A., Warth, B., Hermann, G., Koellenspreger, G., Huan, T., Uritboonthai, W., Aisporna, A.E., et al.. (2018). METLIN: a technology platform for identifying knowns and unknowns. Anal. Chem. 90: 3156–3164, https://doi.org/10.1021/acs.analchem.7b04424.Search in Google Scholar PubMed PubMed Central

Gupta, S., Sharma, U., Jagannathan, N.R., and Gupta, Y.K. (2017). Neuroprotective effect of lercanidipine in middle cerebral artery occlusion model of stroke in rats. Exp. Neurol. 288: 25–37, https://doi.org/10.1016/j.expneurol.2016.10.014.Search in Google Scholar PubMed

Gusev, E.I., Skvortsova, V.I., Dambinova, S.A., Raevskiy, K.S., Alekseev, A.A., Bashkatova, V.G., Kovalenko, A.V., Kudrin, V.S., and Yakovleva, E.V. (2000). Neuroprotective effects of glycine for therapy of acute ischaemic stroke. Cerebrovasc. Dis. 10: 49–60.10.1159/000016025Search in Google Scholar PubMed

Hagberg, H., Andersson, P., Lacarewicz, J., Jacobson, I., Butcher, S., and Sandberg, M. (1987). Extracellular adenosine, inosine, hypoxanthine, and xanthine in relation to tissue nucleotides and purines in rat striatum during transient ischemia. J. Neurochem. 49: 227–231, https://doi.org/10.1111/j.1471-4159.1987.tb03419.x.Search in Google Scholar PubMed

Haghikia, A., Yanchev, G.R., Kayacelebi, A.A., Hanff, E., Bledau, N., Widera, C., Sonnenschein, K., Haghikia, A., Weissenborn, K., Bauersachs, J., et al.. (2017). The role of l-arginine/l-homoarginine/nitric oxide pathway for aortic distensibility and intima-media thickness in stroke patients. Amino Acids 49: 1111–1121, https://doi.org/10.1007/s00726-017-2409-2.Search in Google Scholar PubMed

Halder, S.K., Yano, R., Chun, J., and Ueda, H. (2013). Involvement of LPA1 receptor signaling in cerebral ischemia-induced neuropathic pain. Neuroscience 235: 10–15, https://doi.org/10.1016/j.neuroscience.2013.01.005.Search in Google Scholar PubMed

Hamel, D., Sanchez, M., Duhamel, F., Roy, O., Honore, J.-C., Noueihed, B., Zhou, T., Nadeau-Vallee, M., Hou, X., Lavoie, J.C., et al.. (2014). G-protein-coupled receptor 91 and succinate are key contributors in neonatal postcerebral hypoxia-ischemia recovery. Arterioscler. Thromb. Vasc. Biol. 34: 285–293, https://doi.org/10.1161/atvbaha.113.302131.Search in Google Scholar PubMed

Haserück, N., Erl, W., Pandey, D., Tigyi, G., Ohlmann, P., Ravanat, C., Gashet, C., and Siess, W. (2004). The plaque lipid lysophosphatidic acid stimulates platelet activation and platelet-monocyte aggregate formation in whole blood: involvement of P2Y 1 and P2Y12 receptors. Blood 103: 2585–2592, https://doi.org/10.1182/blood-2003-04-1127.Search in Google Scholar PubMed

Hermesh, O., Kalderon, B., and Bar-Tana, J. (1998). Mitochondria uncoupling by a long chain fatty acyl analogue. J. Biol. Chem. 273: 3937–3742, https://doi.org/10.1074/jbc.273.7.3937.Search in Google Scholar PubMed

Holmes, E., Wilson, I.D., and Nicholson, J.K. (2008). Metabolic phenotyping in health and disease. Cell 134: 714–717, https://doi.org/10.1016/j.cell.2008.08.026.Search in Google Scholar PubMed

Holmes, M.V., Millwood, I.Y., Kartsonaki, C., Hill, M.R., Bennett, D.A., Boxall, R., Guo, Y., Xu, X., Bian, Z., Hu, R., et al.. (2018). Lipids, lipoproteins, and metabolites and risk of myocardial infarction and stroke. J. Am. Coll. Cardiol. 71: 620–632, https://doi.org/10.1016/j.jacc.2017.12.006.Search in Google Scholar PubMed PubMed Central

Hozawa, A., Folsom, A.R., Ibrahim, H., Nieto, J.F., Rosamond, W.D., and Shahar, E. (2006). Serum uric acid and risk of ischemic stroke: the ARIC Study. Atherosclerosis 187: 401–407, https://doi.org/10.1016/j.atherosclerosis.2005.09.020.Search in Google Scholar PubMed

Hrynevich, S.V., Waseem, T.V., Hebert, A., Pellerin, L., and Fedorovich, S.V. (2016). β-hydroxybutirate supports synaptic vesicle cycling but reduces endocytosis and exocytosis in rat brain synaptosomes. Neurochem. Int. 93: 73–81, https://doi.org/10.1016/j.neuint.2015.12.014.Search in Google Scholar PubMed

Hu, Z., Zhu, Z., Cao, Y., Wang, L., Sun, X., Dong, J., Fang, Z., Fang, Y., Xu, X., Gao, P., et al.. (2016). Rapid and sensitive differentiating ischemic and hemorrhagic strokes by dried blood spot based direct injection mass spectrometry metabolomics analysis. J. Clin. Lab. Anal. 30: 823–830, https://doi.org/10.1002/jcla.21943.Search in Google Scholar PubMed PubMed Central

Iadecola, C. (2013). The pathobiology of vascular dementia. Neuron 80: 844–866, https://doi.org/10.1016/j.neuron.2013.10.008.Search in Google Scholar PubMed PubMed Central

Ide, T., Steinke, J., and Cahill, G.F.Jr. (1969). Metabolic interactions of glucose, lactate, and beta-hydroxybutyrate in rat brain slices. Am. J. Physiol. 217: 784–792, https://doi.org/10.1152/ajplegacy.1969.217.3.784.Search in Google Scholar

Ignesti, G., Pino, R., Banchelli, G., Ferrali, C., Pirisino, R., and Raimondi, L. (1996). Increased desensitization by picomolar phorbol ester of the endothelium-mediated effect of histamine in the perfused rat mesenteric bed. Inflamm. Res. 45: 171–175, https://doi.org/10.1007/bf02285157.Search in Google Scholar

Isaev, N.K., Stelmashook, E.V., Lukin, S.V., Freyer, D., Mergenthaler, P., and Zorov, D.B. (2010). Acidosis-induced zinc-dependent death of cultured cerebellar granule neurons. Cell. Mol. Neurobiol. 30: 877–883, https://doi.org/10.1007/s10571-010-9516-x.Search in Google Scholar

Iso, H., Sato, S., Umemura, U., Kudo, M., Koike, K., Kitamura, A., Imano, H., Okamura, T., Naito, Y., and Shimamoto, T. (2002). Linoleic acid, other fatty acids, and the risk of stroke. Stroke 33: 2086–2093, https://doi.org/10.1161/01.str.0000023890.25066.50.Search in Google Scholar

Janero, D.R. (1990). Malondialdehyde and thiobarbituric acid-reactivity as diagnostic indices of lipid peroxidation and peroxidative tissue injury. Free Radic. Biol. Med. 9: 515–540, https://doi.org/10.1016/0891-5849(90)90131-2.Search in Google Scholar

Jauch, E.C., Saver, J.L., Adams, H.P., Bruno, A., Connors, J.J.B., Demaerschalk, B.M., Khatri, P., McMullan, P.W.Jr., Qureshi, A.I., Rosenfield, K., et al.. (2013). Guidelines for the early management of patients with acute ischemic stroke: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 44: 870–947, https://doi.org/10.1161/str.0b013e318284056a.Search in Google Scholar PubMed

Jena, I., Nayak, S.R., Behera, S., Singh, B., Ray, S., Jena, D., Singh, S., and Sahoo, S.K. (2017). Evaluation of ischemia-modified albumin, oxidative stress, and antioxidant status in acute ischemic stroke patients. J. Nat. Sci. Biol. Med. 8: 110–113, https://doi.org/10.4103/0976-9668.198346.Search in Google Scholar PubMed PubMed Central

Jennings, A., MacGregor, A., Welch, A., Chowienczyk, P., Spector, T., and Cassidy, A. (2015). Amino acid intakes are inversely associated with arterial stiffness and central blood pressure in women. J. Nutr. 145: 2130–2138, https://doi.org/10.3945/jn.115.214700.Search in Google Scholar PubMed PubMed Central

Jiang, Z., Sun, J., Liang, Q., Cai, Y., Li, S., Huang, Y., Wang, Y., and Luo, G. (2011). A metabonomic approach applied to predict patients with cerebral infarction. Talanta 84: 298–304, https://doi.org/10.1016/j.talanta.2011.01.015.Search in Google Scholar PubMed

Johnson, L.C., Parker, K., Aguirre, B.F., Nemkov, T.G., D’Alessandro, A., Johnson, S.A., Seals, D.R., and Martens, C.R. (2019). The plasma metabolome as a predictor of biological aging in humans. Geroscience 41: 895–906, https://doi.org/10.1007/s11357-019-00123-w.Search in Google Scholar PubMed PubMed Central

Jourdain, P., Allaman, I., Rothenfusser, K., Fiumelli, H., Marquet, P., and Magistretti, P.J. (2016). L-lactate protects neurons against excitotoxicity: implication of an ATP-mediated signalling cascade. Sci. Rep. 6: 21250, https://doi.org/10.1038/srep21250.Search in Google Scholar PubMed PubMed Central

Jove, M., Mauri-Capdevila, G., Suarez, I., Cambray, S., Sanahuja, J., Quilez, A., Farre, J., Benabdelhak, I., Pamplona, R., Portero-Otin, M., and Purroy, F. (2015). Metabolomics predicts stroke recurrence after transient ischemic attack. Neurology 84: 36–45, https://doi.org/10.1212/wnl.0000000000001093.Search in Google Scholar PubMed PubMed Central

Jung, J.Y., Lee, H.S., Kang, D.G., Kim, N.S., Cha, M.H., Bang, O.S., Ryu, D.H., and Hwang, G.S. (2011). 1H-NMR-based metabolomics study of cerebral infarction. Stroke 42: 1282–1288, https://doi.org/10.1161/strokeaha.110.598789.Search in Google Scholar PubMed

Kagiyama, T., Glushakov, A.V., Sumners, C., Roose, B., Dennis, D.M., Phillips, M.I., Ozcan, M.S., Seubert, C.N., and Martynyuk, A.E. (2004). Neuroprotective action of halogenated derivatives of L-phenylalanine. Stroke 35: 1192–1196, https://doi.org/10.1161/01.str.0000125722.10606.07.Search in Google Scholar

Kaiser, E.E. and West, F.D. (2020). Large animal ischemic stroke models: replicating human stroke pathophysiology. Neural Regen. Res. 15: 1377–1387, https://doi.org/10.4103/1673-5374.274324.Search in Google Scholar PubMed PubMed Central

Kanbay, M., Segal, M., Afsar, B., Kang, D.H., Rodriguez-Iturbe, B., and Johnson, R.J. (2013). The role of uric acid in the pathogenesis of human cardiovascular disease. Heart 99: 759–766, https://doi.org/10.1136/heartjnl-2012-302535.Search in Google Scholar PubMed

Katsura, K.A., Aspluno, A., Ekholm, A., and Siesjo, B.K. (1992). Extra- and intracellular pH in the brain during ischemia, related to tissue lactate content in normo- and hypercapnic rats. Eur. J. Neurosci. 4: 166–176, https://doi.org/10.1111/j.1460-9568.1992.tb00863.x.Search in Google Scholar PubMed

Kim, D.S., Li, Y.K., Bell, G.A., Burt, A.A., Vaisar, T., Hutchins, P.M., Furlog, C.E., Otvos, J.D., Polak, J.F., Aman, M.K., et al.. (2016). Concentration of smaller high-density lipoprotein particle (HDL-P) is inversely correlated with carotid intima media thickening after confounder adjustment: the Multi Ethnic Study of Atherosclerosis (MESA). J. Am. Heart Assoc. 5: e002977.10.1161/JAHA.115.002977Search in Google Scholar PubMed PubMed Central

Kimberly, W.T., Wang, Y., Pham, L., Furie, K.L., and Gerszten, R.E. (2013). Metabolite profiling identifies a branched chain amino acid signature in acute cardioembolic stroke. Stroke 44: 1389–1395, https://doi.org/10.1161/strokeaha.111.000397.Search in Google Scholar PubMed PubMed Central

Kimm, H., Yun, J.E., Jo, J., and Jee, S.H. (2009). Low serum bilirubin level as an independent predictor of stroke incidence: a prospective study in Korean men and women. Stroke 40: 3422–3427, https://doi.org/10.1161/strokeaha.109.560649.Search in Google Scholar

Koizumi, S., Yamamoto, S., Hayasaka, T., Konishi, Y., Yamaguchi-Okada, M., Goto-Inoue, N., Sugira, Y., Setou, M., and Namba, H. (2010). Imaging mass spectrometry revealed the production of lyso-phosphatidylcholine in the injured ischemic rat brain. Neuroscience 168: 219–225, https://doi.org/10.1016/j.neuroscience.2010.03.056.Search in Google Scholar

Kontush, A., Chantepie, S., and Chapman, M.J. (2003). Small, dense HDL particles exert potent protection of atherogenic LDL against oxidative stress. Arterioscler. Thromb. Vasc. Biol. 23: 1881–1888, https://doi.org/10.1161/01.atv.0000091338.93223.e8.Search in Google Scholar

Kris-Etherton, P.M. and Yu, S. (1997). Individual fatty acid effects on plasma lipids and lipoproteins: human studies. Am. J. Clin. Nutr. 65: 1628S–1644S, https://doi.org/10.1093/ajcn/65.5.1628s.Search in Google Scholar

Krishtal, O. and Pidoplichko, V. (1980). A receptor for protons in the nerve cell membrane. Neuroscience 5: 2325–2327, https://doi.org/10.1016/0306-4522(80)90149-9.Search in Google Scholar

Kroetz, D.L. and Xu, F. (2005). Regulation and inhibition of arachidonic acid ω-hydroxylases and 20-HETE formation. Annu. Rev. Pharmacol. 45: 413–438, https://doi.org/10.1146/annurev.pharmtox.45.120403.100045.Search in Google Scholar PubMed

Kulesh, S.D., Filina, N.A., Frantava, N.M., Zhytko, N.L., Kastasinevich, T.M., Kliatskova, L.A., Shumskas, M.S., Hilz, M.J., Schwab, S., and Kolomonsky-Rabas, P.L. (2010). Incidence and case-fatality of stroke on the east border of the European Union. The Grodno stroke study. Stroke 41: 2726–2730, https://doi.org/10.1161/strokeaha.110.596916.Search in Google Scholar PubMed

Lai, T.W., Zhang, S., and Wang, Y.T. (2014). Excitotoxicity and stroke: identifying novel targets for neuroprotection. Prog. Neurobiol. 115: 157–188, https://doi.org/10.1016/j.pneurobio.2013.11.006.Search in Google Scholar PubMed

Lan, K., Zhang, Y., Yang, J., and Xu, L. (2010). Simple quality assessment approach for herbal extracts using high performance liquid chromatography-UV based metabolomics platform. J. Chromatogr. A 1217: 1414–1418, https://doi.org/10.1016/j.chroma.2009.12.031.Search in Google Scholar PubMed

Latchaw, R.E., Alberts, M.J., Lev, M.H., Connors, J.J., Harbaugh, R.E., Higashida, R.T., Hobson, R.T., Kidwell, C.S., Koroshetz, W.J., Mathews, V., et al.. (2009). Recommendations for imaging of acute ischemic stroke: a scientific statement from the american heart association. Stroke 40: 3646–3678, https://doi.org/10.1161/strokeaha.108.192616.Search in Google Scholar PubMed

Lawler, P.R., Akinkuolie, A.O., Chandler, P.D., Moorthy, M.V., Vandenburgh, M.J., Schaumberg, D.A., Schaumberg, D., Lee, I.-M., Glynn, R.J., Ridker, P.M., et al.. (2016). Circulating N-linked glycoprotein acetyls and longitudinal mortality risk. Circ. Res. 118: 1106–1115, https://doi.org/10.1161/circresaha.115.308078.Search in Google Scholar PubMed PubMed Central

Lawton, K.A., Berger, A., Mitchell, M., Milgram, K.E., Evans, A.M., Guo, L., Hanson, R.W., Kalhan, S.C., Ryals, J.A., and Milburn, M.V. (2008). Analysis of the adult human plasma metabolome. Pharmacogenomics 9: 383–397, https://doi.org/10.2217/14622416.9.4.383.Search in Google Scholar

Lee, Y., Khan, A., Hong, S., Jee, S.H., and Park, Y.H. (2017). A metabolomic study on high-risk stroke patients determines low levels of serum lysine metabolites: a retrospective cohort study. Mol. Biosyst. 13: 1109–1120, https://doi.org/10.1039/c6mb00732e.Search in Google Scholar

Lehotskỳ, J., Tothová, B., Kovalská, M., Dobrota, D., Benová, A., Kalenská, D., and Kaplán, P. (2016). Role of homocysteine in the ischemic stroke and development of ischemic tolerance. Front. Neurosci. 10: 538.10.3389/fnins.2016.00538Search in Google Scholar

Levin, L.R. and Buck, J. (2015). Physiological roles of acid-base sensors. Annu. Rev. Physiol. 77: 347–362, https://doi.org/10.1146/annurev-physiol-021014-071821.Search in Google Scholar

Li, Z.G., Yu, Z.C., Wang, D.Z., Ju, W.P., Zhan, X., Wu, Q.Z., Wu, X.J., Cong, H.M., and Man, H.H. (2008). Influence of acetylsalicylate on plasma lysophosphatidic acid level in patients with ischemic cerebral vascular diseases. Neurol. Res. 30: 366–369, https://doi.org/10.1179/174313208x300369.Search in Google Scholar

Liao, R.J., Jiang, L., Wang, R.R., Zhao, H.W., Chen, Y., Li, Y., Wang, L., Jie, L.Y., Zhou, Y.D., Zhang, X.N., et al.. (2015). Histidine provides long-term neuroprotection after cerebral ischemia through promoting astrocyte migration. Sci. Rep. 5: 15356, https://doi.org/10.1038/srep15356.Search in Google Scholar

Lindon, J.C., Holmes, E., and Nicholson, J.K. (2001). Pattern recognition methods and applications in biomedical magnetic resonance. Prog. Nucl. Magn. Reson. Spectrosc. 39: 1–40, https://doi.org/10.1016/s0079-6565(00)00036-4.Search in Google Scholar

Lindon, J.C., Holmes, E., and Nicholson, J.K. (2007). Metabonomics in pharmaceutical R & D. FEBS J. 274: 1140–1151, https://doi.org/10.1111/j.1742-4658.2007.05673.x.Search in Google Scholar PubMed

Lipton, P. (1999). Ischemic cell death in brain neurons. Physiol. Rev. 79: 1431–1568, https://doi.org/10.1152/physrev.1999.79.4.1431.Search in Google Scholar PubMed

Liu, X., Hou, J., Shi, L., Chen, J., Sang, J., Hu, S., Cong, X., and Chen, X. (2009). Lysophosphatidic acid protects mesenchymal stem cells against ischemia-induced apoptosis in vivo. Stem Cell. Dev. 18: 947–953, https://doi.org/10.1089/scd.2008.0352.Search in Google Scholar PubMed

Liu, L., Wang, M., Yang, X., Bi, M., Na, L., Niu, Y., Li, Y., and Sun, C. (2013). Fasting serum lipid and dehydroepiandrosterone sulfate as important metabolites for detecting isolated postchallenge diabetes: serum metabolomics via ultra-high-performance LC-MS. Clin. Chem. 59: 1338–1348, https://doi.org/10.1373/clinchem.2012.200527.Search in Google Scholar PubMed

Liu, M.L., Zheng, P., Liu, Z., Xu, Y., Mu, J., Guo, J., Huang, T., Meng, H.Q., and Xie, P. (2014). GC-MS based metabolomics identification of possible novel biomarkers for schizophrenia in peripheral blood mononuclear cells. Mol. Biosyst. 10: 2398–2406, https://doi.org/10.1039/c4mb00157e.Search in Google Scholar PubMed

Liu, M., Zhou, K., Li, H., Dong, X., Tan, G., Chai, Y., Wang, W., and Bi, X. (2015). Potential of serum metabolites for diagnosing post-stroke cognitive impairment. Mol. Biosyst. 11: 3287–3296, https://doi.org/10.1039/c5mb00470e.Search in Google Scholar PubMed

Liu, W., Mu, F., Liu, T., Xu, H., Chen, J., Jia, N., Zhang, Y., Dou, F., Shi, L., Li, Y., et al.. (2018). Ultra performance liquid chromatography/quadrupole time-of-flight mass spectrometry-based metabonomics reveal protective effect of terminalia chebula extract on ischemic stroke rats. Rejuvenation Res. 21: 541–552.10.1089/rej.2018.2082Search in Google Scholar PubMed

Lo, E.H., Dalkara, T., and Moskowitz, M.A. (2003). Mechanisms, challenges and opportunities in stroke. Nat. Rev. Neurosci. 4: 399–415, https://doi.org/10.1038/nrn1106.Search in Google Scholar PubMed

Lokhov, P.G., Dashtiev, M.I., Moshkovskii, S.A., and Archakov, A.I. (2010). Metabolite profiling of blood plasma of patients with prostate cancer. Metabolomics 6: 156–163, https://doi.org/10.1007/s11306-009-0187-x.Search in Google Scholar

Longa, E.Z., Weinstein, P.R., Carlson, S., and Cummins, R. (1989). Reversible middle cerebral artery occlusion without craniectomy in rats. Stroke 20: 84–91, https://doi.org/10.1161/01.str.20.1.84.Search in Google Scholar PubMed

Ludwig, M.-G., Vanek, M., Guerini, D., Gasser, J.A., Jones, C.E., Junker, U., Hofstetter, H., Wolf, R.M., and Seuwen, K. (2003). Proton-sensing G-protein-coupled receptors. Nature 425: 93–98, https://doi.org/10.1038/nature01905.Search in Google Scholar PubMed

Luo, L., Kang, J., He, Q., Qi, Y., Chen, X., Wang, S., and Liang, S. (2019). A NMR-based metabonomics approach to determine protective effect of a combination of multiple components derived from naodesheng on ischemic stroke rats. Molecules 24: 1831, https://doi.org/10.3390/molecules24091831.Search in Google Scholar PubMed PubMed Central

Ma, C., Bi, K., Zhang, M., Su, D., Fan, X., Ji, W., Wang, X., and Chen, X. (2010). Metabonomic study of biochemical changes in the urine of morning glory seed treated rat. J. Pharmaceut. Biomed. Anal. 53: 559–566, https://doi.org/10.1016/j.jpba.2010.03.034.Search in Google Scholar PubMed

Madsen, R., Lundstedt, T., and Trygg, J. (2010). Chemometrics in metabolomics – a review in human disease diagnosis. Anal. Chim. Acta 659: 23–33, https://doi.org/10.1016/j.aca.2009.11.042.Search in Google Scholar PubMed

Magistretti, P.J. and Allaman, I. (2018). Lactate in the brain: from metabolic end-product to signalling molecule. Nat. Rev. Neurosci. 19: 235–249, https://doi.org/10.1038/nrn.2018.19.Search in Google Scholar PubMed

Makrecka, M., Kuka, J., Volska, K., Antone, U., Sevostjanovs, E., Cirule, H., Grinberga, S., Pugovics, O., Dambrova, M., and Liepinsh, E. (2014). Long-chain acylcarnitine content determines the pattern of energy metabolism in cardiac mitochondria. Mol. Cell. Biochem. 395: 1–10, https://doi.org/10.1007/s11010-014-2106-3.Search in Google Scholar PubMed

Marchesi, J.R., Holmes, E., Khan, F., Kochhar, S., Scanlan, P., Shanahan, F., Wilson, I.D., and Wang, Y. (2007). Rapid and noninvasive metabonomic characterization of inflammatory bowel disease. J. Proteome Res. 6: 546–551, https://doi.org/10.1021/pr060470d.Search in Google Scholar PubMed

Meilhac, O. (2015). High-density lipoproteins in stroke. Handb. Exp. Pharmacol. 224: 509–526, https://doi.org/10.1007/978-3-319-09665-0_16.Search in Google Scholar PubMed

Menni, C., Graham, D., Kastenmüller, G., Alharbi, N.H.J., Alsanosi, S.M., McBride, M., Mangino, M., Titcombe, P., Shin, S.-Y., Psatha, M., et al.. (2015). Metabolomic identification of a novel pathway of blood pressure regulation involving hexadecanedioate. Hypertension 66: 422–429, https://doi.org/10.1161/hypertensionaha.115.05544.Search in Google Scholar PubMed PubMed Central

Moffett, J.R., Ross, B., Arun, P., Madhavarao, C.N., and Namboodiri, A.M.A. (2007). N-acetylaspartate in the CNS: from neurodiagnostics to neurobiology. Prog. Neurobiol. 81: 89–131, https://doi.org/10.1016/j.pneurobio.2006.12.003.Search in Google Scholar PubMed PubMed Central

Monasterio, R.P., Olmo-García, L., Bajoub, A., Fernández-Gutiérrez, A., and Carrasco-Pancorbo, A. (2016). Potential of LC coupled to fluorescence detection in food metabolomics: determination of phenolic compounds in virgin olive oil. Int. J. Mol. Sci. 17: 1627, https://doi.org/10.3390/ijms17101627.Search in Google Scholar PubMed PubMed Central

Mongin, A. (2007). Disruption of ionic and cell volume homeostasis in cerebral ischemia: the perfect storm. Pathophysiology 14: 183–193, https://doi.org/10.1016/j.pathophys.2007.09.009.Search in Google Scholar PubMed PubMed Central

Mosienko, V., Teschemacher, A.G., and Kasparov, S. (2015). Is L-lactate a novel signaling molecule in the brain? J. Cerebr. Blood Flow Metabol. 35: 1069–1075, https://doi.org/10.1038/jcbfm.2015.77.Search in Google Scholar PubMed PubMed Central

Moskowitz, M.A., Lo, E.H., and Iadecola, C. (2010). The science of stroke: mechanisms in search of treatments. Neuron 67: 181–198, https://doi.org/10.1016/j.neuron.2010.07.002.Search in Google Scholar

Mousavi, M., Johnson, P., Antti, H., Adolfson, R., Nordin, A., Bergdahl, J., Erikson, K., Moritz, T., Nilsson, L.-G., and Nyberg, L. (2014). Serum metabolomic biomarkers of dementia. Dement. Geriatr. Cognit. Disord. Extra 4: 252–262, https://doi.org/10.1159/000364816.Search in Google Scholar

Nedergaard, M., Goldman, S.A., Desai, S., and Pulsinelli, W.A. (1991). Acid-induced death in neurons and glia. J. Neurosci. 11: 2489–2497, https://doi.org/10.1523/jneurosci.11-08-02489.1991.Search in Google Scholar

Nicholls, A.W., Lindon, J.C., Farrant, R.D., Shockcor, J.P., Wilson, I.D., and Nicholson, J.K. (1999). Directly-coupled HPLC-NMR spectroscopic studies of metabolism and futile deacetylation of phenacetin in the rat. J. Pharmaceut. Biomed. Anal. 20: 865–873, https://doi.org/10.1016/s0731-7085(99)00104-1.Search in Google Scholar

Nicholls, A.W., Holmes, E., Lindon, J.C., Shockcor, J.P., Farrant, R.D., Haselden, J.N., Damment, S.J., Waterfield, C.J., and Nicholson, J.K. (2001). Metabonomic investigations into hydrazine toxicity in the rat. Chem. Res. Toxicol. 14: 975–987, https://doi.org/10.1021/tx000231j.Search in Google Scholar PubMed

Nicholson, J.K., Lindon, J.C., and Holmes, E. (1999). “Metabonomics”: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29: 1181–1189, https://doi.org/10.1080/004982599238047.Search in Google Scholar PubMed

Nicholson, J.K., Connelly, J., Lindon, J.C., and Holmes, E. (2002). Metabonomics: a platform for studying drug toxicity and gene function. Nat. Rev. Drug Discov. 1: 153–161, https://doi.org/10.1038/nrd728.Search in Google Scholar PubMed

Nicholson, J.K. and Lindon, J.C. (2008). Systems biology: metabonomics. Nature 455: 1054–1056, https://doi.org/10.1038/4551054a.Search in Google Scholar PubMed

Olson, C.A., Vuong, H.E., Yano, J.M., Liang, Q.Y., Nusbaum, D.J., and Hsiao, E.Y. (2018). The gut microbiota mediates the anti-seizure effects of the ketogenic diet. Cell 173: 1728–1741, https://doi.org/10.1016/j.cell.2018.04.027.Search in Google Scholar PubMed PubMed Central

O’Sullivan, J.W., Albasri, A., Nicholson, B.D., Perera, R., Aronson, J.K., Roberts, N., and Heneghan, C. (2018). Overtesting and undertesting in primary care: a systematic review and meta-analysis. BMJ Open 8: e018557, https://doi.org/10.1136/bmjopen-2017-018070corr1.Search in Google Scholar PubMed PubMed Central

Pacher, P., Beckman, J.S., and Liaudet, L. (2007). Nitric oxide and peroxynitrite in health and disease. Physiol Rev. 87: 315–424, https://doi.org/10.1152/physrev.00029.2006.Search in Google Scholar PubMed PubMed Central

Palmnäs, M.S.A., Kopciuk, K.A., Shaykhutdinov, R.A., Robson, P.J., Mignault, D., Rabasa-Lhoret, R., Vogel, H.J., and Csizmadi, I. (2018). Serum metabolomics of activity energy expenditure and its relation to metabolic syndrome and obesity. Sci. Rep. 8: 1–12, https://doi.org/10.1038/s41598-018-21585-6.Search in Google Scholar PubMed PubMed Central

Papadimitropoulos, M.E.P., Vasilopoulou, C.G., Maga-Nteve, C., and Klapa, M.I. (2018). Untargeted GC-MS metabolomics. Methods Mol. Biol. 1738: 133–147, https://doi.org/10.1007/978-1-4939-7643-0_9.Search in Google Scholar PubMed

Peng, Y.F., Xie, L.Q., Xiang, Y., and Xu, G.D. (2016). Serum bilirubin and their association with C-reactive protein in patients with migraine. J. Clin. Lab. Anal. 30: 982–985, https://doi.org/10.1002/jcla.21967.Search in Google Scholar PubMed PubMed Central

Pettigrew, L.C., Bang, H., Chambless, L.E., Howard, V.J., and Toole, J.F. (2008). Assessment of pre- and post-methionine load homocysteine for prediction of recurrent stroke and coronary artery disease in the vitamin intervention for stroke prevention trial. Atherosclerosis 200: 345–349, https://doi.org/10.1016/j.atherosclerosis.2007.11.014.Search in Google Scholar PubMed PubMed Central

Phipps, M.S. and Cronin, C.A. (2020). Management of acute ischemic stroke. BMJ 368: I6983, https://doi.org/10.1136/bmj.l6983.Search in Google Scholar PubMed

Pick, S., Anderson, D.G., Asadi-Pooya, A.A., Asadi-Pooya, A.A., Aybek, S., Baslet, G., Bloem, B.R., Bradley-Westguard, A., Brown, R.J., Carson, A.J., et al.. (2020). Outcome measurement in functional neurological disorder: a systematic review and recommendations. J. Neurol. Neurosurg. Psychiatry 91: 638–649, https://doi.org/10.1136/jnnp-2019-322180.Search in Google Scholar PubMed PubMed Central

Puchowicz, M.A., Zechel, J., Valerio, J., Emancipator, D., Xu, K., Pundik, S., LaManna, J.C., and Lust, W.D. (2008). Neuroprotection in diet induced ketotic rat brain following focal ischemia. J. Cerebr. Blood Flow Metabol. 28: 1907–1916, https://doi.org/10.1038/jcbfm.2008.79.Search in Google Scholar PubMed PubMed Central

Purroy, F., Cambray, S., Mauri-Capdevila, G., Jové, M., Sanahuja, J., Farré, J., Benabdelhak, I., Molina-Seguin, J., Colas-Campas, L., Begue, R., et al.. (2016). Metabolomics predicts neuroimaging characteristics of transient ischemic attack patients. EBioMedicine 14: 131–138, https://doi.org/10.1016/j.ebiom.2016.11.010.Search in Google Scholar PubMed PubMed Central

Rech, V.C., Feksa, L.R., Dutra-Filho, C.S., Wyse, A.T.S., Wajner, M., and Wannmacher, C.M.D. (2002). Inhibition of the mitochondrial respiratory chain by alanine in rat cerebral cortex. Metab. Brain Dis. 17: 123–130, https://doi.org/10.1023/a:1019973719399.10.1023/A:1019973719399Search in Google Scholar

Ros, J., Pecinska, N., Alessandri, B., Landolt, H., and Fillenz, M. (2001). Lactate reduces glutamate-induced neurotoxicity in rat cortex. J. Neurosci. Res. 66: 790–794, https://doi.org/10.1002/jnr.10043.Search in Google Scholar

Roscini, L., Corte, L., Antonielli, L., Rellini, P., Fatichenti, F., and Cardinali, G. (2010). Influence of cell geometry and number of replicas in the reproducibility of whole cell FTIR analysis. Analyst 135: 2099–2105, https://doi.org/10.1039/c0an00127a.Search in Google Scholar

Roux, A., Lison, D., Junot, C., and Heilier, J.F. (2011). Applications of liquid chromatography coupled to mass spectrometry-based metabolomics in clinical chemistry and toxicology: a review. Clin. Biochem. 44: 119–135, https://doi.org/10.1016/j.clinbiochem.2010.08.016.Search in Google Scholar

Ryou, M.G., Liu, R., Ren, M., Sun, J., Mallet, R.T., and Yang, S.H. (2012). Pyruvate protects the brain against ischemia-reperfusion injury by activating the erythropoietin signaling pathway. Stroke 43: 1101–1107, https://doi.org/10.1161/strokeaha.111.620088.Search in Google Scholar

Sahni, P.V., Zhang, J., Sosunov, S., Galkin, A., Niatsetskaya, Z., Starkov, A., Brookes, P.S., and Ten, V.S. (2018). Krebs cycle metabolites and preferential succinate oxidation following neonatal hypoxic-ischemic brain injury in mice. Pediatr. Res. 83: 491–497, https://doi.org/10.1038/pr.2017.277.Search in Google Scholar

Sapieha, P., Sirinyan, M., Hamel, D., Zaniolo, K., Joyal, J.S., Cho, J.H., Honore, J.C., Kermorvant-Duchemin, E., Varma, D.R., Tremblay, S., et al.. (2008). The succinate receptor GPR91 in neurons has a major role in retinal angiogenesis. Nat. Med. 14: 1067–1076, https://doi.org/10.1038/nm.1873.Search in Google Scholar

Saransaari, P. and Oja, S.S. (1998). Mechanisms of ischemia-induced taurine release in mouse hippocampal slices. Brain Res. 807: 118–124, https://doi.org/10.1016/s0006-8993(98)00793-8.Search in Google Scholar

Saric, J., Li, J.V., Utzinger, J., Wang, Y., Keiser, J., Dirnhofer, S., Beckonert, O., Sharabiani, M.T.A., Fonville, J.M., Nicholson, J.K., et al.. (2010). Systems parasitology: effects of Fasciola hepatica on the neurochemical profile in the rat brain. Mol. Syst. Biol. 6: 396, https://doi.org/10.1038/msb.2010.49.Search in Google Scholar PubMed PubMed Central

Savic Azoulay, I., Liu, F., Hu, Q., Rozenfield, M., Ben Kasus Nissim, T., Zhu, M.X., Sekler, I., and Xu, T.L. (2020). ASIC1a channels regulate mitochondrial ion signaling and energy homeostasis in neurons. J. Neurochem. 153: 203–215, https://doi.org/10.1111/jnc.14971.Search in Google Scholar PubMed PubMed Central

Schaller, B. and Graf, R. (2004). Cerebral ischemia and reperfusion: the pathophysiologic concept as a basis for clinical therapy. J. Cerebr. Blood Flow Metabol. 24: 351–371, https://doi.org/10.1097/00004647-200404000-00001.Search in Google Scholar PubMed

Schmidley, J.W. (1990). Free radicals in central nervous system ischemia. Stroke 21: 1086–1090, https://doi.org/10.1161/01.str.21.7.1086.Search in Google Scholar PubMed

Schnackenberg, L.K. (2007). Global metabolic profiling and its role in systems biology to advance personalized medicine in the 21st Century. Expert Rev. Mol. Diagn. 7: 247–259, https://doi.org/10.1586/14737159.7.3.247.Search in Google Scholar PubMed

Schnackenberg, L.K. and Beger, R.D. (2007). Metabolomic biomarkers: their role in the critical path. Drug Discov. Today Technol. 4: 13–16, https://doi.org/10.1016/j.ddtec.2007.10.012.Search in Google Scholar PubMed

Schousboe, A. (2003). Role of astrocytes in the maintenance and modulation of glutamatergic and GABAergic neurotransmission. Neurochem. Res. 28: 347–352, https://doi.org/10.1023/a:1022397704922.10.1023/A:1022397704922Search in Google Scholar

Schwartz, M.W., Woods, S.C., Porte, D., Seeley, R.J., and Baskin, D.G. (2000). Central nervous system control of food intake. Nature 404: 661–671, https://doi.org/10.1038/35007534.Search in Google Scholar PubMed

Selman, C., Kerrison, N.D., Cooray, A., Piper, M.D.W., Lingard, S.J., Barton, R.H., Schuster, E.F., Blanc, E., Gems, D., Nicholson, J.K., et al.. (2006). Coordinated multitissue transcriptional and plasma metabonomic profiles following acute caloric restriction in mice. Physiol. Genom. 27: 187–200, https://doi.org/10.1152/physiolgenomics.00084.2006.Search in Google Scholar PubMed

Seo, W.K., Jo, G., Shin, M.J., and Oh, K. (2018). Medium-chain acylcarnitines are associated with cardioembolic stroke and stroke recurrence a metabolomics study. Arterioscler. Thromb. Vasc. Biol. 38: 2245–2253, https://doi.org/10.1161/atvbaha.118.311373.Search in Google Scholar PubMed

Serkova, N.J. and Niemann, C.U. (2006). Pattern recognition and biomarker validation using quantitative 1H-NMR-based metabolomics. Expert Rev. Mol. Diagn. 6: 717–731, https://doi.org/10.1586/14737159.6.5.717.Search in Google Scholar PubMed

Shen, Z., Jiang, L., Yuan, Y., Deng, T., Zheng, Y.-R., Zhao, Y.-Y., Li, W.-L., Wu, J.-Y., Gao, J.-Q., Hu, W.-W., et al.. (2015). Inhibition of G protein-coupled receptor 81 (GPR81) protects against ischemic brain injury. CNS Neurosci. Ther. 21: 271–279, https://doi.org/10.1111/cns.12362.Search in Google Scholar PubMed PubMed Central

Shimazu, T., Hirshey, M.D., Newman, J., He, W., Shirakawa, K., Le Moan, N., Grueter, C.A., Lim, H., Saunders, L.R., Stevens, R.D., et al.. (2013). Suppression of oxidative stress by β-hydroxybutyrate, an endogenous histone deacetylase inhibitor. Science 339: 211–214, https://doi.org/10.1126/science.1227166.Search in Google Scholar PubMed PubMed Central

Sidorov, E., Sanghera, D.K., and Vanamala, J.K.P. (2019). Biomarker for ischemic stroke using metabolome: a clinician perspective. J. Stroke 21: 31–41, https://doi.org/10.5853/jos.2018.03454.Search in Google Scholar PubMed PubMed Central

Sidorov, E., Bejar, C., Xu, C., Ray, B., Reddivari, L., Chainakul, J., Vanamala, J.K.P., and Sanghera, D.K. (2020). Potential metabolite biomarkers for acute versus chronic stage of ischemic stroke: a pilot study. J. Stroke Cerebrovasc. Dis. 29: 104618, https://doi.org/10.1016/j.jstrokecerebrovasdis.2019.104618.Search in Google Scholar PubMed

Silachev, D.N., Gulyaev, M.V., Zorova, L.D., Khailova, L.S., Gubsky, L.V., Pirogov, Y.A., Plotnikov, E.Y., Sukhikh, G.T., and Zorov, D.B. (2015). Magnetic resonance spectroscopy of the ischemic brain under lithium treatment. Link to mitochondrial disorders under stroke. Chem. Biol. Interact. 237: 175–182, https://doi.org/10.1016/j.cbi.2015.06.012.Search in Google Scholar PubMed

Spagou, K., Tsoukali, H., Raikos, N., Gika, H., Wilson, I.D., and Theodoridis, G. (2010). Hydrophilic interaction chromatography coupled to MS for metabonomic/metabolomic studies. J. Separ. Sci. 33: 716–727, https://doi.org/10.1002/jssc.200900803.Search in Google Scholar PubMed

Srikrishna, G., Toomre, D.K., Manzi, A., Panneerselvam, K., Freeze, H.H., Varki, A., and Varki, N.M. (2001). A novel anionic modification of N -glycans on mammalian endothelial cells is recognized by activated neutrophils and modulates acute inflammatory responses. J. Immunol. 166: 624–632, https://doi.org/10.4049/jimmunol.166.1.624.Search in Google Scholar PubMed

Srivastava, S. (2019). Emerging insights into the metabolic alterations in aging using metabolomics. Metabolites 9: 301, https://doi.org/10.3390/metabo9120301.Search in Google Scholar PubMed PubMed Central

Stepanova, A., Konrad, C., Manfredi, G., Spingett, R., Ten, V., and Galkin, A. (2019). The dependence of brain mitochondria reactive oxygen species production on oxygen level is linear, except when inhibited by antimycin A. J. Neurochem. 148: 731–745, https://doi.org/10.1111/jnc.14654.Search in Google Scholar PubMed PubMed Central

Su, L., Zhao, H., Zhang, X., Lou, Z., and Dong, X. (2016). UHPLC-Q-TOF-MS based serum metabonomics revealed the metabolic perturbations of ischemic stroke and the protective effect of RKIP in rat models. Mol. Biosyst. 12: 1831–1841, https://doi.org/10.1039/c6mb00137h.Search in Google Scholar PubMed

Sun, N., Keep, R.F., Hua, Y., and Xi, G. (2016). Critical role of the sphingolipid pathway in stroke: a review of current utility and potential therapeutic targets. Transl. Stroke Res. 7: 420–438, https://doi.org/10.1007/s12975-016-0477-3.Search in Google Scholar PubMed PubMed Central

Sun, H., Zhao, J., Zhong, D., and Li, G. (2017). Potential serum biomarkers and metabonomic profiling of serum in ischemic stroke patients using UPLC/Q-TOF MS/MS. PloS One 12: e0189009, https://doi.org/10.1371/journal.pone.0189009.Search in Google Scholar PubMed PubMed Central

Sun, D., Tiedt, S., Yu, B., Jian, X., Gottesman, R.F., Mosley, T.H., Boerwinkle, E., Dichigans, M., and Fornage, M. (2019a). A prospective study of serum metabolites and risk of ischemic stroke. Neurology 92: e1890–e1898, https://doi.org/10.1212/wnl.0000000000007279.Search in Google Scholar

Sun, R., Li, Y., Cai, M., Cao, Y., and Piao, X. (2019b). Discovery of a new biomarker pattern for differential diagnosis of acute ischemic stroke using targeted metabolomics. Front. Neurol. 10: 1011, https://doi.org/10.3389/fneur.2019.01011.Search in Google Scholar

Tannahill, G.M., Curtis, A.M., Adamik, J., Palsson-McDermott, E.M., McGettrick, G., Goel, G., Frezza, C., Bernard, N.J., Kelly, B., Foley, N.H., et al.. (2013). Succinate is an inflammatory signal that induces IL-1β through HIF-1α. Nature 496: 238–242, https://doi.org/10.1038/nature11986.Search in Google Scholar

Theodoridis, G.A., Gika, H.G., Plumb, R., and Wilson, I.D. (2013). Liquid chromatographic methods combined with mass spectrometry in metabolomics. In: Isaak, H.J., and Veenstra, T.D. (Eds.), Proteomic and metabolomic approaches to biomarker discovery. Academic Press, Cambridge, Massachusetts, USA, pp. 149–169.10.1016/B978-0-12-394446-7.00009-1Search in Google Scholar

Tiedt, S., Brandmaier, S., Kollmeier, H., Duering, M., Artati, A., Adamski, J., Klein, M., Liebig, T., Holdt, L.M., Teupser, D., et al.. (2020). Circulating metabolites differentiate acute ischemic stroke from stroke mimics. Ann. Neurol. 88: 736–746.10.1002/ana.25859Search in Google Scholar

Tilvis, R.S., Erkinjuntti, T., Sulkava, R., Färkkilä, M., and Miettine, T.A. (1987). Serum lipids and fatty acids in ischemic strokes. Am. Heart J. 113: 615–619, https://doi.org/10.1016/0002-8703(87)90642-9.Search in Google Scholar

Tuttle, K.R., Milton, J.E., Packard, D.P., Shuler, L.A., and Short, R.A. (2012). Dietary amino acids and blood pressure: a cohort study of patients with cardiovascular disease. Am. J. Kidney Dis. 59: 803–809, https://doi.org/10.1053/j.ajkd.2011.12.026.Search in Google Scholar PubMed

Tweeddale, H., Notley-Mcrobb, L., and Ferenci, T. (1998). Effect of slow growth on metabolism of Escherichia coli, as revealed by global metabolite pool (‘metabolome’) analysis. J. Bacteriol. 180: 5109–5116, https://doi.org/10.1128/jb.180.19.5109-5116.1998.Search in Google Scholar PubMed PubMed Central

Villa, R.F., Gorini, A., and Hoyer, S. (2009). Effect of ageing and ischemia on enzymatic activities linked to Krebs’ cycle, electron transfer chain, glutamate and aminoacids metabolism of free and intrasynaptic mitochondria of cerebral cortex. Neurochem. Res. 34: 2102–2116, https://doi.org/10.1007/s11064-009-0004-y.Search in Google Scholar PubMed

Vojinovic, D., Kalaoja, M., Trompet, S., Fischer, K., Shipley, M., Li, S., Havulinna, A.S., Perola, M., Salomaa, A.S., and Yang, Q., et al.. (2021). Association of circulating metabolites in plasma or serum and risk of stroke: meta-analysis from 7 prospective cohorts. Neurology 96: e1110–e1123.10.1212/WNL.0000000000011236Search in Google Scholar PubMed PubMed Central

Wachsmuth, C.J., Vogl, F.C., Oefner, P.J., and Dettmer, K. (2013). Gas chromatographic techniques in metabolomics. In: Hyotylainien, T., and Wiedmar, S. (Eds.), Chromatographic methods in metabolomics. Royal Society of Chemistry, London, UK, pp. 87–113.10.1039/9781849737272-00087Search in Google Scholar

Wafa, H.A., Wolfe, C.D.A., Emmett, E., Roth, G.A., Johnson, C.O., and Wang, Y. (2020). Burden of stroke in Europe: thirty-year projections of incidence, prevalence, deaths, and disability-adjusted life years. Stroke 51: 2418–2427, https://doi.org/10.1161/strokeaha.120.029606.Search in Google Scholar

Waldman, R., Champigny, G., Voilley, N., Lauritzen, I., and Lazdunski, M. (1997). A proton-gated cation channel involved in acid-sensing. Nature 386: 173–177, https://doi.org/10.1038/386173a0.Search in Google Scholar PubMed

Wallimann, T., Tokarska-Schlattner, M., and Schlattner, U. (2011). The creatine kinase system and pleiotropic effects of creatine. Amino Acids 40: 1271–1296, https://doi.org/10.1007/s00726-011-0877-3.Search in Google Scholar PubMed PubMed Central

Wanders, R.J.A., Komen, J., and Kemp, S. (2011). Fatty acid omega-oxidation as a rescue pathway for fatty acid oxidation disorders in humans. FEBS J. 278: 182–194, https://doi.org/10.1111/j.1742-4658.2010.07947.x.Search in Google Scholar PubMed

Wang, Q., van Hoecke, M., Tang, X.N., Lee, H., Zheng, Z., Swanson, R.A., and Yenari, M.A. (2009). Pyruvate protects against experimental stroke via an anti-inflammatory mechanism. Neurobiol. Dis. 36: 223–231, https://doi.org/10.1016/j.nbd.2009.07.018.Search in Google Scholar PubMed PubMed Central

Wang, T.J., Larson, M.G., Vasan, R.S., Cheng, S., Rhee, E.P., McCabe, E., Lewis, G.D., Fox, C.S., Jacques, P.F., Fernadez, C., et al.. (2011). Metabolite profiles and the risk of developing diabetes. Nat. Med. 17: 448–453, https://doi.org/10.1038/nm.2307.Search in Google Scholar PubMed PubMed Central

Wang, P.R., Wang, J.S., Yang, M.H., and Kong, L.Y. (2014). Neuroprotective effects of Huang-Lian-Jie-Du-Decoction on ischemic stroke rats revealed by 1H NMR metabolomics approach. J. Pharmaceut. Biomed. Anal. 88: 106–116, https://doi.org/10.1016/j.jpba.2013.08.025.Search in Google Scholar PubMed

Wang, D., Kong, J., Wu, J., Wang, X., and Lai, M. (2017a). GC–MS-based metabolomics identifies an amino acid signature of acute ischemic stroke. Neurosci. Lett. 642: 7–13, https://doi.org/10.1016/j.neulet.2017.01.039.Search in Google Scholar PubMed

Wang, L., Liu, S., Yang, W., Yu, H., Zhang, L., Ma, P., Wu, P., Li, X., Cho, K., Xue, S., et al.. (2017b). Plasma amino acid profile in patients with aortic dissection. Sci. Rep. 7: 40146, https://doi.org/10.1038/srep40146.Search in Google Scholar PubMed PubMed Central

Wang, Y., Zhao, H., Liu, Y., Guo, W., Bao, Y., Zhang, M., Xu, T., Xie, S., Liu, X., and Xu, Y. (2019). GC-MS-based metabolomics to reveal the protective effect of gross saponins of Tribulus terrestris fruit against ischemic stroke in rat. Molecules 24: 793, https://doi.org/10.3390/molecules24040793.Search in Google Scholar PubMed PubMed Central

Wang, T., Zhou, G., He, M., Xu, Y., Rusyaniak, W.G., Xu, Y., Ji, Y., Simon, R.P., Xiong, Z.G., and Zha, X.M. (2020). GPR68 is a neuroprotective proton receptor in brain ischemia. Stroke 51: 3690–3700, https://doi.org/10.1161/strokeaha.120.031479.Search in Google Scholar

Want, E., Nordström, A., Morita, H., and Siuzdak, G. (2007). From exogenous to endogenous: the inevitable imprint of mass spectrometry in metabolomics. J. Proteome Res. 6: 459–468, https://doi.org/10.1021/pr060505+.10.1021/pr060505+Search in Google Scholar PubMed

Wasilewski, M. and Wojtczak, L. (2005). Effects of N-acylethanolamines on the respiratory chain and production of reactive oxygen species in heart mitochondria. FEBS Lett. 579: 4724–4728, https://doi.org/10.1016/j.febslet.2005.07.047.Search in Google Scholar PubMed

Weljie, A.M., Newton, J., Mercier, P., Carlson, E., and Slupsky, C.M. (2006). Targeted profiling: quantitative analysis of 1H NMR metabolomics data. Anal. Chem. 78: 4430–4442, https://doi.org/10.1021/ac060209g.Search in Google Scholar PubMed

Wemmie, J.A., Taugher, R.J., and Kreple, C.J. (2013). Acid-sensing ion channels in pain and disease. Nat. Rev. Neurosci. 14: 461–471, https://doi.org/10.1038/nrn3529.Search in Google Scholar PubMed PubMed Central

Wesley, U.V., Bhute, V.J., Hatcher, J.F., Palecek, S.P., and Dempsey, R.J. (2019). Local and systemic metabolic alterations in brain, plasma, and liver of rats in response to aging and ischemic stroke, as detected by nuclear magnetic resonance (NMR) spectroscopy. Neurochem. Int. 127: 113–124.10.1016/j.neuint.2019.01.025Search in Google Scholar PubMed

Wiedmer, S.K., and Hyötyläinen, T. (2013). Selection of analytical methodology for metabolomics. In: Hyotylainien, T., and Wiedmar (Eds.), Chromatographic methods in metabolomics. Royal Society of Chemistry, London, UK, pp. 1–10.10.1039/9781849737272-00001Search in Google Scholar

Willoughby, S., Holmes, A., and Loscalzo, J. (2002). Platelets and cardiovascular disease. Eur. J. Cardiovasc. Nurs. 1: 273–288, https://doi.org/10.1016/s1474-51510200038-5.Search in Google Scholar

Wishart, D.S., Feunang, Y.D., Marcu, A., Guo, A.C., Liang, K., Vázquez-Fresno, R., Sayeeda, Z., Lo, E., Assempour, N., Berjanskii, M., et al.. (2018). HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 46: D608–D617, https://doi.org/10.1093/nar/gkx1089.Search in Google Scholar PubMed PubMed Central

Wishart, D.S. (2019). NMR metabolomics: a look ahead. J. Magn. Reson. 306: 155–161, https://doi.org/10.1016/j.jmr.2019.07.013.Search in Google Scholar PubMed

Wu, R., Wu, Z., Wang, X., Yang, P., Yu, D., Zhao, C., Xu, G., and Kang, L. (2012). Metabolomic analysis reveals that carnitines are key regulatory metabolites in phase transition of the locusts. Proc. Natl. Acad. Sci. U.S.A. 109: 3259–3263, https://doi.org/10.1073/pnas.1119155109.Search in Google Scholar PubMed PubMed Central

Wu, B., Luo, H., Zhou, X., Cheng, C.-Y., Lin, L., Liu, B.-L., Liu, K., Li, P., and Yang, H. (2017). Succinate-induced neuronal mitochondrial fission and hexokinase II malfunction in ischemic stroke: therapeutical effects of kaempferol. Biochim. Biophys. Acta (BBA) – Mol. Basis Dis. 1863: 2307–2318, https://doi.org/10.1016/j.bbadis.2017.06.011.Search in Google Scholar PubMed

Würtz, P., Havulinna, A.S., Soininen, P., Tynkkynen, T., Prieto-Merino, D., Tillin, T., Ghorbani, A., Artati, A., Wang, Q., Tianen, M., et al.. (2015). Metabolite profiling and cardiovascular event risk: a prospective study of three population-based cohorts. Circulation 131: 774–785, https://doi.org/10.1161/circulationaha.114.013116.Search in Google Scholar

Xian, W., Wu, Y., Xiong, W., Li, L., Li, T., Pan, S., Song, L., Hu, L., Pei, L., Yao, S., et al.. (2016). The pro-resolving lipid mediator Maresin 1 protects against cerebral ischemia/reperfusion injury by attenuating the pro-inflammatory response. Biochem. Biophys. Res. Commun. 25: 175–181, https://doi.org/10.1016/j.bbrc.2016.02.090.Search in Google Scholar PubMed

Xiong, Z.-G., Zhu, X.-M., Chu, X.-P., Minami, M., Hey, J., Wie, W.-L., MacDonald, J.F., Wemmie, J.A., Price, M.P., Welsh, M.J., et al.. (2004). Neuroprotection in ischemia: blocking calcium-permeable acid-sensing ion channels. Cell 118: 687–698, https://doi.org/10.1016/j.cell.2004.08.026.Search in Google Scholar PubMed

Yamagishi, K., Folsom, A.R., and Steffen, L.M. (2013). Plasma fatty acid composition and incident ischemic stroke in middle-aged adults: the atherosclerosis risk in communities (ARIC) study. Cerebrovasc. Dis. 36: 38–46, https://doi.org/10.1159/000351205.Search in Google Scholar PubMed PubMed Central

Yang, S., Ning, F., Li, J., Guo, D., Zhang, L., Cui, R., and Liu, Y. (2016). Therapeutic effect analysis of sinomenine on rat cerebral ischemia-reperfusion injury. J. Stroke Cerebrovasc. Dis. 25: 1263–1269, https://doi.org/10.1016/j.jstrokecerebrovasdis.2016.02.023.Search in Google Scholar PubMed

Yee, S.W., Giacomini, M.M., Hsueh, C.H., Weitz, D., Liang, X., Goswami, S., Kinchen, J.M., Coelho, A., Zur, A.A., Mertsch, K., et al.. (2016). Metabolomic and genome-wide association studies reveal potential endogenous biomarkers for OATP1B1. Clin. Pharmacol. Ther. 100: 524–536, https://doi.org/10.1002/cpt.434.Search in Google Scholar PubMed PubMed Central

Yi, X., Liao, D., Fu, X., Zhang, B., and Wang, C. (2015). Interaction among CYP2C8, EPHX2, and CYP4A11 gene variants significantly increases the risk for ischemic stroke in Chinese populations. J. Atherosclerosis Thromb. 22: 1148–1157, https://doi.org/10.5551/jat.29025.Search in Google Scholar PubMed

You, J., Shi, Y., Zhao, X., Zhang, H., Suo, Y., Yulin, L., Wang, H., and Sun, J. (2006). Enhancement of atmospheric pressure chemical ionization for the determination of free and glycine-conjugated bile acids in human serum. J. Separ. Sci. 29: 2837–2846, https://doi.org/10.1002/jssc.200500463.Search in Google Scholar PubMed

Yu, T. and Bai, Y. (2013). Analyzing LC/MS metabolic profiling data in the context of existing metabolic networks. Curr. Metabolomics 1: 84–91.10.2174/2213235X130107Search in Google Scholar

Zhang, Z., Lee, Y.C., Kim, S.J., Choi, M.S., Tsai, P.C., Saha, A., Wei, H., Xu, Y., Xiao, Y.J., Zhang, P., et al.. (2007). Production of lysophosphatidylcholine by cPLA2 in the brain of mice lacking PPT1 is a signal for phagocyte infiltration. Hum. Mol. Genet. 16: 837–847, https://doi.org/10.1093/hmg/ddm029.Search in Google Scholar PubMed

Zhang, Z.X., Gao, P.F., Guo, X.F., Wang, H., and Zhang, H.S. (2011). 1,3,5,7-tetramethyl-8-(N-hydroxysuccinimidyl butyric ester) difluoroboradiaza-s-indacene as a new fluorescent labeling reagent for HPLC determination of amino acid neurotransmitters in the cerebral cortex of mice. Anal. Bioanal. Chem. 401: 1905–1914, https://doi.org/10.1007/s00216-011-5253-3.Search in Google Scholar PubMed

Zhang, A., Sun, H., Yan, G., Wang, P., and Wang, X. (2015a). Metabolomics for biomarker discovery: moving to the clinic. Biomed Res. Int. 2015: 354671, https://doi.org/10.1155/2015/354671.Search in Google Scholar PubMed PubMed Central

Zhang, J., Fang, X., Zhou, Y., Deng, X., Lu, Y., Li, J., Li, S., Wang, B., and Xu, R. (2015b). The possible damaged mechanism and the preventive effect of monosialotetrahexosylganglioside in a rat model of cerebral ischemia-reperfusion injury. J. Stroke Cerebrovasc. Dis. 24: 1471–1478, https://doi.org/10.1016/j.jstrokecerebrovasdis.2015.02.008.Search in Google Scholar PubMed

Zhang, Q., Wang, J., Zhang, C., Liao, S., Li, P., Xu, D., Lv, Y., Yang, M., and Kong, L. (2016). The components of Huang-Lian-Jie-Du-Decoction act synergistically to exert protective effects in a rat ischemic stroke model. Oncotarget 7: 80872–80887, https://doi.org/10.18632/oncotarget.12645.Search in Google Scholar PubMed PubMed Central

Zhang, Q., Wang, J., Liao, S., Li, P., Xu, D., Lv, Y., Yang, M., and Kong, L. (2017a). Optimization of Huang-Lian-Jie-Du-decoction for ischemic stroke treatment and mechanistic study by metabolomic profiling and network analysis. Front. Pharmacol. 8: 165, https://doi.org/10.3389/fphar.2017.00165.Search in Google Scholar PubMed PubMed Central

Zhang, Q., Fu, X., Wang, J., Yang, M., and Kong, L. (2017b). Treatment effects of ischemic stroke by berberine, baicalin, and jasminoidin from Huang-Lian-Jie-Du-Decoction (HLJDD) explored by an integrated metabolomics approach. Oxidative Med. Cell. Longev. 2017: 9848594.10.1155/2017/9848594Search in Google Scholar PubMed PubMed Central

Zhong, C., Lv, L., Liu, C., Zhao, L., Zhou, M., Sun, W., Xu, T., and Tong, W. (2014). High homocysteine and blood pressure related to poor outcome of acute ischemia stroke in Chinese population. PloS One 9: e107498, https://doi.org/10.1371/journal.pone.0107498.Search in Google Scholar PubMed PubMed Central

Received: 2021-03-26
Accepted: 2021-06-09
Published Online: 2021-07-01
Published in Print: 2022-02-23

© 2021 Walter de Gruyter GmbH, Berlin/Boston

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