Background Ability to accurately determine time of stroke onset remains challenging. We hypothesized that an early biomarker characterized by a rapid increase in blood after stroke onset may help defining better the time window during which an acute stroke patient may be candidate for intravenous thrombolysis or other intravascular procedures. Methods The blood level of 29 proteins was measured by immunoassays on a prospective cohort of stroke patients (N = 103) and controls (N = 132). Mann-Whitney U tests, ROC curves and diagnostic odds ratios were applied to evaluate their clinical performances. Results Among the 29 molecules tested, GST-π concentration was the most significantly elevated marker in the blood of stroke patients (p<0.001). More importantly, GST-π displayed the best area under the curve (AUC, 0.79) and the best diagnostic odds ratios (10.0) for discriminating early (N = 22, <3 h of stroke onset) vs. late stroke patients (N = 81, >3 h after onset). According to goal-oriented distinct cut-offs (sensitivity(Se)-oriented: 17.7 or specificity(Sp)-oriented: 65.2 ug/L), the GST-π test obtained 91%Se/50%Sp and 50%Se/91%Sp, respectively. Moreover, GST-π showed also the highest AUC (0.83) and performances for detecting patients treated with tPA (N = 12) compared to ineligible patients (N = 103). Conclusions This study demonstrates that GST-π can accurately predict the time of stroke onset in over 50% of early stroke patients. The GST-π test could therefore complement current guidelines for tPA administration and potentially increase the number of patients accessing thrombolysis.
References
[1]
Perkins CJ, Kahya E, Roque CT, Roche PE, Newman GC (2001) Fluid-attenuated inversion recovery and diffusion- and perfusion-weighted MRI abnormalities in 117 consecutive patients with stroke symptoms. Stroke 32: 2774–2781.
[2]
Thomalla G, Rossbach P, Rosenkranz M, Siemonsen S, Krutzelmann A, et al. (2009) Negative fluid-attenuated inversion recovery imaging identifies acute ischemic stroke at 3 hours or less. Ann Neurol 65: 724–732.
[3]
Aoki J, Kimura K, Iguchi Y, Shibazaki K, Sakai K, et al. (2010) FLAIR can estimate the onset time in acute ischemic stroke patients. Journal of the neurological sciences 293: 39–44.
[4]
Ebinger M, Galinovic I, Rozanski M, Brunecker P, Endres M, et al. (2010) Fluid-attenuated inversion recovery evolution within 12 hours from stroke onset: a reliable tissue clock? Stroke; a journal of cerebral circulation 41: 250–255.
[5]
Petkova M, Rodrigo S, Lamy C, Oppenheim G, Touze E, et al. (2010) MR imaging helps predict time from symptom onset in patients with acute stroke: implications for patients with unknown onset time. Radiology 257: 782–792.
[6]
Thomalla G, Cheng B, Ebinger M, Hao Q, Tourdias T, et al. (2011) DWI-FLAIR mismatch for the identification of patients with acute ischaemic stroke within 4.5 h of symptom onset (PRE-FLAIR): a multicentre observational study. Lancet Neurol 10: 978–986.
[7]
Grotta JC, Burgin WS, El-Mitwalli A, Long M, Campbell M, et al. (2001) Intravenous tissue-type plasminogen activator therapy for ischemic stroke: Houston experience 1996 to 2000. Archives of Neurology 58: 2009–2013.
[8]
Nadeau JO, Shi S, Fang J, Kapral MK, Richards JA, et al. (2005) TPA use for stroke in the Registry of the Canadian Stroke Network. The Canadian Journal of Neurological Sciences 32: 433–439.
[9]
Kleindorfer D, Lindsell CJ, Brass L, Koroshetz W, Broderick JP (2008) National US estimates of recombinant tissue plasminogen activator use: ICD-9 codes substantially underestimate. Stroke 39: 924–928.
[10]
Schumacher HC, Bateman BT, Boden-Albala B, Berman MF, Mohr JP, et al. (2007) Use of thrombolysis in acute ischemic stroke: analysis of the Nationwide Inpatient Sample 1999 to 2004. Ann Emerg Med 50: 99–107.
[11]
Khaja AM, Grotta JC (2007) Established treatments for acute ischaemic stroke. Lancet 369: 319–330.
[12]
Fink JN, Kumar S, Horkan C, Linfante I, Selim MH, et al. (2002) The stroke patient who woke up: clinical and radiological features, including diffusion and perfusion MRI. Stroke 33: 988–993.
[13]
Albers GW, Amarenco P, Easton JD, Sacco RL, Teal P (2008) Antithrombotic and thrombolytic therapy for ischemic stroke: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines (8th Edition). Chest 133: 630S–669S.
[14]
Foerch C, Wunderlich MT, Dvorak F, Humpich M, Kahles T, et al. (2007) Elevated serum S100B levels indicate a higher risk of hemorrhagic transformation after thrombolytic therapy in acute stroke. Stroke 38: 2491–2495.
[15]
Sienkiewicz-Jarosz H, Galecka-Wolska M, Bidzinski A, Turzynska D, Sobolewska A, et al. (2009) Predictive value of selected biochemical markers of brain damage for functional outcome in ischaemic stroke patients. Polish Journal of Neurology and Neurosurgery 43: 126–133.
[16]
Herrmann M, Vos P, Wunderlich MT, de Bruijn CH, Lamers KJ (2000) Release of glial tissue-specific proteins after acute stroke: A comparative analysis of serum concentrations of protein S-100B and glial fibrillary acidic protein. Stroke 31: 2670–2677.
[17]
Missler U, Wiesmann M, Friedrich C, Kaps M (1997) S-100 protein and neuron-specific enolase concentrations in blood as indicators of infarction volume and prognosis in acute ischemic stroke. Stroke 28: 1956–1960.
[18]
Montaner J, Alvarez-Sabin J, Molina CA, Angles A, Abilleira S, et al. (2001) Matrix metalloproteinase expression is related to hemorrhagic transformation after cardioembolic stroke. Stroke 32: 2762–2767.
[19]
Montaner J, Molina CA, Monasterio J, Abilleira S, Arenillas JF, et al. (2003) Matrix metalloproteinase-9 pretreatment level predicts intracranial hemorrhagic complications after thrombolysis in human stroke. Circulation 107: 598–603.
[20]
Cunningham RT, Young IS, Winder J, O'Kane MJ, McKinstry S, et al. (1991) Serum neurone specific enolase (NSE) levels as an indicator of neuronal damage in patients with cerebral infarction. European Journal of Clinical Investigation 21: 497–500.
[21]
Brouns R, De Vil B, Cras P, De Surgeloose D, Marien P, et al. Neurobiochemical markers of brain damage in cerebrospinal fluid of acute ischemic stroke patients. Clinical Chemistry 56: 451–458.
[22]
Burgess JA, Lescuyer P, Hainard A, Burkhard PR, Turck N, et al. (2006) Identification of brain cell death associated proteins in human post-mortem cerebrospinal fluid. Journal of Proteome Research 5: 1674–1681.
[23]
Dayon L, Hainard A, Licker V, Turck N, Kuhn K, et al. (2008) Relative quantification of proteins in human cerebrospinal fluids by MS/MS using 6-plex isobaric tags. Analytical Chemistry 80: 2921–2931.
[24]
Lescuyer P, Allard L, Zimmermann-Ivol CG, Burgess JA, Hughes-Frutiger S, et al. (2004) Identification of post-mortem cerebrospinal fluid proteins as potential biomarkers of ischemia and neurodegeneration. Proteomics 4: 2234–2241.
[25]
Zimmermann-Ivol CG, Burkhard PR, Le Floch-Rohr J, Allard L, Hochstrasser DF, et al. (2004) Fatty acid binding protein as a serum marker for the early diagnosis of stroke: a pilot study. Molecular and Cellular Proteomics 3: 66–72.
[26]
Allard L, Turck N, Burkhard PR, al e (2007) UFD1 as a blood marker for the early diagnosis of ischemic stroke. Biomarker Insights 2: 155–164.
[27]
Allard L, Burkhard PR, Lescuyer P, Burgess JA, Walter N, et al. (2005) PARK7 and nucleoside diphosphate kinase A as plasma markers for the early diagnosis of stroke. Clinical Chemistry 51: 2043–2051.
[28]
Mendioroz M, Fernandez-Cadenas I, Rosell A, Delgado P, Domingues-Montanari S, et al. (2011) Osteopontin predicts long-term functional outcome among ischemic stroke patients. J Neurol 258: 486–493.
[29]
Tuck MK, Chan DW, Chia D, Godwin AK, Grizzle WE, et al. (2009) Standard operating procedures for serum and plasma collection: early detection research network consensus statement standard operating procedure integration working group. J Proteome Res 8: 113–117.
[30]
Hainard A, Tiberti N, Robin X, Lejon V, Ngoyi DM, et al. (2009) A Combined CXCL10, CXCL8 and H-FABP Panel for the Staging of Human African Trypanosomiasis Patients. PLoS Neglected Tropical Diseases 3: e459.
[31]
Turck N, Vutskits L, Sanchez-Pena P, Robin X, Hainard A, et al. (2010) A multiparameter panel method for outcome prediction following aneurysmal subarachnoid hemorrhage. Intensive Care Medicine 36: 107–115.
[32]
Glas AS, Lijmer JG, Prins MH, Bonsel GJ, Bossuyt PM (2003) The diagnostic odds ratio: a single indicator of test performance. Journal of Clinical Epidemiology 56: 1129–1135.
[33]
Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, et al. (2011) pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 12: 77.
[34]
Awasthi YC, Sharma R, Singhal SS (1994) Human glutathione S-transferases. International Journal of Biochemistry 26: 295–308.
[35]
Smeyne M, Boyd J, Raviie Shepherd K, Jiao Y, Pond BB, et al. (2007) GSTpi expression mediates dopaminergic neuron sensitivity in experimental parkinsonism. Proceedings of the National Academy of Sciences 104: 1977–1982.
[36]
Martinez-Lara E, Siles E, Hernandez R, Canuelo AR, Luisa del Moral M, et al. (2003) Glutathione S-transferase isoenzymatic response to aging in rat cerebral cortex and cerebellum. Neurobiology of Aging 24: 501–509.
[37]
Tamura Y, Kataoka Y, Cui Y, Takamori Y, Watanabe Y, et al. (2007) Intracellular translocation of glutathione S-transferase pi during oligodendrocyte differentiation in adult rat cerebral cortex in vivo. Neuroscience 148: 535–540.
[38]
Bauer B, Hartz AM, Lucking JR, Yang X, Pollack GM, et al. (2008) Coordinated nuclear receptor regulation of the efflux transporter, Mrp2, and the phase-II metabolizing enzyme, GSTpi, at the blood-brain barrier. Journal of Cerebral Blood Flow and Metabolism 28: 1222–1234.
[39]
Shen H, Ranganathan S, Kuzmich S, Tew KD (1995) Influence of ethacrynic acid on glutathione S-transferase pi transcript and protein half-lives in human colon cancer cells. Biochem Pharmacol 50: 1233–1238.
