Advertisement

Blood Biomarkers for Stroke Differentiation

  • Deepti Vibha
  • Shubham Misra
Protocol
Part of the Neuromethods book series (NM, volume 147)

Abstract

Acute stroke is a neurological emergency. Time sensitive treatment decisions depend on the correct diagnosis of stroke and its subtype: ischemic or hemorrhagic. An early diagnosis of ischemic stroke is required for prompt decision making and administration of thrombolytic therapy within the time frame. Non-contrast computed tomography (CT) scan is currently used for the diagnosis of stroke. However, CT scan facility is not widely available in resource limited settings. Therefore, there is an urgent need to identify blood-based biomarkers for rapid diagnosis and differentiation of stroke in the acute stages for better treatment and management strategies. A blood test that can rapidly identify the correct stroke type could help the practitioners in deciding stroke type specific treatment, thereby improving the management of stroke. This chapter gives an update on all the diagnostic test studies conducted to determine potential blood-based protein biomarkers to diagnose and differentiate ischemic stroke from hemorrhagic stroke, stroke mimics, transient ischemic attack, and mixed cases of ischemic stroke with hemorrhagic transformation.

Key words

Ischemic stroke Hemorrhagic stroke Transient ischemic attack Blood biomarkers Stroke differentiation Stroke mimics Hemorrhagic transformation 

References

  1. 1.
    Feigin VL, Roth GA, Naghavi M, Parmar P, Krishnamurthi R, Chugh S, Mensah GA, Norrving B, Shiue I, Ng M, Estep K, Cercy K, Murray CJL, Forouzanfar MH, Global Burden of Diseases, Injuries and Risk Factors Study 2013 and Stroke Experts Writing Group (2016) Global burden of stroke and risk factors in 188 countries, during 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet Neurol 15:913–924.  https://doi.org/10.1016/S1474-4422(16)30073-4CrossRefPubMedGoogle Scholar
  2. 2.
    Lozano R, Naghavi M, Foreman K, Lim S, Shibuya K, Aboyans V, Abraham J, Adair T, Aggarwal R, Ahn SY, Alvarado M, Anderson HR, Anderson LM, Andrews KG, Atkinson C, Baddour LM, Barker-Collo S, Bartels DH, Bell ML, Benjamin EJ, Bennett D, Bhalla K, Bikbov B, Bin Abdulhak A, Birbeck G, Blyth F, Bolliger I, Boufous S, Bucello C, Burch M, Burney P, Carapetis J, Chen H, Chou D, Chugh SS, Coffeng LE, Colan SD, Colquhoun S, Colson KE, Condon J, Connor MD, Cooper LT, Corriere M, Cortinovis M, de Vaccaro KC, Couser W, Cowie BC, Criqui MH, Cross M, Dabhadkar KC, Dahodwala N, De Leo D, Degenhardt L, Delossantos A, Denenberg J, Des Jarlais DC, Dharmaratne SD, Dorsey ER, Driscoll T, Duber H, Ebel B, Erwin PJ, Espindola P, Ezzati M, Feigin V, Flaxman AD, Forouzanfar MH, Fowkes FGR, Franklin R, Fransen M, Freeman MK, Gabriel SE, Gakidou E, Gaspari F, Gillum RF, Gonzalez-Medina D, Halasa YA, Haring D, Harrison JE, Havmoeller R, Hay RJ, Hoen B, Hotez PJ, Hoy D, Jacobsen KH, James SL, Jasrasaria R, Jayaraman S, Johns N, Karthikeyan G, Kassebaum N, Keren A, Khoo J-P, Knowlton LM, Kobusingye O, Koranteng A, Krishnamurthi R, Lipnick M, Lipshultz SE, Ohno SL, Mabweijano J, MacIntyre MF, Mallinger L, March L, Marks GB, Marks R, Matsumori A, Matzopoulos R, Mayosi BM, McAnulty JH, McDermott MM, McGrath J, Mensah GA, Merriman TR, Michaud C, Miller M, Miller TR, Mock C, Mocumbi AO, Mokdad AA, Moran A, Mulholland K, Nair MN, Naldi L, Narayan KMV, Nasseri K, Norman P, O’Donnell M, Omer SB, Ortblad K, Osborne R, Ozgediz D, Pahari B, Pandian JD, Rivero AP, Padilla RP, Perez-Ruiz F, Perico N, Phillips D, Pierce K, Pope CA, Porrini E, Pourmalek F, Raju M, Ranganathan D, Rehm JT, Rein DB, Remuzzi G, Rivara FP, Roberts T, De León FR, Rosenfeld LC, Rushton L, Sacco RL, Salomon JA, Sampson U, Sanman E, Schwebel DC, Segui-Gomez M, Shepard DS, Singh D, Singleton J, Sliwa K, Smith E, Steer A, Taylor JA, Thomas B, Tleyjeh IM, Towbin JA, Truelsen T, Undurraga EA, Venketasubramanian N, Vijayakumar L, Vos T, Wagner GR, Wang M, Wang W, Watt K, Weinstock MA, Weintraub R, Wilkinson JD, Woolf AD, Wulf S, Yeh P-H, Yip P, Zabetian A, Zheng Z-J, Lopez AD, Murray CJL, AlMazroa MA, Memish ZA (2012) Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet Lond Engl 380:2095–2128.  https://doi.org/10.1016/S0140-6736(12)61728-0CrossRefGoogle Scholar
  3. 3.
    Nor AM, Davis J, Sen B, Shipsey D, Louw SJ, Dyker AG, Davis M, Ford GA (2005) The Recognition of Stroke in the Emergency Room (ROSIER) scale: development and validation of a stroke recognition instrument. Lancet Neurol 4:727–734.  https://doi.org/10.1016/S1474-4422(05)70201-5CrossRefPubMedGoogle Scholar
  4. 4.
    Hand PJ, Kwan J, Lindley RI, Dennis MS, Wardlaw JM (2006) Distinguishing between stroke and mimic at the bedside: the brain attack study. Stroke 37:769–775.  https://doi.org/10.1161/01.STR.0000204041.13466.4cCrossRefPubMedGoogle Scholar
  5. 5.
    Libman RB, Wirkowski E, Alvir J, Rao TH (1995) Conditions that mimic stroke in the emergency department. Implications for acute stroke trials. Arch Neurol 52:1119–1122CrossRefGoogle Scholar
  6. 6.
    Grotta JC, Chiu D, Lu M, Patel S, Levine SR, Tilley BC, Brott TG, Haley EC, Lyden PD, Kothari R, Frankel M, Lewandowski CA, Libman R, Kwiatkowski T, Broderick JP, Marler JR, Corrigan J, Huff S, Mitsias P, Talati S, Tanne D (1999) Agreement and variability in the interpretation of early CT changes in stroke patients qualifying for intravenous rtPA therapy. Stroke J Cereb Circ 30:1528–1533CrossRefGoogle Scholar
  7. 7.
    Allard L, Lescuyer P, Burgess J, Leung K-Y, Ward M, Walter N, Burkhard PR, Corthals G, Hochstrasser DF, Sanchez J-C (2004) ApoC-I and ApoC-III as potential plasmatic markers to distinguish between ischemic and hemorrhagic stroke. Proteomics 4:2242–2251.  https://doi.org/10.1002/pmic.200300809CrossRefPubMedGoogle Scholar
  8. 8.
    Lopez MF, Sarracino DA, Prakash A, Athanas M, Krastins B, Rezai T, Sutton JN, Peterman S, Gvozdyak O, Chou S, Lo E, Buonanno F, Ning M (2012) Discrimination of ischemic and hemorrhagic strokes using a multiplexed, mass spectrometry-based assay for serum apolipoproteins coupled to multi-marker ROC algorithm. Proteomics Clin Appl 6:190–200.  https://doi.org/10.1002/prca.201100041CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Walsh KB, Hart K, Roll S, Sperling M, Unruh D, Davidson WS, Lindsell CJ, Adeoye O (2016) Apolipoprotein A-I and paraoxonase-1 are potential blood biomarkers for ischemic stroke diagnosis. J Stroke Cerebrovasc Dis 25:1360–1365.  https://doi.org/10.1016/j.jstrokecerebrovasdis.2016.02.027CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Kim MH, Kang SY, Kim MC, Lee WI (2010) Plasma biomarkers in the diagnosis of acute ischemic stroke. Ann Clin Lab Sci 40:336–341PubMedGoogle Scholar
  11. 11.
    Katsanos AH, Makris K, Stefani D, Koniari K, Gialouri E, Lelekis M, Chondrogianni M, Zompola C, Dardiotis E, Rizos I, Parissis J, Boutati E, Voumvourakis K, Tsivgoulis G (2017) Plasma glial fibrillary acidic protein in the differential diagnosis of intracerebral hemorrhage. Stroke 48:2586–2588.  https://doi.org/10.1161/STROKEAHA.117.018409CrossRefPubMedGoogle Scholar
  12. 12.
    Rozanski M, Waldschmidt C, Kunz A, Grittner U, Ebinger M, Wendt M, Winter B, Bollweg K, Villringer K, Fiebach JB, Audebert HJ (2017) Glial fibrillary acidic protein for prehospital diagnosis of intracerebral hemorrhage. Cerebrovasc Dis 43:76–81.  https://doi.org/10.1159/000453460CrossRefPubMedGoogle Scholar
  13. 13.
    Foerch C, Curdt I, Yan B, Dvorak F, Hermans M, Berkefeld J, Raabe A, Neumann-Haefelin T, Steinmetz H, Sitzer M (2006) Serum glial fibrillary acidic protein as a biomarker for intracerebral haemorrhage in patients with acute stroke. J Neurol Neurosurg Psychiatry 77:181–184.  https://doi.org/10.1136/jnnp.2005.074823CrossRefPubMedGoogle Scholar
  14. 14.
    Foerch C, Niessner M, Back T, Bauerle M, De Marchis GM, Ferbert A, Grehl H, Hamann GF, Jacobs A, Kastrup A, Klimpe S, Palm F, Thomalla G, Worthmann H, Sitzer M, BE FAST Study Group (2012) Diagnostic accuracy of plasma glial fibrillary acidic protein for differentiating intracerebral hemorrhage and cerebral ischemia in patients with symptoms of acute stroke. Clin Chem 58:237–245.  https://doi.org/10.1373/clinchem.2011.172676CrossRefGoogle Scholar
  15. 15.
    Dvorak F, Haberer I, Sitzer M, Foerch C (2009) Characterisation of the diagnostic window of serum glial fibrillary acidic protein for the differentiation of intracerebral haemorrhage and ischaemic stroke. Cerebrovasc Dis 27:37–41.  https://doi.org/10.1159/000172632CrossRefPubMedGoogle Scholar
  16. 16.
    Undén J, Strandberg K, Malm J, Campbell E, Rosengren L, Stenflo J, Norrving B, Romner B, Lindgren A, Andsberg G (2009) Explorative investigation of biomarkers of brain damage and coagulation system activation in clinical stroke differentiation. J Neurol 256:72–77.  https://doi.org/10.1007/s00415-009-0054-8CrossRefPubMedGoogle Scholar
  17. 17.
    Xiong L, Yang Y, Zhang M, Xu W (2015) The use of serum glial fibrillary acidic protein test as a promising tool for intracerebral hemorrhage diagnosis in Chinese patients and prediction of the short-term functional outcomes. Neurol Sci 36:2081–2087.  https://doi.org/10.1007/s10072-015-2317-8CrossRefPubMedGoogle Scholar
  18. 18.
    Ren C, Kobeissy F, Alawieh A, Li N, Li N, Zibara K, Zoltewicz S, Guingab-Cagmat J, Larner SF, Ding Y, Hayes RL, Ji X, Mondello S (2016) Assessment of serum UCH-L1 and GFAP in acute stroke patients. Sci Rep 6:24588.  https://doi.org/10.1038/srep24588CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Llombart V, García-Berrocoso T, Bustamante A, Giralt D, Rodriguez-Luna D, Muchada M, Penalba A, Boada C, Hernández-Guillamon M, Montaner J (2016) Plasmatic retinol-binding protein 4 and glial fibrillary acidic protein as biomarkers to differentiate ischemic stroke and intracerebral hemorrhage. J Neurochem 136:416–424.  https://doi.org/10.1111/jnc.13419CrossRefPubMedGoogle Scholar
  20. 20.
    Luger S, Witsch J, Dietz A, Hamann GF, Minnerup J, Schneider H, Sitzer M, Wartenberg KE, Niessner M, Foerch C, BE FAST II and the IGNITE Study Groups (2017) Glial fibrillary acidic protein serum levels distinguish between intracerebral hemorrhage and cerebral ischemia in the early phase of stroke. Clin Chem 63:377–385.  https://doi.org/10.1373/clinchem.2016.263335CrossRefGoogle Scholar
  21. 21.
    Zhou S, Bao J, Wang Y, Pan S (2016) S100β as a biomarker for differential diagnosis of intracerebral hemorrhage and ischemic stroke. Neurol Res 38:327–332.  https://doi.org/10.1080/01616412.2016.1152675CrossRefPubMedGoogle Scholar
  22. 22.
    Roudbary SA, Saadat F, Forghanparast K, Sohrabnejad R (2011) Serum C-reactive protein level as a biomarker for differentiation of ischemic from hemorrhagic stroke. Acta Med Iran 49:149–152PubMedGoogle Scholar
  23. 23.
    Montaner J, Mendioroz M, Delgado P, García-Berrocoso T, Giralt D, Merino C, Ribó M, Rosell A, Penalba A, Fernández-Cadenas I, Romero F, Molina C, Alvarez-Sabín J, Hernández-Guillamon M (2012) Differentiating ischemic from hemorrhagic stroke using plasma biomarkers: the S100B/RAGE pathway. J Proteome 75:4758–4765.  https://doi.org/10.1016/j.jprot.2012.01.033CrossRefGoogle Scholar
  24. 24.
    Kavalci C, Genchallac H, Durukan P, Cevik Y (2011) Value of biomarker-based diagnostic test in differential diagnosis of hemorrhagic-ischemic stroke. Bratisl Lek Listy 112:398–401PubMedGoogle Scholar
  25. 25.
    Bustamante A, López-Cancio E, Pich S, Penalba A, Giralt D, García-Berrocoso T, Ferrer-Costa C, Gasull T, Hernández-Pérez M, Millan M, Rubiera M, Cardona P, Cano L, Quesada H, Terceño M, Silva Y, Castellanos M, Garces M, Reverté S, Ustrell X, Marés R, Baiges JJ, Serena J, Rubio F, Salas E, Dávalos A, Montaner J (2017) Blood biomarkers for the early diagnosis of stroke: the Stroke-Chip Study. Stroke 48:2419–2425.  https://doi.org/10.1161/strokeaha.117.017076CrossRefPubMedGoogle Scholar
  26. 26.
    Rainer TH, Wong KS, Lam W, Lam NYL, Graham CA, Lo YMD (2007) Comparison of plasma beta-globin DNA and S-100 protein concentrations in acute stroke. Clin Chim Acta Int J Clin Chem 376:190–196.  https://doi.org/10.1016/j.cca.2006.08.025CrossRefGoogle Scholar
  27. 27.
    Sharma R, Macy S, Richardson K, Lokhnygina Y, Laskowitz DT (2014) A blood-based biomarker panel to detect acute stroke. J Stroke Cerebrovasc Dis 23:910–918.  https://doi.org/10.1016/j.jstrokecerebrovasdis.2013.07.034CrossRefPubMedGoogle Scholar
  28. 28.
    Glickman SW, Phillips S, Anstrom KJ, Laskowitz DT, Cairns CB (2011) Discriminative capacity of biomarkers for acute stroke in the emergency department. J Emerg Med 41:333–339.  https://doi.org/10.1016/j.jemermed.2010.02.025CrossRefPubMedGoogle Scholar
  29. 29.
    González-García S, González-Quevedo A, Peña-Sánchez M, Menéndez-Saínz C, Fernández-Carriera R, Arteche-Prior M, Pando-Cabrera A, Fernández-Concepción O (2012) Serum neuron-specific enolase and S100 calcium binding protein B biomarker levels do not improve diagnosis of acute stroke. J R Coll Physicians Edinb 42:199–204.  https://doi.org/10.4997/JRCPE.2012.302CrossRefPubMedGoogle Scholar
  30. 30.
    An S-A, Kim J, Kim O-J, Kim J-K, Kim N-K, Song J, Oh S-H (2013) Limited clinical value of multiple blood markers in the diagnosis of ischemic stroke. Clin Biochem 46:710–715.  https://doi.org/10.1016/j.clinbiochem.2013.02.005CrossRefPubMedGoogle Scholar
  31. 31.
    Airas L, Lindsberg PJ, Karjalainen-Lindsberg M-L, Mononen I, Kotisaari K, Smith DJ, Jalkanen S (2008) Vascular adhesion protein-1 in human ischaemic stroke. Neuropathol Appl Neurobiol 34:394–402.  https://doi.org/10.1111/j.1365-2990.2007.00911.xCrossRefPubMedGoogle Scholar
  32. 32.
    Doehner W, von Haehling S, Suhr J, Ebner N, Schuster A, Nagel E, Melms A, Wurster T, Stellos K, Gawaz M, Bigalke B (2012) Elevated plasma levels of neuropeptide proenkephalin a predict mortality and functional outcome in ischemic stroke. J Am Coll Cardiol 60:346–354.  https://doi.org/10.1016/j.jacc.2012.04.024CrossRefPubMedGoogle Scholar
  33. 33.
    Ahn JH, Choi SC, Lee WG, Jung YS (2011) The usefulness of albumin-adjusted ischemia-modified albumin index as early detecting marker for ischemic stroke. Neurol Sci 32:133–138.  https://doi.org/10.1007/s10072-010-0457-4CrossRefPubMedGoogle Scholar
  34. 34.
    Meng R, Li Z-Y, Ji X, Ding Y, Meng S, Wang X (2011) Antithrombin III associated with fibrinogen predicts the risk of cerebral ischemic stroke. Clin Neurol Neurosurg 113:380–386.  https://doi.org/10.1016/j.clineuro.2010.12.016CrossRefPubMedGoogle Scholar
  35. 35.
    Dambinova SA, Bettermann K, Glynn T, Tews M, Olson D, Weissman JD, Sowell RL (2012) Diagnostic potential of the NMDA receptor peptide assay for acute ischemic stroke. PLoS One 7:e42362.  https://doi.org/10.1371/journal.pone.0042362CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Dassan P, Keir G, Jäger HR, Brown MM (2012) Value of measuring serum vascular endothelial growth factor levels in diagnosing acute ischemic stroke. Int J Stroke 7:454–459.  https://doi.org/10.1111/j.1747-4949.2011.00677.xCrossRefPubMedGoogle Scholar
  37. 37.
    Wendt M, Ebinger M, Kunz A, Rozanski M, Waldschmidt C, Weber JE, Winter B, Koch PM, Nolte CH, Hertel S, Ziera T, Audebert HJ, STEMO Consortium (2015) Copeptin levels in patients with acute ischemic stroke and stroke mimics. Stroke 46:2426–2431.  https://doi.org/10.1161/STROKEAHA.115.009877CrossRefGoogle Scholar
  38. 38.
    Laskowitz DT, Kasner SE, Saver J, Remmel KS, Jauch EC, BRAIN Study Group (2009) Clinical usefulness of a biomarker-based diagnostic test for acute stroke: the Biomarker Rapid Assessment in Ischemic Injury (BRAIN) Study. Stroke 40:77–85.  https://doi.org/10.1161/STROKEAHA.108.516377CrossRefGoogle Scholar
  39. 39.
    Sibon I, Rouanet F, Meissner W, Orgogozo JM (2009) Use of the Triage Stroke Panel in a neurologic emergency service. Am J Emerg Med 27:558–562.  https://doi.org/10.1016/j.ajem.2008.05.001CrossRefPubMedGoogle Scholar
  40. 40.
    Knauer C, Knauer K, Müller S, Ludolph AC, Bengel D, Müller HP, Huber R (2012) A biochemical marker panel in MRI-proven hyperacute ischemic stroke-a prospective study. BMC Neurol 12:14.  https://doi.org/10.1186/1471-2377-12-14CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Montaner J, Mendioroz M, Ribó M, Delgado P, Quintana M, Penalba A, Chacón P, Molina C, Fernández-Cadenas I, Rosell A, Alvarez-Sabín J (2011) A panel of biomarkers including caspase-3 and D-dimer may differentiate acute stroke from stroke-mimicking conditions in the emergency department. J Intern Med 270:166–174.  https://doi.org/10.1111/j.1365-2796.2010.02329.xCrossRefPubMedGoogle Scholar
  42. 42.
    Montaner J, Alvarez-Sabín J, Molina CA, Anglés A, Abilleira S, Arenillas J, Monasterio J (2001) Matrix metalloproteinase expression is related to hemorrhagic transformation after cardioembolic stroke. Stroke 32:2762–2767CrossRefGoogle Scholar
  43. 43.
    Montaner J, Molina CA, Monasterio J, Abilleira S, Arenillas JF, Ribó M, Quintana M, Alvarez-Sabín J (2003) Matrix metalloproteinase-9 pretreatment level predicts intracranial hemorrhagic complications after thrombolysis in human stroke. Circulation 107:598–603CrossRefGoogle Scholar
  44. 44.
    Castellanos M, Leira R, Serena J, Pumar JM, Lizasoain I, Castillo J, Dávalos A (2003) Plasma metalloproteinase-9 concentration predicts hemorrhagic transformation in acute ischemic stroke. Stroke 34:40–46CrossRefGoogle Scholar
  45. 45.
    Castellanos M, Leira R, Serena J, Blanco M, Pedraza S, Castillo J, Dávalos A (2004) Plasma cellular-fibronectin concentration predicts hemorrhagic transformation after thrombolytic therapy in acute ischemic stroke. Stroke 35:1671–1676.  https://doi.org/10.1161/01.STR.0000131656.47979.39CrossRefPubMedGoogle Scholar
  46. 46.
    Castellanos M, Sobrino T, Millán M, García M, Arenillas J, Nombela F, Brea D, Perez de la Ossa N, Serena J, Vivancos J, Castillo J, Dávalos A (2007) Serum cellular fibronectin and matrix metalloproteinase-9 as screening biomarkers for the prediction of parenchymal hematoma after thrombolytic therapy in acute ischemic stroke: a multicenter confirmatory study. Stroke 38:1855–1859.  https://doi.org/10.1161/STROKEAHA.106.481556CrossRefPubMedGoogle Scholar
  47. 47.
    Banhawy EE, Amer H, Younes K, Nada MAF, Helmy H, Hassan MI (2014) Plasma matrix metalloproteinase-9 (MMP-9) and hemorrhagic transformation in acute ischemic stroke. Egypt J Neurol Psychiat Neurosurg 51:159–166Google Scholar
  48. 48.
    Trouillas P, Derex L, Philippeau F, Nighoghossian N, Honnorat J, Hanss M, Ffrench P, Adeleine P, Dechavanne M (2004) Early fibrinogen degradation coagulopathy is predictive of parenchymal hematomas in cerebral rt-PA thrombolysis: a study of 157 cases. Stroke 35:1323–1328.  https://doi.org/10.1161/01.STR.0000126040.99024.cfCrossRefPubMedGoogle Scholar
  49. 49.
    Cocho D, Borrell M, Martí-Fàbregas J, Montaner J, Castellanos M, Bravo Y, Molina-Porcel L, Belvís R, Díaz-Manera J-A, Martínez-Domeño A, Martínez-Lage M, Millán M, Fontcuberta J, Martí-Vilalta J-L (2006) Pretreatment hemostatic markers of symptomatic intracerebral hemorrhage in patients treated with tissue plasminogen activator. Stroke 37:996–999.  https://doi.org/10.1161/01.str.0000206461.71624.50CrossRefPubMedGoogle Scholar
  50. 50.
    Foerch C, Wunderlich MT, Dvorak F, Humpich M, Kahles T, Goertler M, Alvarez-Sabín J, Wallesch CW, Molina CA, Steinmetz H, Sitzer M, Montaner J (2007) Elevated serum S100B levels indicate a higher risk of hemorrhagic transformation after thrombolytic therapy in acute stroke. Stroke 38:2491–2495.  https://doi.org/10.1161/STROKEAHA.106.480111CrossRefPubMedGoogle Scholar
  51. 51.
    Mendioroz M, Fernández-Cadenas I, Alvarez-Sabín J, Rosell A, Quiroga D, Cuadrado E, Delgado P, Rubiera M, Ribó M, Molina C, Montaner J (2009) Endogenous activated protein C predicts hemorrhagic transformation and mortality after tissue plasminogen activator treatment in stroke patients. Cerebrovasc Dis 28:143–150.  https://doi.org/10.1159/000225907CrossRefPubMedGoogle Scholar
  52. 52.
    Choi K-H, Park M-S, Kim J-T, Nam T-S, Choi S-M, Kim B-C, Kim M-K, Cho K-H (2012) The serum ferritin level is an important predictor of hemorrhagic transformation in acute ischaemic stroke. Eur J Neurol 19:570–577.  https://doi.org/10.1111/j.1468-1331.2011.03564.xCrossRefPubMedGoogle Scholar
  53. 53.
    Kazmierski R, Michalak S, Wencel-Warot A, Nowinski WL (2012) Serum tight-junction proteins predict hemorrhagic transformation in ischemic stroke patients. Neurology 79:1677–1685.  https://doi.org/10.1212/WNL.0b013e31826e9a83CrossRefPubMedGoogle Scholar
  54. 54.
    Guo Z, Yu S, Xiao L, Chen X, Ye R, Zheng P, Dai Q, Sun W, Zhou C, Wang S, Zhu W, Liu X (2016) Dynamic change of neutrophil to lymphocyte ratio and hemorrhagic transformation after thrombolysis in stroke. J Neuroinflammation 13:199.  https://doi.org/10.1186/s12974-016-0680-xCrossRefPubMedPubMedCentralGoogle Scholar
  55. 55.
    Hernandez-Guillamon M, Garcia-Bonilla L, Solé M, Sosti V, Parés M, Campos M, Ortega-Aznar A, Domínguez C, Rubiera M, Ribó M, Quintana M, Molina CA, Alvarez-Sabín J, Rosell A, Unzeta M, Montaner J (2010) Plasma VAP-1/SSAO activity predicts intracranial hemorrhages and adverse neurological outcome after tissue plasminogen activator treatment in stroke. Stroke 41:1528–1535.  https://doi.org/10.1161/STROKEAHA.110.584623CrossRefPubMedGoogle Scholar
  56. 56.
    Rodríguez-González R, Blanco M, Rodríguez-Yáñez M, Moldes O, Castillo J, Sobrino T (2013) Platelet derived growth factor-CC isoform is associated with hemorrhagic transformation in ischemic stroke patients treated with tissue plasminogen activator. Atherosclerosis 226:165–171.  https://doi.org/10.1016/j.atherosclerosis.2012.10.072CrossRefPubMedGoogle Scholar
  57. 57.
    Chen X, Wang Y, Fu M, Lei H, Cheng Q, Zhang X (2017) Plasma immunoproteasome predicts early hemorrhagic transformation in acute ischemic stroke patients. J Stroke Cerebrovasc Dis 26:49–56.  https://doi.org/10.1016/j.jstrokecerebrovasdis.2016.08.027CrossRefPubMedGoogle Scholar
  58. 58.
    Ribo M, Montaner J, Molina CA, Arenillas JF, Santamarina E, Quintana M, Alvarez-Sabín J (2004) Admission fibrinolytic profile is associated with symptomatic hemorrhagic transformation in stroke patients treated with tissue plasminogen activator. Stroke 35:2123–2127.  https://doi.org/10.1161/01.STR.0000137608.73660.4cCrossRefPubMedGoogle Scholar
  59. 59.
    Fonseca AC, Canhão P (2011) Diagnostic difficulties in the classification of transient neurological attacks. Eur J Neurol 18:644–648.  https://doi.org/10.1111/j.1468-1331.2010.03241.xCrossRefPubMedGoogle Scholar
  60. 60.
    Penn AM, Bibok MB, Saly VK, Coutts SB, Lesperance ML, Balshaw RF, Votova K, Croteau NS, Trivedi A, Jackson AM, Hegedus J, Klourfeld E, Yu AYX, Zerna C, Borchers CH, SpecTRA Study Group (2018) Verification of a proteomic biomarker panel to diagnose minor stroke and transient ischaemic attack: phase 1 of SpecTRA, a large scale translational study. Biomarkers 23:392–405.  https://doi.org/10.1080/1354750X.2018.1434681CrossRefGoogle Scholar
  61. 61.
    von Recum J, Searle J, Slagman A, Vollert JO, Endres M, Möckel M, Ebinger M (2015) Copeptin: limited usefulness in early stroke differentiation? Stroke Res Treat 2015:768401.  https://doi.org/10.1155/2015/768401CrossRefGoogle Scholar
  62. 62.
    George PM, Mlynash M, Adams CM, Kuo CJ, Albers GW, Olivot J-M (2015) Novel TIA biomarkers identified by mass spectrometry-based proteomics. Int J Stroke 10:1204–1211.  https://doi.org/10.1111/ijs.12603CrossRefPubMedGoogle Scholar
  63. 63.
    Zhang J, Zhang C-H, Lin X-L, Zhang Q, Wang J, Shi S-L (2013) Serum glial fibrillary acidic protein as a biomarker for differentiating intracerebral hemorrhage and ischemic stroke in patients with symptoms of acute stroke: a systematic review and meta-analysis. Neurol Sci 34:1887–1892.  https://doi.org/10.1007/s10072-013-1541-3CrossRefPubMedGoogle Scholar
  64. 64.
    Misra S, Kumar A, Kumar P, Yadav AK, Mohania D, Pandit AK, Prasad K, Vibha D (2017) Blood-based protein biomarkers for stroke differentiation: a systematic review. Proteomics Clin Appl 11.  https://doi.org/10.1002/prca.201700007
  65. 65.
    Scott PA, Silbergleit R (2003) Misdiagnosis of stroke in tissue plasminogen activator-treated patients: characteristics and outcomes. Ann Emerg Med 42:611–618.  https://doi.org/10.1016/S0196064403004438CrossRefPubMedGoogle Scholar
  66. 66.
    Hamann GF, del Zoppo GJ, von Kummer R (1999) Hemorrhagic transformation of cerebral infarction—possible mechanisms. Thromb Haemost 82(Suppl 1):92–94PubMedGoogle Scholar
  67. 67.
    Anthony DC, Ferguson B, Matyzak MK, Miller KM, Esiri MM, Perry VH (1997) Differential matrix metalloproteinase expression in cases of multiple sclerosis and stroke. Neuropathol Appl Neurobiol 23:406–415CrossRefGoogle Scholar
  68. 68.
    Clark AW, Krekoski CA, Bou SS, Chapman KR, Edwards DR (1997) Increased gelatinase A (MMP-2) and gelatinase B (MMP-9) activities in human brain after focal ischemia. Neurosci Lett 238:53–56CrossRefGoogle Scholar
  69. 69.
    Montaner J, Alvarez-Sabín J, Molina C, Anglés A, Abilleira S, Arenillas J, González MA, Monasterio J (2001) Matrix metalloproteinase expression after human cardioembolic stroke: temporal profile and relation to neurological impairment. Stroke 32:1759–1766CrossRefGoogle Scholar
  70. 70.
    Rosenberg GA, Navratil M, Barone F, Feuerstein G (1996) Proteolytic cascade enzymes increase in focal cerebral ischemia in rat. J Cereb Blood Flow Metab 16:360–366.  https://doi.org/10.1097/00004647-199605000-00002CrossRefPubMedGoogle Scholar
  71. 71.
    Romanic AM, White RF, Arleth AJ, Ohlstein EH, Barone FC (1998) Matrix metalloproteinase expression increases after cerebral focal ischemia in rats: inhibition of matrix metalloproteinase-9 reduces infarct size. Stroke 29:1020–1030CrossRefGoogle Scholar
  72. 72.
    Heo JH, Lucero J, Abumiya T, Koziol JA, Copeland BR, del Zoppo GJ (1999) Matrix metalloproteinases increase very early during experimental focal cerebral ischemia. J Cereb Blood Flow Metab 19:624–633.  https://doi.org/10.1097/00004647-199906000-00005CrossRefPubMedGoogle Scholar
  73. 73.
    Lapchak PA, Chapman DF, Zivin JA (2000) Metalloproteinase inhibition reduces thrombolytic (tissue plasminogen activator)-induced hemorrhage after thromboembolic stroke. Stroke 31:3034–3040CrossRefGoogle Scholar
  74. 74.
    Sumii T, Lo EH (2002) Involvement of matrix metalloproteinase in thrombolysis-associated hemorrhagic transformation after embolic focal ischemia in rats. Stroke 33:831–836CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2020

Authors and Affiliations

  • Deepti Vibha
    • 1
  • Shubham Misra
    • 2
  1. 1.Department of NeurologyAll India Institute of Medical SciencesNew DelhiIndia
  2. 2.Department of NeurologyAll India Institute of Medical SciencesNew DelhiIndia

Personalised recommendations