Stroke Recovery Genetics
2016; Lippincott Williams & Wilkins; Volume: 47; Issue: 9 Linguagem: Inglês
10.1161/strokeaha.116.010648
ISSN1524-4628
Autores Tópico(s)Traumatic Brain Injury and Neurovascular Disturbances
ResumoHomeStrokeVol. 47, No. 9Stroke Recovery Genetics Free AccessResearch ArticlePDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessResearch ArticlePDF/EPUBStroke Recovery Genetics Arne Lindgren, MD, PhD and Jane Maguire, RN, PhD Arne LindgrenArne Lindgren From the Department of Clinical Sciences Lund, Neurology, Lund University, Sweden (A.L.); Department of Neurology and Rehabilitation Medicine, Skåne University Hospital, Lund, Sweden (A.L.); and School of Nursing and Midwifery, Faculty of Health and Medicine, University of Newcastle, NSW, Australia (J.M.). and Jane MaguireJane Maguire From the Department of Clinical Sciences Lund, Neurology, Lund University, Sweden (A.L.); Department of Neurology and Rehabilitation Medicine, Skåne University Hospital, Lund, Sweden (A.L.); and School of Nursing and Midwifery, Faculty of Health and Medicine, University of Newcastle, NSW, Australia (J.M.). Originally published11 Aug 2016https://doi.org/10.1161/STROKEAHA.116.010648Stroke. 2016;47:2427–2434Other version(s) of this articleYou are viewing the most recent version of this article. Previous versions: January 1, 2016: Previous Version 1 Clinical outcomes after stroke are highly variable, and reasons for these variations are often unexplained. Recovery after ischemic or hemorrhagic stroke begins immediately after acute onset, and many different levels of biological responses are involved.1 These responses differ in time and between different areas of the affected brain.2 Recovery after a cerebrovascular event may, therefore, vary from being rapid, without detectable remaining neurological deficits, to prolonged improvement, if any, over months or years. Outcome prediction is consequently difficult and unreliable and often depends on factors with unclear and limited impact.Factors specific to pathophysiological subtypes of stroke add to the complexity of prediction. Stroke genetics research has shown that genome-wide association (GWA) results for stroke risk differ by subtype (for review on stroke genetics, see Lindgren3). The same might be true for stroke recovery because lesion locations vary between stroke subtypes, and different recovery mechanisms may depend on whether cortical/subcortical structures and gray or white cerebral matter are affected. Further indication for differences in outcome between stroke subtypes is that ischemic stroke patients classified as having a cardioembolic mechanism4 have greater incidence of mortality and disability,5,6 whereas for large vessel disease strokes, the risk of new events within 30 days is high, >18%.5 However, it is also likely that some recovery pathways, for example, involved in cerebral ischemia are shared between stroke subtypes.In addition, biological factors, prevention of recurrent stroke, treatment of concomitant conditions, as well as social supports and amount of poststroke rehabilitation therapies are all relevant during recovery.7,8 But predictive models based on clinical factors remain limited by imprecision and difficulty with translation to the individual case.9 This may improve when mechanisms such as brain plasticity10 and brain stunning11 and factors that influence these concepts become better defined.Genetic factors also influence many different aspects of brain function and repair,12–14 as well as recurrent stroke risk and response to pharmacological interventions, and can, thereby, account for hitherto unexplained variation in stroke recovery.The majority of studies reviewed here used a candidate gene association design and investigated numerous gene variants' associations with outcomes of mortality, further vascular event, poststroke depression, functional ability, or rehabilitation treatment (Table 1). We categorized 3 different clinical types of stroke outcomes in line with the International Classification of Function and Disability (ICF39; Table 1) and also considered outcomes investigated by animal models and different surrogate/intermediate markers, such as biochemical and neuroimaging. The 3 ICF categories in this context are (1) neurological/physical deficit; (2) functional ability; and (3) social participation and illustrate different clinical aspects of stroke recovery. Notably, careful attention to timing is also essential in assessment of recovery because biological mechanisms are activated or deactivated at different time points (Table 2).Table 1. Candidate Genetic Associations for Ischemic and ICH Stroke Recovery OutcomesGeneVariant/SNP rs NumberChromosomePhenotype Outcome MeasuredHR/OR/RR; 95% CIP ValueResultReferenceNeurological/physical deficit COX-1rs1330344, rs10306114, rs3842788, rs57889Vascular outcomes, mortalityrs1330344, HR=1.958; 1.15–3.330.013Increased risk of further eventCao et al15 NINJ2rs1242579112Recurrence in LAAHR=2.52; 1.04–6.120.017Recurrence of LAA subtypeZhang et al16rs1183357912Recurrence in LAAHR=2.13; 1.03–4.400.027Recurrence of LAA subtypeZhang et al16 TLR4rs4986791, rs49867909Neurological outcomeHaplotype adjusted OR=12.61; 1.42–111.90.023WorsenedWeinstein et al17 COL3A1rs21385332Recurrence, prognosis, mortalityHR=2.98; 1.27–6.980.012Increased death from cardiovascular disease or stroke in lacunar subtypeLv et al18rs118870922Recurrence, prognosis, mortalityHR=1.59; 1.04–2.440.035Increased recurrence in atherothrombotic subtypeLv et al18rs18002552Recurrence, prognosis, mortalityHR=0.58; 0.36–0.960.024Decreased recurrence in lacunar subtypeLv et al18 GPIIIa, PAI-1, Factor VII, MTHFR, eNOSGPIIIa PlA1/PlA2, PAI-1 4G/5G, FVII G10976A, MTHFR C677T, eNOSSeveralStroke, myocardial infarction, death from all causeN/SN/SN/SYeh et al19 Factor VIIMsp1, insertion13Poststroke mortalityN/SN/SN/SHeywood et al20 APOErs7412, rs42935819Early death from strokeMultiple analysesSignificantPositiveGromadzka et al21 APOErs7412, rs429358191-y neurological impairment, severe functional disability, dependenceN/SN/SN/SGromadzka et al22APOErs7412, rs429358191-y outcomeN/SN/SSarzynska-Dlugosz et al23 GPIIbHPA-3 rs5911 ITGA2B17Poststroke mortalityAa RR=2.42; 0.24–4.71Ab RR=2.13; 1.09–4.17 A)11BDNF polymorphism effect of rTMS on motor recovery post strokeUpper extremity motor function changes over time:(a) Post-rTMS score minus pre-rTMS score,(b) Follow-up score minus pre-rTMS score A)11BDNF polymorphism influence on human motor cortex plasticity in acute strokeLaterality index t=2.2700.036Excitability significantly higher with no variantDi Lazzaro et al30 BDNFrs6265 (−196 G>A)11Clinical parameters and functional outcome in patients with IS and ICHUnfavorable outcome of stroke rehabilitation (Rankin Score >2):BDNF−196 GG polymorphismOR=2.18; 1.09–4.35Not reportedAssociation with independent factorsMirowska-Guzel et al31 BDNFrs6265 (−196 G>A), −270 C>T11Allelic and genotypic distribution BDNF −196 G>A and −270 C>T polymorphisms; impact of rTMS on serum BDNF concentrations measured before rehabilitationN/S differences in serum BDNF concentration were observed in patients with different BDNF −196 G>A or −270 C>T genotypesN/SNo changes detectedMirowska-Guzel et al32 BDNFrs6265 (−196 G>A)11Recovery 1 mo post ISChange scores0.036Poor recoveryCramer et al33Recovery 3 mo post ISChange scoresN/SPoor recoveryCramer et al33 BDNFrs6265 (−196 G>A)112 wk post strokeOR=1.87; 0.92–3.780.027RecoveryKim et al341 y post strokeOR=1.53; 0.64–3.370.048RecoveryKim et al34 CYPC19Loss-of-function alleles *2, *310CYP2C19 polymorphisms on clinical outcomes in IS patients treated with clopidogrel:Functional ability (mRS)CYP2C19 independent predictor of poor prognosis:OR=3.01; 1.23–7.380.016Carriers significant influence on clopidogrel response and prognosisQiu et al35 APOErs7412, rs42935819Recovery 1 mo post ISChange scores0.023Significantly poorer recovery in presence of APOE ϵ4Cramer et al33mRS 3 mo post ISChange scores0.029Significantly poorer mRS in presence of APOE ϵ4Cramer et al33 CRPrs11308641Functional abilityAdditive adjusted OR=1.51; 1.09–2.09Recessive adjusted OR=1.27; 1.08–1.500.0130.008T allele of rs1130864TT+CT genotypes of rs1130864 strongly predicted functional disabilityGuo et al36 COMTrs468022q11BI, RMA, on admission, after 4 wk, after 6 moMultiple ANOVA0.002Carriers of COMT Val/Val alleles better results in BI and RMA than COMT Met/Met carriers at all 3 time pointsLiepert et al37Social participation SERTrs2553117PSDN/SN/SN/SKohen et al385-HTTLPR17PSD5-HTTLPR s/s genotypehigher odds of PSD compared with l/l or l/xl genotype carriers OR=3.1; 1.2–8.30.0453-fold higher risk if carrierKohen et al38STin2 VNTR17PSDSTin2 9/12 or 12/12 genotype higher odds of PSD compared with STin210/10 genotype carriers OR=4.1; 1.2–13.60.014-fold higher risk if carrierKohen et al38BDNF indicates brain-derived neurotrophic factor; BI, Barthel index; GOS, Glasgow outcome scale; HR, hazard ratio; ICH, intracerebral hemorrhage; IS, ischemic stroke; LAA, large-artery atherosclerosis; mRS, modified Rankin Scale; N/S, not significant; OR, odds ratio; PSD, poststroke depression; RMA, Rivermead motor assessment; RR, relative risk; rTMS, repetitive transcranial magnetic stimulation; and SNP, single nucleotide polymorphisms.Table 2. Key Points for Studies on Stroke Recovery GeneticsCategorization of variables Primary outcome variable may differ between studies Neurological/physical impairment Functional outcome Social participation Animal models Surrogate/intermediate markers Concomitant/confounding factors including the following Premorbid conditions Stroke phenotype definition: infarct/hemorrhage; TOAST classification Highly predictive clinical variables, for example, age, sex, stroke risk factors, measure of stroke severity, and lesion size Treatment post stroke Time points for evaluation: days, weeks, months, yearsGeneral key points Stroke outcomes are highly heterogeneous and unpredictable Reported findings from genetic studies for stroke outcome often used candidate approaches, and many results have not been replicated Other approaches such as genome-wide association studies are currently in progressTOAST indicates Trial of Org 10172 in Acute Stroke Treatment.Neurological/Physical DeficitNeurological deficit can be measured according to the National Institutes of Health stroke scale or other neurological assessment scales.4 These measurements are often used for evaluation of recovery in the acute phase after stroke onset when more complex measurements, such as activity and social participation, are not feasible because of, for example, hospitalization. Several factors may influence the degree of initial neurological deficit (Table 3). These factors may be included in multivariate analyses assessing genetic impact. Until now, few studies have focused on the genetics of initial neurological deficit, although studies at 2 and 4 weeks post stroke have reported an association between brain-derived neurotrophic factor (BDNF) and outcome.33,34 Large efforts on studying genetic impact on early treatment effects of thrombolysis are underway.40Table 3. Factors That May Influence Different Types of Clinical Outcomes After StrokeGroup of FactorsSpecific FactorExample of Measurement Types/Specific FactorsPossible Influence on Outcome Type:DemographicAgeYearsIND, FO, SPSexFemale/maleIND, FO, SPPremorbidPremorbid disabilityModified Rankin ScaleIND, FO, SPConcomitant diseasesVascular risk factors (eg, hypertension, heart disease, diabetes mellitus, smoking)IND, FO, SPEducationEducational levelSPAcute stroke situationInitial stroke severityNIH stroke severity scaleIND, FO, SPStroke subtypeIschemic/hemorrhagic strokeIND, FO, SPIschemic stroke according to TOAST/CCS criteriaIND, FO, SPLesion characteristicsLesion volume (mL)IND, FP, SPLesion location (cortical/subcortical/ brain stem/cerebellum)IND, FP, SPPoststroke situationRehabilitationYes/noFO, SPDepressionMADRSFO, SPSocial supportAccess to servicesFO, SPLiving situationAlone/with someoneFO, SPHousing situationHome/institutionFO, SPComplications after strokeInfectionFO, SPDeep vein thrombosisFO, SPFallsFO, SPNutritional problemsFO, SPRecurrent strokeYes/noFO, SPConcomitant medicationsAntidepressants (SSRI, tricyclics, etc)FO, SPStimulating drugs (eg, amphetamines)FO, SPGeneticsGenetic variantsDescription of genetic variationIND, FO, SPCCS indicates the Causative Classification of Stroke System; FO, functional outcome; IND, initial neurological deficit; MADRS, Montgomery-Asberg Depression Rating Scale; NIH, National Institutes of Health; SP, social participation; SSRI, selective serotonin reuptake inhibitor; and TOAST, Trial of Org 10172 in Acute Stroke Treatment.Longer term prognosis on neurological/physical deficit can be grouped into neurological outcomes, stroke recurrence, and mortality. Alterations in the BDNF gene are often studied in stroke recovery. BDNF has a role in brain repair and plasticity and may have an effect on brain recovery.10 The BDNF single nucleotide variation (rs6265, Val66Met; Table 1) influences excitability and outcome.30,31,33 High-frequency repetitive transcranial magnetic stimulation over the primary motor cortex of the affected hemisphere induces positive effects on motor function, and subjects with the Val/Val genotype have better improvement.29Long-term mortality after stroke and stroke recurrence genetics has been studied in several studies (Table 1). In a Chinese population of large-artery atherosclerosis stroke cases, a signal on Chr12p13 predicted stroke recurrence,16 and this variant has also been associated with stroke risk in some but not all populations of European descent.41,42Functional OutcomeSeveral genetic studies focus mainly on functional ability after stroke at a range of time points (Table 1). Many have concentrated on Apolipoprotein E (APOE) and BDNF gene variants. Functional ability can be measured with several assessments, including the modified Rankin Scale, Barthel index, Glasgow outcome scale, and other measures of activities of daily living.43APOE gene variants have been related to stroke risk44 and may also play a role in stroke recovery, although results have been equivocal (Table 1).33,45,46 See also below in Surrogate/Intermediate Markers and Intracerebral Hemorrhage (ICH) sections.The BNDF (rs6265, Val66Met) variation has been reported to be associated with improved recovery, although subsequent findings showed somewhat contradictory results.47,48 Another study reported less favorable effect of rehabilitation on outcome after stroke in patients with the BDNF −196 GG (Val) polymorphism31 (see also the BDNF section in the Neurological/Physical Outcome section earlier and the Surrogate Marker section later).Other examples of genes reported to be related to functional outcome, for example, Aberg et al,25 Hoy et al,26 Maguire et al,28 and Liepert et al,37 are mentioned in Table 1, although these studies need replication.Social ParticipationThis category of stroke recovery can be assessed with metrics, such as quality of life scores. It is also possible to include depression into this category because social engagement is diminished in people experiencing depression.49,50 Several covariates known to influence psychosocial aspects are included in multivariate models examining genetic influence on social participation after stroke (Table 3).Genetic signals associated with poststroke depression and emotional incontinence have mostly been limited to serotonin pathways or regions of serotonergic genes.51 The serotonin transporter (SERT) gene has been widely investigated for association with depression, but the exploration of association with poststroke depression has been limited. One study reported an association between poststroke depression and the SERT gene polymorphisms STin2 VNTR and 5-HTTLPR after adjustment for age, sex, and National Institutes of Health stroke scale scores38 (Table 1), and another small case–control study found the SA and LG alleles of 5-HTTLPR/rs25531 to be more common in depressed stroke participants.52Animal Models and Surrogate Markers for Studying Stroke Recovery GeneticsBecause of space limitations, this review does not contain a detailed account on stroke recovery genetics in animal models. However, some examples can be mentioned: animal model results support the presence of genetic determinants of outcome53 and indicate genetic impact on cerebrovascular collateral density and infarct lesion size.54 Animal models can also examine if genetic variations detected in humans have an impact on poststroke outcome.47Surrogate/intermediate markers for studying stroke recovery genetics are increasingly being explored and include biochemical and neuroimaging analyses.Biomarkers associated with cellular repair, reorganization, and remodeling after an acute event may have effect on outcome after stroke. In apoptosis and cell activation after ischemic injury, many complex signaling pathways are at work, and to identify those relevant to stroke recovery requires integrated understanding of involved multifaceted molecular processes.1Even though one approach is to study how genetic factors influence stroke outcome in patients with similar or identical cerebral lesions, another method is to search for genetic factors related to lesion volume because the infarct size predicts stroke outcome.55 The use of magnetic resonance imaging for stroke outcome prediction shows that several magnetic resonance imaging parameters correlate highly with favorable stroke outcome,56 and this may increase the potential to detect genetic information related to recovery. Diffusion and perfusion-weighted magnetic resonance imaging can be used to measure infarct volume in patients with and without a specific genetic trait, for example, APOE ε4 genotype57 (Table 1).Cortical plastic changes after acute stroke may also be influenced by genetic factors. One study showed that repetitive transcranial magnetic stimulation inducing long term potentiation-like activity differed less between the affected and unaffected hemisphere in patients with the BDNF rs6265, Val66Met polymorphism than those without, and the authors proposed that this may be beneficial in less severe strokes but unfavorable in severe strokes,30 suggesting that genetic variations may play alternative roles in different settings.ICH and RecoverySome genetic variations have similar effects in both ischemic and hemorrhagic stroke, whereas other variations have specific influence on outcome for certain stroke subtypes, for example, ICH or a particular subtype of ICH. There are several remarkable studies on genetic influence on ICH outcome: APOE studies have yielded results where poor outcome and increased mortality after lobar ICH have been associated with the APOE ε2 variant.58 In addition to candidate gene studies, a genome-wide complex trait analysis using data from GWA analyses calculated that apart from the APOE loci, there was a 41% heritability for 90-day ICH mortality.59 A recent study found an association between a haptoglobin allele variant and lower odds of favorable modified Rankin Scale (described as modified Rankin Scale score 0–2) outcome.60 Also genetic factors influencing intermediate ICH risk factors may influence outcome because a report showed that a genetic risk score based on 42 single nucleotide polymorphisms related to blood pressure was related to poor clinical outcome at 90 days specifically for individuals with deep ICH.61Epigenetics and Gene–Gene InteractionEpigenetic mechanisms regulating the DNA transcription have a potential role in stroke recovery and can modulate several downstream pathways—for review see Elder et al.62 Micro-RNA in an ischemic brain area can be up- and downregulated during different time points of the spontaneous recovery phase of ischemic stroke,53 indicating how different biochemical pathways are controlled. Genetic influence on epigenetic mechanisms and epigenetic influence on genetic expression are potentially important targets for understanding and enhancing stroke recovery.Even though most studies have examined only 1 or 2 candidate genes with regard to stroke recovery, it is possible that gene–gene interaction also plays a role in the stroke recovery genetics. One example is a study showing that epistatic interactions between the BDNF, fibroblast growth factor 2, and vascular endothelial growth factor genes may influence stroke recovery.63Pharmacogenetics and Stroke RecoveryEvidence is emerging on the modulation and influence of certain pharmacological agents on brain plasticity and subsequent improved stroke functional outcome. It other complex diseases, pharmacological responses vary depending on genetic variations, and effect sizes are compelling. One example is how genetic polymorphisms affect the response to L-dopa treatment.64,65One class of medications showing promise in stroke is the selective serotonin reuptake inhibitor class. For patients with moderate to severe strokes, fluoxetine plus physiotherapy resulted in enhanced motor recovery at 3 months that seemed to persist ≤12 months.66,67 Whether the stroke recovery response to selective serotonin reuptake inhibitor treatment is influenced by genotype, for example, the SERT 5-HTTLPR genotype, discussed earlier, remains to be investigated.Of great clinical interest is whether response to tissue-type plasminogen activator treatment is influenced by genetic factors. A study of 140 single nucleotide polymorphisms in ischemic stroke patients treated with tissue-type plasminogen activator reported that variants in the IL1B and vWF genes were associated with early recanalization and suggested a relation to activity of coagulation factors.40 In a microarray study, patients with hemorrhagic transformation after tissue-type plasminogen activator treatment had altered expression of genes related to apoptosis and neutrophil regulation pathways.68The genetic impact on metabolism and response to anticoagulation therapy would have important clinical consequences for stroke recovery. Genetic polymorphisms in the cytochrome P-450 enzyme CYP2C9 gene are related to metabolism of vitamin K antagonists. Variants in the VKORC1 gene coding for vitamin K epoxide reductase are associated with variability of the anticoagulation effect of warfarin.69 The risk of warfarin-related lobar ICH may be increased in APOE ε2 and APOE ε4 carriers,61 although it is unclear whether these observations can be used in clinical practice. One study reported that presence of the CES1 rs2244613 minor allele resulted in lower active dabigatran metabolite levels and lower risk of hemorrhagic complications, although no increased risk of ischemic events was detected.70 Future studies may show other genetic variants related to the effect of non–vitamin K antagonist oral anticoagulants.The clinical effect of genetic variations affecting clopidogrel metabolism is not clearly established. However, a study of ischemic stroke patients treated with clopidogrel showed worse prognosis at 6 months in carriers of the CYP2C19 loss of function allele.35Future DirectionsThere are several long-term goals of genetic studies on stroke recovery. These include the understanding of genetic influence on brain plasticity and repair with subsequent intervention possibilities; detection of metabolic pathways that can be targeted with different types of treatments; pharmacogenetics for individualized treatment; improved prognostic accuracy; and improved rehabilitation methods. Alternative approaches to candidate gene studies are emerging. GWA studies examine many thousands of genetic variations simultaneously and have been highly successful in establishing new genetic factors influencing stroke risk.3 The ongoing multicenter GISCOME (Genetics of Ischemic Stroke Outcome) study uses GWA data to search for single nucleotide polymorphism variants associated with stroke recovery.71 Strengths of GWA studies are that they have no preconceived assumption that a specific gene causes the phenotypic observation and that large parts of the genome are examined. GWA study limitations include inadequate capacity to detect rare genetic variants, that advanced statistical analyses involved carries a risk of misinterpretation, and that imbalance between included subject groups may produce biased results. New, recently developed techniques for copy number variation studies, exome sequencing, whole genome sequencing, and epigenetic studies, plus the aid of sophisticated mathematical analyses will lead to better understanding of stroke recovery genetics.3 To quantify the genetic heritability component influencing stroke recovery, the recently developed genome-wide complex trait analysis method can be applied in a similar way as described for stroke risk and mortality,59,72 using data from GWA studies, for example, GISCOME. Replication attempts for already reported preliminary associations and gene–environment, gene–phenotype, and gene–gene interactions also need to be considered. Most importantly, future research in recovery requires clarity and consensus about time points for assessing different types of outcome, outcome phenotype definitions—preferably adhering to the ICF classification, and consideration of rehabilitation and other interventional treatments that may have influence in outcome studies.73 Pharmacogenetic implications and other treatment methods may be the most likely clinical goals to profit from stroke recovery genetics research in the nearest future. Pooling data from large cohorts in, for example, the International Stroke Genetics Consortium (ISGC) (http://www.strokegenetics.org/) will be pivotal to obtain the large sample sizes required for many of these complex genetic studies. The ISGC supports several groups working on short- and long-term outcome after stroke, publication efforts in the field, and project proposals for recovery studies. ISGC workshops, occurring twice a year, allocate time for sessions on stroke recovery, including planning of forward directions.ConclusionsUntil now, many studies on stroke recovery genetics have been candidate gene studies. Several results warrant further investigation. Other methods have also been used, and recent advances in biochemistry and bioinformatics hold promise for the future. However, careful description of clinical phenotypes, interventional treatment, and appropriate selection of clinical or surrogate/intermediate primary outcome variables describing the recovery is crucial. A better understanding of genetic influence on stroke recovery is expected to support the development of new beneficial treatments for stroke patients.Sources of FundingDr Lindgren is supported by Region Skåne, Lund University, the Swedish Heart and Lung Foundation, the Freemasons Lodge of Instruction EOS Lund, and the Swedish Stroke Association. Dr Maguire is supported by the University of Newcastle, School of Nursing, and Midwifery special studies leave program.DisclosuresDr Lindgren reports honoraria from Bristol-Myers Squibb for seminar presentations and from Boehringer Ingelheim, Bayer, and Astra Zeneca for medical advisory board participation. Dr Maguire reports no conflicts.FootnotesCorrespondence to Arne Lindgren, MD, PhD, Department of Clinical Sciences Lund, Neurology, Lund University, SE-22185, Lund, Sweden. E-mail [email protected]References1. Zaleska MM, Mercado ML, Chavez J, Feuerstein GZ, Pangalos MN, Wood A. The development of stroke therapeutics: promising mechanisms and translational challenges.Neuropharmacology. 2009; 56:329–341. doi: 10.1016/j.neuropharm.2008.10.006.CrossrefMedlineGoogle Scholar2. Pekna M, Pekny M, Nilsson M. Modulation of neural plasticity as a basis for stroke rehabilitation.Stroke. 2012; 43:2819–2828. doi: 10.1161/STROKEAHA.112.654228.LinkGoogle Scholar3. Lindgren A. 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