research article

Association Between Serum BDNF Level and Cognitive-Linguistic Outcomes in Aphasic Stroke

Authors: Association Between Serum BDNF Level and Cognitive-Linguistic Outcomes in Aphasic Stroke Lin Zhang1,2#, Yaping Huai1,3#, Mingzhu Xu4, Xin Wang5, Xun Luo6, Xi Zeng7, Qing Mei Wang1,8*

*Corresponding Author: Qing Mei Wang, MD, PhD, Stroke Biological Recovery Laboratory, Spaulding Rehabilitation Hospital, Harvard Medical School, 96 13th street, Charlestown, MA 02129, Massachusetts, USA.

Received Date: 03 January, 2022

Accepted Date: 08 January, 2022

Published Date: 12 January, 2022

Citation: Zhang L, Huai Y, Xu M, Wang X, Luo X, et al. (2022) Association Between Serum BDNF Level and Cognitive-Linguistic Outcomes in Aphasic Stroke. Int J Cerebrovasc Dis Stroke 5: 142. DOI: https://doi.org/10.29011/2688-8734.000042

Abstract

Objective: This study examines the association between serum Brain-Derived Neurotrophic Factor (BDNF) level and cognitivelinguistic outcomes in patients with post-stroke aphasia.

Design: A total of 119 patients with first left hemisphere stroke were divided into two groups: aphasia (n=66) and non-aphasia (n=53). Serum BDNF level, speech language pathology diagnosis, and functional independence measure (FIM) were assessed in all patients. Aphasia severity level, Functional Communication Measure (FCM) spoken language comprehension, and FCM language expression were also tested in aphasic patients. The relationship between serum BDNF level and cognitive-linguistic outcomes were analyzed by Spearman correlation.

Results: The serum BDNF level of aphasic patients had a positive correlation with total FIM (r=0.284, p=0.021) at admission. At discharge, the serum BDNF was related to cognitive subtotal FIM (r=0.284, p=0.021), comprehension (r=0.265, p=0.032), expression FIM (r=0.308, p=0.012), memory FIM (r=0.266, p=0.031), motor subtotal FIM (r=0.290, p=0.018), and total FIM (r=0.315, p=0.010). Similarly, Spearman correlation analysis revealed a correlation between serum BDNF and FCM spoken language expression level changes (r=0.255, p=0.038) and severity of aphasia level changes (r=0.282, p=0.022). With regards to serum concentrations of BDNF and non-aphasic patients’ function, only expression at admission showed significant difference (r=0.339, p=0.013).

Conclusion: Our findings suggest that serum concentrations of BDNF may help to predict the cognitive-linguistic outcomes in aphasic stroke patients during acute rehabilitation. Keywords: BNDF; Aphasia; Stroke; Cognitive-linguistic outcome

What is known: due to language deficit, it has been challenging to measure cognitive function.

What is new: this is the first study to investigate relationship between serum BDNF cognitive-linguistic outcomes in aphasic stroke patients during acute rehabilitation, and this findings may provide insight into the biological mechanism of recovery in poststroke aphasia and may help to develop personalized treatment plans.

Introduction

Stroke patients with aphasia suffer from wide range of language impairment including the auditory comprehension, verbal expression, reading, writing, or functional communication. Aphasia is also associated with an individual’s cognition, emotion, self-image, well-being, relationships, employment, and quality of life [1,2].  Language processing has been shown to be controlled by cognitive-linguistic function, such as attention, executive function, and memory [3]. Fillingham, et al. [4], demonstrated that aphasic patients with impairment in recognition memory and attention had poor response to anomia treatment. Similarly, Nicholas, et al. [5], reported that aphasia with poor executive function had a worse response to a treatment program. Therefore, it is important to identify and treat cognitive deficit in aphasia. However, due to language deficit, it has been challenging to measure cognitive function. Serum biomarkers have the potential to provide important supplementary measure to detect cognitive impairment and insight for personalized target for treatment [6].

Brain-derived neurotrophic factor (BDNF) is a member of the neurotrophin family of growth factors, which implicate neuronal differentiation, maturation, survival, synapse information [7]. It also has been found to play a central role in neuroprotection and neuronal repair, by promoting neurogenesis and angiogenesis [8]. In the central nervous system (CNS), BDNF is widely expressed in the hippocampus, cortex, and basal forebrain, linking to cognition, learning, and memory [9]. Galit, et al. [10], demonstrated there was a relationship between higher serum BDNF concentrations and decreased risk for dementia in healthy adults, especially in older women, in a community-based cohort study of 2131 participants (mean aged 72 years). Similar results were found in a 10-year longitudinal study where low serum BDNF levels were associated with a higher risk of stroke and reduced cognitive function in a stroke-free sample of 3440 men and women (mean aged 65 years) [8]. Acute serum BDNF levels showed a positive correlation with cognitive function, as well as with memory, at 6 months in Traumatic Brain Injured (TBI) patients [11]. However, very few studies revealed the relationship between serum BDNF concentrations and cognitive-linguistic function outcomes in aphasic patients.

This research was designed to explore the relationship between serum BDNF levels and cognitive-linguistic outcome in aphasic patients during acute inpatient rehabilitation. It may provide insight to design personalized rehabilitation plans for aphasic stroke patients.

Materials and Methods

Participants

This retrospective study screened 359 consecutive stroke patients admitted to hospital from March 20, 2014 to August 11, 2015 and was approved by the Institutional Review Board. Patients from our rehabilitation unit with a primary diagnosis of acute cerebrovascular accident of the left hemisphere were included, and patients were excluded if they had prior stroke history, length of hospitalization less than one week, or a diagnosis of profound dysfunction in severity of aphasia. A total of 119 patients were included in this research. They were divided into two groups (aphasia group or non-aphasia group) according to a diagnosis by speech language pathology (as shown in Figure 1). All patients underwent rehabilitation in our rehabilitation unit throughout their inpatient stay. Our unit team is comprised of physicians, speech and language therapists, occupational therapists, physiotherapists, dieticians, and nurses. The team provided personalized comprehensive care and rehabilitation to every patient. The demographic and clinical data of enrolled subjects, including age, gender, Body Mass Index (BMI), preferred language, ethnicity, marital status, risk factors, stroke site, time from stroke onset to hospital admission, length of hospital stay, and discharge destination, were collected from medical records. The ethics committee of hospital has already approved this human study.

Functional outcome measurement

All subjects were assessed using speech language pathology diagnosis, American Speech-language-hearing Association’s Functional Communication Measures (FCMs), and Functional Independence Measure (FIM) test by experienced therapists.

Speech language pathology diagnosis is a comprehensive diagnosis, including language (auditory comprehension, verbal expression, reading comprehension, written expression, motor speech, and voice) and cognitive-linguistic (attention, orientation, memory, problem solving, judgment, and executive function). There are ten levels, ranging from profound injury (level 1) to without function limit (level 10), in each item. The final level and category of aphasia is based on: 1. language and cognitivelinguistic results mentioned previously; 2. results of standardized tests, such as Western Aphasia Battery or Boston Diagnostic Aphasia Examination; 3. clinical judgment of a speech-language pathologist; and 4. medical diagnosis and imaging. The level of aphasia ranges from one (profound dysfunction) to ten (normal).

American Speech-Language Hearing Association’s (ASHA) functional communication measures use seven-rating scales, ranging from least functional (level 1) to most functional (level 7). They describe different aspects of a patient’s functional communication and swallowing abilities: spoken language comprehension, spoken language expression, reading, writing, motor speech, voice, swallowing, attention, memory, problem solving, augmentative/alternative communication, and pragmatics.

Functional Independence Measure (FIM) addresses the level of assistance needed by an individual required to carry out Activities of Daily Living (ADLs). The scale of FIM comprises two parts: motor skills (eating, grooming, bathing, dressing-upper body, dressing-lower body, toileting, bladder management, bowel management, bed/chair/wheelchair transfer, toilet transfer, tub/ shower transfer, walk/wheelchair locomotion, stairs locomotion) and cognitive skills (comprehension, expression, social interaction, problem solving, memory). Each item has a grade from 0 (total assistance) to 7 (complete independence). Scores range from 18 (lowest) to 126 (highest), indicating level of function.

Since this was a retrospective study, there were some missing data. We chose only the integrated items as the results to get a more accurate analysis. In the speech language pathology diagnosis, we used scores of auditory comprehension, verbal expression, motor speech, attention, and severity level of aphasia; In FCMs, we got spoken language comprehension score and spoken language expression score as results.

Serum BDNF measurement

The serum from aphasia patients was collected on admission and then stored in polypropylene test tubes at -80 °C until used. Serum BDNF levels were analyzed using enzyme-linked immunosorbent assay (ELISA kit, R&D Quatikine, Minneapolis, USA). Data were analyzed using SPSS statistical software, version 21.0 (SSPS Inc, Chicago, IL). The data were expressed using mean, median, standard deviation, and percentile analysis. Significance was accepted at a 2-sided p value of less than 0.05.

The demographics and clinical characteristics were compared at baseline by independent t test for continuous variables (age, BMI, time from stroke onset to admission, days, and length of stay) and by Chi-square test or Fisher’s exact test for categorical variables (preferred language, ethnicity, marital status, risk factors, stroke site, and discharge destination). The function between the two groups was tested by the Mann-Whitney U test. The relationships between serum BDNF and functional parameters were assessed using Spearman coefficients.

Demographics and clinical characteristics

Descriptive statistics for demographics and clinical parameters of the two groups are summarized in Table 1. Of the 119 patients in this study, 66 (55.5%) had aphasia. A comparative analysis between the two groups showed similar baseline characteristics except stroke site and the time between onset to admission to rehabilitation hospital. The types of aphasia are shown in Table 2: mixed transcortical 19 (28.8%), global 12 (18.2%), anomic 10 (15.2%), Broca’s 8 (12.1%), transcortical motor 3 (4.5%), Wernicke’s 2 (3.0%), and undefined 12 (18.2%).

Functional outcomes

Compared to those without aphasia, aphasic patients had lower scores in auditory comprehension (P=0.000), verbal expression (P=0.000), motor speech (P=0.000), cognitive FIM (P=0.000), and total FIM (P=0.000) both at admission and discharge, whereas attention and motor FIM were not statistically different (Table 3). The increase of verbal expression was significant between the two groups.

Serum BDNF and functional outcomes

Serum concentrations of BDNF in aphasic patients and non-aphasic patients were 21.19±6.912 ng/ml and 22.70±7.293 ng/ ml, respectively. Spearman correlation showed associations between serum BDNF and aphasic patients’ functional outcomes (Table 4). There was significant correlation between serum BDNF level and total FIM at admission (r=0.284, p=0.021). There was positive correlation among serum BDNF level and cognitive subtotal FIM scores (r=0.284, p=0.021), comprehension FIM scores (r=0.265, p=0.032), expression FIM scores (r=0.308, p=0.012), memory FIM sores (r=0.266, p=0.031), motor subtotal FIM scores (r=0.290, p=0.018), and total FIM scores (r=0.315, p=0.010) at discharge. Moreover, correlation coefficients between serum BDNF level and score of FCM spoken language expression changes and severity of aphasia were 0.255 (p=0.038), 0.282 (p=0.022), respectively. In nonaphasic patients, serum concentration of BDNF was correlated only with expression at admission.

Discussion

The current study aimed to evaluate the relationship between serum BDNF level and cognitive-linguistic outcome in aphasic stroke patients during acute inpatient rehabilitation.

Cognitive-linguistic impairment in left hemisphere stroke

Aphasia is a common after stroke affecting as many as 38% of stroke survivors [12]. Aphasia is an acquired impairment that affects spoken language expression, spoken language comprehension, written expression, or reading comprehension [13]. In the majority of people, the language network is located in the frontal, temporal, and parietal Perisylvian areas of the left hemisphere [14]. The present study compared the functional outcome in left hemisphere, first-ever stroke patients with and without aphasia. The results from this study have confirmed that aphasia patients have poor auditory comprehension, verbal expression, and motor speech.

Cognitive dysfunction frequently occurs in post-stroke patients. The prevalence of post-stroke cognitive impairment ranges from 20% to 80% [15]. Ischemic stroke patients suffer communicative disorders, increasing the risk of non-verbal cognitive deficits. Comprehensive assessment and rehabilitation are needed for these patients. Early prediction of patients’ functional outcome is essential to set proper rehabilitation goals and to determine further rehabilitation plans. Literature also reports that cognitive function of post-stroke aphasia patients was inferior to that of patients without aphasia [16]. Our findings were consistent with previous studies, that cognitive FIM scores in aphasia patients showed significant differences compared to those of non-aphasia patients. Attention as a domain of cognition plays a pivotal role in language processing. One previous investigation reported that in 22 (19 patients had aphasia) participants with lefthemisphere stroke, all of them displayed at least one dysfunction in sustained, selective, or divided attention; however, they didn’t show whether there were differences between patients with and without aphasia [17]. In our trial, the data show no significant differences between first-time left-hemisphere stroke participants with and without aphasia in attention function.

Associations of Cognitive-linguistic impairment and BDNF in acute rehabilitation

There are many screening instruments used to evaluate aphasic patients’ function: Boston Diagnostic Aphasia Examination, Western Aphasia Battery, Cognitive Linguistic Quick Test, etc. They evaluate various perceptual modalities, processing functions, and response modalities. However, these tests do not directly reflect the biological mechanisms of brain recovery. BDNF as a nerve-growth protein plays important roles in synaptic plasticity, synaptic efficacy, neuronal connectivity, cell migration, glutamate release, and neuropeptide expression [18]. It acts via at least two receptors: one is a low-affinity nerve growth factor receptor (LNGFR, 75kDa); the other is a tropomyosin receptor kinase-B (TrkB) receptor (145kDa) [18]. Specifically for BDNF, LNGFR can promote Schwann cell migration near injury and active apoptotic signaling [19]. TrkB receptor is a high-affinity receptor of BDNF attributed to the majority of trophic effects [18]. Cells that express TrkB are thymocytes, pyramidal cells in the hippocampus, motoneurons in the spinal cord, and almost all neurons in the developing brain, etc [20,21]. Via the high-capacity saturable transporter system, BDNF (27kDa) can cross the bloodbrain barrier in both directions [7]; suggesting that serum BDNF reflects brain BDNF levels.

Bejot, et al. [22], have shown that neuronal expression of BDNF increases acutely after stroke as a pro-survival response and that BDNF levels correlate with the degree of functional survival. However, the association of serum BDNF with functional outcome after stroke has been controversial. Stanne, et al. [23], reported that low circulating concentrations of BDNF during the acute phase after stroke are associated with poor long-term functional outcome, as defined by a modified Rankin Scale score of 3-6 at three months follow-up, 3-5 at 7 years follow-up, and 2 at 7 years after ischemic stroke; although BDNF concentrations were not significantly associated with 3-month outcome. Conversely, another study reported a correlation of low serum BDNF with poor outcome at 3 months. Our previous study suggests that serum BDNF offers minimum predictive value for motor outcome during post-acute inpatient rehabilitation [24]. These discrepancies might be due to variations in clinical variables, patient populations, standard treatment, and genetic predisposition. Subgroup analysis would be necessary to uncover the most robust correlation. A study reporting the association between BDNF and verb naming suggested that BDNF might be one factor linked to the recovery of language [25]. Our observational study is the first to show that the serum BDNF level of aphasic stroke patients in the acute rehabilitation period has a positive correlation with improvement of aphasia severity and gain of FCM spoken language expression scores.

Our study also suggests that higher serum BDNF levels at admission correlate to better comprehension, expression, and memory outcomes at discharge. Aaron, et al. [26], point out that BDNF is important for cognitive performance. BDNF and its receptor (TrkB) are widely distributed and highly expressed throughout the CNS, especially in the cerebral cortex and hippocampus where they are implicated in memory formation and long-term potentiation [27]. A common single-nucleotide polymorphism in the BDNF gene, a methionine (Met) substitution for valine (Val) at codon 66 (Val66Met), has been associated with reduced regional brain volumes as well as poorer cognitive performance [28]. Increasing BDNF level can improve memory and learning skills in rats [29]. Decreased or low BDNF levels have been associated with cognitive impairment and depression [30]. Therefore, our findings in the association of BDNF with cognition are consistent with the body of current literature.

Limitations

There are some limitations of the present study. First, this is a single-center study, the result cannot be generalized to the general population. Second, it is a retrospective study, and several aphasia battery results had missing data that we couldn’t use. Third, the sample size is small. Forth, this study examined the association of serum BDNF level with functional outcome of aphasia, but without analysis of Single Nucleotide Polymorphism (SNF) of BDNF. Further study with a large sample size and combination of genetic analysis would be warranted to confirm the findings.

Conclusion

This study investigated the relationship between BDNF level and cognitive-linguistic outcomes in post-stroke aphasia patients. The findings may provide insight into the biological mechanism of recovery in post-stroke aphasia and may help to develop personalized treatment plans.

Conflicts of Interest

No conflicts of interest have been reported by the authors or by any individuals in control of the content of this article.

The study has been presented as an abstract for at Annual Assembly of American Academy of Physical Medicine and Rehabilitation in October 2018.

Figures


Figure 1: Flow chart

Tables

Characteristics

Aphasic(n=66)

Nonaphasia(n=53)

P value

Age (years)

67.39±16.276

66.11±16.544

0.673

Body mass index (BMI, kg/m2)

29.07±7.197

27.90±8.755

0.425

Gender (n)

 

    Male

37 (56.1)

30 (56.6)

0.953

    Female

29 (43.9)

23 (43.4)

 

Preferred language

 

    English

61 (92.4)

48 (90.6)

0.975

    Not English

5 (7.6)

5 (9.4)

 

Ethnicity (n)

 

    Hispanic or latino

2 (3.0)

3 (5.7)

0.802

    Not Hispanic or latino

64 (97.0)

50 (94.3)

 

Marital status

 

    Single

12 (18.2)

14 (26.4)

0.758

    Separated or divorced

7 (10.6)

5 (9.4)

 

    Windowed

13 (19.7)

9 (17.0)

 

    Married

34 (51.5)

25 (47.2)

 

Risk factors (n)

 

    Hypertension

51 (77.3)

43 (81.1)

0.607

    Atrial fibrillation

16 (24.2)

6 (11.3)

0.071

    Coronary artery disease

10 (15.2)

6 (11.3)

0.543

    Diabetes mellitus

16 (30.2)

18 (27.3)

0.726

    Current smoker

10 (15.2)

11 (20.8)

0.426

Stroke site (n)

 

    Supratentorial

60 (90.9)

34 (64.2)

0.000*

    Infratentorial

5 (7.6)

19 (35.8)

 

    Both

1 (1.5)

0 (0.0)

 

From onset to admission(days)

10.50±8.209

6.11±3.343

0.000*

Length of stay (days)

19.64±8.470

19.73±11.064

0.956

Discharge destination (n)

 

    Home

38 (57.6)

36 (67.9)

0.294

    Skilled nursing facility(SNF)

27 (40.9)

15 (28.3)

 

    Acute hospital

1 (1.5)

2 (3.8)

 

Values are represented as mean ± standard deviations or sample number and percentage.

Table 1: Demographics and clinical characteristics.

Category

Participants

Mixed transcortical aphasia

19 (28.8)

Global aphasia

12 (18.2)

Anomic aphasia

10 (15.2)

Broca’s aphasia

8 (12.1)

Transcortical motor aphasia

3 (4.5)

Wernicke’s aphasia

2 (3.0)

undefined

12 (18.2)

Values are represented as sample number and percentage

Table 2: Aphasia Classification.

 

Function outcome

Aphasic(n=66)

Nonaphasic(n=53)

P value

Admission

Auditory comprehension

5.0(3.0-7.0)

9.0(9.0-9.0)

0.000*

Verbal  expression

3.0(3.0-5.0)

9.0(9.0-9.0)

0.000*

Motor speech

6.0(4.0-9.0)

9.0(6.2-9.0)

0.000*

Attention

9.0(6.0-9.0)

7.0(5.0-9.0)

0.346

Cognitive FIM

14.0(9.5-18.5)

22.0(18.5-25.0)

0.000*

Motor FIM

33.0(15.5-42.5)

34.0(22.0-43.0)

0.342

Total FIM

48.0(29.0-68.0)

59.0(42.5-69.0)

0.026*

Discharge

Auditory comprehension

6.0(4.0-7.0)

9.0(9.0-9.0)

0.000*

Verbal expression

5.0(3.0-7.0)

9.0(9.0-9.0)

0.000*

Motor speech

7.0(4.0-9.0)

9.0(7.0-9.0)

0.003*

Attention

7.0(6.0-9.0)

9.0(6.0-9.0)

0.158

Cognitive FIM

21.0(16.5-26.0)

28.0(24.5-32.0)

0.000*

Motor FIM

54.0(33.5-65.0)

55.0(42.0-67.0)

0.475

Total FIM

80.0(52.5-93.0)

89.0(70.5-101.5)

0.032*

Change

Auditory comprehension

0.0(0.0-1.0)

0.0(0.0-0.0)

0.056

Verbal expression

1.0(0.0-1.0)

0.0(0.0-0.0)

0.002*

Motor speech

0.0(0.0-1.0)

0.0(0.0-1.0)

0.966

Attention

0.0(0.0-1.0)

0.0(0.0-1.0)

0.711

Cognitive FIM

7.0(4.0-9.0)

6.0(3.5-8.0)

0.375

Motor FIM

19.0(10.5-25.5)

21.0(12.0-28.5)

0.482

Total FIM

24.0(19.0-37.0)

28.0(16.5-36.5)

0.574

Values are represented as median and interquartile range. FIM: Functional Independence Measure. *, P <0.050.

Table 3: Functional outcome.

Parameter

Admission

Discharge

Change

Function

r

P value

Function

r

P value

Function

r

P value

Spaulding SLP diagnosis

 

Auditory comprehension

5.30±2.172

0.181

0.147

5.72±2.146

0.136

0.275

0.52±1.134

0.037

0.767

Verbal expression

2.99±1.814

0.148

0.234

4.67±1.959

0.177

0.156

0.82±1.158

0.049

0.694

Motor speech

6.19±2.277

0.099

0.43

6.56±2.391

0.047

0.71

0.40±2.335

0.072

0.564

Attention

7.12±2.574

-0.042

0.737

7.36±1.754

-0.003

0.978

0.26±1.928

0.135

0.278

Severity of aphasia

4.32±1.656

0.045

0.717

5.379±1.871

0.219

0.078

0.95±1.143

0.282

0.022*

FCM

 

 Spoken language comprehension

3.68±1.451

0.088

0.481

4.91±1.101

0.235

0.057

1.28±0.778

0.143

0.253

 Spoken language expression

2.99±1.447

0.07

0.577

4.43±1.421

0.202

0.104

1.39±0.903

0.255

0.038*

FIM

 

Cognitive subtotal

14.17±6.050

0.189

0.128

20.82±5.740

0.284

0.021*

6.65±4.028

0.091

0.467

Comprehension

2.89±1.426

0.096

0.442

4.16±1.376

0.265

0.032*

1.27±0.937

0.169

0.174

Expression

2.30±1.358

0.137

0.271

3.43±1.458

0.308

0.012*

1.13±0.875

0.199

0.109

Social interaction

4.15±1.800

0.186

0.135

5.73±1.342

0.071

0.569

1.57±1.745

-0.104

0.405

Problem solving

2.18±1.189

0.21

0.091

3.53±1.338

0.235

0.058

1.35±1.157

0.038

0.762

Memory

2.39±1.036

0.132

0.29

3.76±1.190

0.266

0.031*

1.36±0.987

0.167

0.18

Motor subtotal

31.41±15.628

0.241

0.051

50.39±20.109

0.29

0.018*

18.98±9.936

0.214

0.085

Total

48.03±20.593

0.284

0.021*

74.91±25.479

0.315

0.010*

26.87±1.522

0.24

0.053

Values are represented as mean ± standard deviations. Spaulding SLP diagnosis, Spaulding Rehabilitation Hospital speech-language pathology diagnosis. FCM: Functional Communication Measures; FIM: Functional Independence Measure. *, P <0.050.

Table 4: Spearman correlation coefficients between BDNF level and aphasic functional outcome

References

  1. Marinelli CV, Spaccavento S, Craca A, Marangolo P, Angelelli P (2017) Different Cognitive Profiles of Patients with Severe Aphasia. Behav 2017: 1-15.
  2. Corsten S, Schimpf EJ, Konradi J, Keilmann A, Hardering F (2015) The participants’ perspective: how biographic-narrative intervention influences identity negotiation and quality of life in aphasia. Int J Lang Commun Disord. 50: 788-800.
  3. Shaywitz BA, Shaywitz SE, Pugh KR, Fulbright RK, Skudlarski P, et al. (2001) The functional neural architecture of components of attention in language-processing tasks. NeuroImage. 13: 601-612.
  4. Fillingham JK, Sage K, Lambon Ralph MA (2006) The treatment of anomia using errorless learning. Neuropsychological rehabilitation. 16: 129-154.
  5. Nicholas M, Sinotte M, Helm-Estabrooks N (2005) Using a computer to communicate: Effect of executive function impairments in people with severe aphasia. Aphasiology. 19: 1052-1065.
  6. Simats A, Garcia-Berrocoso T, Montaner J (2016) Neuroinflammatory biomarkers: From stroke diagnosis and prognosis to therapy. Biochimica et biophysica acta. 1862: 411-424.
  7. Zoladz JA, Pilc A, Majerczak J, Grandys M, Zapart-Bukowska J, et al. (2008) Endurance training increases plasma brain-derived neurotrophic factor concentration in young healthy men. J Physiol 7: 119-132.
  8. Pikula A, Beiser AS, Chen TC, Preis SR, Vorgias D, et al. (2013) Serum brain-derived neurotrophic factor and vascular endothelial growth factor levels are associated with risk of stroke and vascular brain injury: Framingham Study. Stroke. 44: 2768-2775.
  9. Reinhart V, Bove SE, Volfson D, Lewis DA, Kleiman RJ, et al. (2015) Evaluation of TrkB and BDNF transcripts in prefrontal cortex, hippocampus, and striatum from subjects with schizophrenia, bipolar disorder, and major depressive disorder. Neurobiol Dis. 77: 220-227.
  10. Weinstein G, Beiser AS, Choi SH, Preis SR, Chen TC, et al. (2014) Serum brain-derived neurotrophic factor and the risk for dementia: the Framingham Heart Study. JAMA neurology. 71: 55-61.
  11. Failla MD, Juengst SB, Arenth PM, Wagner AK (2016) Preliminary Associations Between Brain-Derived Neurotrophic Factor, Memory Impairment, Functional Cognition, and Depressive Symptoms Following Severe TBI. Neurorehabilitation and neural repair. 30: 419
  12. Berthier ML (2005) Poststroke aphasia: epidemiology, pathophysiology and treatment. Drugs Aging. 22: 163-182.
  13. Watila MM, Balarabe SA (2015) Factors predicting post-stroke aphasia J Neurol Sci. 352: 12-18.
  14. Holmgren E, Rudkilde ES (2013) Aphasia: Classification, management practices, and prognosis. Hauppauge, N.Y.: Nova Science Publishers,
  15. Yu ZZ, Jiang SJ, Jia ZS, Xiao HY, Zhou MQ (2017) Study on Language Rehabilitation for Aphasia. Chin Med J. 130: 1491-1497.
  16. Brucki SM (2015) Cognitive deficit and aphasia-a challenging Arquivos de neuro-psiquiatria. 73: 821-822.
  17. Murray LL (2012) Attention and other cognitive deficits in aphasia: presence and relation to language and communication measures. Am J Speech Lang Pathol. 21: S51-64.
  18. Carbone DL, Handa RJ (2013) Sex and stress hormone influences on the expression and activity of brain-derived neurotrophic factor. 239: 295-303.
  19. Martinowich K, Lu B (2008) Interaction between BDNF and serotonin: role in mood disorders. Neuropsychopharmacology. 33: 73-83.
  20. Helgager J, Liu G, McNamara JO (2013) The cellular and synaptic location of activated TrkB in mouse hippocampus during limbic J Comp Neurol. 521: 499-521.
  21. Zhu X, Ward PJ (2016) Selective Requirement for Maintenance of Synaptic Contacts onto Motoneurons by Target-Derived trkB Neural plasticity. 2016: 2371893.
  22. Bejot Y, Mossiat C, Giroud M, Prigent-Tessier A, Marie C (2011) Circulating and brain BDNF levels in stroke rats. Relevance to clinical PLoS One. 6: e29405.
  23. Stanne TM, Aberg ND, Nilsson S, Jood K, Blomstrand C, et al. (2016) Low Circulating Acute Brain-Derived Neurotrophic Factor Levels Are Associated With Poor Long-Term Functional Outcome After Ischemic Stroke. 47: 1943-1945.
  24. Luo W, Liu T, Li S, Wen H, Zhou F, et al. (2018) The Serum BDNF Level Offers Minimum Predictive Value for Motor Function Recovery After Stroke. Translational stroke research. 10: 342-351.
  25. Marangolo P, Fiori V, Cipollari S, Campana S, Razzano C, et al. (2013) Bihemispheric stimulation over left and right inferior frontal region enhances recovery from apraxia of speech in chronic aphasia. Eur J 38: 3370-3377.
  26. Piepmeier AT, Etnier JL (2015) Brain-derived neurotrophic factor (BDNF) as a potential mechanism of the effects of acute exercise on cognitive performance. Journal of Sport and Health Science. 4: 14-23.
  27. Bekinschtein P, Cammarota M, Izquierdo I, Medina JH (2008) BDNF and memory formation and storage. Neuroscientist. 14: 147-156.
  28. Nemoto K, Ohnishi T, Mori T, Moriguchi Y, Hashimoto R, et al. (2006) The Val66Met polymorphism of the brain-derived neurotrophic factor gene affects age-related brain morphology. Neuroscience letters. 397: 25-29.
  29. Mokhtari T, Akbari M, Malek F, Kashani IR, Rastegar T, et al. (2017) Improvement of memory and learning by intracerebroventricular microinjection of T3 in rat model of ischemic brain stroke mediated by upregulation of BDNF and GDNF in CA1 hippocampal region. Daru: Journal of Faculty of Pharmacy. 25: 4.
  30. Zhang L, Chen X, Feng W, Cui Y, Xu S, et al. (2012) Enhancing effects of chronic lithium treatment on detour learning in chicks. Biol Trace Elem Res. 148: 38-43.

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International Journal of Cerebrovascular Disease and Stroke

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