Genetic Variation and Stroke Recovery: The STRONG Study.

BACKGROUND: Genetic association studies can reveal biology and treatment targets but have received limited attention for stroke recovery. STRONG (Stroke, Stress, Rehabilitation, and Genetics) was a prospective, longitudinal (1-year), genetic study in adults with stroke at 28 US stroke centers. The primary aim was to examine the association that candidate genetic variants have with (1) motor/functional outcomes and (2) stress-related outcomes. METHODS: For motor/functional end points, 3 candidate gene variants (ApoE ε4, BDNF [brain-derived neurotrophic factor], and a dopamine polygenic score) were analyzed for associations with change in grip strength (3 months-baseline), function (3-month Stroke Impact Scale-Activities of Daily Living), mood (3-month Patient Health Questionnaire-8), and cognition (12-month telephone-Montreal Cognitive Assessment). For stress-related outcomes, 7 variants (serotonin transporter gene-linked promoter region, ACE [angiotensin-converting enzyme], oxytocin receptor, FKBP5 [FKBP prolyl isomerase 5], FAAH [fatty acid amide hydrolase], BDNF, and COMT [catechol-O-methyltransferase]) were assessed for associations with posttraumatic stress disorder ([PTSD]; PTSD Primary Care Scale) and depression (Patient Health Questionnaire-8) at 6 and 12 months; stress-related genes were examined as a function of poststroke stress level. Statistical models (linear, negative binomial, or Poisson regression) were based on response variable distribution; all included stroke severity, age, sex, and ancestry as covariates. Stroke subtype was explored secondarily. Data were Holm-Bonferroni corrected. A secondary replication analysis tested whether the rs1842681 polymorphism (identified in the GISCOME study [Genetics of Ischaemic Stroke Functional Outcome]) was related to 3-month modified Rankin Scale score in STRONG. RESULTS: The 763 enrollees were 63.1±14.9 (mean±SD) years of age, with a median initial National Institutes of Health Stroke Scale score of 4 (interquartile range, 2-9); outcome data were available in n=515 at 3 months, n=500 at 6 months, and n=489 at 12 months. At 1 year poststroke, the rs6265 (BDNF) variant was associated with poorer cognition (0.9-point lower telephone-Montreal Cognitive Assessment score, P=1×10-5). For stress-related outcomes, rs4291 (ACE) and rs324420 (FAAH) were risk factors linking increased poststroke stress with higher 1-year depression and PTSD symptoms (P<0.05), while rs4680 (COMT) linked poststroke stress with lower 1-year depression and PTSD. Findings were unchanged when considering stroke subtype. STRONG replicated GISCOME: rs1842681 was associated with lower 3-month modified Rankin Scale score (P=3.2×10-5). CONCLUSIONS: This study identified genetic associations with cognitive function, depression, and PTSD 1 year poststroke. Genetic susceptibility to PTSD and depressive symptoms varied according to the amount of poststroke stress, underscoring the critical role of lived experiences in recovery. Together, the results suggest that genetic association studies provide insights into the biology of stroke recovery in humans.

Increased stroke severity and mortality in patients with SARS-CoV-2 infection: An analysis from the N3C database.

BACKGROUND: Studies from early in the COVID-19 pandemic showed that patients with ischemic stroke and concurrent SARS-CoV-2 infection had increased stroke severity. We aimed to test the hypothesis that this association persisted throughout the first year of the pandemic and that a similar increase in stroke severity was present in patients with hemorrhagic stroke. METHODS: Using the National Institute of Health National COVID Cohort Collaborative (N3C) database, we identified a cohort of patients with stroke hospitalized in the United States between March 1, 2020 and February 28, 2021. We propensity score matched patients with concurrent stroke and SARS-COV-2 infection and available NIH Stroke Scale (NIHSS) scores to all other patients with stroke in a 1:3 ratio. Nearest neighbor matching with a caliper of 0.25 was used for most factors and exact matching was used for race/ethnicity and site. We modeled stroke severity as measured by admission NIHSS and the outcomes of death and length of stay. We also explored the temporal relationship between time of SARS-COV-2 diagnosis and incidence of stroke. RESULTS: Our query identified 43,295 patients hospitalized with ischemic stroke (5765 with SARS-COV-2, 37,530 without) and 18,107 patients hospitalized with hemorrhagic stroke (2114 with SARS-COV-2, 15,993 without). Analysis of our propensity matched cohort revealed that stroke patients with concurrent SARS-COV-2 had increased NIHSS (Ischemic stroke: IRR=1.43, 95% CI:1.33-1.52, p<0.001; hemorrhagic stroke: IRR=1.20, 95% CI:1.08-1.33, p<0.001), length of stay (Ischemic stroke: estimate = 1.48, 95% CI: 1.37, 1.61, p<0.001; hemorrhagic stroke: estimate = 1.25, 95% CI: 1.06, 1.47, p=0.007) and higher odds of death (Ischemic stroke: OR 2.19, 95% CI: 1.79-2.68, p<0.001; hemorrhagic stroke: OR 2.19, 95% CI: 1.79-2.68, p<0.001). We observed the highest incidence of stroke diagnosis on the same day as SARS-COV-2 diagnosis with a logarithmic decline in counts. CONCLUSION: This retrospective observational analysis suggests that stroke severity in patients with concurrent SARS-COV-2 was increased throughout the first year of the pandemic.

Vertebral Artery Tortuosity and Morphometric Characteristics of Patients with Recurrent Cervical Artery Dissection.

BACKGROUND: Cervical Artery Dissection is an important cause of stroke in the young. Data on incidence and associations of recurrence in patients with cervical artery dissection are lacking. Increased Vertebral Artery Tortuosity Index has been reported in patients with cervical artery dissection and associated with earlier age of arterial dissection in patients with connective tissue disease. OBJECTIVE: To test the hypothesis that increased vertebral artery tortuosity is associated with recurrent cervical artery dissection. METHODS: We reviewed data from a single-center registry of cervical artery dissection patients enrolled between 2011-2021. CT angiography was reviewed for neck length, vertebral artery dominance, and vertebral artery tortuosity index. Incidence rate of recurrent dissection was calculated using Poisson regression. Differences between groups were analyzed using the Kruskal-Wallis rank sum test and Fisher's exact test. RESULTS: The cohort included 155 patients: women (56%), mean (SD) age 42 (±10) years, and 116 single and 39 multiple artery dissections. Eleven (7.1%) had a recurrence with an incidence rate (95% CI) of 1.91 (1.06, 3.44) per 100 person-years. Vertebral artery tortuosity did not differ significantly between single and recurrent groups (median (IQR) 46.81 (40.85, 53.91) vs 44.97 (40.68, 50.62) p = 0.388). Morphometric characteristics of height, neck length, and BMI were not associated with recurrence. There was no difference in vertebral artery tortuosity by dissection location (carotid vs vertebral). CONCLUSION: In this single center cohort of patients with cervical artery dissection, there was no difference in VTI between single and recurrent groups.

Association of Seizure Control With Cognition in People With Normal Cognition and Mild Cognitive Impairment.

BACKGROUND AND OBJECTIVES: Seizures are common in dementia and associated with accelerated cognitive decline. However, the impact of active vs remote seizures on cognition remains understudied. This study aimed to investigate the impact of active vs remote seizures on cognition in people with normal cognition and mild cognitive impairment (MCI). METHODS: This longitudinal, multicenter cohort is based on National Alzheimer's Coordinating Center data of participants recruited from 39 Alzheimer's Disease Centers in the United States from September 2005 to December 2021. All participants with normal cognition and MCI and at least 2 visits were included. Primary outcome, that is, cognitive decline, was determined using Clinical Dementia Rating (CDR) from (1) normal-to-impaired (CDR ≥0.5) and (2) MCI-to-dementia (CDR ≥1) groups. The effect of active seizures (over the preceding 12 months), remote seizures (previous seizures but none over the preceding 12 months), and no seizures (controls) on cognition was assessed. Subgroups of chronic seizures at enrollment and new-onset seizures were further analyzed. Cox regression models assessed the risk of all-cause MCI and/or dementia. All models were adjusted for age, sex, education, race, hypertension, and diabetes. RESULTS: Of the 13,726 participants with normal cognition at enrollment (9,002 [66%] female; median age 71 years), 118 had active seizures and 226 had remote seizures. Of the 11,372 participants with MCI at enrollment (5,605 [49%] female; median age 73 years), 197 had active seizures and 226 had remote seizures. Active seizures were associated with 2.1 times higher risk of cognitive impairment (adjusted hazard ratio [aHR] 2.13, 95% CI 1.60-2.84, p < 0.001) in cognitively healthy adults (median years to decline: active seizures = ∼1, remote seizures = ∼3, no seizures = ∼3) and 1.6 times higher risk of dementia (aHR 1.58, 95% CI 1.24-2.01, p < 0.001) in those with MCI (median years to decline: active seizures = ∼1, remote seizures = ∼2, controls = ∼2). This risk was not observed with remote seizures. DISCUSSION: In this study, active seizures but not remote seizures were associated with earlier cognitive decline in both cognitively normal adults and those with MCI, independent of other dementia risk factors. Therefore, early identification and management of seizures may present a path to mitigation of cognitive decline in the aging epileptic population. A limitation is that causality cannot be confirmed in our observational longitudinal study.

Genome-Wide Association Studies of 3 Distinct Recovery Phenotypes in Mild Ischemic Stroke.

BACKGROUND AND OBJECTIVES: Stroke genetic research has made substantial progress in the past decade. Its recovery application, however, remains behind, in part due to its reliance on the modified Rankin Scale (mRS) score as a measure of poststroke outcome. The mRS does not map well to biological processes because numerous psychosocial factors drive much of what the mRS captures. Second, the mRS contains multiple disparate biological events into a single measure further limiting its use for biological discovery. This led us to investigate the effect of distinct stroke recovery phenotypes on genetic variation associations with Genome-Wide Association Studies (GWASs) by repurposing the NIH Stroke Scale (NIHSS) and its subscores. METHODS: In the Vitamin Intervention for Stroke Prevention cohort, we estimated changes in cognition, motor, and global impairments over 2 years using specific measures. We included genotyped participants with a total NIHSS score greater than zero at randomization and excluded those with recurrent stroke during the trial. A GWAS linear mixed-effects model predicted score changes, with participant as a random effect, and included initial score, age, sex, treatment group, and the first 5 ancestry principal components. RESULTS: In total, 1,270 participants (64% male) were included with a median NIHSS score of 2 (interquartile range [IQR] 1-3) and median age 68 (IQR 59-75) years. At randomization, 20% had cognitive deficits (NIHSS Cog-4 score >0) and 70% had ≥1 motor deficits (impairment score >1). At 2 years, these percentages improved to 7.2% with cognitive deficits and 30% with motor deficits. GWAS identified novel suggestive gene-impairment associations (p < 5e-6) for cognition (CAMK2D, EVX2, LINC0143, PTPRM, SGMS1, and SMAD2), motor (ACBD6, KDM4B, MARK4, PTPRS, ROBO1, and ROBO2), and global (MSR1 and ROBO2) impairments. DISCUSSION: Defining domain-specific stroke recovery phenotypes and using longitudinal clinical trial designs can help detect novel genes associated with chronic recovery. These data support the use of granular endpoints to identify genetic associations related to stroke recovery.

Single Nucleotide Polymorphisms Associated With Motor Recovery in Patients With Nondisabling Stroke: GWAS Study.

BACKGROUND AND OBJECTIVES: Despite notable advances in genetic understanding of stroke recovery, most studies focus only on candidate genes. To date, only 2 genome-wide association studies (GWAS) have focused on stroke outcomes, but they were limited to the modified Rankin Scale (mRS). The mRS maps poorly to biological processes. Therefore, we performed a GWAS to discover single nucleotide polymorphisms (SNPs) associated with motor recovery poststroke. METHODS: We used the Vitamin Intervention for Stroke Prevention (VISP) data set of 2,100 genotyped participants with nondisabling stroke. We included only participants who had motor impairment at randomization. Participants with a recurrent stroke during the trial were excluded. Genotyped data underwent strict quality control and imputation. The GWAS used logistic regression models with generalized estimating equations to leverage the repeated NIH Stroke Scale motor score measurements spanning 6 time points over 24 months. The primary outcome was a decrease in the motor drift score of ≥1 vs <1 at each time point. Our model estimated the odds ratio (OR) of motor improvement for each SNP after adjusting for age, sex, race, days from stroke to visit, initial motor score, VISP treatment arm, and principal components. RESULTS: A total of 488 (64%) participants with a mean (SD) age of 66 ± 11 years were included in the GWAS. Although no associations reached genome-wide significance (p < 5 × 10-8), our analysis detected 115 suggestive associations (p < 5 × 10-6). Notably, we found multiple SNP clusters near genes with plausible neuronal repair biology mechanisms. The CLDN23 gene had the most convincing association with rs1268196-T as its most significant SNP (OR 0.32; 95% CI 0.21-0.48; p value 6.19 × 10-7). CLDN23 affects blood-brain barrier integrity, neurodevelopment, and immune cell transmigration. DISCUSSION: We identified novel suggestive genetic associations with the first-ever motor-specific poststroke recovery GWAS. The results seem to describe a distinct stroke recovery phenotype compared with prior genetic stroke outcome studies that use outcome measures, such as the mRS. Replication and further mechanistic investigation are warranted. In addition, this study demonstrated a proof-of-principle approach to optimize statistical efficiency with longitudinal data sets for genetic discovery.

Post Stroke Motor Recovery Genome Wide Association Study: A Domain-Specific Approach.

Background: In this genome wide association study (GWAS) we aimed to discover single nucleotide polymorphisms (SNPs) associated with motor recovery post-stroke. Methods: We used the Vitamin Intervention for Stroke Prevention (VISP) dataset of 2,100 genotyped patients with non-disabling stroke. Of these, 488 patients had motor impairment at enrollment. Genotyped data underwent strict quality control and imputation. The GWAS utilized logistic regression models with generalized estimating equations (GEE) to leverage the repeated NIH Stroke Scale (NIHSS) motor score measurements spanning 6 time points over 24 months. The primary outcome was a decrease in the motor drift score of ≥ 1 vs. < 1 at each timepoint. Our model estimated the odds ratio of motor improvement for each SNP after adjusting for age, sex, race, days from stroke to visit, initial motor score, VISP treatment arm, and principal components. Results: Although no associations reached genome-wide significance (p < 5 × 10 -8 ), our analysis detected 115 suggestive associations (p < 5 × 10 -6 ). Notably, we found multiple SNP clusters near genes with plausible neuronal repair biology mechanisms. The CLDN23 gene had the most convincing association which affects blood-brain barrier integrity, neurodevelopment, and immune cell transmigration. Conclusion: We identified novel suggestive genetic associations with the first ever motor-specific post stroke recovery GWAS. The results seem to describe a distinct stroke recovery phenotype compared to prior genetic stroke outcome studies that use outcome measures, like the mRS. Replication and further mechanistic investigation are warranted. Additionally, this study demonstrated a proof-of-principle approach to optimize statistical efficiency with longitudinal datasets for genetic discovery.

Approach to Quantify Eye Movements to Augment Stroke Diagnosis With a Non-Calibrated Eye-Tracker.

Automated eye-tracking technology could enhance diagnosis for many neurological diseases, including stroke. Current literature focuses on gaze estimation through a form of calibration. However, patients with neuro-ocular abnormalities may have difficulty completing a calibration procedure due to inattention or other neurological deficits. OBJECTIVE: We investigated 1) the need for calibration to measure eye movement symmetry in healthy controls and 2) the potential of eye movement symmetry to distinguish between healthy controls and patients. METHODS: We analyzed fixations, smooth pursuits, saccades, and conjugacy measured by a Spearman correlation coefficient and utilized a linear mixed-effects model to estimate the effect of calibration. RESULTS: Healthy participants (n = 18) did not differ in correlations between calibrated and non-calibrated conditions for all tests. The calibration condition did not improve the linear mixed effects model (log-likelihood ratio test p = 0.426) in predicting correlation coefficients. Interestingly, the patient group (n = 17) differed in correlations for the DOT (0.844 [95% CI 0.602, 0.920] vs. 0.98 [95% CI 0.976, 0.985]), H (0.903 [95% CI 0.746, 0.958] vs. 0.979 [95% CI 0.971, 0.986]), and OKN (0.898 [95% CI 0.785, 0.958] vs. 0.993 [95% CI 0.987, 0.996]) tests compared to healthy controls along the x-axis. These differences were not observed along the y-axis. SIGNIFICANCE: This study suggests that automated eye tracking can be deployed without calibration to measure eye movement symmetry. It may be a good discriminator between normal and abnormal eye movement symmetry. Validation of these findings in larger populations is required.

Human vs. Machine Learning Based Detection of Facial Weakness Using Video Analysis.

Background: Current EMS stroke screening tools facilitate early detection and triage, but the tools' accuracy and reliability are limited and highly variable. An automated stroke screening tool could improve stroke outcomes by facilitating more accurate prehospital diagnosis and delivery. We hypothesize that a machine learning algorithm using video analysis can detect common signs of stroke. As a proof-of-concept study, we trained a computer algorithm to detect presence and laterality of facial weakness in publically available videos with comparable accuracy, sensitivity, and specificity to paramedics. Methods and Results: We curated videos of people with unilateral facial weakness (n = 93) and with a normal smile (n = 96) from publicly available web-based sources. Three board certified vascular neurologists categorized the videos according to the presence or absence of weakness and laterality. Three paramedics independently analyzed each video with a mean accuracy, sensitivity and specificity of 92.6% [95% CI 90.1-94.7%], 87.8% [95% CI 83.9-91.7%] and 99.3% [95% CI 98.2-100%]. Using a 5-fold cross validation scheme, we trained a computer vision algorithm to analyze the same videos producing an accuracy, sensitivity and specificity of 88.9% [95% CI 83.5-93%], 90.3% [95% CI 82.4-95.5%] and 87.5 [95% CI 79.2-93.4%]. Conclusions: These preliminary results suggest that a machine learning algorithm using computer vision analysis can detect unilateral facial weakness in pre-recorded videos with an accuracy and sensitivity comparable to trained paramedics. Further research is warranted to pursue the concept of augmented facial weakness detection and external validation of this algorithm in independent data sets and prospective patient encounters.

Video-Based Facial Weakness Analysis.

OBJECTIVE: Facial weakness is a common sign of neurological diseases such as Bell's palsy and stroke. However, recognizing facial weakness still remains as a challenge, because it requires experience and neurological training. METHODS: We propose a framework for facial weakness detection, which models the temporal dynamics of both shape and appearance-based features of each target frame through a bi-directional long short-term memory network (Bi-LSTM). The system is evaluated on a "in-the-wild"video dataset that is verified by three board-certified neurologists. In addition, three emergency medical services (EMS) personnel and three upper level residents rated the dataset. We compare the evaluation of the proposed algorithm with other comparison methods as well as the human raters. RESULTS: Experimental evaluation demonstrates that: (1) the proposed algorithm achieves the accuracy, sensitivity, and specificity of 94.3%, 91.4%, and 95.7%, which outperforms other comparison methods and achieves the equal performance to paramedics; (2) the framework can provide visualizable and interpretable results that increases model transparency and interpretability; (3) a prototype is implemented as a proof-of-concept showcase to show the feasibility of an inexpensive solution for facial weakness detection. CONCLUSION: The experiment results suggest that the proposed framework can identify facial weakness effectively. SIGNIFICANCE: We provide a proof-of-concept study, showing that such technology could be used by non-neurologists to more readily identify facial weakness in the field, leading to increasing coverage and earlier treatment.