Life's Essential 8 and Poor Brain Health Outcomes in Middle-Aged Adults.

BACKGROUND AND OBJECTIVES: Mounting evidence points to a strong connection between cardiovascular risk during middle age and brain health later in life. The American Heart Association's Life's Essential 8 (LE8) constitutes a research and public health construct capturing key determinants of cardiovascular health. However, the overall effect of the LE8 on global, clinically relevant metrics of brain health is still unknown. We tested the hypothesis that worse LE8 profiles are associated with higher composite risk of the most important clinical endpoints related to poor brain health. METHODS: We conducted a two-stage (discovery and replication) prospective study using data from the UK Biobank (UKB) and All of Us (AoU), 2 large population studies in the United Kingdom and the United States, respectively. The primary exposure was the LE8 score, a validated tool that captures 8 modifiable cardiovascular risk factors (blood pressure, glucose, cholesterol, body mass index, smoking, physical activity, diet, and sleep duration), organized in 3 categories (optimal, intermediate, and poor). The primary outcome was a composite of stroke, dementia, or late-life depression. We evaluated associations using multivariable Cox proportional hazard models. RESULTS: The discovery stage included 316,127 UKB participants (mean age 56, 52% female). Over a mean (SD) follow-up time of 4.9 (0.4) years, the unadjusted risk of the composite outcome was 0.7% (95% CI 0.61-0.74), 1.2% (95% CI 1.11-1.22), and 1.8% (95% CI 1.70-1.91) in participants with optimal, intermediate, and poor cardiovascular health, respectively (p < 0.001). This association remained significant in multivariable Cox models (intermediate vs optimal cardiovascular health hazard ratio [HR], 1.37; 95% CI 1.24-1.52, and poor vs optimal cardiovascular health HR, 2.11; 95% CI 1.88-2.36, p trend <0.001). The replication stage included 68,407 AoU participants (mean age 56, 60% female). Over a mean (SD) follow-up time of 2.9 (1.41) years, the unadjusted risk of the composite outcome was 2.8% (95% CI 2.49-3.05), 6% (95% CI 5.76-6.22), and 9.7% (95% CI 9.24-10.24) in participants with optimal, intermediate, and poor cardiovascular health, respectively (p < 0.001). This association remained significant in multivariable Cox models (intermediate vs optimal cardiovascular health, HR 1.35; 95% CI 1.21-1.51, and poor vs optimal cardiovascular health, HR 1.94; 95% CI 1.72-2.18; p trend <0.001). DISCUSSION: Among middle-aged adults enrolled in 2 large population studies, poor cardiovascular health profiles were associated with two-fold higher risk of developing a composite outcome that captures the most important diseases related to poor brain health. Because the evaluated risk factors are all modifiable, our findings highlight the potential brain health benefits of using the Life's Essential 8 to guide cardiovascular health optimization.

Brain Health Outcomes in Sexual and Gender Minority Groups: Results From the All of Us Research Program.

BACKGROUND AND OBJECTIVES: Sexual and gender minority (SGM) groups have been historically underrepresented in neurologic research, and their brain health disparities are unknown. We aim to evaluate whether SGM persons are at higher risk of adverse brain health outcomes compared with cisgender straight (non-SGM) individuals. METHODS: We conducted a cross-sectional study in the All of Us Research Program, a US population-based study, including all participants with information on gender identity and sexual orientation. We used baseline questionnaires to identify sexual minority (lesbian, gay, bisexual, diverse sexual orientation; nonstraight sexual orientation) and gender minority (gender diverse and transgender; gender identity different from sex assigned at birth) participants. The primary outcome was a composite of stroke, dementia, and late-life depression, assessed using electronic health record data and self-report. Secondarily, we evaluated each disease separately. Furthermore, we evaluated all subgroups of gender and sexual minorities stratified by sex assigned at birth. We used multivariable logistic regression (adjusted for age, sex assigned at birth, race/ethnicity, cardiovascular risk factors, other relevant comorbidities, and neighborhood deprivation index) to assess the relationship between SGM groups and the outcomes. RESULTS: Of 413,457 US adults enrolled between May 31, 2017, and June 30, 2022, we included 393,041 participants with available information on sexual orientation and gender identity (mean age 51 [SD 17] years), of whom 39,632 (10%) belonged to SGM groups. Of them, 38,528 (97%) belonged to a sexual minority and 4,431 (11%) to a gender minority. Compared with non-SGM, SGM persons had 15% higher odds of the brain health composite outcome (odds ratio [OR] 1.15, 95% CI 1.08-1.22). In secondary analyses, these results persisted across sexual and gender minorities separately (all 95% CIs > 1). Assessing individual diseases, all SGM groups had higher odds of dementia (SGM vs non-SGM: OR 1.14, 95% CI 1.00-1.29) and late-life depression (SGM vs non-SGM: OR 1.27, 95% CI 1.17-1.38) and transgender women had higher odds of stroke (OR 1.68, 95% CI 1.04-2.70). DISCUSSION: In a large US population study, SGM persons had higher odds of adverse brain health outcomes. Further research should explore structural causes of inequity to advance inclusive and diverse neurologic care.

The predictive validity of a Brain Care Score for late-life depression and a composite outcome of dementia, stroke, and late-life depression: data from the UK Biobank cohort.

Introduction: The 21-point Brain Care Score (BCS) is a novel tool designed to motivate individuals and care providers to take action to reduce the risk of stroke and dementia by encouraging lifestyle changes. Given that late-life depression is increasingly recognized to share risk factors with stroke and dementia, and is an important clinical endpoint for brain health, we tested the hypothesis that a higher BCS is associated with a reduced incidence of future depression. Additionally, we examined its association with a brain health composite outcome comprising stroke, dementia, and late-life depression. Methods: The BCS was derived from the United Kingdom Biobank baseline evaluation in participants with complete data on BCS items. Associations of BCS with the risk of subsequent incident late-life depression and the composite brain health outcome were estimated using multivariable Cox proportional hazard models. These models were adjusted for age at baseline and sex assigned at birth. Results: A total of 363,323 participants were included in this analysis, with a median BCS at baseline of 12 (IQR: 11-14). There were 6,628 incident cases of late-life depression during a median follow-up period of 13 years. Each five-point increase in baseline BCS was associated with a 33% lower risk of incident late-life depression (95% CI: 29%-36%) and a 27% lower risk of the incident composite outcome (95% CI: 24%-30%). Discussion: These data further demonstrate the shared risk factors across depression, dementia, and stroke. The findings suggest that a higher BCS, indicative of healthier lifestyle choices, is significantly associated with a lower incidence of late-life depression and a composite brain health outcome. Additional validation of the BCS is warranted to assess the weighting of its components, its motivational aspects, and its acceptability and adaptability in routine clinical care worldwide.

Brain Care Score and Neuroimaging Markers of Brain Health in Asymptomatic Middle-Age Persons.

OBJECTIVES: To investigate associations between health-related behaviors as measured using the Brain Care Score (BCS) and neuroimaging markers of white matter injury. METHODS: This prospective cohort study in the UK Biobank assessed the BCS, a novel tool designed to empower patients to address 12 dementia and stroke risk factors. The BCS ranges from 0 to 21, with higher scores suggesting better brain care. Outcomes included white matter hyperintensities (WMH) volume, fractional anisotropy (FA), and mean diffusivity (MD) obtained during 2 imaging assessments, as well as their progression between assessments, using multivariable linear regression adjusted for age and sex. RESULTS: We included 34,509 participants (average age 55 years, 53% female) with no stroke or dementia history. At first and repeat imaging assessments, every 5-point increase in baseline BCS was linked to significantly lower WMH volumes (25% 95% CI [23%-27%] first, 33% [27%-39%] repeat) and higher FA (18% [16%-20%] first, 22% [15%-28%] repeat), with a decrease in MD (9% [7%-11%] first, 10% [4%-16%] repeat). In addition, a higher baseline BCS was associated with a 10% [3%-17%] reduction in WMH progression and FA decline over time. DISCUSSION: This study extends the impact of the BCS to neuroimaging markers of clinically silent cerebrovascular disease. Our results suggest that improving one's BCS could be a valuable intervention to prevent early brain health decline.

APOE epsilon variants and composite risk of dementia, disability, and death in the health and retirement study.

BACKGROUND: Clinical trials in older adults are increasingly focused on functional outcomes, and the composite outcome of dementia, disability, and death is gaining pivotal importance. Genetic variation, particularly the APOE epsilon(ε) variants, may modify responses to new treatments. Although APOE ε4 is known to influence these outcomes separately, the magnitude of its effect on this composite outcome remains unknown. We tested the hypothesis that APOE ε4 increases, whereas APOE ε2 decreases, the risk of a composite outcome of dementia, disability, and death. METHODS: We evaluated clinical and genomic data from the Health and Retirement Study collected from 1992 to 2020. We used variants rs429358 and rs7412 to determine APOE genotypes, modeled dominantly (carriers/noncarriers). We conducted survival analysis, using multivariable Cox proportional hazards models with a composite endpoint of dementia, disability, and death. Our primary analysis evaluated participants with genetic data and no previous dementia or disability. In secondary analyses, we focused on persons aged > = 75 years without heart disease or stroke, a subpopulation increasingly important in clinical trials of older adults. RESULTS: We included 14,527 participants in the primary analysis. Over a median of 18 (Interquartile Range [IQR] 12-24) years, 6711 (46%) participants developed the composite outcome. In Cox analyses, APOE ε4 associated with higher risk (HR:1.15, 95%CI:1.09-1.22) of the composite outcome, whereas APOE ε2 associated with lower risk (HR:0.92, 95%CI:0.86-0.99). In the secondary analysis, we included 3174 participants. Over a median of 7 (IQR 4-11) years, 1326 participants (42%) developed the composite outcome. In Cox analyses, APOE ε4 associated with higher risk (HR:1.25, 95%CI:1.10-1.41) of the composite outcome, whereas APOE ε2 associated with lower risk (HR:0.84, 95%CI:0.71-0.98). CONCLUSIONS: APOE ε variants are linked to the risk of dementia, disability, and death in older adults. By examining these variants in clinical trials, we can better elucidate how they might alter the effectiveness of tested interventions. Importantly, this genetic information could help identify participants who may have greater absolute benefit from such interventions.

Deep learning survival model predicts outcome after intracerebral hemorrhage from initial CT scan.

BACKGROUND: Predicting functional impairment after intracerebral hemorrhage (ICH) provides valuable information for planning of patient care and rehabilitation strategies. Current prognostic tools are limited in making long term predictions and require multiple expert-defined inputs and interpretation that make their clinical implementation challenging. This study aimed to predict long term functional impairment of ICH patients from admission non-contrast CT scans, leveraging deep learning models in a survival analysis framework. METHODS: We used the admission non-contrast CT scans from 882 patients from the Massachusetts General Hospital ICH Study for training, hyperparameter optimization, and model selection, and 146 patients from the Yale New Haven ICH Study for external validation of a deep learning model predicting functional outcome. Disability (modified Rankin scale [mRS] > 2), severe disability (mRS > 4), and dependent living status were assessed via telephone interviews after 6, 12, and 24 months. The prediction methods were evaluated by the c-index and compared with ICH score and FUNC score. RESULTS: Using non-contrast CT, our deep learning model achieved higher prediction accuracy of post-ICH dependent living, disability, and severe disability by 6, 12, and 24 months (c-index 0.742 [95% CI -0.700 to 0.778], 0.712 [95% CI -0.674 to 0.752], 0.779 [95% CI -0.733 to 0.832] respectively) compared with the ICH score (c-index 0.673 [95% CI -0.662 to 0.688], 0.647 [95% CI -0.637 to 0.661] and 0.697 [95% CI -0.675 to 0.717]) and FUNC score (c-index 0.701 [95% CI- 0.698 to 0.723], 0.668 [95% CI -0.657 to 0.680] and 0.727 [95% CI -0.708 to 0.753]). In the external independent Yale-ICH cohort, similar performance metrics were obtained for disability and severe disability (c-index 0.725 [95% CI -0.673 to 0.781] and 0.747 [95% CI -0.676 to 0.807], respectively). Similar AUC of predicting each outcome at 6 months, 1 and 2 years after ICH was achieved compared with ICH score and FUNC score. CONCLUSION: We developed a generalizable deep learning model to predict onset of dependent living and disability after ICH, which could help to guide treatment decisions, advise relatives in the acute setting, optimize rehabilitation strategies, and anticipate long-term care needs.

Secondary Prevention in Patients With Stroke Versus Myocardial Infarction: Analysis of 2 National Cohorts.

BACKGROUND: The implementation of preventive therapies among patients with stroke remains inadequately explored, especially when compared with patients with myocardial infarction (MI), despite sharing similar vascular risk profiles. We tested the hypothesis that participants with a history of stroke have a worse cardiovascular prevention profile in comparison to participants with MI. METHODS AND RESULTS: In cross-sectional analyses within the UK Biobank and All of Us Research Program, involving 14 760 (9193 strokes, 5567 MIs) and 7315 (2948 strokes, 4367 MIs) participants, respectively, we evaluated cardiovascular prevention profiles assessing low-density lipoprotein (<100 mg/dL), blood pressure (systolic, <140 mm Hg; and diastolic, <90 mm Hg), statin and antiplatelet use, and a cardiovascular prevention score that required meeting at least 3 of these criteria. The results revealed that, within the UK Biobank, patients with stroke had significantly lower odds of meeting all the preventive criteria compared with patients with MI: low-density lipoprotein control (odds ratio [OR], 0.73 [95% CI, 0.68-0.78]; P<0.001), blood pressure control (OR, 0.63 [95% CI, 0.59-0.68]; P<0.001), statin use (OR, 0.45 [95% CI, 0.42-0.48]; P<0.001), antiplatelet therapy use (OR, 0.30 [95% CI, 0.27-0.32]; P<0.001), and cardiovascular prevention score (OR, 0.42 [95% CI, 0.39-0.45]; P<0.001). Similar patterns were observed in the All of Us Research Program, with significant differences across all comparisons (P<0.05), and further analysis suggested that the odds of having a good cardiovascular prevention score were influenced by race and ethnicity as well as neighborhood deprivation levels (interaction P<0.05 in both cases). CONCLUSIONS: In 2 independent national cohorts, patients with stroke showed poorer cardiovascular prevention profiles and lower adherence to guideline-directed therapies compared with patients with MI. These findings underscore the need to explore the reasons behind the underuse of secondary prevention in vulnerable stroke survivors.

APOE ε4 and Intracerebral Hemorrhage in Patients With Brain Arteriovenous Malformation.

Importance: Intracerebral hemorrhage (ICH) is a serious complication of brain arteriovenous malformation (AVM). Apolipoprotein E (APOE) ε4 is a well-known genetic risk factor for ICH among persons without AVM, and cerebral amyloid angiopathy is a vasculopathy frequently observed in APOE ε4 carriers that may increase the risk of ICH. Objective: To assess whether APOE ε4 is associated with a higher risk of ICH in patients with a known AVM. Design, Setting, and Participants: This cross-sectional study including 412 participants was conducted in 2 stages (discovery and replication) using individual-level data from the UK Biobank (released March 2012 and last updated October 2023) and the All of Us Research Program (commenced on May 6, 2018, with its latest update provided in October 2023). The occurrence of AVM and ICH was ascertained at the time of enrollment using validated International Classification of Diseases, Ninth Revision and Tenth Revision, codes. Genotypic data on the APOE variants rs429358 and rs7412 were used to ascertain the ε status. Main Outcomes and Measures: For each study, the association between APOE ε4 variants and ICH risk was assessed among patients with a known AVM by using multivariable logistic regression. Results: The discovery phase included 253 UK Biobank participants with known AVM (mean [SD] age, 56.6 [8.0] years, 119 [47.0%] female), of whom 63 (24.9%) sustained an ICH. In the multivariable analysis of 240 participants of European ancestry, APOE ε4 was associated with a higher risk of ICH (odds ratio, 4.58; 95% CI, 2.13-10.34; P < .001). The replication phase included 159 participants with known AVM enrolled in All of Us (mean [SD] age, 57.1 [15.9] years; 106 [66.7%] female), of whom 29 (18.2%) sustained an ICH. In multivariable analysis of 101 participants of European ancestry, APOE ε4 was associated with higher risk of ICH (odds ratio, 4.52; 95% CI, 1.18-19.38; P = .03). Conclusions and Relevance: The results of this cross-sectional study of patients from the UK Biobank and All of Us suggest that information on APOE ε4 status may help identify patients with brain AVM who are at particularly high risk of ICH and that cerebral amyloid angiopathy should be evaluated as a possible mediating mechanism of the observed association.

Time-Dependent Changes in Hematoma Expansion Rate after Supratentorial Intracerebral Hemorrhage and Its Relationship with Neurological Deterioration and Functional Outcome.

BACKGROUND: Hematoma expansion (HE) following an intracerebral hemorrhage (ICH) is a modifiable risk factor and a treatment target. We examined the association of HE with neurological deterioration (ND), functional outcome, and mortality based on the time gap from onset to baseline CT. METHODS: We included 567 consecutive patients with supratentorial ICH and baseline head CT within 24 h of onset. ND was defined as a ≥4-point increase on the NIH stroke scale (NIHSS) or a ≥2-point drop on the Glasgow coma scale. Poor outcome was defined as a modified Rankin score of 4 to 6 at 3-month follow-up. RESULTS: The rate of HE was higher among those scanned within 3 h (124/304, 40.8%) versus 3 to 24 h post-ICH onset (53/263, 20.2%) (p < 0.001). However, HE was an independent predictor of ND (p < 0.001), poor outcome (p = 0.010), and mortality (p = 0.003) among those scanned within 3 h, as well as those scanned 3-24 h post-ICH (p = 0.043, p = 0.037, and p = 0.004, respectively). Also, in a subset of 180/567 (31.7%) patients presenting with mild symptoms (NIHSS ≤ 5), hematoma growth was an independent predictor of ND (p = 0.026), poor outcome (p = 0.037), and mortality (p = 0.027). CONCLUSION: Despite decreasing rates over time after ICH onset, HE remains an independent predictor of ND, functional outcome, and mortality among those presenting >3 h after onset or with mild symptoms.

COVID-19 Infection Is Associated With Poor Outcomes in Patients With Intracerebral Hemorrhage.

BACKGROUND: Patients with ischemic stroke and concomitant COVID-19 infection have worse outcomes than those without this infection, but the impact of COVID-19 on hemorrhagic stroke remains unclear. We aimed to assess if COVID-19 worsens outcomes in intracerebral hemorrhage (ICH). METHODS AND RESULTS: We conducted an observational study of ICH outcomes using Get With The Guidelines Stroke data. We compared patients with ICH who were COVID-19 positive and negative during the pandemic (March 2020-February 2021) and prepandemic (March 2019-February 2020). Main outcomes were poor functional outcome (defined as a modified Rankin scale score of 4 to 6 at discharge), mortality, and discharge to a skilled nursing facility or hospice. The first stage included 60 091 patients with ICH who were COVID-19 negative and 1326 COVID-19 positive. In multivariable analyses, patients with ICH with versus without COVID-19 infection had 68% higher odds of poor outcome (odds ratio [OR], 1.68 [95% CI, 1.41-2.01]), 51% higher odds of mortality (OR, 1.51 [95% CI, 1.33-1.71]), and 66% higher odds of being discharged to a skilled nursing facility/hospice (OR, 1.66 [95% CI, 1.43-1.93]). The second stage included 62 743 prepandemic and 64 681 intrapandemic cases with ICH. In multivariable analyses, patients with ICH admitted during versus before the COVID-19 pandemic had 10% higher odds of poor outcomes (OR, 1.10 [95% CI, 1.07-1.14]), 5% higher mortality (OR, 1.05 [95% CI, 1.02-1.08]), and no significant difference in the risk of being discharged to a skilled nursing facility/hospice (OR, 0.93 [95% CI, 0.90-0.95]). CONCLUSIONS: The pathophysiology of the COVID-19 infection and changes in health care delivery during the pandemic played a role in worsening outcomes in the patient population with ICH.

Association of Poor Oral Health With Neuroimaging Markers of White Matter Injury in Middle-Aged Participants in the UK Biobank.

BACKGROUND AND OBJECTIVES: Poor oral health is a modifiable risk factor that is associated with clinically observed cardiovascular disease. However, the relationship between oral and brain health is not well understood. We tested the hypothesis that poor oral health is associated with worse neuroimaging brain health profiles in middle-aged persons without stroke or dementia. METHODS: We performed a 2-stage cross-sectional neuroimaging study using UK Biobank data. First, we tested for association between self-reported poor oral health and MRI neuroimaging markers of brain health. Second, we used Mendelian randomization (MR) analyses to test for association between genetically determined poor oral health and the same neuroimaging markers. Poor oral health was defined as the presence of dentures or loose teeth. As instruments for the MR analysis, we used 116 independent DNA sequence variants linked to increased composite risk of dentures or teeth that are decayed, missing, or filled. Neuroimaging markers of brain health included white matter hyperintensity (WMH) volume and aggregate measures of fractional anisotropy (FA) and mean diffusivity (MD), 2 metrics indicative of white matter tract disintegrity obtained through diffusion tensor imaging across 48 brain regions. RESULTS: We included 40,175 persons (mean age 55 years, female sex 53%) enrolled from 2006 to 2010, who underwent a dedicated research brain MRI between 2014 and 2016. Among participants, 5,470 (14%) had poor oral health. Poor oral health was associated with a 9% increase in WMH volume (ß = 0.09, SD = 0.014, p < 0.001), 10% change in aggregate FA score (ß = 0.10, SD = 0.013, p < 0.001), and 5% change in aggregate MD score (ß = 0.05, SD = 0.013, p < 0.001). Genetically determined poor oral health was associated with a 30% increase in WMH volume (ß = 0.30, SD = 0.06, p < 0.001), 43% change in aggregate FA score (ß = 0.43, SD = 0.06, p < 0.001), and 10% change in aggregate MD score (ß = 0.10, SD = 0.03, p < 0.01). DISCUSSION: Among middle age Britons without stroke or dementia, poor oral health was associated with worse neuroimaging brain health profiles. Genetic analyses confirmed these associations, supporting a potentially causal association. Because the neuroimaging markers evaluated in this study precede and are established risk factors of stroke and dementia, our results suggest that oral health, an easily modifiable process, may be a promising target for very early interventions focused on improving brain health.

Cerebral Amyloid Angiopathy and Risk of Isolated Nontraumatic Subdural Hemorrhage.

Importance: Cerebral amyloid angiopathy (CAA) is a common cause of spontaneous intracerebral hemorrhage in older patients. Although other types of intracranial hemorrhage can occur in conjunction with CAA-related intracerebral hemorrhage, the association between CAA and other subtypes of intracranial hemorrhage, particularly in the absence of intracerebral hemorrhage, remains poorly understood. Objective: To determine whether CAA is an independent risk factor for isolated nontraumatic subdural hemorrhage (SDH). Design, Setting, and Participants: A population-based cohort study was performed using a 2-stage analysis of prospectively collected data in the UK Biobank cohort (discovery phase, 2006-2022) and the All of Us Research Program cohort (replication phase, 2018-2022). Participants included those who contributed at least 1 year of data while they were older than 50 years, in accordance with the diagnostic criteria for CAA. Participants with prevalent intracranial hemorrhage were excluded. Data were analyzed from October 2022 to October 2023. Exposure: A diagnosis of CAA, identified using the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis code. Main Outcomes and Measures: The outcome was an isolated nontraumatic SDH, identified using ICD-10-CM codes. Two identical analyses were performed separately in the 2 cohorts. First, the risk of SDH in patients with and without CAA was assessed using Cox proportional hazards models, adjusting for demographic characteristics, cardiovascular comorbidities, and antithrombotic medication use. Second, multivariable logistic regression was used to study the association between CAA and SDH. Results: The final analytical sample comprised 487 223 of the total 502 480 individuals in the UK Biobank cohort and 158 008 of the total 372 082 individuals in the All of Us cohort. Among the 487 223 participants in the discovery phase of the UK Biobank, the mean (SD) age was 56.5 (8.1) years, and 264 195 (54.2%) were female. There were 649 cases of incident SDH. Of the 126 participants diagnosed with CAA, 3 (2.4%) developed SDH. In adjusted Cox regression analyses, participants with CAA had an increased risk of having an SDH compared with those without CAA (hazard ratio [HR], 8.0; 95% CI, 2.6-24.8). Multivariable logistic regression analysis yielded higher odds of SDH among participants with CAA (odds ratio [OR], 7.6; 95% CI, 1.8-20.4). Among the 158 008 participants in the All of Us cohort, the mean (SD) age was 63.0 (9.5) years, and 89 639 (56.7%) were female. The findings were replicated in All of Us, in which 52 participants had CAA and 320 had an SDH. All of Us participants with CAA had an increased risk of having an SDH compared with those without CAA (HR, 4.9; 95% CI, 1.2-19.8). In adjusted multivariable logistic regression analysis, CAA was associated with higher odds of SDH (OR, 5.2; 95% CI, 0.8-17.6). Conclusions and Relevance: In 2 large, heterogeneous cohorts, CAA was associated with increased risk of SDH. These findings suggest that CAA may be a novel risk factor for isolated nontraumatic SDH.

Suboptimal Sleep Duration Is Associated With Poorer Neuroimaging Brain Health Profiles in Middle-Aged Individuals Without Stroke or Dementia.

BACKGROUND: The American Heart Association's Life's Simple 7, a public health construct capturing key determinants of cardiovascular health, became the Life's Essential 8 after the addition of sleep duration. The authors tested the hypothesis that suboptimal sleep duration is associated with poorer neuroimaging brain health profiles in asymptomatic middle-aged adults. METHODS AND RESULTS: The authors conducted a prospective magnetic resonance neuroimaging study in middle-aged individuals without stroke or dementia enrolled in the UK Biobank. Self-reported sleep duration was categorized as short (<7 hours), optimal (7-<9 hours), or long (≥9 hours). Evaluated neuroimaging markers included the presence of white matter hyperintensities (WMHs), volume of WMH, and fractional anisotropy, with the latter evaluated as the average of 48 white matter tracts. Multivariable logistic and linear regression models were used to test for an association between sleep duration and these neuroimaging markers. The authors evaluated 39 771 middle-aged individuals. Of these, 28 912 (72.7%) had optimal, 8468 (21.3%) had short, and 2391 (6%) had long sleep duration. Compared with optimal sleep, short sleep was associated with higher risk of WMH presence (odds ratio, 1.11 [95% CI, 1.05-1.18]; P<0.001), larger WMH volume (beta=0.06 [95% CI, 0.04-0.08]; P<0.001), and worse fractional anisotropy profiles (beta=-0.04 [95% CI, -0.06 to -0.02]; P=0.001). Compared with optimal sleep, long sleep duration was associated with larger WMH volume (beta=0.04 [95% CI, 0.01-0.08]; P=0.02) and worse fractional anisotropy profiles (beta=-0.06 [95% CI, -0.1 to -0.02]; P=0.002), but not with WMH presence (P=0.6). CONCLUSIONS: Among middle-aged adults without stroke or dementia, suboptimal sleep duration is associated with poorer neuroimaging brain health profiles. Because these neuroimaging markers precede stroke and dementia by several years, these findings are consistent with other findings evaluating early interventions to improve this modifiable risk factor.

Polygenic Risk of Epilepsy and Post-Stroke Epilepsy.

Background and Aims: Epilepsy is highly heritable, with numerous known genetic risk loci. However, the genetic predisposition's role in post-acute brain injury epilepsy remains understudied. This study assesses whether a higher genetic predisposition to epilepsy raises post-stroke or Transient Ischemic Attack (TIA) survivor's risk of Post-Stroke Epilepsy (PSE). Methods: We conducted a three-stage genetic analysis. First, we identified independent epilepsy-associated ( p <5x10 -8 ) genetic variants from public data. Second, we estimated PSE-specific variant weights in stroke/TIA survivors from the UK Biobank. Third, we tested for an association between a polygenic risk score (PRS) and PSE risk in stroke/TIA survivors from the All of Us Research Program. Primary analysis included all ancestries, while a secondary analysis was restricted to European ancestry only. A sensitivity analysis excluded TIA survivors. Association testing was conducted via multivariable logistic regression, adjusting for age, sex, and genetic ancestry. Results: Among 19,708 UK Biobank participants with stroke/TIA, 805 (4.1%) developed PSE. Likewise, among 12,251 All of Us participants with stroke/TIA, 394 (3.2%) developed PSE. After establishing PSE-specific weights for 39 epilepsy-linked genetic variants in the UK Biobank, the resultant PRS was associated with elevated odds of PSE development in All of Us (OR:1.16[1.02-1.32]). A similar result was obtained when restricting to participants of European ancestry (OR:1.23[1.02-1.49]) and when excluding participants with a TIA history (OR:1.18[1.02-1.38]). Conclusions: Our findings suggest that akin to other forms of epilepsy, genetic predisposition plays an essential role in PSE. Because the PSE data were sparse, our results should be interpreted cautiously.

Polygenic Susceptibility to Hypertension and Cognitive Performance in Middle-aged Persons Without Stroke or Dementia.

BACKGROUND AND OBJECTIVES: Mounting evidence indicates that hypertension leads to a higher risk of dementia. Hypertension is a highly heritable trait, and a higher polygenic susceptibility to hypertension (PSH) is known to associate with a higher risk of dementia. We tested the hypothesis that a higher PSH leads to worse cognitive performance in middle-aged persons without dementia. Confirming this hypothesis would support follow-up research focused on using hypertension-related genomic information to risk-stratify middle-aged adults before hypertension develops. METHODS: We conducted a nested cross-sectional genetic study within the UK Biobank (UKB). Study participants with a history of dementia or stroke were excluded. We categorized participants as having low (≤20th percentile), intermediate, or high (≥80th percentile) PSH according to results of 2 polygenic risk scores for systolic and diastolic blood pressure (BP) generated with data on 732 genetic risk variants. A general cognitive ability score was calculated as the first component of an analysis that included the results of 5 cognitive tests. Primary analyses focused on Europeans, and secondary analyses included all race/ethnic groups. RESULTS: Of the 502,422 participants enrolled in the UKB, 48,118 (9.6%) completed the cognitive evaluation, including 42,011 (8.4%) of European ancestry. Multivariable regression models using systolic BP-related genetic variants indicated that compared with study participants with a low PSH, those with intermediate and high PSH had reductions of 3.9% (ß -0.039, SE 0.012) and 6.6% (ß -0.066, SE 0.014), respectively, in their general cognitive ability score (p < 0.001). Secondary analyses including all race/ethnic groups and using diastolic BP-related genetic variants yielded similar results (p < 0.05 for all tests). Analyses evaluating each cognitive test separately indicated that reaction time, numeric memory, and fluid intelligence drove the association between PSH and general cognitive ability score (all individual tests, p < 0.05). DISCUSSION: Among nondemented, community-dwelling, middle-aged Britons, a higher PSH is associated with worse cognitive performance. These findings suggest that genetic predisposition to hypertension influences brain health in persons who have not yet developed dementia. Because information on genetic risk variants for elevated BP is available long before the development of hypertension, these results lay the foundation for further research focused on using genomic data for the early identification of high-risk middle-aged adults.

Poor Oral Health Is Associated with Worse Brain Imaging Profiles.

Importance: Poor oral health is a modifiable risk factor that is associated with a variety of health outcomes. However, the relationship between oral and brain health is not well understood. Objective: To test the hypothesis that poor oral health is associated with worse neuroimaging brain health profiles in persons without stroke or dementia. Design: We conducted a 2-stage cross-sectional neuroimaging study using data from the UK Biobank (UKB). First, we tested for association between self-reported poor oral health and MRI neuroimaging markers of brain health. Second, we used Mendelian Randomization (MR) analyses to test for association between genetically-determined poor oral health and the same neuroimaging markers. Setting: Ongoing population study in the United Kingdom. The UKB enrolled participants between 2006 and 2010. Data analysis was performed from September 1, 2022, to January 10, 2023. Participants: 40,175 persons aged 40 to 70 enrolled between 2006 to 2010 who underwent a dedicated research brain MRI between 2012 and 2013. Exposures: During MRI assessment, poor oral health was defined as the presence of dentures or loose teeth. As instruments for the MR analysis, we used 116 independent DNA sequence variants known to significantly increase the composite risk of decayed, missing, or filled teeth and dentures. Main Outcomes and Measures: As neuroimaging markers of brain health, we assessed the volume of white matter hyperintensities (WMH), as well as aggregate measures of fractional anisotropy (FA) and mean diffusivity (MD), two metrics indicative of white matter tract disintegrity obtained through diffusion tensor imaging. These measurements were evaluated across 48 distinct brain regions, with FA and MD values for each region also considered as individual outcomes for the MR method. Results: Among study participants, 5,470 (14%) had poor oral health. We found that poor oral health was associated with a 9% increase in WMH volume (beta = 0.09, standard deviation (SD) = 0.014, p P< 0.001), a 10% change in the aggregate FA score (beta = 0.10, SD = 0.013, P < 0.001), and a 5% change in the aggregate MD score (beta = 0.05, SD = 0.013, P < 0.001). Genetically-determined poor oral health was associated with a 30% increase in WMH volume (beta = 0.30, SD = 0.06, P < 0.001), a 43% change in aggregate FA score (beta = 0.42, SD = 0.06, P < 0.001), and an 10% change in aggregate MD score (beta = 0.10, SD = 0.03, P = 0.01). Conclusions and Relevance: Among middle age Britons without stroke or dementia enrolled in a large population study, poor oral health was associated with worse neuroimaging brain health profiles. Genetic analyses confirmed these associations, supporting a potential causal association. Because the neuroimaging markers evaluated in the current study are established risk factors for stroke and dementia, our results suggest that oral health may be a promising target for interventions focused on improving brain health.