Impact of sleep quality and physical activity on blood pressure variability.

Increased blood pressure variability (BPV) is linked to cardiovascular disease and mortality, yet few modifiable BPV risk factors are known. We aimed to assess the relationship between sleep quality and activity level on longitudinal BPV in a cohort of community-dwelling adults (age ≥18) from 17 countries. Using Withings home measurement devices, we examined sleep quality and physical activity over one year, operationalized as mean daily step count and number of sleep interruptions, both transformed into tertiles. The primary study outcome was high BPV, defined as the top tertile of systolic blood pressure standard deviation. Our cohort comprised 29,375 individuals (mean age = 58.6 years) with 127.8±90.1 mean days of measurements. After adjusting for age, gender, country, body mass index, measurement days, mean blood pressure, and total time in bed, the odds ratio of having high BPV for those in the top tertile of sleep interruptions (poor sleep) was 1.37 (95% CI, 1.28-1.47) and 1.44 (95% CI, 1.35-1.54) for those in the lowest tertile of step count (physically inactive). Combining these exposures revealed a significant excess relative risk of 0.20 (95% CI, 0.04-0.35, p = 0.012), confirming their super-additive effect. Comparing individuals with the worst exposure status (lowest step count and highest sleep interruptions, n = 2,690) to those with the most optimal status (highest step count and lowest sleep interruptions, n = 3,531) yielded an odds ratio of 2.01 (95% CI, 1.80-2.25) for high BPV. Our findings demonstrate that poor sleep quality and physical inactivity are associated with increased BPV both independently and super-additively.

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.

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.

Impaired mobility and MRI markers of vascular brain injury: Atherosclerosis Risk in Communities and UK Biobank studies.

Background: Vascular brain injury (VBI) may be an under-recognised contributor to mobility impairment. We examined associations between MRI VBI biomarkers and impaired mobility. Methods: We separately analysed Atherosclerosis Risk in Communities (ARIC) and UK Biobank (UKB) study cohorts. Inclusion criteria were no prevalent clinical stroke, and available brain MRI and balance and gait data. MRI VBI biomarkers were (ARIC: ventricular and white matter hyperintensity (WMH) volumes, non-lacunar and lacunar infarctions, microhaemorrhage; UKB: ventricular, brain and WMH volumes, fractional anisotropy (FA), mean diffusivity (MD), intracellular and isotropic free water volume fractions). Quantitative biomarkers were categorised into tertiles. Mobility impairment outcomes were imbalance and slow walk in ARIC and recent fall and slow walk in UKB. Adjusted multivariable logistic regression analyses were performed. Results: We included 1626 ARIC (mean age 76.2 years; 23.4% imbalance, 25.0% slow walk) and 40 098 UKB (mean age 55 years; 15.8% falls, 2.8% slow walk) participants. In ARIC, imbalance associated with four of five VBI measures (all p values<0.05), most strongly with WMH (adjusted OR, aOR 1.64; 95% CI 1.18 to 2.29). Slow walk associated with four of five VBI measures, most strongly with WMH (aOR 2.32; 95% CI 1.66 to 3.24). In UKB, falls associated with all VBI measures except WMH, most strongly with FA (aOR 1.16; 95% CI 1.08 to 1.24). Slow walking associated with WMH, FA and MD, most strongly with FA (aOR 1.57; 95% CI 1.32 to 1.87). Conclusions: VBI is associated with mobility impairment in community-dwelling, clinically stroke-free cohorts. Consequences of VBI may extend beyond clinically apparent stroke to include mobility.

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.

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.

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.

The predictive validity of a Brain Care Score for dementia and stroke: data from the UK Biobank cohort.

Introduction: The 21-point Brain Care Score (BCS) was developed through a modified Delphi process in partnership with practitioners and patients to promote behavior changes and lifestyle choices in order to sustainably reduce the risk of dementia and stroke. We aimed to assess the associations of the BCS with risk of incident dementia and stroke. Methods: The BCS was derived from the United Kingdom Biobank (UKB) baseline evaluation for participants aged 40-69 years, recruited between 2006-2010. Associations of BCS and risk of subsequent incident dementia and stroke were estimated using Cox proportional hazard regressions, adjusted for sex assigned at birth and stratified by age groups at baseline. Results: The BCS (median: 12; IQR:11-14) was derived for 398,990 UKB participants (mean age: 57; females: 54%). There were 5,354 incident cases of dementia and 7,259 incident cases of stroke recorded during a median follow-up of 12.5 years. A five-point higher BCS at baseline was associated with a 59% (95%CI: 40-72%) lower risk of dementia among participants aged <50. Among those aged 50-59, the figure was 32% (95%CI: 20-42%) and 8% (95%CI: 2-14%) for those aged >59 years. A five-point higher BCS was associated with a 48% (95%CI: 39-56%) lower risk of stroke among participants aged <50, 52% (95%CI, 47-56%) among those aged 50-59, and 33% (95%CI, 29-37%) among those aged >59. Discussion: The BCS has clinically relevant and statistically significant associations with risk of dementia and stroke in approximately 0.4 million UK people. Future research includes investigating the feasibility, adaptability and implementation of the BCS for patients and providers worldwide.

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.

Suboptimal Sleep Duration is Associated with Poorer Neuroimaging Brain Health Profiles.

Background: Cardiovascular health optimization during middle age benefits brain health. The American Heart Association's Life's Simple 7 recently added sleep duration as a key determinant of cardiovascular health becoming the Life's Essential 8. We tested the hypothesis that suboptimal sleep duration is associated with poorer neuroimaging brain health profiles in asymptomatic middle-aged adults. Methods: We conducted a prospective MRI neuroimaging study in middle-aged persons without stroke, dementia, or multiple sclerosis 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 of brain health included white matter hyperintensities (presence and volume) and diffusion tensor imaging metrics (fractional anisotropy and mean diffusivity) evaluated in 48 distinct neuroanatomical regions. We used multivariable logistic and linear regression models, as appropriate, to test for association between sleep duration and neuroimaging markers of brain health. Results: We evaluated 39,502 middle-aged persons (mean age 55, 53% female). Of these, 28,712 (72.7%) had optimal, 8,422 (21.3%) short, and 2,368 (6%) long sleep. Compared to optimal sleep, short sleep was associated with higher risk (OR 1.11; 95% CI 1.05-1.17; P<0.001) and larger volume (beta=0.06, SE=0.01; P<0.001) of white matter hyperintensities, while long sleep was associated with higher volume (beta=0.04, SE=0.02; P=0.01) but not higher risk (P>0.05) of white matter hyperintensities. Short (beta=0.03, SE=0.01; P=0.004) and long sleep (beta=0.07, SE=0.02; P<0.001) were associated with worse fractional anisotropy, while only long sleep associated with worse mean diffusivity (beta=0.05, SE=0.02; P=0.005). Conclusions: Among middle-aged adults without clinically observed neurological disease, suboptimal sleep duration is associated with poorer neuroimaging brain health profiles. Because the evaluated neuroimaging markers precede stroke and dementia by several years, our findings support early interventions aimed at correcting this modifiable risk factor.

Higher Hospital Frailty Risk Score Is Associated With Increased Risk of Stroke: Observational and Genetic Analyses.

BACKGROUND: Frailty is a prevalent state associated with several aging-related traits and conditions. The relationship between frailty and stroke remains understudied. Here we aim to investigate whether the hospital frailty risk score (HFRS) is associated with the risk of stroke and determine whether a significant association between genetically determined frailty and stroke exists. DESIGN: Observational study using data from All of Us research program and Mendelian Randomization analyses. METHODS: Participants from All of Us with available electronic health records were selected for analysis. All of Us began national enrollment in 2018 and is expected to continue for at least 10 years. All of Us is recruiting members of groups that have traditionally been underrepresented in research. All participants provided informed consent at the time of enrollment, and the date of consent was recorded for each participant. Incident stroke was defined as stroke event happening on or after the date of consent to the All of Us study HFRS was measured with a 3-year look-back period before the date of consent for stroke risk. The HFRS was stratified into 4 categories: no-frailty (HFRS=0), low (HFRS ≥1 and <5), intermediate (≥5 and <15), and high (HFRS ≥15). Last, we implemented Mendelian Randomization analyses to evaluate whether genetically determined frailty is associated with stroke risk. RESULTS: Two hundred fifty-three thousand two hundred twenty-six participants were at risk of stroke. In multivariable analyses, frailty status was significantly associated with risk of any (ischemic or hemorrhagic) stroke following a dose-response way: not-frail versus low HFRS (HR, 4.9 [CI, 3.5-6.8]; P<0.001), not-frail versus intermediate HFRS (HR, 11.4 [CI, 8.3-15.7]; P<0.001) and not-frail versus high HFRS (HR, 42.8 [CI, 31.2-58.6]; P<0.001). We found similar associations when evaluating ischemic and hemorrhagic stroke separately (P value for all comparisons <0.05). Mendelian Randomization confirmed this association by indicating that genetically determined frailty was independently associated with risk of any stroke (OR, 1.45 [95% CI, 1.15-1.84]; P=0.002). CONCLUSIONS: Frailty, based on the HFRS was associated with higher risk of any stroke. Mendelian Randomization analyses confirmed this association providing evidence to support a causal relationship.

Blood pressure-related white matter microstructural disintegrity and associated cognitive function impairment in asymptomatic adults.

BACKGROUND AND OBJECTIVES: We aimed to investigate the white matter (WM) microstructural/cytostructural disintegrity patterns related to higher systolic blood pressure (SBP), and whether they mediate SBP effects on cognitive performance in middle-aged adults. METHODS: Using the UK Biobank study of community-dwelling volunteers aged 40-69 years, we included participants without a history of stroke, dementia, demyelinating disease or traumatic brain injury. We investigated the association of SBP with MRI diffusion metrics: fractional anisotropy (FA), mean diffusivity (MD), intracellular volume fraction (a measure of neurite density), isotropic (free) water volume fraction (ISOVF) and orientation dispersion across WM tracts. Then, we determined whether WM diffusion metrics mediated the effects of SBP on cognitive function. RESULTS: We analysed 31 363 participants-mean age of 63.8 years (SD: 7.7), and 16 523 (53%) females. Higher SBP was associated with lower FA and neurite density, but higher MD and ISOVF. Among different WM tracts, diffusion metrics of the internal capsule anterior limb, external capsule, superior and posterior corona radiata were most affected by higher SBP. Among seven cognitive metrics, SBP levels were only associated with 'fluid intelligence' (adjusted p<0.001). In mediation analysis, the averaged FA of external capsule, internal capsule anterior limb and superior cerebellar peduncle mediated 13%, 9% and 13% of SBP effects on fluid intelligence, while the averaged MD of external capsule, internal capsule anterior and posterior limbs, and superior corona radiata mediated 5%, 7%, 7% and 6% of SBP effects on fluid intelligence, respectively. DISCUSSION: Among asymptomatic adults, higher SBP is associated with pervasive WM microstructure disintegrity, partially due to reduced neuronal count, which appears to mediate SBP adverse effects on fluid intelligence. Diffusion metrics of select WM tracts, which are most reflective of SBP-related parenchymal damage and cognitive impairment, may serve as imaging biomarkers to assess treatment response in antihypertensive trials.

Prediction of post-stroke motor recovery benefits from measures of sub-acute widespread network damages.

Following a stroke in regions of the brain responsible for motor activity, patients can lose their ability to control parts of their body. Over time, some patients recover almost completely, while others barely recover at all. It is known that lesion volume, initial motor impairment and cortico-spinal tract asymmetry significantly impact motor changes over time. Recent work suggested that disabilities arise not only from focal structural changes but also from widespread alterations in inter-regional connectivity. Models that consider damage to the entire network instead of only local structural alterations lead to a more accurate prediction of patients' recovery. However, assessing white matter connections in stroke patients is challenging and time-consuming. Here, we evaluated in a data set of 37 patients whether we could predict upper extremity motor recovery from brain connectivity measures obtained by using the patient's lesion mask to introduce virtual lesions in 60 healthy streamline tractography connectomes. This indirect estimation of the stroke impact on the whole brain connectome is more readily available than direct measures of structural connectivity obtained with magnetic resonance imaging. We added these measures to benchmark structural features, and we used a ridge regression regularization to predict motor recovery at 3 months post-injury. As hypothesized, accuracy in prediction significantly increased (R 2 = 0.68) as compared to benchmark features (R 2 = 0.38). This improved prediction of recovery could be beneficial to clinical care and might allow for a better choice of intervention.

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.

Analysis of Clinical Traits Associated With Cardiovascular Health, Genomic Profiles, and Neuroimaging Markers of Brain Health in Adults Without Stroke or Dementia.

Importance: The American Heart Association (AHA) Life's Simple 7 (LS7) score captures 7 biological and lifestyle factors associated with promoting cardiovascular health. Objectives: To test whether healthier LS7 profiles are associated with significant brain health benefits in persons without stroke or dementia, and to evaluate whether genomic information can recapitulate the observed LS7. Design, Setting, and Participants: This genetic association study was a nested neuroimaging study within the UK Biobank, a large population-based cohort study in the United Kingdom. Between March 2006 and October 2010, the UK Biobank enrolled 502 480 community-dwelling persons aged 40 to 69 years at recruitment. This study focused on a subset of 35 914 participants without stroke or dementia who completed research brain magnetic resonance imaging (MRI) and had available genome-wide data. All analyses were conducted between March 2021 and March 2022. Exposures: The LS7 (blood pressure, low-density lipoprotein cholesterol, hemoglobin A1c, smoking, exercise, diet, and body mass index) profiles were ascertained clinically and genomically. Independent genetic variants known to influence each of the traits included in the LS7 were assessed. The total LS7 score ranges from 0 (worst) to 14 (best) and was categorized as poor (≤4), average (>4 to 9) and optimal (>9). Main Outcomes and Measures: The outcomes of interest were 2 neuroimaging markers of brain health: white matter hyperintensity (WMH) volume and brain volume (BV). Results: The final analytical sample included 35 914 participants (mean [SD] age 64.1 [7.6] years; 18 830 [52.4%] women). For WMH, compared with persons with poor observed LS7 profiles, those with average profiles had 16% (ß = -0.18; SE, 0.03; P < .001) lower mean volume and those with optimal profiles had 39% (ß = -0.39; SE, 0.03; P < .001) lower mean volume. Similar results were obtained using the genomic LS7 for WMH (average LS7 profile: ß = -0.06; SE, 0.014; P < .001; optimal LS7 profile: ß = -0.08; SE, 0.018; P < .001). For BV, compared with persons with poor observed LS7 profiles, those with average LS7 profiles had 0.55% (ß = 0.09; SE, 0.02; P < .001) higher volume, and those with optimal LS7 profiles had 1.9% (ß = 0.14; SE, 0.02; P < .001) higher volume. The genomic LS7 profiles were not associated with BV. Conclusions and Relevance: These findings suggest that healthier LS7 profiles were associated with better profiles of 2 neuroimaging markers of brain health in persons without stroke or dementia, indicating that cardiovascular health optimization was associated with improved brain health in asymptomatic persons. Genomic information appropriately recapitulated 1 of these associations, confirming the feasibility of modeling the LS7 genomically and pointing to an important role of genetic predisposition in the observed association among cardiometabolic and lifestyle factors and brain health.