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BackgroundPatients with ischemic stroke and concomitant coronavirus 2019 (COVID-19) infection have worse outcomes than those without this infection. However, research on the impact of COVID-19 infection on outcomes following hemorrhagic stroke remains limited. We aim to study whether concomitant COVID-19 infection leads to worse outcomes in spontaneous intracerebral hemorrhage (ICH).DesignWe conducted an observational study using data from Get With The Guidelines® Stroke, an ongoing, multi-center, nationwide quality assurance registry.MethodsWe implemented a two-stage design: first, we compared outcomes of ICH patients with and without COVID-19 infection admitted during the pandemic (from March 2020 to February 2021). Second, we compared the same outcomes between ICH patients admitted before (March 2019 to February 2020) and during (March 2020 and February 2021) the pandemic. Main outcomes were poor functional outcome (defined as a modified Rankin Scale of 4 to 6 [mRS] at discharge), mortality and discharge to skilled nursing facility (SNF) or hospice.ResultsThe first stage included 60,091 COVID-19-negative and 1,326 COVID-19-positive ICH patients. In multivariable analyses, ICH patients with versus without COVID-19 infection had 68% higher odds of poor outcome (OR 1.68, 95%CI 1.41-2.01), 51% higher odds of mortality (OR 1.51, CI 1.33-1.71) and 66% higher odds of being discharged to a SNF/hospice (OR 1.66, 95%CI 1.43-1.93). The second stage included 62,743 pre-pandemic and 64,681 intra-pandemic ICH cases. In multivariable analyses, ICH patients admitted during versus before the COVID-19 pandemic had a 10% higher odds of poor outcome (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 SNF/hospice (OR 0.93, 95%CI 0.90-0.95).ConclusionsThe pathophysiology of the COVID-19 infection and changes in healthcare delivery during the pandemic played a role in worsening outcomes in this patient population. Further research is needed to identify these factors and understand their effect on the long-term outcome.

BackgroundCardiovascular 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.MethodsWe 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 (ResultsWe 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; P0.05) of white matter hyperintensities. Short (beta=0.03, SE=0.01; P=0.004) and long sleep (beta=0.07, SE=0.02; PConclusionsAmong 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.

ObjectiveGenome-wide association studies have identified1q22as a susceptibility locus for cerebral small vessel diseases (CSVDs), including non-lobar intracerebral hemorrhage (ICH) and lacunar stroke. In the present study we performed targeted high-depth sequencing of1q22in ICH cases and controls to further characterize this locus and prioritize potential causal mechanisms, which remain unknown.Methods95,000 base pairs spanning1q22, includingSEMA4A, SLC25A44andPMF1/PMF1-BGLAPwere sequenced in 1,055 spontaneous ICH cases (534 lobar and 521 non-lobar) and 1,078 controls. Firth regression and RIFT analysis were used to analyze common and rare variants, respectively. Chromatin interaction analyses were performed using Hi-C, ChIP-Seq and ChIA-PET databases. Multivariable Mendelian randomization (MVMR) assessed whether alterations in gene-specific expression relative to regionally co-expressed genes at1q22could be causally related to ICH risk.ResultsCommon and rare variant analyses prioritized variants inSEMA4A5’-UTR andPMF1intronic regions, overlapping with active promoter and enhancer regions based on ENCODE annotation. Hi-C data analysis determined that1q22is spatially organized in a single chromatin loop and that the genes therein belong to the same Topologically Associating Domain. ChIP-Seq and ChIA-PET data analysis highlighted the presence of long-range interactions between theSEMA4A-promoter andPMF1-enhancer regions prioritized by association testing. MVMR analyses demonstrated thatPMF1overexpression could be causally related to non-lobar ICH risk.InterpretationAltered promoter-enhancer interactions leading toPMF1overexpression, potentially dysregulating polyamine catabolism, could explain demonstrated associations with non-lobar ICH risk at1q22, offering a potential new target for prevention of ICH and CSVD.

ImportancePoor 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.ObjectiveTo test the hypothesis that poor oral health is associated with worse neuroimaging brain health profiles in persons without stroke or dementia.DesignWe 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.SettingOngoing 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.Participants40,175 persons aged 40 to 70 enrolled between 2006 to 2010 who underwent a dedicated research brain MRI between 2012 and 2013.ExposuresDuring 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 MeasuresAs 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.ResultsAmong 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 RelevanceAmong 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.

BackgroundMounting evidence indicates that hypertension leads to higher risk of cognitive decline and dementia. Hypertension is a highly heritable trait and a higher polygenic susceptibility to hypertension (PSH) is known to be associated with higher risk of dementia. We tested the hypothesis that a higher PSH leads to worse cognitive performance in middle-aged persons without dementia.MethodsWe conducted a nested, cross-sectional, genetic study within the UK Biobank, a large population study that enrolled middle-aged Britons. Study participants with a history of dementia or stroke were excluded. We categorized participants as having low (≤20th percentile), intermediate (>20th and th percentile), or high (≥80th percentile) PSH according to results of 2 polygenic risk scores for systolic and diastolic blood pressure (BP), generated with genomic data on 732 genetic risk variants for these traits. Cognitive performance was evaluated via 5 simple tests: Pairs Memory, Reaction Time, Numeric Memory, Prospective Memory and Fluid Intelligence. A general cognitive ability score was calculated as the first principal component of a principal component analysis that included the results of these 5 tests. Primary analyses focused on Europeans and secondary analyses included all race/ethnic groups.ResultsOut of 409,551 study participants of European ancestry with available genomic data, 42,080 (10.3%) completed all 5 tests. Multivariable regression models using systolic BP-related genetic variants indicated that, compared to study participants with low PSH, those with intermediate and high PSH had reductions of 3.9% (beta -0.039, SE 0.012) and 6.6% (beta - 0.066, SE 0.014), respectively, in their general cognitive ability score (test for trend p ConclusionsAmong non-demented, community-dwelling, middle-aged Britons, a higher PSH is associated with worse cognitive performance. These findings suggest the genetic predisposition to hypertension influence brain health in persons who have not yet developed dementia.

Ischemic stroke (IS) is a highly heritable trait. Genome-wide association studies have identified several commonly occurring susceptibility risk loci for this condition. However, there are limited data on the contribution of rare genetic variation to IS. We conducted a whole-exome association study of IS in 152,058 UK Biobank participants (mean age 57, 6.8 [SD 8.0], 83,131 [54.7%] were females), including 1,777 IS cases (mean age 61.4 [SD 6.6], 666 [37.5%] were females). We performed single-variant analyses for all variants and gene-based analyses for loss of function and deleterious missense rare variants. In the gene-based analysis, rare genetic variation at CYP2R1 was significantly associated with IS risk (P=2.6×10−6), exceeding the Bonferroni-corrected threshold for 16,074 tests (P−6). We first replicated these findings using summary statistics from a genome-wide association study that included 67,162 IS cases and 454,450 controls (gene-based test for CYP2R1, P=0.003). We pursued a second replication focused on IS recurrence using individual-level data from 1,706 IS survivors, including 142 cases of recurrent IS, enrolled in the VISP trial (gene-based test for CYP2R1, P=0.001). We also found that common genetic variation at CYP2R1 was associated with white matter hyperintensity volume (42,310 participants) and both mean diffusivity and fractional anisotropy (17,663 participants) in the subcohort of UK Biobank (all gene-based tests PCYP2R1 plays an important role in vitamin D metabolism, our results support a role of this pathway in the occurrence of ischemic cerebrovascular disease.

BackgroundIntracerebral hemorrhage (ICH), the most fatal form of stroke, has an estimated heritability of 29%. Applying a meta-scoring approach, we developed a genomic risk score for ICH and determined its predictive power in comparison to standard clinical risk factors.MethodsUsing a meta-analytic approach, we combined genome-wide association data from individuals of European ancestry for ICH and ICH-related traits in a meta-genomic risk score (metaGRS) consisting of 2.6 million variants. We tested associations with ICH and the predictive performance of the metaGRS in addition to clinical risk factors in a held-out validation dataset (842 cases and 796 controls). Furthermore, we tested associations with risk of incident ICH in the population-based UK Biobank cohort (486,784 individuals, 1,526 events, median follow-up 11.3 years).ResultsOne SD increment in the metaGRS was significantly associated with 45% higher odds for ICH (OR 1.45; 95%CI: 1.30-1.63) in age- and sex-adjusted models and 31% higher odds for ICH (OR: 1.31, 95%CI: 1.16-1.48) in models further adjusted for clinical risk factors. The metaGRS identified individuals with almost 5-fold higher odds for ICH in the top score percentile (OR: 4.83, 95%CI: 1.56-21.2). Predictive models for ICH incorporating the metaGRS in addition to clinical predictors showed superior performance compared with clinical risk factors alone (c-index: 0.695 vs. 0.686). The metaGRS showed similar associations for both lobar and non-lobar ICH, which were independent of the known APOE risk locus for lobar ICH. In the UK Biobank, the metaGRS was associated with higher risk of incident ICH (HR: 1.15, 95%CI: 1.09-1.21). The associations were significant within both a relatively high-risk population of users of antithrombotic medications, as well as among a relatively low-risk population with a good control of vascular risk factors and no use of anticoagulants.ConclusionsWe developed and validated a genomic risk score that predicts lifetime risk of ICH beyond established clinical risk factors among individuals of European ancestry. Whether implementation of the score in risk prognostication models for high-risk populations, such as patients under antithrombotic treatment, could improve clinical decision making should be explored in future studies.

BackgroundGenome-wide association studies have identified multiple loci associated with stroke. However, the specific stroke subtypes affected, and whether loci influence both ischaemic and haemorrhagic stroke, remains unknown. For loci associated with stroke, we aimed to infer the combination of stroke subtypes likely to be affected, and in doing so assess the extent to which such loci have homogeneous effects across stroke subtypes.MethodsWe performed Bayesian multinomial regression in 16,664 stroke cases and 32,792 controls of European ancestry to determine the most likely combination of stroke subtypes affected for loci with published genome-wide stroke associations, using model selection. Cases were subtyped under two commonly used stroke classification systems, Trial of Org 10172 Acute Stroke Treatment (TOAST) and Causative Classification of Stroke (CCS). All individuals had genotypes imputed to the Haplotype Reference Consortium 1.1 Panel.ResultsSixteen loci were considered for analysis. Seven loci influenced both haemorrhagic and ischaemic stroke, three of which influenced ischaemic and haemorrhagic subtypes under both TOAST and CCS. Under CCS, 4 loci influenced both small vessel stroke and intracerebral haemorrhage. An EDNRA locus demonstrated opposing effects on ischaemic and haemorrhagic stroke. No loci were predicted to influence all stroke subtypes in the same direction and only one locus (12q24) was predicted to influence all ischaemic stroke subtypes.ConclusionsHeterogeneity in the influence of stroke-associated loci on stroke subtypes is pervasive, reflecting differing causal pathways. However, overlap exists between haemorrhagic and ischaemic stroke, which may reflect shared pathobiology predisposing to small vessel arteriopathy. Stroke is a complex, heterogeneous disorder requiring tailored analytic strategies to decipher genetic mechanisms.

Disorders of the brain exhibit considerable epidemiological comorbidity and frequently share symptoms, provoking debate about the extent of their etiologic overlap. Here we apply linkage disequilibrium score regression (LDSC) to quantify the extent of shared genetic contributions across 23 brain disorders (n=842,820), 11 quantitative and four dichotomous traits of interest (n=722,125) based on genome-wide association meta-analyses. Psychiatric disorders show substantial sharing of common variant risk, while many neurological disorders appear more distinct from one another, suggesting substantive differences in the specificity of the genetic etiology of these disorders. Further, we observe little evidence of widespread sharing of the common genetic risk between neurological and psychiatric disorders studied. In addition, we identify significant sharing of genetic influences between the certain quantitative measures and brain disorders, including major depressive disorder and neuroticism personality score. These results highlight the importance of common genetic variation as a source of risk for brain disorders and the potential of using heritability methods to obtain a more comprehensive view of the genetic architecture of brain phenotypes.