18 research outputs found

    Schools as a Framework for COVID-19 Epidemiological Surveillance of Children in Catalonia, Spain: A Population-Based Study

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    COVID-19; Niño; EscuelasCOVID-19; Nen; EscolesCOVID-19; Child; SchoolsObjective: We describe and analyze the childhood (<18 years) COVID-19 incidence in Catalonia, Spain, during the first 36 weeks of the 2020-2021 school-year and to compare it with the incidence in adults. Methods: Data on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) tests were obtained from the Catalan Agency for Quality and Health Assessment. Overall, 7,203,663 SARS-CoV-2 tests were performed, of which 491,819 were positive (6.8%). We collected epidemiological data including age-group incidence, diagnostic effort, and positivity rate per 100,000 population to analyze the relative results for these epidemiological characteristics. Results: Despite a great diagnostic effort among children, with a difference of 1,154 tests per 100,000 population in relation to adults, the relative incidence of SARS-CoV-2 for <18 years was slightly lower than for the general population, and it increased with the age of the children. Additionally, positivity of SARS-CoV-2 in children (5.7%) was lower than in adults (7.2%), especially outside vacation periods, when children were attending school (4.9%). Conclusions: A great diagnostic effort, including mass screening and systematic whole-group contact tracing when a positive was detected in the class group, was associated with childhood SARS-CoV-2 incidence and lower positivity rate in the 2020-2021 school year. Schools have been a key tool in epidemiological surveillance rather than being drivers of SARS-CoV-2 incidence in Catalonia, Spain.This study was partially supported by the Direcció General de Recerca i Innovació en Salut (DGRIS), Catalan Health Ministry, Generalitat de Catalunya through Vall d'Hebron Research Institute (VHIR)

    Increased COVID-19 mortality in people with previous cerebrovascular disease: a population-based cohort study

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    Coronavirus SARS-CoV-2; COVID-19; 2019-nCoV; Ictus hemorràgic; Ictus isquèmic; Hemorràgia subaracnoideaCoronavirus SARS-CoV-2; COVID-19; 2019-nCoV; Ictus hemorrágico; Ictus isquémico; Hemorragia subaracnoideaCoronavirus SARS-CoV-2; COVID-19; 2019-nCoV; Hemorrhagic stroke; Ischemic stroke; Subarachnoid hemorrhageBackground: The aim of the study was to determine the association between previous stroke and mortality after coronavirus disease 2019 (COVID-19) according to sex, age groups, and stroke subtypes. Methods: Prospective population-based cohort study including all COVID-19 positive cases between February 1 and July 31, 2020. Comorbidities and mortality were extracted using linked health administration databases. Previous stroke included transient ischemic attack, ischemic stroke, hemorrhagic stroke, spontaneous subarachnoid hemorrhage, and combined stroke for cases with more than one category. Other comorbidities were obesity, diabetes, hypertension, ischemic heart disease, atrial fibrillation, heart failure, chronic obstructive pulmonary disease, chronic kidney disease, cirrhosis, dementia, individual socioeconomic index, and deprivation index. Cases were followed up until December 31, 2020. Primary outcome was mortality of any cause after COVID-19 positivity. Cox proportional regression analysis adjusted for comorbidities was used. Stratified analyses were performed for sex and age (<60, 60-79, and ≥80 years). Results: There were 91 629 COVID-19 cases. Previous strokes were 5752 (6.27%), of which 3887 (67.57%) were ischemic, 1237 (21.50%) transient ischemic attack, 255 (4.43%) combined, 203 (3.53%) hemorrhagic, and 170 (2.96%) subarachnoid hemorrhage. There were 9512 deaths (10.38%). Mortality was associated with previous stroke (hazard ratio [HR]=1.12 [95% CI, 1.06-1.18]; P<0.001), in both sexes separately (men=1.13 [1.05-1.22]; P=0.001; women=1.09 [1.01-1.18]; P=0.023), in people <60 years (HR=2.97 [1.97-4.48]; P<0.001) and 60 to 79 years (HR=1.32 [1.19-1.48]; P<0.001) but not in people ≥80 years (HR=1.02 [0.96-1.09]; P=0.437). Ischemic (HR=1.11 [1.05-1.18]; P=0.001), hemorrhagic (HR=1.53 [1.20-1.96]; P=0.001) and combined (HR=1.31 [1.05-1.63]; P=0.016) strokes were associated but not transient ischemic attack. Subarachnoid hemorrhage was associated only in people <60 years (HR=5.73 [1.82-18.06]; P=0.003). Conclusions: Previous stroke was associated with a higher mortality in people younger than 80 years. The association occurred for both ischemic and hemorrhagic stroke but not for transient ischemic attack. These data might help healthcare authorities to establish prioritization strategies for COVID-19 vaccination.This work was supported, in part, by Spain’s Ministry of Health (Instituto de Salud Carlos III FEDER, RD16/0019/0002 and RD16/0019/0010 INVICTUS-PLUS

    Age-dependency of the propagation rate of coronavirus disease 2019 inside school bubble groups in Catalonia, Spain

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    We analyzed contagions of coronavirus disease 2019 inside school bubble groups in Catalonia, Spain, in the presence of strong nonpharmaceutical interventions from September to December 2020. More than 1 million students were organized in bubble groups and monitored and analyzed by the Health and the Educational departmentPostprint (published version

    Machine learning approximations to predict epigenetic age acceleration in stroke patients

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    Age acceleration (Age-A) is a useful tool that is able to predict a broad range of health outcomes. It is necessary to determine DNA methylation levels to estimate it, and it is known that Age-A is influenced by environmental, lifestyle, and vascular risk factors (VRF). The aim of this study is to estimate the contribution of these easily measurable factors to Age-A in patients with cerebrovascular disease (CVD), using different machine learning (ML) approximations, and try to find a more accessible model able to predict Age-A. We studied a CVD cohort of 952 patients with information about VRF, lifestyle habits, and target organ damage. We estimated Age-A using Hannum\u27s epigenetic clock, and trained six different models to predict Age-A: a conventional linear regression model, four ML models (elastic net regression (EN), K-Nearest neighbors, random forest, and support vector machine models), and one deep learning approximation (multilayer perceptron (MLP) model). The best-performing models were EN and MLP; although, the predictive capability was modest (

    Identification of 20 novel loci associated with ischaemic stroke. Epigenome-wide association study

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    DNA methylation is dynamic, varies throughout the life course, and its levels are influenced by lifestyle and environmental factors, as well as by genetic variation. The leading genetic variants at stroke risk loci identified to date explain roughly 1–2% of stroke heritability. Most of these single nucleotide polymorphisms are situated within a regulatory sequence marked by DNase I hypersensitivity sites, which would indicate involvement of an epigenetic mechanism. To detect epigenetic variants associated with stroke occurrence and stroke subtypes. A two-stage case–control epigenome-wide association study was designed. The discovery sample with 401 samples included 218 ischaemic stroke (IS) patients, assessed at Hospital del Mar (Barcelona, Spain) and 183 controls from the REGICOR cohort. In two independent samples (N = 226 and N = 166), we replicated 22 CpG sites differentially methylated in IS in 21 loci, including 2 CpGs in locus ZFHX3, which includes known genetic variants associated with stroke. The pathways associated with these loci are inflammation and angiogenesis. The meta-analysis identified 384 differentially methylated CpGs, including loci of known stroke and vascular risk genetic variants, enriched by loci involved in lipid metabolism, adipogenesis, circadian clock, and glycolysis pathways. We identified a set of 22 CpGs in 21 loci associated with IS. Our analysis suggests that DNA methylation changes may contribute to orchestrating gene expression that contributes to IS

    The copy number variation and stroke (CaNVAS) risk and outcome study

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    Background and purpose: The role of copy number variation (CNV) variation in stroke susceptibility and outcome has yet to be explored. The Copy Number Variation and Stroke (CaNVAS) Risk and Outcome study addresses this knowledge gap. Methods: Over 24,500 well-phenotyped IS cases, including IS subtypes, and over 43,500 controls have been identified, all with readily available genotyping on GWAS and exome arrays, with case measures of stroke outcome. To evaluate CNV-associated stroke risk and stroke outcome it is planned to: 1) perform Risk Discovery using several analytic approaches to identify CNVs that are associated with the risk of IS and its subtypes, across the age-, sex- and ethnicity-spectrums; 2) perform Risk Replication and Extension to determine whether the identified stroke-associated CNVs replicate in other ethnically diverse datasets and use biomarker data (e.g. methylation, proteomic, RNA, miRNA, etc.) to evaluate how the identified CNVs exert their effects on stroke risk, and lastly; 3) perform outcome-based Replication and Extension analyses of recent findings demonstrating an inverse relationship between CNV burden and stroke outcome at 3 months (mRS), and then determine the key CNV drivers responsible for these associations using existing biomarker data. Results: The results of an initial CNV evaluation of 50 samples from each participating dataset are presented demonstrating that the existing GWAS and exome chip data are excellent for the planned CNV analyses. Further, some samples will require additional considerations for analysis, however such samples can readily be identified, as demonstrated by a sample demonstrating clonal mosaicism. Conclusion: The CaNVAS study will cost-effectively leverage the numerous advantages of using existing case-control data sets, exploring the relationships between CNV and IS and its subtypes, and outcome at 3 months, in both men and women, in those of African and European-Caucasian descent, this, across the entire adult-age spectrum

    Air pollution and surrounding greenness in relation to ischemic stroke: A population-based cohort study

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    Background: Evidence for the association between environmental exposures and ischemic stroke (IS) is limited and inconsistent. We aimed to assess the relationship between exposure to air pollutants, residential surrounding greenness, and incident IS, and to identify population subgroups particularly sensitive to these exposures. Methods: We used data from administrative health registries of the public healthcare system in Catalonia, Spain to construct a cohort of individuals aged 18 years and older without a previous stroke diagnosis at 1st January 2016 (n = 3 521 274). We collected data on sociodemographic characteristics and cerebrovascular risk factors, and derived exposure at the participant's residence to ambient levels of fine particulate matter (PM2.5), black carbon (BC), nitrogen dioxide (NO2), and Normalized Difference Vegetation Index (NDVI) in a 300 m buffer as an indicator of greenness. The primary outcome was IS diagnosis at any point during the follow-up. We used Cox proportional hazards models to estimate associations between environmental exposures and incident IS and stratified analyses to investigate effect modification. Results: Between 1st January 2016 and 31st December 2017, 10 865 individuals were admitted to public hospitals with an IS diagnosis. Median exposure levels were: 17 µg/m3 PM2.5, 35 µg/m3 NO2, 2.28 µg/m3 BC and 0.27 NDVI. Individuals with higher residential exposure to air pollution were at greater risk of IS: HR 1·04 (95% CI:0·99-1·10) per 5 µg/m3 of PM2.5; HR 1.05 (95% CI:1·00-1·10) per 1 µg/m3 of BC; HR 1·04 (95% CI:1·03-1·06) per 10 µg/m3 of NO2. Conversely, individuals with higher residential surrounding green space, had lower risk of IS (HR 0·84; CI 95%:0·7-1.0). There was no evidence of effect modification by individual characteristics. Conclusions: Higher incidence of IS was observed in relation to long-term exposures to air pollution, particularly NO2, in a region that meets European health-based air quality standards. Residential surrounding greenness was associated with lower incidence of IS

    Identification of 20 novel loci associated with ischaemic stroke. Epigenome-wide association study.

    No full text
    DNA methylation is dynamic, varies throughout the life course, and its levels are influenced by lifestyle and environmental factors, as well as by genetic variation. The leading genetic variants at stroke risk loci identified to date explain roughly 1-2% of stroke heritability. Most of these single nucleotide polymorphisms are situated within a regulatory sequence marked by DNase I hypersensitivity sites, which would indicate involvement of an epigenetic mechanism. To detect epigenetic variants associated with stroke occurrence and stroke subtypes. A two-stage case-control epigenome-wide association study was designed. The discovery sample with 401 samples included 218 ischaemic stroke (IS) patients, assessed at Hospital del Mar (Barcelona, Spain) and 183 controls from the REGICOR cohort. In two independent samples (N = 226 and N = 166), we replicated 22 CpG sites differentially methylated in IS in 21 loci, including 2 CpGs in locus ZFHX3, which includes known genetic variants associated with stroke. The pathways associated with these loci are inflammation and angiogenesis. The meta-analysis identified 384 differentially methylated CpGs, including loci of known stroke and vascular risk genetic variants, enriched by loci involved in lipid metabolism, adipogenesis, circadian clock, and glycolysis pathways. We identified a set of 22 CpGs in 21 loci associated with IS. Our analysis suggests that DNA methylation changes may contribute to orchestrating gene expression that contributes to IS

    Epigenetic Clock Explains White Matter Hyperintensity Burden Irrespective of Chronological Age

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    In this manuscript we studied the relationship between WMH and biological age (B-age) in patients with acute stroke. We included in this study 247 patients with acute stroke recruited at Hospital del Mar having both epigenetic (DNA methylation) and magnetic resonance imaging data. WMH were measured using a semi-automated method. B-age was calculated using two widely used methods: the Hannum and Horvath formulas. We used multiple linear regression models to interrogate the role of B-age on WMH volume after adjusting for chronological age (C-age) and other covariables. Average C-age of the sample was 68.4 (±11.8) and we observed a relatively high median WMH volume (median = 8.8 cm3, Q1–Q3 = 4.05–18.8). After adjusting for potential confounders, we observed a significant effect of B-ageHannum on WMH volume (βHannum = 0.023, p-value = 0.029) independently of C-age, which remained significant (βC-age = 0.021, p-value = 0.036). Finally, we performed a mediation analysis, which allowed us to discover that 42.7% of the effect of C-age on WMH is mediated by B-ageHannum. On the other hand, B-ageHoarvath showed no significant associations with WMH after being adjusted for C-age. In conclusion, we show for the first time that biological age, measured through DNA methylation, contributes substantially to explain WMH volumetric burden irrespective of chronological age

    Epigenetic clock explains white matter hyperintensity burden irrespective of chronological age

    No full text
    In this manuscript we studied the relationship between WMH and biological age (B-age) in patients with acute stroke. We included in this study 247 patients with acute stroke recruited at Hospital del Mar having both epigenetic (DNA methylation) and magnetic resonance imaging data. WMH were measured using a semi-automated method. B-age was calculated using two widely used methods: the Hannum and Horvath formulas. We used multiple linear regression models to interrogate the role of B-age on WMH volume after adjusting for chronological age (C-age) and other covariables. Average C-age of the sample was 68.4 (±11.8) and we observed a relatively high median WMH volume (median = 8.8 cm3, Q1–Q3 = 4.05–18.8). After adjusting for potential confounders, we observed a significant effect of B-ageHannum on WMH volume (βHannum = 0.023, p-value = 0.029) independently of C-age, which remained significant (βC-age = 0.021, p-value = 0.036). Finally, we performed a mediation analysis, which allowed us to discover that 42.7% of the effect of C-age on WMH is mediated by B-ageHannum. On the other hand, B-ageHoarvath showed no significant associations with WMH after being adjusted for C-age. In conclusion, we show for the first time that biological age, measured through DNA methylation, contributes substantially to explain WMH volumetric burden irrespective of chronological age
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