Genetic risk factors for ischaemic stroke and its subtypes (the METASTROKE Collaboration): a meta-analysis of genome-wide association studies

<p>Background - Various genome-wide association studies (GWAS) have been done in ischaemic stroke, identifying a few loci associated with the disease, but sample sizes have been 3500 cases or less. We established the METASTROKE collaboration with the aim of validating associations from previous GWAS and identifying novel genetic associations through meta-analysis of GWAS datasets for ischaemic stroke and its subtypes.</p> <p>Methods - We meta-analysed data from 15 ischaemic stroke cohorts with a total of 12 389 individuals with ischaemic stroke and 62 004 controls, all of European ancestry. For the associations reaching genome-wide significance in METASTROKE, we did a further analysis, conditioning on the lead single nucleotide polymorphism in every associated region. Replication of novel suggestive signals was done in 13 347 cases and 29 083 controls.</p> <p>Findings - We verified previous associations for cardioembolic stroke near PITX2 (p=2·8×10−16) and ZFHX3 (p=2·28×10−8), and for large-vessel stroke at a 9p21 locus (p=3·32×10−5) and HDAC9 (p=2·03×10−12). Additionally, we verified that all associations were subtype specific. Conditional analysis in the three regions for which the associations reached genome-wide significance (PITX2, ZFHX3, and HDAC9) indicated that all the signal in each region could be attributed to one risk haplotype. We also identified 12 potentially novel loci at p<5×10−6. However, we were unable to replicate any of these novel associations in the replication cohort.</p> <p>Interpretation - Our results show that, although genetic variants can be detected in patients with ischaemic stroke when compared with controls, all associations we were able to confirm are specific to a stroke subtype. This finding has two implications. First, to maximise success of genetic studies in ischaemic stroke, detailed stroke subtyping is required. Second, different genetic pathophysiological mechanisms seem to be associated with different stroke subtypes.</p&gt

Linking marine phytoplankton emissions, meteorological processes, and downwind particle properties with FLEXPART

Marine biogenic particle contributions to atmospheric aerosol concentrations are not well understood though they are important for determining cloud optical and cloud-nucleating properties. Here we examine the relationship between marine aerosol measurements (with satellites and model fields of ocean biology) and meteorological variables during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). NAAMES consisted of four field campaigns between November 2015 and April 2018 that aligned with the four major phases of the annual phytoplankton bloom cycle. The FLEXible PARTicle (FLEX-PART) Lagrangian particle dispersion model is used to spatiotemporally connect these variables to ship-based aerosol and dimethyl sulfide (DMS) observations. We find that correlations between some aerosol measurements with satellite-measured and modeled variables increase with increasing trajectory length, indicating that biological and meteorological processes over the air mass history are influential for measured particle properties and that using only spatially coincident data would miss correlative connections that are lagged in time. In particular, the marine non-refractory organic aerosol mass correlates with modeled marine net primary production when weighted by 5 d air mass trajectory residence time (r = 0.62). This result indicates that non-refractory organic aerosol mass is influenced by biogenic volatile organic compound (VOC) emissions that are typically produced through bacterial degradation of dissolved organic matter, zooplankton grazing on marine phytoplankton, and as a by-product of photosynthesis by phytoplankton stocks during advection into the region. This is further supported by the correlation of non-refractory organic mass with 2 d residence-time-weighted chlorophyll a (r = 0.39), a proxy for phytoplankton abundance, and 5 d residence-time-weighted downward shortwave forcing (r = 0.58), a requirement for photosynthesis. In contrast, DMS (formed through biological processes in the seawater) and primary marine aerosol (PMA) concentrations showed better correlations with explanatory biological and meteorological variables weighted with shorter air mass residence times, which reflects their localized origin as primary emissions. Aerosol submicron number and mass negatively correlate with sea surface wind speed. The negative correlation is attributed to enhanced PMA concentrations under higher wind speed conditions. We hypothesized that the elevated total particle surface area associated with high PMA concentrations leads to enhanced rates of condensation of VOC oxidation products onto PMA. Given the high deposition velocity of PMA relative to submicron aerosol, PMA can limit the accumulation of secondary aerosol mass. This study provides observational evidence for connections between marine aerosols and underlying ocean biology through complex secondary formation processes, emphasizing the need to consider air mass history in future analyses

The relationships between workaholism and symptoms of psychiatric disorders: a large-scale cross-sectional study

Despite the many number of studies examining workaholism, large-scale studies have been lacking. The present study utilized an open web-based cross-sectional survey assessing symptoms of psychiatric disorders and workaholism among 16,426 workers (Mage = 37.3 years, SD = 11.4, range = 16–75 years). Participants were administered the Adult ADHD Self-Report Scale, the Obsession-Compulsive Inventory-Revised, the Hospital Anxiety and Depression Scale, and the Bergen Work Addiction Scale, along with additional questions examining demographic and work-related variables. Correlations between workaholism and all psychiatric disorder symptoms were positive and significant. Workaholism comprised the dependent variable in a three-step linear multiple hierarchical regression analysis. Basic demographics (age, gender, relationship status, and education) explained 1.2% of the variance in workaholism, whereas work demographics (work status, position, sector, and annual income) explained an additional 5.4% of the variance. Age (inversely) and managerial positions (positively) were of most importance. The psychiatric symptoms (ADHD, OCD, anxiety, and depression) explained 17.0% of the variance. ADHD and anxiety contributed considerably. The prevalence rate of workaholism status was 7.8% of the present sample. In an adjusted logistic regression analysis, all psychiatric symptoms were positively associated with being a workaholic. The independent variables explained between 6.1% and 14.4% in total of the variance in workaholism cases. Although most effect sizes were relatively small, the study’s findings expand our understanding of possible psychiatric predictors of workaholism, and particularly shed new insight into the reality of adult ADHD in work life. The study’s implications, strengths, and shortcomings are also discussed

The Human Phenotype Ontology in 2024: phenotypes around the world

\ua9 The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research. The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs

Sex and gender differences in autism spectrum disorder: summarizing evidence gaps and identifying emerging areas of priority

One of the most consistent findings in autism spectrum disorder (ASD) research is a higher rate of ASD diagnosis in males than females. Despite this, remarkably little research has focused on the reasons for this disparity. Better understanding of this sex difference could lead to major advancements in the prevention or treatment of ASD in both males and females. In October of 2014, Autism Speaks and the Autism Science Foundation co-organized a meeting that brought together almost 60 clinicians, researchers, parents, and self-identified autistic individuals. Discussion at the meeting is summarized here with recommendations on directions of future research endeavors. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13229-015-0019-y) contains supplementary material, which is available to authorized users

Smoke radiocarbon measurements from Indonesian fires provide evidence for burning of millennia-aged peat

10.1073/pnas.1806003115Proceedings of the National Academy of Sciences of the United States of America1154912419-1242

Black carbon aerosol dynamics and isotopic composition in Alaska linked with boreal fire emissions and depth of burn in organic soils

Black carbon (BC) aerosol emitted by boreal fires has the potential to accelerate losses of snow and ice in many areas of the Arctic, yet the importance of this source relative to fossil fuel BC emissions from lower latitudes remains uncertain. Here we present measurements of the isotopic composition of BC and organic carbon (OC) aerosols collected at two locations in interior Alaska during the summer of 2013, as part of NASA's Carbon in Arctic Reservoirs Vulnerability Experiment. We isolated BC from fine air particulate matter (PM2.5) and measured its radiocarbon (Δ14C) content with accelerator mass spectrometry. We show that fires were the dominant contributor to variability in carbonaceous aerosol mass in interior Alaska during the summer by comparing our measurements with satellite data, measurements from an aerosol network and predicted concentrations from a fire inventory coupled to an atmospheric transport model. The Δ14C of BC from boreal fires was 131 ± 52‰ in the year 2013 when the Δ14C of atmospheric CO2 was 23 ± 3‰, corresponding to a mean fuel age of 20 years. Fire-emitted OC had a similar Δ14C (99 ± 21‰) as BC, but during background (low fire) periods OC (45 to 51‰) was more positive than BC (-354 to -57‰). We also analyzed the carbon and nitrogen elemental and stable isotopic composition of the PM2.5. Fire-emitted aerosol had an elevated carbon to nitrogen (C/N) ratio (29 ± 2) and δ15N (16 ± 4‰). Aerosol Δ14C and δ13C measurements were consistent with a mean depth of burning in organic soil horizons of 20 cm (and a range of 8 to 47 cm). Our measurements of fire-emitted BC and PM2.5 composition constrain the end-member of boreal forest fire contributions to aerosol deposition in the Arctic and may ultimately reduce uncertainties related to the impact of a changing boreal fire regime on the climate system

Black carbon aerosol dynamics and isotopic composition in Alaska linked with boreal fire emissions and depth of burn in organic soils

Black carbon (BC) aerosol emitted by boreal fires has the potential to accelerate losses of snow and ice in many areas of the Arctic, yet the importance of this source relative to fossil fuel BC emissions from lower latitudes remains uncertain. Here we present measurements of the isotopic composition of BC and organic carbon (OC) aerosols collected at two locations in interior Alaska during the summer of 2013, as part of NASA's Carbon in Arctic Reservoirs Vulnerability Experiment. We isolated BC from fine air particulate matter (PM ) and measured its radiocarbon (Δ C) content with accelerator mass spectrometry. We show that fires were the dominant contributor to variability in carbonaceous aerosol mass in interior Alaska during the summer by comparing our measurements with satellite data, measurements from an aerosol network and predicted concentrations from a fire inventory coupled to an atmospheric transport model. The Δ C of BC from boreal fires was 131 ± 52‰ in the year 2013 when the Δ C of atmospheric CO was 23 ± 3‰, corresponding to a mean fuel age of 20 years. Fire-emitted OC had a similar Δ C (99 ± 21‰) as BC, but during background (low fire) periods OC (45 to 51‰) was more positive than BC (-354 to -57‰). We also analyzed the carbon and nitrogen elemental and stable isotopic composition of the PM . Fire-emitted aerosol had an elevated carbon to nitrogen (C/N) ratio (29 ± 2) and δ N (16 ± 4‰). Aerosol Δ C and δ C measurements were consistent with a mean depth of burning in organic soil horizons of 20 cm (and a range of 8 to 47 cm). Our measurements of fire-emitted BC and PM composition constrain the end-member of boreal forest fire contributions to aerosol deposition in the Arctic and may ultimately reduce uncertainties related to the impact of a changing boreal fire regime on the climate system. 2.5 2 2.5 2.5 14 14 14 14 15 14 1

The influence of daily meteorology on boreal fire emissions and regional trace gas variability

Relationships between boreal wildfire emissions and day-to-day variations in meteorological variables are complex and have important implications for the sensitivity of high-latitude ecosystems to climate change. We examined the influence of environmental conditions on boreal fire emissions and fire contributions to regional trace gas variability in interior Alaska during the summer of 2013 using two types of analysis. First, we quantified the degree to which meteorological and fire weather indices explained regional variability in fire activity using four different products, including active fires, fire radiative power, burned area, and carbon emissions. Second, we combined daily emissions from the Alaskan Fire Emissions Database (AKFED) with the coupled Polar Weather Research and Forecasting/Stochastic Time-Inverted Lagrangian Transport model to estimate fire contributions to trace gas concentration measurements at the Carbon in Arctic Reservoirs Vulnerability Experiment-NOAA Global Monitoring Division (CRV) tower in interior Alaska. Tower observations during two high fire periods were used to estimate CO and CH4 emission factors. We found that vapor pressure deficit and temperature had a level of performance similar to more complex fire weather indices. Emission factors derived from CRV tower measurements were 134 ± 25 g CO per kg of combusted biomass and 7.74 ± 1.06 g CH4 per kg of combusted biomass. Predicted daily CO mole fractions from AKFED emissions were moderately correlated with CRV observations (r = 0.68) and had a high bias. The modeling system developed here allows for attribution of emission factors to individual fires and has the potential to improve our understanding of regional CO, CH4, and CO2 budgets