Participation‐related constructs and participation of children with additional support needs in schools

From Wiley via Jisc Publications RouterHistory: received 2022-03-07, rev-recd 2022-07-21, accepted 2022-07-25, pub-electronic 2022-09-25Article version: VoRPublication status: PublishedFunder: City of Edinburgh CouncilFunder: National Health Service LothianFunder: Scottish Government; Id: http://dx.doi.org/10.13039/100012095Funder: Queen Margaret University, Edinburgh; Id: http://dx.doi.org/10.13039/100010033Abstract: Aim: To investigate associations between participation‐related constructs and participation frequency and involvement in inclusive schools. Method: In this cross‐sectional study, teachers of children with additional support needs, including intellectual disability, autism, and learning difficulties, completed measures. Participation‐related constructs were measured using the School Participation Questionnaire; participation frequency and involvement were measured using the Participation and Environment Measure for Children and Youth. A series of multilevel linear mixed‐effects regression models with maximum likelihood estimates and bootstrap confidence intervals with p‐values were obtained. Final models included participation‐related constructs and participation, controlling for demographic and diagnostic confounders (including age, sex, language, level of school support, and autism). Results: Six hundred and eighty‐eight children (448 [65.1%] males; mean age 8 years 7 months [range 4 years 10 months–12 years 13 months, standard deviation 2 years 1 months]) were assessed by 252 teachers. Across a series of models, participation‐related constructs were consistently associated with more intensive participation (competence, environment, identity p < 0.001; symptoms p = 0.007), independent of confounders. More frequent participation remained associated with three of four participation‐related constructs (competence, identity p < 0.001; environment p = 0.021). Age (p = 0.046), language (p = 0.002), and level of school support (p = 0.039) also remained significantly associated with frequency of participation. Interpretation: Children with additional support needs in inclusive schools may have several participation barriers. Policies and interventions to improve participation are needed

The Angular Power Spectrum of Galaxies from Early SDSS Data

We compute the angular power spectrum C_l from 1.5 million galaxies in early SDSS data on large angular scales, l<600. The data set covers about 160 square degrees, with a characteristic depth of order 1 Gpc/h in the faintest (21<r<22) of our four magnitude bins. Cosmological interpretations of these results are presented in a companion paper by Dodelson et al (2001). The data in all four magnitude bins are consistent with a simple flat ``concordance'' model with nonlinear evolution and linear bias factors of order unity. Nonlinear evolution is particularly evident for the brightest galaxies. A series of tests suggest that systematic errors related to seeing, reddening, etc., are negligible, which bodes well for the sixtyfold larger sample that the SDSS is currently collecting. Uncorrelated error bars and well-behaved window functions make our measurements a convenient starting point for cosmological model fitting.Comment: Replaced to match accepted ApJ version (14 pages). Data, window functions etc available at http://www.hep.upenn.edu/~max/sdss.html or from [email protected]

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Genetic Evidence for Causal Relationships Between Maternal Obesity-Related Traits and Birth Weight

ImportanceNeonates born to overweight or obese women are larger and at higher risk of birth complications. Many maternal obesity-related traits are observationally associated with birth weight, but the causal nature of these associations is uncertain.ObjectiveTo test for genetic evidence of causal associations of maternal body mass index (BMI) and related traits with birth weight.Design, Setting, and ParticipantsMendelian randomization to test whether maternal BMI and obesity-related traits are potentially causally related to offspring birth weight. Data from 30 487 women in 18 studies were analyzed. Participants were of European ancestry from population- or community-based studies in Europe, North America, or Australia and were part of the Early Growth Genetics Consortium. Live, term, singleton offspring born between 1929 and 2013 were included.ExposuresGenetic scores for BMI, fasting glucose level, type 2 diabetes, systolic blood pressure (SBP), triglyceride level, high-density lipoprotein cholesterol (HDL-C) level, vitamin D status, and adiponectin level.Main Outcome and MeasureOffspring birth weight from 18 studies.ResultsAmong the 30 487 newborns the mean birth weight in the various cohorts ranged from 3325 g to 3679 g. The maternal genetic score for BMI was associated with a 2-g (95% CI, 0 to 3 g) higher offspring birth weight per maternal BMI-raising allele (P = .008). The maternal genetic scores for fasting glucose and SBP were also associated with birth weight with effect sizes of 8 g (95% CI, 6 to 10 g) per glucose-raising allele (P = 7 × 10−14) and −4 g (95% CI, −6 to −2g) per SBP-raising allele (P = 1×10−5), respectively. A 1-SD ( ≈ 4 points) genetically higher maternal BMI was associated with a 55-g higher offspring birth weight (95% CI, 17 to 93 g). A 1-SD ( ≈ 7.2 mg/dL) genetically higher maternal fasting glucose concentration was associated with 114-g higher offspring birth weight (95% CI, 80 to 147 g). However, a 1-SD ( ≈ 10 mm Hg) genetically higher maternal SBP was associated with a 208-g lower offspring birth weight (95% CI, −394 to −21 g). For BMI and fasting glucose, genetic associations were consistent with the observational associations, but for systolic blood pressure, the genetic and observational associations were in opposite directions.Conclusions and RelevanceIn this mendelian randomization study, genetically elevated maternal BMI and blood glucose levels were potentially causally associated with higher offspring birth weight, whereas genetically elevated maternal SBP was potentially causally related to lower birth weight. If replicated, these findings may have implications for counseling and managing pregnancies to avoid adverse weight-related birth outcomes

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Social Media as a Conduit for Spreading Misinformation: An Examination of Antivaccination Messages in the Wake of the 2019 Washington Measles Outbreak

Public health experts have studied global pandemics long before the COVID-19 outbreak of 2020. Since the worldwide spread of HIV, SARS, H1N1, and Ebola among others, scholars have focused on identifying best practices for risk mitigation and reaching disparate publics to engage in appropriate risk mitigation behaviors. The 2019 measles outbreak in Washington, USA flourished in large part due to the viral spread of misinformation on social networking platforms. Due to intended openness of these platforms, antivaccination messaging became prominent, and the U.S. among other countries to have eradicated measles saw a number of outbreaks. In the U.S. in 2019, many of these occurred in Washington state. These outbreaks served as an impetus for social media platforms to reconsider their role in spreading health misinformation and its contribution to real world danger. This analysis considers open media ethics to understand social media platforms’ initial decisions to allow vaccine misinformation and the role of communication scholars and practitioners have in understanding, and acting on misinformation. Using a case study approach, this article examines online discourse about the measles, mumps, and rubella vaccine, policy measures related to vaccine exemption, and social media organization formal responses in 2019 directly related to the increase in U.S. measles outbreaks. Using an open media ethics framework, findings from this study illustrate the ways in which these organizations initially intended to have an open platform for health-related discussions. Further analysis demonstrates that these organizations focused on existing terms of use to put in place protective measures that would prevent further spread of this mis- and disinformation. However, conclusions draw illustrate that placing the onus on the social media organizations alone is insufficient to prevent outbreaks such as this to occur, and as the COVID-19 pandemic began the following year, the implications of this study continue to pose questions about social media misinformation management.</jats:p