Morbidity and pollution: model specification analysis for time-series data on hospital admissions

Time-series analysis of effects of pollutants on emergency hospital admissions indicates important synergistic interactions among pollutants and to a lesser degree nonlinearities in effects of single pollutants. Comparisons of alternative econometric specifications are made to determine the appropriateness of incorporating nonuniform pollution impacts. The data substantially support the existence of synergisms among pollutants with high levels of sulfur dioxide, SO, (particulates), increasing the impact of particulates (SO,) on emergency hospital admissions. Marginal effects of either pollutant are, however, small at current ambient air quality levels. These results indicate that damage estimates were likely to be understated during the 1960’s when pollution levels were high, while, at current levels of those pollutants considered here, marginal damages are lower than would be estimated in studies failing to incorporate synergistic and nonlinear impacts.time series; hospital admissions; pollution and human health; synergisms; nonlinearities; econometric model specification

Morbidity and pollution: model specification analysis for time-series data on hospital admissions

Time-series analysis of effects of pollutants on emergency hospital admissions indicates important synergistic interactions among pollutants and to a lesser degree nonlinearities in effects of single pollutants. Comparisons of alternative econometric specifications are made to determine the appropriateness of incorporating nonuniform pollution impacts. The data substantially support the existence of synergisms among pollutants with high levels of sulfur dioxide, SO, (particulates), increasing the impact of particulates (SO,) on emergency hospital admissions. Marginal effects of either pollutant are, however, small at current ambient air quality levels. These results indicate that damage estimates were likely to be understated during the 1960’s when pollution levels were high, while, at current levels of those pollutants considered here, marginal damages are lower than would be estimated in studies failing to incorporate synergistic and nonlinear impacts

Morbidity and pollution: model specification analysis for time-series data on hospital admissions

Time-series analysis of effects of pollutants on emergency hospital admissions indicates important synergistic interactions among pollutants and to a lesser degree nonlinearities in effects of single pollutants. Comparisons of alternative econometric specifications are made to determine the appropriateness of incorporating nonuniform pollution impacts. The data substantially support the existence of synergisms among pollutants with high levels of sulfur dioxide, SO, (particulates), increasing the impact of particulates (SO,) on emergency hospital admissions. Marginal effects of either pollutant are, however, small at current ambient air quality levels. These results indicate that damage estimates were likely to be understated during the 1960’s when pollution levels were high, while, at current levels of those pollutants considered here, marginal damages are lower than would be estimated in studies failing to incorporate synergistic and nonlinear impacts

Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population

Almost all genetic risk factors for autism spectrum disorders (ASDs) can be found in the general population, but the effects of that risk are unclear in people not ascertained for neuropsychiatric symptoms. Using several large ASD consortia and population based resources, we find genetic links between ASDs and typical variation in social behavior and adaptive functioning. This finding is evidenced through both inherited and de novo variation, indicating that multiple types of genetic risk for ASDs influence a continuum of behavioral and developmental traits, the severe tail of which can result in an ASD or other neuropsychiatric disorder diagnosis. A continuum model should inform the design and interpretation of studies of neuropsychiatric disease biology

ASD and schizophrenia show distinct developmental profiles in common genetic overlap with population-based social communication difficulties

Difficulties in social communication are part of the phenotypic overlap between autism spectrum disorders (ASD) and schizophrenia. Both conditions follow, however, distinct developmental patterns. Symptoms of ASD typically occur during early childhood, whereas most symptoms characteristic of schizophrenia do not appear before early adulthood. We investigated whether overlap in common genetic in fluences between these clinical conditions and impairments in social communication depends on the developmental stage of the assessed trait. Social communication difficulties were measured in typically-developing youth (Avon Longitudinal Study of Parents and Children,N⩽5553, longitudinal assessments at 8, 11, 14 and 17 years) using the Social Communication Disorder Checklist. Data on clinical ASD (PGC-ASD: 5305 cases, 5305 pseudo-controls; iPSYCH-ASD: 7783 cases, 11 359 controls) and schizophrenia (PGC-SCZ2: 34 241 cases, 45 604 controls, 1235 trios) were either obtained through the Psychiatric Genomics Consortium (PGC) or the Danish iPSYCH project. Overlap in genetic in fluences between ASD and social communication difficulties during development decreased with age, both in the PGC-ASD and the iPSYCH-ASD sample. Genetic overlap between schizophrenia and social communication difficulties, by contrast, persisted across age, as observed within two independent PGC-SCZ2 subsamples, and showed an increase in magnitude for traits assessed during later adolescence. ASD- and schizophrenia-related polygenic effects were unrelated to each other and changes in trait-disorder links reflect the heterogeneity of genetic factors in fluencing social communication difficulties during childhood versus later adolescence. Thus, both clinical ASD and schizophrenia share some genetic in fluences with impairments in social communication, but reveal distinct developmental profiles in their genetic links, consistent with the onset of clinical symptom

The First Post-Kepler Brightness Dips of KIC 8462852

We present a photometric detection of the first brightness dips of the unique variable star KIC 8462852 since the end of the Kepler space mission in 2013 May. Our regular photometric surveillance started in October 2015, and a sequence of dipping began in 2017 May continuing on through the end of 2017, when the star was no longer visible from Earth. We distinguish four main 1-2.5% dips, named "Elsie," "Celeste," "Skara Brae," and "Angkor", which persist on timescales from several days to weeks. Our main results so far are: (i) there are no apparent changes of the stellar spectrum or polarization during the dips; (ii) the multiband photometry of the dips shows differential reddening favoring non-grey extinction. Therefore, our data are inconsistent with dip models that invoke optically thick material, but rather they are in-line with predictions for an occulter consisting primarily of ordinary dust, where much of the material must be optically thin with a size scale <<1um, and may also be consistent with models invoking variations intrinsic to the stellar photosphere. Notably, our data do not place constraints on the color of the longer-term "secular" dimming, which may be caused by independent processes, or probe different regimes of a single process

RNA sequencing of identical twins discordant for autism reveals blood-based signatures implicating immune and transcriptional dysregulation

Background: A gap exists in our mechanistic understanding of how genetic and environmental risk factors converge at the molecular level to result in the emergence of autism symptoms. We compared blood-based gene expression signatures in identical twins concordant and discordant for autism spectrum condition (ASC) to differentiate genetic and environmentally driven transcription differences, and establish convergent evidence for biological mechanisms involved in ASC. Methods: Genome-wide gene expression data were generated using RNA-seq on whole blood samples taken from 16 pairs of monozygotic (MZ) twins and seven twin pair members (39 individuals in total), who had been assessed for ASC and autism traits at age 12. Differential expression (DE) analyses were performed between (a) affected and unaffected subjects (N = 36) and (b) within discordant ASC MZ twin pairs (total N = 11) to identify environmental-driven DE. Gene set enrichment and pathway testing was performed on DE gene lists. Finally, an integrative analysis using DNA methylation data aimed to identify genes with consistent evidence for altered regulation in cis. Results: In the discordant twin analysis, three genes showed evidence for DE at FDR < 10%: IGHG4, EVI2A and SNORD15B. In the case-control analysis, four DE genes were identified at FDR<10% including IGHG4, PRR13P5, DEPDC1B, and ZNF501. We find enrichment for DE of genes curated in the SFARI human gene database. Pathways showing evidence of enrichment included those related to immune cell signalling and immune response, transcriptional control and cell cycle/proliferation. Integrative methylomic and transcriptomic analysis identified a number of genes showing suggestive evidence for cis dysregulation. Limitations: Identical twins stably discordant for ASC are rare, and as such the sample size was limited and constrained to the use of peripheral blood tissue for transcriptomic and methylomic profiling. Given these primary limitations, we focused on transcript-level analysis. Conclusions: Using a cohort of ASC discordant and concordant MZ twins, we add to the growing body of transcriptomic-based evidence for an immune-based component in the molecular aetiology of ASC. Whilst the sample size was limited, the study demonstrates the utility of the discordant MZ twin design combined with multi-omics integration for maximising the potential to identify disease-associated molecular signals