Shakespeare's references to consumption, climate, and fresh air

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Immunology and genetics of type 1 diabetes

Type 1 diabetes is one of the most well-characterized autoimmune diseases. Type 1 diabetes compromises an individual's insulin production through the autoimmune destruction of pancreatic Β-cells. Although much is understood about the mechanisms of this disease, multiple potential contributing factors are thought to play distinct parts in triggering type 1 diabetes. The immunological diagnosis of type 1 diabetes relies primarily on the detection of autoantibodies against islet antigens in the serum of type 1 diabetes mellitus patients. Genetic analyses of type 1 diabetes have linked human leukocyte antigen, specifically class II alleles, to susceptibility to disease onset. Environmental catalysts include various possible factors, such as viral infections, although the evidence linking infections with type 1 diabetes remains inconclusive. Imbalances within the immune system's system of checks and balances may promote immune activation, while undermining immune regulation. A lack of proper regulation and overactive pathogenic responses provide a framework for the development of autoimmune abnormalities. Type 1 diabetes is a predictable and potentially treatable disease that still requires much research to fully understand and pinpoint the exact triggering events leading to autoimmune activation. In silico research can aid the comprehension of the etiology of complex disease pathways, including Type I diabetes, in order to and help predict the outcome of therapeutic strategies aimed at preserving Β-cell function. Mt Sinai J Med 75:314–327, 2008. © 2008 Mount Sinai School of MedicinePeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/60987/1/20052_ftp.pd

Meta-analysis indicates that common variants at the DISC1 locus are not associated with schizophrenia

Several polymorphisms in the Disrupted-in-Schizophrenia-1 (DISC1) gene are reported to be associated with schizophrenia. However, to date, there has been little effort to evaluate the evidence for association systematically. We carried out an imputation-driven meta-analysis, the most comprehensive to date, using data collected from 10 candidate gene studies and three genome-wide association studies containing a total of 11 626 cases and 15 237 controls. We tested 1241 single-nucleotide polymorphisms in total, and estimated that our power to detect an effect from a variant with minor allele frequency >5% was 99% for an odds ratio of 1.5 and 51% for an odds ratio of 1.1. We find no evidence that common variants at the DISC1 locus are associated with schizophrenia

The influence of the ectomycorrhizal fungus Rhizopogon subareolatus on growth and nutrient element localisation in two varieties of Douglas fir (Pseudotsuga menziesii var. menziesii and var. glauca) in response to manganese stress

Acidification of forest ecosystems leads to increased plant availability of the micronutrient manganese (Mn), which is toxic when taken up in excess. To investigate whether ectomycorrhizas protect against excessive Mn by improving plant growth and nutrition or by retention of excess Mn in the hyphal mantle, seedlings of two populations of Douglas fir (Pseudotsuga menziesii), two varieties, one being menziesii (DFM) and the other being glauca (DFG), were inoculated with the ectomycorrhizal fungus Rhizopogon subareolatus in sand cultures. Five months after inoculation, half of the inoculated and non-inoculated seedlings were exposed to excess Mn in the nutrient solution for further 5 months. At the end of this period, plant productivity, nutrient concentrations, Mn uptake and subcellular compartmentalisation were evaluated. Non-inoculated, non-stressed DFM plants produced about 2.5 times more biomass than similarly treated DFG. Excess Mn in the nutrient solution led to high accumulation of Mn in needles and roots but only to marginal loss in biomass. Colonisation with R. subareolatus slightly suppressed DFM growth but strongly reduced that of DFG (−50%) despite positive effects of mycorrhizas on plant phosphorus nutrition. Growth reductions of inoculated Douglas fir seedlings were unexpected since the degree of mycorrhization was not high, i.e. ca. 30% in DFM and 8% in DFG. Accumulation of high Mn was not prevented in inoculated seedlings. The hyphal mantle of mycorrhizal root tips accumulated divalent cations such as Ca, but not Mn, thus not providing a barrier against excessive Mn uptake into the plants associated with R. subareolatus

Long COVID and episodic disability: advancing the conceptualisation, measurement and knowledge of episodic disability among people living with Long COVID - protocol for a mixed-methods study

Introduction- As the prevalence of Long COVID increases, there is a critical need for a comprehensive assessment of disability. Our aims are to: (1) characterise disability experiences among people living with Long COVID in Canada, UK, USA and Ireland; and (2) develop a patient-reported outcome measure to assess the presence, severity and episodic nature of disability with Long COVID. Methods and analysis- In phase 1, we will conduct semistructured interviews with adults living with Long COVID to explore experiences of disability (dimensions, uncertainty, trajectories, influencing contextual factors) and establish an episodic disability (ED) framework in the context of Long COVID (n~10 each country). Using the conceptual framework, we will establish the Long COVID Episodic Disability Questionnaire (EDQ). In phase 2, we will examine the validity (construct, structural) and reliability (internal consistency, test–retest) of the EDQ for use in Long COVID. We will electronically administer the EDQ and four health status criterion measures with adults living with Long COVID, and readminister the EDQ 1 week later (n~170 each country). We will use Rasch analysis to refine the EDQ, and confirm structural and cross-cultural validity. We will calculate Cronbach’s alphas (internal consistency reliability), and intraclass correlation coefficients (test–retest reliability), and examine correlations for hypotheses theorising relationships between EDQ and criterion measure scores (construct validity). Using phase 2 data, we will characterise the profile of disability using structural equation modelling techniques to examine relationships between dimensions of disability and the influence of intrinsic and extrinsic contextual factors. This research involves an academic–clinical–community partnership building on foundational work in ED measurement, Long COVID and rehabilitation. Ethics and dissemination- This study was approved by the University of Toronto Research Ethics Board. Knowledge translation will occur with community collaborators in the form of presentations and publications in open access peer-reviewed journals and presentations

Balanced translocation linked to psychiatric disorder, glutamate and cortical structure/function

Rare genetic variants of large effect can help elucidate the pathophysiology of brain disorders. Here we expand the clinical and genetic analyses of a family with a (1;11)(q42;q14.3) translocation multiply affected by major psychiatric illness and test the effect of the translocation on the structure and function of prefrontal, and temporal brain regions. The translocation showed significant linkage (LOD score 6.1) with a clinical phenotype that included schizophrenia, schizoaffective disorder, bipolar disorder, and recurrent major depressive disorder. Translocation carriers showed reduced cortical thickness in the left temporal lobe, which correlated with general psychopathology and positive psychotic symptom severity. They showed reduced gyrification in prefrontal cortex, which correlated with general psychopathology severity. Translocation carriers also showed significantly increased activation in the caudate nucleus on increasing verbal working memory load, as well as statistically significant reductions in the right dorsolateral prefrontal cortex glutamate concentrations. These findings confirm that the t(1;11) translocation is associated with a significantly increased risk of major psychiatric disorder and suggest a general vulnerability to psychopathology through altered cortical structure and function, and decreased glutamate levels

Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A

The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods - recursive partitioning and regression - to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios >1.5; Pcombined = 2.01 × 10-19 and 2.35 × 10-13, respectively) in addition to the established associations of the MHC class II genes. Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples. Taken together with previous studies, we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes. ©2007 Nature Publishing Group

Mammal responses to global changes in human activity vary by trophic group and landscape

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human–wildlife interactions along gradients of human influence.Peer reviewe

Applying polygenic risk scoring for psychiatric disorders to a large family with bipolar disorder and major depressive disorder

Psychiatric disorders are thought to have a complex genetic pathology consisting of interplay of common and rare variation. Traditionally, pedigrees are used to shed light on the latter only, while here we discuss the application of polygenic risk scores to also highlight patterns of common genetic risk. We analyze polygenic risk scores for psychiatric disorders in a large pedigree (n similar to 260) in which 30% of family members suffer from major depressive disorder or bipolar disorder. Studying patterns of assortative mating and anticipation, it appears increased polygenic risk is contributed by affected individuals who married into the family, resulting in an increasing genetic risk over generations. This may explain the observation of anticipation in mood disorders, whereby onset is earlier and the severity increases over the generations of a family. Joint analyses of rare and common variation may be a powerful way to understand the familial genetics of psychiatric disorders

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers