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Aim: The individual effects of climate and soil properties on functional trait distributions have become increasingly clear with recent syntheses of large datasets. However, the distribution of traits in a given climate may depend on the fertility of the soil. Our aim was to quantify how soil-climate interactions explain community-level variation in functional traits from every plant organ to improve predictions of plant community responses to environmental change. Location: Temperate forests throughout New Zealand. Methods: We measured traits of foliar, stem, root and reproductive tissue for 64 species and calculated abundance-weighted mean trait values on 324 forest plots. Multiple linear regression was used to model the variation in each of the traits as functions of mean annual temperature (MAT), vapour pressure deficit (VPD), soil pH, soil total phosphorus (P) and their interactions. Results: Soil-climate interactions explained significant variation in functional traits. For example, specific leaf area (SLA) was highest in high-P soil within a wet and warm climate; however, strong interactions indicate that SLA was lowest in wet and warm climates in low-P soil. Root tissue density was lowest in warm climates and high-P soil, but it was high in warm climates and low-P soil and in cold climates and high-P soil. According to model predictions, the largest potential responses of vegetation to warming may occur in fertile and wet environments. Main conclusions: Pervasive soil-climate interactions demonstrate that interpreting simple bivariate relationships between traits and climate must be done with caution because the adaptive value of traits in a given climate depends on the fertility of the soil. Predictions of vegetation responses to climate change will improve significantly by incorporating local-scale soil properties into modelling frameworks. Rising global temperatures may shift community-level trait values in opposite directions depending on whether the soil is fertile or infertile.

The relationship between allergic sensitisation and asthma is complex; the data about the strength of this association are conflicting. We propose that the discrepancies arise in part because allergic sensitisation may not be a single entity (as considered conventionally) but a collection of several different classes of sensitisation. We hypothesise that pairings between immunoglobulin E (IgE) antibodies to individual allergenic molecules (components), rather than IgE responses to 'informative' molecules, are associated with increased risk of asthma. In a cross-sectional analysis among 461 children aged 11 years participating in a population-based birth cohort, we measured serum-specific IgE responses to 112 allergen components using a multiplex array (ImmunoCAP Immuno‑Solid phase Allergy Chip [ISAC]). We characterised sensitivity to 44 active components (specific immunoglobulin E [sIgE] > 0.30 units in at least 5% of children) among the 213 (46.2%) participants sensitised to at least one of these 44 components. We adopted several machine learning methodologies that offer a powerful framework to investigate the highly complex sIgE-asthma relationship. Firstly, we applied network analysis and hierarchical clustering (HC) to explore the connectivity structure of component-specific IgEs and identify clusters of component-specific sensitisation ('component clusters'). Of the 44 components included in the model, 33 grouped in seven clusters (C.sIgE-1-7), and the remaining 11 formed singleton clusters. Cluster membership mapped closely to the structural homology of proteins and/or their biological source. Components in the pathogenesis-related (PR)-10 proteins cluster (C.sIgE-5) were central to the network and mediated connections between components from grass (C.sIgE-4), trees (C.sIgE-6), and profilin clusters (C.sIgE-7) with those in mite (C.sIgE-1), lipocalins (C.sIgE-3), and peanut clusters (C.sIgE-2). We then used HC to identify four common 'sensitisation clusters' among study participants: (1) multiple sensitisation (sIgE to multiple components across all seven component clusters and singleton components), (2) predominantly dust mite sensitisation (IgE responses mainly to components from C.sIgE-1), (3) predominantly grass and tree sensitisation (sIgE to multiple components across C.sIgE-4-7), and (4) lower-grade sensitisation. We used a bipartite network to explore the relationship between component clusters, sensitisation clusters, and asthma, and the joint density-based nonparametric differential interaction network analysis and classification (JDINAC) to test whether pairwise interactions of component-specific IgEs are associated with asthma. JDINAC with pairwise interactions provided a good balance between sensitivity (0.84) and specificity (0.87), and outperformed penalised logistic regression with individual sIgE components in predicting asthma, with an area under the curve (AUC) of 0.94, compared with 0.73. We then inferred the differential network of pairwise component-specific IgE interactions, which demonstrated that 18 pairs of components predicted asthma. These findings were confirmed in an independent sample of children aged 8 years who participated in the same birth cohort but did not have component-resolved diagnostics (CRD) data at age 11 years. The main limitation of our study was the exclusion of potentially important allergens caused by both the ISAC chip resolution as well as the filtering step. Clustering and the network analyses might have provided different solutions if additional components had been available. Interactions between pairs of sIgE components are associated with increased risk of asthma and may provide the basis for designing diagnostic tools for asthma.

The term \"atopic march\" has been used to imply a natural progression of a cascade of symptoms from eczema to asthma and rhinitis through childhood. We hypothesize that this expression does not adequately describe the natural history of eczema, wheeze, and rhinitis during childhood. We propose that this paradigm arose from cross-sectional analyses of longitudinal studies, and may reflect a population pattern that may not predominate at the individual level. Data from 9,801 children in two population-based birth cohorts were used to determine individual profiles of eczema, wheeze, and rhinitis and whether the manifestations of these symptoms followed an atopic march pattern. Children were assessed at ages 1, 3, 5, 8, and 11 y. We used Bayesian machine learning methods to identify distinct latent classes based on individual profiles of eczema, wheeze, and rhinitis. This approach allowed us to identify groups of children with similar patterns of eczema, wheeze, and rhinitis over time. Using a latent disease profile model, the data were best described by eight latent classes: no disease (51.3%), atopic march (3.1%), persistent eczema and wheeze (2.7%), persistent eczema with later-onset rhinitis (4.7%), persistent wheeze with later-onset rhinitis (5.7%), transient wheeze (7.7%), eczema only (15.3%), and rhinitis only (9.6%). When latent variable modelling was carried out separately for the two cohorts, similar results were obtained. Highly concordant patterns of sensitisation were associated with different profiles of eczema, rhinitis, and wheeze. The main limitation of this study was the difference in wording of the questions used to ascertain the presence of eczema, wheeze, and rhinitis in the two cohorts. The developmental profiles of eczema, wheeze, and rhinitis are heterogeneous; only a small proportion of children (∼ 7% of those with symptoms) follow trajectory profiles resembling the atopic march. Please see later in the article for the Editors' Summary.

Developmental patterns of lung function during childhood may have major implications for our understanding of the pathogenesis of respiratory disease throughout life. To explore longitudinal trajectories of lung function during childhood and factors associated with lung function decline. In a population-based birth cohort, specific airway resistance (sRaw) was assessed at age 3 (n = 560), 5 (n = 829), 8 (n = 786), and 11 years (n = 644). Based on prospective data (questionnaires, skin tests, IgE), children were assigned to wheeze phenotypes (no wheezing, transient, late-onset, and persistent) and atopy phenotypes (no atopy, dust mite, non-dust mite, multiple early, and multiple late). We used longitudinal linear mixed models to determine predictors of change in sRaw over time. Contrary to the assumption that sRaw is independent of age and sex, boys had higher sRaw than girls (mean difference, 0.080; 95% confidence interval [CI], 0.049-0.111; P < 0.001) and a higher rate of increase over time. For girls, sRaw increased by 0.017 kPa ⋅ s(-1) per year (95% CI, 0.011-0.023). In boys this increase was significantly greater (P = 0.012; mean between-sex difference, 0.011 kPa ⋅ s(-1); 95% CI, 0.003-0.019). Children with persistent wheeze (but not other wheeze phenotypes) had a significantly greater rate of deterioration in sRaw over time compared with never wheezers (P = 0.009). Similarly, children with multiple early, but not other atopy phenotypes had significantly poorer lung function than those without atopy (mean difference, 0.116 kPa ⋅ s(-1); 95% CI, 0.065-0.168; P < 0.001). sRaw increased progressively with the increasing number of asthma exacerbations. Children with persistent wheeze, frequent asthma exacerbations, and multiple early atopy have diminished lung function throughout childhood, and are at risk of a progressive loss of lung function from age 3 to 11 years. These effects are more marked in boys.

There is evidence for adverse effects of outdoor air pollution on lung function of children. Quantitative summaries of the effects of air pollution on lung function, however, are lacking due to large differences among studies. We aimed to study the association between residential exposure to air pollution and lung function in five European birth cohorts with a standardized exposure assessment following a common protocol. As part of the European Study of Cohorts for Air Pollution Effects (ESCAPE) we analyzed data from birth cohort studies situated in Germany, Sweden, the Netherlands, and the United Kingdom that measured lung function at 6-8 years of age (n = 5,921). Annual average exposure to air pollution [nitrogen oxides (NO2, NOx), mass concentrations of particulate matter with diameters < 2.5, < 10, and 2.5-10 μm (PM2.5, PM10, and PMcoarse), and PM2.5 absorbance] at the birth address and current address was estimated by land-use regression models. Associations of lung function with estimated air pollution levels and traffic indicators were estimated for each cohort using linear regression analysis, and then combined by random effects meta-analysis. Estimated levels of NO2, NOx, PM2.5 absorbance, and PM2.5 at the current address, but not at the birth address, were associated with small decreases in lung function. For example, changes in forced expiratory volume in 1 sec (FEV1) ranged from -0.86% (95% CI: -1.48, -0.24%) for a 20-μg/m3 increase in NOx to -1.77% (95% CI: -3.34, -0.18%) for a 5-μg/m3 increase in PM2.5. Exposure to air pollution may result in reduced lung function in schoolchildren.

Spiders are commonly found in terrestrial environments and many rely heavily on their silks for fitness related tasks such as reproduction and dispersal. Although rare, a few species occupy aquatic or semi-aquatic habitats and for them, silk-related specializations are also essential to survive in aquatic environments. Most spider silks studied to date are from cob-web and orb-web weaving species, leaving the silks from many other terrestrial spiders as well as water-associated spiders largely undescribed. Here, we characterize silks from three Dictynoidea species: the aquatic spiders Argyroneta aquatica and Desis marina as well as the terrestrial Badumna longinqua . From silk gland RNA-Seq libraries, we report a total of 47 different homologs of the spidroin (spider fibroin) gene family. Some of these 47 spidroins correspond to known spidroin types (aciniform, ampullate, cribellar, pyriform, and tubuliform), while other spidroins represent novel branches of the spidroin gene family. We also report a hydrophobic amino acid motif (GV) that, to date, is found only in the spidroins of aquatic and semi-aquatic spiders. Comparison of spider silk sequences to the silks from other water-associated arthropods, shows that there is a diversity of strategies to function in aquatic environments.

Groups were well matched for age (P = 0.11), body mass index (P = 0.25), FEV1% predicted (P = 0.85), smoking status (P = 0.3), serum total IgE (P = 0.23), fractional exhaled nitric oxide (P = 0.58), blood eosinophil count (P = 0.58), and treatment (intramuscular triamcinolone [P = 0.71], oral prednisolone [P = 0.31], or daily inhaled corticosteroids [beclomethasone dipropionate equivalent]; P = 0.31). H.J.D. is supported by an Asthma UK Senior Clinical Academic Development Award (AuK-SCAD-2013-229), the J P Moulton Charitable Foundation, a North West Lung Centre Charity project grant, and the University of Manchester Dean's Prize for Clinicians. D.W.R. is a Wellcome Trust Investigator (107849/Z/15/Z) and received a Medical Research Council Program grant (MR/P023576/1). A.S. was supported by grants from the Medical Research Council, National Institute for Health Research, EU FP7, and the NIHR Manchester Biomedical Research Centre.

The worldwide plant economic spectrum hypothesis predicts that leaf, stem, and root traits are correlated across vascular plant species because carbon gain depends on leaves being adequately supplied with water and nutrients, and because construction of each organ involves a trade‐off between performance and persistence. Despite its logical and intuitive appeal, this hypothesis has received mixed empirical support. If traits within species diverge in their responses to an environmental gradient, then interspecific trait correlations could be weakened when measured in natural ecosystems. To test this prediction, we measured relative growth rates (RGR) and seven functional traits that have been shown to be related to fluxes of water, nutrients, and carbon across 56 functionally diverse tree species on (1) juveniles in a controlled environment, (2) juveniles in forest understories, and (3) mature trees in forests. Leaf, stem, and fine root traits of juveniles grown in a controlled environment were closely correlated with each other, and with RGR. Remarkably, the seven leaf, stem, and fine root tissue traits spanned a single dimension of variation when measured in the controlled environment. Forest‐grown juveniles expressed lower leaf mass per area, but higher wood and fine root tissue density, than greenhouse‐grown juveniles. Traits and growth rates were decoupled in forest‐grown juveniles and mature trees. Our results indicate that constraints exist on the covariation, not just the variation, among vegetative plant organs; however, divergent responses of traits within species to environmental gradients can mask interspecific trait correlations in natural environments. Correlations among organs and relationships between traits and RGR were strong when plants were compared in a standardized environment. Our results may reconcile the discrepancies seen among studies, by showing that if traits and growth rates of species are compared across varied environments, then the interorgan trait correlations observed in controlled conditions can weaken or disappear. Phenotypic coordination across leaves, stems, and roots has recently been proposed to explain worldwide interspecific variation in resource use and growth rates among all vascular plant species, but empirical evidence for this “whole‐plant economic spectrum” is mixed. We have compiled an unprecedented dataset to test the hypothesis that leaf, wood, and fine root traits would be coordinated with each other and with relative growth rate under standardized environmental conditions, but that intraspecific trait variation could decouple this phenotypic coordination in field‐grown plants. We show for the first time that juvenile trees grown in a controlled environment express strong coordination of traits and growth rates, but that intraspecific trait variation can weaken interspecific trait correlations when assessing the whole‐plant economic spectrum in natural ecosystems.

The mechanisms explaining excess morbidity and mortality in respiratory infections among males are poorly understood. Innate immune responses are critical in protection against respiratory virus infections. We hypothesised that innate immune responses to respiratory viruses may be deficient in males. We stimulated peripheral blood mononuclear cells from 345 participants at age 16 years in a population-based birth cohort with three live respiratory viruses (rhinoviruses A16 and A1, and respiratory syncytial virus) and two viral mimics (R848 and CpG-A, to mimic responses to SARS-CoV-2) and investigated sex differences in interferon (IFN) responses. IFN-α responses to all viruses and stimuli were 1.34–2.06-fold lower in males than females ( P  = 0.018 −  < 0.001). IFN-β, IFN-γ and IFN-induced chemokines were also deficient in males across all stimuli/viruses. Healthcare records revealed 12.1% of males and 6.6% of females were hospitalized with respiratory infections in infancy ( P  = 0.017). In conclusion, impaired innate anti-viral immunity in males likely results in high male morbidity and mortality from respiratory virus infections.

Functional enrichment analysis of genome-wide association study (GWAS)-summary statistics has suggested that CD4 + T-cells play an important role in asthma pathogenesis. Despite this, CD4 + T-cells are under-represented in asthma transcriptome studies. To fill the gap, 3'-RNA-Seq was used to generate gene expression data on CD4 + T-cells (isolated within 2 h from collection) from peripheral blood from participants with well-controlled asthma (n = 32) and healthy controls (n = 11). Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify sets of co-expressed genes (modules) associated with the asthma phenotype. We identified three modules associated with asthma, which are strongly enriched for GWAS-identified asthma genes, antigen processing/presentation and immune response to viral infections. Through integration of publicly available eQTL and GWAS summary statistics (colocalisation), and protein–protein interaction (PPI) data, we identified PTPRC , a potential druggable target, as a putative master regulator of the asthma gene-expression profiles. Using a co-expression network approach, with integration of external genetic and PPI data, we showed that CD4 + T-cells from peripheral blood from asthmatics have different expression profiles, albeit small in magnitude, compared to healthy controls, for sets of genes involved in immune response to viral infections (upregulated) and antigen processing/presentation (downregulated).