Biology subjects

Haworth, S.

Publications and source records attributed to Haworth, S..

5 recordsLinked to original sources

bioRxiv2026

Circadian and Sex-Specific Responses to Alternaria alternata in Allergic Airway Inflammation

Asthma severity and immune responses are regulated by circadian rhythms, yet the role of circadian timing in fungal allergen-induced airway inflammation remains poorly defined. Alternaria alternata, a clinically relevant fungal allergen, is strongly associated with severe asthma exacerbations and persistent airway dysfunction. Using a preclinical mouse model, we investigated whether pulmonary responses to Alternaria exposure are influenced by time of day and sex. We demonstrate that Alternaria induces allergic airway inflammation, airway hyperresponsiveness (AHR), and epithelial barrier disruption in a circadian- and sex-dependent manner. Female mice exhibited enhanced eosinophilic, neutrophilic, interstitial macrophage, and dendritic cell infiltration predominantly at Zeitgeber Time 0 (ZT0), whereas males showed stronger inflammatory responses at ZT12. Alternaria exposure increased IL-33 release and promoted ILC2 and Th2 cell accumulation, with distinct temporal patterns between sexes. Cytokine and chemokine profiling revealed robust Th2, proinflammatory, and Th17 responses that varied with exposure time, with higher responses at ZT12 in females and ZT0 in males. Markers of tissue injury, including lactate dehydrogenase and uric acid, followed similar circadian-dependent trends. Functionally, Alternaria-exposed mice displayed greater AHR during the resting phase, particularly in males. Additionally, Alternaria disrupted epithelial junctional proteins (E-cadherin and ZO-1) and altered expression of core circadian clock proteins CLOCK, BMAL1, and REV-ERB. Mechanistically, peak inflammation coincided with enhanced STAT1, STAT3, and STAT6 activation. Collectively, these findings identify circadian timing and sex as key determinants of fungal allergen-induced airway inflammation and suggest chronotherapeutic approaches may improve asthma outcomes.

immunology↗

bioRxiv2019

Inference and visualization of phenome-wide causal relationships using genetic data: an application to dental caries and periodontitis.

BackgroundHypothesis-free Mendelian randomization studies provide a way to assess the causal relevance of a trait across the human phenome but can be limited by statistical power or complicated by horizontal pleiotropy. The recently described latent causal variable (LCV) approach provides an alternative method for causal inference which might be useful in hypothesis-free experiments. MethodsWe developed an automated pipeline for phenome-wide tests using the LCV approach including steps to estimate partial genetic causality, filter to a meaningful set of estimates, apply correction for multiple testing and then present the findings in a graphical summary termed a causal architecture plot. We apply this process to body mass index and lipid traits as exemplars of traits where there is strong prior expectation for causal effects and dental caries and periodontitis as exemplars of traits where there is a need for causal inference. ResultsThe results for lipids and BMI suggest that these traits are best viewed as creating consequences on a multitude of traits and conditions, thus providing additional evidence that supports viewing these traits as targets for interventions to improve health. On the other hand, caries and periodontitis are best viewed as a downstream consequence of other traits and diseases rather than a cause of ill health. ConclusionsThe automated process is available as part of the MASSIVE pipeline from the Complex-Traits Genetics Virtual Lab (https://vl.genoma.io) and results are available in (https://view.genoma.io). We propose causal architecture plots based on phenome-wide partial genetic causality estimates as a way visualizing the overall causal map of the human phenome. Key messagesO_LIThe latent causal variable approach uses summary statistics from genome-wide association studies to estimate a parameter termed genetic causality proportion. C_LIO_LISystematic estimation of genetic causality proportion for many pairs of traits provides an alternative method for phenome-wide causal inference with some theoretical and practical advantages compared to phenome-wide Mendelian randomization. C_LIO_LIUsing this approach, we confirm that lipid traits are an upstream risk factor for other traits and diseases, and we identify that dental diseases are predominantly a downstream consequence of other traits rather than a cause of poor systemic health. C_LIO_LIThe method assumes no bidirectional causality and no confounding by environmental correlates of genotypes, so care is needed when these assumptions are not met. C_LIO_LIWe developed an automated and accessible pipeline for estimating phenome-wide causal relationships and generating interactive visual summaries. C_LI

genetics↗

bioRxiv2018

Low-frequency variation in TP53 has large effects on head circumference and intracranial volume

Cranial growth and development affects the closely related traits of head circumference (HC) and intracranial volume (ICV). Here we model the developmental genetic architecture of HC, showing this is genetically stable and correlated with genetic determinants of ICV. Investigating up to 46,000 children and adults of European descent, we identify association with final HC and/or final ICV+HC at 9 novel common and low-frequency loci, illustrating that genetic variation from a wide allele frequency spectrum contributes to cranial growth. The largest effects are reported for low-frequency variants within TP53, with 0.5 cm wider heads in increaser-allele carriers versus non-carriers during mid-childhood.

genetics↗

bioRxiv2018

Common genetic variants and health outcomes appear geographically structured in the UK Biobank sample: Old concerns returning and their implications.

Introductory paragraphThe inclusion of genetic data in large studies has enabled the discovery of genetic contributions to complex traits and their application in applied analyses including those using genetic risk scores (GRS) for the prediction of phenotypic variance. If genotypes show structure by location and coincident structure exists for the trait of interest, analyses can be biased. Having illustrated structure in an apparently homogeneous collection, we aimed to a) test for geographical stratification of genotypes in UK Biobank and b) assess whether stratification might induce bias in genetic association analysis.\n\nWe found that single genetic variants are associated with birth location within UK Biobank and that geographic structure in genetic data could not be accounted for using routine adjustment for study centre and principal components (PCs) derived from genotype data. We found that GRS for complex traits do appear geographically structured and analysis using GRS can yield biased associations. We discuss the likely origins of these observations and potential implications for analysis within large-scale population based genetic studies.

genetics↗

bioRxiv2017

Consortium genome-wide meta-analysis for childhood dental caries traits

Prior studies suggest dental caries traits in children and adolescents are partially heritable, but there has been no large-scale consortium genome-wide association study (GWAS) to date. We therefore performed GWAS for caries in participants aged 2.5-18.0 years from 9 contributing centers. Phenotype definitions were created for the presence or absence of treated or untreated caries, stratified by primary and permanent dentition. All studies tested for association between caries and genotype dosage (imputed to Haplotype Reference Consortium or 1000 Genomes phase 1 version 3 panels) accounting for population stratification. Fixed-effects meta-analysis was performed weighted by inverse standard error. Analysis included up to 19,003 individuals (7,530 affected) for primary teeth and 13,353 individuals (5,875 affected) for permanent teeth. Evidence for association with caries status was observed at rs1594318-C for primary teeth (intronic within ALLC, Odds Ratio (OR) 0.85, Effect Allele Frequency (EAF) 0.60, p 4.13e-8) and rs7738851-A (intronic within NEDD9, OR 1.28, EAF 0.85, p 1.63e-8) for permanent teeth. Consortium-wide estimated heritability of caries was low (h2 of 1% [95% CI: 0%:7%] and 6% [95% CI 0%:13%] for primary and permanent dentitions, respectively) compared to corresponding within-study estimates (h2 of 28%, [95% CI: 9%:48%] and 17% [95% CI:2%:31%]) or previously published estimates. This study was designed to identify common genetic variants with modest effects which are consistent across different populations. We found few single variants associated with caries status under these assumptions. Phenotypic heterogeneity between cohorts and limited statistical power will have contributed; these findings could also reflect complexity not captured by our study design, such as genetic effects which are conditional on environmental exposure.\n\nAuthor summaryDental caries (tooth decay) is a common disease in children. Previous studies suggest genetic factors alter caries risk, but to date there is a gap of knowledge in identifying which specific genetic variants are responsible. We undertook analysis in a consortium including around 19,000 children and investigated whether any of 8 million common genetic variants were associated with risk of caries in primary (milk) or permanent teeth. If identified, these variants are used as tags to highlight genes which may be involved in a disease. We identified variants in two loci associated with caries status; in the primary (rs1594318) and permanent dentition (rs7738851). The former is intronic in ALLC, a gene with poorly understood function. The latter is an intronic variant within NEDD9, a gene which has several known functions including a role in development of craniofacial structures. To gain a more comprehensive understanding of genetic effects which influence caries larger studies and a better understanding of environmental modifiers or interactions with genetic effects are required.

genetics↗