Biology subjects

Mansell, T.

Publications and source records attributed to Mansell, T..

6 recordsLinked to original sources

bioRxiv2026

Genetic, intrinsic, and environmental determinants of innate immune cytokine responses in healthy four-year-old children

Abstract/SummaryInnate immune responses are crucial for host defence but vary markedly between individuals. Although determinants of this variation are well characterised in adults, data from healthy children remain scarce. We therefore profiled whole-blood cytokine responses to innate immune stimulation in 286 children aged approximately four years and examined genetic, host-intrinsic, and environmental correlates of response. Cytokine responses showed marked inter-individual heterogeneity and stimulus-specific patterns. The top 50 genetic variants explained a substantial proportion ([~]20-45%) of this variance across many stimulus conditions, including a biologically coherent association of the STING locus with cGAMP-induced cytokine production. In contrast, sex, age, adiposity, and perinatal variables showed limited or modest associations. Systemic inflammatory biomarkers of systemic inflammation (hsCRP, glycoprotein acetyls, granulocyte-to-lymphocyte ratio) were strongly positively associated with cytokine responses. Finally, seasonal population-level viral infection burden was positively associated with antiviral and inflammatory cytokine responses. Collectively, these findings advance our understanding of variation in early-life whole-blood cytokine responses, underscoring this developmental period as a critical window for understanding immune development trajectories relevant to long-term health.

immunology↗

bioRxiv2025

Prenatal Environmental Determinants of Aromatase Brain-Promoter Methylation in Cord Blood: Chemical, Airborne, Pharmacological, and Nutritional Factors

Aromatase, an enzyme encoded by the gene CYP19A1, plays central roles in neurodevelopment. In the brain, its function is to convert androgens into neuroestrogens, ensuring balanced hormonal signalling. Both animal experiments and human studies have shown that, in males, disruption of aromatase, either genetically or epigenetically, can increase symptoms of autism. Prenatal exposure to bisphenol A (BPA), a common plastic chemical, can increase levels of DNA methylation--a key epigenetic modification--at the brain-specific CYP19A1 promoter, P1.f, reducing CYP19A1 expression. However, the extent to which other neurodevelopmentally relevant environmental exposures influence P1.f methylation remains unclear. Here, in the Barwon Infant Study (BIS) birth cohort (N = 906), we analysed the association between 25 prenatal exposures (from five classes previously linked to neurodevelopmental outcomes: manufactured chemicals, air pollution, and pharmacological, nutrition and sunlight-related factors) and methylation of the CYP19A1 P1.f promoter using Weighted Quantile Sum (WQS) regression. We found that the WQS mixture index, a weighted combination of the prenatal exposures, was positively associated with higher P1.f methylation (Adjusted Mean Difference (AMD) = 0.712 (95% CI 0.11, 1.315), p = 0.021), indicating reduced brain aromatase activity. Prenatal exposures with the strongest contribution to the mixture effect included bisphenols (including BPA), reduced sunlight, household mould, phthalates, low folate intake, and air pollution. These findings highlight epigenetic modification of the aromatase gene as a biologically plausible, convergent mechanism through which multiple environmental risk factors for autism may exert effects.

genomics↗

bioRxiv2025

Prenatal DEHP plastic chemical exposure increases the likelihood of child autism and ADHD symptoms through epigenetic programming

Increasing evidence implicates prenatal exposure to di-(2-ethylhexyl) phthalate (DEHP), a common endocrine-disrupting plastic chemical, in autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). However, the underlying mechanisms are poorly understood. Here we examined whether cord blood DNA methylation, a key epigenetic marker, mediates the association between prenatal DEHP exposure and ASD/ADHD symptoms in 847 children enrolled in the Barwon Infant Study. ASD and ADHD are complex phenotypes characterised by differences at the gene regulatory network and neuronal circuit level, where heterogeneous genetic and environmental risk factors converge. Accordingly, we employed a data-driven computational strategy that helped elucidate broader functional epigenetic signatures of ASD and ADHD elicited by DEHP exposure. This included (1) a methylation profile score for DEHP exposure (MPSDEHP), and (2) an analysis of co-methylated gene networks. Causal mediation analysis demonstrated that both MPSDEHP and a DEHP-associated network of co-methylated genes mediated the effect of DEHP exposure on increased ASD and ADHD symptoms at ages 2 and 4 years (proportion of effect mediated ranged from 0.21 to 0.80). The co-methylation network was enriched for neural cell-type markers, ASD risk genes (including FOXP1, SHANK2, and PLXNB1), and targets of endocrine receptors previously linked to DEHP (including targets of the estrogen receptor ER and the glucocorticoid receptor GR), providing biological plausibility. We validated key results in independent blood (n=66) and postmortem brain (n=40) DNA methylation datasets. These findings provide mechanistic evidence linking DEHP to ASD and ADHD symptoms and reinforce growing concerns regarding the risks of prenatal exposure.\n\nSignificanceExposure to endocrine-disrupting plastic chemicals has been linked to adverse neurodevelopment, but the underlying biological mechanisms remain unclear. We demonstrate that prenatal exposure to di-(2-ethylhexyl) phthalate (DEHP), a common plasticizer, increases autism and ADHD symptoms through alterations in DNA methylation, a key epigenetic regulator of gene activity. Using birth cohort data, we identify epigenetic signatures of prenatal DEHP exposure, including alterations in an endocrine-related co-methylation network enriched for neural cell-type markers and known autism-associated genes. These signatures mediate the effects of DEHP on autism and ADHD symptoms and are also associated with autism in external blood and postmortem-brain datasets, providing independent validation. This causal evidence further underscores concerns regarding the consequences of prenatal plastic-chemical exposure on the developing brain.

neuroscience↗

bioRxiv2024

Exploring putative enteric methanogenesis inhibitors using molecular simulations and a graph neural network

Atmospheric methane (CH4) acts as a key contributor to global warming. As CH4 is a short-lived climate forcer (12 years atmospheric lifespan), its mitigation represents the most promising means to address climate change in the short term. Enteric CH4 (the biosynthesized CH4 from the rumen of ruminants) represents 5.1% of total global greenhouse gas (GHG) emissions, 23% of emissions from agriculture, and 27.2% of global CH4 emissions. Therefore, it is imperative to investigate methanogenesis inhibitors and their underlying modes of action. We hereby elucidate the detailed biophysical and thermodynamic interplay between anti-methanogenic molecules and cofactor F430 of methyl coenzyme M reductase and interpret the stoichiometric ratios and binding affinities of sixteen inhibitor molecules. We leverage this as prior in a graph neural network to first functionally cluster these sixteen known inhibitors among [~]54,000 bovine metabolites. We subsequently demonstrate a protocol to identify precursors to and putative inhibitors for methanogenesis, based on Tanimoto chemical similarity and membrane permeability predictions. This work lays the foundation for computational and de novo design of inhibitor molecules that retain/ reject one or more biochemical properties of known inhibitors discussed in this study. COVER ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=146 SRC="FIGDIR/small/613350v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@1fd4518org.highwire.dtl.DTLVardef@c34d87org.highwire.dtl.DTLVardef@16eef9org.highwire.dtl.DTLVardef@1a33512_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2022

Genomic contributions to infant and toddler vocabulary scores: Implications for association with health-, cognition- and behaviour-related outcomes

BackgroundThe number of words children produce (expressive vocabulary) and understand (receptive vocabulary) changes rapidly during early development, partially due to genetic factors, although mechanisms are not well understood. Here, we performed a meta-genome-wide association study within the EAGLE consortium and investigated polygenic overlap with later-life traits, including Attention-Deficit/Hyperactivity Disorder (ADHD) and cognition. MethodsWe studied 37,913 parent-reported vocabulary size measures (English, Dutch, Danish) for 17,298 children of European descent. Meta-analyses were performed for early-phase expressive (infancy, 15-18 months), late-phase expressive (toddlerhood, 24-38 months) and late-phase receptive (toddlerhood, 24-38 months) vocabulary. Subsequently, we estimated Single-Nucleotide Polymorphism heritability (SNP-h2), genetic correlations (rg) and modelled underlying genetic factor structures with multivariate models. ResultsContributions of common genetic variation to early-life vocabulary were modest (SNP-h2: 0.08(SE=0.01) to 0.24(SE=0.03)) and multi-factorial. Genetic overlap between infant expressive and toddler receptive vocabulary was near zero (rg=0.07(SE=0.10)), although both measures were genetically related to toddler expressive vocabulary (rg=0.69(SE=0.14) and rg=0.67(SE=0.16), respectively). Consistently, polygenic association patterns with later-life traits differed: Genetic links with cognition emerged only in toddlerhood (e.g. toddler receptive vocabulary and intelligence: rg=0.36(SE=0.12)), despite comparable study power for infant measures. Furthermore, increased polygenic ADHD risk was associated with larger infant expressive vocabulary (rg=0.23(SE=0.08)), as confirmed by ADHD-symptom-based follow-up analyses in the Avon Longitudinal Study of Parents and Children (ALSPAC-rg=0.54(SE=0.26)). Genetic relationships with toddler receptive vocabulary were, however, opposite (ALSPAC-rg=-0.74(SE=0.23)), highlighting developmental changes in genetic architectures. ConclusionsMultiple genetic components contribute to early-life vocabulary development, shaping polygenic association patterns with later-life ADHD symptoms and cognition.

genomics↗

bioRxiv2017

Improving Designer Glycan Production in Escherichia coli through Model-Guided Metabolic Engineering

Asparagine-linked (N-linked) glycosylation is the most common protein modification in eukaryotes, affecting over two-thirds of the proteome. Glycosylation is also critical to the pharmacokinetic activity and immunogenicity of many therapeutic proteins currently produced in complex eukaryotic hosts. The discovery of a protein glycosylation pathway in the pathogen Campylobacter jejuni and its subsequent transfer into laboratory strains of Escherichia coli has spurred great interest in glycoprotein production in prokaryotes. However, prokaryotic glycoprotein production has several drawbacks, including insufficient availability of non-native glycan precursors. To address this limitation, we used a constraint-based model of E. coli metabolism in combination with heuristic optimization to design gene knockout strains that overproduced glycan precursors. First, we incorporated reactions associated with C. jejuni glycan assembly into a genome-scale model of E. coli metabolism. We then identified gene knockout strains that coupled optimal growth to glycan synthesis. Simulations suggested that these growth-coupled glycan overproducing strains had metabolic imbalances that rerouted flux toward glycan precursor synthesis. We then validated the model-identified knockout strains experimentally by measuring glycan expression using a flow cytometric-based assay involving fluorescent labeling of cell surface-displayed glycans. Overall, this study demonstrates the promising role that metabolic modeling can play in optimizing the performance of a next-generation microbial glycosylation platform.

systems biology↗