Biology subjects

Turvey, S. E.

Publications and source records attributed to Turvey, S. E..

6 recordsLinked to original sources

bioRxiv2026

Interactions between human milk components and infant polygenic risk predict childhood atopy

BackgroundAlthough human milk (HM) confers important health benefits, how bioactive milk components (e.g., microbiota, oligosaccharides, and fatty acids) interact with infant genetics to influence childhood atopy remains poorly understood. ObjectiveWe investigated interactions between infant genomic susceptibility and exposure to maternal human milk components (HMCs) and assessed whether integrating these genetic and milk features improves prediction of childhood atopy. MethodsLeveraging infant genomic and maternal HMC data from the CHILD Cohort Study, we conducted gene-milk interaction analysis using linear regression models that integrated polygenic risk scores (PRS) of nursing infants with multiple HMC types. Gradient-boosting machines (GBMs) were used to evaluate predictive performance of HMCs and infant PRS for childhood atopy. ResultsChildhood atopy was associated with interactions between infant genomics (e.g., PRS associated with atopy) and exposure to specific human milk microbes (e.g., Abiotrophia, PBonf=0.005, {beta}=0.29), as well as networks of co-occurring HMCs (e.g., a module containing Bifidobacterium longum, 2-fucosyllactose, and eicosapentaenoic acid, P=0.009, {beta}=-12.3). A GBM integrating HMCs and infant PRS achieved the highest predictive performance for childhood atopy with an area under the curve (AUC) of 0.78, outperforming models based on individual HMC types or PRS alone (AUC range: 0.54-0.63). ConclusionIntegration of maternal HMC exposures with infant genomics reveals interaction effects that contribute to prediction of childhood atopy. Understanding how early-life exposures such as HMCs impact the health of children differently depending on their genomic profiles may facilitate the development of personalized intervention strategies to reduce the burden of these health outcomes during childhood. Key messagesO_LIInteractions between infant polygenic risk and exposure to human milk components are associated with childhood atopy. C_LIO_LINetworks of co-occurring human milk microbiota, oligosaccharides, and fatty acids may influence childhood atopy, with effects varying by infant genomic susceptibility. C_LIO_LIIntegration of human milk components with infant genomics improves prediction of childhood atopy compared with individual milk components or genomics alone. C_LI Capsule SummaryThis study demonstrates that interactions between infant polygenic risk and maternal milk components improve prediction of childhood atopy, highlighting opportunities for personalized early-life prevention strategies.

genomics↗

bioRxiv2026

Infant gut microbiomes contribute to metabolic states that impact brain function

Alterations in the gut microbiome are associated with neurodevelopmental disorders, but causal mechanisms and therapeutic strategies remain undefined. Here, we demonstrate that human infant microbiomes isolated during the first six months of life drive behavioral impairments in mice and that microbiota-based interventions restore mice to normal behavior. Early-life microbiomes from twelve infants who later exhibited cognitive deficits at 2 years old (low-scoring) transferred adverse metabolic, brain, and behavioral phenotypes to mice, in contrast to microbiomes from twenty-three cognitively typical or high-scoring infants. Deficits in mice were rescued by fecal microbiota transplant from high-scoring infants or a rationally designed consortium that promoted amino acid levels. We confirmed lower fecal amino acid concentrations in low-scoring infants and replicated the association between early-life microbiome composition and cognitive outcomes in a second geographically independent infant cohort. Altogether, we discovered an early-life microbiome-mediated metabolic state causally linked to cognitive deficits and amenable to microbial intervention.

microbiology↗

bioRxiv2025

Human milk components interact with infant genomics to modulate gut microbiota, childhood asthma and atopy

The benefits of breastfeeding are well established; however, the mechanisms by which human milk components (HMCs) impact childrens long-term health remain poorly understood. We leveraged datasets from the CHILD Cohort Study to explore how exposure to variable HMCs-- including oligosaccharides (HMOs), fatty acids (HMFAs), and microbiota (HMM)--may influence infants gut microbiota and risk of childhood asthma and atopy. We identified HMCs (e.g., HMO lacto-N-fucopentaose III and HMFA linoleic acid) associated with gut microbes and microbial networks implicated in atopic diseases. Additionally, we determined that HMCs (e.g., HMM Pseudomonas oryzihabitans) interact with infants polygenic risk scores (PRSs) to influence these gut microbial features. Integration of HMCs, gut microbiota, and disease-associated PRSs into an unsupervised machine-learning model that clustered two groups of infants with differing disease prevalence. Our findings suggest that HMCs influence childhood asthma and atopy through modifications to the gut microbiota and modulated by interactions with infant genomics.

genomics↗

bioRxiv2025

Advancing Pediatric and Longitudinal DNA Methylation Studies with CellsPickMe, an Integrated Blood Cell Deconvolution Method

Prospective birth cohorts offer the potential to interrogate the relation between early life environment and embedded biological processes such as DNA methylation (DNAme). These association studies are frequently conducted in the context of blood, a heterogeneous tissue composed of diverse cell types. Accounting for this cellular heterogeneity across samples is essential, as it is a main contributor to inter-individual DNAme variation. Integrated blood cell deconvolution of pediatric and longitudinal birth cohorts poses a major challenge, as existing methods fail to account for the distinct cell population shift between birth and adolescence. In this paper, we critically evaluated the reference-based deconvolution procedure and optimized its prediction accuracy for longitudinal birth cohorts using DNAme data from the Canadian Healthy Infant Longitudinal Development (CHILD) cohort. The optimized algorithm, CellsPickMe, integrates cord and adult references and picks DNAme features for each population of cells with machine learning algorithms. It demonstrated improved deconvolution accuracy in cord, pediatric, and adult blood samples compared to existing benchmark methods. CellsPickMe supports blood cell deconvolution across early developmental periods under a single framework, enabling cross-time-point integration of longitudinal DNAme studies. Given the increased resolution of cell populations predicted by CellsPickMe, this R package empowers researchers to explore immune system dynamics using DNAme data in population studies across the life course.

bioinformatics↗

bioRxiv2023

Persistent DNA methylation changes associated with prenatal NO2 exposure in a Canadian prospective birth study

BackgroundAccumulating evidence suggests prenatal air pollution exposure alters DNA methylation (DNAm), which could go on to affect long-term health. However, it remains unclear whether prenatal DNAm alterations persist through early life. Identifying DNAm changes that persist from birth into childhood would provide greater insight into the molecular mechanisms that most likely contribute to the association of prenatal air pollution exposure with health outcomes such as atopic disease. ObjectivesThis study investigated the persistence of DNAm changes associated with prenatal NO2 exposure (a surrogate measure of traffic-related air pollution) at age one to begin characterizing which DNAm changes most likely to contribute to atopic disease. MethodsWe used an atopy-enriched subset of CHILD study participants (N=145) to identify individual and regional cord blood DNAm differences associated with prenatal NO2, followed by an investigation of persistence in age one peripheral blood. As we had repeated DNAm measures, we also isolated postnatal-specific DNAm changes and examined their association with NO2 exposure in the first year of life. MANOVA tests were used to examine the association between DNAm changes associated with NO2 and child wheeze and atopy. ResultsWe identified 24 regions of altered cord blood DNAm, with several annotated to HOX genes. Two regions annotated to MPDU1 and C5orf63 were significantly associated with age one wheeze. Further, we found the effect of prenatal NO2 exposure across CpGs within all altered regions remained similar at age one. A single region of postnatal-specific DNAm annotated to HOXB6 was associated with year one NO2 and age one atopy. DiscussionRegional cord blood DNAm changes associated with prenatal NO2 exposure persist through at least the first year of life, and some of these changes are associated with age one wheeze. The early-postnatal period remains a sensitive window to DNAm perturbations that may also influence child health.

genetics↗

bioRxiv2019

Non-nutritive sweetener consumption during pregnancy affects adiposity in mouse and human offspring

Overweight and obesity affect over 20% of children worldwide. Emerging evidence shows that nonnutritive sweeteners (NNS) could adversely influence weight gain and metabolic health, particularly during critical periods of development. Thus, we aimed to investigate the impact of prenatal NNS exposure on postnatal growth and adiposity. Among 2298 families participating in the CHILD cohort study, children born to mothers who regularly consumed NNS during pregnancy had elevated body mass index and adiposity at 3 years of age. In a complementary study designed to eliminate confounding by human lifestyle factors and investigate causal mechanisms, we exposed pregnant mice and cultured adipocytes to NNS (aspartame or sucralose) at doses relevant to human consumption. In mice, maternal NNS exposure caused elevated body weight, adiposity and insulin resistance in offspring, especially in males. Further, in 3T3-L1 pre-adipocyte cells, sucralose exposure during early stages of differentiation caused increased lipid accumulation and expression of adipocyte differentiation genes (e.g. C/EBP-, FABP4, FAS). The same genes were upregulated in the adipose tissue of male mouse offspring born to sucralose-fed dams. Together, these clinical and experimental findings provide evidence suggesting that maternal NNS consumption induces obesity risk in the offspring through effects on adiposity and adipocyte differentiation.\n\nOne Sentence SummaryMaternal consumption of non-nutritive sweeteners during pregnancy stimulates adipocyte differentiation, insulin resistance, weight gain, and adiposity in mouse and human offspring.

developmental biology↗