Genetic susceptibility to asthma increases the vulnerability to indoor air pollution

INTRODUCTION: Indoor air pollution and maternal smoking during pregnancy are associated with respiratory symptoms in infants, but little is known about the direct association with lung function or interactions with genetic risk factors. We examined associations of exposure to indoor particulate matter with a 50% cut-off aerodynamic diameter of 10 µm (PM10) and maternal smoking with infant lung function and the role of gene-environment interactions. METHODS: Data from the Drakenstein Child Health Study, a South African birth cohort, were analysed (n=270). Lung function was measured at 6 weeks and 1 year of age, and lower respiratory tract infection episodes were documented. We measured pre- and postnatal PM10 exposures using devices placed in homes, and prenatal tobacco smoke exposure using maternal urine cotinine levels. Genetic risk scores determined from associations with childhood-onset asthma in the UK Biobank were used to investigate effect modifications. RESULTS: Pre- and postnatal exposure to PM10 as well as maternal smoking during pregnancy were associated with reduced lung function at 6 weeks and 1 year as well as with lower respiratory tract infection in the first year. Due to a significant interaction between the genetic risk score and prenatal exposure to PM10, infants carrying more asthma-related risk alleles were more susceptible to PM10-associated reduced lung function (pinteraction=0.007). This interaction was stronger in infants with Black African ancestry (pinteraction=0.001) and nonexistent in children with mixed ancestry (pinteraction=0.876). CONCLUSIONS: PM10 and maternal smoking exposures were associated with reduced lung function, with a higher susceptibility for infants with an adverse genetic predisposition for asthma that also depended on the infant's ancestry

Epigenetic aging in children from a small-scale farming society in The Congo Basin: Associations with child growth and family conflict

Developmental environments influence individuals' long-term health trajectories, and there is increasing emphasis on understanding the biological pathways through which this occurs. Epigenetic aging evaluates DNA methylation at a suite of distinct CpG sites in the genome, and epigenetic age acceleration (EAA) is linked to heightened chronic morbidity and mortality risks in adults. Consequently, EAA provides insights on trajectories of biological aging, which early life experiences may help shape. However, few studies have measured correlates of children's epigenetic aging, especially outside of the U.S. and Europe. In particular, little is known about how children's growth and development relate to EAA in ecologies in which energetic and pathogenic stressors are commonplace. We studied EAA from dried blood spots among Bondongo children (n = 54) residing in a small-scale, fisher-farmer society in a remote region of the Republic of the Congo. Here, infectious disease burdens and their resultant energy demands are high. Children who were heavier for height or taller for age, respectively, exhibited greater EAA, including intrinsic EAA, which is considered to measure EAA internal to cells. Furthermore, we found that children in families with more conflict between parents had greater intrinsic EAA. These results suggest that in contexts in which limited energy must be allocated to competing demands, more investment in growth may coincide with greater EAA, which parallels findings in European children who do not face similar energetic constraints. Our findings also indicate that associations between adverse family environments and greater intrinsic EAA were nonetheless observable but only after adjustment for covariates relevant to the energetically and immunologically demanding nature of the local ecology

The PedBE clock accurately estimates DNA methylation age in pediatric buccal cells

The development of biological markers of aging has primarily focused on adult samples. Epigenetic clocks are a promising tool for measuring biological age that show impressive accuracy across most tissues and age ranges. In adults, deviations from the DNA methylation (DNAm) age prediction are correlated with several age-related phenotypes, such as mortality and frailty. In children, however, fewer such associations have been made, possibly because DNAm changes are more dynamic in pediatric populations as compared to adults. To address this gap, we aimed to develop a highly accurate, noninvasive, biological measure of age specific to pediatric samples using buccal epithelial cell DNAm. We gathered 1,721 genome-wide DNAm profiles from 11 different cohorts of typically developing individuals aged 0 to 20 y old. Elastic net penalized regression was used to select 94 CpG sites from a training dataset (n = 1,032), with performance assessed in a separate test dataset (n = 689). DNAm at these 94 CpG sites was highly predictive of age in the test cohort (median absolute error = 0.35 y). The Pediatric-Buccal-Epigenetic (PedBE) clock was characterized in additional cohorts, showcasing the accuracy in longitudinal data, the performance in nonbuccal tissues and adult age ranges, and the association with obstetric outcomes. The PedBE tool for measuring biological age in children might help in understanding the environmental and contextual factors that shape the DNA methylome during child development, and how it, in turn, might relate to child health and disease.publishe

Systematic evaluation of DNA methylation age estimation with common preprocessing methods and the Infinium MethylationEPIC BeadChip array

Background: The capacity of technologies measuring DNA methylation (DNAm) is rapidly evolving, as are the options for applicable bioinformatics methods. The most commonly used DNAm microarray, the Illumina Infinium HumanMethylation450 (450K array), has recently been replaced by the Illumina Infinium HumanMethylationEPIC (EPIC array), nearly doubling the number of targeted CpG sites. Given that a subset of 450K CpG sites is absent on the EPIC array and that several tools for both data normalization and analyses were developed on the 450K array, it is important to assess their utility when applied to EPIC array data. One of the most commonly used 450K tools is the pan-tissue epigenetic clock, a multivariate predictor of biological age based on DNAm at 353 CpG sites. Of these CpGs, 19 are missing from the EPIC array, thus raising the question of whether EPIC data can be used to accurately estimate DNAm age. We also investigated a 71-CpG epigenetic age predictor, referred to as the Hannum method, which lacks 6 probes on the EPIC array. To evaluate these epigenetic clocks in EPIC data properly, a prior assessment of the effects of data preprocessing methods on DNAm age is also required. Methods: DNAm was quantified, on both the 450K and EPIC platforms, from human primary monocytes derived from 172 individuals. We calculated DNAm age from raw, and three different preprocessed data forms to assess the effects of different processing methods on the DNAm age estimate. Using an additional cohort, we also investigated DNAm age of peripheral blood mononuclear cells, bronchoalveolar lavage, and bronchial brushing samples using the EPIC array. Results: Using monocyte-derived data from subjects on both the 450K and EPIC, we found that DNAm age was highly correlated across both raw and preprocessing methods (r > 0.91). Thus, the correlation between chronological age and the DNAm age estimate is largely unaffected by platform differences and normalization methods. However, we found that the choice of normalization method and measurement platform can lead to a systematic offset in the age estimate which in turn leads to an increase in the median error. Comparing the 450K and EPIC DNAm age estimates, we observed that the median absolute difference was 1.44–3.10 years across preprocessing methods. Conclusions: Here, we have provided evidence that the epigenetic clock is resistant to the lack of 19 CpG sites missing from the EPIC array as well as highlighted the importance of considering the technical variance of the epigenetic when interpreting group differences below the reported error. Furthermore, our study highlights the utility of epigenetic age acceleration measure, the residuals from a linear regression of DNAm age on chronological age, as the resulting values are robust with respect to normalization methods and measurement platforms.Medicine, Faculty ofOther UBCNon UBCMedical Genetics, Department ofMedicine, Department ofRespiratory Medicine, Division ofReviewedFacult

Fetal sex-specific epigenetic associations with prenatal maternal depressive symptoms

Prenatal maternal mental health is a global health challenge with poorly defined biological mechanisms. We used maternal blood samples collected during the second trimester from a Singaporean longitudinal birth cohort study to examine the association between inter-individual genome-wide DNA methylation and prenatal maternal depressive symptoms. We found that (1) the maternal methylome was significantly associated with prenatal maternal depressive symptoms only in mothers with a female fetus; and (2) this sex-dependent association was observed in a comparable, UK-based birth cohort study. Qualitative analyses showed fetal sex-specific differences in genomic features of depression-related CpGs and genes mapped from these CpGs in mothers with female fetuses implicated in a depression-associated WNT/β-catenin signaling pathway. These same genes also showed enriched expression in brain regions linked to major depressive disorder. We also found similar female-specific associations with fetal-facing placenta methylome. Our fetal sex-specific findings provide evidence for maternal-fetal interactions as a mechanism for intergenerational transmission

The PedBE clock accurately estimates DNA methylation age in pediatric buccal cells.

The development of biological markers of aging has primarily focused on adult samples. Epigenetic clocks are a promising tool for measuring biological age that show impressive accuracy across most tissues and age ranges. In adults, deviations from the DNA methylation (DNAm) age prediction are correlated with several age-related phenotypes, such as mortality and frailty. In children, however, fewer such associations have been made, possibly because DNAm changes are more dynamic in pediatric populations as compared to adults. To address this gap, we aimed to develop a highly accurate, noninvasive, biological measure of age specific to pediatric samples using buccal epithelial cell DNAm. We gathered 1,721 genome-wide DNAm profiles from 11 different cohorts of typically developing individuals aged 0 to 20 y old. Elastic net penalized regression was used to select 94 CpG sites from a training dataset (n = 1,032), with performance assessed in a separate test dataset (n = 689). DNAm at these 94 CpG sites was highly predictive of age in the test cohort (median absolute error = 0.35 y). The Pediatric-Buccal-Epigenetic (PedBE) clock was characterized in additional cohorts, showcasing the accuracy in longitudinal data, the performance in nonbuccal tissues and adult age ranges, and the association with obstetric outcomes. The PedBE tool for measuring biological age in children might help in understanding the environmental and contextual factors that shape the DNA methylome during child development, and how it, in turn, might relate to child health and disease