Hypercapnia, elevated carbon dioxide (CO2), is common in advanced chronic obstructive pulmonary disease (COPD) and predicts poor clinical outcomes. Traditionally considered a consequence of disease severity, hypercapnia may drive disease progression by promoting airway dysfunction. Here, we show that hypercapnia acts as an active stressor, driving airway smooth muscle (ASM) constriction through a stromal interaction molecule 1-dependent (STIM1-dependent) pathway. Hypercapnia rapidly activates ERK, triggering sarcoplasmic reticulum calcium (Ca2+) release via phosphorylation of the inositol 1,4,5-trisphosphate receptor. ERK also induces nuclear translocation of the transcription factor c-Fos, enhancing STIM1 transcription. These responses were observed under both supraphysiological (~120 mmHg) and clinically relevant (50-60 mmHg) hypercapnia. Increased STIM1 abundance sustains store-operated Ca2+ entry (SOCE), amplifying ASM signaling. In mice, hypercapnia increased ASM and airway contractility in a STIM1-dependent manner. Human genetic analyses revealed noncoding STIM1 variants associated with reduced lung expression that were enriched in patients with COPD. These variants correlated with lower airway resistance under normocapnia; however, this benefit was lost during hypercapnia, indicating a potential gene-environment interaction. Together, our findings position STIM1 as a key mechanistic node linking hypercapnia to Ca2+ dysregulation and airway obstruction, defining a CO2/ERK/STIM1/SOCE axis with translational relevance to chronic lung disease.

DNA methylation (DNAm), capturing biological gestational age (GA) and epigenetic gestational age acceleration (EGAA), can be modified by environmental exposures. The Asthma&Allergy array is a new DNAm array developed with content focused on asthma and allergy loci. The association between content on the Asthma&Allergy array and chronological GA and EGAA has not been evaluated alone or in the context of perinatal exposures. We performed an epigenome wide association study(EWAS) based on chronological GA at single CpG sites and regions. We further constructed a multi-CpG site methylation model to predict chronological GA in cord blood from 391 newborn children from a Detroit-based birth cohort. Associations between perinatal environmental factors with GA, epigenetic gestational age (EGA), and EGAA were assessed. We identified 2,435 CpG sites associated with chronological GA. HLA class II (HLA-DRB1,HLA-DQB1,HLA-DRB6) were the most significantly associated with chronological GA. Our multi-CpG site model attained predictive accuracy (cross-validated Pearson's correlation=0.75) comparable to other EGA methods. Using genes implicated in region-based analyses (n=395 regions), the pathways most significantly enriched with chronological GA-associated CpGs included T helper 1(Th1) and 2(Th2) activation, macrophage classical activation, and IL10 signaling, which were also enriched in at least one of the other published epigenetic clocks. In multi-exposure models, prenatal indoor pet exposure and unplanned C-section were associated with EGA deceleration, while infant's first-born status was associated with EGAA. Our findings highlight enrichment for T cell modulated pathways and antigen presentation as biological processes enriched in chronological GA, as well as novel perinatal factors that may impact EGAA.

Background: Childhood-onset asthma is highly heritable, with nearly 200 risk loci identified in genome-wide association studies. Aggregated polygenic risk scores (PRSs) can be used to quantify genetic predisposition to asthma, but their power to predict asthma severity in multiancestral groups has not been previously evaluated. Objective: Our aim was to examine the predictive power of biobank-derived asthma PRSs in 4 multiancestry asthma study cohorts of children living in US urban environments. Methods: We generated PRSs for asthma, derived from a large-scale genome-wide association meta-analysis, and assessed genetic predictions across different subphenotypes of asthma and tested for associations between genetic asthma risk and measures of asthma severity. Results: PRS prediction was significantly stronger for more symptomatic asthma phenotypes (P < .001), and scores were significantly higher in difficult-to-control versus easy-to-control asthma (P = .02). Genetic risk was also significantly associated with more frequent exacerbations (P = .03), higher blood eosinophil levels (P = .01), and lower lung function (P < .001). Conclusion: Cumulative genetic risk for asthma is associated with disease severity and exacerbation risk in children with asthma.

Investigation of in utero, tissue-specific molecular pathways contributing to prenatal programming of childhood-onset asthma is needed to develop effective, targeted prevention strategies. We aimed to examine the relationship between predicted gene expression in placenta and childhood-onset asthma and to compare relationships between childhood- and adult-onset asthma. Asthma genome-wide association study published summary statistics were obtained from the UK Biobank and published placental gene expression quantitative trait loci were obtained from the Rhode Island Child Health Study. We used S-PrediXcan to evaluate and compare associations between placental predicted gene expression and childhood- and adult-onset asthma and to determine whether signals were placenta-specific. Among 8,038 tested placental predicted expression-asthma associations, we identified 56 (0.7%) genes only significantly associated with childhood-onset asthma, 12 (0.1%) genes only significantly associated with adult-onset asthma, and 18 (0.2%) shared genes. Predicted expression of several genes (ACTL9, AMN, C9orf38, C11orf30, CTSE, EFCAB13, EIF4E1B, FN1, GLS2, IL6, IVL, LZIC, MAN2A2, MEGT1, RACGAP1, SMAD6, SPATA5, TMEM25, VTI1B, WDR19) was not significantly associated with childhood- or adult-onset asthma in any non-placental tissue, suggesting that the associations may be placenta-specific. This study identified alterations in predicted expression of placental genes associated with transcriptional pathways critical to the development of asthma. We identified unique and shared pathways, particularly related to immune regulation, associated with childhood- and adult-onset. This expands our understanding of the fetal origins of asthma, highlights the placenta as an informative tissue in understanding asthma pathogenesis, and identifies target genes to prioritize for future functional studies.

BACKGROUND:DNA methylation accurately predicts chronological age, including gestational age (GA). Previous studies have used 5'-C-phosphate-G-3' sites (CpGs) on the EPIC or 450K arrays to generate epigenetic clocks for estimating GA. OBJECTIVE:Using the Asthma&Allergy array, we estimated GA and calculated GA acceleration (GAA) in cord blood DNA from 2451 ancestrally diverse participants from 7 birth cohorts investigating early life risk factors for asthma and allergic diseases and disease onset in childhood. METHODS:Two gestational epigenetic clocks were constructed: one used GA-associated CpGs in an epigenome-wide association study (EWAS) and a second used CpGs associated with GA in specific cell types. For both, we calculated GAA and tested for associations with 6 prenatal variables and 8 allergy-related childhood outcomes. We then conducted pathway analysis of expressed genes correlated with GAA and validated gene expression signatures in peripheral blood at age 2 years. RESULTS:Strong correlations between reported GA and estimated GA were observed using the EWAS and the cell-specific clocks (r = 0.90 and 0.83, respectively). Using the cell-specific clock, GAA was associated with 2 outcomes (higher birthweight, Padj = 1.69 × 10-5; less allergic asthma, Padj = .025), while the EWAS clock was associated with birthweight (Padj = 4.68 × 10-4). A significant sex-by-GAA interaction effect on birthweight, with a larger effect size in females, was observed with both clocks (EWAS, Pint = 5.77 × 10-3; cell-specific, Pint = .021). Cord blood RNA-sequencing analysis revealed upregulated IL6 and TNF and downregulated IL10 signaling pathways associated with GAA, and gene expression in blood at age 2 years further revealed associations with asthma at age 7 years. CONCLUSION:Positive correlations between GAA and inflammatory gene expression and the negative association with allergic asthma suggest that increased expression of inflammatory genes in cord blood and at age 2 years is protective against developing asthma. CpGs on the Asthma&Allergy array are accurate predictors of GA, capturing aging aspects specifically related to inflammatory programs.

We previously reported improved respiratory outcomes in babies born to pregnant smokers supplemented with vitamin C (500 mg/day) versus placebo in a randomized clinical trial. Improved respiratory outcomes persisted to 5 years of age and were associated with buccal DNA methylation (DNAm) measured using the InfiniumMethylationEPIC array. The objective of this study was to examine associations of vitamin C treatment and lung function with buccal DNAm using a custom-content Asthma Allergy array enriched for asthma and allergy loci likely to have a functional impact on gene expression. We profiled DNAm at 36,999 CpGs in loci previously associated with asthma or allergic diseases using custom-content Asthma Allergy arrays in 137 subjects (65 placebo; 72 vitamin C) with pulmonary function testing (PFT) at the 5-year visit in the “Vitamin C to Decrease the Effects of Smoking in Pregnancy on Infant Lung Function” (VCSIP) double-blind, placebo-controlled randomized clinical trial. We examined the association of buccal DNAm with (1) vitamin C treatment vs placebo, (2) forced expiratory flow between 25 and 75

This study examined whether SNPs at the 17q12-q21 locus that are associated with childhood asthma are also associated with severe respiratory syncytial virus (RSV) infection and viral load. We conducted a candidate SNP association study in the subset of RSV-infected infants who were parent-identified as White (n = 159) in the INSPIRE cohort. Nine SNPs at the 17q12-q21 locus were genotyped. We used an additive model to evaluate each SNP’s association with RSV infection severity and viral load. Replication of significant associations was tested in the TCRI cohort: infants with severe RSV illness. In INSPIRE, an SNP rs8069202-G in the GSDMA gene was associated with increased RSV viral load (and marginally associated with RSV severity). SNP rs2941504, in the PGAP3 gene, was associated with a reduced risk of RSV severity. All significant associations were directionally replicated in the TCRI cohort but were insignificant at a p-value < 0.05. The association of a SNP in GSDMA with RSV viral load and RSV infection severity suggests that GSDMA may be contributing to both severe RSV infection and asthma development. On the other hand, the association between an SNP in PGAP3 and reduced RSV infection severity suggests distinct pathways link PGAP3 to these two respiratory outcomes.

Background:Genome-wide association studies (GWAS) have identified hundreds of loci underlying adult-onset asthma (AOA) and childhood-onset asthma (COA). However, the causal variants, regulatory elements, and effector genes at these loci are largely unknown. Methods:We performed heritability enrichment analysis to determine relevant cell types for AOA and COA, respectively. Next, we fine-mapped putative causal variants at AOA and COA loci. To improve the resolution of fine-mapping, we integrated ATAC-seq data in blood and lung cell types to annotate variants in candidate cis-regulatory elements (CREs). We then computationally prioritized candidate CREs underlying asthma risk, experimentally assessed their enhancer activity by massively parallel reporter assay (MPRA) in bronchial epithelial cells (BECs) and further validated a subset by luciferase assays. Combining chromatin interaction data and expression quantitative trait loci, we nominated genes targeted by candidate CREs and prioritized effector genes for AOA and COA. Results:Heritability enrichment analysis suggested a shared role of immune cells in the development of both AOA and COA while highlighting the distinct contribution of lung structural cells in COA. Functional fine-mapping uncovered 21 and 67 credible sets for AOA and COA, respectively, with only 16% shared between the two. Notably, one-third of the loci contained multiple credible sets. Our CRE prioritization strategy nominated 62 and 169 candidate CREs for AOA and COA, respectively. Over 60% of these candidate CREs showed open chromatin in multiple cell lineages, suggesting their potential pleiotropic effects in different cell types. Furthermore, COA candidate CREs were enriched for enhancers experimentally validated by MPRA in BECs. The prioritized effector genes included many genes involved in immune and inflammatory responses. Notably, multiple genes, including TNFSF4, a drug target undergoing clinical trials, were supported by two independent GWAS signals, indicating widespread allelic heterogeneity. Four out of six selected candidate CREs demonstrated allele-specific regulatory properties in luciferase assays in BECs. Conclusions:We present a comprehensive characterization of causal variants, regulatory elements, and effector genes underlying AOA and COA genetics. Our results supported a distinct genetic basis between AOA and COA and highlighted regulatory complexity at many GWAS loci marked by both extensive pleiotropy and allelic heterogeneity.

Asthma is a common respiratory disease, with contributions from both genes and the environment and significant heterogeneity in underlying endotypes; yet, little is known about the relative contributions of each to these endotypes. To address this gap, we used nasal mucosal cell DNA methylation (DNAm) and gene expression and genotypes for 284 children in the Urban Environment and Childhood Asthma (URECA) birth cohort. Using an unbiased data-reduction approach and 37,256 CpGs on a custom-content Asthma&Allergy array, empirical Bayesian factorization was implemented to identify three DNAm signatures that were associated with phenotypes reflecting allergic diseases (allergic asthma and allergic rhinitis), allergic sensitization (atopy) (specific and total immunoglobulin E), and/or type 2 inflammation (eosinophil count and fractional exhaled nitric oxide [FeNO]). These associations were replicated in the Infant Susceptibility to Pulmonary Infections and Asthma (INSPIRE) and the Children's Respiratory Environment Workgroup (CREW) cohorts. The genes that were correlated with each signature in URECA reflected three cardinal endotypes of asthma: inhibited immune response to microbes, impaired epithelial barrier integrity, and activated type 2 immune pathways. To estimate the genetic contributions to these signatures, we used a common set of genotypes available in the three cohorts. The joint SNP heritability of each signature was 0.21 (p = 0.037), 0.26 (p = 1.7 × 10-8), and 0.17 (p = 7.7 × 10-6), respectively. The heritabilities of the DNAm signatures suggest that genetic variation contributes significantly to epigenetic signatures of allergic phenotypes and that susceptibility to the development of specific endotypes of asthma is present at birth and is poised to mediate individual epigenetic responses to early-life environments.

Background:Childhood-onset asthma is highly heritable, with nearly 200 risk loci identified in genome-wide association studies. Aggregated polygenic risk scores can be used to quantify genetic predisposition to asthma, but their power to predict asthma severity in multi-ancestral groups has not been determined. Objective:Our aim was to examine the predictive power of biobank-derived asthma polygenic risk scores in children with asthma living in urban environments. Methods:We generated polygenic risk scores for asthma, derived from a large-scale genome-wide association meta-analysis, in four multi-ancestry asthma study cohorts of children living in urban environments. We assessed genetic predictions across different subphenotypes of asthma and tested for associations between genetic asthma risk and measures of asthma severity. Results:Genetic asthma prediction was significantly stronger for more symptomatic asthma phenotypes (P<0.001). Polygenic risk scores were significantly higher in difficult-to-control vs. easy-to-control asthma (P=0.02). Genetic risk was also significantly associated with more frequent exacerbations (P=0.03), higher blood eosinophil levels (P=0.01), and lower lung function (P<0.001). Conclusion:Cumulative genetic risk for asthma is associated with disease severity and exacerbation risk in children with asthma living in urban environments.

Prenatal exposure to air pollution is an important risk factor for child health outcomes, including asthma. Identification of DNA methylation changes associated with air pollutant exposure can provide new intervention targets to improve children’s health. The aim of this study is to test the association between prenatal air pollutant exposure and DNA methylation in developmental and asthma-/allergy-relevant biospecimens (placenta, buccal, cord blood, nasal mucosa, and lavage). A subset of 2294 biospecimens collected from 1906 child participants enrolled in the Environmental Influences on Child Health Outcomes program with prenatal air pollutant and high-quality Illumina Asthma&Allergy DNA methylation array measures (n = 37 197 probes) were included. Prenatal ozone, nitrogen dioxide, and fine particulate matter were derived using residential history during pregnancy and spatiotemporal models. For each pollutant, biospecimen type, and prenatal exposure window, we estimated the effects of air pollution on gene DNA methylation levels. We compared results across pollutants, biospecimen types, and trimesters and tested for critical months of exposure using distributed lag models. DNA methylation levels at 154 out of 4746 tested genes were associated with air pollution; over 95% were exposure window, pollutant, and biospecimen-type specific. The fewest gene associations were detected in trimester 2, relative to other exposure windows. A variety of trends in methylation patterns were observed in response to lagged monthly pollution levels. Child DNA methylation changes at specific respiratory- and immune-relevant genes are associated with prenatal air pollutant exposures. Future studies should examine the relationship between these pollution-sensitive genes and child health.

Asthma, allergic rhinitis, and atopic dermatitis are common, complex traits that are frequently co-morbid and have strong genetic correlation. However, the extent to which genome-wide genetic correlation between traits reflects shared causal variants or risk genes remains unclear. To address this question, we used functional fine-mapping. We generated genomic annotations from primary cells treated with immunomodulatory stimuli, then used these data to identify likely causal variants mediating genetic risk for allergic diseases including adult-onset asthma, childhood-onset asthma, allergic rhinitis, and atopic dermatitis. After identifying likely causal variants, we combined our functional annotations with expression quantitative trait loci and activity-by-contact modeling to predict effector genes. We confirmed a high degree of genetic correlation between GWAS loci for allergic diseases, but on the local level very few of the hundreds of likely causal variants identified by functional fine-mapping were shared between diseases. Instead, we found that each allergic disease was associated with a set of mostly unique variants. Nonetheless, nearly 40% of effector genes predicted to be the regulatory targets of these variants were shared between more than one allergic disease. When we tested candidate regulatory elements containing likely causal variants, we found that regulatory elements demonstrated variable allele-specific enhancer activity depending on the cell type in which they were tested. Overall, our findings suggest a highly pleiotropic gene regulatory network underlying allergic diseases, wherein disease-specific risk variants affect different regulatory elements that converge on the same set of target genes.

Abstract Asthma has striking disparities across ancestral groups, but the molecular underpinning of these differences is poorly understood and minimally studied. A goal of the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) is to understand multi-omic signatures of asthma focusing on populations of African ancestry. RNASeq and DNA methylation data are generated from nasal epithelium including cases (current asthma, N = 253) and controls (never-asthma, N = 283) from 7 different geographic sites to identify differentially expressed genes (DEGs) and gene networks. We identify 389 DEGs; the top DEG, FN1, was downregulated in cases (q = 3.26 × 10−9) and encodes fibronectin which plays a role in wound healing. The top three gene expression modules implicate networks related to immune response (CEACAM5; p = 9.62 × 10−16 and CPA3; p = 2.39 × 10−14) and wound healing (FN1; p = 7.63 × 10−9). Multi-omic analysis identifies FKBP5, a co-chaperone of glucocorticoid receptor signaling known to be involved in drug response in asthma, where the association between nasal epithelium gene expression is likely regulated by methylation and is associated with increased use of inhaled corticosteroids. This work reveals molecular dysregulation on three axes – increased Th2 inflammation, decreased capacity for wound healing, and impaired drug response – that may play a critical role in asthma within the African Diaspora.

PDF file - 46K, KDR regions containing dense clusters of transcription factor binding motifs identified by Cluster-Buster.

PDF file - 29K, VEGFR-2 levels and disease stage. Panel A shows the log2-transformed VEGFR-2 levels from NSCLC samples of different disease stages. In panel B, Group 1 is composed of stages I and II; Group 2 is composed of stages III and IV. The result of a t-test examining the differences between the two groups is shown.

PDF file - 948K, Analysis of LD between KDR SNPs in the NSCLC cohort. The values in the squares show significant r2 values.

PDF file - 30K, MVD and tumor histology. Panel A shows the log2-transformed MVD percentage of NSCLC samples from different tumor histologies (SCC = squamous cell carcinoma; AC = adenocarcinoma; LCC = large cell carcinoma; NOS = not otherwise specified). In panel B, Group 1 is composed of squamous cell carcinomas and NSCLCs not otherwise specified/mixed; Group 2 is composed of adenocarcinomas and large cell carcinomas. The result of a t-test examining the differences between the two groups is shown.