Background:Extreme-phenotype comparisons allowed the discovery of novel asthma genetic risk loci. However, this approach remains unexplored in epigenome-wide association studies (EWAS). We aimed to identify bulk and cell-specific methylation markers of asthma with severe exacerbations across diverse ancestry groups. Methods:We conducted a meta-EWAS of 739,543 CpGs in whole blood among 1,192 African American and Latino pediatric populations, comparing non-asthmatics and asthma exacerbators. Genome-wide CpGs were followed up for replication in a meta-analysis across 1,516 ethnically diverse participants and in a cross-tissue evaluation of 393 nasal samples. We conducted differentially methylated region (DMRs), cell-type-deconvoluted, and quantitative trait loci analyses (whole-genome sequencing n=1,668; RNA-seq n=1,209). We examined enrichment in traits, pathways, and druggable genes, and analyzed DNAm predictors of plasma proteins and aging. Results:DNAm at 505 CpGs and 119 DMRs in whole blood were associated with asthma exacerbations (p <9x10-8, λ=1.05). We replicated 25 CpGs in blood cells, cross-validated 7 in nasal samples, and detected 42 cell-specific DNAm markers mainly driven by T cells. DNAm at 134 CpGs was associated with gene expression in whole blood, including 118 associations with T-cell receptor genes, and 446 CpGs were regulated by > 1 genetic variant. We found enrichment for previous associations with environmental exposures, immune disorders, immune and inflammatory pathways, and druggable genes by developmental drugs. 21 methylation-predicted plasma proteins, involved in host defense, and one lung aging clock were associated with asthma exacerbations. Conclusions:The first meta-EWAS of extreme asthma phenotypes identified hundreds of novel DNAm markers, suggesting novel methylation biomarkers and candidate drugs for asthma and supporting the role of T cells.

Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals (P < 5 × 10-9). Notably, we identified and replicated a novel low frequency single nucleotide polymorphism (SNP) in MTMR3 that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the POC5 and DMD loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine.

RATIONALE Asthma, the most common chronic childhood disease, consists of heterogeneous subtypes that respond differently to therapies. Current biomarkers, including blood eosinophil count (BEC) and total immunoglobulin E (IgE) level, inform the selection of type 2 (T2)-targeted treatments (i.e., biologics) but their predictive accuracy varies across diverse populations. Precision medicine efforts are hindered by unrecognized heterogeneity within asthma endotypes and their associated biomarkers. METHODS We developed Phenotype Aware Component Analysis (PACA), a contrastive machine-learning approach, to isolate disease-specific heterogeneity in DNA methylation (DNAm) data from pediatric asthma cohorts. Using whole-blood DNAm from Latino (discovery; n=1,016) and African American (replication; n=756) cohorts, we applied PACA to identify the primary latent axis of variation distinguishing asthma patients from healthy controls. This yielded a DNAm stratification score based on 7,662 CpGs, which we applied to predict bronchodilator response (BDR) to albuterol. We also examined its associations with clinical variables, eosinophil-specific DNAm, and gene expression, and assessed its predictive value for omalizumab response in an independent cohort (Upchurch et al.). RESULTS While BEC and IgE correlate with BDR overall, their predictive value for BDR is observed only in patients with high DNAm scores. BEC correlates with BDR in patients with upper-quartile DNAm scores (odds ratio [OR] for response 1.12; 95% CI [1.04, 1.22]; P=7.9e-4) but not lower-quartile scores (OR 1.05; 95% CI [0.95, 1.17]; P=0.21). Similarly, IgE correlates with BDR in above-median scores (OR 1.42; 95% CI [1.24, 1.63]; P=3.9e-7) but not below-median scores (OR 1.05; 95% CI [0.92, 1.2]; P=0.57). These findings remain consistent within the T2-high endotype but not in T2-low patients, suggesting that our DNAm score identifies previously unrecognized heterogeneity in T2-high asthma. T2-high patients with high DNAm scores display clinical features associated with biologic therapy response, including higher exacerbation scores, lower body mass index (BMI), recent oral corticosteroid use, and reduced lung function. T2-high patients with high DNAm scores exhibited eosinophil-specific hypermethylation, notably in the hallmark eosinophilic inflammation marker CLC, and overexpressed ten genes, including TNFRSF13B and TNFRSF17, which are linked to B cell function and antibody production. Higher pretreatment expression of these genes showed a suggestive association with omalizumab response among T2-high patients (P=0.088; n=40). CONCLUSIONS Our DNAm score enhances the clinical utility of existing biomarkers and captures previously unrecognized heterogeneity within T2 asthma. This approach enables refined patient stratification, improving precision medicine strategies and ensuring broader applicability across diverse populations.

Patagonia, the last region settled by humans after the out-of-Africa migration, provides a unique case for studying genetic adaptations to extreme environments. Despite archaeological evidence of human occupation for at least 13,500 years, the genetic history of Indigenous Patagonians remains understudied. Here, we analyze genome-wide data from individuals with high Native American ancestry to investigate their genetic structure, admixture history, and response to environmental pressures through selection. Our results reveal widespread European admixture, which in Chilean Patagonia started 5 generations earlier than in the capital of the colony, suggesting prolonged European contact relative to lower latitudes. We identified a strong north-south genomic differentiation, where common ancestry with Mapuche people is observed in northern Patagonia while Tierra del Fuego shows a unique component of genetic variation. We found selection signals predating European contact, possibly shaped during the settlement of native ancestors in Patagonia. These signals support adaptation to extreme cold and maritime diet, including genomic regions associated with height ( SUPT3H, CADM1, RUNX2 ), lipid metabolism ( MSMO1, SORT1/PSCR2, CELSR2 ), and energy homeostasis ( ZNF202 ). Furthermore, enrichment of Native American ancestry was observed in the MHC complex, likely representing the genetic footprint of past selection events driven by adaptation to endemic pathogens that were still beneficial after admixture with Europeans. These findings provide novel insights into the genetic legacy of Patagonian populations, demonstrating how natural selection has shaped their resilience to environmental challenges and the dynamics of demographic changes over time.

Despite biomarker-guided treatment strategies, clinical outcomes among patients with type 2 (T2)-high asthma remain heterogeneous, with some patients responding poorly to T2-targeted biologic therapies. We developed a contrastive machine learning method for patient stratification based on whole-blood DNA methylation (DNAm), applying it to pediatric asthma cohorts of Latino (discovery; n=1,016) and African American (replication; n=429) children. The resulting DNAm stratification score revealed a continuum of clinical severity and drug response within the T2-high asthma endotype. Molecular profiling of high-score asthma patients identified eosinophil-specific hypermethylation-validated in an independent Canadian adult cohort using purified eosinophil DNAm-as well as upregulation of canonical T2-associated genes. Transcriptomic analysis of elevated DNAm scores within T2-high patients further uncovered a gene signature linked to B-cell lineage activity, predominantly reflecting plasma cell activity orthogonal to canonical T2 inflammation programs. This defines a previously unrecognized sub-endotype, which we term T2-high asthma with Altered B Cell response (T2ABC). In a randomized controlled trial of the anti-IgE biologic omalizumab in primarily White adult T2-high asthmatic patients (n=300), the T2ABC gene expression signature was prognostic of poor outcomes, including a 24% mean increase in disease exacerbation rates compared to the trial baseline (P=0.004), which could not be explained by treatment or placebo assignment. Patients treated with omalizumab showed better outcomes than patients in the placebo arm within the T2ABC-low group (P=0.019) but not within the T2ABC-high group (P=0.48), suggesting that IgE blockade does not adequately target the pathogenic mechanisms active in T2ABC-high disease. Single-cell transcriptomic analysis demonstrated that the T2ABC signature reflects heightened activity of non-IgE plasma cells, consistent with the presence of additional antibody isotype responses in a form of severe asthma arising within a T2-high immunologic context. Our findings, replicated and validated across four ancestrally and ethnically diverse pediatric and adult cohorts, support the use of DNAm- and transcriptome-based patient stratification to refine drug development, eligibility, and administration strategies for improving precision in T2 asthma therapy.

BackgroundPrevious research showed that 5-hydroxytryptophan (5HTP), a metabolic precursor of serotonin, reduces allergic lung inflammation by inhibiting eosinophil migration across endothelial monolayers.ObjectiveIt is unknown if serotonin receptors are involved in mediating this 5HTP function or if serotonin receptor (HTR) single nucleotide polymorphisms (SNPs) associate with lung function in humans.MethodsSerotonin receptor subtypes were assessed by qPCR, western blot, confocal microscopy, pharmacological inhibitors and siRNA knockdown. HTR SNPs were assessed in two cohorts.ResultsPharmacological inhibition or siRNA knockdown of the serotonin receptors HTR1A or HTR1B in endothelial cells abrogated the inhibitory effects of 5HTP on eosinophil transendothelial migration. In contrast, eosinophil transendothelial migration was not inhibited by siRNA knockdown of HTR1A or HTR1B in eosinophils. Surprisingly, these HTRs were intracellular in endothelial cells and an extracellular supplementation with serotonin did not inhibit eosinophil transendothelial migration. This is consistent with the inability of serotonin to cross membranes, the lack of selective serotonin reuptake receptors on endothelial cells, and the studies showing minimal impact of selective serotonin reuptake inhibitors on asthma. To extend our HTR studies to humans with asthma, we examined the CHIRAH and GALA cohorts for HTR SNPs that affect HTR function or are associated with behavior disorders. A polygenic index of SNPs in HTRs was associated with lower lung function in asthmatics.ConclusionsSerotonin receptors mediate 5HTP inhibition of transendothelial migration and HTR SNPs associate with lower lung function. These results may serve to aid in design of novel interventions for allergic inflammation.

Recently, an African ancestry-specific Parkinson disease (PD) risk signal was identified at the gene encoding glucocerebrosidase (GBA1). This variant (rs3115534-G) is carried by ~50% of West African PD cases and imparts a dose-dependent increase in risk for disease. The risk variant has varied frequencies across African ancestry groups but is almost absent in European and Asian ancestry populations. GBA1 is a gene of high clinical and therapeutic interest. Damaging biallelic protein-coding variants cause Gaucher disease and monoallelic variants confer risk for PD and dementia with Lewy bodies, likely by reducing the function of glucocerebrosidase. Interestingly, the African ancestry-specific GBA1 risk variant is a noncoding variant, suggesting a different mechanism of action. Using full-length RNA transcript sequencing, we identified partial intron 8 expression in risk variant carriers (G) but not in nonvariant carriers (T). Antibodies targeting the N terminus of glucocerebrosidase showed that this intron-retained isoform is likely not protein coding and subsequent proteomics did not identify a shorter protein isoform, suggesting that the disease mechanism is RNA based. Clustered regularly interspaced short palindromic repeats editing of the reported index variant (rs3115534) revealed that this is the sequence alteration responsible for driving the production of these transcripts containing intron 8. Follow-up analysis of this variant showed that it is in a key intronic branchpoint sequence and, therefore, has important implications in splicing and disease. In addition, when measuring glucocerebrosidase activity, we identified a dose-dependent reduction in risk variant carriers. Overall, we report the functional effect of a GBA1 noncoding risk variant, which acts by interfering with the splicing of functional GBA1 transcripts, resulting in reduced protein levels and reduced glucocerebrosidase activity. This understanding reveals a potential therapeutic target in an underserved and underrepresented population.

Identifying and refining clinically significant patient stratification is a critical step toward realizing the promise of precision medicine in asthma. Several peripheral blood hallmarks, including total peripheral blood eosinophil count (BEC) and immunoglobulin E (IgE) levels, are routinely used in asthma clinical practice for endotype classification and predicting response to state-of-the-art targeted biologic drugs. However, these biomarkers appear ineffective in predicting treatment outcomes in some patients, and they differ in distribution between racially and ethnically diverse populations, potentially compromising medical care and hindering health equity due to biases in drug eligibility. Here, we propose constructing an unbiased patient stratification score based on DNA methylation (DNAm) and utilizing it to refine the efficacy of hallmark biomarkers for predicting drug response. We developed Phenotype Aware Component Analysis (PACA), a novel contrastive machine-learning method for learning combinations of DNAm sites reflecting biomedically meaningful patient stratifications. Leveraging whole-blood DNAm from Latino (discovery; n=1,016) and African American (replication; n=756) pediatric asthma case-control cohorts, we applied PACA to refine the prediction of bronchodilator response (BDR) to the short-acting β2-agonist albuterol, the most used drug to treat acute bronchospasm worldwide. While BEC and IgE correlate with BDR in the general patient population, our PACA-derived DNAm score renders these biomarkers predictive of drug response only in patients with high DNAm scores. BEC correlates with BDR in patients with upper-quartile DNAm scores (OR 1.12; 95% CI [1.04, 1.22]; P=7.9 e-4) but not in patients with lower-quartile scores (OR 1.05; 95% CI [0.95, 1.17]; P=0.21); and IgE correlates with BDR in above-median (OR for response 1.42; 95% CI [1.24, 1.63]; P=3.9e-7) but not in below-median patients (OR 1.05; 95% CI [0.92, 1.2]; P=0.57). These results hold within the commonly recognized type 2 (T2)-high asthma endotype but not in T2-low patients, suggesting that our DNAm score primarily represents an unknown variation of T2 asthma. Among T2-high patients with high DNAm scores, elevated BEC or IgE also corresponds to baseline clinical presentation that is known to benefit more from biologic treatment, including higher exacerbation scores, higher allergen sensitization, lower BMI, more recent oral corticosteroids prescription, and lower lung function. Our findings suggest that BEC and IgE, the traditional asthma biomarkers of T2-high asthma, are poor biomarkers for millions worldwide. Revisiting existing drug eligibility criteria relying on these biomarkers in asthma medical care may enhance precision and equity in treatment.

The impact of early-life daycare attendance on the development of asthma and allergic diseases has been the subject of multiple studies, yielding mixed findings. If early-life daycare attendance influences aeroallergen sensitization, daycare attendance could significantly influence later childhood health.

By incompletely understood mechanisms, type 2 (T2) inflammation present in the airways of severe asthmatics drives the formation of pathologic mucus which leads to airway mucus plugging. Here we investigate the molecular role and clinical significance of intelectin-1 (ITLN-1) in the development of pathologic airway mucus in asthma. Through analyses of human airway epithelial cells we find that ITLN1 gene expression is highly induced by interleukin-13 (IL-13) in a subset of metaplastic MUC5AC+ mucus secretory cells, and that ITLN-1 protein is a secreted component of IL-13-induced mucus. Additionally, we find ITLN-1 protein binds the C-terminus of the MUC5AC mucin and that its deletion in airway epithelial cells partially reverses IL-13-induced mucostasis. Through analysis of nasal airway epithelial brushings, we find that ITLN1 is highly expressed in T2-high asthmatics, when compared to T2-low children. Furthermore, we demonstrate that both ITLN-1 gene expression and protein levels are significantly reduced by a common genetic variant that is associated with protection from the formation of mucus plugs in T2-high asthma. This work identifies an important biomarker and targetable pathways for the treatment of mucus obstruction in asthma. Type 2 inflammation drives the formation of pathologic mucus in patients with asthma. Here, authors reveal a role for intelectin-1 in IL-13-induced mucus properties, and that an ITLN1 eQTL is associated with protection from the formation of mucus plugs in T2-high asthma.

Epidemiologic studies demonstrate an association between early-life respiratory illnesses (RIs) and the development of childhood asthma. However, it remains uncertain whether these children are predisposed to both conditions or if early-life RIs induce alterations in airway function, immune responses, or other human biology that contribute to the development of asthma. Puerto Rican children experience a disproportionate burden of early-life RIs and asthma, making them an important population for investigating this complex interplay. PRIMERO, the Puerto Rican Infant Metagenomics and Epidemiologic Study of Respiratory Outcomes , recruited pregnant women and their newborns to investigate how the airways develop in early life among infants exposed to different viral RIs, and will thus provide a critical understanding of childhood asthma development. As the first asthma birth cohort in Puerto Rico, PRIMERO will prospectively follow 2,100 term healthy infants. Collected samples include post-term maternal peripheral blood, infant cord blood, the child's peripheral blood at the year two visit, and the child's nasal airway epithelium, collected using minimally invasive nasal swabs, at birth, during RIs over the first two years of life, and at annual healthy visits until age five. Herein, we describe the study's design, population, recruitment strategy, study visits and procedures, and primary outcomes.

Hispanic/Latino children have the highest risk of acute lymphoblastic leukemia (ALL) in the US compared to other racial/ethnic groups, yet the basis of this remains incompletely understood. Through genetic fine-mapping analyses, we identified a new independent childhood ALL risk signal near IKZF1 in self-reported Hispanic/Latino individuals, but not in non-Hispanic White individuals, with an effect size of ∼1.44 (95% confidence interval = 1.33-1.55) and a risk allele frequency of ∼18% in Hispanic/Latino populations and <0.5% in European populations. This risk allele was positively associated with Indigenous American ancestry, showed evidence of selection in human history, and was associated with reduced IKZF1 expression. We identified a putative causal variant in a downstream enhancer that is most active in pro-B cells and interacts with the IKZF1 promoter. This variant disrupts IKZF1 autoregulation at this enhancer and results in reduced enhancer activity in B cell progenitors. Our study reveals a genetic basis for the increased ALL risk in Hispanic/Latino children.

Background Albuterol is the first-line asthma medication used in diverse populations. Although DNA methylation (DNAm) is an epigenetic mechanism involved in asthma and bronchodilator drug response (BDR), no study has assessed whether albuterol could induce changes in the airway epithelial methylome. We aimed to characterize albuterol-induced DNAm changes in airway epithelial cells, and assess potential functional consequences and the influence of genetic variation and asthma-related clinical variables. Results We followed a discovery and validation study design to characterize albuterol-induced DNAm changes in paired airway epithelial cultures stimulated in vitro with albuterol. In the discovery phase, an epigenome-wide association study using paired nasal epithelial cultures from Puerto Rican children ( n = 97) identified 22 CpGs genome-wide associated with repeated-use albuterol treatment ( p < 9 × 10 –8 ). Albuterol predominantly induced a hypomethylation effect on CpGs captured by the EPIC array across the genome (probability of hypomethylation: 76%, p value = 3.3 × 10 –5 ). DNAm changes on the CpGs cg23032799 ( CREB3L1 ), cg00483640 ( MYLK4-LINC01600 ), and cg05673431 ( KSR1 ) were validated in nasal epithelia from 10 independent donors (false discovery rate [FDR] < 0.05). The effect on the CpG cg23032799 ( CREB3L1 ) was cross-tissue validated in bronchial epithelial cells at nominal level ( p = 0.030). DNAm changes in these three CpGs were shown to be influenced by three independent genetic variants (FDR < 0.05). In silico analyses showed these polymorphisms regulated gene expression of nearby genes in lungs and/or fibroblasts including KSR1 and LINC01600 (6.30 × 10 –14 ≤ p ≤ 6.60 × 10 –5 ). Additionally, hypomethylation at the CpGs cg10290200 ( FLNC ) and cg05673431 (KSR1 ) was associated with increased gene expression of the genes where they are located (FDR < 0.05). Furthermore, while the epigenetic effect of albuterol was independent of the asthma status, severity, and use of medication, BDR was nominally associated with the effect on the CpG cg23032799 ( CREB3L1) ( p = 0.004). Gene-set enrichment analyses revealed that epigenomic modifications of albuterol could participate in asthma-relevant processes (e.g., IL-2, TNF-α, and NF-κB signaling pathways). Finally, nine differentially methylated regions were associated with albuterol treatment, including CREB3L1 , MYLK4 , and KSR1 (adjusted p value < 0.05). Conclusions This study revealed evidence of epigenetic modifications induced by albuterol in the mucociliary airway epithelium. The epigenomic response induced by albuterol might have potential clinical implications by affecting biological pathways relevant to asthma.

We explored ancestry-related differences in the genetic architecture of whole-blood gene expression using whole-genome and RNA sequencing data from 2,733 African Americans, Puerto Ricans and Mexican Americans. We found that heritability of gene expression significantly increased with greater proportions of African genetic ancestry and decreased with higher proportions of Indigenous American ancestry, reflecting the relationship between heterozygosity and genetic variance. Among heritable protein-coding genes, the prevalence of ancestry-specific expression quantitative trait loci (anc-eQTLs) was 30% in African ancestry and 8% for Indigenous American ancestry segments. Most anc-eQTLs (89%) were driven by population differences in allele frequency. Transcriptome-wide association analyses of multi-ancestry summary statistics for 28 traits identified 79% more gene-trait associations using transcriptome prediction models trained in our admixed population than models trained using data from the Genotype-Tissue Expression project. Our study highlights the importance of measuring gene expression across large and ancestrally diverse populations for enabling new discoveries and reducing disparities.

We conducted an epigenome-wide association study of bronchodilator drug response (BDR) in a discovery and validation design. The discovery phase was focused on 221 African American children with asthma. The association between DNA methylation and BDR was conducted using the limma package correcting for age, sex, ancestry, and tissue heterogeneity. Summary statistics include the output from toptable limma function and CpG annotation (based on Illumina EPIC Manifest file v 1.0 B4) organized in the following columns: Probe: Probe ID Chr: chromosome Pos: genomic position based on GRCh37/hg19 Gene: Gene annotation based on Illumina EPIC Manifest file v 1.0 B4 logFC: estimate of the log2-fold-change corresponding to the effect or contrast SE: standard error AveExpr: average log2-expression for the probe over all arrays and channels t: moderated t-statistic P.value: raw p-value FDR: adjusted p-value by false discovery rate B: log-odds that the gene is differentially expressed Problem: Flagged potentially problematic probes