Dysanapsis Genetic Risk Predicts Lung Function Across the Lifespan.

Rationale Dysanapsis refers to a mismatch between airway tree caliber and lung size arising early in life. Dysanapsis assessed by computed tomography (CT) is evident by early adulthood and associated with chronic obstructive pulmonary disease (COPD) risk later in life. Objective By examining the genetic factors associated with CT-assessed dysanapsis, we aimed to elucidate its molecular underpinnings and physiological significance across the lifespan. Methods We performed a genome-wide association study (GWAS) of CT-assessed dysanapsis in 11,951 adults, including individuals from two population-based and two COPD-enriched studies. We applied colocalization analysis to integrate GWAS and gene expression data from whole blood and lung. Genetic variants associated with dysanapsis were combined into a genetic risk score that was applied to examine association with lung function in children from a population-based birth cohort (n=1,278) and adults from the UK Biobank (n=369,157). Measurements and Main Results CT-assessed dysanapsis was associated with genetic variants from 21 independent signals in 19 gene regions, implicating HHIP, DSP, and NPNT as potential molecular targets based on colocalization of their expression. Higher dysanapsis genetic risk score was associated with obstructive spirometry among 5 year old children and among adults in the 5th, 6th and 7th decades of life. Conclusions CT-assessed dysanapsis is associated with variation in genes previously implicated in lung development and dysanapsis genetic risk is associated with obstructive lung function from early life through older adulthood. Dysanapsis may represent an endo-phenotype link between the genetic variations associated with lung function and COPD.

Loss of Airway Phylogenetic Diversity Is Associated with Clinical and Pathobiological Markers of Disease Development in Chronic Obstructive Pulmonary Disease.

Rationale: The airway microbiome has the potential to shape chronic obstructive pulmonary disease (COPD) pathogenesis, but its relationship to outcomes in milder disease is unestablished. Objectives: To identify sputum microbiome characteristics associated with markers of COPD in participants of the Subpopulations and Intermediate Outcome Measures of COPD Study (SPIROMICS). Methods: Sputum DNA from 877 participants was analyzed using 16S ribosomal RNA gene sequencing. Relationships between baseline airway microbiota composition and clinical, radiographic, and mucoinflammatory markers, including longitudinal lung function trajectory, were examined. Measurements and Main Results: Participant data represented predominantly milder disease (Global Initiative for Chronic Obstructive Lung Disease stage 0-2 obstruction in 732 of 877 participants). Phylogenetic diversity (i.e., range of different species within a sample) correlated positively with baseline lung function, decreased with higher Global Initiative for Chronic Obstructive Lung Disease stage, and correlated negatively with symptom burden, radiographic markers of airway disease, and total mucin concentrations (P < 0.001). In covariate-adjusted regression models, organisms robustly associated with better lung function included Alloprevotella, Oribacterium, and Veillonella species. Conversely, lower lung function, greater symptoms, and radiographic measures of small airway disease were associated with enrichment in members of Streptococcus, Actinobacillus, Actinomyces, and other genera. Baseline sputum microbiota features were also associated with lung function trajectory during SPIROMICS follow-up (stable/improved, decline, or rapid decline groups). The stable/improved group (slope of FEV1 regression ⩾66th percentile) had greater bacterial diversity at baseline associated with enrichment in Prevotella, Leptotrichia, and Neisseria species. In contrast, the rapid decline group (FEV1 slope ⩽33rd percentile) had significantly lower baseline diversity associated with enrichment in Streptococcus species. Conclusions: In SPIROMICS, baseline airway microbiota features demonstrate divergent associations with better or worse COPD-related outcomes.

Utility of eosinophil peroxidase as a biomarker of eosinophilic inflammation in asthma.

BACKGROUND: The relative utility of eosinophil peroxidase (EPX) and blood and sputum eosinophil counts as disease biomarkers in asthma is uncertain. OBJECTIVE: We sought to determine the utility of EPX as a biomarker of systemic and airway eosinophilic inflammation in asthma. METHODS: EPX protein was measured by immunoassay in serum and sputum in 110 healthy controls to establish a normal reference range and in repeated samples of serum and sputum collected during 3 years of observation in 480 participants in the Severe Asthma Research Program 3. RESULTS: Over 3 years, EPX levels in patients with asthma were higher than normal in 27% to 31% of serum samples and 36% to 53% of sputum samples. Eosinophils and EPX correlated better in blood than in sputum (rs values of 0.74 and 0.43, respectively), and high sputum EPX levels occurred in 27% of participants with blood eosinophil counts less than 150 cells/µL and 42% of participants with blood eosinophil counts between 150 and 299 cells/µL. Patients with persistently high sputum EPX values for 3 years were characterized by severe airflow obstruction, frequent exacerbations, and high mucus plug scores. In 59 patients with asthma who started mepolizumab during observation, serum EPX levels normalized in 96% but sputum EPX normalized in only 49%. Lung function remained abnormal even when sputum EPX normalized. CONCLUSIONS: Serum EPX is a valid protein biomarker of systemic eosinophilic inflammation in asthma, and sputum EPX levels are a more sensitive biomarker of airway eosinophilic inflammation than sputum eosinophil counts. Eosinophil measures in blood frequently miss airway eosinophilic inflammation, and mepolizumab frequently fails to normalize airway eosinophilic inflammation even though it invariably normalizes systemic eosinophilic inflammation.

A novel DNase assay reveals low DNase activity in severe asthma.

Secreted deoxyribonucleases (DNases), such as DNase-I and DNase-IL3, degrade extracellular DNA, and endogenous DNases have roles in resolving airway inflammation and guarding against autoimmune responses to nucleotides. Subsets of patients with asthma have high airway DNA levels, but information about DNase activity in health and in asthma is lacking. To characterize DNase activity in health and in asthma, we developed a novel kinetic assay using a Taqman probe sequence that is quickly cleaved by DNase-I to produce a large product signal. We used this kinetic assay to measure DNase activity in sputum from participants in the Severe Asthma Research Program (SARP)-3 (n = 439) and from healthy controls (n = 89). We found that DNase activity was lower than normal in asthma [78.7 relative fluorescence units (RFU)/min vs. 120.4 RFU/min, P < 0.0001]. Compared to patients with asthma with sputum DNase activity in the upper tertile activity levels, those in the lower tertile of sputum DNase activity were characterized clinically by more severe disease and pathologically by airway eosinophilia and airway mucus plugging. Carbamylation of DNase-I, a post-translational modification that can be mediated by eosinophil peroxidase, inactivated DNase-I. In summary, a Taqman probe-based DNase activity assay uncovers low DNase activity in the asthma airway that is associated with more severe disease and airway mucus plugging and may be caused, at least in part, by eosinophil-mediated carbamylation.NEW & NOTEWORTHY We developed a new DNase assay and used it to show that DNase activity is impaired in asthma airways.

Genetic and T2 biomarkers linked to the efficacy of HDM sublingual immunotherapy in asthma.

BACKGROUND: Hypersensitivity to house dust mite (HDM) allergens is a common cause of allergic asthma symptoms and can be effectively treated with allergy immunotherapy (AIT). OBJECTIVE: To investigate whether genetic and type 2 (T2) inflammatory biomarkers correlate with disease severity in subjects with allergic asthma, and whether this can be modified by AIT. METHODS: MITRA (NCT01433523) was a phase III, randomised, double-blind, placebo-controlled trial of HDM sublingual immunotherapy (SLIT)-tablets in adults with HDM allergic asthma. Post hoc analyses of the study population (N=742) evaluated associations between T2 inflammatory (blood eosinophils, eosinophil cationic protein (ECP), total IgE and tryptase) and genetic (single-nucleotide polymorphisms, SNP) biomarkers (n=582) for the primary study endpoint (time to first moderate/severe asthma exacerbation). SNP associations were verified in HDM-positive subgroup from an independent 3-year Severe Asthma Research Programme (SARP3) subject cohort. RESULTS: An increased asthma exacerbation risk in subjects homozygous for SNP rs7216389 (chromosomal locus 17q12-21) was reduced (p=0.037) by treatment with HDM SLIT (HR=0.37 (95% CI 0.22 to 0.64), p<0.001). The associations between exacerbation risk and 17q12-21 SNPs were replicated in the SARP3 HDM-positive subgroup. High levels of T2 biomarkers were associated with increased risk of asthma exacerbations in the placebo group. HDM SLIT-tablet treatment reduced this risk (blood eosinophils: HR=0.50 (95% CI 0.30 to 0.85); ECP: HR=0.45 (95% CI 0.29 to 0.87); tryptase: HR=0.45 (95% CI 0.25 to 0.80)). The treatment effect was higher (p=0.006) for subjects with a higher number of elevated T2 biomarkers. CONCLUSIONS: HDM SLIT-tablet AIT is efficacious in HDM-sensitised asthma subjects with a genetic asthma predisposition and/or an underlying T2 endotype. TRIAL REGISTRATION NUMBER: NCT01433523.

Protein-Protein interactive networks identified in bronchoalveolar lavage of severe compared to nonsevere asthma.

INTRODUCTION: Previous bronchoalveolar lavage fluid (BALF) proteomic analysis has evaluated limited numbers of subjects for only a few proteins of interest, which may differ between asthma and normal controls. Our objective was to examine a more comprehensive inflammatory biomarker panel in quantitative proteomic analysis for a large asthma cohort to identify molecular phenotypes distinguishing severe from nonsevere asthma. METHODS: Bronchoalveolar lavage fluid from 48 severe and 77 nonsevere adult asthma subjects were assessed for 75 inflammatory proteins, normalized to BALF total protein concentration. Validation of BALF differences was sought through equivalent protein analysis of autologous sputum. Subjects' data, stratified by asthma severity, were analysed by standard statistical tests, principal component analysis and 5 machine learning algorithms. RESULTS: The severe group had lower lung function and greater health care utilization. Significantly increased BALF proteins for severe asthma compared to nonsevere asthma were fibroblast growth factor 2 (FGF2), TGFα, IL1Ra, IL2, IL4, CCL8, CCL13 and CXCL7 and significantly decreased were platelet-derived growth factor a-a dimer (PDGFaa), vascular endothelial growth factor (VEGF), interleukin 5 (IL5), CCL17, CCL22, CXCL9 and CXCL10. Four protein differences were replicated in sputum. FGF2, PDGFaa and CXCL7 were independently identified by 5 machine learning algorithms as the most important variables for discriminating severe and nonsevere asthma. Increased and decreased proteins identified for the severe cluster showed significant protein-protein interactions for chemokine and cytokine signalling, growth factor activity, and eosinophil and neutrophil chemotaxis differing between subjects with severe and nonsevere asthma. CONCLUSION: These inflammatory protein results confirm altered airway remodelling and cytokine/chemokine activity recruiting leukocytes into the airways of severe compared to nonsevere asthma as important processes even in stable status.

Asthma control in the United States: Relationships between short-acting ß2-agonist and systemic corticosteroid use.

BACKGROUND: Asthma control assessment is based on impairment (current symptoms) and risk (exacerbation history). OBJECTIVE: To understand the extent of uncontrolled asthma, we assessed relationships between prescription fills for systemic corticosteroids (SCS) and short-acting ß2-agonists (SABA) as risk and impairment markers, respectively. METHODS: Annual SCS and SABA fills among US patients with asthma were evaluated by a retrospective analysis of the IQVIA Longitudinal Access and Adjudication Data. Patients' disease severity was assigned based on the Global Initiative for Asthma step-therapy level. Exacerbations were evaluated by SCS fills within 12 months of a first asthma prescription fill. Uncontrolled asthma was defined as 2 or more SCS and/or 3 or more SABA fills annually. Individual patient relationships between SCS and SABA fills were assessed using Pearson's correlation coefficients. RESULTS: A total of 4,506,527 patients were included; 15.1% had 2 or more SCS fills, 29.1% had 3 or more SABA fills, and 37.4% fulfilled either or both criteria. If only SCS use was assessed, 21.4% of cases that were treated as mild to moderate and 27.6% that were treated as severe asthma would have been misclassified as controlled. If only SABA use was evaluated, 7.8% of cases treated as mild to moderate and 11.2% treated as severe asthma would have been misclassified. Overall, 80.9% of uncontrolled asthma occurred in patients treated for mild to moderate disease. Among patients with 2 or more SCS fills, the mean SABA fills were 2.9; the correlation between SCS and SABA fills per patient was significant but weak (r = 0.18; P < .001). CONCLUSION: High symptom burden and SCS exposures are not limited to severe asthma but are also characteristic of patients treated for mild to moderate disease. Both impairment and risk assessments are required to understand the full extent of uncontrolled asthma across disease severities.

Real-world effectiveness of dupilumab versus benralizumab and mepolizumab.

Introduction: In the United States, this real-world study compared the effectiveness of dupilumab, benralizumab, and mepolizumab in reducing exacerbations and systemic corticosteroid (SCS) prescriptions among patients with asthma. Methods: Patients (≥12 years old) who initiated dupilumab, benralizumab, or mepolizumab (index) between November 2018 and September 2020 were identified by using electronic medical record data. Subjects were included if they had ≥ 12 months of data before and after the index date and two or more severe asthma-related exacerbations before the index date. Differences in baseline characteristics were addressed by using inverse probability treatment weighting (IPTW). Pairwise comparisons between dupilumab and benralizumab, or mepolizumab were conducted by using negative binomial regression, adjusting for baseline rates and unbalance characteristics (≥10% standardized differences) after IPTW. Results: Overall, a total of 1737 subjects met all criteria: 825 dupilumab, 461 benralizumab, and 451 mepolizumab initiators. In the postindex period, dupilumab was associated with a 24% and 28% significant reduction in the risk of severe asthma exacerbations versus benralizumab (incidence rate ratio [IRR] 0.76 [95% confidence interval {CI}, 0.67-0.86)] and mepolizumab (IRR 0.72 [95% CI, 0.63-0.82]), respectively. In addition, dupilumab treatment significantly reduced SCS prescriptions by 16% and 25% versus benralizumab and mepolizumab, respectively (p < 0.05). Conclusion: This study represents one of the largest real-world comparisons of biologics (dupilumab, benralizumab, and mepolizumab) for asthma in the United States to date. This analysis shows that the use of dupilumab was associated with a significantly greater reduction in both severe asthma exacerbations and SCS prescriptions compared with benralizumab and mepolizumab.

Multivariate Cluster Analyses to Characterize Asthma Heterogeneity and Benralizumab Responsiveness.

BACKGROUND: An improved understanding of how severe asthma heterogeneity affects response could inform treatment decisions. OBJECTIVES: Characterize heterogeneity and benralizumab responsiveness in patients grouped by predefined Severe Asthma Research Program clusters using a multivariate approach. METHODS: In post-hoc analyses of the randomized, double-blind, placebo-controlled phase III SIROCCO (NCT01928771) and CALIMA (NCT01914757) studies, patients with severe asthma who received benralizumab or placebo were assigned to clusters using an established discriminant function to analyze 11 clinical characteristics simultaneously. The annualized asthma exacerbation rate, exacerbation incidence, and lung function were analyzed across clusters. RESULTS: Patients (n = 2,281) met criteria for four of five clusters: cluster 2 (early-onset moderate asthma, n = 393), cluster 4 (early-onset severe asthma, n = 386), cluster 3 (late-onset severe asthma, n = 641), and cluster 5 (late-onset severe, obstructed asthma, n = 861); no patients met cluster 1 criteria. Exacerbation rate reductions were significant in late-onset severe asthma (-48% [95% CI, -61% to -31%]; P < .0001) and late-onset severe, obstructed asthma (-50% [95% CI, -59% to -38%]; P < .0001), with nonsignificant reductions in early-onset clusters. These differences could not be fully explained by blood eosinophil count differences. Values for improvements in FEV1 were significant in late-onset severe asthma (+133 mL [95% CI, 66-200]; P = .0001) and late-onset severe, obstructed asthma (+160 mL [95% CI, 85-235]; P < .0001) while maintaining acute bronchodilator responsiveness. CONCLUSIONS: Benralizumab reduced exacerbations and improved lung function, primarily in late-onset asthma clusters. This multivariate approach to identify subphenotypes, potentially reflecting pathobiological mechanisms, can guide therapy beyond univariate approaches.

Novel Machine Learning Identifies 5 Asthma Phenotypes Using Cluster Analysis of Real-World Data.

BACKGROUND: Asthma classification into different subphenotypes is important to guide personalized therapy and improve outcomes. OBJECTIVES: To further explore asthma heterogeneity through determination of multiple patient groups by using novel machine learning (ML) approaches and large-scale real-world data. METHODS: We used electronic health records of patients with asthma followed at the Cleveland Clinic between 2010 and 2021. We used k-prototype unsupervised ML to develop a clustering model where predictors were age, sex, race, body mass index, prebronchodilator and postbronchodilator spirometry measurements, and the usage of inhaled/systemic steroids. We applied elbow and silhouette plots to select the optimal number of clusters. These clusters were then evaluated through LightGBM's supervised ML approach on their cross-validated F1 score to support their distinctiveness. RESULTS: Data from 13,498 patients with asthma with available postbronchodilator spirometry measurements were extracted to identify 5 stable clusters. Cluster 1 included a young nonsevere asthma population with normal lung function and higher frequency of acute exacerbation (0.8 /patient-year). Cluster 2 had the highest body mass index (mean ± SD, 44.44 ± 7.83 kg/m2), and the highest proportion of females (77.5%) and Blacks (28.9%). Cluster 3 comprised patients with normal lung function. Cluster 4 included patients with lower percent of predicted FEV1 of 77.03 (12.79) and poor response to bronchodilators. Cluster 5 had the lowest percent of predicted FEV1 of 68.08 (15.02), the highest postbronchodilator reversibility, and the highest proportion of severe asthma (44.9%) and blood eosinophilia (>300 cells/µL) (34.8%). CONCLUSIONS: Using real-world data and unsupervised ML, we classified asthma into 5 clinically important subphenotypes where group-specific asthma treatment and management strategies can be designed and deployed.

Comparison of Asthma Phenotypes in Severe Asthma Cohorts (SARP, U-BIOPRED, ProAR and COREA) From 4 Continents.

PURPOSE: Asthma is a clinical syndrome with various underlying pathomechanisms and clinical phenotypes. Genetic, ethnic, and geographic factors may influence the differences in clinical presentation, severity, and prognosis. We compared the characteristics of asthma based on the geographical background by analyzing representative cohorts from the United States, Europe, South America, and Asia using the Severe Asthma Research Program (SARP), Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED), Program for Control of Asthma in Bahia (ProAR), and Cohort for Reality and Evolution of Adult Asthma in Korea (COREA), respectively. METHODS: The clinical characteristics and medications for the SARP (n = 669), U-BIOPRED (n = 509), ProAR (n = 996), and COREA (n = 3,748) were analyzed. Subgroup analysis was performed for severe asthma. RESULTS: The mean age was highest and lowest in the COREA and SARP, respectively. The asthma onset age was lowest in the ProAR. The mean body mass index was highest and lowest in the SARP and COREA, respectively. Baseline pulmonary function was lowest and highest in the U-BIOPRED and COREA, respectively. The number of patients with acute exacerbation in the previous year was highest in U-BIOPRED. The mean blood eosinophil count was highest in COREA. The total immunoglobulin E was highest in the ProAR. The frequency of atopy was highest in the SARP. The principal component analysis plot revealed differences among all cohorts. CONCLUSIONS: The cohorts from 4 different continents exhibited different clinical and physiological characteristics, probably resulting from the interplay between genetic susceptibility and geographical factors.

Dynamic and prognostic proteomic associations with FEV1 decline in chronic obstructive pulmonary disease.

Rationale: Identification and validation of circulating biomarkers for lung function decline in COPD remains an unmet need. Objective: Identify prognostic and dynamic plasma protein biomarkers of COPD progression. Methods: We measured plasma proteins using SomaScan from two COPD-enriched cohorts, the Subpopulations and Intermediate Outcomes Measures in COPD Study (SPIROMICS) and Genetic Epidemiology of COPD (COPDGene), and one population-based cohort, Multi-Ethnic Study of Atherosclerosis (MESA) Lung. Using SPIROMICS as a discovery cohort, linear mixed models identified baseline proteins that predicted future change in FEV1 (prognostic model) and proteins whose expression changed with change in lung function (dynamic model). Findings were replicated in COPDGene and MESA-Lung. Using the COPD-enriched cohorts, Gene Set Enrichment Analysis (GSEA) identified proteins shared between COPDGene and SPIROMICS. Metascape identified significant associated pathways. Measurements and Main Results: The prognostic model found 7 significant proteins in common (p < 0.05) among all 3 cohorts. After applying false discovery rate (adjusted p < 0.2), leptin remained significant in all three cohorts and growth hormone receptor remained significant in the two COPD cohorts. Elevated baseline levels of leptin and growth hormone receptor were associated with slower rate of decline in FEV1. Twelve proteins were nominally but not FDR significant in the dynamic model and all were distinct from the prognostic model. Metascape identified several immune related pathways unique to prognostic and dynamic proteins. Conclusion: We identified leptin as the most reproducible COPD progression biomarker. The difference between prognostic and dynamic proteins suggests disease activity signatures may be different from prognosis signatures.

A common polymorphism in the Intelectin-1 gene influences mucus plugging in severe asthma.

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.

Design of the SPIROMICS Study of Early COPD Progression: SOURCE Study.

The biological mechanisms leading some tobacco-exposed individuals to develop early-stage chronic obstructive pulmonary disease (COPD) are poorly understood. This knowledge gap hampers development of disease-modifying agents for this prevalent condition. Accord-ingly, with National Heart, Lung and Blood Institute support, we initiated the SPIROMICS Study of Early COPD Progression (SOURCE), a multicenter observational cohort study of younger individuals with a history of cigarette smoking and thus at-risk for, or with, early-stage COPD. Our overall objectives are to identify those who will develop COPD earlier in life, characterize them thoroughly, and by contrasting them to those not developing COPD, define mechanisms of disease progression. SOURCE utilizes the established SPIROMICS clinical network. Its goal is to enroll n=649 participants, ages 30-55 years, all races/ethnicities, with ≥10 pack-years cigarette smoking, in either Global Initiative for Chronic Obstructive Lung Disease (GOLD) groups 0-2 or with Preserved Ratio Impaired Spirometry (PRISm); and an additional n=40 never-smoker controls. Participants undergo baseline and three-year follow-up visits, each including high-resolution computed tomography; respiratory oscillometry and spirometry (pre- and post-bronchodilator administration), exhaled breath condensate (baseline only); and extensive biospecimen collection, including sputum induction. Symptoms, interim healthcare utilization, and exacerbations are captured every six months via follow-up phone calls. An embedded bronchoscopy sub-study involving n=100 participants (including all never-smokers) will allow collection of lower airway samples for genetic, epigenetic, genomic, immunological, microbiome, mucin analyses, and basal cell culture. SOURCE should provide novel insights into the natural history of lung disease in younger individuals with a smoking history, and its biological basis.

Validation of human telomere length multi-ancestry meta-analysis association signals identifies POP5 and KBTBD6 as human telomere length regulation genes.

Genome-wide association studies (GWAS) have become well-powered to detect loci associated with telomere length. However, no prior work has validated genes nominated by GWAS to examine their role in telomere length regulation. We conducted a multi-ancestry meta-analysis of 211,369 individuals and identified five novel association signals. Enrichment analyses of chromatin state and cell-type heritability suggested that blood/immune cells are the most relevant cell type to examine telomere length association signals. We validated specific GWAS associations by overexpressing KBTBD6 or POP5 and demonstrated that both lengthened telomeres. CRISPR/Cas9 deletion of the predicted causal regions in K562 blood cells reduced expression of these genes, demonstrating that these loci are related to transcriptional regulation of KBTBD6 and POP5. Our results demonstrate the utility of telomere length GWAS in the identification of telomere length regulation mechanisms and validate KBTBD6 and POP5 as genes affecting telomere length regulation.

Mitochondrial DNA Copy Number Variation in Asthma Risk, Severity, and Exacerbations.

Rationale: Although airway oxidative stress and inflammation are central to asthma pathogenesis, there is limited knowledge of the relationship of asthma risk, severity, or exacerbations to mitochondrial dysfunction, which is pivotal to oxidant generation and inflammation. Objectives: We investigated whether mitochondrial DNA copy number (mtDNA-CN) as a measure of mitochondrial function is associated with asthma diagnosis, severity, oxidative stress, and exacerbations. Methods: We measured mtDNA-CN in blood in two cohorts. In the UK Biobank (UKB), we compared mtDNA-CN in mild and moderate-severe asthmatics to non-asthmatics. In the Severe Asthma Research Program (SARP), we evaluated mtDNA-CN in relation to asthma severity, biomarkers of oxidative stress and inflammation, and exacerbations. Measures and Main Results: In UK Biobank, asthmatics (n = 29,768) have lower mtDNA-CN compared to non-asthmatics (n = 239,158) (beta, -0.026 [95% CI, -0.038 to -0.014], P = 2.46×10-5). While lower mtDNA-CN is associated with asthma, mtDNA-CN did not differ by asthma severity in either UKB or SARP. Biomarkers of inflammation show that asthmatics have higher white blood cells (WBC), neutrophils, eosinophils, fraction exhaled nitric oxide (FENO), and lower superoxide dismutase (SOD) than non-asthmatics, confirming greater oxidative stress in asthma. In one year follow-up in SARP, higher mtDNA-CN is associated with reduced risk of three or more exacerbations in the subsequent year (OR 0.352 [95% CI, 0.164 to 0.753], P = 0.007). Conclusions: Asthma is characterized by mitochondrial dysfunction. Higher mtDNA-CN identifies an exacerbation-resistant asthma phenotype, suggesting mitochondrial function is important in exacerbation risk.

The pharmacogenetics of asthma and the road to personalized medicine / A farmacogenética da asma e o caminho para a medicina personalizada

A asma é uma doença frequente e heterogênea, tanto em termos de expressão fenotípica, como de resposta aos diferentes tratamentos medicamentosos. Até o momento, os estudos farmacogenéticos investigaram o papel da variação genética na resposta farmacológica em três classes principais de medicamentos: agonistas dos receptores β2-adrenérgicos (β2-agonistas), corticosteroides e modificadores de leucotrienos. Essas análises contribuíram para a compreensão dos determinantes da resposta clínica às diferentes terapias contra asma; porém, a maioria dessas análises é limitada, pois são análises retrospectivas de pequenos grupos populacionais, feitas com base numa abordagem de identificação do gene candidato sujeita a vieses, o que pode requerer replicação em coortes maiores. Estudos farmacogenéticos também vêm investigando determinantes genéticos da resposta a terapias biológicas, tais como a inibição de citocinas por anticorpo. Abordagens futuras deveriam utilizar ensaios clínicos com abordagens sem vieses, com genomas amplos em grandes populações. Na investigação de eventos incomuns, o ressequenciamento de genes candidatos ou de todo o genoma deveria ser usado para identificar variações genéticas raras com potencial na identificação de efeitos genéticos raros em fenótipos baseados na resposta ao tratamento. Algumas das variantes genéticas que determinam a resposta ao fármaco têm frequência baixa, embora não raras, e deveriam ser validadas através de estudos prospectivos com desenho estratificado por genótipo