Despite evidence for a genetic component, few genetic associations with lung function decline have been identified. We aimed to evaluate genome-wide associations and putative downstream functionality of genetic variants for lung function decline. We conducted genome-wide association study (GWAS) analyses of decline in FEV1, FVC, and FEV1/FVC in 52,056 White (N = 44,988), Black (N = 5,788), Hispanic (N = 550), and Chinese American (N = 730) participants across seven general population cohorts. GWAS analyses were stratified by cohort, ancestry, and sex. Results were combined in cross-ancestry and ancestry-specific meta-analyses. Significant variants available in two independent COPD-enriched cohorts were tested for replication. We identified 361 distinct genome-wide significant (p < 5E-08) variants for one or more of the FEV1, FVC, and FEV1/FVC decline phenotypes, which overlapped with previously reported genetic signals for pulmonary traits. Four variants, or 10.3

While respiratory diseases such as chronic obstructive pulmonary disease (COPD) and asthma share many risk factors, most studies investigate them in isolation and in predominantly European-ancestry populations. Here, we conducted the most powerful multi-trait and multi-ancestry genetic analysis of respiratory diseases and auxiliary traits to date, identifying 25 new loci associated with lung function in individuals of East Asian ancestry. Using these results, we developed PRSxtra (cross-trait and cross-ancestry), a multi-trait and multi-ancestry polygenic risk score (PRS) approach that leverages shared components of heritable risk via pleiotropic effects. PRSxtra significantly improved the prediction of asthma, COPD and lung cancer compared to trait- and ancestry-matched PRSs in a multi-ancestry cohort from the All of Us Research Program, especially in diverse populations. Our results present a new framework for multi-trait and multi-ancestry studies of respiratory diseases to improve genetic discovery and polygenic prediction. Multi-trait genome-wide analyses identify variants associated with comorbid lung diseases. Polygenic scores leveraging shared components of heritable risk improve prediction of asthma, chronic obstructive pulmonary disease and lung cancer in a multi-ancestry cohort.

Despite its high prevalence and the discovery of hundreds of genetic associations, the genetic determinants and heterogeneous manifestations of asthma remain incompletely understood. Incorporating polygenic risk scores (PRS) into asthma research offers a powerful approach to quantify inherited susceptibility, refine risk profiles, and advance mechanistic understanding of disease development. For this study, we leveraged whole-genome sequencing (WGS) data from two family-based cohorts of childhood asthma - the Genetics of Asthma in Costa Rica Study (GACRS) and the Childhood Asthma Management Program (CAMP) - to examine the transmission profiles of externally derived asthma PRS and their associations with clinical phenotypes in children with asthma. To further elucidate molecular mechanisms, we integrated large-scale external genome-wide association study (GWAS) summary statistics and genetic prediction models of protein abundance in a two-step proteome-wide association study (PWAS) of asthma. Our findings provide robust evidence supporting the validity of externally derived asthma PRS (asthma PRS association p-value p = 10-24 [GACRS and CAMP trios combined] for the Global Biobank Meta-analysis Initiative [GBMI]) and reveal consistent associations with spirometry measures and atopy markers across both studies, as 13 of 21 traits (62%) were significantly associated with the GBMI-PRS in the meta-analysis after multiple-testing correction. Moreover, the results of the integrative proteomic analysis implicate IL-1 signaling in the etiology of asthma, reinforcing the candidacy of IL1R1 antagonists for drug repurposing.

BACKGROUND:Idiopathic pulmonary fibrosis (IPF) and telomere length are both strongly linked to rare and common genetic variants. Shortened telomere length might itself be causal for IPF. We aimed to evaluate whether rare and common variants compete or cooperate to confer genetic risk of IPF uniformly. METHODS:In this genetic analysis, we used whole-genome sequencing (WGS) data from a discovery case-control cohort sequenced at Columbia University and validated findings using WGS data from Trans-Omics for Precision Medicine (TOPMed) and UK Biobank. In all cohorts, we identified rare damaging variants in disease-associated genes and computed control-normalised non-overlapping polygenic risk scores (PRS) for IPF and telomere length. We assessed the MUC5B rs35705950 single-nucleotide polymorphism (SNP), an IPF common risk variant with a large effect, independently from the polygenic scores. Telomere length in blood leukocytes was measured using a quantitative PCR assay for the discovery cohort and UK Biobank validation cohort. We conducted logistic regression (adjusting for age, sex, and principal components of ancestry) to evaluate the association between IPF risk and the MUC5B SNP, the IPF PRS excluding MUC5B (IPF-PRS-noMUC5B), and the PRS for telomere length in the overall cohort and analysed their effects in patient subgroups for IPF endotypes (carriers and non-carriers of rare variants stratified by telomere length cutoffs). To assess disease prediction, we calculated cross-validated area under the receiver operating receiver operating curve (AUC). We also compared the liability of IPF explained by genetic variables. FINDINGS:The discovery cohort was recruited between April 23, 2003 and June 19, 2019 and included 777 patients with IPF and 2905 controls. We replicated the analyses in the TOPMed (1148 patients with IPF and 5202 controls) and UK Biobank (2739 patients with IPF and 395 331 controls) cohorts. 23-43% of patients with IPF had damaging rare variants or telomeres shorter than the tenth percentile. Analysis of the association of genetic variables with IPF diagnosis yielded odds ratios of 1·63 (95% CI 1·47-1·81) for telomere length PRS and 1·60 (1·44-1·77) for IPF-PRS-noMUC5B in the discovery cohort, with similar effect sizes for the two variables in the replication cohorts (1·47, 1·36-1·59 vs 1·37, 1·25-1·50 in TOPMed; 1·24, 1·19-1·29 vs 1·25, 1·21-1·30 in UK Biobank). The telomere length PRS had the greatest effect on disease risk in patients with IPF not harbouring rare variants and with telomere length shorter than the tenth percentile in the discovery cohort (2·02, 1·76-2·33) and UK Biobank replication cohort (1·70, 1·56-1·85). Accounting for clinical variables and all genetic variables (rare variants, MUC5B SNP, IPF PRS, and telomere length PRS) led to the best disease prediction in the discovery cohort (combined AUC 0·89), TOPMed cohort (0·89), and UK Biobank cohort (0·77). Rare and common variants contributed jointly to the genetic liability of IPF. The telomere length PRS accounted for 13% of the explained genetic liability of IPF in the discovery cohort and 8% and 13% in the TOPMed and UK Biobank cohorts, respectively. INTERPRETATION:Common and rare genetic variation confer context-specific genetic risk in patients with IPF both competitively and cooperatively. In contrast to known IPF common risk variants, the telomere length PRS, which includes more than 180 genetic loci not previously associated with IPF, is associated with increased risk of disease in patients with specific IPF endotypes. Polygenic risk from telomere-associated common variants is a key feature of genetic heterogeneity in IPF. FUNDING:US National Institutes of Health, UK Medical Research Council, and UK National Institute for Health and Care Research.

INTRODUCTION:Bronchodilator responsiveness (BDR) is associated with progression to COPD. Genetic risk for COPD, summarized by polygenic risk scores (PRS), predicts low lung function and COPD. However, it remains unclear whether genetic predisposition to COPD is related to BDR and whether PRS and BDR together influence lung function decline in individuals at risk for the disease. METHODS:We analyzed data from COPDGene participants with a smoking history and normal spirometry at study enrollment. We cross-sectionally examined the association of a PRS with 2005-BDR-FEV1 % (change relative to pre-bronchodilator) and 2021-BDR-FEV1 % (change relative to predicted). We also examined the association of PRS, 2005-BDR-FEV1 %, and 2021-BDR-FEV1 % with progression to COPD and longitudinal FEV1 decline between enrollment and follow-up adjusted for demographics, smoking history, and FEV1 at enrollment. RESULTS:PRS did not correlate with 2005-BDR-FEV1 % in 1446 African Americans (AA) but PRS correlates with BDR in both unadjusted (rho = 0.01, P < 0.001) and adjusted analysis in 3378 non-Hispanic Whites (NHW). NHW participants with BDR had higher PRS than those without. Models including 2005-BDR-FEV1 % demonstrated better accuracy than those including PRS (Area under the curve: 0.762 vs 0.743 in NHW; 0.693 vs 0.653 in AA). BDR models also outperformed PRS models for longitudinal FEV1 decline. Mediation analysis showed that about one third of the PRS effect on FEV1 decline in NHW was explained through BDR. CONCLUSIONS:BDR is more strongly associated with progression to COPD and FEV1 decline than PRS, and part of the PRS effect is mediated through BDR.

Rationale:Idiopathic pulmonary fibrosis (IPF) is an age-related disorder with common and rare genetic risk factors. It is unknown if the effects of PF genetic risk factors differ by chronologic age. Objectives:To assess age-specific effects of genetic risk factors in PF patients and their relatives. Methods:We identified common and rare genetic risk factors using a Columbia whole genome sequencing (WGS) cohort (777 IPF, 2905 controls) and replicated findings using Trans-Omics for Precision Medicine (TOPMed, 1148 IPF, 5202 controls). We assessed age-stratified genetic risk of IPF and assessed for interaction with age across a range of cutoffs. We analyzed 313 FPF pedigrees and compared age-specific prevalence of interstitial lung disease in relatives stratified by proband genetic risk factors. Measurements and Main Results:Adjusted odds of disease from MUC5B SNP increase with age, while odds of disease from rare variants decrease with age. The magnitude of the interaction term between age and both genetic variables was greatest in younger individuals. There were significant interactions between age <55 and the MUC5B SNP (discovery pinteraction=0.01; replication pinteraction<0.0001) and rare variants (discovery pinteraction<0.0001; replication pinteraction=0.03). Pedigree analysis showed more prevalent disease especially in younger relatives in FPF families with rare variants versus without (p<0.0001). Conclusions:Age modifies the effects of genetic risk factors in IPF. Rare variants confer greater risk in younger individuals whereas the MUC5B SNP confers greater risk in older individuals. Relatives of FPF patients with rare variants exhibit earlier prevalent disease, which has implications for preclinical disease screening.

Chronic obstructive pulmonary disease (COPD) is a debilitating and progressive lung disease that affects millions of people worldwide. There is a continuing clinical need to characterize COPD at the molecular level to be able to identify the multi-omic biomarkers of its pathogenesis and to enable more accurate diagnoses and more effective treatment. We used Multi-Omics Factor Analysis (MOFA) to jointly analyze genomic, blood transcriptomic, and plasma proteomic data collected from 1,872 participants in the Genetic Epidemiology of COPD study who had moderate to very severe COPD. Five latent factors identified by MOFA were associated with COPD-related lung function, chest computed tomography (CT) imaging, and blood count phenotypes, as well as all-cause mortality. The top genetic, transcriptomic and proteomic contributors to these latent factors were also individually associated with COPD-related outcomes. Moreover, factor loadings and expression levels of top omic drivers helped distinguish between patient subgroups. Quantitative trait loci analysis of a latent factor that was jointly driven by transcriptomics and proteomics revealed potential common genetic control of gene expression and protein abundance. Polygenic risk scores derived from a genomics-driven latent factor were associated with chest CT imaging and lung function phenotypes, and these associations were replicated in an independent COPD cohort. Together, our results suggest the potential of integrative omic approaches to identify the major axes of heterogeneity in COPD and uncover the multi-omic interplay between the contributors to each axis.

While low BMI is associated with emphysema and obesity is associated with airway disease in COPD, the underlying mechanisms are unclear. To examine the association between BMI-related genetic variants and emphysema and airway disease imaging phenotypes. We aggregated genetic variants from population-based genome-wide association studies to generate a polygenic score of BMI (PGSBMI). We examined associations of the PGSBMI with automated quantification and visual interpretation of computed tomographic emphysema and airway wall thickness (AWT) in COPD-enriched and community-based cohorts. We summarized the results using meta-analysis. In the meta-analyses combining results of all cohorts (n = 16,349), a standard-deviation increase of the PGSBMI was associated with less emphysema as quantified by log-transformed percent of low attenuation areas ≤950 Hounsfield units (β = -0.062, P <0.0001) and 15th percentile value of lung density histogram (β = 2.27, P <0.0001), and increased AWT as quantified by the square root of wall area of a 10-mm lumen perimeter airway (β = 0.016, P = 0.0006) and mean segmental bronchial wall area percent (β = 0.26, P = 0.0013). For imaging characteristics assessed by visual interpretation, a higher PGSBMI was associated with reduced emphysema in both COPD-enriched cohorts (OR for a higher severity grade = 0.89, P = 0.0080) and in the community-based Framingham Heart Study (OR for the presence of emphysema = 0.82, P = 0.0034), and a higher risk of airway wall thickening in the COPDGene study (OR = 1.17, P = 0.0023). In individuals with and without COPD, a higher BMI polygenic risk is associated with both quantitative and visual decreased emphysema and increased AWT, suggesting genetic determinants of BMI affect both emphysema and airway wall thickening.

RATIONALE:While low body mass index (BMI) is associated with emphysema and obesity is associated with airway disease in chronic obstructive pulmonary disease (COPD), the underlying mechanisms are unclear. OBJECTIVES:To examine the association between BMI-related genetic variants and emphysema and airway disease imaging phenotypes. METHODS:We aggregated genetic variants from population-based genome-wide association studies to generate a polygenic score of BMI (PGSBMI). We examined associations of the PGSBMI with automated quantification and visual interpretation of computed tomographic emphysema and airway wall thickness (AWT) in COPD-enriched and community-based cohorts. We summarized the results using meta-analysis. MEASUREMENTS AND MAIN RESULTS:In the meta-analyses combining results of all cohorts (n = 16 349), a standard-deviation increase of the PGSBMI was associated with less emphysema as quantified by log-transformed percent of low attenuation areas ≤950 Hounsfield units (β = -0.062, P < .0001) and 15th percentile value of lung density histogram (β = 2.27, P < .0001), and increased AWT as quantified by the square root of wall area of a 10-mm lumen perimeter airway (β = 0.016, P = .0006) and mean segmental bronchial wall area percent (β = 0.26, P = .0013). For imaging characteristics assessed by visual interpretation, a higher PGSBMI was associated with reduced emphysema in both COPD-enriched cohorts (odds ratio [OR] for a higher severity grade = 0.89, P = .0080) and in the community-based Framingham Heart Study (OR for the presence of emphysema = 0.82, P = .0034), and a higher risk of airway wall thickening in the COPDGene study (OR = 1.17, P = .0023). CONCLUSIONS:In individuals with and without COPD, a higher BMI polygenic risk is associated with both quantitative and visual decreased emphysema and increased AWT, suggesting genetic determinants of BMI affect both emphysema and airway wall thickening.

Plasma proteomic scores for body mass index have been derived primarily in European populations, and it is unclear whether these scores are generalizable and useful in other ancestries. Here, we show that plasma proteomic BMI scores developed in participants of European, East Asian, South Asian and African ancestries from the UK Biobank (UKBB; N=50,621) and the South African Middle-Aged Soweto Cohort (MASC; N=948) are portable across ancestries, explain up to 48.7% of trait variance and significantly predict incident obesity. We identified eight protein biomarkers common across all scores, six of which showed causal associations with BMI in Mendelian randomization analyses and were associated with BMI across the Olink (UKBB, MASC) and SomaScan platforms (Qatar Biobank; N= 2410). Discrepancy analysis between the high predicted proteomic BMI and low measured BMI revealed metabolically unhealthy normal weight (MUNW) individuals, with higher visceral fat, elevated triglycerides, and low insulin sensitivity. Thus, plasma proteomic BMI scores may enhance the precision of cardiometabolic risk stratification across diverse populations

Plasma proteomic scores for body mass index have been derived primarily in European populations, and it is unclear whether these scores are generalizable and useful in other ancestries. Here, we show that plasma proteomic BMI scores developed in participants of European, East Asian, South Asian and African ancestries from the UK Biobank (UKBB; N = 50,621) and the South African Middle-Aged Soweto Cohort (MASC; N = 948) are portable across ancestries, explain up to 48.7% of trait variance and significantly predict incident obesity. We identified eight protein biomarkers common across all scores, six of which showed causal associations with BMI in Mendelian randomization analyses and were associated with BMI across the Olink (UKBB, MASC) and SomaScan platforms (Qatar Biobank; N = 2410). Discrepancy analysis between the high predicted proteomic BMI and low measured BMI revealed metabolically unhealthy normal weight (MUNW) individuals, with higher visceral fat, elevated triglycerides, and low insulin sensitivity. Thus, plasma proteomic BMI scores may enhance the precision of cardiometabolic risk stratification across diverse populations.

RATIONALE: Chronic Obstructive Pulmonary Disease (COPD) exacerbations, manifesting as episodes of respiratory symptoms worsening, are a major cause of COPD morbidity and mortality. While severe COPD patients are prone to exacerbations, there is marked heterogeneity in exacerbation frequency, duration, severity, and response to treatment. Understanding the molecular mechanisms behind this heterogeneity could inform the development of targeted therapies. OBJECTIVES: To identify COPD exacerbation endotypes – i.e. individuals with shared biology – within individuals with severe COPD (GOLD spirometry grade 3-4) using individual-level networks. METHODS: We use a gene regulatory network (GRN) modeling approach to dissect heterogeneity among participants in the COPDGene study with severe COPD (GOLD 3-4). Generally, GRNs model molecular interactions regulating gene expression as networks of genes and transcription factors (TF). We reconstruct individual GRNs for each study subject by applying the PANDA and LIONESS algorithms to predicted TF-binding and whole blood RNA-Seq data from the COPDGene 5-year follow-up visit. These GRNs are composed of weighted edges representing subject-specific TF-gene interactions. For each TF-gene pair, we perform linear regression of subjects’ edge weights against annual exacerbation rates, adjusting for confounders, and select TF-gene edges with significant associations (FDR<0.1). We cluster COPD subjects by their weights in this significant edge subset and compare spirometry, imaging, and molecular traits across clusters. Marker regulatory edges—edges with weight distributions differing significantly in a given cluster compared to others—are identified for each group. Finally, we perform Gene Set Enrichment Analysis. RESULTS: We include 418 GOLD 3-4 COPD participants with individual-level regulatory networks. Clustering analysis identifies two endotypes with similar exacerbation rates and quantitative emphysema but different clinical and molecular characteristics. One endotype (low airway group) exhibits significantly lower (p-val<0.1) CT-assessed wall area percentage and Pi10, lower FEV1/FVC ratio, and higher peripheral blood lymphocyte percentage. Marker nodes of this cluster are associated (FDR<0.1) with the Cell Adhesion Molecules, Antigen Processing and Presentation, and Asthma KEGG pathways. Conversely, another cluster (high airway group) displays significantly higher (p-val<0.1) airway wall area percentage, Pi10, and neutrophil percentage, and lower lymphocyte percentage. Enriched pathways (FDR<0.1) in its marker nodes include the Cytokine-cytokine Receptor Interaction, WNT signaling, and Purine Metabolism KEGG pathways. CONCLUSION: By reconstructing the individual GRNs of severe COPD subjects, our study identifies two endotypes with distinct physiological, clinical, and molecular patterns. These results shed light on the molecular processes underlying COPD exacerbation risk, generating testable predictions that could improve the drug-target selection process.

Rationale: Patients with chronic obstructive pulmonary disease (COPD) often suffer from comorbid conditions, including type 2 diabetes (T2DM). There is increasing evidence that the presence of COPD and concomitant T2DM is associated with an increased risk of exacerbations, hospitalizations, and mortality. Recent real-world data suggest the exacerbation reduction effect of inhaled triple therapy is attenuated among patients with T2DM, as compared to those receiving dual bronchodilator therapy. Thus, the effectiveness of COPD treatments may be affected by the presence of comorbidities, specifically T2DM. Ensifentrine is a first-in-class, selective, dual inhibitor of phosphodiesterase (PDE)3 and PDE4 with bronchodilation and non-steroidal anti-inflammatory effects. Objective: To compare the effects of ensifentrine vs placebo on lung function and exacerbation rate in patients with moderate-to-severe COPD and concomitant T2DM in a pooled, post-hoc analysis of the ENHANCE program. Methods: Two Phase 3, global, multi-center, randomized, double-blind, placebo-controlled trials were conducted in symptomatic, moderate-to-severe COPD patients (FEV1 30–70% predicted; FEV1/FVC <0.7; mMRC ≥2). Patients were randomized (5:3) to receive nebulized ensifentrine 3 mg or placebo twice daily via standard jet nebulizer for 24 weeks. The primary endpoint was average FEV1 AUC0-12h at Week 12 (change from baseline [CFB]). Moderate/severe exacerbation rate was evaluated over 24 weeks. A post-hoc pooled evaluation was conducted on the effect of ensifentrine vs placebo on lung function and moderate/severe exacerbations in a subgroup of patients with concomitant type 2 diabetes. Results: The pooled analyses included 975 ensifentrine-treated and 574 placebo-treated subjects. The subgroup of patients with comorbid T2DM consisted of 138 (14%) ensifentrine-treated and 107 (19%) placebo-treated patients. Treatment with ensifentrine improved lung function vs placebo at Week 12 (placebo-corrected least-squares mean CFB: average FEV1 AUC0-12h = 116 mL; peak FEV1 = 179 mL; both p<0.0001). Moderate/severe exacerbation rate was numerically reduced by 36% with ensifentrine vs placebo (rate ratio: 0.64, 95% CI 0.32, 1.31; p=0.223). The safety profile of ensifentrine in patients with concomitant COPD and T2DM was consistent with the previously reported primary results and similar to patients taking placebo. Conclusion: In patients with COPD and T2DM, ensifentrine treatment resulted in significant improvements in lung function and a numerical reduction in the moderate/severe exacerbation rate vs placebo. Given concerns about the risks of triple therapy in patients with T2DM, this data supports that ensifentrine has the potential for clinically meaningful benefits in this population by offering a novel, non-steroidal, anti-inflammatory mechanism of action.

Background Chronic Obstructive Pulmonary Disease (COPD) has a broad spectrum of clinical characteristics. The aetiology of these differences is not well understood. The objective of this study is to assess whether respiratory genetic variants cluster by phenotype and associate with COPD heterogeneity. Methods We clustered genome-wide association studies of COPD, lung function, and asthma and phenotypes from the UK Biobank using non-negative matrix factorization. We constructed cluster-specific genetic risk scores and tested these scores for association with phenotypes in non-Hispanic white subjects in the COPDGene study. Findings We identified three clusters from 482 variants and 44 traits from genetic associations in 379,337 UK Biobank participants. Variants from asthma, COPD, and lung function were found in all three clusters. Clusters displayed varying effects on white blood cell counts, height, and body mass index (BMI)-related phenotypes in the UK Biobank. In the COPDGene cohort, cluster-specific genetic risk scores were associated with differences in steroid use, BMI, lymphocyte counts, and chronic bronchitis, as well as variations in gene and protein expression. Interpretation Our results suggest that multi-phenotype analysis of obstructive lung disease-related risk variants may identify genetically driven phenotypic patterns in COPD.

Micro-ribonucleic acids (miRNAs) are key post-transcriptional regulators of the immune system and may play a role in Chronic Obstructive Pulmonary Disease (COPD). In this paper, we constructed subject-specific miRNA-mRNA regulatory networks using bulk and deconvoluted whole blood RNA-sequencing, whole blood miRNA-sequencing, and B-cell receptor-sequencing data from up to 570 miRNAs, 11,859 mRNAs, and 3,190 participants in the COPDGene study. Analysis of whole blood networks revealed two subnetworks of miRNA-mRNA interactions significantly (FDR<0.05) associated with changes in FEV 1 / FVC . We found that miRNAs (and mRNAs) in the network-identified groups had distinct expression patterns, with miRNAs (and mRNAs) in one group having overall higher expression in COPD (decreasing FEV 1 / FVC ) and miRNAs (and mRNAs) in the other group having overall higher expression in controls (increasing FEV 1 / FVC ). In addition, miRNAs (and mRNAs) within the same group were positively correlated, while those in different groups were negatively correlated, indicating distinct functional roles for these miRNAs (and mRNAs) as a function of increased COPD severity. Network analysis also identified PAX5, a transcription factor master regulator of B-cell development, as the main mRNA network hub. Using ChIP-seq data in lymphoblastoid cells, we identified a PAX5 binding site overlapping with a COPD genome-wide association signal in the promoter region of ADAM19. We also found a loss of co-expression between PAX5 and ADAM19 in COPD subjects. Furthermore, in B-cell deconvoluted data, PAX5 was differentially co-expressed with genes associated with B-cell activation and differentiation, revealing a possible mechanism for the regulation of the immune response in COPD. Finally, in B-cell receptor sequencing data, PAX5 and the identified mRNA subnetworks were negatively associated (FDR<0.05) with immunoglobulin class switching, and positively associated with IgM and IgD counts. In conclusion, PAX5 is a known regulator of B-cell identity. B cells are recognized as key players in chronic inflammation and immune dysregulation in COPD. Our work suggests that PAX5 plays a mediating role both in ADAM19 regulation and in miRNA regulation of early B cells in COPD.

Rationale: Lung function trajectories are associated with risk for cardiopulmonary diseases and mortality. While many genetic variants influencing lung function measured at a single time point have been identified, it remains unclear whether these variants are associated with lung function decline in adulthood. Methods: We selected participants aged ≥21 years from the Framingham Heart Study (FHS) and the Coronary Artery Risk Development in Young Adults (CARDIA) study, two population-based studies with longitudinal lung function measurements. Based on external GWAS data, we previously developed polygenic risk scores (PRS) for FEV1 (PRSFEV1) and FEV1/FVC (PRSratio), summarizing the cumulative effects of genetic variants across the genome, with higher scores indicating lower genetically predicted lung function. Associations between the PRSs and corresponding traits were tested using mixed-effects models to account for repeated measures. We tested an interaction between each PRS and age to estimate its effect on lung function decline and conducted stratified analyses by sex. We adjusted for height, smoking, and genetic ancestry. We tested the association between PRSratio and early-life airflow limitation (defined as FEV1/FVC < 0.7 before age of 40) using logistic regression, and compared the prediction performance between PRSratio and clinical risk factors (age, sex, and smoking pack-years) using the Area-Under-the-Receiver-Operating-Characteristic-Curve (AUC-ROC) metrics. Measurements and Main Results: We included 5,682 (mean baseline age 45.5 years; 47.5% male) FHS and 2,387 (mean baseline age 26.1 years; 43.0% male) CARDIA participants, with average follow-up duration of 12.0 and 15.0 years, respectively. A one-standard-deviation increase in the PRSFEV1 was associated with 153.6 ml and 148.4 ml lower FEV1 in FHS and CARDIA, respectively; however, no significant effect of PRSFEV1 on FEV1 decline was observed. We found a significant interaction between PRSratio and age on FEV1/FVC in FHS (β= -0.0093%, p=0.0013) but not in CARDIA (β= -0.0077%, p=0.087). In sex-stratified analyses, the interaction between PRSratio and age was significant in females in both FHS (β= -0.013%, p=0.0021) and CARDIA (β= -0.022%, p=0.0002), but not in males (β= -0.0066%, p=0.16 in FHS; β= 0.0073%, p=0.27 in CARDIA). For predicting early-life airflow limitation, the PRSratio outperformed clinical risk (AUC: 0.70 versus 0.58; p-value for AUC difference=0.0002) in FHS. Conclusions: The PRSFEV1 was associated with low FEV1 early in adulthood but not with its decline. The PRSratio was associated with FEV1/FVC decline in females and showed superior predictive performance for early-life airflow limitation than clinical risk factors.

ImportanceChronic obstructive pulmonary disease (COPD) is often undiagnosed. Although genetic risk plays a significant role in COPD susceptibility, its utility in guiding spirometry testing and identifying undiagnosed cases is unclear.ObjectiveTo determine whether a COPD polygenic risk score (PRS) enhances the identification of undiagnosed COPD beyond a case-finding questionnaire (eg, the Lung Function Questionnaire) using conventional risk factors and respiratory symptoms.Design, Setting, and ParticipantsThis cross-sectional analysis of participants 35 years or older who reported no history of physician-diagnosed COPD was conducted using data from 2 observational studies: the community-based Framingham Heart Study (FHS) and the COPD-enriched Genetic Epidemiology of COPD (COPDGene) study.ExposuresModified Lung Function Questionnaire (mLFQ) scores and COPD PRS.Main Outcomes and MeasuresThe primary outcome was spirometry-defined moderate to severe COPD (forced expiratory volume in the first second of expiration/forced vital capacity [FEV1/FVC] <0.7 and FEV1 [percent predicted] <80%). The performance of logistic models was assessed using the PRS, mLFQ score, and PRS plus mLFQ score for predicting spirometry-defined COPD.ResultsAmong 3385 FHS participants (median age, 52.0 years; 45.9% male) and 4095 COPDGene participants (median age, 56.8 years; 55.5% male) who reported no history of COPD, 160 (4.7%) FHS and 775 (18.9%) COPDGene participants had spirometry-defined COPD. Adding the PRS to the mLFQ score significantly improved the area under the curve from 0.78 to 0.84 (P < .001) in FHS, 0.69 to 0.72 (P = .04) in COPDGene non-Hispanic African American, and 0.75 to 0.78 (P < .001) in COPDGene non-Hispanic White participants. At a risk threshold for spirometry referral of 10%, the addition of the PRS to the mLFQ score correctly reclassified 13.8% (95% CI, 6.6%-21.0%) of COPD cases in FHS, but not in COPDGene.Conclusions and RelevanceA COPD PRS enhances the identification of undiagnosed COPD beyond a conventional case-finding approach in the general population. Further research is needed to assess its impact on COPD diagnosis and outcomes.

There is substantial unexplained variability in the development of disease. A genetic risk score for COPD identifies individuals at markedly elevated risk of COPD; however, many high-genetic risk individuals do not develop disease. We sought to define genetic resilience in COPD by identifying and characterizing individuals who are resistant to their elevated genetic susceptibility. We defined resilience to genetic risk (genetic resilience) as absence of airflow obstruction (FEV1/FVC ≥ 0.70) in individuals with cigarette smoking exposure with a polygenic risk score for COPD at the 90th percentile or above. We defined clinical resilience according to previously published criteria, including a low symptom burden, limited radiographic disease, and normal lung-function decline despite similar smoking history. Using data from the Genetic Epidemiology of COPD (COPDGene) study, we compared genetically resilient individuals to clinically resilient individuals and genetic risk-matched individuals with COPD on clinical characteristics, radiographic findings, longitudinal outcomes, mortality, biomarkers, and social determinants of health. We found that, after adjustment for covariates, genetically resilient individuals (n = 144) had better lung function (β = 35.9