Whole-genome sequencing in 333,100 individuals reveals rare non-coding single variant and aggregate associations with height.

The role of rare non-coding variation in complex human phenotypes is still largely unknown. To elucidate the impact of rare variants in regulatory elements, we performed a whole-genome sequencing association analysis for height using 333,100 individuals from three datasets: UK Biobank (N = 200,003), TOPMed (N = 87,652) and All of Us (N = 45,445). We performed rare ( < 0.1% minor-allele-frequency) single-variant and aggregate testing of non-coding variants in regulatory regions based on proximal-regulatory, intergenic-regulatory and deep-intronic annotation. We observed 29 independent variants associated with height at P < 6 × 10 - 10 after conditioning on previously reported variants, with effect sizes ranging from -7cm to +4.7 cm. We also identified and replicated non-coding aggregate-based associations proximal to HMGA1 containing variants associated with a 5 cm taller height and of highly-conserved variants in MIR497HG on chromosome 17. We have developed an approach for identifying non-coding rare variants in regulatory regions with large effects from whole-genome sequencing data associated with complex traits.

B cell immune repertoire sequencing in tobacco cigarette smoking, vaping, and chronic obstructive pulmonary disease in the COPDGene cohort.

Rationale: Cigarette smoking (CS) impairs B cell function and antibody production, increasing infection risk. The impact of e-cigarette use ('vaping') and combined CS and vaping ('dual-use') on B cell activity is unclear. Objective: To examine B cell receptor sequencing (BCR-seq) profiles associated with CS, vaping, dual-use, COPD-related outcomes, and demographic factors. Methods: BCR-seq was performed on blood RNA samples from 234 participants in the COPDGene study. We assessed multivariable associations of B cell function measures (immunoglobulin heavy chain (IGH) subclass expression and usage, class-switching, V-segment usage, and clonal expansion) with CS, vaping, dual-use, COPD severity, age, sex, and race. We adjusted for multiple comparisons using the Benjamini-Hochberg method, identifying significant associations at 5% FDR and suggestive associations at 10% FDR. Results: Among 234 non-Hispanic white (NHW) and African American (AA) participants, CS and dual-use were significantly positively associated with increased secretory IgA production, with dual-use showing the strongest associations. Dual-use was positively associated with class switching and B cell clonal expansion, indicating increased B cell activation, with similar trends in those only smoking or only vaping. We observed significant associations between race and IgG antibody usage. AA participants had higher IgG subclass proportions and lower IgM usage compared to NHW participants. Conclusions: CS and vaping additively enhance B cell activation, most notably in dual-users. Self-reported race was strongly associated with IgG isotype usage. These findings highlight associations between B cell activation and antibody transcription, suggesting potential differences in immune and vaccine responses linked to CS, vaping, and race.

Airway Mucus Plugs on Chest Computed Tomography Are Associated with Exacerbations in COPD.

Rationale/Objective: Acute exacerbations (AEs) of chronic obstructive pulmonary disease (COPD) are associated with significant morbidity and mortality. Whether mucus plugs are associated with prospective exacerbations has not been examined extensively. METHODS: Mucus plugs were visually-identified on baseline chest computed tomography (CT) scans from smokers with Global Initiative for Chronic Obstructive Lung Disease (GOLD) grades 2-4 COPD enrolled in two multicenter cohort studies: Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) and COPDGene. Associations between ordinal mucus plug score categories (0/1-2/≥3) and prospectively-ascertained AEs, defined as worsening respiratory symptoms requiring systemic steroids and/or antibiotics (moderate-to-severe) and/or ER/hospitalization (severe), were assessed using multivariable-adjusted zero-inflated Poisson regression; subjects were exacerbation-free at enrollment. RESULTS: Among 3,250 participants in COPDGene (mean±SD age 63.7±8.4 years, FEV1 50.6%±17.8% predicted, 45.1% female) and 1,716 participants in ECLIPSE (age 63.3±7.1 years, FEV1 48.3%±15.8% predicted, 36.2% female), 44.4% and 46.0% had mucus plugs, respectively. The incidence rates of AEs were 61.0 (COPDGene) and 125.7 (ECLIPSE) per 100 person-years. Relative to those without mucus plugs, the presence of 1-2 and ≥3 mucus plugs was associated with increased risk (adjusted rate ratio, aRR [95%CI]=1.07[1.05-1.09] and 1.15[1.1-1.2] in COPDGene; aRR=1.06[1.02-1.09] and 1.12[1.04-1.2] in ECLIPSE, respectively) for prospective moderate-to-severe AEs. The presence of 1-2 and ≥3 mucus plugs was also associated with increased risk for severe AEs during follow-up (aRR=1.05[1.01-1.08] and 1.09[1.02-1.18] in COPDGene; aRR=1.17[1.07-1.27] and 1.37[1.15-1.62] in ECLIPSE, respectively). CONCLUSION: CT-based mucus plugs are associated with an increased risk for future COPD AEs.

Partial correlation network analysis identifies coordinated gene expression within a regional cluster of COPD genome-wide association signals.

Chronic obstructive pulmonary disease (COPD) is a complex disease influenced by well-established environmental exposures (most notably, cigarette smoking) and incompletely defined genetic factors. The chromosome 4q region harbors multiple genetic risk loci for COPD, including signals near HHIP, FAM13A, GSTCD, TET2, and BTC. Leveraging RNA-Seq data from lung tissue in COPD cases and controls, we estimated the co-expression network for genes in the 4q region bounded by HHIP and BTC (~70MB), through partial correlations informed by protein-protein interactions. We identified several co-expressed gene pairs based on partial correlations, including NPNT-HHIP, BTC-NPNT and FAM13A-TET2, which were replicated in independent lung tissue cohorts. Upon clustering the co-expression network, we observed that four genes previously associated to COPD: BTC, HHIP, NPNT and PPM1K appeared in the same network community. Finally, we discovered a sub-network of genes differentially co-expressed between COPD vs controls (including FAM13A, PPA2, PPM1K and TET2). Many of these genes were previously implicated in cell-based knock-out experiments, including the knocking out of SPP1 which belongs to the same genomic region and could be a potential local key regulatory gene. These analyses identify chromosome 4q as a region enriched for COPD genetic susceptibility and differential co-expression.

HHIP's Dynamic Role in Epithelial Wound Healing Reveals a Potential Mechanism of COPD Susceptibility.

A genetic variant near HHIP has been consistently identified as associated with increased risk for Chronic Obstructive Pulmonary Disease (COPD), the third leading cause of death worldwide. However HHIP's role in COPD pathogenesis remains elusive. Canonically, HHIP is a negative regulator of the hedgehog pathway and downstream GLI1 and GLI2 activation. The hedgehog pathway plays an important role in wound healing, specifically in activating transcription factors that drive the epithelial mesenchymal transition (EMT), which in its intermediate state (partial EMT) is necessary for the collective movement of cells closing the wound. Herein, we propose a mechanism to explain HHIP's role in faulty epithelial wound healing, which could contribute to the development of emphysema, a key feature of COPD. Using two different Boolean models compiled from the literature, we show dysfunctional HHIP results in a lack of negative feedback on GLI, triggering a full EMT, where cells become mesenchymal and do not properly close the wound. We validate these Boolean models with experimental evidence gathered from published scientific literature. We also experimentally test if low HHIP expression is associated with EMT at the edge of wounds by using a scratch assay in a human lung epithelial cell line. Finally, we show evidence supporting our hypothesis in bulk and single cell RNA-Seq data from different COPD cohorts. Overall, our analyses suggest that aberrant wound healing due to dysfunctional HHIP, combined with chronic epithelial damage through cigarette smoke exposure, may be a primary cause of COPD-associated emphysema.

Chitinase 3-like-1 Inhibits Innate Antitumor and Tissue Remodeling Immune Responses by Regulating CD47-SIRPα- and CD24-Siglec10-Mediated Phagocytosis.

Innate immune responses such as phagocytosis are critically linked to the generation of adaptive immune responses against the neoantigens in cancer and the efferocytosis that is essential for homeostasis in diseases characterized by lung injury, inflammation, and remodeling as in chronic obstructive pulmonary disease (COPD). Chitinase 3-like-1 (CHI3L1) is induced in many cancers where it inhibits adaptive immune responses by stimulating immune checkpoint molecules (ICPs) and portends a poor prognosis. CHI3L1 is also induced in COPD where it regulates epithelial cell death. In this study, we demonstrate that pulmonary melanoma metastasis inhibits macrophage phagocytosis by stimulating the CD47-SIRPα and CD24-Siglec10 phagocytosis checkpoint pathways while inhibiting macrophage "eat me" signals from calreticulin and HMGB1. We also demonstrate that these effects on macrophage phagocytosis are associated with CHI3L1 stimulation of the SHP-1 and SHP-2 phosphatases and inhibition of the accumulation and phosphorylation of cytoskeleton-regulating nonmuscle myosin IIa. This inhibition of innate immune responses such as phagocytosis provides a mechanistic explanation for the ability of CHI3L1 to stimulate ICPs and inhibit adaptive immune responses in cancer and diseases such as COPD. The ability of CHI3L1 to simultaneously inhibit innate immune responses, stimulate ICPs, inhibit T cell costimulation, and regulate a number of other oncogenic and inflammation pathways suggests that CHI3L1-targeted therapeutics are promising interventions in cancer, COPD, and other disorders.

A protein risk score for all-cause and respiratory-specific mortality in non-Hispanic white and African American individuals who smoke.

Protein biomarkers are associated with mortality in cardiovascular disease, but their effect on predicting respiratory and all-cause mortality is not clear. We tested whether a protein risk score (protRS) can improve prediction of all-cause mortality over clinical risk factors in smokers. We utilized smoking-enriched (COPDGene, LSC, SPIROMICS) and general population-based (MESA) cohorts with SomaScan proteomic and mortality data. We split COPDGene into training and testing sets (50:50) and developed a protRS based on respiratory mortality effect size and parsimony. We tested multivariable associations of the protRS with all-cause, respiratory, and cardiovascular mortality, and performed meta-analysis, area-under-the-curve (AUC), and network analyses. We included 2232 participants. In COPDGene, a penalized regression-based protRS was most highly associated with respiratory mortality (OR 9.2) and parsimonious (15 proteins). This protRS was associated with all-cause mortality (random effects HR 1.79 [95% CI 1.31-2.43]). Adding the protRS to clinical covariates improved all-cause mortality prediction in COPDGene (AUC 0.87 vs 0.82) and SPIROMICS (0.74 vs 0.6), but not in LSC and MESA. Protein-protein interaction network analyses implicate cytokine signaling, innate immune responses, and extracellular matrix turnover. A blood-based protein risk score predicts all-cause and respiratory mortality, identifies potential drivers of mortality, and demonstrates heterogeneity in effects amongst cohorts.

Genetic Architecture and Analysis Practices of Circulating Metabolites in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program.

Circulating metabolite levels partly reflect the state of human health and diseases, and can be impacted by genetic determinants. Hundreds of loci associated with circulating metabolites have been identified; however, most findings focus on predominantly European ancestry or single study analyses. Leveraging the rich metabolomics resources generated by the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program, we harmonized and accessibly cataloged 1,729 circulating metabolites among 25,058 ancestrally-diverse samples. We provided recommendations for outlier and imputation handling to process metabolite data, as well as a general analytical framework. We further performed a pooled analysis following our practical recommendations and discovered 1,778 independent loci associated with 667 metabolites. Among 108 novel locus - metabolite pairs, we detected not only novel loci within previously implicated metabolite associated genes, but also novel genes (such as GAB3 and VSIG4 located in the X chromosome) that have putative roles in metabolic regulation. In the sex-stratified analysis, we revealed 85 independent locus-metabolite pairs with evidence of sexual dimorphism, including well-known metabolic genes such as FADS2 , D2HGDH , SUGP1 , UTG2B17 , strongly supporting the importance of exploring sex difference in the human metabolome. Taken together, our study depicted the genetic contribution to circulating metabolite levels, providing additional insight into the understanding of human health.

Sex-biased Regulation of Extracellular Matrix Genes in COPD.

Compared to men, women often develop COPD at an earlier age with worse respiratory symptoms despite lower smoking exposure. However, most preventive, and therapeutic strategies ignore biological sex differences in COPD. Our goal was to better understand sex-specific gene regulatory processes in lung tissue and the molecular basis for sex differences in COPD onset and severity. We analyzed lung tissue gene expression and DNA methylation data from 747 individuals in the Lung Tissue Research Consortium (LTRC), and 85 individuals in an independent dataset. We identified sex differences in COPD-associated gene regulation using gene regulatory networks. We used linear regression to test for sex-biased associations of methylation with lung function, emphysema, smoking, and age. Analyzing gene regulatory networks in the control group, we identified that genes involved in the extracellular matrix (ECM) have higher transcriptional factor targeting in females than in males. However, this pattern is reversed in COPD, with males showing stronger regulatory targeting of ECM-related genes than females. Smoking exposure, age, lung function, and emphysema were all associated with sex-specific differential methylation of ECM-related genes. We identified sex-based gene regulatory patterns of ECM-related genes associated with lung function and emphysema. Multiple factors including epigenetics, smoking, aging, and cell heterogeneity influence sex-specific gene regulation in COPD. Our findings underscore the importance of considering sex as a key factor in disease susceptibility and severity.

Development, Progression, and Mortality of Suspected Interstitial Lung Disease in COPDGene.

RATIONALE: Some with interstitial lung abnormalities (ILA) have suspected interstitial lung disease (ILD), a subgroup with adverse outcomes. Rates of development and progression of suspected ILD and their effect on mortality are unknown. OBJECTIVES: To determine rates of development and progression of suspected ILD and assess effects of individual ILD and progression criteria on mortality. METHODS: Participants from COPDGene were included. ILD was defined as ILA and fibrosis and/or FVC <80% predicted. Prevalent ILD was assessed at enrollment, incident ILD and progression at 5-year follow-up. CT progression was assessed visually and FVC decline as relative change. Multivariable Cox regression tested associations between mortality and ILD groups. RESULTS: Of 9,588 participants at enrollment, 267 (2.8%) had prevalent ILD. Those with prevalent ILD had 52% mortality after median 10.6 years, which was higher than ILA (33%; HR=2.0; p<0.001). The subgroup of prevalent ILD with fibrosis only had worse mortality (59%) than ILA (HR=2.2; p<0.001). 97 participants with prevalent ILD completed 5-year follow-up: 32% had stable CT and relative FVC decline <10%, 6% FVC decline ≥10% only, 39% CT progression only, and 22% both CT progression and FVC decline ≥10%. Mortality rates were 32%, 50%, 45%, and 46% respectively; those with CT progression only had worse mortality than ILA (HR=2.6; p=0.005). At 5-year follow-up, incident ILD occurred in 168/4,843 participants without prevalent ILD and had worse mortality than ILA (HR=2.5; p<0.001). CONCLUSION: Rates of mortality and progression are high among those with suspected ILD in COPDGene; fibrosis and radiologic progression are important predictors of mortality.

COPD Subtypes Are Differentially Associated With Cardiovascular Events and COPD Exacerbations.

BACKGROUND: The coronary artery calcium score (CACS) and ratio of the pulmonary artery to aorta diameters (PA:A ratio) measured from chest CT scans have been established as predictors of cardiovascular events and COPD exacerbations, respectively. However, little is known about the reciprocal relationship between these predictors and outcomes. Furthermore, the prognostic implications of COPD subtypes on clinical outcomes remain insufficiently characterized. RESEARCH QUESTION: How can these two chest CT scan-derived parameters predict subsequent cardiovascular events and COPD exacerbations in different COPD subtypes? STUDY DESIGN AND METHODS: Using COPDGene study data, we assessed prospective cardiovascular disease (CVD) and COPD exacerbation risk in patients with COPD (Global Initiative for Chronic Obstructive Lung Disease spirometric grades 2-4), focusing on CACS and PA:A ratio at study enrollment, with logistic regression models. These outcomes were analyzed in three COPD subtypes: 1,042 patients with non-emphysema-predominant disease (NEPD) (low attenuation area at -950 Hounsfield units [LAA-950] < 5%), 1,324 patients with emphysema-predominant disease (EPD) (LAA-950 ≥ 10%), and 465 patients with intermediate emphysema disease (5% ≤ LAA-950 < 10%). RESULTS: Our study indicated significantly higher overall risk for cardiovascular events in patients with higher CACS (≥ median; OR, 1.61; 95% CI, 1.30-2.00) and increased COPD exacerbations in those with higher PA:A ratios (≥ 1; OR, 1.80; 95% CI, 1.46-2.23). Notably, patients with NEPD showed a stronger association between these indicators and clinical events than those with EPD (with CACS/CVD, NEPD vs EPD: OR, 2.02 vs 1.41; with PA:A ratio/COPD exacerbation, NEPD vs EPD: OR, 2.50 vs 1.65); the difference in ORs between COPD subtypes was statistically significant for CACS/CVD. INTERPRETATION: Two chest CT scan parameters, CACS and PA:A ratio, hold distinct predictive values for cardiovascular events and COPD exacerbations that are influenced by specific COPD subtypes. TRIAL REGISTRATION: ClinicalTrials.gov; No.: NCT00608764; URL: www. CLINICALTRIALS: gov.

Identification of factors directly linked to incident chronic obstructive pulmonary disease: A causal graph modeling study.

BACKGROUND: Beyond exposure to cigarette smoking and aging, the factors that influence lung function decline to incident chronic obstructive pulmonary disease (COPD) remain unclear. Advancements have been made in categorizing COPD into emphysema and airway predominant disease subtypes; however, predicting which healthy individuals will progress to COPD is difficult because they can exhibit profoundly different disease trajectories despite similar initial risk factors. This study aimed to identify clinical, genetic, and radiological features that are directly linked-and subsequently predict-abnormal lung function. METHODS AND FINDINGS: We employed graph modeling on 2,643 COPDGene participants (aged 45 to 80 years, 51.25% female, 35.1% African Americans; enrollment 11/2007-4/2011) with smoking history but normal spirometry at study enrollment to identify variables that are directly linked to future lung function abnormalities. We developed logistic regression and random forest predictive models for distinguishing individuals who maintain lung function from those who decline. Of the 131 variables analyzed, 6 were identified as informative to future lung function abnormalities, namely forced expiratory flow in the middle range (FEF25-75%), average lung wall thickness in a 10 mm radius (Pi10), severe emphysema, age, sex, and height. We investigated whether these features predict individuals leaving GOLD 0 status (normal spirometry according to Global Initiative for Obstructive Lung Disease (GOLD) criteria). Linear models, trained with these features, were quite predictive (area under receiver operator characteristic curve or AUROC = 0.75). Random forest predictors performed similarly to logistic regression (AUROC = 0.7), indicating that no significant nonlinear effects were present. The results were externally validated on 150 participants from Specialized Center for Clinically Oriented Research (SCCOR) cohort (aged 45 to 80 years, 52.7% female, 4.7% African Americans; enrollment: 7/2007-12/2012) (AUROC = 0.89). The main limitation of longitudinal studies with 5- and 10-year follow-up is the introduction of mortality bias that disproportionately affects the more severe cases. However, our study focused on spirometrically normal individuals, who have a lower mortality rate. Another limitation is the use of strict criteria to define spirometrically normal individuals, which was unavoidable when studying factors associated with changes in normalized forced expiratory volume in 1 s (FEV1%predicted) or the ratio of FEV1/FVC (forced vital capacity). CONCLUSIONS: This study took an agnostic approach to identify which baseline measurements differentiate and predict the early stages of lung function decline in individuals with previous smoking history. Our analysis suggests that emphysema affects obstruction onset, while airway predominant pathology may play a more important role in future FEV1 (%predicted) decline without obstruction, and FEF25-75% may affect both.

Overlap between COPD genetic association results and transcriptional quantitative trait loci.

Rationale: Genome-wide association studies (GWAS) have identified multiple genetic loci associated with chronic obstructive pulmonary disease (COPD). When integrated with GWAS results, expression quantitative trait locus (eQTL) studies can provide insight into biological mechanisms involved in disease by identifying single nucleotide polymorphisms (SNPs) that contribute to whole gene expression. However, there are multiple genetically driven regulatory and isoform-specific effects which cannot be detected in traditional eQTL analyses. Here, we identify SNPs that are associated with alternative splicing (sQTL) in addition to eQTLs to identify novel functions for COPD associated genetic variants. Methods: We performed RNA sequencing on whole blood from 3743 subjects in the COPDGene Study. RNA sequencing data from lung tissue of 1241 subjects from the Lung Tissue Research Consortium (LTRC), and whole genome sequencing data on all subjects. Associations between all SNPs within 1000 kb of a gene (cis-) and splice and gene expression quantifications were tested using tensorQTL. In COPDGene a total of 11,869,333 SNPs were tested for association with 58,318 splice clusters, and 8,792,206 SNPs were tested for association with 70,094 splice clusters in LTRC. We assessed colocalization with COPD-associated SNPs from a published GWAS[1]. Results: After adjustment for multiple statistical testing, we identified 28,110 splice-sites corresponding to 3,889 unique genes that were significantly associated with genotype in COPDGene whole blood, and 58,258 splice-sites corresponding to 10,307 unique genes associated with genotype in LTRC lung tissue. We found 7,576 sQTL splice-sites corresponding to 2,110 sQTL genes were shared between whole blood and lung, while 20,534 sQTL splice-sites in 3,518 genes were unique to blood and 50,682 splice-sites in 9,677 genes were unique to lung. To determine what proportion of COPD-associated SNPs were associated with transcriptional splicing, we performed colocalization analysis between COPD GWAS and sQTL data, and found that 38 genomic windows, corresponding to 38 COPD GWAS loci had evidence of colocalization between QTLs and COPD. The top five colocalizations between COPD and lung sQTLs include NPNT , FBXO38 , HHIP , NTN4 and BTC . Conclusions: A total of 38 COPD GWAS loci contain evidence of sQTLs, suggesting that analysis of sQTLs in whole blood and lung tissue can provide novel insights into disease mechanisms.

Association of PHACTR1 with Coronary Artery Calcium Differs by Sex and Cigarette Smoking.

Background: Coronary artery calcium (CAC) is a marker of subclinical atherosclerosis and is a complex heritable trait with both genetic and environmental risk factors, including sex and smoking. Methods: We performed genome-wide association (GWA) analyses for CAC among all participants and stratified by sex in the COPDGene study (n = 6144 participants of European ancestry and n = 2589 participants of African ancestry) with replication in the Diabetes Heart Study (DHS). We adjusted for age, sex, current smoking status, BMI, diabetes, self-reported high blood pressure, self-reported high cholesterol, and genetic ancestry (as summarized by principal components computed within each racial group). For the significant signals from the GWA analyses, we examined the single nucleotide polymorphism (SNP) by sex interactions, stratified by smoking status (current vs. former), and tested for a SNP by smoking status interaction on CAC. Results: We identified genome-wide significant associations for CAC in the chromosome 9p21 region [CDKN2B-AS1] among all COPDGene participants (p = 7.1 × 10-14) and among males (p = 1.0 × 10-9), but the signal was not genome-wide significant among females (p = 6.4 × 10-6). For the sex stratified GWA analyses among females, the chromosome 6p24 region [PHACTR1] had a genome-wide significant association (p = 4.4 × 10-8) with CAC, but this signal was not genome-wide significant among all COPDGene participants (p = 1.7 × 10-7) or males (p = 0.03). There was a significant interaction for the SNP rs9349379 in PHACTR1 with sex (p = 0.02), but the interaction was not significant for the SNP rs10757272 in CDKN2B-AS1 with sex (p = 0.21). In addition, PHACTR1 had a stronger association with CAC among current smokers (p = 6.2 × 10-7) than former smokers (p = 7.5 × 10-3) and the SNP by smoking status interaction was marginally significant (p = 0.03). CDKN2B-AS1 had a strong association with CAC among both former (p = 7.7 × 10-8) and current smokers (p = 1.7 × 10-7) and the SNP by smoking status interaction was not significant (p = 0.40). Conclusions: Among current and former smokers of European ancestry in the COPDGene study, we identified a genome-wide significant association in the chromosome 6p24 region [PHACTR1] with CAC among females, but not among males. This region had a significant SNP by sex and SNP by smoking interaction on CAC.

Lung Transcriptomics Links Emphysema to Barrier Dysfunction and Macrophage Subpopulations.

RATIONALE: While many studies have examined gene expression in lung tissue, the gene regulatory processes underlying emphysema are still not well understood. Finding efficient non-imaging screening methods and disease-modifying therapies has been challenging, but knowledge of the transcriptomic features of emphysema may help in this effort. OBJECTIVES: Our goals were to identify emphysema-associated biological pathways through transcriptomic analysis of bulk lung tissue, to determine the lung cell types in which these emphysema-associated pathways are altered, and to detect unique and overlapping transcriptomic signatures in blood and lung samples. METHODS: Using RNA-sequencing data from 446 samples in the Lung Tissue Research Consortium (LTRC) and 3,606 blood samples from the COPDGene study, we examined the transcriptomic features of chest computed tomography-quantified emphysema. We also leveraged publicly available lung single-cell RNA-sequencing data to identify cell types showing COPD-associated differential expression of the emphysema pathways found in the bulk analyses. MEASUREMENTS AND MAIN RESULTS: In the bulk lung RNA-seq analysis, 1,087 differentially expressed genes and 34 dysregulated pathways were significantly associated with emphysema. We observed alternative splicing of several genes and increased activity in pluripotency and cell barrier function pathways. Lung tissue and blood samples shared differentially expressed genes and biological pathways. Multiple lung cell types displayed dysregulation of epithelial barrier function pathways, and distinct pathway activities were observed among various macrophage subpopulations. CONCLUSIONS: This study identified emphysema-related changes in gene expression and alternative splicing, cell-type specific dysregulated pathways, and instances of shared pathway dysregulation between blood and lung.

Multi-center Korean cohort study based on RNA-sequencing data targeting COPD patients.

In 2023, WHO ranked chronic obstructive pulmonary disease (COPD) as the third leading cause of death, with 3.23 million fatalities in 2019. The intricate nature of the disease, which is influenced by genetics, environment, and lifestyle, is evident. The effect of air pollution and changes in atmospheric substances because of global warming highlight the need for this research. These environmental shifts are associated with the emergence of various respiratory infections such as COVID-19. RNA sequencing is pivotal in airway diseases, including COPD, as it enables comprehensive transcriptome analysis, biomarker discovery, and uncovers novel pathways. It facilitates personalized medicine by tracking dynamic changes in gene expression in response to various triggers. However, the limited research on East Asian populations may overlook the unique nuances of COPD development and progression. Bridging this gap and using peripheral blood samples for systemic analysis are crucial for comprehensive and globally applicable COPD diagnosis and treatment.

Rheumatoid arthritis and changes on spirometry by smoking status in two prospective longitudinal cohorts.

OBJECTIVE: To compare longitudinal changes in spirometric measures between patients with rheumatoid arthritis (RA) and non-RA comparators. METHODS: We analysed longitudinal data from two prospective cohorts: the UK Biobank and COPDGene. Spirometry was conducted at baseline and a second visit after 5-7 years. RA was identified based on self-report and disease-modifying antirheumatic drug use; non-RA comparators reported neither. The primary outcomes were annual changes in the per cent-predicted forced expiratory volume in 1 s (FEV1%) and per cent predicted forced vital capacity (FVC%). Statistical comparisons were performed using multivariable linear regression. The analysis was stratified based on baseline smoking status and the presence of obstructive pattern (FEV1/FVC <0.7). RESULTS: Among participants who underwent baseline and follow-up spirometry, we identified 233 patients with RA and 37 735 non-RA comparators. Among never-smoking participants without an obstructive pattern, RA was significantly associated with more FEV1% decline (ß=-0.49, p=0.04). However, in ever smokers with ≥10 pack-years, those with RA exhibited significantly less FEV1% decline than non-RA comparators (ß=0.50, p=0.02). This difference was more pronounced among those with an obstructive pattern at baseline (ß=1.12, p=0.01). Results were similar for FEV1/FVC decline. No difference was observed in the annual FVC% change in RA versus non-RA. CONCLUSIONS: Smokers with RA, especially those with baseline obstructive spirometric patterns, experienced lower FEV1% and FEV1/FVC decline than non-RA comparators. Conversely, never smokers with RA had more FEV1% decline than non-RA comparators. Future studies should investigate potential treatments and the pathogenesis of obstructive lung diseases in smokers with RA.

Polygenic and transcriptional risk scores identify chronic obstructive pulmonary disease subtypes.

Rationale: Genetic variants and gene expression predict risk of chronic obstructive pulmonary disease (COPD), but their effect on COPD heterogeneity is unclear. Objectives: Define high-risk COPD subtypes using both genetics (polygenic risk score, PRS) and blood gene expression (transcriptional risk score, TRS) and assess differences in clinical and molecular characteristics. Methods: We defined high-risk groups based on PRS and TRS quantiles by maximizing differences in protein biomarkers in a COPDGene training set and identified these groups in COPDGene and ECLIPSE test sets. We tested multivariable associations of subgroups with clinical outcomes and compared protein-protein interaction networks and drug repurposing analyses between high-risk groups. Measurements and Main Results: We examined two high-risk omics-defined groups in non-overlapping test sets (n=1,133 NHW COPDGene, n=299 African American (AA) COPDGene, n=468 ECLIPSE). We defined "High activity" (low PRS/high TRS) and "severe risk" (high PRS/high TRS) subgroups. Participants in both subgroups had lower body-mass index (BMI), lower lung function, and alterations in metabolic, growth, and immune signaling processes compared to a low-risk (low PRS, low TRS) reference subgroup. "High activity" but not "severe risk" participants had greater prospective FEV 1 decline (COPDGene: -51 mL/year; ECLIPSE: - 40 mL/year) and their proteomic profiles were enriched in gene sets perturbed by treatment with 5-lipoxygenase inhibitors and angiotensin-converting enzyme (ACE) inhibitors. Conclusions: Concomitant use of polygenic and transcriptional risk scores identified clinical and molecular heterogeneity amongst high-risk individuals. Proteomic and drug repurposing analysis identified subtype-specific enrichment for therapies and suggest prior drug repurposing failures may be explained by patient selection.

Epigenetic and proteomic signatures associate with clonal hematopoiesis expansion rate.

Clonal hematopoiesis of indeterminate potential (CHIP), whereby somatic mutations in hematopoietic stem cells confer a selective advantage and drive clonal expansion, not only correlates with age but also confers increased risk of morbidity and mortality. Here, we leverage genetically predicted traits to identify factors that determine CHIP clonal expansion rate. We used the passenger-approximated clonal expansion rate method to quantify the clonal expansion rate for 4,370 individuals in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) cohort and calculated polygenic risk scores for DNA methylation aging, inflammation-related measures and circulating protein levels. Clonal expansion rate was significantly associated with both genetically predicted and measured epigenetic clocks. No associations were identified with inflammation-related lab values or diseases and CHIP expansion rate overall. A proteome-wide search identified predicted circulating levels of myeloid zinc finger 1 and anti-Müllerian hormone as associated with an increased CHIP clonal expansion rate and tissue inhibitor of metalloproteinase 1 and glycine N-methyltransferase as associated with decreased CHIP clonal expansion rate. Together, our findings identify epigenetic and proteomic patterns associated with the rate of hematopoietic clonal expansion.

Correlation-based network integration of lung RNA sequencing and DNA methylation data in chronic obstructive pulmonary disease.

Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous, chronic inflammatory process of the lungs and, like other complex diseases, is caused by both genetic and environmental factors. Detailed understanding of the molecular mechanisms of complex diseases requires the study of the interplay among different biomolecular layers, and thus the integration of different omics data types. In this study, we investigated COPD-associated molecular mechanisms through a correlation-based network integration of lung tissue RNA-seq and DNA methylation data of COPD cases (n = 446) and controls (n = 346) derived from the Lung Tissue Research Consortium. First, we performed a SWIM-network based analysis to build separate correlation networks for RNA-seq and DNA methylation data for our case-control study population. Then, we developed a method to integrate the results into a coupled network of differentially expressed and differentially methylated genes to investigate their relationships across both molecular layers. The functional enrichment analysis of the nodes of the coupled network revealed a strikingly significant enrichment in Immune System components, both innate and adaptive, as well as immune-system component communication (interleukin and cytokine-cytokine signaling). Our analysis allowed us to reveal novel putative COPD-associated genes and to analyze their relationships, both at the transcriptomics and epigenomics levels, thus contributing to an improved understanding of COPD pathogenesis.