Woodruff, P.

Abstract Rationale Impaired lung health may serve as a risk factor for, and a post-acute sequela of, SARS-CoV-2 infection. Yet most prior studies of lung health sequelae of COVID-19 lacked information on pre-infection lung health, a major antecedent confounder. To identify associations of COVID-19 with changes in lung health, we leveraged paired pre- and post-pandemic data on respiratory symptoms, lung function, and lung structure in a general population-based cohort. Methods We studied participants in the Multi-Ethnic Study of Atherosclerosis Lung Study with paired pre-pandemic (2016-2018) and post-pandemic (2022-2024) assessments of respiratory symptoms, spirometry, and lung CT. SARS-CoV-2 infection (2020-2023) was ascertained using a composite of questionnaires, serology, and medical record adjudication, and classified as severe (requiring hospitalization) or non-severe (not requiring hospitalization). Lung health was assessed by questionnaire (mMRC grade ≥2 dyspnea, chronic cough, chronic phlegm, chronic bronchitis), pre-bronchodilator spirometry (FEV1, FVC, FEV1:FVC), and lung density on non-contrast lung CT (% low attenuation areas, % high attenuation areas). Each post-pandemic lung health measure was regressed on infection history and the corresponding pre-pandemic lung health measure, adjusting for age at post-pandemic exam, sex, race/ethnicity, smoking status, and vaccination status at infection. Sensitivity analyses were included- (a) restriction to participants without pre-pandemic respiratory symptoms and (b) with additional adjustment for time since infection and variant wave. Results Among 2,015 participants (mean age 77.2±7.5 years; 55% female; 40% non-Hispanic White; 25% Black; 11% Asian; 23% Hispanic/Latino), 59 (3%) experienced severe and 506 (25%) non-severe SARS-CoV-2 infection. The prevalence of respiratory symptoms was similar or slightly higher at the post- vs. pre-pandemic exam (grade ≥2 dyspnea: 14% vs. 10%; chronic cough: 10% vs. 8%; chronic phlegm: 9% vs. 8%; chronic bronchitis: 4% vs. 4%; p-values <0.0001). Compared with participants without infection, those with severe infection had higher odds of chronic cough (OR:2.9, 95%CI:1.3-6.3) and chronic bronchitis (OR:3.3, 95%CI:1.2-9.0) at the post-pandemic exam (Table). Associations were stronger among individuals infected >90 days prior to the post-pandemic assessment and during pre-Omicron waves. Results were similar when restricted to participants without pre-pandemic symptoms. No significant associations were observed for non-severe infection (vs. no infection) or for any other lung health outcomes. Conclusions Controlling for pre-pandemic lung health, severe COVID-19 was associated with increased odds of chronic cough and chronic bronchitis but not with changes in lung function or structure in a general population-based sample. Non-severe COVID-19 was not associated with lung health outcomes. This abstract is funded by: OT2HL156812, R21HL165405, R01HL077612, 75N92025D00022, 75N92025D00026, 75N92020D00002, 75N92025D00024, 75N92025D00027, 75N92025D00025, 75N92025D00028

Abstract Background Prostaglandin E2 (PGE2) exerts paradoxical effects in asthma, acting as both a protective mediator and a contributor to pathology depending on context. Its role is shaped by type 2 (T2)-status, eosinophilia, and exacerbation frequency. In epithelial cell cultures from asthmatic and healthy individuals, interleukin (IL)-13 suppresses PGE2 synthesis genes (PTGS2 and PGES) while upregulating HPGD, which encodes for the PGE2 catabolic enzyme 15-prostaglandin dehydrogenase (15-PGDH) (PMID:16751012), suggesting diminished PGE2 availability during T2 inflammation. Similarly, in aspirin-exacerbated respiratory disease (AERD), impaired cyclooxygenase disrupts PGE2 biosynthesis, fueling unchecked leukotriene production and eosinophilic inflammation (PMID: 30516547), underscoring PGE2’s protective role in limiting disease progression. Conversely, in nasal polyps, tuft cells are activated by IL-13 to produce PGE2 (PMID: 35608904), highlighting PGE2’s potential pathogenicity. Objective To assess associations between PGE2-pathway gene expression in bronchial brushings and asthma severity, and to determine how nasal polyp history modifies these relationships. Methods We analyzed bronchial epithelial brushings from 109 adults with asthma (mean age 42.4±12.1, 64% female, 52% severe asthma, 18% nasal polyps) using normalized and batch-corrected RNA-seq data from the baseline visit in the Severe Asthma Research Program (SARP)3 (PMID: 36796454). Age-adjusted and nasal polyp-adjusted relationships were calculated between ratios of PGE2 synthesis and metabolism genes and clinical outcomes (ASSESS score, FEV1 %predicted). The composite PGE2 score (PMID: 35608904), derived from nasal polyp analysis, was calculated from the average scaled log-normalized expression of six PGE2-responsive genes. All data were analyzed using a linear regression mixed model with a random effect for site. Results Ratios of PGE2 synthesis genes (PTGS1/2, PTGES2) to HPGD were significantly associated with greater disease severity (change in ASSESS Score) (Fig.1A, solid lines) and lower lung function (change in FEV1 %predicted) (Fig.1B, solid lines). These relationships persisted after adjusting for nasal polyps (Fig.1, dashed lines). The composite PGE2 score was also related to disease severity (Fig.1A, black solid line) but attenuated when nasal polyps were accounted for (Fig.1A, black dashed lines). Interestingly, lower lung function remained associated with the PGE2 score even after nasal polyp adjustment (Fig.1B, dashed black lines). Conclusions Our analysis demonstrates that the balance between PGE2 synthesis and degradation in the bronchial epithelium is closely linked to asthma severity and lung function, independent of nasal polyp status. Future work will integrate transcriptomic and clinical data longitudinally to establish whether PGE2 could serve as a biomarker for asthma trajectory. This abstract is funded by: HL115118 (LCD), U10HL109152 (S.E.W.), U10HL109172 (to E.I. and B.D.L), U10HL109168 (N.N.J.), U10HL109250 (S.C.E), U10HL109164 (W.C.M), U10HL109257 (M.C), and U10HL109146 (to P.G.W. and S.A.C.)

Abstract Introduction Resilient smokers, who maintain respiratory health despite smoking, remain poorly characterized. Airway epithelial cell gene expression in resilient smokers can provide insight into mechanisms and pathways that may protect smokers from developing smoking-related lung disease. The objective of this study is to identify genes and potential pathways associated with lung-related resilience. Methods Resilient smokers were defined based on a previously published multi-dimensional definition which includes the absence of: 1) spirometric airflow limitation, 2) symptoms (cough/sputum, dyspnea), 3) radiographic (HRCT) abnormalities, 4) exacerbations, and 5) an accelerated FEV1 decline. “Non-resilient” smokers had preserved spirometry but showed abnormalities in at least one domain of resilience. We analyzed airway epithelial brush samples from 21 resilient and 34 non-resilient smokers from SPIROMICS. Differential gene expression was performed using DESeq2 package in R, which estimates differential expression using generalized linear models. We adjusted for sequencing batch, age (continuous), race, gender, and current smoking status. While controlling for these covariates we evaluated differential gene expression between resilient and non-resilient smokers, the interaction between resilience and smoking status, and in each sub-category of resilient (absence of symptoms, radiographic abnormalities, exacerbations, and accelerated decline in FEV1). Results We identified 98 genes that were differentially expressed (FDR ≤0.1) when comparing resilient to non-resilient smokers, 20 of those genes were up regulated in resilient smokers (Figure 1). Notable genes included cadherin-12 (CDH12), aspartate beta-hydroxylase (ASPH), and protein kinase AMP-activated alpha 2 (PRKAA2). CDH12 is involved in cell adhesion and epithelial integrity. ASPH influences cell adhesion and signaling. PRKAA2 plays role in cellular homeostasis and stress response, which may be altered in non-resilient smokers, affecting cellular metabolism and inflammation. BPI folding containing family A member (BPIFA1) was significantly associated with smoking status in the interaction analysis, suggesting its role in modulating the impact of smoking on resilience. BPIFA1 has anti-microbial properties, regulates immune responses, and contributes mucosal surface protection. Sub-category analysis identified 17 genes associated with resilience to symptoms and 2 genes related to physiologic resilience (FEV1 decline), though no significant genes were associated with radiographic or exacerbation resilience. Conclusion Differential gene expression of airway epithelial cells identified distinct expression patterns between resilient and non-resilient smokers. Specifically, genes associated with epithelial cell adhesion, signaling, and cellular homeostasis were up regulated in resilient smokers. These findings suggest that resilient smokers may have transcriptomic profiles and potential mechanisms that mitigate the effects of cigarette smoke.

Abstract Rationale: Adverse social determinants of health (SDOH) are common in COPD and associated with increased mortality. However, cause-specific mortality is understudied. We evaluated associations of neighborhood-level SDOH with all-cause and cause-specific mortality among individuals with or at-risk for COPD. Methods: SPIROMICS is an ongoing, multi-center, longitudinal observational study of individuals across the US with current or former personal smoking histories (≥20 pack-years), with or without spirometrically-defined COPD. We established geocoded neighborhood-level SDOH at baseline using 2010 census tract data, including specifically, area deprivation index (ADI) (range 0-100, 100 = most disadvantaged), poverty level (percentage of households below the poverty line), poor food access (>1/3 of residents with no access to fresh food stores within 1 mile in urban areas and 10 miles in rural areas), and food desert (low income plus poor food access). We ascertained all-cause and cause-specific mortality through 12/31/2021 using the National Death Index. Using Cox proportional hazards models, we evaluated the risk of all-cause mortality for each SDOH. We utilized competing-risk regression models to evaluate the risk of cardiovascular, respiratory, COPD (a subset of respiratory), and neoplastic causes of death individually with each SDOH. Models were adjusted for demographics, smoking status, pack-years, BMI categories, coronary heart disease, FEV1% predicted and study site. Effect modification by lung function was assessed using multiplicative interactions between SDOH and FEV1% predicted. Results: Among 2977 participants, mean ADI was 40.1±27.8. Within a participant's neighborhood, on average 10.4±10.4% of households were below the poverty line, 933 (31.3%) had poor food access, and 220 (7.4%) resided in a food desert. During a median follow-up of 7.8 years (IQR 5.6-9.2), 744 (25.0%) participants died, most commonly from respiratory causes including COPD. Neither ADI nor neighborhood poverty level were associated with all-cause mortality or any specific cause of death (Table). Despite lack of associations between food access and mortality (Table), individuals residing in a food desert had elevated risks of all-cause (HR: 1.36 [95%CI: 1.03-1.79]) and cardiovascular (HR: 2.62 [95%CI: 1.5-4.35]) deaths. There was no significant effect modification by lung function. Conclusions: In a large cohort of individuals with personal smoking histories, with or without COPD, living in a food desert was associated with increased all-cause and cardiovascular mortality. However, neighborhood poverty level and food access, the two components of food desert, were not independently associated with mortality, suggesting the association of multimodal SDOH variables with mortality in this population.

Abstract Rationale: MUC5B and MUC5AC are neighboring genes on chromosome 11p15 that encode the two predominant mucins secreted in the respiratory airways. Increased airway mucin concentrations and an imbalance between these two mucins drive COPD symptoms and the development of airflow obstruction or COPD, but the epigenomic regulation of this loci has not been characterized in the airways. Methods: We isolated DNA from bronchial airway brushings of 72 participants with >20 pack-years smoking history from the Subpopulations and Intermediate Outcomes Measures in COPD Study (SPIROMICS). 36 participants had GOLD-based moderate-to-severe COPD (FEV1/FVC<0.70, FEV1<80%) and 36 were without or with mild COPD. We used the Illumina Infinium Methylation EPIC BeadChip Array to assess proportion of DNA methylation (β) spanning 689,937 CpG sites. We evaluated proportional DNA methylation (β) at 96 CpG loci within a 103kB region using matrixQTL for cis-expression quantitative trait methylation (eQTM: 10kB flanks relative to MUC5AC/MUC5B) integrating bulk RNA-seq data and mQTL models integrating gene sequencing data to identify DNA variation associated with proportion eQTM methylation. Models included age, sex, BMI, clinical site, current smoking vs past smoking, total pack-years, three ancestral components of ancestry, chipset, and position. Results: We identified a top eQTM, cg00524486, marginally associated with MUC5B expression (coefficient estimate=8.75, punadjusted=0.0014, pFDR=0.065, Figure 1B). This eQTM was associated with CT scan parametric response mapping-based functional small airways disease (PRM-fSAD, beta coefficient[β]=3.64, p=0.011). We tested for DNA variation associated with methylation of this top eQTM which identified two methylation quantitative trait loci (mQTL: rs885454 [β=0.044, minor allele frequency[MAF]=0.09, pFDR=0.01], rs868902 [β=0.020, MAF=0.43, pFDR=0.08, Figure 1A) associated with cg00524486 methylation, of which the more frequent mQTL, rs868902, was marginally associated with PRM-fSAD (p=0.07) in the larger SPIROMICS cohort with MUC5B DNA sequencing data. Conclusions: This preliminary multi-omic study of the lower airway epithelium demonstrates that the expression of MUC5B is epigenetically regulated by neighboring CpG probe methylation (eQTM) represented by DNA variation (mQTL). These studies require further confirmation in a larger dataset of airway samples and support a role for epigenetic variation as a biologic contributor and biomarker of early COPD pathogenesis.

Abstract RATIONALE: Airway-to-lung ratio (AirLR), calculated as the mean of airway lumen diameters at standard anatomic locations divided by the cube-root of total lung volume, is associated with COPD risk regardless of smoking status, and we have previously shown an association between total-pulmonary-vascular-volume-to-lung-size relationship with AirLR. [PMCID: PMC11284327] Using dual energy computed tomography (DECT), we recently developed a deep learning-based algorithm for pulmonary arterial segmentation to compute pulmonary-arterial-to-lung ratio (ArtLR) which correlated significantly with AirLR and markers COPD. Here we automate image processing in a larger cohort to estimate ArtLR, introduce an alternative ArtLR standardization and correlate it to COPD-related measures of lung structure and function. METHODS: Using a SPIROMICS sub-cohort (110 participants), imaged via contrast enhanced DECT at functional residual capacity (FRC), an automatic deep learning pipeline segmented the arteries from the pulmonary vascular tree. Another pipeline automatically extracted the centerlines and calculated average arterial segment diameters. A paired non-contrast total lung capacity (TLC) scan was registered to the DECT FRC scan to transfer airway segment labels from the TLC to FRC domain. AirLR was calculated as the mean of airway lumen diameters at standard anatomic locations (trachea-to-subsegments) divided by cube root of lung volume [TLC or FRC]. A simple Long Short-Term Memory (LSTM) network was used to find corresponding anatomic arterial segments. Associations between ArtLR and %Emphysema, AirLR, pre- and post-bronchodilator FEV1/FVC, and a texture-based (AMFM) measure of %broncho-vascular bundles was assessed using linear regression to adjust for age, sex and BMI. RESULTS: In adjusted analyses, a 1-SD decrement in ArtLR-TLC was associated with 4.198 units increase in %Emphysema-910 (95%CI: 1.360-7.037; p = 0.0041), and 0.8198 units decrease in %Bronchovascular (95%CI: 0.5037-1.136; p < 0.0001). A 1-SD increment in ArtLR-TLC was associated with 0.2515 SD increase in AirLR-Outer (95%CI: 0.04947SD-0.4536SD; p = 0.0152), and 0.02083 units increase in PreBronch-FEV1FVC (95%CI: 0.001814-0.03984; p = 0.0321). Sex and BMI show significant associations with ArtLR-TLC, where female is associated with 1.068 SD decrease in ArtLR, and a unit increase in BMI is associated with 0.05788 SD increase in ArtLR (both p-values < 0.0001), and age was not association with ArtLR. CONCLUSIONS: An automated pipeline for pulmonary arterial tree segmentation and standardization from contrast enhanced DECT FRC scans demonstrates a significant relationship between ArtLR and AirLR as well as between ArtLR and %emphysema, and FEV1/FVC. A standardized method of arterial tree size assessment provides for expanded exploration of vascular vs airway disease etiologies.

Abstract Rationale Chronic obstructive pulmonary disease (COPD) manifests later in life and is a leading cause of death worldwide. While smoking-related lung pathology is a long-recognized COPD etiotype, emerging evidence suggests that early-life growth conditions also play an important role. A recently-developed index of early-life growth conditions – the difference between attained height and genotype-predicted height (height-GaP) – has been validated against prospectevely ascertained adverse early-life growth conditions. This study used height-GaP to evaluate the association of early-life growth conditions with COPD phenotype and prognosis later in life. Methods Among current and former smokers with spirometry-defined COPD in the SubPopulations and Intermediate Outcomes Measures in COPD Study (SPIROMICS), we computed height-GaP as the difference between attained height and genotype-predicted height. Regression models were fit for respiratory mortality (defined by primary diagnostic code), dyspnea prevalence (Medical Research Council dyspnea rating >1), chronic bronchitis prevalence, airflow obstruction severity as quantified by FEV1Q, and functional capacity (six-minute walk distance), adjusting for age, age2, sex, race-ethnicity, genotype-predicted height, cigarette smoking status and pack-years. Sensitivity analyses accounted for competing risks of death (Fine-Gray subdistribution hazard model) and accounted for later-life height loss (restricting sample to participants under 50 years). Results Among 1,258 participants with COPD (mean±SD age: 65.4±8.0 years, 42.4% female, mean±SD pack-years: 53.6±28.2, mean±SD FEV1%: 63.3±23.9%), there were 202 respiratory deaths over a median 7.5 years of follow-up (Figure). Larger height-GaP deficit was associated with higher respiratory mortality (adjusted hazard ratio [aHR]: 1.30 [95%CI: 1.12 to 1.50] per 1-SD increment in height-GaP deficit). This association remained significant after accounting for competing events (p=0.001) and when restricted to participants under 50 years (p=0.032). Larger height-GaP deficit was associated with higher dyspnea prevalence (adjusted prevalence ratio: 1.13 [95%CI: 1.02 to 1.25] per 1-SD increment in height-GaP deficit), lower FEV1Q (adjusted mean difference: -0.37 [95%CI: -0.45 to -0.29] per 1-SD height-GaP deficit), and shorter 6-minute walk (adjusted mean difference: -16.6 m [95%CI: -23.1 m to -10.0 m] per 1-SD increment in height-GaP deficit), but not chronic bronchitis or CAT score ≥10 (p>0.05 for each). Conclusions Among current and former smokers with COPD, a quantitative index of early-life conditions was associated with higher respiratory mortality, in addition to dyspnea, airflow obstruction severity and reduced functional capacity. These results suggest that early-life growth conditions may influence COPD phenotype and prognosis later in life.

Abstract Rationale: We have previously shown reduced total IgG, IgG subclasses, and levels/function of pneumococcal-specific antibodies are associated with increased risk for exacerbations of COPD (ECOPD). The binding of IgG to its receptor, the Fc receptor for IgG (FcγR) on immune cells, has a critical role in determining antibody levels and function. In addition to our research demonstrating that IgG heavy chain gene (IGHG) variants are associated with ECOPD, single nucleotide variants (SNVs) in genes encoding FcγR (FCGR1-3, which encode receptor subtypes FcγRI, FcγRIIa/b/c, and FcγRIIIa/b) may also result in antibody deficiency and increased exacerbation risk. Due to technical challenges in accurately identifying SNVs in FCGR, this region has not been well-characterized. The limited data that exist are from people of European descent, and prior studies have not included African American participants. We therefore sought to investigate the hypothesis that distinct SNVs in genes encoding FcγR are associated with disease severity and history of exacerbations in African American people with COPD. Methods: We developed a novel pipeline to identify SNVs in the coding (CDS) regions of chromosome 1 using short-read whole genome sequence data. The pipeline was benchmarked using paired long-read samples from Genome in a Bottle. SNVs were called within CDS regions and analyzed in a meta-analysis of self-reported African American participants in SPIROMICS and COPDGene (n=3063). Genetic variants were tested for association with COPD severity (GOLD spirometry stage 1-2 vs 3-4) as well as COPD exacerbations, adjusting for age, sex and principal components controlling for population structure. Results: Eight SNVs were significantly associated with frequent ECOPD (≥2 in one year) in the meta-analysis of African American COPDGene and SPIROMICS participants (Table). Seven of these 8 SNVs were found in FCGR3; 4 in the activating FCGR3A subtype, and 3 in FCGR3B. Seven of 11 SNVs associated with COPD severity were in FCGR3 (4 in FCGR3A; 3 in FCGR3B). One SNV (rs371849) was associated with both frequent exacerbations (P=0.002) and COPD severity (P=0.044). Conclusions: We used a cutting-edge variant calling pipeline to identify multiple SNVs in FCGR, primarily involving FcγRIII receptor subtypes, associated with COPD severity and exacerbations in African American participants in SPIROMICS and COPDGene. FcγRIII variants are known to cause impaired antibody levels and function in people of European descent. The structural and functional importance of newly recognized variants in African American cohorts require further study, as they may represent immunogenetic risk factors for antibody deficiency and exacerbations.

Abstract Rationale: The club cell secretory protein (CC16), encoded by the SCGB1A1 gene, has an anti-inflammatory role in airways diseases, including asthma (Li, AJRCCM 2023; Voraphani, AJRCCM 2023). We hypothesize that additional pathway genes regulated or co-expressed with CC16 have cumulative effects on asthma severity outcomes by modulating airway inflammation and maintaining lung homeostasis. Methods: As published previously, four genes were downregulated in CC16 knockout experiments and correlated with CC16 levels: BPIFA1, SFTPD, LTF, and LYZ (Iannuzo, Front. Immunol 2023). We developed a four-gene biomarker score in 94 patients with asthma from the NHLBI-sponsored Severe Asthma Research Program (SARP3) who underwent research bronchoscopy for lower airway epithelial brushings, RNA isolation, and bulk RNA sequencing. We log-transformed the raw values of each transcript; obtained standardized residuals from regression models that included sex, age, and batch effects; and summed the standardized residuals of all four proteins to estimate a standardized sum score (Zhai, JACI Allergy 2024). Logistic regression models tested the four-gene score, three-gene score without LTF, and individual transcripts for associations with exacerbations during 12-month follow-up and zero-inflated negative binomial regression for number of exacerbations. Results: 30.85% percent of 94 patients experienced at least one exacerbation at the end of follow-up. The CC16-associated four-gene biomarker score showed protective effects on asthma exacerbation risk with a 54% percent reduction in exacerbation risk for every one-fold higher score (OR=0.46, 95% CI: 0.27-0.78, p =0.0040, Figure 1). Transcript expression of BPIFA1 (OR=0.87, 95% CI:0.66-1.16, p=0.337), SFTPD (OR=0.33, 95% CI:0.04-2.52, p=0.283), LYZ (OR=0.62, 95%CI:0.28-1.39, p=0.248), and LTF (OR=0.36, 95% CI:0.18-0.74, p=0.0053) all indicated protective directionality with respect to exacerbation risk. However, only LTF demonstrated a statistically significant association. When we excluded LTF, the remaining three-gene score showed a trend toward association with risk (OR=0.64, 95% CI:0.40-1.03, p=0.068) and was significantly associated with number of exacerbations (RR=0.49, 95% CI:0.26-0.95, p=0.034). Compared to LTF alone (OR=0.48, PPV=0.50, NPV=0.71, Sensitivity=0.14, AUC=0.65), the combined four-gene score (OR=0.46, PPV=0.60, NPV= 0.73, Sensitivity=0.21, AUC=0.68) showed improved predictive performance. Conclusions: We identified a CC16-associated transcriptomic predictive score for asthma exacerbations, with LTF showing the strongest effect. Although the other three genes showed individually weak and non-significant associations with exacerbations, the three gene score was significant for number of exacerbations.We demonstrate the potential of this transcriptomic score as a predictive biomarker for asthma severity-related outcomes. Further research investigating these genes and their interaction with other CC16-associated immune pathways could provide insight into therapeutic targets.