Hoffman, E.A.

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 Chronic obstructive pulmonary disease (COPD) and pulmonary emphysema were the third-leading cause of death globally in 2019. Besides alpha-1 antitrypsin deficiency, emphysema lacks disease-modifying medications due to its heterogeneity and there remains a need to further investigate emphysema subtypes to advance its diagnosis and treatment. Recent unsupervised machine learning of the texture and anatomical location of emphysema on computed tomography (CT) images of the lung defined six quantitative CT emphysema subtypes uniquely associated with specific gene variants, environmental exposures, symptoms, physiology and clinical events. We aim to identify associations of plasma proteins with each CT emphysema subtype cross-sectionally in a multi-ethnic general population sample. MESA is a prospective cohort study that recruited 6,814 participants from six communities who self-identified as White, Black, Hispanic, or Asian race/ethnicity, ages 45-84 years old and free of clinical cardiovascular disease in 2000-02. The MESA Lung Study performed CT scans among 3,137 participants in 2010-12, which were labeled with previously described (PMID: 37268414) CT emphysema subtypes. Proteomics was assessed using SomaScan version 4.1 assay (7,596 plasma proteins). Linear regression models were adjusted for age, height, weight, sex, race, educational attainment, smoking status, pack years, urine cotinine level, body-mass index (BMI), estimated glomerular filtration rate (eGFR), CT scanner manufacturer and other CT emphysema subtypes. Results were adjusted to reflect a False Discovery Rate (FDR) p-value of less than 5% using the Benjamini-Hochberg method. Among 2,343 participants with both CT and proteomic data (mean age 69.5 years, 52.3% women, 23.7% with COPD), we identified statistically significant associations of proteins with the vanishing lung subtype (42 proteins; top hit Natural cytotoxicity triggering receptor 3 ligand 1, q = 2.9[asterisk]10-9), restrictive combined pulmonary fibrosis/emphysema (CPFE) subtype (11 proteins; top hit Integrin alpha-2/b1, q=1.0[asterisk]10-5), the combined bronchitis-apical emphysema subtype (9 proteins; top hit Desmoglein-2, q=8.8[asterisk]10-13), and the diffuse emphysema subtype (4 proteins; top hit Pulmonary surfactant-associated protein D, q=5.7[asterisk]10-3). No significant proteins were associated with the obstructive CPFE or senile subtypes after FDR correction. Most proteins were uniquely associated with one CT emphysema subtype, while a few proteins were associated with more than one subtype. This study identified specific proteins for different CT emphysema subtypes, many of which have been related less specifically to emphysema, including pulmonary surfactant production, anti-inflammatory pathways, and mitochondrial deregulation, amongst others. Validation of these proteomic associations can provide insight into further pathway assessment, clinical biomarker discovery, and targeted prevention of emphysema in the general population.

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.