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Abstract Background Sarcopenia is common in chronic obstructive pulmonary disease (COPD) and contributes to adverse outcomes. Alpha-1 antitrypsin deficiency (AATD) is the most common genetic cause of COPD, but its impact on skeletal muscle remains to be determined. Methods We performed a retrospective analysis of 487,207 participants in the UK Biobank with available SERPINA1 genotyping. Associations between AAT genotypes and measures of skeletal muscle mass were determined using multivariable linear and logistic regression models. Models adjusted for age, sex, smoking status, genetic principal components, lung function (FEV₁% predicted), and liver fibrosis risk (FIB-4). We determined that the Z-allele was associated with sarcopenia and mortality using regression models and mediation analysis. Results Compared with PI*MM individuals, carriers of the Z allele (PI*MZ, PI*SZ, PI*ZZ) demonstrated significantly lower fat free mass index (FFMI) and appendicular skeletal muscle index (ASMI), as well as higher odds of sarcopenia by binary definition. Associations persisted after adjustment for lung and liver function. A dose-dependent relationship was observed, with the greatest reductions in muscle mass and highest sarcopenia associated with PI*ZZ individuals (adjusted OR for FFMI-defined sarcopenia 2.02, 95% CI 1.16-3.32). Each additional Z allele was associated with increased mortality risk (adjusted OR 1.09, 95% CI 1.02-1.16), with sarcopenia mediating a modest proportion (∼2.6%) of this association. Conclusions. The SERPINA1 Z allele is associated with reduced muscle mass and increased risk for sarcopenia independent of lung and liver disease. Our findings expand the phenotypic spectrum of AATD-related diseases to include skeletal muscle as a modifiable target for intervention.

Abstract Rationale Alpha-1 antitrypsin deficiency (AATD) continues to be underdiagnosed. The estimated prevalence of the most common severe deficient genotype, PI*ZZ, is ∼1:3500 or 100,000 Americans but only ∼10,000 such individuals have been recognized. Diagnostic delays persist and these delays are associated with worse disease. High-resolution CT (HRCT) imaging may contain latent phenotypic AATD signatures that are not visibly apparent to clinicians. We hypothesized a deep learning model could identify imaging patterns predictive of AATD from inspiratory HRCT scans. Methods Confirmed genotypes and HRCT scans were pooled from COPDGene, SPIROMICS, and GRADS, yielding 350 MM, 102 MZ, and 69 ZZ participants. Only scans reconstructed with smooth kernels (GE STANDARD, Philips B, Siemens B31f/B35f) and slice thickness < =1.25mm were used. The cohort was selected to have similar distributions of quantitative emphysema, sex, and age by matching five MZ and two MM subjects to each ZZ subject (<10-year age difference, same sex, and <3% difference in %LAA). Tobacco smoke-exposure was more prevalent among the MM/MZ groups given these were predominantly from the tobacco smoke-enriched COPDGene and SPIROMICS cohorts. A DenseNet121 convolutional neural network (CNN) was trained using the MONAI platform to predict genotype by outputting probabilities for MM, MZ, and ZZ. Input to the CNN was a three-channel LAA-910, LAA-950, and LAA-970 map downsampled to 2.0mm3 resolution to remove bias due to differences in scanner and image reconstruction parameters. Five-fold cross-validation was performed. Area under the curve (AUC) was calculated for classification of ZZ vs other genotypes (MM/MZ) and MZ vs MM, with statistical significance assessed at p < 0.05. Results The three groups were similar across age (mean±SD years: MM 57.9±8.8, MZ: 57.5±8.9, ZZ: 55.0±10.7), sex (% female: MM: 48.2%, MZ: 46.7%, ZZ: 47.6), and emphysema (LAA-950%: MM: 13.0±12.2, MZ: 12.4±11.8, ZZ: 13.1±11.9). There was a higher prevalence of ever smokers among MM (100%) and MZ (91.7%), compared to ZZ (47.6%). The model achieved an AUC of 0.806 (p < 0.001) for classification of ZZ vs other genotypes, demonstrating robust discriminatory ability for homozygous AATD. Classification of MZ vs other genotypes did not achieve an AUC significantly greater than 0.5. Conclusions This proof-of-concept study demonstrates that deep learning applied to routine inspiratory HRCT can accurately identify homozygous AATD. These findings support the potential role of imaging-based machine learning as a non-invasive screening tool for undiagnosed ZZ individuals. Future work will focus on cohort enrichment, integration with clinical parameters, and explainability of model-derived imaging features. This abstract is funded by: NIH NHLBI K23HL173570

Abstract Rationale Chronic lower respiratory diseases (CLRD), including chronic obstructive pulmonary disease (COPD), were the third-leading causes of death globally in 2019. Quantitative computed tomography (CT) measures of airway wall and lumen areas are associated with greater respiratory symptoms, reduced FEV1, accelerated lung function decline, and higher risk of incident COPD. Even in individuals without COPD, greater airway wall thickness—corresponding to smaller absolute wall and lumen areas—predicts incident COPD and CLRD-related hospitalizations and mortality. Aims To identify protein signatures and biological pathways underlying airway lumen and wall areas using cross-sectional plasma protein associations with CT measures. Methods SPIROMICS is a multicenter longitudinal case-control study that recruited 2,983 adults with COPD and a 20+ packyear smoking history and controls aged 40-80 years between 2010-2015. Standardized chest CT scans were labeled with airway measures. A total of 1,255 plasma proteins measured by SomaScan were included. Linear regression models adjusted for demographic, clinical, and imaging covariates. Significance was defined by a False Discovery Rate (FDR) p-value (q-value) <0.05 using the Benjamini-Hochberg method. Replication was performed in two external cohorts with inverse variance-weighted meta-analysis. Proteins meeting nominal replication underwent elastic net regression and pathway enrichment (Gene Ontology [GO] and Reactome). Results Among 2,065 participants with CT and proteomic data (mean age 63.2 years, 46.3% women, 61.6% with COPD), proteins meeting replication were significantly associated with lumen area (2 proteins; top hit a disintegrin and metalloproteinase with thrombospondin motifs 5, q = 0.016), wall area (3 proteins; top hit leptin, q = 0.011), and percent wall area (16 proteins; top hit roundabout homolog 2, q = 0.002). Elastic net selected 2 proteins for lumen area, 3 for wall area, and 12 for percent wall area. Pathway enrichment revealed FDR-significant pathways only for percent wall area via GO (50 pathways; top hit axogenesis) and Reactome (1 pathway; diseases of glycosylation). Conclusions This study identified distinct proteins, signatures, and biological pathways associated with CT airway measures of lumen area, wall area, and percent wall area. Proteins linked to airway lumen and wall area are involved in metabolic and vasoactive processes, while those for percent wall area are involved in vascular remodeling, cell adhesion, and extracellular matrix organization—highlighting structural pathophysiologic features of COPD. These findings may inform biomarker discovery and prediction of disease onset and progression. This abstract is funded by: Funding: Daniel E. Guzman, MD, MSE was funded by T32-HL144442. SPIROMICS was supported by contracts from the NIH/NHLBI (HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN268200900019C, HHSN268200900020C, 75N92024D00012), grants from the NIH/NHLBI (U01HL137880, U24HL141762, R01HL182622, R01HL144718, and R01HL093081), and supplemented by contributions made through the Foundation for the NIH and the COPD Foundation from Amgen; AstraZeneca/MedImmune; Bayer; Bellerophon Therapeutics; Boehringer-Ingelheim Pharmaceuticals, Inc.; Bristol Myers Squibb; Chiesi Farmaceutici S.p.A.; Forest Research Institute, Inc.; Genentech; GlaxoSmithKline; Grifols Therapeutics, Inc.; Ikaria, Inc.; MGC Diagnostics; Novartis Pharmaceuticals Corporation; Nycomed GmbH; Polarean; ProterixBio; Regeneron Pharmaceuticals, Inc.; Sanofi; Sunovion; Takeda Pharmaceutical Company; Theravance Biopharma; Verona; and Mylan/Viatris.

Abstract Background Muscle loss in COPD results from both disuse atrophy and systemic inflammation. We sought to identify inflammatory biomarkers associated with loss of pectoralis muscle area in COPD using serial CT scans and peripheral blood proteomics. Design We analyzed five-year longitudinal data from COPDGene, an ongoing observational cohort of current and former tobacco smokers with or without airflow obstruction. We quantified pectoralis major muscle (PMM) area on chest CT scans using a 3D convolutional neural network (CNN) trained on CT volumes and annotations provided by the TotalSegmentator project. We compared participants with CT PMM data and plasma proteins by SOMAScan (1K platform) from Phase 2 and 3 (paired n = 1,191). The correlation coefficient (r) between longitudinal changes in protein and in PMM area was plotted against the false discovery rate (FDR)-adjusted p-values. Proteins significantly associated with muscle loss (blue) or gain (red) were visualized using volcano plots. We then analyzed a subset (paired n = 500) of individuals with BMI>25 in Phase 2 whose BMI declined in Phase 3. Proteomic models were adjusted for age and clinical center. Pathway analysis utilized G:Profiler. Results Of the participants with paired proteomic and PMM data, mean PMM area was 21.7 ± 17.3 cm² at Phase 2 and 21.3 ± 17.9 cm² at Phase 3, with an annual change in PMM area of -0.31 + 0.99 cm². Multiple proteins were associated with muscle loss from Phase 2 to 3 (including leptin, FABP, and growth hormone receptor) and muscle gain (including F172A, GMEB2, and RNF41) (Fig 1a). Significant pathways were related to cancer, growth factor receptor dysregulation, and PI3K/AKT signaling. When restricting to those with BMI>25 who experienced BMI decline at Phase 3, muscle loss was associated with increased leptin and PACAP, versus association of gain with increased GDF118, EF1β, and FJF6 (Fig 1b). In the entire group, leptin declined between Phase 2 to Phase 3 in n = 571 participants and increased or was unchanged in n = 620. Compared with leptin decline, unchanged or increased leptin was associated with significantly greater interval PMM loss (−2.25 ± 9.75 cm² vs + 0.98 ± 9.43 cm²; p < 0.001) (Fig 1c). Conclusion Loss of PMM over five years was associated with several plasma proteins, including FABP and growth hormone receptor. The top biomarker, leptin, is a pleiotropic adipokine that regulates energy balance and inflammation. Integrating imaging and proteomics may identify future therapeutic targets to mitigate skeletal muscle loss in COPD. This abstract is funded by: This work was supported by NHLBI grants U01 HL089897 and U01 HL089856 and by NIH contract 75N92023D00011

ABSTRACT Background Chronic obstructive pulmonary disease (COPD) is associated with musculoskeletal comorbidities, including cachexia. Weight loss (WL) is the major criterion for cachexia and increases risk for mortality in COPD. Risk factors for WL in COPD are incompletely understood. We performed this whole genome sequencing (WGS) analysis to identify genetic risk variants for WL in COPD. Methods We studied 16 972 participants from the Trans‐Omics for Precision Medicine (TOPMed) Initiative and All of Us Research Program. COPD was diagnosed using spirometry in TOPMed, while diagnosis codes were used in All of Us. WL was defined as WL ≥ 5% or a final body mass index (BMI) < 20 kg/m 2 . WGS data came from white blood cells in all cohorts. Single‐variant testing was conducted on both race‐ and study‐stratified cohorts and in a cosmopolitan, ancestry‐independent manner using GENESIS in TOPMed and SAIGE in All of Us. SAIGE‐GENE+ gene‐based analyses were performed on race‐stratified and cosmopolitan cohorts. Single variant meta‐analyses were conducted using METAL within (B/AA and NHW analyses of Black/African–American and non‐Hispanic white participants, respectively) and across racial groups (COSMO). Rare variant gene‐based results were combined using Fisher's method. Transcriptomic effects were predicted using MetaXcan. We used the GWAS Catalogue to analyse for colocalization with other related traits. Results Two single variants were associated with WL in COPD among All of Us participants: one intronic variant in HCN1 in Black/African–American participants (chr5:45271359:TACACAC:T, odds ratio with 95% confidence interval (OR (CI 95 )) = 2.43(1.78–3.31), p = 1.95 × 10 −8 ) and one intergenic variant between PPP4R2 and PDZRN3 in the cosmopolitan and NHW cohorts (chr3:73345901:A:G, OR (CI 95 ) = 0.21(0.12–0.35), p = 8.84 × 10 −9 in cosmopolitan and OR (CI 95 ) = 0.18(0.10–0.33), p = 9.44 × 10 −9 in NHW). Single‐variant meta‐analysis identified two loci associated with WL in COPD: five variants within DRAIC in the B/AA meta‐analysis (lead variant chr15:69571341:A:G, OR (CI 95 ) = 1.37(1.23–1.51), p = 1.29 × 10 −9 ) and two intronic variants within RFX3 in the cosmopolitan meta‐analysis (lead variant chr9:3390983:T:C, OR (CI 95 ) = 1.50(1.31–1.73), p = 1.06 × 10 −8 ). Rare variants within RNU6‐565P (NHW analysis in All of Us; p = 2.83 × 10 −7 ) and LOC339298 (B/AA analysis in All of Us, p = 1.85 × 10 −6 ) were associated with WL in COPD. The RNU‐565P signal remained significant after combination with TOPMed results (p combined = 1.23 × 10 −6 ). MetaXcan predicted differential expression of LNC00959 in visceral adipose tissue ( p = 1.16 × 10 −6 in COSMO analysis). Colocalization analyses identified genomic associations between BMI and variants in or near DRAIC , RFX3 , PDZRN3 , and LINC00959 . Conclusions In the first WGS analysis of WL in COPD, we have identified seven novel loci. Further characterization of these loci will validate our findings and improve our understanding of the molecular pathophysiology of this condition.

Abstract Dysphagia is defined as a subjective sensation of difficulty swallowing and can result from oropharyngeal or esophageal etiologies based upon patient symptoms. Dysphagia affects approximately 16% of adults in the general population, with prevalence increasing with age. Esophagogastroduodenuoscopy (EGD) is initially performed to assess for structural abnormalities resulting in esophageal dysphagia. However, if EGD reveals no pathologic abnormalities, high-resolution manometry (HRM) and barium esophagography are performed in order to assess for underlying causes of dysmotility. Esophageal motility disorders (EMDs) are an underrecognized cause of dysphagia and can be characterized by impaired esophageal peristalsis or lower esophageal sphincter dysfunction. High-resolution manometry (HRM) measures key metrics such as integrated relaxation pressure (IRP), which is the deglutitive relaxation across the LES, and metrics of esophageal body peristalsis based on distal contractile integral (DCI) and distal latency (DL). The Chicago Classification version 4 (CCv4.0), published in 2021, provides a standardized classification scheme for differentiating EMDs using metrics from HRM. Additionally, barium esophagography has remained an important adjunctive diagnostic modality, as this may identify strictures, neoplasms, or hiatal hernias, but can also identify major motility disorders such as achalasia and distal esophageal spasm. The combined use of HRM with timed barium esophagram can enhance the diagnostic accuracy of EMDs, particularly when HRM demonstrates inconclusive findings. Therefore, radiologists should be familiar with how imaging findings from barium esophagram integrate with findings noted on HRM. The aim of this review is to highlight the findings of EMDs noted on HRM in conjunction with barium esophagography, thereby illustrating characteristic patterns of primary and secondary EMDs.

Abstract Rationale Mucus plugs occur in chronic obstructive pulmonary disease (COPD), but little is known about their size and airway location or whether these mucus plug features change as emphysema worsens. Methods Computed tomographic lung scans from 31 participants with COPD from the SubPopulations and InteRmediate Outcomes In COPD Study (SPIROMICS) cohort were analyzed to quantify mucus plug size and airway location and extent of emphysema. Radiologist annotations of mucus plugs were incorporated in an image processing pipeline to generate size and location information. Emphysema was quantified as the percentage of voxels less than -950 Hounsfield units. Measurements and Main Results The length distribution of 563 annotated mucus plugs varied from 2 to 50 mm. The distribution was multimodal, and an 11-mm length defined short (“stubby,” ≤11 mm) and long (“stringy,” &gt;11 mm) plug phenotypes, with stubby plugs being most common (64%). Mucus plugs localized predominantly to airway generations 6 to 9, and their prevalence was highest in lower lobes. On a lobar basis, the mucus plug number decreased as emphysema percentage increased, whereas average mucus plug volume tended to increase. Conclusion COPD is characterized by mucus plugs of varying size and shape, and emphysematous lung regions may be differentially susceptible to formation of these plugs. The location of mucus plugs in segmental and subsegmental airways in COPD makes them amenable to treatment with inhaled medications or bronchoscopy.

Abstract Background The evaluation of gastrointestinal (GI) bleeding is frequently negative despite a prolonged workup involving several different radiologic and endoscopic tests. Ferumoxytol, a superparamagnetic iron oxide agent used for treatment of iron deficiency anemia, can be used off-label as a blood pool contrast agent at MRI. Purpose To perform a proof-of-concept study to determine if ferumoxytol-enhanced MRI (FeMRI) can be performed to assist in detecting the presence and location of GI bleeding in patients who have undergone a negative standard evaluation. Methods A retrospective convenience cohort of patients examined with FeMRI at a single center over a 2-year period was evaluated. Inclusion criteria included clinical suspicion for slow or intermittent, active GI bleeding not localized following conventional testing. Exclusion criteria included any allergy to ferumoxytol or iron-containing agents, additional MRI scans scheduled within the following 72 hours, current pregnancy or breastfeeding, history of medication-related hypotensive episodes not related to an acute illness, syncopal events, arrhythmia, or low resting blood pressure. The patient’s clinical characteristics, examination results, and outcome during their hospital stay were examined. Results Five males and 1 female with average age of 66 years (range, 37-79 years) were imaged with FeMRI. All had undergone full diagnostic evaluation of the GI tract including upper and lower endoscopy and small bowel evaluation with imaging and/or endoscopic testing; in all patients, repeated rounds of testing were performed. Diagnostic images were obtained in all patients who underwent FeMRI. In 4/6 (67%) patients, FeMRI demonstrated active bleeding in the small bowel (n = 3) and colon (n = 1). Conclusion FeMRI was able to demonstrate the presence and location of active GI bleeding in hospitalized patients with previous extensive negative evaluation. FeMRI should be further evaluated to determine its performance characteristics as an examination in evaluating patients with GI bleeding.

BACKGROUND: Although chronic obstructive pulmonary disease (COPD) and heart failure with preserved ejection fraction often coexist with overlapping clinical features, they are usually studied separately. The SPIROMICS HF (Subpopulations and Intermediate Outcome Measures in COPD and Heart Failure Study) is testing hypotheses that new computed tomography emphysema subtypes are associated with specific cardiovascular phenotypes (eg, cor pulmonale , cor pulmonale parvus ), common airway branch variants are associated with right heart dysfunction, and symptomatic tobacco-exposed persons with preserved spirometry have signs of increased left ventricular afterload. METHODS: SPIROMICS is a multicenter observational study of COPD with extensive pulmonary phenotyping of participants with ≥20 pack-years smoking and nonsmoking controls. COPD and COPD severity were defined by standard spirometric criteria and symptomatic tobacco-exposed persons with preserved spirometry by ≥20 pack-years, normal spirometry, and COPD Assessment Test score >10. SPIROMICS HF selected all participants in SPIROMICS visit 5 at major sites. Its comprehensive speckle-tracking echocardiography, which included physiological perturbations of leg raise and low-intensity exercise, was harmonized prospectively with the Multi-Ethnic Study of Atherosclerosis Early Heart Failure and HeartSHARE (Combining Omics, Deep Phenotyping, and Electronic Health Records for Heart Failure Subtypes and Treatment Targets) studies. The cardiopulmonary magnetic resonance imaging protocol with gadolinium administration included myocardial fibrosis sequences, pulmonary angiography, time-resolved 3-dimensional cine magnetic resonance imaging (4-dimensional flow) of venous return, and metronome-paced tachypnea to induce dynamic hyperinflation. Coronary artery calcium was assessed on computed tomography scans. The Kansas City Cardiomyopathy Questionnaire was administered. RESULTS: Of the final sample of 753 participants, 57% had COPD (15% mild, 27% moderate, and 15% severe), 18% had symptomatic tobacco-exposed persons with preserved spirometry, 16% were smoking controls, and 8% were nonsmoking controls. Reproducibility of the main measures from speckle-tracking echocardiography (intraclass correlation coefficient, 0.83–0.99), exercise echocardiography (intraclass correlation coefficient, 0.71–0.99) and magnetic resonance imaging (intraclass correlation coefficient, 0.57–0.99) were good-to-excellent, including in severe COPD. CONCLUSIONS: SPIROMICS HF aims to characterize and understand cardiopulmonary interactions in COPD and COPD-related phenotypes to inform targeted treatments for combined cardiopulmonary failure.

Abstract Rationale Inflammation is central to chronic obstructive pulmonary disease (COPD) pathogenesis but incompletely represented in COPD prognostic models. The neutrophil-to-lymphocyte ratio (NLR) is a readily available inflammatory biomarker. Objectives To explore the associations of NLR with smoking status, clinical features of COPD, and future adverse outcomes. Methods We analyzed NLR calculated from the complete blood count of participants who currently or formerly smoked (n = 2,624) and tobacco-naive control subjects (n = 187) in the SPIROMICS multicenter observational cohort study. We assessed the stability of NLR at 6 weeks and 1 year, the association with select blood biomarkers, and the impact of smoking on NLR and cell counts. We stratified participants by NLR quartiles to compare cross-sectional clinical features at enrollment, prospectively observed exacerbations at 1 year, and mortality during longitudinal follow up. Results Higher NLR quartiles were broadly associated with more severe clinical features of COPD. NLR values were repeatable at 6 weeks (intraclass correlation coefficient, 0.74) and 1 year (intraclass correlation coefficient, 0.62). The impact of smoking on NLR varied with the severity of airflow limitation, mediated by an interaction between smoking, forced expiratory volume in 1 second percent predicted, and neutrophil counts but not lymphocyte counts. The highest NLR quartile (&gt;3.11) was associated with an increased risk of exacerbation over 1 year (adjusted odds ratio, 1.51; 95% confidence interval, 1.18, 1.92) and increased risk of mortality (adjusted hazard ratio, 1.41; 95% confidence interval, 1.20, 1.66) compared with quartiles 1–3. Conclusions Elevated NLR in stable COPD is a widely available biomarker associated with increased risk for exacerbation and death. The impact of cigarette smoking on NLR varies with disease severity.