BACKGROUND:Coronary artery calcification (CAC) is a specific feature of atherosclerotic cardiovascular disease. Continued improvements in computed tomography (CT) technology may complicate CAC progression assessment in longitudinal studies that change scanner protocols. Herein, we assessed agreement in CAC measures derived from consecutive non-ECG-gated, chest CT scans performed on the same visit and differing only in radiation dose. METHODS:Agreement in quantitative CAC scores and CAC score categories were determined from a subset of COPDGene participants (N ​= ​115; age: 66 (9) years; 50% male) who received full- (mean effective radiation dose of 6.5 (1.0) mSv) and reduced- (1.5 (0.7) mSv) dose non-ECG-gated CT chest scans at maximal inspiration during their Phase 2 COPDGene study visit. RESULTS:CAC measures from the two scanning protocols had high correlation (r ​= ​0.99, 95%CI: 0.99-0.99, p ​< ​0.001), excellent reliability (ICC ​= ​0.98, 95%CI: 0.97-0.99, p ​= ​0.012), and almost perfect agreement (Kw= ​0.96, SE ​= ​0.01, 95% CI: 0.95-0.98). With the full-dose protocol as reference, the reduced-dose protocol had high sensitivity and specificity for determining CAC presence, 94.5% (95%CI: 87.6%-98.2%) and 100% (95% CI: 85.8%-100%), respectively. A Bland-Altman analysis revealed a non-significant higher CAC score with the full-dose protocol: mean bias between protocols of 26 with 95% limits of agreement of -185 to 237. CONCLUSION:CAC scores from non-ECG-gated, chest CT scans are robust to changes in radiation dose at the group level; however, when CAC burden increases, the variability of the CAC score differences increases. CLINICAL TRIALS: GOV IDENTIFIER:NCT00608764.

Background Cognitive impairment (CI) is among the extrapulmonary comorbidities that are increasingly recognised in individuals with COPD and a history of cigarette smoke exposure. While severe hypoxaemia is a well-established risk factor for CI, the role of moderate hypoxaemia (peripheral oxygen saturation ( S pO 2 ) 89–93%) is unknown. Methods We evaluated the association between moderate hypoxaemia, assessed by pulse oximetry, and CI in participants from the Genetic epidemiology of COPD (COPDGene) study who completed the Phase 3 (10-year follow-up) visit. We performed mediation analysis of moderate hypoxaemia on the association between COPD and CI. We tested for differences in proteomic biomarkers of cerebral hypoxia and performed differential gene expression and pathway enrichment analyses to compare individuals with moderate hypoxaemia with those with CI. Findings We found that moderate hypoxaemia at the 5-year follow-up visit, but not at the baseline visit, is associated with CI as assessed at the 10-year follow-up visit (OR 1.49, 95% confidence interval 1.10–1.99). In addition, moderate hypoxaemia significantly mediates the association between COPD and CI (average causal-mediated effect, 27.3%; p<0.001). Out of 38 proteins previously associated with cerebral hypoxia, 13 were significantly associated with moderate hypoxaemia. Interpretation Our study establishes moderate hypoxaemia as an important risk factor for CI in individuals with a history of cigarette smoke exposure and as a mediator of the risk of CI in individuals with COPD. We also identify multi-omic biomarkers that better characterise the biological pathways underlying the association between moderate hypoxaemia and CI. Future studies are needed to identify individuals with moderate hypoxaemia who are at the highest risk of CI.

Abstract Background The development of pulmonary hypertension (PH) is a serious complication of chronic obstructive pulmonary disease (COPD). Despite advances in characterizing pulmonary vascular remodeling in COPD-PH, the lack of targeted therapies limits the routine use of gold-standard invasive diagnostics, highlighting the need for novel biomarkers. The pulmonary vascular endothelium is central to the pathogenesis of both PH and COPD. Since most endothelium-derived modulators of vascular tone and remodeling are targets of endothelial-enriched microRNA-126 (miR-126), a master vascular regulator that is suppressed in COPD, these and related ‘angiocentric molecules’ may be promising biomarkers for COPD-PH. Research Goal To identify angiocentric proteins elevated in individuals with suspected COPD-PH, defined by a pulmonary artery-to-aorta ratio (PA/A) > 1 on thoracic CT, and to evaluate if they are significantly associated with the severity of airflow limitation (FEV₁). Study Design We analyzed plasma proteomic profiles from 1,056 COPDGene Phase-1 participants. Using PA/A > 1 as the outcome, we identified differentially abundant angiocentric proteins. We then assessed the abundance of angiocentric proteins in those with severe airflow obstruction (FEV₁ <50% predicted) among both the COPDGene Phase-1 participants and 188 SPIROMICS Visit-1 participants, and validated the findings in an independent cohort of 363 COPDGene Phase-2 participants. Mediation analyses of multi-omic data examined the relationships between specific miR-126-3p and -p strands levels, their target mRNA and protein levels, and the severity of airflow obstruction. Results Seventeen angiocentric proteins were increased in participants with PA/A > 1, with interleukin-1 receptor-like 1 (IL1RL1) and platelet-derived growth factor B (PDGFB) showing the most significant elevations. Among those with FEV₁ <50% predicted, eleven angiocentric proteins were increased, including IL1RL1, angiopoietin-2, and peroxiredoxin-5. Mediation analyses supported a contribution of reduced miR-126 levels to lower FEV₁ via select angiocentric molecules, including the direct miR-126 target selenoprotein T. Additionally, LINC01506 and CAPZA1 had a mediation effect on multiple clinical outcomes, including FEV₁, DLCO, and hematocrit. Conclusion In addition to their role in pulmonary vascular remodeling, miR-126–regulated angiocentric proteins are also linked to airflow limitation, highlighting their potential as candidate biomarkers for COPD-associated pulmonary hypertension.

BACKGROUNDWe constructed multi-trait polygenic risk scores (PRSs) predicting chronic obstructive pulmonary disease (COPD) and exacerbations, validated their performance in diverse cohorts, and identified PRS-related proteins for potential therapeutic targeting.METHODSPRSmix+, a multi-trait PRS framework, is used to train a composite PRS (PRSmulti) in COPDGene non-Hispanic White participants (n = 6,647). Associations of PRSmulti with COPD status (GOLD 2-4 vs. GOLD 0 or ICD) and exacerbation frequency were tested in COPDGene African American (n = 2,466), ECLIPSE (n = 1,858), Mass General Brigham Biobank (n = 15,152), and All of Us (n = 118,566). Protein prediction models were applied to GWAS summary statistics from traits contributing to PRSmulti and were validated with proteomic data in COPDGene (n = 5,173) and UK Biobank (n = 5,012).RESULTSPRSmix+ selected 7 traits for PRSmulti. In multivariable models, PRSmulti was associated with COPD status (meta-analysis random effects [RE] OR 1.58 [95% CI: 1.28-1.94]) and exacerbation frequency (meta-analysis RE β 0.21 [95% CI: 0.11-0.31]), with higher effect sizes observed in smoking-enriched cohorts. PRSmulti outperformed traditional single-trait PRS in all tested cohorts. Using protein prediction models, we identified 73 proteins associated with the PRSs that were also validated with measured protein levels in COPDGene and UK Biobank. Of these proteins, 25 were linked to approved or investigational drugs. Notable targets include RAGE/sRAGE, IL1RL1, and SCARF2, all implicated in COPD pathogenesis and exacerbations.CONCLUSIONSMulti-trait PRS improves prediction of COPD and exacerbation risk. Integration with proteomic data identifies druggable protein targets, offering a promising avenue for precision medicine in COPD management.TRIAL REGISTRATIONCOPDGene: ClinicalTrials.gov NCT00608764; ECLIPSE: ClinicalTrials.gov NCT00292552.

Measures from affinity-proteomics platforms often correlate poorly, challenging interpretation of protein associations with genetic variants and phenotypes. Here, we examine 2157 proteins measured on both SomaScan 7k and Olink Explore 3072 across 1930 participants with genetic similarity to European, African, East Asian, and Admixed American ancestry references. Inter-platform correlation coefficients for these 2157 proteins follow a bimodal distribution (median r = 0.30). We evaluate protein measure associations with genetic variants, and find approximately 25-30

Background Chronic obstructive pulmonary disease (COPD) increases cardiovascular disease risk. Coronary artery calcification (CAC) predicts cardiovascular events and mortality in COPD. We hypothesized that plasma proteins linked to pulmonary phenotypes mediate CAC burden. Methods Pulmonary function, emphysema, airway wall thickening, Agatston CAC scores (inverse normal transformed), and relative abundance of 1305 plasma proteins (log‐transformed) were assessed in 989 Phase 1 COPDGene (Genetic Epidemiology of COPD) participants. Proteins associated with both pulmonary phenotypes (FEV 1 [forced expiratory volume in 1 second]%predicted, FVC [forced vital capacity], FEV 1 /FVC, emphysema, airway wall thickness, wall area percentage) and CAC (false discovery rate P ≤0.20) were evaluated using multivariable mediation. Model adjustments included sex, age, race, body mass index, smoking, comorbidities, and medications. Adjustment for pulmonary artery‐to‐aortic diameter ratio—a marker of pulmonary vascular pressure—was also explored. The95% bootstrap CIs that excluded zero were considered significant. Results FEV 1 %predicted ( P =0.026) and FEV 1 /FVC ( P =0.010) were associated with CAC. After adjusting for FEV 1 , visual emphysema, and visual airway wall thickening remained associated with CAC. Five proteins (TSP2 [thrombospondin‐2], renin, MMP‐7 [matrix metalloproteinase‐7], ERBB1 [epidermal growth factor receptor], MIC‐1 [macrophage inhibitory cytokine‐1]) mediated the FEV 1 %predicted and CAC association. All except MIC‐1 mediated FEV 1 /FVC and CAC. All except renin mediated quantitative airway wall thickness or wall area percentage and CAC. Additionally, α2‐antiplasmin (alpha‐2 antiplasmin) mediated airway wall thickness and CAC. ERBB1 mediated visual paraseptal emphysema and CAC. Pulmonary artery‐to‐aortic diameter ratio adjustment reduced or eliminated some mediation effects. ERBB1 remained an independent mediator across multiple phenotypes. Conclusions Six plasma proteins mediated associations between COPD phenotypes and CAC burden. These effects were partially influenced by pulmonary artery‐to‐aortic diameter ratio A, suggesting shared molecular pathways linking lung dysfunction to cardiovascular risk in COPD.

BACKGROUND:Among individuals with a history of smoking but preserved spirometry (tobacco exposed with preserved spirometry, or TEPS), lung volume-based stratification identifies 2 phenotypes at increased risk for chronic obstructive pulmonary disease (pre-COPD): those with a relatively elevated total lung capacity ([TLC]high) and those with a relatively elevated functional residual capacity-to-TLC ratio ([FRC/TLC]high). These subgroups exhibit distinct respiratory symptoms, radiographic abnormalities, and clinical trajectories. OBJECTIVE:This study aimed to determine whether these lung volume-based pre-COPD phenotypes have distinct biological features reflected in their circulating proteomes. METHODS:We analyzed peripheral blood proteomic profiles (SomaScan v4.0; 4979 aptamers) from 1959 TEPS participants at the 5-year follow-up visit (visit 2) of the Genetic Epidemiology of COPD study cohort. Participants with [TLC]high and [FRC/TLC]high (based on computerized tomography scan-derived supine lung volumes) were compared with a low-COPD-risk reference group (without high TLC or high FRC/TLC). Analyses included covariate-adjusted regression, machine learning, and pathway enrichment modeling, with adjustment for age, sex, height, weight, smoking status and burden, leukocyte and platelet counts, forced expiratory volume in 1 second (percent predicted), and study site (random effect). RESULTS:Using visit 2 data and visit 3 (10-year) follow-up outcomes, we confirmed the reproducibility and prognostic validity of the lung volume-based phenotypes in 1232 participants with longitudinal data. Over a mean (SD) of 5.3 (1.1) years, spirometric COPD developed in 17% (133 out of 761) of pre-COPD TEPS vs 8% (37 out of 471) of low-risk TEPS (adjusted odds ratio [aOR], 2.51; 95% confidence interval [CI], 1.69-3.75; P < .001). Among pre-COPD subgroups, [FRC/TLC]high TEPS showed greater progression to a Global Initiative for Chronic Obstructive Lung Disease stage 2 or higher (aOR, 2.90; 95% CI, 1.62-5.18; P < .001) and preserved ratio and impaired spirometry (aOR, 3.29; 95% CI, 1.41-7.69; P = .005). At baseline (n = 1959), plasma proteomic analysis identified 165 upregulated and 145 downregulated proteins in [TLC]high TEPS compared with low-COPD-risk TEPS, whereas only 22 proteins were differentially expressed in [FRC/TLC]high TEPS vs low-risk group. Comparison between the 2 pre-COPD phenotypes identified 269 differentially expressed proteins (116 upregulated and 153 downregulated in [FRC/TLC]high vs [TLC]high), including previously described COPD-related mediators (eg, soluble receptor for advanced glycation end products, insulin-like growth factor-binding protein) and novel candidates (eg, zymogen granule membrane protein 16). Pathway analysis highlighted immune signaling, cellular trafficking, and apoptotic pathways relevant to COPD pathogenesis. CONCLUSIONS:Lung volume-based stratification in TEPS identifies biologically distinct subgroups with differing plasma proteomic signature and COPD risk, underscoring the heterogeneity of early disease and revealing potential circulating biomarkers of pre-COPD states. REGISTRATION:COPDGene study is registered with ClinicalTrials.gov: ID NCT00608764.Keywordspre-COPD, lung volumes, proteomics, biomarkers, chronic obstructive pulmonary disease.

Individuals with chronic obstructive pulmonary disease (COPD) and cigarette smoking exposure are at increased risk of cognitive impairment; however, the clinical characteristics of those at risk are incompletely understood. We conducted a secondary analysis of COPDGene cohort data to identify clinical characteristics, particularly pulmonary function and lung CT metrics, associated with cognitive impairment. Cognitive items available from Phase 3 included: self-report of a cognitive disorder diagnosis and cognitive difficulties, and probable cognitive impairment (pCI) defined by Mini-Cog ≤ 3. Thirty-seven variables were considered for inclusion in a mixed effects logistic regression with pCI as the dependent variable including demographics, smoking history, medical history, symptom severity, pulmonary function testing, and COPD-related lung CT variables. Among 2,079 participants (mean age = 68.7[SD ± 8.6] years, 51.2

Chronic obstructive pulmonary disease (COPD) exhibits marked heterogeneity in lung function decline, mortality, exacerbations, and other disease-related outcomes. Omic risk scores (ORS) estimate the cumulative contribution of omics, such as the transcriptome, proteome, and metabolome, to a particular trait. This study evaluated associations between blood-based ORS and COPD-related traits in both smoking-enriched and general population cohorts. ORS were developed and tested in 3,339 participants of Genetic Epidemiology of COPD (COPDGene) with blood RNA-sequencing, proteomic, and metabolomic data. Single- and multi-omic risk scores were trained on 24 cross-sectional and five longitudinal traits using 80

BACKGROUND:Chronic Obstructive Pulmonary Disease (COPD) is a complex and heterogeneous disease. Emphysema-predominant and non-emphysema predominant COPD are two major disease subtypes capturing important aspects of COPD heterogeneity. Molecular differences between these COPD subtypes are unknown. METHODS:We assessed plasma proteomic associations (using SomaScan) with emphysema-predominant vs. non-emphysema predominant COPD subtypes in COPDGene; replication of significant associations was performed in SPIROMICS. We performed pathway analyses on COPD subtype plasma proteomic associations and used weighted gene correlation network analysis to find COPD subtype-associated protein correlation networks. We tested previously reported COPD genetic variants for association with COPD subtypes and COPD subtype-associated proteomic biomarkers. FINDINGS:One hundred and twenty-four proteins were significantly associated with COPD subtypes in COPDGene, with 64 proteins (65 SOMAmers) validated in SPIROMICS. Higher correlations were observed between proteomic biomarkers with greater expression levels in non-emphysema predominant participants with COPD. Cell adhesion, collagen-containing extracellular matrix, and epithelial mesenchymal transition were biological pathways enriched for COPD subtype proteomic associations. One COPD subtype-associated correlation network module was identified, including highly connected proteomic biomarkers like PXDN and EFNA2. We observed significant genetic effects on COPD subtypes for rs2579762 in LRMDA and on COPD subtype-associated proteomic biomarkers including sRAGE and Ganglioside GM2 Activator. INTERPRETATION:We identified and replicated multiple plasma proteomic biomarkers associated with emphysema-predominant vs. non-emphysema predominant COPD. Pathway analyses, correlation-based network analyses, and genetic association analyses of these proteins may provide insight into the molecular heterogeneity of COPD. FUNDING:National Heart, Lung, and Blood Institute (NIH).

Importance:Individuals at risk for chronic obstructive pulmonary disease (COPD) but without spirometric airflow obstruction can have respiratory symptoms and structural lung disease on chest computed tomography. Current guidelines recommend COPD diagnostic schemas that do not incorporate imaging abnormalities. Objective:To determine whether a multidimensional COPD diagnostic schema that includes respiratory symptoms and computed tomographic imaging abnormalities identifies additional individuals with disease. Design, Setting, and Participants:This cohort study included 2 longitudinal cohorts: the Genetic Epidemiology of COPD (COPDGene), which enrolled 10 305 participants between November 9, 2007, and April 15, 2011, with longitudinal follow-up through August 31, 2022; and the Canadian Cohort Obstructive Lung Disease (CanCOLD), which enrolled 1561 participants between November 26, 2009, and July 15, 2015, with follow-up through December 31, 2023. Exposure:Exposure included the new multidimensional COPD diagnostic schema, defined by (1) major diagnostic category: presence of the major criterion (airflow obstruction based on postbronchodilator forced expiratory volume in the first second of expiration [FEV1]/forced vital capacity ratio <0.70) and at least 1 of 5 minor criteria (emphysema or bronchial wall thickening on computed tomography, dyspnea, poor respiratory quality of life, and chronic bronchitis); or (2) minor diagnostic category: presence of least 3 of 5 minor criteria (which must include emphysema and bronchial wall thickening for individuals with respiratory symptoms potentially due to other causes). Main Outcomes and Measures:All-cause mortality, respiratory cause-specific mortality, exacerbations, and annualized change in FEV1. Results:Among 9416 adults in COPDGene (mean [SD] age at enrollment, 59.6 [9.0] years; 5035 [53.5%] were men; 3071 [32.6%] were Black; 6345 (67.4%) were White; 4943 [52.5%] currently smoked), 811 of 5250 individuals (15.4%) without airflow obstruction were newly classified as having COPD by minor diagnostic category, and 282 of 4166 individuals (6.8%) with airflow obstruction were classified as not having COPD. Reclassified individuals with a new COPD diagnosis had greater all-cause mortality (adjusted hazard ratio, 1.98; 95% CI, 1.67-2.35; P < .001) and respiratory-specific mortality (adjusted hazard ratio, 3.58; 95% CI, 1.56-8.20; P = .003), more exacerbations (adjusted incidence rate ratio, 2.09; 95% CI, 1.79-2.44; P < .001), and more rapid FEV1 decline (adjusted β = -7.7 mL/y; 95% CI, -13.2 to -2.3; P = .006) compared with individuals classified as not having COPD. Among individuals with airflow obstruction on spirometry, those no longer classified as having COPD based on this new diagnostic schema had outcomes similar to those without airflow obstruction. Among 1341 adults in CanCOLD, individuals newly classified as having COPD experienced more exacerbations (adjusted incidence rate ratio, 2.09; 95% CI, 1.25-3.51; P < .001). Conclusions and Relevance:A new COPD diagnostic schema integrating respiratory symptoms, respiratory quality of life, spirometry, and structural lung abnormalities on computed tomographic imaging newly classified some individuals as having COPD. These individuals had an increased risk of all-cause and respiratory-related death, frequent exacerbations, and rapid lung function decline compared with individuals classified as not having COPD. Some individuals with airflow obstruction without respiratory symptoms or evidence of structural lung disease were no longer classified as having COPD.

Introduction There is an increased risk of chronic obstructive pulmonary disease (COPD) in heterozygotes for the alpha-1 antitrypsin (AAT) Z allele (PI*MZ), but there is significant variation in outcomes. Matrix metalloproteinases (MMPs) contribute to worse airway disease and emphysema. Given that the AAT protein is an antiprotease, we hypothesised that MMPs play a modifying role among AAT-deficient individuals.Methods We studied PI*MZ (n=39) and PI*ZZ (n=27) individuals from the Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis Study cohort. MMP (MMP3, MMP9, MMP10, MMP12 and MMP15) gene expression was assessed in bronchoalveolar lavage cells and peripheral blood mononuclear cells. Plasma protein MMP (MMP3, MMP9, MMP10 and MMP12) expression was assessed using SomaScan and BAL MMP15 protein using ELISA. MMP values were log-transformed, and linear regression analyses were used to assess lung function, patient-reported outcomes and CT emphysema adjusted for age, body mass index, sex and duration of smoking.Results Alveolar MMP3 and MMP15 were uniquely associated with worse lung function, patient-reported outcomes and emphysema among PI*MZ individuals. MMP10 was associated with less disease severity among PI*MZ individuals.Discussion Our study shows that alveolar MMP3 and MMP15 may uniquely contribute to disease among PI*MZ individuals, raising the possibility that they could serve as biomarkers or therapeutic targets in this highly prevalent COPD phenotype. Furthermore, we show that MMP10 may serve a protective effect. In aggregate, these data support further studies of the MMP pathway among lung-affected PI*MZ individuals, as they may serve as biomarkers or pharmacological targets in future studies.

Multiple -omics (genomics, proteomics, etc.) profiles are commonly generated to gain insight into a disease or physiological system. Constructing multi-omics networks with respect to the trait(s) of interest provides an opportunity to understand relationships between molecular features but integration is challenging due to multiple data sets with high dimensionality. One approach is to use canonical correlation to integrate one or two omics types and a single trait of interest. However, these types of methods may be limited due to (1) not accounting for higher-order correlations existing among features, (2) computational inefficiency when extending to more than two omics data when using a penalty term-based sparsity method, and (3) lack of flexibility for focusing on specific correlations (e.g., omics-to-phenotype correlation versus omics-to-omics correlations). In this work, we have developed a novel multi-omics network analysis pipeline called Sparse Generalized Tensor Canonical Correlation Analysis Network Inference (SGTCCA-Net) that can effectively overcome these limitations. We also introduce an implementation to improve the summarization of networks for downstream analyses. Simulation and real-data experiments demonstrate the effectiveness of our novel method for inferring omics networks and features of interest.

Individuals homozygous for the Alpha-1 Antitrypsin (AAT) Z allele (Pi*ZZ) exhibit heterogeneity in COPD risk. COPD occurrence in non-smokers with AAT deficiency (AATD) suggests that inflammatory processes may contribute to COPD risk independently of smoking. We hypothesized that inflammatory protein biomarkers in non-AATD COPD are associated with moderate-to-severe COPD in AATD individuals, after accounting for clinical factors. Participants from the COPDGene (Pi*MM) and AAT Genetic Modifiers Study (Pi*ZZ) were included. Proteins associated with FEV1/FVC were identified, adjusting for confounders and familial relatedness. Lung-specific protein–protein interaction (PPI) networks were constructed. Proteins associated with AAT augmentation therapy were identified, and drug repurposing analyses performed. A protein risk score (protRS) was developed in COPDGene and validated in AAT GMS using AUROC analysis. Machine learning ranked proteomic predictors, adjusting for age, sex, and smoking history. Among 4,446 Pi*MM and 352 Pi*ZZ individuals, sixteen blood proteins were associated with airflow obstruction, fourteen of which were highly expressed in lung. PPI networks implicated regulation of immune system function, cytokine and interleukin signaling, and matrix metalloproteinases. Eleven proteins, including IL4R, were linked to augmentation therapy. Drug repurposing identified antibiotics, thyroid medications, hormone therapies, and antihistamines as potential adjunctive AATD treatments. Adding protRS improved COPD prediction in AAT GMS (AUROC 0.86 vs. 0.80, p = 0.0001). AGER was the top-ranked protein predictor of COPD. Sixteen proteins are associated with COPD and inflammatory processes that predict airflow obstruction in AATD after accounting for age and smoking. Immune activation and inflammation are modulators of COPD risk in AATD.

Introduction and Objective: Ferritin is one of the most reliable markers of body iron stores. While most of the known gene mutations associated with hemochromatosis are observed less frequently in Blacks, mutations in the SL40A1 gene (rarely observed in European ancestry populations), characterized by low hemoglobin and high ferritin levels, is more common in Blacks. Black Americans generally have higher ferritin levels even in the presence of low hemoglobin. Increased ferritin has been linked to impaired glucose tolerance and frank diabetes, independent of inflammation, while iron has been shown to be directly toxic to pancreatic beta cells. We tested whether variations in SNPs of the SL40A1 gene and plasma proteomic iron storage markers with diabetes risk among Black Americans. Methods: African American (AA) participants from the COPDGene Cohort who were free of diabetes (4,227) at study baseline were followed for the incidence of diabetes. The Somascan was used to determine relative amounts of ferritin among participants, and was natural log transformed for all analysis. Logistic regression was used to calculate OR (95% CIs) of the relationship of SNPs on the SL40A1 gene, using a dominant genetic model, and ferritin with diabetes risk. Results: There were 341 incident diabetes cases (8.1%) during the 5.6 years of followup. SNPs rs11539983_C, rs4667287_C, rs1439812_G, rs1123110_A, rs1123109_C were associated with increased plasma proteomic ferritin levels. Of these, heterozygosity or homozygosity for one of the following SNPs was significantly associated with incident diabetes: rs1123109_C (OR=2.53, 1.03-6.22); rs11539983_C (OR=1.59, 1.21-2.10); and rs4667287_C (OR=1.27, 1.04-1.55). In each of the models, ferritin was associated with significantly increased risk of diabetes (ORs ranged from 1.18-1.21). Conclusion: SNPs located on the SL40A1 that codes for ferritin storage are associated with increased risk of diabetes among African Americans. Disclosure R.B. Conway: None. K.A. Young: None. K.A. Pratte: None. G.L. Kinney: None. R. Bowler: None. Funding This work was supported by NHLBI (U01 HL089897, U01 HL089856). The COPDGene study (NCT00608764) is also supported by the COPD Foundation through contributions made to an Industry Advisory Committee that has included AstraZeneca, Bayer Pharmaceuticals, Boehringer-Ingelheim, Genentech, GlaxoSmithKline, Novartis, Pfizer, and Sunovion

Pulmonary emphysema occurs frequently in older adults, often without airflow limitation. Its presence predicts symptoms, respiratory hospitalizations and deaths, and all-cause mortality. Proteomics may provide further insights into emphysema pathogenesis and inform therapeutic targets. We performed a proteomic discovery analysis of percent emphysema on computed tomography (CT) in a population-based, multiethnic sample from the Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study. Replication was performed in two chronic obstructive pulmonary disease (COPD)-based studies, the SubPopulations and InteRmediate Outcome Measures in COPD Study (SPIROMICS) and the Genetic Epidemiology of COPD (COPDGene) Study. MESA recruited participants from the general population in 2000–02. The MESA Lung Study performed full-lung CT scans in 2010–12. Percent emphysema was defined as the percentage of lung voxels < -950 Hounsfield units. Over 7,200 plasma aptamers were measured via SomaScan. Cross-sectional linear and least absolute shrinkage and selection operator (LASSO) regression models were adjusted for demographics, anthropometrics, smoking, renal function, and scanner parameters. Statistical significance was defined as a false discovery rate p-value < 0.05. Gene Ontology (GO)/Reactome enrichment analyses were performed. LASSO-selected proteins’ predictive performance was evaluated. Among 2,504 participants in the MESA Lung Study, mean age was 69.4 years, 1,291 had ever smoked, and median percent emphysema-like lung was 1.4

ABSTRACTRationaleEmphysema is a COPD phenotype with important prognostic implications. Identifying blood-based biomarkers of emphysema will facilitate early diagnosis and development of targeted therapies.ObjectivesDiscover blood omics biomarkers for chest CT-quantified emphysema and develop predictive biomarker panels.MethodsEmphysema blood biomarker discovery was performed using differential gene expression, alternative splicing, and protein association analyses in a training set of 2,370 COPDGene participants with available whole blood RNA sequencing, plasma SomaScan proteomics, and clinical data. Validation was conducted in a testing set of 1,016 COPDGene subjects. Since low body mass index (BMI) and emphysema often co-occur, we performed a mediation analysis to quantify the effect of BMI on gene and protein associations with emphysema. Elastic net models were also developed in the training sample sequentially using clinical, complete blood count (CBC) cell proportions, RNA sequencing, and proteomic biomarkers to predict quantitative emphysema. Model accuracy was assessed in the testing sample by the area under the receiver-operator-characteristic-curves (AUROC) for subjects stratified into tertiles of emphysema severity.Measurements and Main Results4,913 genes, 1,478 isoforms, 386 exons, and 881 proteins were significantly associated with emphysema(FDR 10%)and yielded 109 biological pathways. 75% of the genes and 77% of the proteins associated with emphysema showed evidence of mediation by BMI. The highest-performing predictive model used clinical, CBC, and protein biomarkers, distinguishing the top from the bottom tertile of emphysema with an AUROC of 0.92.ConclusionsBlood transcriptome and proteome-wide analyses reveal key biological pathways of emphysema and enhance the prediction of emphysema.AT A GLANCE COMMENTARYScientific Knowledge on the SubjectDifferential gene expression and protein analyses have uncovered some of the molecular underpinnings of emphysema. However, no studies have assessed alternative splicing mechanisms and analyzed proteomic data from recently developed high-throughput panels. In addition, although emphysema has been associated with low body mass index (BMI), it is still unclear how BMI affects the transcriptome and proteome of the disease. Finally, the effectiveness of multi-omic biomarkers in determining the severity of emphysema has not yet been investigated.What This Study Adds to the FieldWe performed whole-blood genome-wide RNA sequencing and plasma SomaScan proteomic analyses in the large and well-phenotyped COPDGene study. In addition to confirming earlier findings, our differential gene expression, alternative splicing, and protein analyses identified novel biomarkers and pathways of chest CT-quantified emphysema. Our mediation analysis detected varying degrees of transcriptomic and proteomic mediation due to BMI. Our supervised machine learning modeling demonstrated the utility of incorporating multi-omics data in enhancing the prediction of emphysema.

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.