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Most transcriptome-wide association studies (TWASs) so far focus on European ancestry and lack diversity. To overcome this limitation, we aggregated genome-wide association study (GWAS) summary statistics, whole-genome sequences and expression quantitative trait locus (eQTL) data from diverse ancestries. We developed a new approach, TESLA (multi-ancestry integrative study using an optimal linear combination of association statistics), to integrate an eQTL dataset with a multi-ancestry GWAS. By exploiting shared phenotypic effects between ancestries and accommodating potential effect heterogeneities, TESLA improves power over other TWAS methods. When applied to tobacco use phenotypes, TESLA identified 273 new genes, up to 55% more compared with alternative TWAS methods. These hits and subsequent fine mapping using TESLA point to target genes with biological relevance. In silico drug-repurposing analyses highlight several drugs with known efficacy, including dextromethorphan and galantamine, and new drugs such as muscle relaxants that may be repurposed for treating nicotine addiction.

IntroductionIn the personalized risk quantification of chronic obstructive pulmonary disease (COPD), genome-wide association studies and polygenic risk scores (PRS) complement traditional risk factors, such as age and cigarette smoking. However, despite being at considerable levels of risk, some individuals do not develop COPD. Research on COPD resilience remains largely unexplored.MethodsWe applied the previously published COPD PRS to whole genome sequencing data from non-Hispanic white and African American individuals in the COPDGene study. We defined genetic resilience as individuals unaffected by COPD with a polygenic risk score above the 90thpercentile. We defined risk-matched case individuals as those with COPD (i.e., FEV1/FVC < 0.70) and a PRS above the 90thpercentile. We defined low risk individuals without COPD (i.e., FEV1/FVC > 0.70) as a polygenic risk score below the 10thpercentile. We compared genetically resilient individuals to risk-matched individuals with COPD and low risk individuals by demographics, lung function, respiratory symptoms, co-morbidities, and chest CT scan measurements. We also performed survival analyses, differential expression analysis, and matching for sensitivity analyses.ResultsWe identified 211 resilient individuals without COPD, 605 genetic risk-matched individuals with COPD, and 527 low-risk individuals without COPD. Resilient individuals had higher FEV1% predicted and lower percent emphysema. In contrast, resilient individuals had higher airway wall thickness compared to low-risk unaffected individuals. While there was no difference in survival between low-risk and resilient individuals, resilient individuals had higher survival compared to risk matched cases. We also identified two genes that were differentially expressed between low-risk unaffected individuals and resilient individuals.ConclusionGenetically resilient individuals had a reduced burden of COPD disease-related measures compared to risk-matched cases but had subtly increased measures compared to low-risk unaffected individuals. Further genetic studies will be needed to illuminate the underlying pathobiology of our observations.

While polygenic risk scores (PRSs) enable early identification of genetic risk for chronic obstructive pulmonary disease (COPD), predictive performance is limited when the discovery and target populations are not well matched. Hypothesizing that the biological mechanisms of disease are shared across ancestry groups, we introduce a PrediXcan-derived polygenic transcriptome risk score (PTRS) to improve cross-ethnic portability of risk prediction. We constructed the PTRS using summary statistics from application of PrediXcan on large-scale GWASs of lung function (forced expiratory volume in 1 s [FEV(1)] and its ratio to forced vital capacity [FEV(1)/FVC]) in the UK Biobank. We examined prediction performance and cross-ethnic portability of PTRS through smoking-stratified analyses both on 29,381 multi-ethnic participants from TOPMed population/family-based cohorts and on 11,771 multi-ethnic participants from TOPMed COPD-enriched studies. Analyses were carried out for two dichotomous COPD traits (moderate-to-severe and severe COPD) and two quantitative lung function traits (FEV(1) and FEV(1)/FVC). While the proposed PTRS showed weaker associations with disease than PRS for European ancestry, the PTRS showed stronger association with COPD than PRS for African Americans (e.g., odds ratio [OR] = 1.24 [95% confidence interval [CI]: 1.08–1.43] for PTRS versus 1.10 [0.96–1.26] for PRS among heavy smokers with ≥ 40 pack-years of smoking) for moderate-to-severe COPD. Cross-ethnic portability of the PTRS was significantly higher than the PRS (paired t test p

Chronic obstructive pulmonary disease (COPD) is associated with age and smoking, but other determinants of the disease are incompletely understood. Clonal hematopoiesis of indeterminate potential (CHIP) is a common, age-related state in which somatic mutations in clonal blood populations induce aberrant inflammatory responses. Patients with CHIP have an elevated risk for cardiovascular disease, but the association of CHIP with COPD remains unclear. We analyzed whole-genome sequencing and whole-exome sequencing data to detect CHIP in 48 835 patients, of whom 8444 had moderate to very severe COPD, from four separate cohorts with COPD phenotyping and smoking history. We measured emphysema in murine models in which Tet2 was deleted in hematopoietic cells. In the COPDGene cohort, individuals with CHIP had risks of moderate-to-severe, severe, or very severe COPD that were 1.6 (adjusted 95% confidence interval [CI], 1.1-2.2) and 2.2 (adjusted 95% CI, 1.5-3.2) times greater than those for noncarriers. These findings were consistently observed in three additional cohorts and meta-analyses of all patients. CHIP was also associated with decreased FEV1% predicted in the COPDGene cohort (mean between-group differences, −5.7%; adjusted 95% CI, −8.8% to −2.6%), a finding replicated in additional cohorts. Smoke exposure was associated with a small but significant increased risk of having CHIP (odds ratio, 1.03 per 10 pack-years; 95% CI, 1.01-1.05 per 10 pack-years) in the meta-analysis of all patients. Inactivation of Tet2 in mouse hematopoietic cells exacerbated the development of emphysema and inflammation in models of cigarette smoke exposure. Somatic mutations in blood cells are associated with the development and severity of COPD, independent of age and cumulative smoke exposure.

Rationale: The ability of peripheral blood biomarkers to assess COPD risk and progression is unknown. Genetics and gene expression may capture important aspects of COPD-related biology that predict...

Chronic Obstructive Pulmonary Disease (COPD) has a simple physiological diagnostic criterion but a wide range of clinical characteristics. The mechanisms underlying this variability in COPD phenotypes are unclear. To investigate the potential contribution of genetic variants to phenotypic heterogeneity, we examined the association of genome-wide associated lung function, COPD, and asthma variants with other phenotypes using phenome-wide association results derived in the UK Biobank. Our clustering analysis of the variants-phenotypes association matrix identified three clusters of genetic variants with different effects on white blood cell counts, height, and body mass index (BMI). To assess the potential clinical and molecular effects of these groups of variants, we investigated the association between cluster-specific genetic risk scores and phenotypes in the COPDGene cohort. We observed differences in steroid use, BMI, lymphocyte counts, chronic bronchitis, and differential gene and protein expression across the three genetic risk scores. Our results suggest that multi-phenotype analysis of obstructive lung disease-related risk variants may identify genetically driven phenotypic patterns in COPD.

ObjectivesInvestigate the prevalence and mortality impact of interstitial lung abnormalities (ILA) in rheumatoid arthritis (RA) and non-RA comparators.MethodsWe analyzed associations between ILA, RA, and mortality in COPDGene, a multicenter prospective cohort study of current or former smokers, excluding known interstitial lung disease (ILD) or bronchiectasis. All participants had research chest high-resolution computed tomography (HRCT) reviewed by a sequential reading method to classify ILA as present, indeterminate, or absent as well as fibrotic or nonfibrotic ILA subtype. RA cases were identified by self-report RA and DMARD use; non-RA comparators had neither an RA diagnosis nor used DMARDs. We examined the association and mortality risk of RA and ILA using multivariable logistic regression and Cox regression.ResultsWe identified 83 RA cases and 8725 non-RA comparators with HRCT performed for research purposes. ILA prevalence was 16.9% in RA cases and 5.0% in non-RA comparators. After adjusting for potential confounders including genetics, smoking, and other lifestyle factors, ILA were more common among those with RA compared to non-RA (OR 4.76 95%CI 2.54 to 8.92). RA with ILA or indeterminate for ILA was associated with higher mortality compared to non-RA without ILA (HR 3.16, 95%CI 2.11 to 4.74) and RA cases without ILA (HR 3.02, 95%CI 1.36 to 6.75).ConclusionsRA was associated with ILA and this persisted after adjustment for smoking and genetic/lifestyle risk factors. RA with ILA in chronic heavy smokers had 3-fold increased mortality, emphasizing the importance of further screening and treatment strategies for subclinical ILD in RA.KEY MESSAGESWhat is already known on this topicUp to a third of patients with rheumatoid arthritis (RA) may have evidence of subclinical interstitial lung abnormalities on computed tomography (CT) scans of the chest.Cigarette smoking and theMUC5Bpromoter variant are known risk factors for RA-associated interstitial lung disease.What this study addsWe found that 17% of RA patients had subclinical interstitial lung abnormalities. RA had 4-fold higher odds of interstitial lung abnormalities than non-RA comparators, adjusted for smoking, theMUC5Bpromoter variant, and other factors.Participants with RA and no interstitial lung abnormalities were not at increased mortality risk while those with interstitial lung abnormalities or indeterminate for ILA had a three-fold increased risk of mortality compared to RA and non-RA patients without interstitial lung abnormalities.How this study might affect research, practice or policyThe presence of subclinical interstitial lung abnormalities confers significant mortality risk in RA and emphasizes the need to establish the clinical utility of screening, prevention, and treatment strategies targeting subclinical lung disease.

BACKGROUND Polygenic risk scores (PRSs) will have important utility for asthma and other chronic diseases as a tool for predicting disease incidence and subphenotypes. OBJECTIVE We utilized findings from a large multiancestry GWAS of asthma to compute a PRS for asthma with relevance for racially diverse populations. METHODS We derived two PRSs for asthma using a standard approach (based on genome-wide significant variants) and a lasso sum regression approach (allowing all genetic variants to potentially contribute). We used data from the racially diverse Kaiser Permanente GERA cohort (68 638 non-Hispanic Whites, 5874 Hispanics, 6870 Asians and 2760 Blacks). Race was self-reported by questionnaire. RESULTS For the standard PRS, non-Hispanic Whites showed the highest odds ratio for a standard deviation increase in PRS for asthma (OR = 1.16 (95% CI 1.14-1.18)). The standard PRS was also associated with asthma in Hispanic (OR = 1.12 (95% CI 1.05-1.19)) and Asian (OR = 1.10 (95% CI 1.04-1.17)) subjects, with a trend towards increased risk in Blacks (OR = 1.05 (95% CI 0.97-1.15)). We detected an interaction by sex, with men showing a higher risk of asthma with an increase in PRS as compared to women. The lasso sum regression-derived PRS showed stronger associations with asthma in non-Hispanic White subjects (OR = 1.20 (95% CI 1.18-1.23)), Hispanics (OR = 1.17 (95% 1.10-1.26)), Asians (OR = 1.18 (95% CI 1.10-1.27)) and Blacks (OR = 1.10 (95% CI 0.99-1.22)). CONCLUSION Polygenic risk scores across multiple racial/ethnic groups were associated with increased asthma risk, suggesting that PRSs have potential as a tool for predicting disease development.

The serpin family A member 1 (SERPINA1) Z allele is present in approximately one in 25 individuals of European ancestry. Z allele homozygosity (Pi*ZZ) is the most common cause of alpha 1‐antitrypsin deficiency and is a proven risk factor for cirrhosis. We examined whether heterozygous Z allele (Pi*Z) carriers in United Kingdom (UK) Biobank, a population‐based cohort, are at increased risk of liver disease. We replicated findings in Massachusetts General Brigham Biobank, a hospital‐based cohort. We also examined variants associated with liver disease and assessed for gene–gene and gene–environment interactions. In UK Biobank, we identified 1,493 cases of cirrhosis, 12,603 Z allele heterozygotes, and 129 Z allele homozygotes among 312,671 unrelated white British participants. Heterozygous carriage of the Z allele was associated with cirrhosis compared to noncarriage (odds ratio [OR], 1.53; P = 1.1×10−04); homozygosity of the Z allele also increased the risk of cirrhosis (OR, 11.8; P = 1.8 × 10−09). The OR for cirrhosis of the Z allele was comparable to that of well‐established genetic variants, including patatin‐like phospholipase domain containing 3 (PNPLA3) I148M (OR, 1.48; P = 1.1 × 10−22) and transmembrane 6 superfamily member 2 (TM6SF2) E167K (OR, 1.34; P = 2.6 × 10−06). In heterozygotes compared to noncarriers, the Z allele was associated with higher alanine aminotransferase (ALT; P = = 4.6 × 10−46), aspartate aminotransferase (AST; P = 2.2 × 10−27), alkaline phosphatase (P = 3.3 × 10−43), gamma‐glutamyltransferase (P = 1.2 × 10−05), and total bilirubin (P = 6.4 × 10−06); Z allele homozygotes had even greater elevations in liver biochemistries. Body mass index (BMI) amplified the association of the Z allele for ALT (P interaction = 0.021) and AST (P interaction = 0.0040), suggesting a gene–environment interaction. Finally, we demonstrated genetic interactions between variants in PNPLA3, TM6SF2, and hydroxysteroid 17‐beta dehydrogenase 13 (HSD17B13); there was no evidence of epistasis between the Z allele and these variants. Conclusion: SERPINA1 Z allele heterozygosity is an important risk factor for liver disease; this risk is amplified by increasing BMI.

Genome-wide association studies (GWASs) have identified regions associated with chronic obstructive pulmonary disease (COPD). GWASs of other diseases have shown an approximately 10-fold overrepresentation of nonsynonymous variants, despite limited exonic coverage on genotyping arrays. We hypothesized that a large-scale analysis of coding variants could discover novel genetic associations with COPD, including rare variants with large effect sizes. We performed a meta-analysis of exome arrays from 218,399 controls and 33,851 moderate-to-severe COPD cases. All exome-wide significant associations were present in regions previously identified by GWAS. We did not identify any novel rare coding variants with large effect sizes. Within GWAS regions on chromosomes 5q, 6p, and 15q, four coding variants were conditionally significant ( P < 0.00015) when adjusting for lead GWAS single-nucleotide polymorphisms A common gasdermin B ( GSDMB) splice variant (rs11078928) previously associated with a decreased risk for asthma was nominally associated with a decreased risk for COPD [minor allele frequency (MAF) = 0.46, P = 1.8e-4]. Two stop variants in coiled-coil α-helical rod protein 1 ( CCHCR1), a gene involved in regulating cell proliferation, were associated with COPD (both P < 0.0001). The SERPINA1 Z allele was associated with a random-effects odds ratio of 1.43 for COPD (95% confidence interval = 1.17–1.74), though with marked heterogeneity across studies. Overall, COPD-associated exonic variants were identified in genes involved in DNA methylation, cell-matrix interactions, cell proliferation, and cell death. In conclusion, we performed the largest exome array meta-analysis of COPD to date and identified potential functional coding variants. Future studies are needed to identify rarer variants and further define the role of coding variants in COPD pathogenesis.

RationaleCOPD can be assessed using multidimensional grading systems with components from three domains: pulmonary function tests, symptoms and systemic features. Clinically, measures may be used interchangeably, though it is not known if they share similar pathobiology.ObjectiveTo use RNA sequencing (RNA-seq) to determine if there is an overlap in the underlying biological mechanisms and consequences driving different components of the multidimensional grading systems.MethodsWhole blood was collected for RNA-seq from current and former smokers in the Genetic Epidemiology of COPD study. We tested the overlap in gene expression and biological pathways associated with case–control status and quantitative COPD phenotypes within and between the three domains.ResultsIn 2647 subjects, there were 3030 genes differentially expressed in any of the three domains or case–control status. There were five genes that overlapped between the three domains and case–control status, including G protein-coupled receptor 15(GPR15), sestrin 1 (SESN1) and interferon-induced guanylate-binding protein 1 (GBP1), which were associated with longitudinal decline in FEV1. The overlap between the three domains was enriched for pathways related to cellular components.ConclusionsWe identified gene sets and pathways that overlap between 12 COPD-related phenotypes and case–control status. There were no pathways represented in the overlap between the three domains and case–control status, but we identified multiple genes that demonstrated a consistent pattern of expression across several of the phenotypes. Patterns of gene expression correlation were generally similar to the correlation of clinical phenotypes in the PFT and symptom domains but not the systemic features.

Lung function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry GWAS meta-analysis of lung function to date, comprising 580,869 participants, 1020 independent association signals identified 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score (GRS) showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies (PheWAS) for selected associated variants, and trait and pathway-specific GRS to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies.

Objectives To investigate the associations of the common MUC5B promoter variant with timing of RA-associated interstitial lung disease (RA-ILD) and RA onset. Methods We identified patients with RA meeting 2010 ACR/EULAR criteria and available genotype information in the Mass General Brigham Biobank, a multihospital biospecimen and clinical data collection research study. We determined RA-ILD presence by reviewing all RA patients who had CT imaging, lung biopsy or autopsy results. We determined the dates of RA and RA-ILD diagnoses by manual records review. We examined the associations of the MUC5B promoter variant (G>T at rs35705950) with RA-ILD, RA-ILD occurring before or within 2 years of RA diagnosis and RA diagnosis at age >55 years. We used multivariable logistic regression to estimate odds ratios (ORs) for each outcome by MUC5B promoter variant status, adjusting for potential confounders including genetic ancestry and smoking. Results We identified 1005 RA patients with available genotype data for rs35705950 (mean age 45 years, 79% female, 81% European ancestry). The MUC5B promoter variant was present in 155 (15.4%) and was associated with RA-ILD [multivariable OR 3.34 (95% CI 1.97, 5.60)], RA-ILD before or within 2 years of RA diagnosis [OR 4.01 (95% CI 1.78, 8.80)] and RA onset after age 55 years [OR 1.52 (95% CI 1.08, 2.12)]. Conclusions The common MUC5B promoter variant was associated with RA-ILD onset earlier in the RA disease course and older age of RA onset. These findings suggest that the MUC5B promoter variant may impact RA-ILD risk early in the RA disease course, particularly in patients with older-onset RA.

Background Despite its proven utility, integration of point-of-care ultrasound (POCUS) into internal medicine (IM) residency training has been inconsistent. Due to their unique constraints, community-based teaching hospitals may face particular challenges in providing POCUS training to IM residents. Objectives To evaluate short-term educational outcomes of an academic center’s POCUS curriculum following its adaptation and delivery to IM residents at a community-based teaching hospital. Methods A needs assessment (NA) regarding POCUS training was distributed to PGY-2 and PGY-3 IM residents at a community-based teaching hospital in 2017. Based on the NA results, a POCUS curriculum from an academic center was modified and a revised course was offered to the same residents. Participants completed cognitive assessments before and after three of the four didactic sessions. Observed placement of an ultrasound-guided peripheral IV before and after the training program comprised the skills assessment. Results 17 of 28 (61%) residents completed the NA; eleven participated in the course. Of 33 possible quiz pairs, 15 (45%) were completed. Average quiz scores rose after the first and third sessions. Skills assessment scores increased after course completion. Conclusion Adaptation of POCUS curricula from academic centers may be a feasible instructional strategy for community-based IM residency programs.

Background: Genetic factors influence chronic obstructive pulmonary disease (COPD) risk, but the individual variants that have been identified have small effects. We hypothesised that a polygenic risk score using additional variants would predict COPD and associated phenotypes. Methods: We constructed a polygenic risk score using a genome-wide association study of lung function (FEV1 and FEV1/forced vital capacity [FVC]) from the UK Biobank and SpiroMeta. We tested this polygenic risk score in nine cohorts of multiple ethnicities for an association with moderate-to-severe COPD (defined as FEV1/FVC 1

The risk factors and clinical outcomes of quantitative interstitial abnormality progression over time have not been characterized.What are the associations of quantitative interstitial abnormality progression with lung function, exercise capacity, and mortality? What are the demographic and genetic risk factors for quantitative interstitial abnormality progression?Quantitative interstitial abnormality progression between visits 1 and 2 was assessed from 4,635 participants in the Genetic Epidemiology of COPD (COPDGene) cohort and 1,307 participants in the Pittsburgh Lung Screening Study (PLuSS) cohort. We used multivariable linear regression to determine the risk factors for progression and the longitudinal associations between progression and FVC and 6-min walk distance, and Cox regression models for the association with mortality.Age at enrollment, female sex, current smoking status, and the MUC5B minor allele were associated with quantitative interstitial abnormality progression. Each percent annual increase in quantitative interstitial abnormalities was associated with annual declines in FVC (COPDGene: 8.5 mL/y; 95% CI, 4.7-12.4 mL/y; P .001; PLuSS: 9.5 mL/y; 95% CI, 3.7-15.4 mL/y; P = .001) and 6-min walk distance, and increased mortality (COPDGene: hazard ratio, 1.69; 95% CI, 1.34-2.12; P .001; PLuSS: hazard ratio, 1.28; 95% CI, 1.10-1.49; P = .001).The objective, longitudinal measurement of quantitative interstitial abnormalities may help identify people at greatest risk for adverse events and most likely to benefit from early intervention.

The identification and understanding of gene-environment interactions can provide insights into the pathways and mechanisms underlying complex diseases. However, testing for gene-environment interaction remains a challenge since statistical power is often limited, the specification of environmental effects is nontrivial, and such misspecifications can lead to false positive findings. To address the lack of statistical power, recent methods aim to identify interactions on an aggregated level using, for example, polygenic risk scores. While this strategy increases power to detect interactions, identifying contributing key genes and pathways is difficult based on these global results.Here, we propose RITSS (Robust Interaction Testing using Sample Splitting), a gene-environment interaction testing framework for quantitative traits that is based on sample splitting and robust test statistics. RITSS can incorporate multiple genetic variants and/or multiple environmental factors. Using sample splitting, a screening step enables the selection and combination of potential interactions into scores with improved interpretability, based on the user’s unrestricted choices for statistical/machine learning approaches. In the testing step, the application of robust test statistics minimizes the susceptibility of the results to main effect misspecifications.Using extensive simulation studies, we demonstrate that RITSS controls the type 1 error rate in a wide range of scenarios. In an application to lung function phenotypes and human height in the UK Biobank, RITSS identified genome-wide significant interactions with subcomponents of genetic risk scores. While the contributing single variant interactions are moderate, our analysis results indicate interesting interaction patterns that result in strong aggregated signals that provide further insights into gene-environment interaction mechanisms.

RATIONALE: Multiple studies have demonstrated an increased risk of chronic obstructive pulmonary disease (COPD) in heterozygous carriers of the AAT (alpha-1 antitrypsin) Z allele. However, it is not known if MZ subjects with COPD are phenotypically different from noncarriers (MM genotype) with COPD. OBJECTIVES: To assess if MZ subjects with COPD have different clinical features compared with MM subjects with COPD. METHODS: Genotypes of SERPINA1 were ascertained by using whole-genome sequencing data in three independent studies. We compared outcomes between MM subjects with COPD and MZ subjects with COPD in each study and combined the results in a meta-analysis. We performed longitudinal and survival analyses to compare outcomes in MM and MZ subjects with COPD over time. MEASUREMENTS AND MAIN RESULTS: We included 290 MZ subjects with COPD and 6,184 MM subjects with COPD across the three studies. MZ subjects had a lower FEV(1)% predicted and greater quantitative emphysema on chest computed tomography scans compared with MM subjects. In a meta-analysis, the FEV(1) was 3.9% lower (95% confidence interval [CI], −6.55% to −1.26%) and emphysema (the percentage of lung attenuation areas

Background Chronic obstructive pulmonary disease (COPD) and idiopathic pulmonary fibrosis (IPF) are characterized by shared exposures and clinical features, but distinct genetic and pathologic features exist. These features have not been well-studied using large-scale gene expression datasets. We hypothesized that there are divergent gene, pathway, and cellular signatures between COPD and IPF. Methods We performed RNA-sequencing on lung tissues from individuals with IPF (n = 231) and COPD (n = 377) compared to control (n = 267), defined as individuals with normal spirometry. We grouped the overlapping differential expression gene sets based on direction of expression and examined the resultant sets for genes of interest, pathway enrichment, and cell composition. Using gene set variation analysis, we validated the overlap group gene sets in independent COPD and IPF data sets. Results We found 5010 genes differentially expressed between COPD and control, and 11,454 genes differentially expressed between IPF and control (1% false discovery rate). 3846 genes overlapped between IPF and COPD. Several pathways were enriched for genes upregulated in COPD and downregulated in IPF; however, no pathways were enriched for genes downregulated in COPD and upregulated in IPF. There were many myeloid cell genes with increased expression in COPD but decreased in IPF. We found that the genes upregulated in COPD but downregulated in IPF were associated with lower lung function in the independent validation cohorts. Conclusions We identified a divergent gene expression signature between COPD and IPF, with increased expression in COPD and decreased in IPF. This signature is associated with worse lung function in both COPD and IPF.

BackgroundBody composition measures, specifically low weight or reduced muscle mass, are associated with mortality in COPD, but the effect of longitudinal body composition changes is undefined.Research questionIs the longitudinal loss of fat-free mass (FFM) associated with increased mortality, including in those with initially normal or elevated body composition metrics?Study design and methodsParticipants with complete data for at least one visit in the COPDGene study (n= 9,268) and the ECLIPSE study (n= 1,760) were included and monitored for 12 and 8 years, respectively. Pectoralis muscle area (PMA) was derived from thoracic CT scans and used as a proxy for FFM. A longitudinal mixed submodel for PMA and a Cox proportional hazards submodel for survival were fitted on a joint distribution, using a shared random intercept parameter and Markov chain Monte Carlo parameter estimation.ResultsBoth cohorts demonstrated a left-shifted distribution of baseline FFM, not reflected in BMI, and an increase in all-cause mortality risk associated with longitudinal loss of PMA. For each 1-cm2 PMA loss, mortality increased 3.1%(95%CI, 2.4%-3.7%; P< .001) in COPDGene, and 2.4%(95%CI, 0.9%-4.0%; P< .001) in ECLIPSE. Increased mortality risk was independent of enrollment values for BMI and disease severity [BODE (body mass, airflow obstruction, dyspnea, and exercise capacity) index quartiles] and was significant even in participants with initially greater than average PMA.InterpretationLongitudinal loss of PMA is associated with increased all-cause mortality, regardless of BMI or initial muscle mass. Consideration of novel screening tests and further research into mechanisms contributing to muscle decline may improve risk stratification and identify novel therapeutic targets in ever smokers.

IMPORTANCE: Thrombotic events are commonly reported in critically ill patients with COVID-19. Limited data exist to guide the intensity of antithrombotic prophylaxis. OBJECTIVE: To evaluate the effects of intermediate-dose vs standard-dose prophylactic anticoagulation among patients with COVID-19 admitted to the intensive care unit (ICU). DESIGN, SETTING, AND PARTICIPANTS: Multicenter randomized trial with a 2 × 2 factorial design performed in 10 academic centers in Iran comparing intermediate-dose vs standard-dose prophylactic anticoagulation (first hypothesis) and statin therapy vs matching placebo (second hypothesis; not reported in this article) among adult patients admitted to the ICU with COVID-19. Patients were recruited between July 29, 2020, and November 19, 2020. The final follow-up date for the 30-day primary outcome was December 19, 2020. INTERVENTIONS: Intermediate-dose (enoxaparin, 1 mg/kg daily) (n = 276) vs standard prophylactic anticoagulation (enoxaparin, 40 mg daily) (n = 286), with modification according to body weight and creatinine clearance. The assigned treatments were planned to be continued until completion of 30-day follow-up. MAIN OUTCOMES AND MEASURES: The primary efficacy outcome was a composite of venous or arterial thrombosis, treatment with extracorporeal membrane oxygenation, or mortality within 30 days, assessed in randomized patients who met the eligibility criteria and received at least 1 dose of the assigned treatment. Prespecified safety outcomes included major bleeding according to the Bleeding Academic Research Consortium (type 3 or 5 definition), powered for noninferiority (a noninferiority margin of 1.8 based on odds ratio), and severe thrombocytopenia (platelet count .99). Severe thrombocytopenia occurred only in patients assigned to the intermediate-dose group (6 vs 0 patients; risk difference, 2.2% [95% CI, 0.4%-3.8%]; P = .01). CONCLUSIONS AND RELEVANCE: Among patients admitted to the ICU with COVID-19, intermediate-dose prophylactic anticoagulation, compared with standard-dose prophylactic anticoagulation, did not result in a significant difference in the primary outcome of a composite of adjudicated venous or arterial thrombosis, treatment with extracorporeal membrane oxygenation, or mortality within 30 days. These results do not support the routine empirical use of intermediate-dose prophylactic anticoagulation in unselected patients admitted to the ICU with COVID-19. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04486508

ImportanceRisk to airflow limitation and Chronic Obstructive Pulmonary Disease (COPD) is influenced by combinations of cigarette smoking and genetic susceptibility, yet it remains unclear whether gene-by-smoking interactions contribute to quantitative measures of lung function.ObjectiveDetermine whether smoking modifies the effect of a polygenic risk score’s (PRS’s) association with reduced lung function.DesignUnited Kingdom (UK) Biobank prospective cohort study.SettingPopulation cohort.ParticipantsUK citizens of European ancestry aged 40-69 years, with genetic and spirometry data passing quality control metrics.ExposuresPRS, self-reported pack-years of smoking, ever-versus never-smoking status, and current-versus former-/never-smoking status.Main Outcomes and MeasuresForced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC). We tested for interactions with models including the main effects of PRS, different smoking variables, and their cross-product term(s). We also compared the effects of pack-years of smoking on FEV1/FVC for those in the highest versus lowest decile of predicted genetic risk for low lung function.ResultsWe included 319,730 individuals (24,915 with moderate-to-severe COPD). The PRS and pack-years were significantly associated with lower FEV1/FVC, as was the interaction term (β [interaction] = −0.0028 [95% CI: −0.0029, −0.0026]; all p < 0.0001). A stepwise increment in estimated effect sizes for these interaction terms was observed per 10 pack-years of smoking exposure (all p < 0.0001). There was evidence of significant interaction between PRS with ever/never smoking status (β [interaction] = −0.0064 [95% CI: −0.0068, −0.0060]) and current/not-current smoking (β [interaction] = −0.0091 [95% CI: −0.0097, −0.0084]). For any given level of pack-years of smoking exposure, FEV1/FVC was significantly lower for individuals in the tenth compared to the first decile of genetic risk (p < 0.0001). For every 20 pack-years of smoking, those in the top compared to the bottom decile of genetic risk showed nearly a twofold reduction in FEV1/FVC.Conclusions and RelevanceCOPD is characterized by diminished lung function, and our analyses suggest there is substantial interaction between genome-wide PRS and smoking exposures. While smoking has negative effects on lung function across all genetic risk categories, effects of smoking are highest in those with higher predicted genetic risk.Key PointsQuestionDoes cigarette smoking modify the magnitude of genetic effects on forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC)?FindingsFEV1/FVC is influenced by PRS-by-smoking interactions. Smoking was detrimental across all categories of predicted genetic risk, though it was worse for those with highest predicted genetic risks. For every reported 20 pack-years of reported smoking, individuals in the top compared to the bottom decile of genetic risk showed nearly twice the reduction in FEV1/FVC.MeaningElucidating mechanisms for the interaction between smoking and genetic risk could yield greater insight into the pathogenesis of chronic obstructive pulmonary disease (COPD).

Background Prognostic tools are required to guide clinical decision-making in COVID-19. Methods We studied the relationship between the ratio of interleukin (IL)-6 to IL-10 and clinical outcome in 80 patients hospitalized for COVID-19, and created a simple 5-point linear score predictor of clinical outcome, the Dublin-Boston score. Clinical outcome was analysed as a three-level ordinal variable (“Improved”, “Unchanged”, or “Declined”). For both IL-6:IL-10 ratio and IL-6 alone, we associated clinical outcome with a) baseline biomarker levels, b) change in biomarker level from day 0 to day 2, c) change in biomarker from day 0 to day 4, and d) slope of biomarker change throughout the study. The associations between ordinal clinical outcome and each of the different predictors were performed with proportional odds logistic regression. Associations were run both “unadjusted” and adjusted for age and sex. Nested cross-validation was used to identify the model for incorporation into the Dublin-Boston score. Findings The 4-day change in IL-6:IL-10 ratio was chosen to derive the Dublin-Boston score. Each 1 point increase in the score was associated with a 5.6 times increased odds for a more severe outcome (OR 5.62, 95% CI -3.22–9.81, P = 1.2 × 10−9). Both the Dublin-Boston score and the 4-day change in IL-6:IL-10 significantly outperformed IL-6 alone in predicting clinical outcome at day 7. Interpretation The Dublin-Boston score is easily calculated and can be applied to a spectrum of hospitalized COVID-19 patients. More informed prognosis could help determine when to escalate care, institute or remove mechanical ventilation, or drive considerations for therapies. Funding Funding was received from the Elaine Galwey Research Fellowship, American Thoracic Society, National Institutes of Health and the Parker B Francis Research Opportunity Award.

Background: Risk factor identification is a proven strategy in advancing treatments and preventive therapy for many chronic conditions. Quantifying the impact of those risk factors on health outcomes can consolidate and focus efforts on individuals with specific high-risk profiles. Using multiple risk factors and longitudinal outcomes in 2 independent cohorts, we developed and validated a risk score model to predict mortality in current and former cigarette smokers. Methods: We obtained extensive data on current and former smokers from the COPD Genetic Epidemiology (COPDGene(®)) study at enrollment. Based on physician input and model goodness-of-fit measures, a subset of variables was selected to fit final Weibull survival models separately for men and women. Coefficients and predictors were translated into a point system, allowing for easy computation of mortality risk scores and probabilities. We then used the SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) cohort for external validation of our model. Results: Of 9867 COPDGene participants with standard baseline data, 17.6% died over 10 years of follow-up, and 9074 of these participants had the full set of baseline predictors (standard plus 6-minute walk distance and computed tomography variables) available for full model fits. The average age of participants in the cohort was 60 for both men and women, and the average predicted 10-year mortality risk was 18% for women and 25% for men. Model time-integrated area under the receiver operating characteristic curve statistics demonstrated good predictive model accuracy (0.797 average), validated in the external cohort (0.756 average). Risk of mortality was impacted most by 6-minute walk distance, forced expiratory volume in 1 second and age, for both men and women. Conclusions: Current and former smokers exhibited a wide range of mortality risk over a 10- year period. Our models can identify higher risk individuals who can be targeted for interventions to reduce risk of mortality, for participants with or without chronic obstructive pulmonary disease (COPD) using current Global initiative for chronic Obstructive Lung Disease (GOLD) criteria.

Background COPD is a leading cause of mortality. Research Question We hypothesized that applying machine learning to clinical and quantitative CT imaging features would improve mortality prediction in COPD. Study Design and Methods We selected 30 clinical, spirometric, and imaging features as inputs for a random survival forest. We used top features in a Cox regression to create a machine learning mortality prediction (MLMP) in COPD model and also assessed the performance of other statistical and machine learning models. We trained the models in subjects with moderate to severe COPD from a subset of subjects in Genetic Epidemiology of COPD (COPDGene) and tested prediction performance in the remainder of individuals with moderate to severe COPD in COPDGene and Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE). We compared our model with the BMI, airflow obstruction, dyspnea, exercise capacity (BODE) index; BODE modifications; and the age, dyspnea, and airflow obstruction index. Results We included 2,632 participants from COPDGene and 1,268 participants from ECLIPSE. The top predictors of mortality were 6-min walk distance, FEV1 % predicted, and age. The top imaging predictor was pulmonary artery-to-aorta ratio. The MLMP-COPD model resulted in a C index ≥ 0.7 in both COPDGene and ECLIPSE (6.4- and 7.2-year median follow-ups, respectively), significantly better than all tested mortality indexes (P Interpretation An MLMP-COPD model outperformed four existing models for predicting all-cause mortality across two COPD cohorts. Performance of machine learning was similar to that of traditional statistical methods. The model is available online at: https://cdnm.shinyapps.io/cgmortalityapp/.