Association Between Interstitial Lung Abnormalities and All-Cause Mortality.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files. This article is open access.Interstitial lung abnormalities have been associated with lower 6-minute walk distance, diffusion capacity for carbon monoxide, and total lung capacity. However, to our knowledge, an association with mortality has not been previously investigated.To investigate whether interstitial lung abnormalities are associated with increased mortality.Prospective cohort studies of 2633 participants from the FHS (Framingham Heart Study; computed tomographic [CT] scans obtained September 2008-March 2011), 5320 from the AGES-Reykjavik Study (Age Gene/Environment Susceptibility; recruited January 2002-February 2006), 2068 from the COPDGene Study (Chronic Obstructive Pulmonary Disease; recruited November 2007-April 2010), and 1670 from ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints; between December 2005-December 2006).Interstitial lung abnormality status as determined by chest CT evaluation.All-cause mortality over an approximate 3- to 9-year median follow-up time. Cause-of-death information was also examined in the AGES-Reykjavik cohort.Interstitial lung abnormalities were present in 177 (7%) of the 2633 participants from FHS, 378 (7%) of 5320 from AGES-Reykjavik, 156 (8%) of 2068 from COPDGene, and in 157 (9%) of 1670 from ECLIPSE. Over median follow-up times of approximately 3 to 9 years, there were more deaths (and a greater absolute rate of mortality) among participants with interstitial lung abnormalities when compared with those who did not have interstitial lung abnormalities in the following cohorts: 7% vs 1% in FHS (6% difference [95% CI, 2% to 10%]), 56% vs 33% in AGES-Reykjavik (23% difference [95% CI, 18% to 28%]), and 11% vs 5% in ECLIPSE (6% difference [95% CI, 1% to 11%]). After adjustment for covariates, interstitial lung abnormalities were associated with a higher risk of death in the FHS (hazard ratio [HR], 2.7 [95% CI, 1.1 to 6.5]; P = .03), AGES-Reykjavik (HR, 1.3 [95% CI, 1.2 to 1.4]; P < .001), COPDGene (HR, 1.8 [95% CI, 1.1 to 2.8]; P = .01), and ECLIPSE (HR, 1.4 [95% CI, 1.1 to 2.0]; P = .02) cohorts. In the AGES-Reykjavik cohort, the higher rate of mortality could be explained by a higher rate of death due to respiratory disease, specifically pulmonary fibrosis.In 4 separate research cohorts, interstitial lung abnormalities were associated with a greater risk of all-cause mortality. The clinical implications of this association require further investigation.National Institutes of Health (NIH) T32 HL007633 Icelandic Research Fund 141513-051 Landspitali Scientific Fund A-2015-030 National Cancer Institute grant 1K23CA157631 NIH K08 HL097029 R01 HL113264 R21 HL119902 K25 HL104085 R01 HL116931 R01 HL116473 K01 HL118714 R01 HL089897 R01 HL089856 N01-AG-1-2100 HHSN27120120022C P01 HL105339 P01 HL114501 R01 HL107246 R01 HL122464 R01 HL111024 National Heart, Lung, and Blood Institute's Framingham Heart Study contract N01-HC-2519.5 GlaxoSmithKline NCT00292552 5C0104960 National Institute on Aging (NIA) grant 27120120022C NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association) Althingi (the Icelandic Parliament) NIA 27120120022

Chronic obstructive pulmonary disease and related phenotypes: polygenic risk scores in population-based and case-control cohorts

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 <0·7 and FEV1 <80% of predicted). Associations were tested using logistic regression models, adjusting for age, sex, height, smoking pack-years, and principal components of genetic ancestry. We assessed predictive performance of models by area under the curve. In a subset of studies, we also studied quantitative and qualitative CT imaging phenotypes that reflect parenchymal and airway pathology, and patterns of reduced lung growth. Findings The polygenic risk score was associated with COPD in European (odds ratio [OR] per SD 1·81 [95% CI 1·74–1·88] and non-European (1·42 [1·34–1·51]) populations. Compared with the first decile, the tenth decile of the polygenic risk score was associated with COPD, with an OR of 7·99 (6·56–9·72) in European ancestry and 4·83 (3·45–6·77) in non-European ancestry cohorts. The polygenic risk score was superior to previously described genetic risk scores and, when combined with clinical risk factors (ie, age, sex, and smoking pack-years), showed improved prediction for COPD compared with a model comprising clinical risk factors alone (AUC 0·80 [0·79–0·81] vs 0·76 [0·75–0·76]). The polygenic risk score was associated with CT imaging phenotypes, including wall area percent, quantitative and qualitative measures of emphysema, local histogram emphysema patterns, and destructive emphysema subtypes. The polygenic risk score was associated with a reduced lung growth pattern. Interpretation A risk score comprised of genetic variants can identify a small subset of individuals at markedly increased risk for moderate-to-severe COPD, emphysema subtyp

Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p 10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group

Quantitative CT metrics are associated with longitudinal lung function decline and future asthma exacerbations: Results from SARP-3

BackgroundCurrently, there is limited knowledge regarding which imaging assessments of asthma are associated with accelerated longitudinal decline in lung function.ObjectivesWe aimed to assess whether quantitative computed tomography (qCT) metrics are associated with longitudinal decline in lung function and morbidity in asthma.MethodsWe analyzed 205 qCT scans of adult patients with asthma and calculated baseline markers of airway remodeling, lung density, and pointwise regional change in lung volume (Jacobian measures) for each participant. Using multivariable regression models, we then assessed the association of qCT measurements with the outcomes of future change in lung function, future exacerbation rate, and changes in validated measurements of morbidity.ResultsGreater baseline wall area percent (β&nbsp;= -0.15 [95% CI&nbsp;= -0.26 to -0.05]; P&nbsp;&lt; .01), hyperinflation percent (β&nbsp;= -0.25 [95% CI&nbsp;= -0.41 to -0.09]; P &lt; .01), and Jacobian gradient measurements (cranial-caudal β&nbsp;= 10.64 [95% CI&nbsp;= 3.79-17.49]; P&nbsp;&lt; .01; posterior-anterior β&nbsp;= -9.14, [95% CI&nbsp;= -15.49 to -2.78]; P&nbsp;&lt; .01) were associated with more severe future lung function decline. Additionally, greater wall area percent (rate ratio&nbsp;= 1.06 [95% CI&nbsp;= 1.01-1.10]; P&nbsp;= .02) and air trapping percent (rate ratio&nbsp;=1.01 [95% CI&nbsp;= 1.00-1.02]; P&nbsp;= .03), as well as lower decline in the Jacobian determinant mean (rate ratio&nbsp;= 0.58 [95% CI&nbsp;= 0.41-0.82]; P&nbsp;&lt; .01) and Jacobian determinant standard deviation (rate ratio&nbsp;= 0.52 [95% CI&nbsp;= 0.32-0.85]; P&nbsp;= .01), were associated with a greater rate of future exacerbations. However, imaging metrics were not associated with clinically meaningful changes in scores on validated asthma morbidity questionnaires.ConclusionsBaseline qCT measures of more severe airway remodeling, more small airway disease and hyperinflation, and&nbsp;less pointwise regional change in lung volumes were associated with future lung function decline and asthma exacerbations

Longitudinal Association Between Muscle Loss and Mortality in Ever Smokers.

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&nbsp;= 9,268) and the ECLIPSE study (n&nbsp;= 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%&nbsp;(95%&nbsp;CI, 2.4%-3.7%; P&nbsp;&lt; .001) in COPDGene, and 2.4%&nbsp;(95%&nbsp;CI, 0.9%-4.0%; P&nbsp;&lt; .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

Quantitative CT Characteristics of Cluster Phenotypes in the Severe Asthma Research Program Cohorts.

Background Clustering key clinical characteristics of participants in the Severe Asthma Research Program (SARP), a large, multicenter prospective observational study of patients with asthma and healthy controls, has led to the identification of novel asthma phenotypes. Purpose To determine whether quantitative CT (qCT) could help distinguish between clinical asthma phenotypes. Materials and Methods A retrospective cross-sectional analysis was conducted with the use of qCT images (maximal bronchodilation at total lung capacity [TLC], or inspiration, and functional residual capacity [FRC], or expiration) from the cluster phenotypes of SARP participants (cluster 1: minimal disease; cluster 2: mild, reversible; cluster 3: obese asthma; cluster 4: severe, reversible; cluster 5: severe, irreversible) enrolled between September 2001 and December 2015. Airway morphometry was performed along standard paths (RB1, RB4, RB10, LB1, and LB10). Corresponding voxels from TLC and FRC images were mapped with use of deformable image registration to characterize disease probability maps (DPMs) of functional small airway disease (fSAD), voxel-level volume changes (Jacobian), and isotropy (anisotropic deformation index [ADI]). The association between cluster assignment and qCT measures was evaluated using linear mixed models. Results A total of 455 participants were evaluated with cluster assignments and CT (mean age ± SD, 42.1 years ± 14.7; 270 women). Airway morphometry had limited ability to help discern between clusters. DPM fSAD was highest in cluster 5 (cluster 1 in SARP III: 19.0% ± 20.6; cluster 2: 18.9% ± 13.3; cluster 3: 24.9% ± 13.1; cluster 4: 24.1% ± 8.4; cluster 5: 38.8% ± 14.4