Associations of a plant-centered diet and lung function across early to mid-adulthood: The CARDIA Lung Study.

BACKGROUND: Lung function throughout adulthood predicts morbidity and mortality even among adults without chronic respiratory disease. Diet quality may represent a modifiable risk factor for lung function impairment later in life. We investigated associations between nutritionally-rich plant-centered diet and lung function across early and middle adulthood from the Coronary Artery Risk Development in Young Adults (CARDIA) Study. METHODS: Diet was assessed at baseline and years 7 and 20 of follow-up using the validated CARDIA diet history questionnaire. Plant-centered diet quality was scored using the validated A Priori Diet Quality Score (APDQS), which weights food groups to measure adherence to a nutritionally-rich plant-centered diet for 20 beneficially rated foods and 13 adversely rated foods. Scores were cumulatively averaged over follow-up and categorized into quintiles. The primary outcome was lung function decline, including forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC), measured at years 0, 2, 5, 10, 20, and 30. We estimated the association of APDQS with annual pulmonary function changes and cross-sectional differences in a repeated measures regression model, adjusting for clinically relevant covariates. RESULTS: The study included 3,787 Black and White men and women aged 18-30 in 1985-86 and followed for 30 years. In multivariable repeated measures regression models, individuals in the lowest APDQS quintile (poorest diet) had declines in FEV1 that were 1.6 ml/year greater than individuals in the highest quintile (35.0 vs. 33.4 ml/year, ß ± SE per 1 SD change APDQS 0.94 ± 0.36, p = 0.009). Additionally, declines in FVC were 2.4 ml/year greater in the lowest APDQS quintile than those in the highest quintile (37.0 vs 34.6 ml/year, ß ± SE per 1 SD change APDQS 1.71 ± 0.46, p < 0.001). The association was not different between never and ever smokers (pint = 0.07 for FVC and 0.32 for FEV1). In sensitivity analyses where current asthma diagnosis and cardiorespiratory fitness were further adjusted, results remained similar. Cross-sectional analysis at each exam year also showed significant differences in lung function according to diet after covariate adjustment. CONCLUSIONS: In this 30-year longitudinal cohort study, long-term adherence to a nutritionally-rich plant-centered diet was associated with cross-sectional differences in lung function as well as slower decline in lung function, highlighting diet quality as a potential treatable trait supporting long-term lung health.

Proteomics and Machine Learning in the Prediction and Explanation of Low Pectoralis Muscle Area.

Low muscle mass is associated with numerous adverse outcomes independent of other associated comorbid diseases. We aimed to predict and understand an individual's risk for developing low muscle mass using proteomics and machine learning. We identified 8 biomarkers associated with low pectoralis muscle area (PMA). We built 3 random forest classification models that used either clinical measures, feature selected biomarkers, or both to predict development of low PMA. The area under the receiver operating characteristic curve for each model was: clinical-only = 0.646, biomarker-only = 0.740, and combined = 0.744. We displayed the heterogenetic nature of an individual's risk for developing low PMA and identified 2 distinct subtypes of participants who developed low PMA. While additional validation is required, our methods for identifying and understanding individual and group risk for low muscle mass could be used to enable developments in the personalized prevention of low muscle mass.

Utility of peripheral protein biomarkers for the prediction of incident interstitial features: a multicentre retrospective cohort study.

INTRODUCTION/RATIONALE: Protein biomarkers may help enable the prediction of incident interstitial features on chest CT. METHODS: We identified which protein biomarkers in a cohort of smokers (COPDGene) differed between those with and without objectively measured interstitial features at baseline using a univariate screen (t-test false discovery rate, FDR p<0.001), and which of those were associated with interstitial features longitudinally (multivariable mixed effects model FDR p<0.05). To predict incident interstitial features, we trained four random forest classifiers in a two-thirds random subset of COPDGene: (1) imaging and demographic information, (2) univariate screen biomarkers, (3) multivariable confirmation biomarkers and (4) multivariable confirmation biomarkers available in a separate testing cohort (Pittsburgh Lung Screening Study (PLuSS)). We evaluated classifier performance in the remaining one-third of COPDGene, and, for the final model, also in PLuSS. RESULTS: In COPDGene, 1305 biomarkers were available and 20 differed between those with and without interstitial features at baseline. Of these, 11 were associated with feature progression over a mean of 5.5 years of follow-up, and of these 4 were available in PLuSS, (angiopoietin-2, matrix metalloproteinase 7, macrophage inflammatory protein 1 alpha) over a mean of 8.8 years of follow-up. The area under the curve (AUC) of classifiers using demographics and imaging features in COPDGene and PLuSS were 0.69 and 0.59, respectively. In COPDGene, the AUC of the univariate screen classifier was 0.78 and of the multivariable confirmation classifier was 0.76. The AUC of the final classifier in COPDGene was 0.75 and in PLuSS was 0.76. The outcome for all of the models was the development of incident interstitial features. CONCLUSIONS: Multiple novel and previously identified proteomic biomarkers are associated with interstitial features on chest CT and may enable the prediction of incident interstitial diseases such as idiopathic pulmonary fibrosis.

Can We Use Lung Function Thresholds and Respiratory Symptoms to Identify Pre-COPD? A Prospective, Population-based Cohort Study.

RATIONALE: The term 'pre-COPD' refers to individuals at high-risk of developing Chronic Obstructive Pulmonary Disease (COPD) who do not meet conventional spirometric criteria for airflow obstruction. New approaches to identifying these individuals are needed, particularly in younger populations. OBJECTIVE: To determine whether lung function thresholds and respiratory symptoms can be used to identify individuals at-risk of developing COPD. METHODS: The Tasmanian Longitudinal Health Study is a population-based cohort first studied in 1968 (age 7). Respiratory symptoms, pre- and post-bronchodilator (BD) spirometry, diffusing capacity and static lung volumes were measured on a subgroup at age 45, and incidence of COPD was assessed at age 53. For each lung function measure, z-scores were calculated using Global Lung Initiative references. The optimal threshold for best discrimination of COPD incidence was determined by the unweighted Youden Index. MEASUREMENTS AND MAIN RESULTS: Among 801 participants who did not have COPD at age 45, the optimal threshold for COPD incidence by age 53 was pre-BD FEV1/FVC z-score < -1.264, corresponding to the lowest 10th percentile. Those below this threshold had 36-fold increased risk of developing COPD over an eight-year follow-up period (RR 35.8, 95%CI 8.88 to 144), corresponding to a risk difference of +16.4% (95%CI 3.7-67.4). The sensitivity was 88% and specificity 87%. Positive and negative likelihood ratios were 6.79 and 0.14, respectively. Respiratory symptoms, post-BD spirometry, diffusing capacity and static lung volumes did not improve on the classification achieved by pre-BD FEV1/FVC alone. CONCLUSION: Our findings support the inclusion of pre-BD spirometry in the physiological definition of pre-COPD and indicate that pre-BD FEV1/FVC at the 10th percentile accurately identifies individuals at high-risk of developing COPD in community-based settings.

Proteomic Biomarkers of Quantitative Interstitial Abnormalities in COPDGene and CARDIA Lung Study.

Rationale: Quantitative interstitial abnormalities (QIA) are early measures of lung injury automatically detected on chest computed tomography (CT) scans. QIA is associated with impaired respiratory health and shares features with advanced lung diseases, but its biological underpinnings are not well understood. Objective: We analyzed high-throughput plasma proteomic panels within two multi-center cohorts to identify novel protein biomarkers of QIA. Methods: We measured the plasma proteomics of 4,383 participants in an older, ever-smoker cohort (Genetic Epidemiology of COPD, COPDGene) and 2,925 participants in a younger population cohort (Coronary Artery Disease Risk in Young Adults, CARDIA) with the SomaLogic SomaScan assays. We measured QIA using a local density histogram method. We assessed the associations between proteomics levels and QIA using multivariable linear regression models adjusted for age, sex, body mass index, smoking status, and study center (Benjamini-Hochberg False Discovery Rate p-value ≤0.05). Measurements and Main Results: 852 proteins were significantly associated with QIA in COPDGene and 185 in CARDIA. Of the 144 proteins that overlapped between COPDGene and CARDIA, all but one shared directionalities and magnitudes. These proteins were enriched for 49 Gene Ontology pathways, including Biological Processes in inflammatory response, cell adhesion, immune response, ERK1/2 regulation, and signaling; Cellular Components in extracellular regions; and Molecular Functions including calcium ion and heparin binding. Conclusions: We identified the proteomic biomarkers of QIA in an older, smoking population with higher prevalence of pulmonary disease and in a younger, healthier community cohort. These proteomics features may be markers of early precursors of advanced lung diseases.

Quantification of Emphysema Progression at CT Using Simultaneous Volume, Noise, and Bias Lung Density Correction.

Background CT attenuation is affected by lung volume, dosage, and scanner bias, leading to inaccurate emphysema progression measurements in multicenter studies. Purpose To develop and validate a method that simultaneously corrects volume, noise, and interscanner bias for lung density change estimation in emphysema progression at CT in a longitudinal multicenter study. Materials and Methods In this secondary analysis of the prospective Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study, lung function data were obtained from participants who completed baseline and 5-year follow-up visits from January 2008 to August 2017. CT emphysema progression was measured with volume-adjusted lung density (VALD) and compared with the joint volume-noise-bias-adjusted lung density (VNB-ALD). Reproducibility was studied under change of dosage protocol and scanner model with repeated acquisitions. Emphysema progression was visually scored in 102 randomly selected participants. A stratified analysis of clinical characteristics was performed that considered groups based on their combined lung density change measured by VALD and VNB-ALD. Results A total of 4954 COPDGene participants (mean age, 60 years ± 9 [SD]; 2511 male, 2443 female) were analyzed (1329 with repeated reduced-dose acquisition in the follow-up visit). Mean repeatability coefficients were 30 g/L ± 0.46 for VALD and 14 g/L ± 0.34 for VNB-ALD. VALD measurements showed no evidence of differences between nonprogressors and progressors (mean, -5.5 g/L ± 9.5 vs -8.6 g/L ± 9.6; P = .11), while VNB-ALD agreed with visual readings and showed a difference (mean, -0.67 g/L ± 4.8 vs -4.2 g/L ± 5.5; P < .001). Analysis of progression showed that VNB-ALD progressors had a greater decline in forced expiratory volume in 1 second (-42 mL per year vs -32 mL per year; Tukey-adjusted P = .002). Conclusion Simultaneously correcting volume, noise, and interscanner bias for lung density change estimation in emphysema progression at CT improved repeatability analyses and agreed with visual readings. It distinguished between progressors and nonprogressors and was associated with a greater decline in lung function metrics. Clinical trial registration no. NCT00608764 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Goo in this issue.

Dysanapsis is differentially related to lung function trajectories with distinct structural and functional patterns in COPD and variable risk for adverse outcomes.

Background: Abnormal lung function trajectories are associated with increased risk of chronic obstructive pulmonary disease (COPD) and premature mortality; several risk factors for following these trajectories have been identified. Airway under-sizing dysanapsis (small airway lumens relative to lung size), is associated with an increased risk for COPD. The relationship between dysanapsis and lung function trajectories at risk for adverse outcomes of COPD is largely unexplored. We test the hypothesis that dysanapsis differentially affects distinct lung function trajectories associated with adverse outcomes of COPD. Methods: To identify lung function trajectories, we applied Bayesian trajectory analysis to longitudinal FEV1 and FVC Z-scores in the COPDGene Study, an ongoing longitudinal study that collected baseline data from 2007 to 2012. To ensure clinical relevance, we selected trajectories based on risk stratification for all-cause mortality and prospective exacerbations of COPD (ECOPD). Dysanapsis was measured in baseline COPDGene CT scans as the airway lumen-to-lung volume (a/l) ratio. We compared a/l ratios between trajectories and evaluated their association with trajectory assignment, controlling for previously identified risk factors. We also assigned COPDGene participants for whom only baseline data is available to their most likely trajectory and repeated our analysis to further evaluate the relationship between trajectory assignment and a/l ratio measures. Findings: We identified seven trajectories: supranormal, reference, and five trajectories at increased risk for mortality and exacerbations. Three at-risk trajectories are characterized by varying degrees of concomitant FEV1 and FVC impairments and exhibit airway predominant COPD patterns as assessed by quantitative CT imaging. These trajectories have lower a/l ratio values and increased risk for mortality and ECOPD compared to the reference trajectory. Two at-risk trajectories are characterized by disparate levels of FEV1 and FVC impairment and exhibit mixed airway and emphysema COPD patterns on quantitative CT imaging. These trajectories have markedly lower a/l ratio values compared to both the reference trajectory and airway-predominant trajectories and are at greater risk for mortality and ECOPD compared to the airway-predominant trajectories. These findings were observed among the participants with baseline-only data as well. Interpretation: The degree of dysanapsis appears to portend patterns of progression leading to COPD. Assignment of individuals-including those without spirometric obstruction-to distinct trajectories is possible in a clinical setting and may influence management strategies. Strategies that combine CT-assessed dysanapsis together with spirometric measures of lung function and smoke exposure assessment are likely to further improve trajectory assignment accuracy, thereby improving early detection of those most at risk for adverse outcomes. Funding: United States National Institute of Health, COPD Foundation, and Brigham and Women's Hospital.

Implications of Mean Pulmonary Arterial Wedge Pressure Trajectories in Pulmonary Arterial Hypertension.

Rationale: The mean pulmonary arterial wedge pressure (mPAWP) is the critical hemodynamic factor differentiating group 1 pulmonary arterial hypertension (PAH) from group 2 pulmonary hypertension associated with left heart disease. Despite the discrepancy between the mPAWP upper physiologic normal and current PAH definitions, the implications of the initial mPAWP for PAH clinical trajectory are poorly understood. Objectives: To model longitudinal mPAWP trajectories in PAH over 10 years and examine the clinical and hemodynamic factors associated with trajectory membership. Methods: Adult patients with PAH with two or more right heart catheterizations were identified from a multiinstitution healthcare system in eastern Massachusetts. mPAWP trajectories were constructed via group-based trajectory modeling. Feature selection was performed in least absolute shrinkage and selection operator regression. Logistic regression was used to assess associations between trajectory membership, baseline characteristics, and transplant-free survival. Measurements and Main Results: Among 301 patients with PAH, there were two distinct mPAWP trajectories, termed "mPAWP-high" (n = 71; 23.6%) and "mPAWP-low" (n = 230; 76.4%), based on the ultimate mPAWP value. Initial mPAWP clustered around median 12 mm Hg (interquartile range [IQR], 8-14 mm Hg) in the mPAWP-high and 9 mm Hg (IQR, 6-11 mm Hg) in the mPAWP-low trajectories (P < 0.001). After feature selection, initial mPAWP ⩾12 mm Hg predicted an mPAWP-high trajectory (odds ratio, 3.2; 95% confidence interval, 1.4-6.1; P = 0.0006). An mPAWP-high trajectory was associated with shorter transplant-free survival (vs. mPAWP-low, median, 7.8 vs. 11.3 yr; log-rank P = 0.017; age-adjusted P = 0.217). Conclusions: Over 10 years, the mPAWP followed two distinct trajectories, with 25% evolving into group 2 pulmonary hypertension physiology. Using routine baseline data, longitudinal mPAWP trajectory could be predicted accurately, with initial mPAWP ⩾12 mm Hg as one of the strongest predictors.

Rheumatoid arthritis, quantitative parenchymal lung features, and mortality among smokers.

OBJECTIVES: There have been limited investigations of the prevalence and mortality impact of quantitative computed tomography (QCT) parenchymal lung features in rheumatoid arthritis (RA). We examined the cross-sectional prevalence and mortality associations of QCT features, comparing RA and non-RA participants. METHODS: We identified participants with and without RA in COPDGene, a multicentre cohort study of current or former smokers. Using a k-nearest neighbor quantifier, high resolution CT chest scans were scored for percentage of normal lung, interstitial changes, and emphysema. We examined associations between QCT features and RA using multivariable linear regression. After dichotomizing participants at the 75th percentile for each QCT feature among non-RA participants, we investigated mortality associations by RA/non-RA status and quartile 4 vs quartiles 1-3 of QCT features using Cox regression. We assessed for statistical interactions between RA and QCT features. RESULTS: We identified 82 RA cases and 8820 non-RA comparators. In multivariable linear regression, RA was associated with higher percentage of interstitial changes (ß = 1.7 ± 0.5, p= 0.0008) but not emphysema (ß = 1.3 ± 1.7, p= 0.44). Participants with RA and >75th percentile of emphysema had significantly higher mortality than non-RA participants (HR 5.86, 95%CI 3.75-9.13) as well as RA participants (HR 5.56, 95%CI 2.71-11.38) with ≤75th percentile of emphysema. There were statistical interactions between RA and emphysema for mortality (multiplicative p= 0.014; attributable proportion 0.53, 95%CI 0.30-0.70). CONCLUSIONS: Using machine learning-derived QCT data in a cohort of smokers, RA was associated with higher percentage of interstitial changes. The combination of RA and emphysema conferred >5-fold higher mortality.

A Plant-Centered Diet is Inversely Associated with Radiographic Emphysema: Findings from the CARDIA Lung Study.

Chronic obstructive pulmonary disease (COPD) is a significant public health concern and intercepting the development of emphysema is vital for COPD prevention. Smokers are a high-risk population for emphysema with limited prevention strategies. We aimed to determine if adherence to a nutritionally rich plant-centered diet among young ever-smokers is associated with reduced risk of future radiographic emphysema. We studied participants from the Coronary Artery Risk Development in Young Adults (CARDIA) Lung Prospective Cohort Study who were 18-30 years old at enrollment and followed for 30 years. We analyzed 1,706 adults who reported current or former smoking by year 20. Repeated measures of diet history were used to calculate A Priori Diet Quality Scores (APDQS), and categorized into quintiles, with higher quintiles representing higher nutritionally rich plant-centered food intake. Emphysema was assessed at year 25 (n=1,351) by computed tomography (CT). Critical covariates were selected, acknowledging potential residual confounding. Emphysema was observed in 13.0% of the cohort, with a mean age of 50.4 ± 3.5 years. The prevalence of emphysema was 4.5% in the highest APDQS quintile (nutritionally rich), compared with 25.4% in the lowest quintile. After adjustment for multiple covariates, including smoking, greater adherence to a plant-centered diet was inversely associated with emphysema (highest vs lowest quintile odds ratio: 0.44, 95% CI 0.19-0.99, ptrend=0.008). To conclude, longitudinal adherence to a nutritionally rich plant-centered diet was associated with decreased risk of emphysema development in middle adulthood, warranting further examination of diet as a strategy for emphysema prevention in a high-risk smoking population.

Plasma metabolomics and quantitative interstitial abnormalities in ever-smokers.

BACKGROUND: Quantitative interstitial abnormalities (QIA) are an automated computed tomography (CT) finding of early parenchymal lung disease, associated with worse lung function, reduced exercise capacity, increased respiratory symptoms, and death. The metabolomic perturbations associated with QIA are not well known. We sought to identify plasma metabolites associated with QIA in smokers. We also sought to identify shared and differentiating metabolomics features between QIA and emphysema, another smoking-related advanced radiographic abnormality. METHODS: In 928 former and current smokers in the Genetic Epidemiology of COPD cohort, we measured QIA and emphysema using an automated local density histogram method and generated metabolite profiles from plasma samples using liquid chromatography-mass spectrometry (Metabolon). We assessed the associations between metabolite levels and QIA using multivariable linear regression models adjusted for age, sex, body mass index, smoking status, pack-years, and inhaled corticosteroid use, at a Benjamini-Hochberg False Discovery Rate p-value of ≤ 0.05. Using multinomial regression models adjusted for these covariates, we assessed the associations between metabolite levels and the following CT phenotypes: QIA-predominant, emphysema-predominant, combined-predominant, and neither- predominant. Pathway enrichment analyses were performed using MetaboAnalyst. RESULTS: We found 85 metabolites significantly associated with QIA, with overrepresentation of the nicotinate and nicotinamide, histidine, starch and sucrose, pyrimidine, phosphatidylcholine, lysophospholipid, and sphingomyelin pathways. These included metabolites involved in inflammation and immune response, extracellular matrix remodeling, surfactant, and muscle cachexia. There were 75 metabolites significantly different between QIA-predominant and emphysema-predominant phenotypes, with overrepresentation of the phosphatidylethanolamine, nicotinate and nicotinamide, aminoacyl-tRNA, arginine, proline, alanine, aspartate, and glutamate pathways. CONCLUSIONS: Metabolomic correlates may lend insight to the biologic perturbations and pathways that underlie clinically meaningful quantitative CT measurements like QIA in smokers.

Genome-wide association meta-analysis identifies 17 loci associated with nonalcoholic fatty liver disease.

Nonalcoholic fatty liver disease (NAFLD) is common and partially heritable and has no effective treatments. We carried out a genome-wide association study (GWAS) meta-analysis of imaging (n = 66,814) and diagnostic code (3,584 cases versus 621,081 controls) measured NAFLD across diverse ancestries. We identified NAFLD-associated variants at torsin family 1 member B (TOR1B), fat mass and obesity associated (FTO), cordon-bleu WH2 repeat protein like 1 (COBLL1)/growth factor receptor-bound protein 14 (GRB14), insulin receptor (INSR), sterol regulatory element-binding transcription factor 1 (SREBF1) and patatin-like phospholipase domain-containing protein 2 (PNPLA2), as well as validated NAFLD-associated variants at patatin-like phospholipase domain-containing protein 3 (PNPLA3), transmembrane 6 superfamily 2 (TM6SF2), apolipoprotein E (APOE), glucokinase regulator (GCKR), tribbles homolog 1 (TRIB1), glycerol-3-phosphate acyltransferase (GPAM), mitochondrial amidoxime-reducing component 1 (MARC1), microsomal triglyceride transfer protein large subunit (MTTP), alcohol dehydrogenase 1B (ADH1B), transmembrane channel like 4 (TMC4)/membrane-bound O-acyltransferase domain containing 7 (MBOAT7) and receptor-type tyrosine-protein phosphatase δ (PTPRD). Implicated genes highlight mitochondrial, cholesterol and de novo lipogenesis as causally contributing to NAFLD predisposition. Phenome-wide association study (PheWAS) analyses suggest at least seven subtypes of NAFLD. Individuals in the top 10% and 1% of genetic risk have a 2.5-fold to 6-fold increased risk of NAFLD, cirrhosis and hepatocellular carcinoma. These genetic variants identify subtypes of NAFLD, improve estimates of disease risk and can guide the development of targeted therapeutics.

"It's a cause I believe in": factors motivating participation and engagement in longitudinal, respiratory-focused research studies.

BACKGROUND: Key to the success of any prospective cohort study is the effective recruitment and retention of participants, but the specific factors that influence younger adults of the Millennial generation to participate in research are not well-understood. The objective of this qualitative study was to identify factors that motivated participation and engagement in longitudinal research studies focused on respiratory health among a diverse group of young adults. METHODS: We conducted qualitative, semi-structured interviews with 50 younger adult participants (aged 25-35 years) regarding factors influencing their participation in longitudinal research studies. Thematic analysis was used to develop, organize, and tabulate the frequency of key themes. In exploratory analyses, we examined for patterns in the distribution of key themes across racial, ethnic, or socioeconomic groups. RESULTS: Participants identified several key themes that affected their willingness to participate in longitudinal studies. These included the health-related benefits generated by research (both to the individual and to society at-large), factors related to the institution and study team conducting the research, concerns regarding unethical and/or unrepresentative study design, and barriers to participation in research. Certain factors may be more impactful to underrepresented groups, including concerns regarding data privacy and confidentiality. CONCLUSIONS: In this diverse group of younger adults, we identified specific factors that motivated participation and predicted high engagement in longitudinal research studies focused on respiratory health. Implementing and integrating these factors into study protocols may improve recruitment and retention, including among participants who are historically underrepresented in research.