Proteomic Risk Score of Increased Respiratory Susceptibility: A Multicohort Study

Abstract

Rationale: Accelerated decline in lung function is associated with incident chronic obstructive pulmonary disease (COPD), hospitalization, and death. However, identifying this trajectory with longitudinal spirometry measurements is challenging in clinical practice. Objectives: To determine whether a proteomic risk score trained on accelerated decline in lung function can assess the risk of future respiratory disease and mortality. Methods: In the Coronary Artery Risk Development in Young Adults Study, a population-based cohort starting in young adulthood, longitudinal measurements of FEV₁ percent predicted (up to six time points over 30 yr) were used to identify accelerated and normal decline trajectories. Protein aptamers associated with an accelerated decline trajectory were identified with multivariable logistic regression followed by LASSO (least absolute shrinkage and selection operator) regression. The proteomic respiratory susceptibility score was derived on the basis of these circulating proteins and applied to the U.K. Biobank (UKBB) and COPDGene studies to examine associations with future respiratory morbidity and mortality. Measurements and Main Results: Higher susceptibility score was independently associated with all-cause mortality (UKBB hazard ratio [HR], 1.56; 95% confidence interval [CI], 1.50-1.61; COPDGene HR, 1.75 95% CI, 1.63-1.88), respiratory mortality (UKBB HR, 2.39; 95% CI, 2.16-2.64; COPDGene HR, 1.81; 95% CI, 1.32-2.47), incident COPD (UKBB HR, 1.84; 95% CI, 1.71-1.98), incident respiratory exacerbation (COPDGene odds ratio, 1.10; 95% CI, 1.02-1.19), and incident exacerbation requiring hospitalization (COPDGene OR, 1.17; 95% CI, 1.08-1.27). Conclusions: A proteomic signature of increased respiratory susceptibility identifies people at risk of respiratory death, incident COPD, and respiratory exacerbations. This susceptibility score is composed of proteins with well-known and novel associations with lung health and holds promise for the early detection of lung disease without requiring years of spirometry measurements.

Keywords: chronic obstructive pulmonary disease; lung function trajectories; lung health; population health; proteomics.

Figure 1.

Study design and timeline. Top: In the CARDIA cohort, we identified participants with normal decline (n = 2,332) and accelerated decline (n = 138) in lung function trajectories. These trajectories were adapted from previously developed and published trajectories (7) based on up to six measurements of FEV₁ percent predicted taken at Years 0, 2, 5, 10, 20, and 30 (mean ages, 25, 27, 30, 35, 45, and 55 yr). Plasma samples drawn at Year 25 (mean age, 50 yr) were analyzed for large-scale protein identification (proteomics). We then examined which circulating proteins were associated with an accelerated decline in FEV₁ trajectory, independent of cross-sectional FEV₁ at Year 20. We used these proteins to derive the proteomic “respiratory susceptibility score.” Bottom: We applied the respiratory susceptibility score to the U.K. Biobank and COPDGene cohort studies. Plasma samples drawn at the baseline visit in U.K. Biobank and the Year 5 visit (visit 2) in COPDGene were analyzed for the proteins in the susceptibility score. We examined the association between susceptibility score and incident chronic obstructive pulmonary disease, respiratory exacerbations, respiratory death, and all-cause death. The median follow-up time for all-cause death was 13.7 years (interquartile range, 12.0–14.5) in U.K. Biobank and 6.5 years (interquartile range, 4.9–7.5) in COPDGene. Figure created with BioRender.com.

Figure 2.

Proteins in the susceptibility score and their function and/or associations with lung health and disease, ranked by lung-specific gene expression. Hierarchical clustering was generated using the Genotype-Tissue Expression portal based on lung-specific gene expression measured in median transcripts per million. Least absolute shrinkage and selection operator (LASSO) directionality refers to the direction of their association with accelerated decline lung function trajectory in the LASSO model. Protein function data were obtained from the UniProt database unless indicated by reference numbers (–74).

Figure 3.

Mortality, incident COPD, and incident respiratory exacerbation by quartile of proteomic respiratory susceptibility score. (A) Adjusted hazard ratio (HR) for all-cause death and respiratory death ascertained in U.K. Biobank (UKBB) and COPDGene. (B) Adjusted HR for incident chronic obstructive pulmonary disease (COPD) in UKBB. (C) Adjusted odds ratio for one or more exacerbations and one or more severe exacerbations. All analyses were adjusted for age, sex, self-identified race, body mass index (BMI), smoking status, and pack-years at the time of proteomic measurement. In COPDGene, additional adjustment was made for self-reported asthma, post-bronchodilator FEV₁ percent predicted, and income. UKBB analyses were adjusted for self-report of current respiratory disease (COPD, emphysema, chronic bronchitis, asthma, or respiratory failure) and Townsend deprivation index. The Townsend deprivation index estimates deprivation within a census area and comprises four variables: unemployment, non–car ownership, non–home ownership, and household overcrowding. Analyses in COPDGene were additionally adjusted for platelet count and white blood cell count on the basis of prior internal quality control. CI = confidence interval.

Figure 4.

Cumulative incidence plots of all-cause mortality by quartile of proteomic respiratory susceptibility score. Unadjusted cumulative incidence of all-cause death by quartile of proteomic susceptibility score in the U.K. Biobank (top) and COPDGene (bottom) cohorts. Shaded areas around each line represent the 95% confidence interval.