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Rationale: Knowledge on biomarkers of interstitial lung disease is incomplete. Interstitial lung abnormalities (ILAs) are radiologic changes that may present in its early stages. Objectives: To uncover blood proteins associated with ILAs using large-scale proteomics methods. Methods: Data from two prospective cohort studies, the AGES-Reykjavik (Age, Gene/Environment Susceptibility-Reykjavik) study ( N  = 5,259) for biomarker discovery and the COPDGene (Genetic Epidemiology of COPD) study ( N  = 4,899) for replication, were used. Blood proteins were measured using DNA aptamers, targeting more than 4,700 protein analytes. The association of proteins with ILAs and ILA progression was assessed with regression modeling, as were associations with genetic risk factors. Adaptive Least Absolute Shrinkage and Selection Operator models were applied to bootstrap data samples to discover sets of proteins predictive of ILAs and their progression. Measurements and Main Results: Of 287 associations, SFTPB (surfactant protein B) (odds ratio [OR], 3.71 [95% confidence interval (CI), 3.20-4.30]; P  = 4.28 × 10 -67 ), SCGB3A1 (Secretoglobin family 3A member 1) (OR, 2.43 [95% CI, 2.13-2.77]; P  = 8.01 × 10 -40 ), and WFDC2 (WAP four-disulfide core domain protein 2) (OR, 2.42 [95% CI, 2.11-2.78]; P  = 4.01 × 10 -36 ) were most significantly associated with ILA in AGES-Reykjavik and were replicated in COPDGene. In AGES-Reykjavik, concentrations of SFTPB were associated with the rs35705950 MUC5B (mucin 5B) promoter polymorphism, and SFTPB and WFDC2 had the strongest associations with ILA progression. Multivariate models of ILAs in AGES-Reykjavik, ILAs in COPDGene, and ILA progression in AGES-Reykjavik had validated areas under the receiver operating characteristic curve of 0.880, 0.826, and 0.824, respectively. Conclusions: Novel, replicated associations of ILA, its progression, and genetic risk factors with numerous blood proteins are demonstrated as well as machine-learning-based models with favorable predictive potential. Several proteins are revealed as potential markers of early fibrotic lung disease.

Rationale: Interstitial lung abnormalities (ILA) are radiologic abnormalities on chest computed tomography scans that have been associated with an early or mild form of pulmonary fibrosis. Although ILA have been associated with radiologic progression, it is not known if specific imaging patterns are associated with progression or risk of mortality. Objectives: To determine the role of imaging patterns on the risk of death and ILA progression. Methods: ILA (and imaging pattern) were assessed in 5,320 participants from the AGES-Reykjavik Study, and ILA progression was assessed in 3,167 participants. Multivariable logistic regression was used to assess factors associated with ILA progression, and Cox proportional hazards models were used to assess time to mortality. Measurements and Main Results: Over 5 years, 327 (10%) had ILA on at least one computed tomography, and 1,435 (45%) did not have ILA on either computed tomography. Of those with ILA, 238 (73%) had imaging progression, whereas 89 (27%) had stable to improved imaging; increasing age and copies of MUC5B genotype were associated with imaging progression. The definite fibrosis pattern was associated with the highest risk of progression (odds ratio, 8.4; 95% confidence interval, 2.7-25; P  = 0.0003). Specific imaging patterns were also associated with an increased risk of death. After adjustment, both a probable usual interstitial pneumonia and usual interstitial pneumonia pattern were associated with an increased risk of death when compared with those indeterminate for usual interstitial pneumonia (hazard ratio, 1.7; 95% confidence interval, 1.2-2.4; P = 0.001; hazard ratio, 3.9; 95% confidence interval, 2.3-6.8; P  < 0.0001), respectively. Conclusions: In those with ILA, imaging patterns can be used to help predict who is at the greatest risk of progression and early death.