The Proteomic Profile of Interstitial Lung Abnormalities

Abstract

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.

Keywords: biomarkers; idiopathic pulmonary fibrosis; interstitial lung abnormalities; interstitial lung disease; proteomics.

Figure 1.

The associations of single proteins with interstitial lung abnormalities (ILAs) at baseline and progression of ILAs. Shown in red circles are results from the AGES-Reykjavik (Age, Gene/Environment Susceptibility–Reykjavik) study. Results from COPDGene (Genetic Epidemiology of COPD) are shown in blue triangles. Models are (A) logistic regression models of a single protein with ILAs at baseline, and (B) progression of ILAs, adjusted for age, sex, pack-years, and smoking at study entry. Models in COPDGene are additionally adjusted for white blood cell count, platelet count, and study center. BPIFB1 = BPI fold containing family B member 1; CTSH = cathepsin H; GDF-15 = growth differentiation factor 15; SCGB3A1 = secretoglobin family 3A member 1; SFTPB = surfactant protein B; UBE2E1 = ubiquitin conjugating enzyme E2 E1; WFDC2 = WAP four-disulfide core domain protein 2.

Figure 2.

Multivariate logistic regression models of the association of proteins with interstitial lung abnormalities (ILAs) and ILA progression. (A) A model of the associations of the eight proteins selected for 200 adaptive Least Absolute Shrinkage and Selection Operator (LASSO) models with ILAs in the AGES-Reykjavik (Age, Gene/Environment Susceptibility–Reykjavik) cohort. (B) A model of the associations of the eight proteins selected for 200 adaptive LASSO models with ILA in the COPDGene (Genetic Epidemiology of COPD) cohort. (C) A model of the associations of the four proteins selected for 200 adaptive LASSO models with progression of ILA in the AGES-Reykjavik cohort. Models in AGES-Reykjavik are logistic regression models, adjusted for age, sex, pack-years, and smoking at study entry. The model in COPDGene is additionally adjusted for white blood cell count, platelet count, and study center. ADAM9 = ADAM metallopeptidase domain 9; ALPP = alkaline phosphatase, placental; ANXA9 = annexin A9; CBLN4 = cerebellin 4 precursor; CCL8 = C-C motif chemokine ligand 8; EMC1 = ER membrane protein complex subunit 1; SCGB3A1 = secretoglobin family 3A member 1; SFTPB = surfactant protein B; WFDC2 = WAP four-disulfide core domain protein 2; WFIKKN2 = WAP, Kazal, immunoglobulin, Kunitz and NTR domain-containing protein 2.

Figure 3.

Receiver operating characteristic (ROC) curves of models of the associations of proteins with interstitial lung abnormalities (ILAs) at baseline and ILA progression. ROC curves for the specified logistic regression models. (A) Curves for models in the AGES-Reykjavik (Age, Gene/Environment Susceptibility–Reykjavik) cohort with ILAs at baseline as the outcome. (B) Curves for models in the COPDGene (Genetic Epidemiology of COPD) cohort with ILAs at baseline as the outcome. (C) Curves for models in the AGES-Reykjavik cohort with progression of ILAs as the outcome. Baseline: A model with age, sex, pack-years, and smoking at study entry, for which all other models are adjusted. Names of proteins refer to single-protein models of that protein with ILAs at baseline or at progression. Eight proteins (A and B): A model with proteins used in 200 adaptive Least Absolute Shrinkage and Selection Operator (LASSO) models of ILAs at baseline. Four proteins (C): A model with proteins used in 200 adaptive LASSO models of ILA progression. AUC = area under curve; SCGB3A1 = secretoglobin family 3A member 1; SFTPB = surfactant protein B; WFDC2 = WAP four-disulfide core domain protein 2; vAUC = area under curve, validated with 200-fold resampling.