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Background: Diagnostic delays are common in patients with interstitial lung disease (ILD). A substantial percentage of patients experience a diagnostic delay in the primary care setting, but the factors underpinning this observation remain unclear. In this multi-center investigation, we assessed ILD reporting on diagnostic test interpretation and its association with subsequent pulmonology referral by a primary care physician (PCP).Methods: A retrospective cohort analysis of patients referred to the ILD programs at UC-Davis and University of Chicago by a PCP within each institution was performed. Computed tomography (CT) of the chest and abdomen and pulmonary function test (PFT) were reviewed to identify the date ILD features were first present and determine the time from diagnostic test to pulmonology referral. The association between ILD reporting on diagnostic test interpretation and pulmonology referral was assessed, as was the association between years of diagnostic delay and changes in fibrotic features on longitudinal chest CT.Results: One hundred and forty-six patients were included in the final analysis. Prior to pulmonology referral, 66% (n = 97) of patients underwent chest CT, 15% (n = 21) underwent PFT and 15% (n = 21) underwent abdominal CT. ILD features were reported on 84, 62 and 33% of chest CT, PFT and abdominal CT interpretations, respectively. ILD reporting was associated with shorter time to pulmonology referral when undergoing chest CT (1.3 vs 15.1 months, respectively; p = 0.02), but not PFT or abdominal CT. ILD reporting was associated with increased likelihood of pulmonology referral within 6 months of diagnostic test when undergoing chest CT (rate ratio 2.17, 95% CI 1.03-4.56; p = 0.04), but not PFT or abdominal CT. Each year of diagnostic delay was associated with a 1.8% increase in percent fibrosis on chest CT. Patients with documented dyspnea had shorter time to chest CT acquisition and pulmonology referral than patients with documented cough and lung crackles.Conclusions: Determinants of ILD diagnostic delays in the primary care setting include underreporting of ILD features on diagnostic testing and prolonged time to pulmonology referral even when ILD is reported. Interventions to modulate these factors may reduce ILD diagnostic delays in the primary care setting. [ABSTRACT FROM AUTHOR]

Rationale: Rare genetic variants in telomere-related genes have been identified in familial, idiopathic, and rheumatoid arthritis-associated pulmonary fibrosis. Short peripheral blood leukocyte (PBL) telomere length predicts poor outcomes in chronic hypersensitivity pneumonitis (CHP).Objectives: Determine the prevalence and clinical relevance of rare protein-altering variants in telomere-related genes in patients with CHP.Methods: Next-generation sequences from two CHP cohorts were analyzed to identify variants in TERT (telomerase reverse transcriptase), TERC (telomerase RNA component), DKC1 (dyskerin pseudouridine synthase 1), RTEL1 (regulator of telomere elongation helicase 1), PARN (poly[A]-specific RNase), and TINF2 (TERF1-interacting nuclear factor 2). To qualify, variants were required to have a minor allele frequency less than 0.005 and be predicted to be damaging to protein function. Variant status (binary variable) was used in statistical association tests, including Cox proportional hazard models for transplant-free survival. PBL telomere length was measured using quantitative PCR.Measurements and Main Results: Qualifying variants were identified in 16 of 144 patients (11.1%; 95% confidence interval [CI], 6.5-17.4) in the discovery cohort and 17 of 209 patients (8.1%; 95% CI, 4.8-12.7) in the replication cohort. Age- and ancestry-adjusted PBL telomere length was significantly shorter in the presence of a variant in both cohorts (discovery: -561 bp; 95% CI, -933 to -190; P = 0.003; replication: -612 bp; 95% CI, -870 to -354; P = 5.30 × 10-6). Variant status was significantly associated with transplant-free survival in both cohorts (discovery: age-, sex-, and ancestry-adjusted hazard ratio, 3.73; 95% CI, 1.92-7.28; P = 0.0001; replication: hazard ratio, 2.72; 95% CI, 1.26-5.88; P = 0.011).Conclusions: A substantial proportion of patients diagnosed with CHP have rare, protein-altering variants in telomere-related genes, which are associated with short peripheral blood telomere length and significantly reduced transplant-free survival. [ABSTRACT FROM AUTHOR]

Connective tissue diseases (CTD) comprise a group of autoimmune diseases that can affect multiple organs in the body including the lungs. The most common form of pulmonary involvement is interstitial lung disease (ILD). CTD-associated ILD (CTD-ILD) can take one of several courses including nonprogressive, chronically progressive, or rapidly progressive. Chronically and rapidly progressive patterns are associated with increased mortality. Limited randomized controlled trial data are available for treatment of CTD-ILD, with most data coming from systemic sclerosis-related ILD. The current first-line treatment for all CTD-ILD is immunosuppression with consideration of antifibrotics, stem cell transplant, and lung transplant in progressive disease. In this article, we review data for ILD treatment options in systemic sclerosis, rheumatoid arthritis, myositis, and primary Sjögren's syndrome-related ILDs. [ABSTRACT FROM AUTHOR]

The article presents the discussion on Idiopathic pulmonary fibrosis (IPF) being an inexorably progressive interstitial lung disease (ILD) of unknown origin with limited therapeutic options. Topics include understanding of disease etiology hindering prevention and development of novel pharmacotherapies; and proteomic investigation showing cytokeratin 19 predicting disease progression across diverse ILD subtypes.

Background: The course of disease for patients with idiopathic pulmonary fibrosis (IPF) is highly heterogeneous. Prognostic models rely on demographic and clinical characteristics and are not reproducible. Integrating data from genomic analyses may identify novel prognostic models and provide mechanistic insights into IPF.Methods: Total RNA of peripheral blood mononuclear cells was subjected to microarray profiling in a training (45 IPF individuals) and two independent validation cohorts (21 IPF/10 controls, and 75 IPF individuals, respectively). To identify a gene set predictive of IPF prognosis, we incorporated genomic, clinical, and outcome data from the training cohort. Predictor genes were selected if all the following criteria were met: 1) Present in a gene co-expression module from Weighted Gene Co-expression Network Analysis (WGCNA) that correlated with pulmonary function (p < 0.05); 2) Differentially expressed between observed "good" vs. "poor" prognosis with fold change (FC) >1.5 and false discovery rate (FDR) < 2%; and 3) Predictive of mortality (p < 0.05) in univariate Cox regression analysis. "Survival risk group prediction" was adopted to construct a functional genomic model that used the IPF prognostic predictor gene set to derive a prognostic index (PI) for each patient into either high or low risk for survival outcomes. Prediction accuracy was assessed with a repeated 10-fold cross-validation algorithm and independently assessed in two validation cohorts through multivariate Cox regression survival analysis.Results: A set of 118 IPF prognostic predictor genes was used to derive the functional genomic model and PI. In the training cohort, high-risk IPF patients predicted by PI had significantly shorter survival compared to those labeled as low-risk patients (log rank p < 0.001). The prediction accuracy was further validated in two independent cohorts (log rank p < 0.001 and 0.002). Functional pathway analysis revealed that the canonical pathways enriched with the IPF prognostic predictor gene set were involved in T-cell biology, including iCOS, T-cell receptor, and CD28 signaling.Conclusions: Using supervised and unsupervised analyses, we identified a set of IPF prognostic predictor genes and derived a functional genomic model that predicted high and low-risk IPF patients with high accuracy. This genomic model may complement current prognostic tools to deliver more personalized care for IPF patients. [ABSTRACT FROM AUTHOR]

Background: Gastroesophageal reflux disease (GERD) is a common comorbidity in patients with interstitial lung disease (ILD). We built and validated a model using the national inpatient sample (NIS) database to assess the contributory role of GERD in ILD-related hospitalizations mortality. Methods: In this retrospective analysis, we extracted ILD-related hospitalizations data between 2007 and 2019 from the NIS database. Univariable logistic regression was used for predictor selection. Data were split into the training and validation cohorts (0.6 and 0.4, respectively). We used decision tree analysis (classification and regression tree, CART) to create a predictive model to explore the role of GERD in ILD-related hospitalizations mortality. Different metrics were used to evaluate our model. A bootstrap-based technique was implemented to balance our training data outcome to improve our model metrics in the validation cohort. We conducted a variance-based sensitivity analysis to evaluate GERD's importance in our model. Findings: The model had a sensitivity of 73.43%, specificity of 66.15%, precision of 0.27, negative predictive value (NPV) of 93.62%, accuracy of 67.2%, Matthews Correlation Coefficient (MCC) of 0.3, F1 score of 0.4, and area under the curve (AUC) for the receiver operating characteristic (ROC) curve of 0.76. GERD did not predict survival in our cohort. GERD contribution to the model was ranked the eleventh among twenty-nine variables included in this analysis (importance of 0.003, normalized importance of 5%). GERD was the best predictor in ILD-related hospitalizations who didn't receive mechanical ventilation. Interpretations: GERD is associated with mild ILD-related hospitalization. Our model-performance measures suggest overall an acceptable discrimination. Our model showed that GERD does not have a prognostic value in ILD-related hospitalization, indicating that GERD per se might not have any impact on mortality in hospitalized ILD patients. [ABSTRACT FROM AUTHOR]

Objectives: To determine if a quantitative imaging variable (vessel-related structures [VRS]) could identify subjects with a non-IPF diagnosis CT pattern who were highly likely to have UIP histologically. Methods: Subjects with a multidisciplinary diagnosis of interstitial lung disease including surgical lung biopsy and chest CT within 1 year of each other were included in the study. Non-contrast CT scans were analyzed using the Computer-Aided Lung Informatics for Pathology Evaluation and Rating (CALIPER) program, which quantifies the amount of various abnormal CT patterns on chest CT. Quantitative data were analyzed relative to pathological diagnosis as well as the qualitative CT pattern. Results: CALIPER-derived volumes of reticulation (p = 0.012), honeycombing (p = 0.017), and VRS (p < 0.001) were associated with a UIP pattern on pathology on univariate analysis but only VRS was associated with a UIP pathology on multivariable analysis (p = 0.013). Using a VRS cut-off of 173 cm3, the sensitivity and specificity for pathological UIP were similar to those for standard qualitative CT assessment (55.9% and 80.4% compared to 60.6% and 80.4%, respectively). VRS differentiated pathological UIP cases in those with a non-IPF diagnosis CT category (p < 0.001) but not in other qualitative CT patterns (typical UIP, probable UIP, and indeterminate for UIP). The rate of pathological UIP in those with VRS greater than 173 cm3 (84.2%) was nearly identical to those who had a qualitative CT pattern of probable UIP (88.9%). Conclusions: VRS may be an adjunct to CT in predicting pathology in patients with interstitial lung disease. Key Points: • Volume of vessel-related structures (VRS) was associated with usual interstitial pneumonia (UIP) on pathology. • This differentiation arose from those with CT scans with a non-IPF diagnosis imaging pattern. • Higher VRS has similar diagnostic ramifications for UIP as probable UIP, transitively suggesting in patients with high VRS, pathology may be obviated. [ABSTRACT FROM AUTHOR]

Lung transplantation remains the sole curative option for patients with idiopathic pulmonary fibrosis (IPF), but donor organs remain scarce, and many eligible patients die before transplant. Tools to optimize the timing of transplant referrals are urgently needed. Least absolute shrinkage and selection operator was applied to clinical and proteomic data generated as part of a prospective cohort study of interstitial lung disease (ILD) to derive clinical, proteomic, and multidimensional logit models of near-term death or lung transplant within 18 months of blood draw. Model-fitted values were dichotomized at the point of maximal sensitivity and specificity, and decision curve analysis was used to select the best-performing classifier. We then applied this classifier to independent IPF and non-IPF ILD cohorts to determine test performance characteristics. Cohorts were restricted to patients aged ≤72 years with body mass index 18 to 32 to increase the likelihood of transplant eligibility. IPF derivation, IPF validation, and non-IPF ILD validation cohorts consisted of 314, 105, and 295 patients, respectively. A multidimensional model comprising 2 clinical variables and 20 proteins outperformed stand-alone clinical and proteomic models. Following dichotomization, the multidimensional classifier predicted near-term outcome with 70% sensitivity and 92% specificity in the IPF validation cohort and 70% sensitivity and 80% specificity in the non-IPF ILD validation cohort. A multidimensional classifier of near-term outcomes accurately discriminated this end-point with good test performance across independent IPF and non-IPF ILD cohorts. These findings support refinement and prospective validation of this classifier in transplant-eligible individuals. [ABSTRACT FROM AUTHOR]

Preclinical experiments suggest protective effects of omega-3 fatty acids and their metabolites in lung injury and fibrosis. Whether higher intake of omega-3 fatty acids is associated with disease progression and survival in humans with pulmonary fibrosis is unknown. What are the associations of plasma omega-3 fatty acid levels (a validated marker of omega-3 nutritional intake) with disease progression and transplant-free survival in pulmonary fibrosis? Omega-3 fatty acid levels were measured from plasma samples of patients with clinically diagnosed pulmonary fibrosis from the Pulmonary Fibrosis Foundation Patient Registry (n = 150), University of Virginia (n = 58), and University of Chicago (n = 101) cohorts. The N-3 index (docosahexaenoic acid + eicosapentaenoic acid) was the primary exposure variable of interest. Linear-mixed effects models with random intercept and slope were used to examine associations of plasma omega-3 fatty acid levels with changes in FVC and diffusing capacity for carbon monoxide over a period of 12 months. Cox proportional hazards models were used to examine transplant-free survival. Stratified analyses by telomere length were performed in the University of Chicago cohort. Most of the cohort were patients with idiopathic pulmonary fibrosis (88%) and male patients (74%). One-unit increment in log-transformed N-3 index plasma level was associated with a change in diffusing capacity for carbon monoxide of 1.43 mL/min/mm Hg per 12 months (95% CI, 0.46-2.41) and a hazard ratio for transplant-free survival of 0.44 (95% CI, 0.24-0.83). Cardiovascular disease history, smoking, and antifibrotic usage did not significantly modify associations. Omega-3 fatty acid levels were not significantly associated with changes in FVC. Higher eicosapentaenoic acid plasma levels were associated with longer transplant-free survival among University of Chicago participants with shorter telomere length (P value for interaction =.02). Further research is needed to investigate underlying biological mechanisms and whether omega-3 fatty acids are a potential disease-modifying therapy. [ABSTRACT FROM AUTHOR]

Because chest CT scan has largely supplanted surgical lung biopsy for diagnosing most cases of interstitial lung disease (ILD), tools to standardize CT scan interpretation are urgently needed. Does a deep learning (DL)-based classifier for usual interstitial pneumonia (UIP) derived using CT scan features accurately discriminate radiologist-determined visual UIP? A retrospective cohort study was performed. Chest CT scans acquired in individuals with and without ILD were drawn from a variety of public and private data sources. Using radiologist-determined visual UIP as ground truth, a convolutional neural network was used to learn discrete CT scan features of UIP, with outputs used to predict the likelihood of UIP using a linear support vector machine. Test performance characteristics were assessed in an independent performance cohort and multicenter ILD clinical cohort. Transplant-free survival was compared between UIP classification approaches using the Kaplan-Meier estimator and Cox proportional hazards regression. A total of 2,907 chest CT scans were included in the training (n = 1,934), validation (n = 408), and performance (n = 565) data sets. The prevalence of radiologist-determined visual UIP was 12.4% and 37.1% in the performance and ILD clinical cohorts, respectively. The DL-based UIP classifier predicted visual UIP in the performance cohort with sensitivity and specificity of 93% and 86%, respectively, and in the multicenter ILD clinical cohort with 81% and 77%, respectively. DL-based and visual UIP classification similarly discriminated survival, and outcomes were consistent among cases with positive DL-based UIP classification irrespective of visual classification. A DL-based classifier for UIP demonstrated good test performance across a wide range of UIP prevalence and similarly discriminated survival when compared with radiologist-determined UIP. This automated tool could efficiently screen for UIP in patients undergoing chest CT scan and identify a high-risk phenotype among those with known ILD. [Display omitted] [ABSTRACT FROM AUTHOR]

Interstitial lung diseases (ILDs) are complex and heterogeneous diseases. The use of traditional diagnostic classification in ILD can lead to suboptimal management, which is worsened by not considering the molecular pathways, biological complexity, and disease phenotypes. The identification of specific "treatable traits" in ILDs, which are clinically relevant and modifiable disease characteristics, may improve patient's outcomes. Treatable traits in ILDs may be classified into four different domains (pulmonary, aetiological, comorbidities, and lifestyle), which will facilitate identification of related assessment tools, treatment options, and expected benefits. A multidisciplinary care team model is a potential way to implement a "treatable traits" strategy into clinical practice with the aim of improving patients' outcomes. Multidisciplinary models of care, international registries, and the use of artificial intelligence may facilitate the implementation of the "treatable traits" approach into clinical practice. Prospective studies are needed to test potential therapies for a variety of treatable traits to further advance care of patients with ILD. [ABSTRACT FROM AUTHOR]

Background: Idiopathic pulmonary fibrosis (IPF) is a progressive fibrosing interstitial lung disease characterised by decline in lung function. We evaluated trajectories of forced vital capacity (FVC) and diffusing capacity (DLco) in a cohort of patients with IPF. Methods: Patients with IPF that was diagnosed or confirmed at the enrolling centre in the previous 6 months were enrolled into the IPF-PRO Registry between June 2014 and October 2018. Patients were followed prospectively, with lung function data collected as part of routine clinical care. Mean trajectories of FVC and DLco % predicted in all patients and in subgroups by characteristics assessed at enrolment were estimated using a joint model that accounted for factors such as disease severity and visit patterns. Results: Of 1002 patients in the registry, 941 had ≥ 1 FVC and/or DLco measurement after enrolment. The median (Q1, Q3) follow-up period was 35.1 (18.9, 47.2) months. Overall, mean estimated declines in FVC and DLco % predicted were 2.8% and 2.9% per year, respectively. There was no evidence that the mean trajectories of FVC or DLco had a non-linear relationship with time at the population level. Patients who were male, white, had a family history of ILD, were using oxygen, or had prior/current use of antifibrotic therapy at enrolment had greater rates of decline in FVC % predicted. Patients who were male or white had greater rates of decline in DLco % predicted. Conclusions: Data from the IPF-PRO Registry suggest a constant rate of decline in lung function over a prolonged period, supporting the inexorably progressive nature of IPF. A graphical abstract summarising the data in this manuscript is available at: https://www.usscicomms.com/respiratory/IPF-PRORegistry%5fLungFunctionTrajectories. Trial registration: NCT01915511. [ABSTRACT FROM AUTHOR]

Background: Interstitial lung abnormalities (ILA) may represent undiagnosed early-stage or subclinical interstitial lung disease (ILD). ILA are often observed incidentally in patients who subsequently develop clinically overt ILD. There is limited information on consensus definitions for, and the appropriate evaluation of, ILA. Early recognition of patients with ILD remains challenging, yet critically important. Expert consensus could inform early recognition and referral.Research Question: Can consensus-based expert recommendations be identified to guide clinicians in the recognition, referral, and follow-up of patients with or at risk of developing early ILDs?Study Design and Methods: Pulmonologists and radiologists with expertise in ILD participated in two iterative rounds of surveys. The surveys aimed to establish consensus regarding ILA reporting, identification of patients with ILA, and identification of populations that might benefit from screening for ILD. Recommended referral criteria and follow-up processes were also addressed. Threshold for consensus was defined a priori as ≥ 75% agreement or disagreement.Results: Fifty-five experts were invited and 44 participated; consensus was reached on 39 of 85 questions. The following clinically important statements achieved consensus: honeycombing and traction bronchiectasis or bronchiolectasis indicate potentially progressive ILD; honeycombing detected during lung cancer screening should be reported as potentially significant (eg, with the Lung CT Screening Reporting and Data System "S-modifier" [Lung-RADS; which indicates clinically significant or potentially significant noncancer findings]), recommending referral to a pulmonologist in the radiology report; high-resolution CT imaging and full pulmonary function tests should be ordered if nondependent subpleural reticulation, traction bronchiectasis, honeycombing, centrilobular ground-glass nodules, or patchy ground-glass opacity are observed on CT imaging; patients with honeycombing or traction bronchiectasis should be referred to a pulmonologist irrespective of diffusion capacity values; and patients with systemic sclerosis should be screened with pulmonary function tests for early-stage ILD.Interpretation: Guidance was established for identifying clinically relevant ILA, subsequent referral, and follow-up. These results lay the foundation for developing practical guidance on managing patients with ILA. [ABSTRACT FROM AUTHOR]

Idiopathic pulmonary fibrosis (IPF) is characterized by progressive scarring and loss of lung function. With limited treatment options, patients succumb to the disease within 2 to 5 years. The molecular pathogenesis of IPF regarding the immunologic changes that occur is poorly understood. We characterize a role for non-canonical aryl-hydrocarbon receptor signaling (ncAHR) in dendritic cells (DCs) that leads to production of IL-6 and increased IL-17+ cells, promoting fibrosis. TLR9 signaling in myofibroblasts is shown to regulate production of TDO2 which converts tryptophan into the endogenous AHR ligand kynurenine. Mice with augmented ncAHR signaling were created by crossing floxed AHR exon-2 deletion mice (AHRΔex2) with mice harboring a CD11c-Cre. Bleomycin (blm) was used to study fibrotic pathogenesis. Isolated CD11c+ cells and primary fibroblasts were treated ex-vivo with relevant TLR agonists and AHR modulating compounds to study how AHR signaling influenced inflammatory cytokine production. Human datasets were also interrogated. Inhibition of all AHR signaling rescued fibrosis, however, AHRΔex2 mice treated with blm developed more fibrosis and DCs from these mice were hyperinflammatory and profibrotic upon adoptive transfer. Treatment of fibrotic fibroblasts with TLR9 agonist increased expression of TDO2 and fibrotic fibroblasts activated IL-6 production in CD103+ DCs. Study of human samples corroborates the relevance of these findings in IPF patients. We also, for the first time, identify that AHR exon-2 floxed mice retain capacity for ncAHR signaling.