A multidimensional classifier to support lung transplant referral in patients with pulmonary fibrosis.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Association study of human leukocyte antigen variants and idiopathic pulmonary fibrosis.

Introduction: Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial pneumonia marked by progressive lung fibrosis and a poor prognosis. Recent studies have highlighted the potential role of infection in the pathogenesis of IPF, and a prior association of the HLA-DQB1 gene with idiopathic fibrotic interstitial pneumonia (including IPF) has been reported. Owing to the important role that the human leukocyte antigen (HLA) region plays in the immune response, here we evaluated if HLA genetic variation was associated specifically with IPF risk. Methods: We performed a meta-analysis of associations of the HLA region with IPF risk in individuals of European ancestry from seven independent case-control studies of IPF (comprising 5159 cases and 27 459 controls, including a prior study of fibrotic interstitial pneumonia). Single nucleotide polymorphisms, classical HLA alleles and amino acids were analysed and signals meeting a region-wide association threshold of p<4.5×10-4 and a posterior probability of replication >90% were considered significant. We sought to replicate the previously reported HLA-DQB1 association in the subset of studies independent of the original report. Results: The meta-analysis of all seven studies identified four significant independent single nucleotide polymorphisms associated with IPF risk. However, none met the posterior probability for replication criterion. The HLA-DQB1 association was not replicated in the independent IPF studies. Conclusion: Variation in the HLA region was not consistently associated with risk in studies of IPF. However, this does not preclude the possibility that other genomic regions linked to the immune response may be involved in the aetiology of IPF.

Machine Learning of Plasma Proteomics Classifies Diagnosis of Interstitial Lung Disease.

RATIONALE: Distinguishing connective tissue disease associated interstitial lung disease (CTD-ILD) from idiopathic pulmonary fibrosis (IPF) can be clinically challenging. OBJECTIVES: Identify proteins that separate and classify CTD-ILD from IPF patients. METHODS: Four registries with 1247 IPF and 352 CTD-ILD patients were included in analyses. Plasma samples were subjected to high-throughput proteomics assays. Protein features were prioritized using Recursive Feature Elimination (RFE) to construct a proteomic classifier. Multiple machine learning models, including Support Vector Machine, LASSO regression, Random Forest (RF), and imbalanced-RF, were trained and tested in independent cohorts. The validated models were used to classify each case iteratively in external datasets. MEASUREMENT AND MAIN RESULTS: A classifier with 37 proteins (PC37) was enriched in biological process of bronchiole development and smooth muscle proliferation, and immune responses. Four machine learning models used PC37 with sex and age score to generate continuous classification values. Receiver-operating-characteristic curve analyses of these scores demonstrated consistent Area-Under-Curve 0.85-0.90 in test cohort, and 0.94-0.96 in the single-sample dataset. Binary classification demonstrated 78.6%-80.4% sensitivity and 76%-84.4% specificity in test cohort, 93.5%-96.1% sensitivity and 69.5%-77.6% specificity in single-sample classification dataset. Composite analysis of all machine learning models confirmed 78.2% (194/248) accuracy in test cohort and 82.9% (208/251) in single-sample classification dataset. CONCLUSIONS: Multiple machine learning models trained with large cohort proteomic datasets consistently distinguished CTD-ILD from IPF. Identified proteins involved in immune pathways. We further developed a novel approach for single sample classification, which could facilitate honing the differential diagnosis of ILD in challenging cases and improve clinical decision-making.

Risk Factors for Hospital Readmission in Patients With Interstitial Lung Disease.

BACKGROUND: Little is known about the rates, causes, or risk factors for hospital readmission among patients with interstitial lung disease (ILD). We investigated the prevalence, features, and comorbidities of subjects hospitalized with ILD and their subsequent re-hospitalizations in this retrospective study. METHODS: A retrospective analysis of subjects enrolled in the University of Chicago ILD Natural History registry was conducted. Demographic data, comorbidities, and timing and cause of subsequent hospitalizations were collected from the medical record. The primary outcome was time to first readmission via a cause-specific Cox hazards model with a sensitivity analysis with the Fine-Gray cumulative hazard model; the secondary outcome was the number of hospitalizations per subject via a Poisson multivariable model. RESULTS: Among 1,796 patients with ILD, 443 subjects were hospitalized, with 978 total hospitalizations; 535 readmissions were studied, 282 (53%) for a respiratory indication. For the outcome of time to readmission, Black race was the only subject characteristic associated with an increased hazard of readmission in the Cox model (hazard ratio 1.50, P = .03) while Black race, hypersensitivity pneumonitis, and sarcoidosis were associated with increased hazard of readmission in the Fine-Gray model. Black race, female sex, atrial fibrillation, obstructive lung disease, and pulmonary hypertension were associated with an increased number of hospitalizations in the Poisson model. CONCLUSIONS: We demonstrated that hospital readmission from any cause was a common occurrence in subjects with ILD. Further efforts to improve quality of life among these subjects could focus on risk scores for readmission, mitigating racial health disparities, and treatment of comorbidities.

Deep Learning Classification of Usual Interstitial Pneumonia Predicts Outcomes.

Rationale: Computed tomography (CT) enables noninvasive diagnosis of usual interstitial pneumonia (UIP), but enhanced image analyses are needed to overcome the limitations of visual assessment. Objectives: Apply multiple instance learning (MIL) to develop an explainable deep learning algorithm for prediction of UIP from CT and validate its performance in independent cohorts. Methods: We trained an MIL algorithm using a pooled dataset (n = 2,143) and tested it in three independent populations: data from a prior publication (n = 127), a single-institution clinical cohort (n = 239), and a national registry of patients with pulmonary fibrosis (n = 979). We tested UIP classification performance using receiver operating characteristic analysis, with histologic UIP as ground truth. Cox proportional hazards and linear mixed-effects models were used to examine associations between MIL predictions and survival or longitudinal FVC. Measurements and Main Results: In two cohorts with biopsy data, MIL improved accuracy for histologic UIP (area under the curve, 0.77 [n = 127] and 0.79 [n = 239]) compared with visual assessment (area under the curve, 0.65 and 0.71). In cohorts with survival data, MIL-UIP classifications were significant for mortality (n = 239, mortality to April 2021: unadjusted hazard ratio, 3.1; 95% confidence interval [CI], 1.96-4.91; P < 0.001; and n = 979, mortality to July 2022: unadjusted hazard ratio, 3.64; 95% CI, 2.66-4.97; P < 0.001). Individuals classified as UIP positive by the algorithm had a significantly greater annual decline in FVC than those classified as UIP negative (-88 ml/yr vs. -45 ml/yr; n = 979; P < 0.01), adjusting for extent of lung fibrosis. Conclusions: Computerized assessment using MIL identifies clinically significant features of UIP on CT. Such a method could improve confidence in radiologic assessment of patients with interstitial lung disease, potentially enabling earlier and more precise diagnosis.

Genome-wide SNP-sex interaction analysis of susceptibility to idiopathic pulmonary fibrosis.

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic lung condition that is more prevalent in males than females. The reasons for this are not fully understood, with differing environmental exposures due to historically sex-biased occupations, or diagnostic bias, being possible explanations. To date, over 20 independent genetic variants have been identified to be associated with IPF susceptibility, but these have been discovered when combining males and females. Our aim was to test for the presence of sex-specific associations with IPF susceptibility and assess whether there is a need to consider sex-specific effects when evaluating genetic risk in clinical prediction models for IPF. Methods: We performed genome-wide single nucleotide polymorphism (SNP)-by-sex interaction studies of IPF risk in six independent IPF case-control studies and combined them using inverse-variance weighted fixed effect meta-analysis. In total, 4,561 cases (1,280 females and 2,281 males) and 23,500 controls (8,360 females and 14,528 males) of European genetic ancestry were analysed. We used polygenic risk scores (PRS) to assess differences in genetic risk prediction between males and females. Findings: Three independent genetic association signals were identified. All showed a consistent direction of effect across all individual IPF studies and an opposite direction of effect in IPF susceptibility between females and males. None had been previously identified in IPF susceptibility genome-wide association studies (GWAS). The predictive accuracy of the PRSs were similar between males and females, regardless of whether using combined or sex-specific GWAS results. Interpretation: We prioritised three genetic variants whose effect on IPF risk may be modified by sex, however these require further study. We found no evidence that the predictive accuracy of common SNP-based PRSs varies significantly between males and females.

Associations of Plasma Omega-3 Fatty Acids With Progression and Survival in Pulmonary Fibrosis.

BACKGROUND: 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. RESEARCH QUESTION: 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? STUDY DESIGN AND METHODS: 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. RESULTS: 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). INTERPRETATION: Further research is needed to investigate underlying biological mechanisms and whether omega-3 fatty acids are a potential disease-modifying therapy.

Pulmonary Alveolar Proteinosis-associated Pulmonary Fibrosis: Evolutional Changes and Radiologic-Pathologic Correlation.

Pulmonary alveolar proteinosis (PAP) is a rare disease with frequently favorable outcomes. In a minority of patients with primary or secondary PAP, the disease course may be complicated by pulmonary fibrosis (PF) despite appropriate management. Imaging and histopathologic manifestations of uncomplicated PAP are well-known. In contrast, radiologic-pathologic descriptions of PAP-associated PF (PAP-PF) are limited. The current manuscript presents three cases of PAP-PF, each with serial high-resolution CT imaging demonstrating the longitudinal progression of this unusual complication, with concordant pathologic findings in two patients. Much remains to be known regarding adverse prognostic factors contributing to PAP-PF. Early recognition of radiologic-pathologic manifestations would allow timely diagnosis and management optimization. Keywords: CT, Lung, Inflammation, Pathology © RSNA, 2023.

Proteomic Biomarkers of Survival in Idiopathic Pulmonary Fibrosis.

RATIONALE: Idiopathic pulmonary fibrosis (IPF) causes progressive lung scarring and high mortality. Reliable and accurate prognostic biomarkers are urgently needed. OBJECTIVE: To identify and validate circulating protein biomarkers of IPF survival. METHODS: High-throughput proteomic data were generated using prospectively collected plasma samples from patients with IPF from the Pulmonary Fibrosis Foundation Patient Registry (discovery cohort) and the Universities of California-Davis, Chicago, and Virginia (validation cohort). Proteins associated with three-year transplant-free survival (TFS) were identified using multivariable Cox proportional hazards regression. Those associated with TFS after adjustment for false discovery in the discovery cohort were advanced for testing in the validation cohort, with proteins maintaining TFS association with consistent effect direction considered validated. After combining cohorts, functional analyses were performed, and machine learning used to derive a proteomic signature of TFS. MAIN RESULTS: Of 2921 proteins tested in the discovery cohort (n=871), 231 were associated with differential TFS. Of these, 140 maintained TFS association with consistent effect direction in the validation cohort (n=355). After combining cohorts, validated proteins with strongest TFS association were latent-transforming growth factor beta-binding protein 2 (HR 2.43, 95% CI 2.09-2.82), collagen alpha-1(XXIV) chain (HR 2.21; 95% CI 1.86-2.39) and keratin 19 (HR 1.60; 95% CI 1.47-1.74). In decision curve analysis, a proteomic signature of TFS outperformed a similarly derived clinical prediction model. CONCLUSIONS: In largest proteomic investigation of IPF outcomes performed to date, we identified and validated 140 protein biomarkers of TFS. These results shed important light on potential drivers of IPF progression.

Association study of human leukocyte antigen (HLA) variants and idiopathic pulmonary fibrosis.

Introduction: Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial pneumonia marked by progressive lung fibrosis and a poor prognosis. Recent studies have highlighted the potential role of infection in the pathogenesis of IPF and a prior association of the HLA-DQB1 gene with idiopathic fibrotic interstitial pneumonia (including IPF) has been reported. Due to the important role that the Human Leukocyte Antigen (HLA) region plays in the immune response, here we evaluated if HLA genetic variation was associated specifically with IPF risk. Methods: We performed a meta-analysis of associations of the HLA region with IPF risk in individuals of European ancestry from seven independent case-control studies of IPF (comprising a total of 5,159 cases and 27,459 controls, including the prior study of fibrotic interstitial pneumonia). Single nucleotide polymorphisms, classical HLA alleles and amino acids were analysed and signals meeting a region-wide association threshold p<4.5×10-4 and a posterior probability of replication >90% were considered significant. We sought to replicate the previously reported HLA-DQB1 association in the subset of studies independent of the original report. Results: The meta-analysis of all seven studies identified four significant independent single nucleotide polymorphisms associated with IPF risk. However, none met the posterior probability for replication criterion. The HLA-DQB1 association was not replicated in the independent IPF studies. Conclusion: Variation in the HLA region was not consistently associated with risk in studies of IPF. However, this does not preclude the possibility that other genomic regions linked to the immune response may be involved in the aetiology of IPF.

Telomere length and immunosuppression in non-idiopathic pulmonary fibrosis interstitial lung disease.

BACKGROUND: Studies suggest a harmful pharmacogenomic interaction exists between short leukocyte telomere length (LTL) and immunosuppressants in idiopathic pulmonary fibrosis (IPF). It remains unknown if a similar interaction exists in non-IPF interstitial lung disease (ILD). METHODS: A retrospective, multicentre cohort analysis was performed in fibrotic hypersensitivity pneumonitis (fHP), unclassifiable ILD (uILD) and connective tissue disease (CTD)-ILD patients from five centres. LTL was measured by quantitative PCR for discovery and replication cohorts and expressed as age-adjusted percentiles of normal. Inverse probability of treatment weights based on propensity scores were used to assess the association between mycophenolate or azathioprine exposure and age-adjusted LTL on 2-year transplant-free survival using weighted Cox proportional hazards regression incorporating time-dependent immunosuppressant exposure. RESULTS: The discovery and replication cohorts included 613 and 325 patients, respectively. In total, 40% of patients were exposed to immunosuppression and 22% had LTL <10th percentile of normal. fHP and uILD patients with LTL <10th percentile experienced reduced survival when exposed to either mycophenolate or azathioprine in the discovery cohort (mortality hazard ratio (HR) 4.97, 95% CI 2.26-10.92; p<0.001) and replication cohort (mortality HR 4.90, 95% CI 1.74-13.77; p=0.003). Immunosuppressant exposure was not associated with differential survival in patients with LTL ≥10th percentile. There was a significant interaction between LTL <10th percentile and immunosuppressant exposure (discovery pinteraction=0.013; replication pinteraction=0.011). Low event rate and prevalence of LTL <10th percentile precluded subgroup analyses for CTD-ILD. CONCLUSION: Similar to IPF, fHP and uILD patients with age-adjusted LTL <10th percentile may experience reduced survival when exposed to immunosuppression.

Treatable traits: a comprehensive precision medicine approach in interstitial lung disease.

Interstitial lung disease (ILD) is a diverse group of inflammatory and fibrotic lung conditions causing significant morbidity and mortality. A multitude of factors beyond the lungs influence symptoms, health-related quality of life, disease progression and survival in patients with ILD. Despite an increasing emphasis on multidisciplinary management in ILD, the absence of a framework for assessment and delivery of comprehensive patient care poses challenges in clinical practice. The treatable traits approach is a precision medicine care model that operates on the premise of individualised multidimensional assessment for distinct traits that can be targeted by specific interventions. The potential utility of this approach has been described in airway diseases, but has not been adequately considered in ILD. Given the similar disease heterogeneity and complexity between ILD and airway diseases, we explore the concept and potential application of the treatable traits approach in ILD. A framework of aetiological, pulmonary, extrapulmonary and behavioural and lifestyle treatable traits relevant to clinical care and outcomes for patients with ILD is proposed. We further describe key research directions to evaluate the application of the treatable traits approach towards advancing patient care and health outcomes in ILD.

Abnormalities on baseline chest imaging are risk factors for immune checkpoint inhibitor associated pneumonitis.

BACKGROUND: Chronic lung disease is a proposed risk factor for immune checkpoint inhibitor pneumonitis (ICI-pneumonitis); however, data is sparse regarding the impact of pre-existing lung disease and baseline chest imaging abnormalities on the risk of developing ICI-pneumonitis. METHODS: We conducted a retrospective cohort study of patients with ICI treatment for cancer from 2015 to 2019. ICI-pneumonitis was determined by the treating physician with corroboration via an independent physician review and exclusion of alternative etiologies. Controls were patients treated with ICI without a diagnosis of ICI-pneumonitis. Fisher's exact tests, Student's t-tests, and logistic regression were used for statistical analysis. RESULTS: We analyzed 45 cases of ICI-pneumonitis and 135 controls. Patients with abnormal baseline chest CT imaging (emphysema; bronchiectasis; reticular, ground glass and/or consolidative opacities) had increased risk for ICI-pneumonitis (OR 3.41, 95%CI: 1.68-6.87, p = 0.001). Patients with gastroesophageal reflux disease (GERD) (OR 3.83, 95%CI: 1.90-7.70, p = < 0.0001) also had increased risk for ICI-pneumonitis. On multivariable logistic regression, patients with abnormal baseline chest imaging and/or GERD remained at increased risk for ICI-pneumonitis. Eighteen percent of all patients (32/180) had abnormal baseline chest CT consistent with chronic lung disease without a documented diagnosis. CONCLUSION: Patients with baseline chest CT abnormalities and GERD were at increased risk for developing ICI-pneumonitis. The large proportion of patients with baseline radiographic abnormalities without a clinical diagnosis of chronic lung disease highlights the importance of multidisciplinary evaluation prior to ICI initiation.

Tobacco smoking is associated with combined pulmonary fibrosis and emphysema and worse outcomes in interstitial lung disease.

Tobacco smoking is an established cause of pulmonary disease whose contribution to interstitial lung disease (ILD) is incompletely characterized. We hypothesized that compared with nonsmokers, subjects who smoked tobacco would differ in their clinical phenotype and have greater mortality. We performed a retrospective cohort study of tobacco smoking in ILD. We evaluated demographic and clinical characteristics, time to clinically meaningful lung function decline (LFD), and mortality in patients stratified by tobacco smoking status (ever vs. never) within a tertiary center ILD registry (2006-2021) and replicated mortality outcomes across four nontertiary medical centers. Data were analyzed by two-sided t tests, Poisson generalized linear models, and Cox proportional hazard models adjusted for age, sex, forced vital capacity (FVC), diffusion capacity of the lung for carbon monoxide (DLCO), ILD subtype, antifibrotic therapy, and hospital center. Of 1,163 study participants, 651 were tobacco smokers. Smokers were more likely to be older, male, have idiopathic pulmonary fibrosis (IPF), coronary artery disease, CT honeycombing and emphysema, higher FVC, and lower DLCO than nonsmokers (P < 0.01). Time to LFD in smokers was shorter (19.7 ± 20 mo vs. 24.8 ± 29 mo; P = 0.038) and survival time was decreased [10.75 (10.08-11.50) yr vs. 20 (18.67-21.25) yr; adjusted mortality HR = 1.50, 95%CI 1.17-1.92; P < 0.0001] compared with nonsmokers. Smokers had 12% greater odds of death for every additional 10 pack yr of smoking (P < 0.0001). Mortality outcomes remained consistent in the nontertiary cohort (HR = 1.51, 95%CI = 1.03-2.23; P = 0.036). Tobacco smokers with ILD have a distinct clinical phenotype strongly associated with the syndrome of combined PF and emphysema, shorter time to LFD, and decreased survival. Smoking prevention may improve ILD outcomes.NEW & NOTEWORTHY Smoking in ILD is associated with combined pulmonary fibrosis and emphysema and worse clinical outcomes.

Integrative multi-omics analysis reveals novel idiopathic pulmonary fibrosis endotypes associated with disease progression.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is characterized by the accumulation of extracellular matrix in the pulmonary interstitium and progressive functional decline. We hypothesized that integration of multi-omics data would identify clinically meaningful molecular endotypes of IPF. METHODS: The IPF-PRO Registry is a prospective registry of patients with IPF. Proteomic and transcriptomic (including total RNA [toRNA] and microRNA [miRNA]) analyses were performed using blood collected at enrollment. Molecular data were integrated using Similarity Network Fusion, followed by unsupervised spectral clustering to identify molecular subtypes. Cox proportional hazards models tested the relationship between these subtypes and progression-free and transplant-free survival. The molecular subtypes were compared to risk groups based on a previously described 52-gene (toRNA expression) signature. Biological characteristics of the molecular subtypes were evaluated via linear regression differential expression and canonical pathways (Ingenuity Pathway Analysis [IPA]) over-representation analyses. RESULTS: Among 232 subjects, two molecular subtypes were identified. Subtype 1 (n = 105, 45.3%) and Subtype 2 (n = 127, 54.7%) had similar distributions of age (70.1 +/- 8.1 vs. 69.3 +/- 7.6 years; p = 0.31) and sex (79.1% vs. 70.1% males, p = 0.16). Subtype 1 had more severe disease based on composite physiologic index (CPI) (55.8 vs. 51.2; p = 0.002). After adjusting for CPI and antifibrotic treatment at enrollment, subtype 1 experienced shorter progression-free survival (HR 1.79, 95% CI 1.28,2.56; p = 0.0008) and similar transplant-free survival (HR 1.30, 95% CI 0.87,1.96; p = 0.20) as subtype 2. There was little agreement in the distribution of subjects to the molecular subtypes and the risk groups based on 52-gene signature (kappa = 0.04, 95% CI= -0.08, 0.17), and the 52-gene signature risk groups were associated with differences in transplant-free but not progression-free survival. Based on heatmaps and differential expression analyses, proteins and miRNAs (but not toRNA) contributed to classification of subjects to the molecular subtypes. The IPA showed enrichment in pulmonary fibrosis-relevant pathways, including mTOR, VEGF, PDGF, and B-cell receptor signaling. CONCLUSIONS: Integration of transcriptomic and proteomic data from blood enabled identification of clinically meaningful molecular endotypes of IPF. If validated, these endotypes could facilitate identification of individuals likely to experience disease progression and enrichment of clinical trials. TRIAL REGISTRATION: NCT01915511.

PhIP-Seq uncovers novel autoantibodies and unique endotypes in interstitial lung disease.

Interstitial lung diseases (ILDs) are a heterogeneous group of disorders that can develop in patients with connective tissue diseases (CTD). Establishing autoimmunity in ILD impacts prognosis and treatment. ILD patients are screened for autoimmunity by assaying for anti-nuclear autoantibodies, rheumatoid factors and other non-specific tests. However, this approach has not been rigorously validated and may miss autoimmunity that manifests as autoantibodies to tissue antigens not previously defined in ILD. Here, we use Phage Immunoprecipitation-Sequencing (PhIP-Seq) to conduct a large, multi-center unbiased autoantibody discovery screen of ILD patients and controls. PhIP-Seq identified 17 novel autoreactive targets, and machine learning classifiers derived from these targets discriminated ILD serum from controls. Among these 17 candidates, we validated Cadherin Related Family Member 5 (CDHR5) as an autoantigen and found CDHR5 autoantibodies in patients with rheumatologic disorders and importantly, subjects not previously diagnosed with autoimmunity. Lung tissue of CDHR5 autoreactive patients showed transcriptional profiles consistent with activation of NFκB signaling and upregulation of chitotriosidase (CHIT1), a molecular pathway linked to fibrosis. Our study shows PhIP-Seq uncovers novel autoantibodies in ILD patients not revealed by standard clinical tests. Furthermore, CDHR5 autoantibodies may define a novel molecular endotype of ILD characterized by inflammation and fibrosis.

Antigenic responses are hallmarks of fibrotic interstitial lung diseases independent of underlying etiologies.

Interstitial lung diseases (ILD) are heterogeneous conditions that may lead to progressive fibrosis and death of affected individuals. Despite diversity in clinical manifestations, enlargement of lung-associated lymph nodes (LLN) in fibrotic ILD patients predicts worse survival. Herein, we revealed a common adaptive immune landscape in LLNs of all ILD patients, characterized by highly activated germinal centers and antigen-activated T cells including regulatory T cells (Tregs). In support of these findings, we identified serum reactivity to 17 candidate auto-antigens in ILD patients through a proteome-wide screening using phage immunoprecipitation sequencing. Autoantibody responses to actin binding LIM protein 1 (ABLIM1), a protein highly expressed in aberrant basaloid cells of fibrotic lungs, were correlated with LLN frequencies of T follicular helper cells and Tregs in ILD patients. Together, we demonstrate that end-stage ILD patients have converging immune mechanisms, in part driven by antigen-specific immune responses, which may contribute to disease progression.

Evaluation of Pulmonary Fibrosis Outcomes by Race and Ethnicity in US Adults.

Importance: Pulmonary fibrosis (PF) is characterized by progressive scarring of lung tissue and poor survival. Racial and ethnic minority populations face the greatest risk of morbidity and mortality from disparities impacting respiratory health, but the pattern of age at clinically relevant outcomes across diverse racial and ethnic populations with PF is unknown. Objective: To compare the age at PF-related outcomes and the heterogeneity in survival patterns among Hispanic, non-Hispanic Black, and non-Hispanic White participants. Design, Setting, and Participants: This cohort study included adult patients with a PF diagnosis and used data from prospective clinical registries: the Pulmonary Fibrosis Foundation Registry (PFFR) for the primary cohort and registries from 4 geographically distinct tertiary hospitals in the US for the external multicenter validation (EMV) cohort. Patients were followed between January 2003 and April 2021. Exposures: Race and ethnicity comparisons between Black, Hispanic, and White participants with PF. Main Outcomes and Measures: Age and sex distribution of participants were measured at the time of study enrollment. All-cause mortality and age at PF diagnosis, hospitalization, lung transplant, and death were assessed in participants over 14 389 person-years. Differences between racial and ethnic groups were compared using Wilcoxon rank sum tests, Bartlett 1-way analysis of variance, and χ2 tests, and crude mortality rates and rate ratios were assessed across racial and ethnic categories using Cox proportional hazards regression models. Results: In total, 4792 participants with PF were assessed (mean [SD] age, 66.1 [11.2] years; 2779 [58.0%] male; 488 [10.2%] Black, 319 [6.7%] Hispanic, and 3985 [83.2%] White); 1904 were in the PFFR and 2888 in the EMV cohort. Black patients with PF were consistently younger than White patients (mean [SD] age at baseline, 57.9 [12.0] vs 68.6 [9.6] years; P < .001). Hispanic and White patients were predominantly male (Hispanic: PFFR, 73 of 124 [58.9%] and EMV, 109 of 195 [55.9%]; and White: PFFR, 1090 of 1675 [65.1%] and EMV, 1373 of 2310 [59.4%]), while Black patients were less likely to be male (PFFR, 32 of 105 [30.5%] and EMV, 102 of 383 [26.6%]). Compared with White patients, Black patients had a lower crude mortality rate ratio (0.57 [95% CI, 0.31-0.97), but for Hispanic patients, the mortality rate ratio was similar to that of White patients (0.89; 95% CI, 0.57-1.35). Mean (SD) hospitalization events per person were highest among Black patients compared with Hispanic and White patients (Black: 3.6 [5.0]; Hispanic, 1.8 [1.4]; and White, 1.7 [1.3]; P < .001). Black patients were consistently younger than Hispanic and White patients at first hospitalization (mean [SD] age: Black, 59.4 [11.7] years; Hispanic, 67.5 [9.8] years; and White, 70.0 [9.3] years; P < .001), lung transplant (Black, 58.6 [8.6] years; Hispanic, 60.5 [6.1] years; and White, 66.9 [6.7] years; P < .001), and death (Black, 68.7 [8.4] years; Hispanic, 72.9 [7.6] years; and White, 73.5 [8.7] years; P < .001). These findings remained consistent in the replication cohort and in sensitivity analyses within prespecified deciles of age groups. Conclusions and Relevance: In this cohort study of participants with PF, racial and ethnic disparities, especially among Black patients, were found in PF-related outcomes, including earlier onset of death. Further research is essential to identify and mitigate the underlying responsible factors.

Telomere length associates with chronological age and mortality across racially diverse pulmonary fibrosis cohorts.

Pulmonary fibrosis (PF) is characterized by profound scarring and poor survival. We investigated the association of leukocyte telomere length (LTL) with chronological age and mortality across racially diverse PF cohorts. LTL measurements among participants with PF stratified by race/ethnicity were assessed in relation to age and all-cause mortality, and compared to controls. Generalized linear models were used to evaluate the age-LTL relationship, Cox proportional hazards models were used for hazard ratio estimation, and the Cochran-Armitage test was used to assess quartiles of LTL. Standardized LTL shortened with increasing chronological age; this association in controls was strengthened in PF (R = -0.28; P < 0.0001). In PF, age- and sex-adjusted LTL below the median consistently predicted worse mortality across all racial groups (White, HR = 2.21, 95% CI = 1.79-2.72; Black, HR = 2.22, 95% CI = 1.05-4.66; Hispanic, HR = 3.40, 95% CI = 1.88-6.14; and Asian, HR = 2.11, 95% CI = 0.55-8.23). LTL associates uniformly with chronological age and is a biomarker predictive of mortality in PF across racial groups.