Clinically Relevant Biomarkers in Connective Tissue Disease-Associated Interstitial Lung Disease.

Interstitial lung disease (ILD) complicates connective tissue disease (CTD) with variable incidence and is a leading cause of death in these patients. To improve CTD-ILD outcomes, early recognition and management of ILD is critical. Blood-based and radiologic biomarkers that assist in the diagnosis CTD-ILD have long been studied. Recent studies, including -omic investigations, have also begun to identify biomarkers that may help prognosticate such patients. This review provides an overview of clinically relevant biomarkers in patients with CTD-ILD, highlighting recent advances to assist in the diagnosis and prognostication of CTD-ILD.

Biological Age, Chronological Age, and Survival in Pulmonary Fibrosis: A Causal Mediation Analysis.

Rationale: Accelerated biological aging has been implicated in the development of interstitial lung disease (ILD) and other diseases of aging but remains poorly understood. Objectives: To identify plasma proteins that mediate the relationship between chronological age and survival association in patients with ILD. Methods: Causal mediation analysis was performed to identify plasma proteins that mediated the chronological age-survival relationship in an idiopathic pulmonary fibrosis discovery cohort. Proteins mediating this relationship after adjustment for false discovery were advanced for testing in an independent ILD validation cohort and explored in a chronic obstructive pulmonary disease cohort. A proteomic-based measure of biological age was constructed and survival analysis performed, assessing the impact of biological age and peripheral blood telomere length on the chronological age-survival relationship. Measurements and Main Results: Twenty-two proteins mediated the chronological age-survival relationship after adjustment for false discovery in the idiopathic pulmonary fibrosis discovery cohort (n = 874), with 19 remaining significant mediators of this relationship in the ILD validation cohort (n = 983) and one mediating this relationship in the chronic obstructive pulmonary disease cohort. Latent transforming growth factor-ß binding protein 2 and ectodysplasin A2 receptor showed the strongest mediation across cohorts. A proteomic measure of biological age completely attenuated the chronological age-survival association and better discriminated survival than chronological age. Results were robust to adjustment for peripheral blood telomere length, which did not mediate the chronological age-survival relationship. Conclusions: Molecular measures of aging completely mediate the relationship between chronological age and survival, suggesting that chronological age has no direct effect on ILD survival.

Novel Therapeutic Approaches in Connective Tissue Disease-Associated Interstitial Lung Disease.

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.

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.

Overview of Rheumatoid Arthritis-Associated Interstitial Lung Disease and Its Treatment.

Interstitial lung disease (ILD) is a common pulmonary complication of rheumatoid arthritis (RA), causing significant morbidity and mortality. Optimal treatment for RA-ILD is not yet well defined. Reliable prognostic indicators are largely byproducts of prior ILD progression, including low or decreasing forced vital capacity and extensive or worsening fibrosis on imaging. In the absence of validated tools to predict treatment response, decisions about whether to initiate or augment treatment are instead based on clinical judgment. In general, treatment should be initiated in patients who are symptomatic, progressing, or at high risk of poor outcomes. Retrospective data suggest that mycophenolate mofetil, azathioprine, and rituximab are likely effective therapies for RA-ILD. Abatacept is also emerging as a potential first-line treatment option for patients with RA-ILD. Further, recent data demonstrate that immunosuppression may be beneficial even in patients with a usual interstitial pneumonia (UIP) pattern on imaging, suggesting that immunosuppression should be considered irrespective of imaging pattern. Recent randomized controlled trials have shown that antifibrotic medications, such as nintedanib and likely pirfenidone, slow forced vital capacity decline in RA-ILD. Consideration can be given to antifibrotic initiation in patients progressing despite immunosuppression, particularly in patients with a UIP pattern. Future research directions include developing tools to predict which patients will remain stable from patients who will progress, discriminating patients who will respond to treatment from nonresponders, and developing algorithms for starting immunosuppression, antifibrotics, or both as first-line therapies.

A Deep Learning-Based Radiomic Classifier for Usual Interstitial Pneumonia.

BACKGROUND: 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. RESEARCH QUESTION: Does a deep learning (DL)-based classifier for usual interstitial pneumonia (UIP) derived using CT scan features accurately discriminate radiologist-determined visual UIP? STUDY DESIGN AND METHODS: 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. RESULTS: 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. INTERPRETATION: 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.

Clinically Relevant Biomarkers in Connective Tissue Disease-Associated Interstitial Lung Disease.

Interstitial lung disease (ILD) complicates connective tissue disease (CTD) with variable incidence and is a leading cause of death in these patients. To improve CTD-ILD outcomes, early recognition and management of ILD is critical. Blood-based and radiologic biomarkers that assist in the diagnosis CTD-ILD have long been studied. Recent studies, including -omic investigations, have also begun to identify biomarkers that may help prognosticate such patients. This review provides an overview of clinically relevant biomarkers in patients with CTD-ILD, highlighting recent advances to assist in the diagnosis and prognostication of CTD-ILD.

Recent innovations in the screening and diagnosis of systemic sclerosis-associated interstitial lung disease.

INTRODUCTION: Interstitial lung disease (ILD) is the leading cause of mortality in patients with systemic sclerosis (SSc). Risk of developing progressive ILD is highest among patients with diffuse cutaneous disease, positive anti-topoisomerase I antibody, and elevated acute phase reactants. With the FDA approval of two medications and a pipeline of novel therapeutics in trials, early recognition and intervention is critical. High-resolution computed tomography of the chest is the current gold standard test for diagnosis of ILD. Yet, it is not offered as a screening tool to all patients due to which ILD can be missed in up to a third of patients. There is a need to develop and validate more innovative screening modalities. AREAS COVERED: In this review, we provide an overview of screening and diagnosis of SSc-ILD, highlighting the recent innovations particularly the role of soluble serologic, radiomic (quantitative lung imaging, lung ultrasound), and breathomic (exhaled breath analysis) biomarkers in the early detection of SSc-ILD. EXPERT OPINION: There is remarkable progress in the development of new radiomics and serum biomarkers in diagnosing SSc-ILD. There is an urgent need for conceptualizing and testing composite ILD screening strategies that incorporate these biomarkers.

PCSK6 and Survival in Idiopathic Pulmonary Fibrosis.

Rationale: Idiopathic pulmonary fibrosis (IPF) is a devastating disease characterized by limited treatment options and high mortality. A better understanding of the molecular drivers of IPF progression is needed. Objectives: To identify and validate molecular determinants of IPF survival. Methods: A staged genome-wide association study was performed using paired genomic and survival data. Stage I cases were drawn from centers across the United States and Europe and stage II cases from Vanderbilt University. Cox proportional hazards regression was used to identify gene variants associated with differential transplantation-free survival (TFS). Stage I variants with nominal significance (P < 5 × 10-5) were advanced for stage II testing and meta-analyzed to identify those reaching genome-wide significance (P < 5 × 10-8). Downstream analyses were performed for genes and proteins associated with variants reaching genome-wide significance. Measurements and Main Results: After quality controls, 1,481 stage I cases and 397 stage II cases were included in the analysis. After filtering, 9,075,629 variants were tested in stage I, with 158 meeting advancement criteria. Four variants associated with TFS with consistent effect direction were identified in stage II, including one in an intron of PCSK6 (proprotein convertase subtilisin/kexin type 6) reaching genome-wide significance (hazard ratio, 4.11 [95% confidence interval, 2.54-6.67]; P = 9.45 × 10-9). PCSK6 protein was highly expressed in IPF lung parenchyma. PCSK6 lung staining intensity, peripheral blood gene expression, and plasma concentration were associated with reduced TFS. Conclusions: We identified four novel variants associated with IPF survival, including one in PCSK6 that reached genome-wide significance. Downstream analyses suggested that PCSK6 protein plays a potentially important role in IPF progression.

Interstitial lung disease progression after genomic usual interstitial pneumonia testing.

BACKGROUND: A genomic classifier for usual interstitial pneumonia (gUIP) has been shown to predict histological UIP with high specificity, increasing diagnostic confidence for idiopathic pulmonary fibrosis (IPF). Whether those with positive gUIP classification exhibit a progressive, IPF-like phenotype remains unknown. METHODS: A pooled, retrospective analysis of patients who underwent clinically indicated diagnostic bronchoscopy with gUIP testing at seven academic medical centres across the USA was performed. We assessed the association between gUIP classification and 18-month progression-free survival (PFS) using Cox proportional hazards regression. PFS was defined as the time from gUIP testing to death from any cause, lung transplant, ≥10% relative decline in forced vital capacity (FVC) or censoring at the time of last available FVC measure. Longitudinal change in FVC was then compared between gUIP classification groups using a joint regression model. RESULTS: Of 238 consecutive patients who underwent gUIP testing, 192 had available follow-up data and were included in the analysis, including 104 with positive gUIP classification and 88 with negative classification. In multivariable analysis, positive gUIP classification was associated with reduced PFS (hazard ratio 1.58, 95% CI 0.86-2.92; p=0.14), but this did not reach statistical significance. Mean annual change in FVC was -101.8 mL (95% CI -142.7- -60.9 mL; p<0.001) for those with positive gUIP classification and -73.2 mL (95% CI -115.2- -31.1 mL; p<0.001) for those with negative classification (difference 28.7 mL, 95% CI -83.2-25.9 mL; p=0.30). CONCLUSIONS: gUIP classification was not associated with differential rates of PFS or longitudinal FVC decline in a multicentre interstitial lung disease cohort undergoing bronchoscopy as part of the diagnostic evaluation.

Validation of Proposed Criteria for Progressive Pulmonary Fibrosis.

Rationale: Criteria for progressive pulmonary fibrosis (PPF) have been proposed, but their prognostic value beyond categorical decline in FVC remains unclear. Objectives: To determine whether proposed PPF criteria predict transplant-free survival (TFS) in patients with non-idiopathic pulmonary fibrosis (IPF) forms of interstitial lung disease (ILD). Methods: A retrospective, multicenter cohort analysis was performed. Patients with diagnoses of fibrotic connective tissue disease-associated ILD, fibrotic hypersensitivity pneumonitis, and non-IPF idiopathic interstitial pneumonia from three U.S. centers and one UK center constituted the test and validation cohorts, respectively. Cox proportional hazards regression was used to test the association between 5-year TFS and ⩾10% FVC decline, followed by 13 additional PPF criteria satisfied in the absence of ⩾10% FVC decline. Measurements and Main Results: One thousand three hundred forty-one patients met the inclusion criteria. A ⩾10% relative FVC decline was the strongest predictor of reduced TFS and showed consistent TFS association across cohorts, ILD subtypes, and treatment groups, resulting in a phenotype that closely resembled IPF. Ten additional PPF criteria satisfied in the absence of 10% relative FVC decline were also associated with reduced TFS in the U.S. test cohort, with 6 maintaining TFS associations in the UK validation cohort. Validated PPF criteria requiring a combination of physiologic, radiologic, and symptomatic worsening performed similarly to their stand-alone components but captured a smaller number of patients. Conclusions: An FVC decline of ⩾10% and six additional PPF criteria satisfied in the absence of such decline identify patients with non-IPF ILD at increased risk for death or lung transplantation.

Proteomic biomarkers of progressive fibrosing interstitial lung disease: a multicentre cohort analysis.

BACKGROUND: Progressive fibrosing interstitial lung disease (ILD) is characterised by parenchymal scar formation, leading to high morbidity and mortality. The ability to predict this phenotype remains elusive. We conducted a proteomic analysis to identify novel plasma biomarkers of progressive fibrosing ILD and developed a proteomic signature to predict this phenotype. METHODS: Relative plasma concentrations for 368 biomarkers were determined with use of a semi-quantitative, targeted proteomic platform in patients with connective tissue disease-associated ILD, chronic hypersensitivity pneumonitis, or unclassifiable ILD who provided research blood draws at the University of California (discovery cohort) and the University of Texas (validation cohort). Univariable logistic regression was used to identify individual biomarkers associated with 1-year ILD progression, defined as death, lung transplant, or 10% or greater relative forced vital capacity (FVC) decline. A proteomic signature of progressive fibrosing ILD was then derived with use of machine learning in the University of California cohort and validated in the University of Texas cohort. FINDINGS: The discovery cohort comprised 385 patients (mean age 63·6 years, 59% female) and the validation cohort comprised 204 patients (mean age 60·7 years, 61% female). 31 biomarkers were associated with progressive fibrosing ILD in the discovery cohort, with 17 maintaining an association in the validation cohort. Validated biomarkers showed a consistent association with progressive fibrosing ILD irrespective of ILD clinical diagnosis. A proteomic signature comprising 12 biomarkers was derived by machine learning and validated in the University of Texas cohort, in which it had a sensitivity of 0·90 and corresponding negative predictive value of 0·91, suggesting that approximately 10% of patients with a low-risk proteomic signature would experience ILD progression in the year after blood draw. Those with a low-risk proteomic signature experienced an FVC change of +85·7 mL (95% CI 6·9 to 164·4) and those with a high-risk signature experienced an FVC change of -227·1 mL (-286·7 to -167·5). A theoretical clinical trial restricted to patients with a high-risk proteomic signature would require 80% fewer patients than one designed without regard to proteomic signature. INTERPRETATION: 17 plasma biomarkers of progressive fibrosing ILD were identified and showed consistent associations across ILD subtypes. A proteomic signature of progressive fibrosing ILD could enrich clinical trial cohorts and avoid the need for antecedent progression when defining progressive fibrosing ILD for clinical trial enrolment. FUNDING: National Heart Lung and Blood Institute.

Lung function trajectory in progressive fibrosing interstitial lung disease.

BACKGROUND: Proposed criteria for progressive fibrosing interstitial lung disease (PF-ILD) have been linked to increased mortality risk, but lung function trajectory after satisfying individual criteria remains unknown. Because survival is rarely employed as the primary end-point in therapeutic trials, identifying PF-ILD criteria that best predict subsequent change in forced vital capacity (FVC) could improve clinical trial design. METHODS: A retrospective, multicentre longitudinal cohort analysis was performed in consecutive patients with fibrotic connective tissue disease-associated ILD (CTD-ILD), chronic hypersensitivity pneumonitis and idiopathic interstitial pneumonia at three US centres (test cohort) and one UK centre (validation cohort). 1-year change in FVC after satisfying proposed PF-ILD criteria was estimated using joint modelling. Subgroup analyses were performed to determine whether results varied across key subgroups. RESULTS: 1227 patients were included, with CTD-ILD predominating. Six out of nine PF-ILD criteria were associated with differential 1-year change in FVC, with radiological progression of fibrosis, alone and in combination with other features, associated with the largest subsequent decline in FVC. Findings varied significantly by ILD subtype, with CTD-ILD demonstrating little change in FVC after satisfying most PF-ILD criteria, while other ILDs showed significantly larger changes. Findings did not vary after stratification by radiological pattern or exposure to immunosuppressant therapy. Near-term change in FVC after satisfying proposed PF-ILD criteria was heterogeneous depending on the criterion assessed and was strongly influenced by ILD subtype. CONCLUSIONS: These findings may inform future clinical trial design and suggest ILD subtype should be taken into consideration when applying PF-ILD criteria.

Family History of Pulmonary Fibrosis Predicts Worse Survival in Patients With Interstitial Lung Disease.

BACKGROUND: A number of genetic markers linked to familial pulmonary fibrosis predict differential survival in interstitial lung disease (ILD) patients. Although genetic testing is not performed routinely for ILD, family history commonly is obtained and may inform outcome risk. RESEARCH QUESTION: Does survival vary between patients with and without self-reported familial pulmonary fibrosis? METHODS: Family history was acquired systematically for consecutive ILD patients who consented to clinical registry enrollment at the University of Texas Southwestern and the University of California at Davis. Patients were stratified by idiopathic pulmonary fibrosis (IPF) and non-IPF ILD diagnosis and were substratified by presence or absence of familial pulmonary fibrosis, defined as one or more additional affected family members. Transplant-free survival was compared using multilevel, mixed-effects Cox proportional hazards regression. RESULTS: Of the 1,262 patients included, 534 (42%) had IPF ILD and 728 (58%) had non-IPF ILD. Of those with non-IPF ILD, 18.5% had connective tissue disease, 15.6% had chronic hypersensitivity pneumonitis, and 23.5% had unclassifiable ILD. Familial pulmonary fibrosis was reported in 134 IPF ILD patients (25.1%) and 90 non-IPF ILD patients (12.4%). Those with familial IPF showed an 80% increased risk of death or transplantation compared with those with sporadic IPF (hazard ratio [HR], 1.8; 95% CI, 1.37-2.37; P < .001), whereas those with familial non-IPF ILD showed a twofold increased risk compared with their counterparts with sporadic disease (HR, 2.08; 95% CI, 1.46-2.96; P < .001). Outcome risk among those with familial non-IPF ILD was no different than for those with sporadic IPF ILD (HR, 1.27; 95% CI, 0.89-1.84; P = .19). INTERPRETATION: Patient-reported familial pulmonary fibrosis is predictive of reduced transplant-free survival in IPF and non-IPF ILD patients. Because survival among patients with familial non-IPF ILD approximates that of sporadic IPF ILD, early intervention should be considered for such patients. Until clinical genetic testing is widely available and provides actionable results, family history should be ascertained and considered in risk stratification.

Investigation of nosocomial SARS-CoV-2 transmission from two patients to healthcare workers identifies close contact but not airborne transmission events.

OBJECTIVE: To describe the pattern of transmission of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) during 2 nosocomial outbreaks of coronavirus disease 2019 (COVID-19) with regard to the possibility of airborne transmission. DESIGN: Contact investigations with active case finding were used to assess the pattern of spread from 2 COVID-19 index patients. SETTING: A community hospital and university medical center in the United States, in February and March, 2020, early in the COVID-19 pandemic. PATIENTS: Two index patients and 421 exposed healthcare workers. METHODS: Exposed healthcare workers (HCWs) were identified by analyzing the electronic medical record (EMR) and conducting active case finding in combination with structured interviews. Healthcare coworkers (HCWs) were tested for COVID-19 by obtaining oropharyngeal/nasopharyngeal specimens, and RT-PCR testing was used to detect SARS-CoV-2. RESULTS: Two separate index patients were admitted in February and March 2020, without initial suspicion for COVID-19 and without contact or droplet precautions in place; both patients underwent several aerosol-generating procedures in this context. In total, 421 HCWs were exposed in total, and the results of the case contact investigations identified 8 secondary infections in HCWs. In all 8 cases, the HCWs had close contact with the index patients without sufficient personal protective equipment. Importantly, despite multiple aerosol-generating procedures, there was no evidence of airborne transmission. CONCLUSION: These observations suggest that, at least in a healthcare setting, most SARS-CoV-2 transmission is likely to take place during close contact with infected patients through respiratory droplets, rather than by long-distance airborne transmission.

Myositis-specific Antibodies Identify A Distinct Interstitial Pneumonia with Autoimmune Features Phenotype.

Interstitial pneumonia with autoimmune features (IPAF) characterises individuals with interstitial lung disease (ILD) and features of connective tissue disease (CTD) who fail to satisfy CTD criteria. Inclusion of myositis-specific antibodies (MSAs) in the IPAF criteria has generated controversy, as these patients also meet proposed criteria for an anti-synthetase syndrome. Whether MSAs and myositis associated antibodies (MAA) identify phenotypically distinct IPAF subgroups remains unclear.A multi-center, retrospective investigation was conducted to assess clinical features and outcomes in patients meeting IPAF criteria stratified by the presence of MSAs and MAAs. IPAF subgroups were compared to cohorts of patients with idiopathic inflammatory myopathy-ILD (IIM-ILD), idiopathic pulmonary fibrosis (IPF) and non-IIM CTD-ILDs. The primary endpoint assessed was three-year transplant-free survival. Two hundred sixty-nine patients met IPAF criteria, including 35 (13%) with MSAs and 65 (24.2%) with MAAs. Survival was highest among patients with IPAF-MSA and closely approximated those with IIM-ILD. Survival did not differ between IPAF-MAA and IPAF without MSA/MAA cohorts. Usual interstitial pneumonia (UIP) morphology was associated with differential outcome risk, with IPAF patients with non-UIP morphology approximating survival observed in non-IIM CTD-ILDs. MSAs, but not MAAs identified a unique IPAF phenotype characterised by clinical features and outcomes similar to IIM-ILD. UIP morphology was a strong predictor of outcome in others meeting IPAF criteria. Because IPAF is a research classification without clear treatment approach, these findings suggest MSAs should be removed from the IPAF criteria and such patients should be managed as an IIM-ILD.