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Background: The Gender, Age and Physiology (GAP) model is a simple mortality prediction tool in patients with idiopathic pulmonary fibrosis that uses demographic and physiological variables available at initial evaluation. White blood cell variables may have associations with idiopathic pulmonary fibrosis outcomes. We evaluated whether incorporating blood cell counts in modified GAP (cGAP) models would improve outcome prediction in patients with idiopathic pulmonary fibrosis. Patients and methods: This retrospective analysis included pooled data from phase 3 randomised trials of pirfenidone in idiopathic pulmonary fibrosis (ASCEND, CAPACITY 004, CAPACITY 006). Study outcomes (disease progression, all-cause mortality, all-cause hospitalisation, respiratory-related hospitalisation) were evaluated during the initial 1-year period. Shared frailty models were used to evaluate associations between continuous and categorical baseline white and red blood cell parameters and study outcomes in a bivariate context, and to evaluate the impact of adding continuous monocyte count (cGAP1) or white and red blood cell parameters (cGAP2) to traditional GAP variables in a multivariable context based on C-statistics changes. Results: Data were pooled from 1247 patients (pirfenidone, n=623; placebo, n=624). Significant associations (bivariate analyses) were idiopathic pulmonary fibrosis progression with neutrophil and eosinophil counts; all-cause mortality with monocyte and neutrophil counts; all-cause hospitalisation with monocyte count, neutrophil count and haemoglobin level; and respiratory-related hospitalisation with monocyte count, neutrophil count and haemoglobin level. In multivariate analyses, C-statistics were highest for the cGAP2 model for each of the outcomes. Conclusion: Modified GAP models incorporating monocyte counts alone or plus other white and red blood cell variables may be useful to improve prediction of outcomes in patients with idiopathic pulmonary fibrosis.
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Rationale: Idiopathic pulmonary fibrosis (IPF) causes irreversible fibrosis of the lung parenchyma. Although antifibrotic therapy can slow IPF progression, treatment response is variable. There exists a critical need to develop a precision medicine approach to IPF. Objectives: To identify and validate biologically driven molecular endotypes of IPF. Methods: Latent class analysis (LCA) was independently performed in prospectively recruited discovery (n = 875) and validation (n = 347) cohorts. Twenty-five plasma biomarkers associated with fibrogenesis served as class-defining variables. The association between molecular endotype and 4-year transplant-free survival was tested using multivariable Cox regression adjusted for baseline confounders. Endotype-dependent differential treatment response to future antifibrotic exposure was then assessed in a pooled cohort of patients naive to antifibrotic therapy at the time of biomarker measurement (n = 555). Measurements and Main Results: LCA independently identified two latent classes in both cohorts (P < 0.0001). WFDC2 (WAP four-disulfide core domain protein 2) was the most important determinant of class membership across cohorts. Membership in class 2 was characterized by higher biomarker concentrations and a higher risk of death or transplant (discovery, hazard ratio [HR], 2.02; 95% confidence interval [CI], 1.64-2.48; P < 0.001; validation, HR, 1.95; 95% CI, 1.34-2.82; P < 0.001). In pooled analysis, significant heterogeneity in treatment effect was observed between endotypes (P = 0.030 for interaction), with a favorable antifibrotic response in class 2 (HR, 0.64; 95% CI, 0.45-0.93; P = 0.018) but not in class 1 (HR, 1.19; 95% CI, 0.77-1.84; P = 0.422). Conclusions: In this multicohort study, we identified two novel molecular endotypes of IPF with divergent clinical outcomes and responses to antifibrotic therapy. Pending further validation, these endotypes could enable a precision medicine approach for future IPF clinical trials.
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Biomarcadores , Fibrose Pulmonar Idiopática , Análise de Classes Latentes , Humanos , Fibrose Pulmonar Idiopática/sangue , Fibrose Pulmonar Idiopática/mortalidade , Masculino , Feminino , Pessoa de Meia-Idade , Biomarcadores/sangue , Idoso , Estudos de Coortes , Estudos ProspectivosRESUMO
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 (IPF) 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 (COPD) 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. RESULTS: Twenty-two proteins mediated the chronological age-survival relationship after adjustment for false discovery in the IPF discovery cohort (n=874), with nineteen remaining significant mediators of this relationship in the ILD validation cohort (n=983) and one mediating this relationship in the COPD cohort. Latent transforming growth factor beta 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.
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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.
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Doenças do Tecido Conjuntivo , Imunossupressores , Doenças Pulmonares Intersticiais , Doenças Pulmonares Intersticiais/etiologia , Doenças Pulmonares Intersticiais/terapia , Humanos , Doenças do Tecido Conjuntivo/complicações , Doenças do Tecido Conjuntivo/terapia , Imunossupressores/uso terapêutico , Transplante de Pulmão , Progressão da Doença , Transplante de Células-Tronco , Síndrome de Sjogren/complicações , Síndrome de Sjogren/terapia , Escleroderma Sistêmico/complicações , Escleroderma Sistêmico/terapia , Artrite Reumatoide/complicações , Ensaios Clínicos Controlados Aleatórios como Assunto , Miosite/complicações , Miosite/terapiaRESUMO
Recent genetic and genomic advancements have elucidated the complex etiology of idiopathic pulmonary fibrosis (IPF) and other progressive fibrotic interstitial lung diseases (ILDs), emphasizing the contribution of heritable factors. This state-of-the-art review synthesizes evidence on significant genetic contributors to pulmonary fibrosis (PF), including rare genetic variants and common SNPs. The MUC5B promoter variant is unusual, a common SNP that markedly elevates the risk of early and established PF. We address the utility of genetic variation in enhancing understanding of disease pathogenesis and clinical phenotypes, improving disease definitions, and informing prognosis and treatment response. Critical research gaps are highlighted, particularly the underrepresentation of non-European ancestries in PF genetic studies and the exploration of PF phenotypes beyond usual interstitial pneumonia/IPF. We discuss the role of telomere length, often critically short in PF, and its link to progression and mortality, underscoring the genetic complexity involving telomere biology genes (TERT, TERC) and others like SFTPC and MUC5B. In addition, we address the potential of gene-by-environment interactions to modulate disease manifestation, advocating for precision medicine in PF. Insights from gene expression profiling studies and multiomic analyses highlight the promise for understanding disease pathogenesis and offer new approaches to clinical care, therapeutic drug development, and biomarker discovery. Finally, we discuss the ethical, legal, and social implications of genomic research and therapies in PF, stressing the need for sound practices and informed clinical genetic discussions. Looking forward, we advocate for comprehensive genetic testing panels and polygenic risk scores to improve the management of PF and related ILDs across diverse populations.
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Genômica , Fibrose Pulmonar Idiopática , Mucina-5B , Medicina de Precisão , Humanos , Medicina de Precisão/métodos , Fibrose Pulmonar Idiopática/genética , Fibrose Pulmonar Idiopática/terapia , Mucina-5B/genética , Predisposição Genética para Doença/genética , Fibrose Pulmonar/genética , Fibrose Pulmonar/terapia , Polimorfismo de Nucleotídeo Único/genéticaRESUMO
Idiopathic pulmonary fibrosis (IPF) is characterized by progressive scarring and loss of lung function. With limited treatment options, patients succumb to the disease within 2-5 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 IL-17, 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 (AHR Δex2 ) with mice harboring a CD11c-Cre. Bleomycin 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, AHR Δex2 mice treated with bleomycin 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. Study of human samples corroborate 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.
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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.
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Fibrose Pulmonar Idiopática , Transplante de Pulmão , Encaminhamento e Consulta , Humanos , Masculino , Feminino , Pessoa de Meia-Idade , Estudos Prospectivos , Fibrose Pulmonar Idiopática/cirurgia , Fibrose Pulmonar Idiopática/classificação , Fibrose Pulmonar Idiopática/diagnóstico , Fibrose Pulmonar Idiopática/sangue , Idoso , ProteômicaRESUMO
Rationale: Despite evidence demonstrating a prognostic role for computed tomography (CT) scans in idiopathic pulmonary fibrosis (IPF), image-based biomarkers are not routinely used in clinical practice or trials. Objectives: To develop automated imaging biomarkers using deep learning-based segmentation of CT scans. Methods: We developed segmentation processes for four anatomical biomarkers, which were applied to a unique cohort of treatment-naive patients with IPF enrolled in the PROFILE (Prospective Observation of Fibrosis in the Lung Clinical Endpoints) study and tested against a further United Kingdom cohort. The relationships among CT biomarkers, lung function, disease progression, and mortality were assessed. Measurements and Main Results: Data from 446 PROFILE patients were analyzed. Median follow-up duration was 39.1 months (interquartile range, 18.1-66.4 mo), with a cumulative incidence of death of 277 (62.1%) over 5 years. Segmentation was successful on 97.8% of all scans, across multiple imaging vendors, at slice thicknesses of 0.5-5 mm. Of four segmentations, lung volume showed the strongest correlation with FVC (r = 0.82; P < 0.001). Lung, vascular, and fibrosis volumes were consistently associated across cohorts with differential 5-year survival, which persisted after adjustment for baseline gender, age, and physiology score. Lower lung volume (hazard ratio [HR], 0.98 [95% confidence interval (CI), 0.96-0.99]; P = 0.001), increased vascular volume (HR, 1.30 [95% CI, 1.12-1.51]; P = 0.001), and increased fibrosis volume (HR, 1.17 [95% CI, 1.12-1.22]; P < 0.001) were associated with reduced 2-year progression-free survival in the pooled PROFILE cohort. Longitudinally, decreasing lung volume (HR, 3.41 [95% CI, 1.36-8.54]; P = 0.009) and increasing fibrosis volume (HR, 2.23 [95% CI, 1.22-4.08]; P = 0.009) were associated with differential survival. Conclusions: Automated models can rapidly segment IPF CT scans, providing prognostic near and long-term information, which could be used in routine clinical practice or as key trial endpoints.
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Aprendizado Profundo , Progressão da Doença , Fibrose Pulmonar Idiopática , Tomografia Computadorizada por Raios X , Humanos , Fibrose Pulmonar Idiopática/diagnóstico por imagem , Fibrose Pulmonar Idiopática/mortalidade , Masculino , Feminino , Tomografia Computadorizada por Raios X/métodos , Idoso , Pessoa de Meia-Idade , Estudos Prospectivos , Prognóstico , Reino Unido , Pulmão/diagnóstico por imagem , Pulmão/patologia , Valor Preditivo dos Testes , Estudos de CoortesRESUMO
Rationale: Distinguishing connective tissue disease-associated interstitial lung disease (CTD-ILD) from idiopathic pulmonary fibrosis (IPF) can be clinically challenging. Objectives: To identify proteins that separate and classify patients with CTD-ILD and those with IPF. Methods: Four registries with 1,247 patients with IPF and 352 patients with CTD-ILD were included in analyses. Plasma samples were subjected to high-throughput proteomics assays. Protein features were prioritized using recursive feature elimination to construct a proteomic classifier. Multiple machine learning models, including support vector machine, LASSO (least absolute shrinkage and selection operator) regression, random forest, and imbalanced Random Forest, were trained and tested in independent cohorts. The validated models were used to classify each case iteratively in external datasets. Measurements and Main Results: A classifier with 37 proteins (proteomic classifier 37 [PC37]) was enriched in the 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 areas under the curve of 0.85-0.90 in the 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 the test cohort and 93.5-96.1% sensitivity and 69.5-77.6% specificity in the single-sample classification dataset. Composite analysis of all machine learning models confirmed 78.2% (194 of 248) accuracy in the test cohort and 82.9% (208 of 251) in the single-sample classification dataset. Conclusions: Multiple machine learning models trained with large cohort proteomic datasets consistently distinguished CTD-ILD from IPF. Many of the identified proteins are 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.
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Doenças Pulmonares Intersticiais , Aprendizado de Máquina , Proteômica , Humanos , Doenças Pulmonares Intersticiais/sangue , Doenças Pulmonares Intersticiais/diagnóstico , Feminino , Masculino , Proteômica/métodos , Pessoa de Meia-Idade , Idoso , Fibrose Pulmonar Idiopática/sangue , Fibrose Pulmonar Idiopática/diagnóstico , Diagnóstico Diferencial , Doenças do Tecido Conjuntivo/sangue , Doenças do Tecido Conjuntivo/diagnóstico , Biomarcadores/sangueRESUMO
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.
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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.
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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.
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Aprendizado Profundo , Fibrose Pulmonar Idiopática , Doenças Pulmonares Intersticiais , Humanos , Estudos Retrospectivos , Radiômica , Doenças Pulmonares Intersticiais/diagnóstico por imagem , Pulmão/diagnóstico por imagem , Pulmão/patologiaRESUMO
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.