The peripheral blood transcriptome identifies the presence and extent of disease in idiopathic pulmonary fibrosis

SLC15A3 plays a crucial role in pulmonary fibrosis by regulating macrophage oxidative stress

Idiopathic pulmonary fibrosis (IPF) is a fatal and irreversible disease with few effective treatments. Alveolar macrophages (AMs) are involved in the development of IPF from the initial stages due to direct exposure to air and respond to external oxidative damage (a major inducement of pulmonary fibrosis). Oxidative stress in AMs plays an indispensable role in promoting fibrosis development. The oligopeptide histidine transporter SLC15A3, mainly expressed on the lysosomal membrane of macrophages and highly expressed in the lung, has proved to be involved in innate immune and antiviral signaling pathways. In this study, we demonstrated that during bleomycin (BLM)- or radiation-induced pulmonary fibrosis, the recruitment of macrophages induced an increase of SLC15A3 in the lung, and the deficiency of SLC15A3 protected mice from pulmonary fibrosis and maintained the homeostasis of the pulmonary microenvironment. Mechanistically, deficiency of SLC15A3 resisted oxidative stress in macrophages, and SLC15A3 interacted with the scaffold protein p62 to regulate its expression and phosphorylation activation, thereby regulating p62-nuclear factor erythroid 2-related factor 2 (NRF2) antioxidant stress pathway protein, which is related to the production of reactive oxygen species (ROS). Overall, our data provided a novel mechanism for targeting SLC15A3 to regulate oxidative stress in macrophages, supporting the therapeutic potential of inhibiting or silencing SLC15A3 for the precautions and treatment of pulmonary fibrosis.

A Call for Gene Expression Analysis in Whole Blood of Patients With Rheumatoid Arthritis (RA) as a Biomarker for RA-Associated Interstitial Lung Disease

OBJECTIVE

Rheumatoid arthritis (RA)-associated interstitial lung disease (ILD) is one of the most common and prognostic organ manifestations of RA. Therefore, to allow effective treatment, it is of crucial importance to diagnose RA-ILD at the earliest possible stage. So far, the gold standard of early detection has been high-resolution computed tomography (HRCT) of the lungs. This procedure involves considerable radiation exposure for the patient and is therefore unsuitable as a routine screening measure for ethical reasons. Here, we propose the analysis of characteristic gene expression patterns as a biomarker to aid in the early detection and initiation of appropriate, possibly antifibrotic, therapy.

METHODS

To investigate unique molecular patterns of RA-ILD, whole blood samples were taken from 12 female patients with RA-ILD (n = 7) or RA (n = 5). The RNA was extracted, sequenced by RNA-Seq, and analyzed for characteristic differences in the gene expression patterns between patients with RA-ILD and those with RA without ILD.

RESULTS

The differential gene expression analysis revealed 9 significantly upregulated genes in RA-ILD compared to RA without ILD: arginase 1 (ARG1), thymidylate synthetase (TYMS), sortilin 1 (SORT1), marker of proliferation Ki-67 (MKI67), olfactomedin 4 (OLFM4), baculoviral inhibitor of apoptosis repeat containing 5 (BIRC5), membrane spanning 4-domains A4A (MS4A4A), C-type lectin domain family 12 member A (CLEC12A), and the long intergenic nonprotein coding RNA (LINC02967).

CONCLUSION

All gene products of these genes (except for LINC02967) are known from the literature to be involved in the pathogenesis of fibrosis. Further, for some, a contribution to the development of pulmonary fibrosis has even been demonstrated in experimental studies. Therefore, the results presented here provide an encouraging perspective for using specific gene expression patterns as biomarkers for the early detection and differential diagnosis of RA-ILD as a routine screening test.

Rationale and design of the prognostic transcriptomic signature in fibrotic hypersensitivity pneumonitis (PREDICT) study

Hypersensitivity pneumonitis is an immunologically mediated form of lung disease, resulting from inhalational exposure to a large variety of antigens. A subgroup of patients with fibrotic hypersensitivity pneumonitis (FHP) develop symptomatic, functional and radiographic disease progression. Mortality occurs primarily from respiratory failure as a result of progressive and self-sustaining lung injury that often occurs despite immunosuppression and removal of the inciting antigen. The development and validation of a prognostic transcriptomic signature for FHP (PREDICT-HP) is an observational multicentre cohort study designed to explore a transcriptomic signature from peripheral blood mononuclear cells in patients with FHP that is predictive of disease progression. This article describes the design and rationale of the PREDICT-HP study. This study will enrol ∼135 patients with FHP at approximately seven academic medical sites. Participants with a confirmed diagnosis of FHP are followed over 24 months and undergo physical examinations, self-administered questionnaires, chest computed tomography, pulmonary function tests, a 6-min walk test and blood testing for transcriptomic analyses. At each 6-month follow-up visit the study will assess the participants' clinical course and clinical events including hospitalisations and respiratory exacerbations. The PREDICT study has the potential to enhance our ability to predict disease progression and fundamentally advance our understanding of the pathobiology of FHP disease progression.

Bioinformatics approach to identify the hub gene associated with COVID-19 and idiopathic pulmonary fibrosis

The coronavirus disease 2019 (COVID-19) has developed into a global health crisis. Pulmonary fibrosis, as one of the complications of SARS-CoV-2 infection, deserves attention. As COVID-19 is a new clinical entity that is constantly evolving, and many aspects of disease are remain unknown. The datasets of COVID-19 and idiopathic pulmonary fibrosis were obtained from the Gene Expression Omnibus. The hub genes were screened out using the Random Forest (RF) algorithm depending on the severity of patients with COVID-19. A risk prediction model was developed to assess the prognosis of patients infected with SARS-CoV-2, which was evaluated by another dataset. Six genes (named NELL2, GPR183, S100A8, ALPL, CD177, and IL1R2) may be associated with the development of PF in patients with severe SARS-CoV-2 infection. S100A8 is thought to be an important target gene that is closely associated with COVID-19 and pulmonary fibrosis. Construction of a neural network model was successfully predicted the prognosis of patients with COVID-19. With the increasing availability of COVID-19 datasets, bioinformatic methods can provide possible predictive targets for the diagnosis, treatment, and prognosis of the disease and show intervention directions for the development of clinical drugs and vaccines.

Cluster analysis of transcriptomic datasets to identify endotypes of idiopathic pulmonary fibrosis

BACKGROUND

Considerable clinical heterogeneity in idiopathic pulmonary fibrosis (IPF) suggests the existence of multiple disease endotypes. Identifying these endotypes would improve our understanding of the pathogenesis of IPF and could allow for a biomarker-driven personalised medicine approach. We aimed to identify clinically distinct groups of patients with IPF that could represent distinct disease endotypes.

METHODS

We co-normalised, pooled and clustered three publicly available blood transcriptomic datasets (total 220 IPF cases). We compared clinical traits across clusters and used gene enrichment analysis to identify biological pathways and processes that were over-represented among the genes that were differentially expressed across clusters. A gene-based classifier was developed and validated using three additional independent datasets (total 194 IPF cases).

FINDINGS

We identified three clusters of patients with IPF with statistically significant differences in lung function (p=0.009) and mortality (p=0.009) between groups. Gene enrichment analysis implicated mitochondrial homeostasis, apoptosis, cell cycle and innate and adaptive immunity in the pathogenesis underlying these groups. We developed and validated a 13-gene cluster classifier that predicted mortality in IPF (high-risk clusters vs low-risk cluster: HR 4.25, 95% CI 2.14 to 8.46, p=3.7×10-5).

INTERPRETATION

We have identified blood gene expression signatures capable of discerning groups of patients with IPF with significant differences in survival. These clusters could be representative of distinct pathophysiological states, which would support the theory of multiple endotypes of IPF. Although more work must be done to confirm the existence of these endotypes, our classifier could be a useful tool in patient stratification and outcome prediction in IPF.

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.

Toward a Systematic Assessment of Sex Differences in Cystic Fibrosis

(1) Background: Cystic fibrosis (CF) is a disease with well-documented clinical differences between female and male patients. However, this gender gap is very poorly studied at the molecular level. (2) Methods: Expression differences in whole blood transcriptomics between female and male CF patients are analyzed in order to determine the pathways related to sex-biased genes and assess their potential influence on sex-specific effects in CF patients. (3) Results: We identify sex-biased genes in female and male CF patients and provide explanations for some sex-specific differences at the molecular level. (4) Conclusion: Genes in key pathways associated with CF are differentially expressed between sexes, and thus may account for the gender gap in morbidity and mortality in CF.

Integrative bioinformatics and validation studies reveal KDM6B and its associated molecules as crucial modulators in Idiopathic Pulmonary Fibrosis

Background

Idiopathic Pulmonary Fibrosis (IPF) can be described as a debilitating lung disease that is characterized by the complex interactions between various immune cell types and signaling pathways. Chromatin-modifying enzymes are significantly involved in regulating gene expression during immune cell development, yet their role in IPF is not well understood.

Methods

In this study, differential gene expression analysis and chromatin-modifying enzyme-related gene data were conducted to identify hub genes, common pathways, immune cell infiltration, and potential drug targets for IPF. Additionally, a murine model was employed for investigating the expression levels of candidate hub genes and determining the infiltration of different immune cells in IPF.

Results

We identified 33 differentially expressed genes associated with chromatin-modifying enzymes. Enrichment analyses of these genes demonstrated a strong association with histone lysine demethylation, Sin3-type complexes, and protein demethylase activity. Protein-protein interaction network analysis further highlighted six hub genes, specifically KDM6B, KDM5A, SETD7, SUZ12, HDAC2, and CHD4. Notably, KDM6B expression was significantly increased in the lungs of bleomycin-induced pulmonary fibrosis mice, showing a positive correlation with fibronectin and α-SMA, two essential indicators of pulmonary fibrosis. Moreover, we established a diagnostic model for IPF focusing on KDM6B and we also identified 10 potential therapeutic drugs targeting KDM6B for IPF treatment.

Conclusion

Our findings suggest that molecules related to chromatin-modifying enzymes, primarily KDM6B, play a critical role in the pathogenesis and progression of IPF.

Biochemical and genomic identification of novel biomarkers in progressive sarcoidosis: HBEGF, eNAMPT, and ANG-2

Background

Progressive pulmonary fibrosis is a serious complication in subjects with sarcoidosis. The absence of reliable, non-invasive biomarkers that detect early progression exacerbates the difficulty in predicting sarcoidosis severity. To potentially address this unmet need, we evaluated a panel of markers for an association with sarcoidosis progression (HBEGF, NAMPT, IL1-RA, IL-6, IL-8, ANG-2). This panel encompasses proteins related to inflammation, vascular injury, cell proliferation, and fibroblast mitogenesis processes.

Methods

Plasma biomarker levels and biomarker protein expression in lung and lymph nodes tissues (immunohistochemical studies) from sarcoidosis subjects with limited disease and progressive (complicated) sarcoidosis were performed. Gene expression of the protein-coding genes included in this panel was analyzed using RNAseq in sarcoidosis granulomatous tissues from lung and lymph nodes.

Results

Except for IL-8, plasma levels of each biomarker—eNAMPT, IL-1RA, IL-6, ANG-2, and HBEGF—were significantly elevated in sarcoidosis subjects compared to controls. In addition, plasma levels of HBEGF were elevated in complicated sarcoidosis, while eNAMPT and ANG-2 were observed to serve as markers of lung fibrosis in a subgroup of complicated sarcoidosis. Genomic studies corroborated HBEGF and NAMPT among the top dysregulated genes and identified cytokine-related and fibrotic pathways in lung granulomatous tissues from sarcoidosis.

Conclusion

These findings suggest HBEGF, eNAMPT, and ANG-2 may serve as potential novel indicators of the clinical severity of sarcoidosis disease.

At-home blood collection and stabilization in high temperature climates using homeRNA

Expanding whole blood sample collection for transcriptome analysis beyond traditional phlebotomy clinics will open new frontiers for remote immune research and telemedicine. Determining the stability of RNA in blood samples exposed to high ambient temperatures (>30°C) is necessary for deploying home-sampling in settings with elevated temperatures (e.g., studying physiological response to natural disasters that occur in warm locations or in the summer). Recently, we have developed homeRNA, a technology that allows for self-blood sampling and RNA stabilization remotely. homeRNA consists of a lancet-based blood collection device, the Tasso-SST™ which collects up to 0.5 ml of blood from the upper arm, and a custom-built stabilization transfer tube containing RNAlater™. In this study, we investigated the robustness of our homeRNA kit in high temperature settings via two small pilot studies in Doha, Qatar (no. participants = 8), and the Western and South Central USA during the summer of 2021, which included a heatwave of unusually high temperatures in some locations (no. participants = 11). Samples collected from participants in Doha were subjected to rapid external temperature fluctuations from being moved to and from air-conditioned areas and extreme heat environments (up to 41°C external temperature during brief temperature spikes). In the USA pilot study, regions varied in outdoor temperature highs (between 25°C and 43.4°C). All samples that returned a RNA integrity number (RIN) value from the Doha, Qatar group had a RIN ≥7.0, a typical integrity threshold for downstream transcriptomics analysis. RIN values for the Western and South Central USA samples (n = 12 samples) ranged from 6.9–8.7 with 9 out of 12 samples reporting RINs ≥7.0. Overall, our pilot data suggest that homeRNA can be used in some regions that experience elevated temperatures, opening up new geographical frontiers in disseminated transcriptome analysis for applications critical to telemedicine, global health, and expanded clinical research. Further studies, including our ongoing work in Qatar, USA, and Thailand, will continue to test the robustness of homeRNA.

Alterations in Immune-Related Defensin Alpha 4 (DEFA4) Gene Expression in Health and Disease

Defensin Alpha 4 (DEFA4) is the fourth member of the Alpha Defensins family known as a part of antimicrobial peptides in the innate immune system. DEFA4 has a strong preference to kill Gram-negative bacteria more than Gram-positive bacteria. In addition, DEFA4 exhibits antiviral activity against human immunodeficiency virus type 1 (HIV-1) in vitro. Moreover, DEFA4 can act as an inhibitor of corticosterone production (Corticostatin). On the other hand, alternations in DEFA4 gene expression have been reported in different disorders such as diseases related to inflammation and immunity dysfunction, brain-related disorders, and various cancers. The up-regulation of DEFA4 appears to be involved in the malignant transformation or aggressive form of cancer. Interestingly, the modified version of DEFA4 fragment (1-11) was potent and efficient against antibiotic-resistant bacteria. This review provides a general background abSaudi Arabia out DEFA4 and sheds light on changes in DEFA4 gene expression in different diseases. The paper also discusses other aspects related to DEFA4 as an antimicrobial and antiviral agent. The research was conducted based on available articles obtained from databases starting from 1988 to the present.

Inhibition of lung microbiota-derived proapoptotic peptides ameliorates acute exacerbation of pulmonary fibrosis

Idiopathic pulmonary fibrosis is an incurable disease of unknown etiology. Acute exacerbation of idiopathic pulmonary fibrosis is associated with high mortality. Excessive apoptosis of lung epithelial cells occurs in pulmonary fibrosis acute exacerbation. We recently identified corisin, a proapoptotic peptide that triggers acute exacerbation of pulmonary fibrosis. Here, we provide insights into the mechanism underlying the processing and release of corisin. Furthermore, we demonstrate that an anticorisin monoclonal antibody ameliorates lung fibrosis by significantly inhibiting acute exacerbation in the human transforming growth factorβ1 model and acute lung injury in the bleomycin model. By investigating the impact of the anticorisin monoclonal antibody in a general model of acute lung injury, we further unravel the potential of corisin to impact such diseases. These results underscore the role of corisin in the pathogenesis of acute exacerbation of pulmonary fibrosis and acute lung injury and provide a novel approach to treating this incurable disease.

PACSIN proteins in vivo: Roles in development and physiology

Protein kinase C and casein kinase substrate in neurons (PACSINs), or syndapins (synaptic dynamin‐associated proteins), are a family of proteins involved in the regulation of cell cytoskeleton, intracellular trafficking and signalling. Over the last twenty years, PACSINs have been mostly studied in the in vitro and ex vivo settings, and only in the last decade reports on their function in vivo have emerged. We first summarize the identification, structure and cellular functions of PACSINs, and then focus on the relevance of PACSINs in vivo. During development in various model organisms, PACSINs participate in diverse processes, such as neural crest cell development, gastrulation, laterality development and neuromuscular junction formation. In mouse, PACSIN2 regulates angiogenesis during retinal development and in human, PACSIN2 associates with monosomy and embryonic implantation. In adulthood, PACSIN1 has been extensively studied in the brain and shown to regulate neuromorphogenesis, receptor trafficking and synaptic plasticity. Several genetic studies suggest a role for PACSIN1 in the development of schizophrenia, which is also supported by the phenotype of mice depleted of PACSIN1. PACSIN2 plays an essential role in the maintenance of intestinal homeostasis and participates in kidney repair processes after injury. PACSIN3 is abundant in muscle tissue and necessary for caveolar biogenesis to create membrane reservoirs, thus controlling muscle function, and has been linked to certain genetic muscular disorders. The above examples illustrate the importance of PACSINs in diverse physiological or tissue repair processes in various organs, and associations to diseases when their functions are disturbed.

CD247, a Potential T Cell-Derived Disease Severity and Prognostic Biomarker in Patients With Idiopathic Pulmonary Fibrosis

Background

Idiopathic pulmonary fibrosis (IPF) has high mortality worldwide. The CD247 molecule (CD247, as known as T-cell surface glycoprotein CD3 zeta chain) has been reported as a susceptibility locus in systemic sclerosis, but its correlation with IPF remains unclear.

Methods

Datasets were acquired by researching the Gene Expression Omnibus (GEO). CD247 was identified as the hub gene associated with percent predicted diffusion capacity of the lung for carbon monoxide (Dlco% predicted) and prognosis according to Pearson correlation, logistic regression, and survival analysis.

Results

CD247 is significantly downregulated in patients with IPF compared with controls in both blood and lung tissue samples. Moreover, CD247 is significantly positively associated with Dlco% predicted in blood and lung tissue samples. Patients with low-expression CD247 had shorter transplant-free survival (TFS) time and more composite end-point events (CEP, death, or decline in FVC >10% over a 6-month period) compared with patients with high-expression CD247 (blood). Moreover, in the follow-up 1st, 3rd, 6th, and 12th months, low expression of CD247 was still the risk factor of CEP in the GSE93606 dataset (blood). Thirteen genes were found to interact with CD247 according to the protein-protein interaction network, and the 14 genes including CD247 were associated with the functions of T cells and natural killer (NK) cells such as PD-L1 expression and PD-1 checkpoint pathway and NK cell-mediated cytotoxicity. Furthermore, we also found that a low expression of CD247 might be associated with a lower activity of TIL (tumor-infiltrating lymphocytes), checkpoint, and cytolytic activity and a higher activity of macrophages and neutrophils.

Conclusion

These results imply that CD247 may be a potential T cell-derived disease severity and prognostic biomarker for IPF.

Molecular Signatures of Idiopathic Pulmonary Fibrosis

Molecular patterns and pathways in idiopathic pulmonary fibrosis (IPF) have been extensively investigated, but few studies have assimilated multiomic platforms to provide an integrative understanding of molecular patterns that are relevant in IPF. Herein, we combine the coding and noncoding transcriptomes, DNA methylomes, and proteomes from IPF and healthy lung tissue to identify molecules and pathways associated with this disease. RNA sequencing, Illumina MethylationEPIC array, and liquid chromatography-mass spectrometry proteomic data were collected on lung tissue from 24 subjects with IPF and 14 control subjects. Significant differential features were identified by using linear models adjusting for age and sex, inflation, and bias when appropriate. Data Integration Analysis for Biomarker Discovery Using a Latent Component Method for Omics Studies was used for integrative multiomic analysis. We identified 4,643 differentially expressed transcripts aligning to 3,439 genes, 998 differentially abundant proteins, 2,500 differentially methylated regions, and 1,269 differentially expressed long noncoding RNAs (lncRNAs) that were significant after correcting for multiple tests (false discovery rate < 0.05). Unsupervised hierarchical clustering using 20 coding mRNA, protein, methylation, and lncRNA features with the highest loadings on the top latent variable from the four data sets demonstrates perfect separation of IPF and control lungs. Our analysis confirmed previously validated molecules and pathways known to be dysregulated in disease and implicated novel molecular features as potential drivers and modifiers of disease. For example, 4 proteins, 18 differentially methylated regions, and 10 lncRNAs were found to have strong correlations (|r| > 0.8) with MMP7 (matrix metalloproteinase 7). Therefore, by using a system biology approach, we have identified novel molecular relationships in IPF.

Prognostic accuracy of a peripheral blood transcriptome signature in chronic hypersensitivity pneumonitis

The prognostic value of peripheral blood mononuclear cell (PBMC) expression profiles, when used in patients with chronic hypersensitivity pneumonitis (CHP), as an adjunct to traditional clinical assessment is unknown. RNA-seq analysis on PBMC from 37 patients with CHP at initial presentation determined that (1) 74 differentially expressed transcripts at a 10% false discovery rate distinguished those with (n=10) and without (n=27) disease progression, defined as absolute FVC and/or diffusing capacity of the lungs for carbon monoxide (DLCO) decline of ≥10% and increased fibrosis on chest CT images within 24 months, and (2) classification models based on gene expression and clinical factors strongly outperform models based solely on clinical factors (baseline FVC%, DLCO% and chest CT fibrosis).

Blood Transcriptomics Predicts Progression of Pulmonary Fibrosis and Associated Natural Killer Cells

Rationale: Disease activity in idiopathic pulmonary fibrosis (IPF) remains highly variable, poorly understood, and difficult to predict. Objectives: To identify a predictor using short-term longitudinal changes in gene expression that forecasts future FVC decline and to characterize involved pathways and cell types. Methods: Seventy-four patients from COMET (Correlating Outcomes with Biochemical Markers to Estimate Time-Progression in IPF) cohort were dichotomized as progressors (≥10% FVC decline) or stable. Blood gene-expression changes within individuals were calculated between baseline and 4 months and regressed with future FVC status, allowing determination of expression variations, sample size, and statistical power. Pathway analyses were conducted to predict downstream effects and identify new targets. An FVC predictor for progression was constructed in COMET and validated using independent cohorts. Peripheral blood mononuclear single-cell RNA-sequencing data from healthy control subjects were used as references to characterize cell type compositions from bulk peripheral blood mononuclear RNA-sequencing data that were associated with FVC decline. Measurements and Main Results: The longitudinal model reduced gene-expression variations within stable and progressor groups, resulting in increased statistical power when compared with a cross-sectional model. The FVC predictor for progression anticipated patients with future FVC decline with 78% sensitivity and 86% specificity across independent IPF cohorts. Pattern recognition receptor pathways and mTOR pathways were downregulated and upregulated, respectively. Cellular deconvolution using single-cell RNA-sequencing data identified natural killer cells as significantly correlated with progression. Conclusions: Serial transcriptomic change predicts future FVC decline. An analysis of cell types involved in the progressor signature supports the novel involvement of natural killer cells in IPF progression.

A new computational drug repurposing method using established disease-drug pair knowledge

MOTIVATION

Drug repurposing is a potential alternative to the classical drug discovery pipeline. Repurposing involves finding novel indications for already approved drugs. In this work, we present a novel machine learning-based method for drug repurposing. This method explores the anti-similarity between drugs and a disease to uncover new uses for the drugs. More specifically, our proposed method takes into account three sources of information: (i) large-scale gene expression profiles corresponding to human cell lines treated with small molecules, (ii) gene expression profile of a human disease and (iii) the known relationship between Food and Drug Administration (FDA)-approved drugs and diseases. Using these data, our proposed method learns a similarity metric through a supervised machine learning-based algorithm such that a disease and its associated FDA-approved drugs have smaller distance than the other disease-drug pairs.

RESULTS

We validated our framework by showing that the proposed method incorporating distance metric learning technique can retrieve FDA-approved drugs for their approved indications. Once validated, we used our approach to identify a few strong candidates for repurposing.

AVAILABILITY AND IMPLEMENTATION

The R scripts are available on demand from the authors.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Idiopathic Pulmonary Fibrosis: Pathogenesis and the Emerging Role of Long Non-Coding RNAs

Idiopathic pulmonary fibrosis (IPF) is a progressive chronic disease characterized by excessing scarring of the lungs leading to irreversible decline in lung function. The aetiology and pathogenesis of the disease are still unclear, although lung fibroblast and epithelial cell activation, as well as the secretion of fibrotic and inflammatory mediators, have been strongly associated with the development and progression of IPF. Significantly, long non-coding RNAs (lncRNAs) are emerging as modulators of multiple biological processes, although their function and mechanism of action in IPF is poorly understood. LncRNAs have been shown to be important regulators of several diseases and their aberrant expression has been linked to the pathophysiology of fibrosis including IPF. This review will provide an overview of this emerging role of lncRNAs in the development of IPF.

RNA sequencing of transplant-stage idiopathic pulmonary fibrosis lung reveals unique pathway regulation

Idiopathic pulmonary fibrosis (IPF), the scarring of lung parenchyma resulting in the loss of lung function, remains a fatal disease with a significant unmet medical need. Patients with severe IPF often develop acute exacerbations resulting in the rapid deterioration of lung function, requiring transplantation. Understanding the pathophysiological mechanisms contributing to IPF is key to develop novel therapeutic approaches for end-stage disease. We report here RNA-sequencing analyses of lung tissues from a cohort of patients with transplant-stage IPF (n=36), compared with acute lung injury (ALI) (n=11) and nondisease controls (n=19), that reveal a robust gene expression signature unique to end-stage IPF. In addition to extracellular matrix remodelling pathways, we identified pathways associated with T-cell infiltration/activation, tumour development, and cholesterol homeostasis, as well as novel alternatively spliced transcripts that are differentially regulated in the advanced IPF lung versus ALI or nondisease controls. Additionally, we show a subset of genes that are correlated with percent predicted forced vital capacity and could reflect disease severity. Our results establish a robust transcriptomic fingerprint of an advanced IPF lung that is distinct from previously reported microarray signatures of moderate, stable or progressive IPF and identifies hitherto unknown candidate targets and pathways for therapeutic intervention in late-stage IPF as well as biomarkers to characterise disease progression and enable patient stratification.

A robust data-driven genomic signature for idiopathic pulmonary fibrosis with applications for translational model selection

Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive lung disease affecting ~5 million people globally. We have constructed an accurate model of IPF disease status using elastic net regularized regression on clinical gene expression data. Leveraging whole transcriptome microarray data from 230 IPF and 89 control samples from Yang et al. (2013), sourced from the Lung Tissue Research Consortium (LTRC) and National Jewish Health (NJH) cohorts, we identify an IPF gene expression signature. We performed optimal feature selection to reduce the number of transcripts required by our model to a parsimonious set of 15. This signature enables our model to accurately separate IPF patients from controls. Our model outperforms existing published models when tested with multiple independent clinical cohorts. Our study underscores the utility of elastic nets for gene signature/panel selection which can be used for the construction of a multianalyte biomarker of disease. We also filter the gene sets used for model input to construct a model reliant on secreted proteins. Using this approach, we identify the preclinical bleomycin rat model that is most congruent with human disease at day 21 post-bleomycin administration, contrasting with earlier timepoints suggested by other studies.

RNA-sequencing across three matched tissues reveals shared and tissue-specific gene expression and pathway signatures of COPD

BACKGROUND

Multiple gene expression studies have been performed separately in peripheral blood, lung, and airway tissues to study COPD. We performed RNA-sequencing gene expression profiling of large-airway epithelium, alveolar macrophage and peripheral blood samples from the same subset of COPD cases and controls from the COPDGene study who underwent bronchoscopy at a single center. Using statistical and gene set enrichment approaches, we sought to improve the understanding of COPD by studying gene sets and pathways across these tissues, beyond the individual genomic determinants.

METHODS

We performed differential expression analysis using RNA-seq data obtained from 63 samples from 21 COPD cases and controls (includes four non-smokers) via the R package DESeq2. We tested associations between gene expression and variables related to lung function, smoking history, and CT scan measures of emphysema and airway disease. We examined the correlation of differential gene expression across the tissues and phenotypes, hypothesizing that this would reveal preserved and private gene expression signatures. We performed gene set enrichment analyses using curated databases and findings from prior COPD studies to provide biological and disease relevance.

RESULTS

The known smoking-related genes CYP1B1 and AHRR were among the top differential expression results for smoking status in the large-airway epithelium data. We observed a significant overlap of genes primarily across large-airway and macrophage results for smoking and airway disease phenotypes. We did not observe specific genes differentially expressed in all three tissues for any of the phenotypes. However, we did observe hemostasis and immune signaling pathways in the overlaps across all three tissues for emphysema, and amyloid and telomere-related pathways for smoking. In peripheral blood, the emphysema results were enriched for B cell related genes previously identified in lung tissue studies.

CONCLUSIONS

Our integrative analyses across COPD-relevant tissues and prior studies revealed shared and tissue-specific disease biology. These replicated and novel findings in the airway and peripheral blood have highlighted candidate genes and pathways for COPD pathogenesis.

Progress in Understanding and Treating Idiopathic Pulmonary Fibrosis

This is a time of substantial progress in the evaluation and care of patients with idiopathic pulmonary fibrosis (IPF). In addition to the approval and widespread availability of the first IPF-specific therapies, there have been improvements in imaging interpretation and lung biopsy methods to enable more expeditious and more accurate diagnosis. Recent advances in identifying genetic factors that underlie susceptibility to IPF and affect prognosis have raised the possibility of personalized therapeutic approaches in the future. Further, evolving work is elucidating novel mechanisms influencing epithelial, mesenchymal, and inflammatory cell responses during the injury-repair process, thus advancing understanding of disease pathogenesis. As analytic approaches mature, the field is now poised to harness the power of rapidly advancing "omics" technologies to further accelerate progress.

Age-related but not longevity-related genes are found by weighted gene co-expression network analysis in the peripheral blood cells of humans

Human lifespan is determined by genetic and environmental factors. Potential longevity genes are neither specific nor reproducible, and longevity-related genes are constantly confused with age-related genes. To distinguish specific age- and longevity-related genes, we analyzed a Gene Expression Omnibus (GEO) dataset established by the Leiden Longevity Study. The individuals were classified into longevity (mean age, 93.4 ± 3.0 years), longevity offspring (60.8 ± 6.1) and control (61.9 ± 6.9) groups. The series matrix files were downloaded, and average expression values were calculated. Differentially expressed genes (DEGs) between longevity and control groups and those between longevity and their offspring were identified by GEO2R online. A total of 507 longevity- and 755 age-related DEGs were visualized using a Venn diagram. Weighted gene co-expression network analysis (WGCNA) was performed on the longevity- and age-related DEGs. Age-related color modules and genes were identified. However, no longevity-related modules or genes were found. The green module, with 46 age-related DEGs, was the most biologically significant to age and aging. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction pathway analyses were conducted on these 46 DEGs, which are mainly enriched in B cell activation and receptor signaling pathways. CR2, VPREB3, MS4A1 and CCR6 were considered the most crucial candidate genes for aging.

Clinical Genetics in Interstitial Lung Disease

Interstitial lung disease (ILD) comprises a heterogeneous group of diffuse parenchymal lung processes with overlapping clinical, radiographic, and histopathologic features. Among the most common and deadly ILDs are idiopathic pulmonary fibrosis (IPF) and chronic hypersensitivity pneumonitis (CHP). As the name implies, the cause of IPF remains elusive, but a variety of genetic and infectious risk factors have been identified. CHP results from chronic inhalation of an organic antigen, usually of avian or mold origin, and may occur in patients with a genetic predisposition. While IPF is treated with anti-fibrotic compounds, CHP is generally treated by suppression of the immune system and elimination of the causative antigen. Despite advances in our understanding of IPF and CHP, there exists substantial variability in the diagnosis and treatment of these disease processes. Furthermore, IPF and CHP natural history and treatment response remain far from uniform, leaving it unclear which patients derive the most benefit from disease-specific therapy. While clinical prediction models have improved our understanding of outcome risk in patients with various forms of ILD, recent advances in genomic technology provides a valuable opportunity to begin understanding the basis for outcome variability. Such advances will ultimately allow for the incorporation of genomic markers into risk stratification and clinical decision-making. In this piece, we highlight recent advances in our understanding of the genomic factors that influence susceptibility and outcome risk among patients with IPF and CHP. Genomic modalities used to identify these genomic markers include genome-wide association studies, analyses of gene expression, drug–gene interaction testing, telomere length determination, telomerase mutation analysis, and studies of the lung microbiome. We then identify gaps in knowledge that should be addressed to help facilitate the incorporation of these genomic technologies into ILD clinical practice.

Personalised medicine in interstitial lung diseases

Interstitial lung diseases in general, and idiopathic pulmonary fibrosis in particular, are complex disorders with multiple pathogenetic pathways, various disease behaviour profiles and different responses to treatment, all facets that make personalised medicine a highly attractive concept. Personalised medicine is aimed at describing distinct disease subsets taking into account individual lifestyle, environmental exposures, genetic profiles and molecular pathways. The cornerstone of personalised medicine is the identification of biomarkers that can be used to inform diagnosis, prognosis and treatment stratification. At present, no data exist validating a personalised approach in individual diseases. However, the importance of the goal amply justifies the characterisation of genotype and pathway signatures with a view to refining prognostic evaluation and trial design, with the ultimate aim of selecting treatments according to profiles in individual patients.

Impact of Transcriptomics on Our Understanding of Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a lethal fibrotic lung disease characterized by aberrant remodeling of the lung parenchyma with extensive changes to the phenotypes of all lung resident cells. The introduction of transcriptomics, genome scale profiling of thousands of RNA transcripts, caused a significant inversion in IPF research. Instead of generating hypotheses based on animal models of disease, or biological plausibility, with limited validation in humans, investigators were able to generate hypotheses based on unbiased molecular analysis of human samples and then use animal models of disease to test their hypotheses. In this review, we describe the insights made from transcriptomic analysis of human IPF samples. We describe how transcriptomic studies led to identification of novel genes and pathways involved in the human IPF lung such as: matrix metalloproteinases, WNT pathway, epithelial genes, role of microRNAs among others, as well as conceptual insights such as the involvement of developmental pathways and deep shifts in epithelial and fibroblast phenotypes. The impact of lung and transcriptomic studies on disease classification, endotype discovery, and reproducible biomarkers is also described in detail. Despite these impressive achievements, the impact of transcriptomic studies has been limited because they analyzed bulk tissue and did not address the cellular and spatial heterogeneity of the IPF lung. We discuss new emerging technologies and applications, such as single-cell RNAseq and microenvironment analysis that may address cellular and spatial heterogeneity. We end by making the point that most current tissue collections and resources are not amenable to analysis using the novel technologies. To take advantage of the new opportunities, we need new efforts of sample collections, this time focused on access to all the microenvironments and cells in the IPF lung.

Idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease characterized by progressive lung scarring and the histological picture of usual interstitial pneumonia (UIP). It is associated with increasing cough and dyspnoea and impaired quality of life. IPF affects ∼3 million people worldwide, with incidence increasing dramatically with age. The diagnostic approach includes the exclusion of other interstitial lung diseases or overlapping conditions and depends on the identification of the UIP pattern, usually with high-resolution CT; lung biopsy might be required in some patients. The UIP pattern is predominantly bilateral, peripheral and with a basal distribution of reticular changes associated with traction bronchiectasis and clusters of subpleural cystic airspaces. The biological processes underlying IPF are thought to reflect an aberrant reparative response to repetitive alveolar epithelial injury in a genetically susceptible ageing individual, although many questions remain on how to define susceptibility. Substantial progress has been made in the understanding of the clinical management of IPF, with the availability of two pharmacotherapeutic agents, pirfenidone and nintedanib, that decrease physiological progression and likely improve progression-free survival. Current efforts are directed at identifying IPF early, potentially relying on combinations of biomarkers that include circulating factors, demographics and imaging data.

Drug repurposing in idiopathic pulmonary fibrosis filtered by a bioinformatics-derived composite score

Idiopathic Pulmonary Fibrosis (IPF) is a rare disease of the respiratory system in which the lungs stiffen and get scarred, resulting in breathing weakness and eventually leading to death. Drug repurposing is a process that provides evidence for existing drugs that may also be effective in different diseases. In this study, we present a computational pipeline having as input a number of gene expression datasets from early and advanced stages of IPF and as output lists of repurposed drugs ranked with a novel composite score. We have devised and used a scoring formula in order to rank the repurposed drugs, consolidating the standard repurposing score with structural, functional and side effects' scores for each drug per stage of IPF. The whole pipeline involves the selection of proper gene expression datasets, data preprocessing and statistical analysis, selection of the most important genes related to the disease, analysis of biological pathways, investigation of related molecular mechanisms, identification of fibrosis-related microRNAs, drug repurposing, structural and literature-based analysis of the repurposed drugs.

Hepatitis C Virus-Associated Extrahepatic Manifestations in Lung and Heart and Antiviral Therapy-Related Cardiopulmonary Toxicity

Besides liver cirrhosis and hepatocellular carcinoma, chronic hepatitis C virus (HCV) infection is associated with many extrahepatic manifestations (EHMs). HCV exhibits lymphotropism that is responsible for various EHM. An important characteristic of HCV is escape from the immune system, which enables it to produce chronic infections and autoimmune disorders along with accumulation of circulating immune complexes. These EHMs have large spectrum, because they affect many organs such as heart, lungs, kidney, brain, thyroid, and skin. HCV-related cardiac and pulmonary manifestations include myocarditis, cardiomyopathies, cardiovascular diseases (i.e., Stroke, ischemic heart disease), chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, asthma, and interstitial lung diseases. This review discusses etiology and pathogenesis of HCV-associated cardiac and pulmonary manifestations and how different genes, immune system, indirectly linked factors (mixed cryoglobulinemia), liver cirrhosis, and antiviral treatment are involved in HCV-related heart and lung diseases, however, their exact mechanism is not clear.

Quantitative reproducibility analysis for identifying reproducible targets from high-throughput experiments

BACKGROUND

High-throughput assays are widely used in biological research to select potential targets. One single high-throughput experiment can efficiently study a large number of candidates simultaneously, but is subject to substantial variability. Therefore it is scientifically important to performance quantitative reproducibility analysis to identify reproducible targets with consistent and significant signals across replicate experiments. A few methods exist, but all have limitations.

METHODS

In this paper, we propose a new method for identifying reproducible targets. Considering a Bayesian hierarchical model, we show that the test statistics from replicate experiments follow a mixture of multivariate Gaussian distributions, with the one component with zero-mean representing the irreproducible targets.

RESULTS

A target is thus classified as reproducible or irreproducible based on its posterior probability belonging to the reproducible components. We study the performance of our proposed method using simulations and a real data example.

CONCLUSION

The proposed method is shown to have favorable performance in identifying reproducible targets compared to other methods.

Using omics approaches to understand pulmonary diseases

Omics approaches are high-throughput unbiased technologies that provide snapshots of various aspects of biological systems and include: 1) genomics, the measure of DNA variation; 2) transcriptomics, the measure of RNA expression; 3) epigenomics, the measure of DNA alterations not involving sequence variation that influence RNA expression; 4) proteomics, the measure of protein expression or its chemical modifications; and 5) metabolomics, the measure of metabolite levels. Our understanding of pulmonary diseases has increased as a result of applying these omics approaches to characterize patients, uncover mechanisms underlying drug responsiveness, and identify effects of environmental exposures and interventions. As more tissue- and cell-specific omics data is analyzed and integrated for diverse patients under various conditions, there will be increased identification of key mechanisms that underlie pulmonary biological processes, disease endotypes, and novel therapeutics that are efficacious in select individuals. We provide a synopsis of how omics approaches have advanced our understanding of asthma, chronic obstructive pulmonary disease (COPD), acute respiratory distress syndrome (ARDS), idiopathic pulmonary fibrosis (IPF), and pulmonary arterial hypertension (PAH), and we highlight ongoing work that will facilitate pulmonary disease precision medicine.

Microbes Are Associated with Host Innate Immune Response in Idiopathic Pulmonary Fibrosis

RATIONALE

Differences in the lung microbial community influence idiopathic pulmonary fibrosis (IPF) progression. Whether the lung microbiome influences IPF host defense remains unknown.

OBJECTIVES

To explore the host immune response and microbial interaction in IPF as they relate to progression-free survival (PFS), fibroblast function, and leukocyte phenotypes.

METHODS

Paired microarray gene expression data derived from peripheral blood mononuclear cells as well as 16S ribosomal RNA sequencing data from bronchoalveolar lavage obtained as part of the COMET-IPF (Correlating Outcomes with Biochemical Markers to Estimate Time-Progression in Idiopathic Pulmonary Fibrosis) study were used to conduct association pathway analyses. The responsiveness of paired lung fibroblasts to Toll-like receptor 9 (TLR9) stimulation by CpG-oligodeoxynucleotide (CpG-ODN) was integrated into microbiome-gene expression association analyses for a subset of individuals. The relationship between associated pathways and circulating leukocyte phenotypes was explored by flow cytometry.

MEASUREMENTS AND MAIN RESULTS

Down-regulation of immune response pathways, including nucleotide-binding oligomerization domain (NOD)-, Toll-, and RIG1-like receptor pathways, was associated with worse PFS. Ten of the 11 PFS-associated pathways correlated with microbial diversity and individual genus, with species accumulation curve richness as a hub. Higher species accumulation curve richness was significantly associated with inhibition of NODs and TLRs, whereas increased abundance of Streptococcus correlated with increased NOD-like receptor signaling. In a network analysis, expression of up-regulated signaling pathways was strongly associated with decreased abundance of operational taxonomic unit 1341 (OTU1341; Prevotella) among individuals with fibroblasts responsive to CpG-ODN stimulation. The expression of TLR signaling pathways was also linked to CpG-ODN responsive fibroblasts, OTU1341 (Prevotella), and Shannon index of microbial diversity in a network analysis. Lymphocytes expressing C-X-C chemokine receptor 3 CD8 significantly correlated with OTU1348 (Staphylococcus).

CONCLUSIONS

These findings suggest that host-microbiome interactions influence PFS and fibroblast responsiveness.

The respiratory microbiome in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal disease of unknown cause. Current evidence suggests that it arises in genetically susceptible individuals as a consequence of an aberrant wound-healing response following repetitive alveolar injury. Overt respiratory infection and immunosuppression carry a high mortality, while polymorphisms in genes related to epithelial integrity and host defence predispose to IPF. Recent advances in sequencing technologies have allowed the use of molecular microbial technologies to characterise the respiratory microbiota in patients with IPF. Studies have suggested that changes in the overall bacterial burden are related to disease progression and highlighted significant differences between the microbiota in IPF subjects and healthy controls. Indeed differences in the microbiota between IPF patients may differentiate those with stable compared to progressive disease. As our understanding of the IPF microbiome evolves, along with refinement and advances in sampling and sequencing methodologies we may be able to use microbial signatures as a biomarker to guide prognostication and even treatment stratification in this devastating disease.

Metabolic heterogeneity of idiopathic pulmonary fibrosis: a metabolomic study

Introduction

Idiopathic pulmonary fibrosis (IPF) is a chronic and fatal disease of unknown cause characterised by progressive fibrotic formation in lung tissue. We hypothesise that disrupted metabolic pathways in IPF contribute to disease pathogenesis.

Methods

Metabolomics of human IPF was performed using mass spectroscopy (IPF lung=8; donor lung=8). Gene expression of key metabolic enzymes was measured using microarrays. Of the 108 metabolites whose levels were found altered, 48 were significantly increased, whereas 60 were significantly decreased in IPF samples compared with normal controls.

Results

Specific metabolic pathways mediating the IPF remodelling were found with a downregulated sphingolipid metabolic pathway but an upregulated arginine pathway in IPF. In addition, disrupted glycolysis, mitochondrial beta-oxidation and tricarboxylic acid cycle, altered bile acid, haem and glutamate/aspartate metabolism were found in IPF samples compared with control.

Conclusions

Our results show alterations in metabolic pathways for energy consumption during lung structural remodelling, which may contribute to IPF pathogenesis. We believe that this is the first report of simultaneously and systemically measuring changes of metabolites involving nine metabolic pathways in human severe IPF lungs. The measurement of the metabolites may serve in the future diagnosis and prognosis of IPF.

The peripheral blood proteome signature of idiopathic pulmonary fibrosis is distinct from normal and is associated with novel immunological processes

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal interstitial pneumonia. The disease pathophysiology is poorly understood and the etiology remains unclear. Recent advances have generated new therapies and improved knowledge of the natural history of IPF. These gains have been brokered by advances in technology and improved insight into the role of various genes in mediating disease, but gene expression and protein levels do not always correlate. Thus, in this paper we apply a novel large scale high throughput aptamer approach to identify more than 1100 proteins in the peripheral blood of well-characterized IPF patients and normal volunteers. We use systems biology approaches to identify a unique IPF proteome signature and give insight into biological processes driving IPF. We found IPF plasma to be altered and enriched for proteins involved in defense response, wound healing and protein phosphorylation when compared to normal human plasma. Analysis also revealed a minimal protein signature that differentiated IPF patients from normal controls, which may allow for accurate diagnosis of IPF based on easily-accessible peripheral blood. This report introduces large scale unbiased protein discovery analysis to IPF and describes distinct biological processes that further inform disease biology.

Pathway‑based detection of idiopathic pulmonary fibrosis at an early stage

Idiopathic pulmonary fibrosis (IPF) is the most common interstitial pneumonia and the most aggressive interstitial lung disease. Usually, IPF is confirmed by the histopathological pattern of typical interstitial pneumonia and requires an integrated multidisciplinary approach from pulmonologists, radiologists and pathologists. However, these diagnoses are performed at an advanced stage of IPF. At present, pathway‑based detection requires investigation, as it can be performed at an early stage of the disease. The aim of the present study was to find an effective method of diagnosing IPF at an early stage. Microarray data forE‑GEOD‑33566 were downloaded from the ArrayExpress database. Human pathways were downloaded from Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database. An individual pathway‑based method to diagnose IPF at an early stage was introduced. Pathway statistics were analyzed with an individualized pathway aberrance score. P‑values were obtained with different methods, including the Wilcoxon test, linear models for microarray data (Limma) test and attract methods, generating three pathway groups. Support vector machines (SVM) were used to identify the best group for diagnosing IPF at an early stage. There were 106 differential pathways in Wilcoxon‑based KEGG Pathway (n>5) group, 100 in the Limma‑based KEGG Pathway (n>5) group, and seven in the attract‑based KEGG Pathway (n>5) group. The pathway statistics of these differential pathways in three groups were analyzed with linear SVM. The results demonstrated that the Wilcoxon‑based KEGG Pathway (n>5) group performed best in diagnosing IPF.

iTRAQ-Based Proteomics Reveals Novel Biomarkers for Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a gradual lung disease with a survival of less than 5 years post-diagnosis for most patients. Poor molecular description of IPF has led to unsatisfactory interpretation of the pathogenesis of this disease, resulting in the lack of successful treatments. The objective of this study was to discover novel noninvasive biomarkers for the diagnosis of IPF. We employed a coupled isobaric tag for relative and absolute quantitation (iTRAQ)-liquid chromatography–tandem mass spectrometry (LC–MS/MS) approach to examine protein expression in patients with IPF. A total of 97 differentially expressed proteins (38 upregulated proteins and 59 downregulated proteins) were identified in the serum of IPF patients. Using String software, a regulatory network containing 87 nodes and 244 edges was built, and the functional enrichment showed that differentially expressed proteins were predominantly involved in protein activation cascade, regulation of response to wounding and extracellular components. A set of three most significantly upregulated proteins (HBB, CRP and SERPINA1) and four most significantly downregulated proteins (APOA2, AHSG, KNG1 and AMBP) were selected for validation in an independent cohort of IPF and other lung diseases using ELISA test. The results confirmed the iTRAQ profiling results and AHSG, AMBP, CRP and KNG1 were found as specific IPF biomarkers. ROC analysis indicated the diagnosis potential of the validated biomarkers. The findings of this study will contribute in understanding the pathogenesis of IPF and facilitate the development of therapeutic targets.

The diagnosis of idiopathic pulmonary fibrosis: current and future approaches

With the recent development of two effective treatments for patients with idiopathic pulmonary fibrosis, an accurate diagnosis is crucial. The traditional approach to diagnosis emphasises the importance of thorough clinical and laboratory evaluations to exclude secondary causes of disease. High-resolution CT is a critical initial diagnostic test and acts as a tool to identify patients who should undergo surgical lung biopsy to secure a definitive histological diagnosis of usual interstitial pneumonia pattern. This diagnostic approach faces several challenges. Many patients with suspected idiopathic pulmonary fibrosis present with atypical high-resolution CT characteristics but are unfit for surgical lung biopsy, therefore preventing a confident diagnosis. The state of the art suggests an iterative, multidisciplinary process that incorporates available clinical, laboratory, imaging, and histological features. Recent research has explored genomic techniques to molecularly phenotype patients with interstitial lung disease. In the future, clinicians will probably use blood-specific or lung-specific molecular markers in combination with other clinical, physiological, and imaging features to enhance diagnostic efforts, refine prognostic recommendations, and influence the initial or subsequent treatment options. There is an urgent and increasing need for well designed, large, prospective studies measuring the effect of different diagnostic approaches. Ultimately, this will help to inform the development of guidelines and tailor clinical practice for the benefit of patients.

Toll-like receptors and autophagy in interstitial lung diseases

Interstitial lung diseases (ILDs) include a number of diseases whose pathogenesis still is not fully understood. Idiopathic pulmonary fibrosis (IPF), the most frequent and severe form of ILDs is an epithelial-driven disease and the treatment consists of the use of antifibrotic agents. In the rest of ILDs an inflammation-driven pathway is believed to be the main pathogenetic mechanism and treatment consists of the use of immunomodulatory agents. In both groups it is believed that infection can play an important role in the development and progression of the diseases. The immune system can recognize exogenous threats or endogenous stress through specialized receptors namely pattern recognition receptors (PRRs) which in turn, initiate downstream signaling pathways to control immune responses. Recently, a link between PRRs and autophagy, a specialized biological process involved in maintaining cellular homeostasis but also involved in various immunologic processes, has been described. In this review, we focus on the reciprocal influences of PRRs with particular emphasis on Toll-like receptors and autophagy in modulating innate immune responses.

Viruses in Idiopathic Pulmonary Fibrosis. Etiology and Exacerbation

Viral infections are important contributors to exacerbation of asthma and chronic obstructive pulmonary disease; however, the role of viruses in the pathogenesis of idiopathic pulmonary fibrosis (IPF) is less clear. This likely reflects that fact that IPF acute exacerbations are defined clinically as "noninfectious," and little attention has been paid to the outcomes of patients with IPF with diagnosed infections. However, accumulating evidence suggests that infections (both bacterial and viral) may influence disease outcomes either as exacerbating agents or initiators of disease. Support for a viral role in disease initiation comes from studies demonstrating the presence of herpesviral DNA and epithelial cell stress in the lungs of asymptomatic relatives at risk for developing familial IPF. In addition, the number of studies that can associate viral (especially herpesviral) signatures in the lung with the development of IPF is steadily growing, and activated leukocyte signatures in patients with IPF provide further support for infectious processes driving IPF progression. Animal modeling has been used to better understand how a gamma herpesvirus infection can modulate the pathogenesis of lung fibrosis and has demonstrated that preceding infections appear to reprogram lung epithelial cells during latency to produce profibrotic factors, making the lung more susceptible to subsequent fibrotic insult, whereas exacerbations of existing fibrosis, or infections in susceptible hosts, involve active viral replication and are influenced by antiviral therapy. In addition, there is new evidence that bacterial burden in the lungs of patients with IPF may predict a poor prognosis.

Peripheral blood myeloid-derived suppressor cells reflect disease status in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a fibroproliferative disease with irreversible lung function loss and poor survival. Myeloid-derived suppressor cells (MDSC) are associated with poor prognosis in cancer, facilitating immune evasion. The abundance and function of MDSC in IPF is currently unknown.

Fluorescence-activated cell sorting was performed in 170 patients (IPF: n=69; non-IPF interstitial lung disease (ILD): n=56; chronic obstructive pulmonary disease (COPD): n=23; healthy controls: n=22) to quantify blood MDSC and lymphocyte subtypes. MDSC abundance was correlated with lung function, MDSC localisation was performed by immunofluorescence. Peripheral blood mononuclear cell (PBMC) mRNA levels were analysed by qRT-PCR.

We detected increased MDSC in IPF and non-IPF ILD compared with controls (30.99±15.61% versus 18.96±8.17%, p≤0.01). Circulating MDSC inversely correlated with maximum vital capacity (r= −0.48, p≤0.0001) in IPF, but not in COPD or non-IPF ILD. MDSC suppressed autologous T-cells. The mRNA levels of co-stimulatory T-cell signals were significantly downregulated in IPF PBMC. Importantly, CD33+CD11b+ cells, suggestive of MDSC, were detected in fibrotic niches of IPF lungs.

We identified increased MDSC in IPF and non-IPF ILD, suggesting that elevated MDSC may cause a blunted immune response. MDSC inversely correlate with lung function only in IPF, identifying them as potent biomarkers for disease progression. Controlling expansion and accumulation of MDSC, or blocking their T-cell suppression, represents a promising therapy in IPF.

Recent advances in understanding idiopathic pulmonary fibrosis

Despite major research efforts leading to the recent approval of pirfenidone and nintedanib, the dismal prognosis of idiopathic pulmonary fibrosis (IPF) remains unchanged. The elaboration of international diagnostic criteria and disease stratification models based on clinical, physiological, radiological, and histopathological features has improved the accuracy of IPF diagnosis and prediction of mortality risk. Nevertheless, given the marked heterogeneity in clinical phenotype and the considerable overlap of IPF with other fibrotic interstitial lung diseases (ILDs), about 10% of cases of pulmonary fibrosis remain unclassifiable. Moreover, currently available tools fail to detect early IPF, predict the highly variable course of the disease, and assess response to antifibrotic drugs.

Recent advances in understanding the multiple interrelated pathogenic pathways underlying IPF have identified various molecular phenotypes resulting from complex interactions among genetic, epigenetic, transcriptional, post-transcriptional, metabolic, and environmental factors. These different disease endotypes appear to confer variable susceptibility to the condition, differing risks of rapid progression, and, possibly, altered responses to therapy. The development and validation of diagnostic and prognostic biomarkers are necessary to enable a more precise and earlier diagnosis of IPF and to improve prediction of future disease behaviour. The availability of approved antifibrotic therapies together with potential new drugs currently under evaluation also highlights the need for biomarkers able to predict and assess treatment responsiveness, thereby allowing individualised treatment based on risk of progression and drug response. This approach of disease stratification and personalised medicine is already used in the routine management of many cancers and provides a potential road map for guiding clinical care in IPF.

Relationship between gene expression and lung function in Idiopathic Interstitial Pneumonias

Background

Idiopathic interstitial pneumonias (IIPs) are a group of heterogeneous, somewhat unpredictable diseases characterized by progressive scarring of the interstitium. Since lung function is a key determinant of survival, we reasoned that the transcriptional profile in IIP lung tissue would be associated with measures of lung function, and could enhance prognostic approaches to IIPs.

Results

Using gene expression profiling of 167 lung tissue specimens with IIP diagnosis and 50 control lungs, we identified genes whose expression is associated with changes in lung function (% predicted FVC and % predicted D_LCO) modeled as categorical (severe vs mild disease) or continuous variables while adjusting for smoking status and IIP subtype; false discovery rate (FDR) approach was used to correct for multiple comparisons. This analysis identified 58 transcripts that are associated with mild vs severe disease (categorical analysis), including those with established role in fibrosis (ADAMTS4, ADAMTS9, AGER, HIF-1α, SERPINA3, SERPINE2, and SELE) as well as novel IIP candidate genes such as rhotekin 2 (RTKN2) and peptidase inhibitor 15 (PI15). Protein-protein interactome analysis of 553 genes whose expression is significantly associated with lung function when modeled as continuous variables demonstrates that more severe presentation of IIPs is characterized by an increase in cell cycle progression and apoptosis, increased hypoxia, and dampened innate immune response. Our findings were validated in an independent cohort of 131 IIPs and 40 controls at the mRNA level and for one gene (RTKN2) at the protein level by immunohistochemistry in a subset of samples.

Conclusions

We identified commonalities and differences in gene expression among different subtypes of IIPs. Disease progression, as characterized by lower measures of FVC and D_LCO, results in marked changes in expression of novel and established genes and pathways involved in IIPs. These genes and pathways represent strong candidates for biomarker studies and potential therapeutic targets for IIP severity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2102-3) contains supplementary material, which is available to authorized users.

Transcriptional profiles of peripheral blood leukocytes identify patients with cholangiocarcinoma and predict outcome

Cholangiocarcinoma (CCA), a slow growing but highly metastatic tumor, is highly prevalent in Northeast Thailand. Specific tests that predict prognosis of CCA remain elusive. The present study was designed to investigate whether peripheral blood leukocyte (PBL) transcriptional profiles might be of use as a prognostic test in CCA patients. Gene expression profiles of PBLs from 9 CCA and 8 healthy subjects were conducted using the Affymetrix HG_U133 Plus 2.0 GeneChip. We indentified informative PBLs gene expression profiles that could reliably distinguish CCA patients from healthy subjects. Of these CCA specific genes, 117 genes were up regulated and 60 were down regulated. The molecular and cellular functions predicted for these CCA specific genes according to the Gene Ontology database indicated differential PBL expression of host immune response and tumor progression genes (EREG, TGF β1, CXCL2, CXCL3, IL-8, and VEGFA). The expression levels of 9 differentially expressed genes were verified in 36 CCA vs 20 healthy subjects. A set of three tumor invasion related genes (PLAU, CTSL and SERPINB2) computed as "prognostic index" was found to be an independent and statistically significant predictor for CCA patient survival. The present study shows that CCA PBLs may serve as disease predictive clinically accessible surrogates for indentifying expressed genes reflective of CCA disease severity.

IRAK-M promotes alternative macrophage activation and fibroproliferation in bleomycin-induced lung injury

Idiopathic pulmonary fibrosis is a devastating lung disease characterized by inflammation and the development of excessive extracellular matrix deposition. Currently, there are only limited therapeutic intervenes to offer patients diagnosed with pulmonary fibrosis. Although previous studies focused on structural cells in promoting fibrosis, our study assessed the contribution of macrophages. Recently, TLR signaling has been identified as a regulator of pulmonary fibrosis. IL-1R-associated kinase-M (IRAK-M), a MyD88-dependent inhibitor of TLR signaling, suppresses deleterious inflammation, but may paradoxically promote fibrogenesis. Mice deficient in IRAK-M (IRAK-M(-/-)) were protected against bleomycin-induced fibrosis and displayed diminished collagen deposition in association with reduced production of IL-13 compared with wild-type (WT) control mice. Bone marrow chimera experiments indicated that IRAK-M expression by bone marrow-derived cells, rather than structural cells, promoted fibrosis. After bleomycin, WT macrophages displayed an alternatively activated phenotype, whereas IRAK-M(-/-) macrophages displayed higher expression of classically activated macrophage markers. Using an in vitro coculture system, macrophages isolated from in vivo bleomycin-challenged WT, but not IRAK-M(-/-), mice promoted increased collagen and α-smooth muscle actin expression from lung fibroblasts in an IL-13-dependent fashion. Finally, IRAK-M expression is upregulated in peripheral blood cells from idiopathic pulmonary fibrosis patients and correlated with markers of alternative macrophage activation. These data indicate expression of IRAK-M skews lung macrophages toward an alternatively activated profibrotic phenotype, which promotes collagen production, leading to the progression of experimental pulmonary fibrosis.

Quantitative proteomics of bronchoalveolar lavage fluid in idiopathic pulmonary fibrosis

The proteomic analysis of bronchoalveolar lavage fluid (BALF) can give insight into pulmonary disease pathology and response to therapy. Here, we describe the first gel-free quantitative analysis of BALF in idiopathic pulmonary fibrosis (IPF), a chronic and fatal scarring lung disease. We utilized two-dimensional reversed-phase liquid chromatography and ion-mobility-assisted data-independent acquisition (HDMSE) for quantitation of >1000 proteins in immunodepleted BALF from the right middle and lower lobes of normal controls and patients with IPF. Among the analytes that were increased in IPF were well-described mediators of pulmonary fibrosis (osteopontin, MMP7, CXCL7, CCL18), eosinophil- and neutrophil-derived proteins, and proteins associated with fibroblast foci. For additional discovery and targeted validation, BALF was also screened by multiple reaction monitoring (MRM), using the JPT Cytokine SpikeMix library of >400 stable isotope-labeled peptides. A refined MRM assay confirmed the robust expression of osteopontin, and demonstrated, for the first time, upregulation of the pro-fibrotic cytokine, CCL24, in BALF in IPF. These results show the utility of BALF proteomics for the molecular profiling of fibrotic lung diseases and the targeted quantitation of soluble markers of IPF. More generally, this study addresses critical quality control measures that should be widely applicable to BALF profiling in pulmonary disease.