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Longitudinal genomics data and survival outcome are common in biomedical studies, where the genomics data are often of high dimension. It is of great interest to select informative longitudinal biomarkers (e.g. genes) related to the survival outcome. In this paper, we develop a computationally efficient tool, LCox, for selecting informative biomarkers related to the survival outcome using the longitudinal genomics data. LCox is powerful to detect different forms of dependence between the longitudinal biomarkers and the survival outcome. We show that LCox has improved performance compared to existing methods through extensive simulation studies. In addition, by applying LCox to a dataset of patients with idiopathic pulmonary fibrosis, we are able to identify biologically meaningful genes while all other methods fail to make any discovery. An R package to perform LCox is freely available at https://CRAN.R-project.org/package=LCox. [ABSTRACT FROM AUTHOR]

ABSTRACT: Background and objective: Molecular biomarkers are needed to refine prognostication and phenotyping of pulmonary hypertension (PH) patients. S100A12 is an emerging biomarker of various inflammatory diseases. This study aims to determine the prognostic value of S100A12 in PH. Methods: Exploratory microarray analysis performed on peripheral blood mononuclear cells (PBMC) collected from idiopathic pulmonary fibrosis (IPF) patients suggested an association between S100A12 and both PH and mortality. So the current study was designed to evaluate for an association between S100A12 in peripheral blood collected from two well‐phenotyped PH cohorts in two other centres to derive and validate an association between S100A12 protein serum concentrations and mortality. Results: The majority of the patients in the discovery and validation cohorts were either World Health Organization (WHO) group 1 (pulmonary arterial hypertension (PAH)) or 3 (lung disease‐associated) PH. In the discovery PH cohort, S100A12 was significantly increased in patients with PH (n = 51) compared to controls (n = 22) (29.8 vs 15.7 ng/mL, P < 0.001) and negatively correlated with cardiac output (r = −0.58, P < 0.001) in PH patients. When S100A12 data were pooled from both cohorts, PAH and non‐PAH PH patients had higher S100A12 compared to healthy external controls (32.6, 30.9, 15.7 ng/mL; P < 0.001). S100A12 was associated with an increased risk in overall mortality in PH patients in both the discovery (n = 51; P = 0.008) and validation (n = 40; P < 0.001) cohorts. Conclusion: S100A12 levels are increased in PH patients and are associated with increased mortality. [ABSTRACT FROM AUTHOR]

Subgroup identification (clustering) is an important problem in biomedical research. Gene expression profiles are commonly utilized to define subgroups. Longitudinal gene expression profiles might provide additional information on disease progression than what is captured by baseline profiles alone. Therefore, subgroup identification could be more accurate and effective with the aid of longitudinal gene expression data. However, existing statistical methods are unable to fully utilize these data for patient clustering. In this article, we introduce a novel clustering method in the Bayesian setting based on longitudinal gene expression profiles. This method, called BClustLonG, adopts a linear mixed-effects framework to model the trajectory of genes over time, while clustering is jointly conducted based on the regression coefficients obtained from all genes. In order to account for the correlations among genes and alleviate the high dimensionality challenges, we adopt a factor analysis model for the regression coefficients. The Dirichlet process prior distribution is utilized for the means of the regression coefficients to induce clustering. Through extensive simulation studies, we show that BClustLonG has improved performance over other clustering methods. When applied to a dataset of severely injured (burn or trauma) patients, our model is able to identify interesting subgroups. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Background and objective Idiopathic pulmonary fibrosis ( IPF) is a progressive disease with poor prognosis and variable clinical course. Although matrix metalloproteinase-7 ( MMP-7) is emerging as an important IPF biomarker, reproducibility across studies is unclear. We aimed to determine whether a previously reported prognostic threshold for MMP-7 was predictive of mortality in an independent cohort of IPF patients. Methods MMP-7 concentrations obtained from heparinized plasma samples were determined by ELISA in 97 patients with IPF and 41 healthy controls. The association of the previously published heparin plasma MMP-7 threshold of 12.1 ng/mL with all-cause mortality or transplant-free survival ( TFS) was determined, either as an independent biomarker or as part of the modified personal clinical and molecular mortality index (m- PCMI). Results MMP-7 plasma concentrations were significantly higher in IPF patients compared to healthy controls (14.40 ± 6.55 ng/mL vs 6.03 ± 2.51 ng/mL, P < 0.001). The plasma MMP-7 threshold of 12.1 ng/mL was significantly associated with both all-cause mortality and TFS (unadjusted Cox proportional hazard ratio ( HR) = 25.85 and 15.49, 95% CI: 10.91-61.23 and 5.41-44.34, respectively, P < 0.001). MMP-7 concentrations, split by 12.1 ng/mL, were significantly ( P < 0.05) predictive of mortality and TFS after adjusting for age, gender, smoking and baseline pulmonary function parameters, in a multivariate Cox proportional hazards model. MMP-7 concentrations were negatively correlated with diffusing lung capacity of carbon monoxide (DLCO) (r = −0.21, P = 0.02), and positively with a mortality risk scoring system ( GAP) that combines age, gender, forced vital capacity ( FVC) and DLCO (r = 0.32, P = 0.001). Conclusion This study confirms that MMP-7 concentrations could be used to accurately predict outcomes across cohorts and centres, when similar collection protocols are applied. [ABSTRACT FROM AUTHOR]

Background: The increased multi-omics information on carefully phenotyped patients in studies of complex diseases requires novel methods for data integration. Unlike continuous intensity measurements from most omics data sets, phenome data contain clinical variables that are binary, ordinal and categorical. Results: In this paper we introduce an integrative phenotyping framework (iPF) for disease subtype discovery. A feature topology plot was developed for effective dimension reduction and visualization of multi-omics data. The approach is free of model assumption and robust to data noises or missingness. We developed a workflow to integrate homogeneous patient clustering from different omics data in an agglomerative manner and then visualized heterogeneous clustering of pairwise omics sources. We applied the framework to two batches of lung samples obtained from patients diagnosed with chronic obstructive lung disease (COPD) or interstitial lung disease (ILD) with well-characterized clinical (phenomic) data, mRNA and microRNA expression profiles. Application of iPF to the first training batch identified clusters of patients consisting of homogenous disease phenotypes as well as clusters with intermediate disease characteristics. Analysis of the second batch revealed a similar data structure, confirming the presence of intermediate clusters. Genes in the intermediate clusters were enriched with inflammatory and immune functional annotations, suggesting that they represent mechanistically distinct disease subphenotypes that may response to immunomodulatory therapies. The iPF software package and all source codes are publicly available. Conclusions: Identification of subclusters with distinct clinical and biomolecular characteristics suggests that integration of phenomic and other omics information could lead to identification of novel mechanism-based disease sub-phenotypes. [ABSTRACT FROM AUTHOR]

Pulmonary fibrosis results from a plethora of abnormal pathogenetic events. In idiopathic pulmonary fibrosis (IPF), inhalational, environmental, or occupational exposures in genetically and epigenetically predisposed individuals trigger recurrent cycles of alveolar epithelial cell injury, activation of coagulation pathways, chemoattraction, and differentiation of monocytes into monocytederived alveolar macrophages (Mo-AMs). When these events happen intermittently and repeatedly throughout the individual's life cycle, the wound repair process becomes aberrant leading to bronchiolization of distal air spaces, fibroblast accumulation, extracellular matrix deposition, and loss of the alveolar-capillary architecture. The role of immune dysregulation in IPF pathogenesis and progression has been underscored in the past mainly after the disappointing results of immunosuppressant use in IPF patients; however, recent reports highlighting the prognostic and mechanistic roles of monocytes and Mo-AMs revived the interest in immune dysregulation in IPF. In this review, we will discuss the role of these cells in the onset and progression of IPF, as well as potential targeted therapies. [ABSTRACT FROM AUTHOR]

Mast-cell expressed membrane protein-1 (MCEMP1) is higher in patients with idiopathic pulmonary fibrosis (IPF) with an increased risk of death. Here we aimed to establish the mechanistic role of MCEMP1 in pulmonary fibrosis. We identified increased MCEMP1 expression in classical monocytes and alveolar macrophages in IPF compared with controls. MCEMP1 is upregulated by transforming growth factor beta (TGFβ) at the mRNA and protein levels in monocytic leukemia THP-1 cells. TGFβ-mediated MCEMP1 upregulation results from the cooperation of SMAD3 and SP1 via concomitant binding to SMAD3/SP1 cis-regulatory elements within the MCEMP1 promoter. We also found that MCEMP1 regulates TGFb-mediated monocyte chemotaxis, adhesion, and migration. Our results suggest that MCEMP1 may regulate the migration and transition of monocytes to monocyte-derived alveolar macrophages during pulmonary fibrosis development and progression. [ABSTRACT FROM AUTHOR]

Longitudinal gene expression profiles of subjects are collected in some clinical studies to monitor disease progression and understand disease etiology. The identification of gene sets that have coordinated changes with relevant clinical outcomes over time from these data could provide significant insights into the molecular basis of disease progression and lead to better treatments. In this article, we propose a Distance-Correlation based Gene Set Analysis (dcGSA) method for longitudinal gene expression data. dcGSA is a non-parametric approach, statistically robust, and can capture both linear and nonlinear relationships between gene sets and clinical outcomes. In addition, dcGSA is able to identify related gene sets in cases where the effects of gene sets on clinical outcomes differ across subjects due to the subject heterogeneity, remove the confounding effects of some unobserved time-invariant covariates, and allow the assessment of associations between gene sets and multiple related outcomes simultaneously. Through extensive simulation studies, we demonstrate that dcGSA is more powerful of detecting relevant genes than other commonly used gene set analysis methods. When dcGSA is applied to a real dataset on systemic lupus erythematosus, we are able to identify more disease related gene sets than other methods. [ABSTRACT FROM AUTHOR]

Background: Mediastinal lymph node enlargement is prevalent in patients with idiopathic pulmonary fibrosis (IPF). Studies investigating whether this phenomenon reflects specific immunologic activation are lacking. Methods: Programmed cell death-1 (PD-1)/ programmed cell death ligand-1 (PD-L1) expression in mediastinal lymph nodes and lung tissues was analyzed. PD-1, PD-L1 mRNA expression was measured in tracheobronchial lymph nodes of mice following bleomycin-induced injury on day 14. Finally, the effect of the PD-1 inhibitor, pembrolizumab, in bleomycin-induced pulmonary fibrosis was investigated. Results: We analyzed mediastinal lymph nodes of thirty-three patients (n = 33, IPF: n = 14, lung cancer: n = 10, concomitant IPF and lung cancer: n = 9) and lung tissues of two hundred nineteen patients (n = 219, IPF: 123, controls: 96). PD-1 expression was increased, while PD-L1 expression was decreased, in mediastinal lymph nodes of patients with IPF compared to lung cancer and in IPF lungs compared to control lungs. Tracheobronchial lymph nodes isolated on day 14 from bleomycin-treated mice exhibited increased size and higher PD-1, PD-L1 mRNA levels compared to saline-treated animals. Pembrolizumab blunted bleomycin-induced lung fibrosis, as indicated by reduction in Ashcroft score and improvement in respiratory mechanics. Conclusions: Mediastinal lymph nodes of patients with IPF exhibit differential expression profiles than those of patients with lung cancer indicating distinct immune-mediated pathways regulating fibrogenesis and carcinogenesis. PD-1 expression in mediastinal lymph nodes is in line with lung tissue expression. Lower doses of pembrolizumab might exert antifibrotic effects. Clinical trials aiming to endotype patients based on mediastinal lymph node profiling and accordingly implement targeted therapies such as PD-1 inhibitors are greatly anticipated. [ABSTRACT FROM AUTHOR]

Subgroup identification (clustering) is an important problem in biomedical research. Gene expression profiles are commonly utilized to define subgroups. Longitudinal gene expression profiles might provide additional information on disease progression than what is captured by baseline profiles alone. Therefore, subgroup identification could be more accurate and effective with the aid of longitudinal gene expression data. However, existing statistical methods are unable to fully utilize these data for patient clustering. In this article, we introduce a novel clustering method in the Bayesian setting based on longitudinal gene expression profiles. This method, called BClustLonG, adopts a linear mixed-effects framework to model the trajectory of genes over time, while clustering is jointly conducted based on the regression coefficients obtained from all genes. In order to account for the correlations among genes and alleviate the high dimensionality challenges, we adopt a factor analysis model for the regression coefficients. The Dirichlet process prior distribution is utilized for the means of the regression coefficients to induce clustering. Through extensive simulation studies, we show that BClustLonG has improved performance over other clustering methods. When applied to a dataset of severely injured (burn or trauma) patients, our model is able to identify interesting subgroups. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: Although many modeling approaches have been developed to jointly analyze longitudinal biomarkers and a time‐to‐event outcome, most of these methods can only handle one or a few biomarkers. In this article, we propose a novel joint latent class model to deal with high dimensional longitudinal biomarkers. Our model has three components: a class membership model, a survival submodel, and a longitudinal submodel. In our model, we assume that covariates can potentially affect biomarkers and class membership. We adopt a penalized likelihood approach to infer which covariates have random effects and/or fixed effects on biomarkers, and which covariates are informative for the latent classes. Through extensive simulation studies, we show that our proposed method has improved performance in prediction and assigning subjects to the correct classes over other joint modeling methods and that bootstrap can be used to do inference for our model. We then apply our method to a dataset of patients with idiopathic pulmonary fibrosis, for whom gene expression profiles were measured longitudinally. We are able to identify four interesting latent classes with one class being at much higher risk of death compared to the other classes. We also find that each of the latent classes has unique trajectories in some genes, yielding novel biological insights. [ABSTRACT FROM AUTHOR]

Background: We have previously shown that SHP2 downregulation may predispose fibroblasts to differentiate into myofibroblasts and proposed a role for SHP2 downregulation in the pathogenesis of idiopathic pulmonary fibrosis (IPF). Recent data have shown that SHP2 localizes to the mitochondrial intercristae, and its overexpression enhances mitochondrial metabolism leading to oxidative stress and senescence. Objective: To determine the effect of SHP2 on fibrotic responses. Methods and Results: Primary mouse lung fibroblasts derived from mice carrying a conditional knock-in mutation (D61G/+), rendering the SHP2 catalytic domain constitutively active, had reduced proliferation (1.6-fold, p < 0.05), migration (2-fold, p < 0.05), as well as reduced responsiveness of TGFB-1 induced fibroblasts-to-myofibroblasts differentiation, compared to wild-type ones. Electron microscope analysis revealed that SHP2 D61G/+ mouse lung fibroblasts were characterized by mitochondrial abnormalities, including swollen mitochondria with disrupted electron-lucent cristae and an increased number of autophagosomes compared to wild-type ones. SHP2 D61G/+ MLFs exhibited increased protein levels of autophagy markers, including LC3B-II and p-62, evidence that was confirmed by immunofluorescence analysis. Mitochondrial function analysis revealed that stable (genotype D61G/+) overexpression of SHP2 led to impaired mitochondrial function, as assessed by decreased mitochondrial membrane potential (1.29-fold, p < 0.05), coupling efficiency (1.82 fold, p < 0.05), oxygen consumption rate (1.9-fold, p < 0.05), and increased reactive oxygen species production both at baseline (1.75-fold, p < 0.05) and following H2O2 stimulation (1.63-fold, p < 0.05) compared to wild-type ones (SHP2+/+). SHP2 D61G/+ mouse lung fibroblasts showed enhanced AMPK activity, as well as decreased activation of the mTORC1 signaling pathway, potentially leading to ineffective mitochondrial metabolism and increased autophagy. Conclusions: SHP2 attenuates fibrotic responses in fibroblast cell lines through negative regulation of mitochondrial metabolism and induction of autophagy. SHP2 activation may represent a promising therapeutic strategy for patients with fibrotic lung diseases. [ABSTRACT FROM AUTHOR]

Mitogen-activated protein kinase (MAPK) phosphatase 5 (MKP-5) is a member of the dual-specificity family of protein tyrosine phosphatases that negatively regulates p38 MAPK and the JNK. MKP-5-deficient mice exhibit improved muscle repair and reduced fibrosis in an animal model of muscular dystrophy. Here, we asked whether the effects of MKP-5 on muscle fibrosis extend to other tissues. Using a bleomycin-induced model of pulmonary fibrosis, we found that MKP-5-deficient mice were protected from the development of lung fibrosis, expressed reduced levels of hydroxyproline and fibrogenic genes, and displayed marked polarization towards an M1-macrophage phenotype. We showed that the profibrogenic effects of the transforming growth factor-β1 (TGF-β1) were inhibited in MKP5-deficient lung fibroblasts. MKP-5-deficient fibroblasts exhibited enhanced p38 MAPK activity, impaired Smad3 phosphorylation, increased Smad7 levels, and decreased expression of fibrogenic genes. Myofibroblast differentiation was attenuated in MKP-5-deficient fibroblasts. Finally, we found that MKP-5 expression was increased in idiopathic pulmonary fibrosis (IPF)-derived lung fibroblasts but not in whole IPF lungs. These data suggest that MKP-5 plays an essential role in promoting lung fibrosis. Our results couple MKP-5 with the TGF-1 signaling machinery and imply that MKP-5 inhibition may serve as a therapeutic target for human lung fibrosis. [ABSTRACT FROM AUTHOR]

Bpifa1 (BPI fold-containing group A member 1) is an airway host-protective protein with immunomodulatory properties that binds to LPS and is regulated by infectious and inflammatory signals. Differential expression of Bpifa1 has been widely reported in lung disease, yet the biological significance of this observation is unclear. We sought to understand the role of Bpifa1 fluctuations in modulating lung inflammation. We treated wild-type (WT) and Bpifa1−/− mice with intranasal LPS and performed immunological and transcriptomic analyses of lung tissue to determine the immune effects of Bpifa1 deficiency. We show that neutrophil (polymorphonuclear cells, PMNs) lung recruitment and transmigration to the airways in response to LPS is impaired in Bpifa1−/− mice. Transcriptomic analysis revealed a signature of 379 genes that differentiated Bpifa1−/− from WT mice. During acute lung inflammation, the most downregulated genes in Bpifa1−/− mice were Cxcl9 and Cxcl10. Bpifa1−/− mice had lower bronchoalveolar lavage concentrations of C-X-C motif chemokine ligand 10 (Cxcl10) and Cxcl9, interferon-inducible PMN chemokines. This was consistent with lower expression of IFNγ, IFNλ, downstream IFN-stimulated genes, and IFN-regulatory factors, which are important for the innate immune response. Administration of Cxcl10 before LPS treatment restored the inflammatory response in Bpifa1−/− mice. Our results identify a novel role for Bpifa1 in the regulation of Cxcl10-mediated PMN recruitment to the lungs via IFNγ and -λ signaling during acute inflammation. [ABSTRACT FROM AUTHOR]

Investigation of the Th1 immune response in sarcoidosis CD4+ T cells has revealed reduced proliferative capacity and cytokine expression upon TCR stimulation. In other disease models, such cellular dysfunction has been associated with a step-wise, progressive loss of T cell function that results from chronic antigenic stimulation. T cell exhaustion is defined by decreased cytokine production upon TCR activation, decreased proliferation, increased expression of inhibitory cell surface receptors, and increased susceptibility to apoptosis. We characterized sarcoidosis CD4+ T cell immune function in systemic and local environments among subjects undergoing disease progression compared to those experiencing disease resolution. Spontaneous and TCR-stimulated Th1 cytokine expression and proliferation assays were performed in 53 sarcoidosis subjects and 30 healthy controls. PD-1 expression and apoptosis were assessed by flow cytometry. Compared to healthy controls, sarcoidosis CD4+ T cells demonstrated reductions in Th1 cytokine expression, proliferative capacity (p < 0.05), enhanced apoptosis (p < 0.01), and increased PD-1 expression (p < 0.001). BAL-derived CD4+ T cells also demonstrated multiple facets of T cell exhaustion (p < 0.05). Reversal of CD4+ T cell exhaustion was observed in subjects undergoing spontaneous resolution (p < 0.05). Sarcoidosis CD4+ T cells exhibit loss of cellular function during progressive disease that follows the archetype of T cell exhaustion. [ABSTRACT FROM AUTHOR]

Pulmonary fibrosis is a progressive and often fatal condition that is believed to be partially orchestrated by macrophages. Mechanisms that control migration of these cells into and within the lung remain undefined. We evaluated the contributions of the semaphorin receptor, plexin C1 (PLXNC1), and the exocytic calcium sensor, synaptotagmin 7 (Syt7), in these processes. We evaluated the role of PLXNC1 in macrophage migration by using Boyden chambers and scratch tests, characterized its contribution to experimentally induced lung fibrosis in mice, and defined the mechanism for our observations. Our findings reveal that relative to control participants, patients with idiopathic pulmonary fibrosis demonstrate excessive monocyte migration and underexpression of PLXNC1 in the lungs and circulation, a finding that is recapitulated in the setting of scleroderma-related interstitial lung disease. Relative to wild type, PLXNC1-/- mouse macrophages are excessively migratory, and PLXNC1-/- mice show exacerbated collagen accumulation in response to either inhaled bleomycin or inducible lung targeted TGF-β1 overexpression. These findings are ameliorated by replacement of PLXNC1 on bone marrow-derived cells or by genetic deletion of Syt7. These data demonstrate the previously unrecognized observation that PLXNC1 deficiency permits Syt7-mediated macrophage migration and enhances mammalian lung fibrosis. [ABSTRACT FROM AUTHOR]

Although aging is a known risk factor for idiopathic pulmonary fibrosis (IPF), the pathogenic mechanisms that underlie the effects of advancing age remain largely unexplained. Some age-related neurodegenerative diseases have an etiologythat is related to mitochondrial dysfunction. Here, we found that alveolar type II cells (AECIIs) in the lungs of IPF patients exhibit marked accumulation of dysmorphic and dysfunctional mitochondria. These mitochondrial abnormalities in AECIIs of IPF lungs were associated with upregulation of ER stress markers and were recapitulated in normal mice with advancing age in response to stimulation of ER stress. We found that impaired mitochondria in IPF and aging lungs were associated with low expression of PTEN-induced putative kinase 1 (PINK1). Knockdown of PINK1 expression in lung epithelial cells resulted in mitochondria depolarization and expression of profibrotic factors. Moreover, young PINKl-deficient mice developed similarly dysmorphic, dysfunctional mitochondria in the AECIIs and were vulnerable to apoptosis and development of lung fibrosis. Our data indicate that PINK1 deficiency results in swollen, dysfunctional mitochondria and defective mitophagy, and promotes fibrosis in the aging lung. [ABSTRACT FROM AUTHOR]