A blood and bronchoalveolar lavage protein signature of rapid FEV1 decline in smoking-associated COPD.

Accelerated progression of chronic obstructive pulmonary disease (COPD) is associated with increased risks of hospitalization and death. Prognostic insights into mechanisms and markers of progression could facilitate development of disease-modifying therapies. Although individual biomarkers exhibit some predictive value, performance is modest and their univariate nature limits network-level insights. To overcome these limitations and gain insights into early pathways associated with rapid progression, we measured 1305 peripheral blood and 48 bronchoalveolar lavage proteins in individuals with COPD [n = 45, mean initial forced expiratory volume in one second (FEV1) 75.6 ± 17.4% predicted]. We applied a data-driven analysis pipeline, which enabled identification of protein signatures that predicted individuals at-risk for accelerated lung function decline (FEV1 decline ≥ 70 mL/year) ~ 6 years later, with high accuracy. Progression signatures suggested that early dysregulation in elements of the complement cascade is associated with accelerated decline. Our results propose potential biomarkers and early aberrant signaling mechanisms driving rapid progression in COPD.

Identification of a unique temporal signature in blood and BAL associated with IPF progression.

Idiopathic pulmonary fibrosis (IPF) is a progressive and heterogeneous interstitial lung disease of unknown origin with a low survival rate. There are few treatment options available due to the fact that mechanisms underlying disease progression are not well understood, likely because they arise from dysregulation of complex signaling networks spanning multiple tissue compartments. To better characterize these networks, we used systems-focused data-driven modeling approaches to identify cross-tissue compartment (blood and bronchoalveolar lavage) and temporal proteomic signatures that differentiated IPF progressors and non-progressors. Partial least squares discriminant analysis identified a signature of 54 baseline (week 0) blood and lung proteins that differentiated IPF progression status by the end of 80 weeks of follow-up with 100% cross-validation accuracy. Overall we observed heterogeneous protein expression patterns in progressors compared to more homogenous signatures in non-progressors, and found that non-progressors were enriched for proteomic processes involving regulation of the immune/defense response. We also identified a temporal signature of blood proteins that was significantly different at early and late progressor time points (p < 0.0001), but not present in non-progressors. Overall, this approach can be used to generate new hypothesis for mechanisms associated with IPF progression and could readily be translated to other complex and heterogeneous diseases.

Inference of Cellular Immune Environments in Sputum and Peripheral Blood Associated with Acute Exacerbations of COPD.

INTRODUCTION: Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States, with high associated costs. Most of the cost burden results from acute exacerbations of COPD (AE-COPD), events associated with heightened symptoms and mortality. Cellular mechanisms underlying AE-COPD are poorly understood, likely because they arise from dysregulation of complex immune networks across multiple tissue compartments. METHODS: To gain systems-level insight into cellular environments relevant to exacerbation, we applied data-driven modeling approaches to measurements of immune factors (cytokines and flow cytometry) measured previously in two different human tissue environments (sputum and peripheral blood) during the stable and exacerbated state. RESULTS: Using partial least squares discriminant analysis, we identified a unique signature of cytokines in serum that differentiated stable and AE-COPD better than individual measurements. Furthermore, we found that models integrating data across tissue compartments (serum and sputum) trended towards being more accurate. The resulting paracrine signature defining AE-COPD events combined elevations of proteins associated with cell adhesion (sVCAM-1, sICAM-1) and increased levels of neutrophils and dendritic cells in blood with elevated chemoattractants (IP-10 and MCP-2) in sputum. CONCLUSIONS: Our results supported a new hypothesis that AE-COPD is driven by immune cell trafficking into the lung, which requires expression of cell adhesion molecules and raised levels of innate immune cells in blood, with parallel upregulated expression of specific chemokines in pulmonary tissue. Overall, this work serves as a proof-of-concept for using data-driven modeling approaches to generate new insights into cellular processes involved in complex pulmonary diseases.

Lung Microbiota Contribute to Pulmonary Inflammation and Disease Progression in Pulmonary Fibrosis.

Rationale: Idiopathic pulmonary fibrosis (IPF) causes considerable global morbidity and mortality, and its mechanisms of disease progression are poorly understood. Recent observational studies have reported associations between lung dysbiosis, mortality, and altered host defense gene expression, supporting a role for lung microbiota in IPF. However, the causal significance of altered lung microbiota in disease progression is undetermined. Objectives: To examine the effect of microbiota on local alveolar inflammation and disease progression using both animal models and human subjects with IPF. Methods: For human studies, we characterized lung microbiota in BAL fluid from 68 patients with IPF. For animal modeling, we used a murine model of pulmonary fibrosis in conventional and germ-free mice. Lung bacteria were characterized using 16S rRNA gene sequencing with novel techniques optimized for low-biomass sample load. Microbiota were correlated with alveolar inflammation, measures of pulmonary fibrosis, and disease progression. Measurements and Main Results: Disruption of the lung microbiome predicts disease progression, correlates with local host inflammation, and participates in disease progression. In patients with IPF, lung bacterial burden predicts fibrosis progression, and microbiota diversity and composition correlate with increased alveolar profibrotic cytokines. In murine models of fibrosis, lung dysbiosis precedes peak lung injury and is persistent. In germ-free animals, the absence of a microbiome protects against mortality. Conclusions: Our results demonstrate that lung microbiota contribute to the progression of IPF. We provide biological plausibility for the hypothesis that lung dysbiosis promotes alveolar inflammation and aberrant repair. Manipulation of lung microbiota may represent a novel target for the treatment of IPF.

Proteomics: Clinical and research applications in respiratory diseases.

The proteome is the study of the protein content of a definable component of an organism in biology. However, the tissue-specific expression of proteins and the varied post-translational modifications, splice variants and protein-protein complexes that may form, make the study of protein a challenging yet vital tool in answering many of the unanswered questions in medicine and biology to date. Indeed, the spatial, temporal and functional composition of proteins in the human body has proven difficult to elucidate for many years. Given the effect of microRNA and epigenetic regulation on silencing and enhancing gene transcription, the study of protein arguably provides more accurate information on homeostasis and perturbation in health and disease. There have been significant advances in the field of proteomics in recent years, with new technologies and platforms available to the research community. In this review, we briefly discuss some of these new technologies and developments in the context of respiratory disease. We also discuss the types of data science approaches to analyses and interpretation of the large volumes of data generated in proteomic studies. We discuss the application of these technologies with regard to respiratory disease and highlight the potential for proteomics in generating major advances in the understanding of respiratory pathophysiology into the future.

Lung Dysbiosis, Inflammation, and Injury in Hematopoietic Cell Transplantation.

RATIONALE: Hematopoietic cell transplant (HCT) is a common treatment for hematological neoplasms and autoimmune disorders. Among HCT recipients, pulmonary complications are common, morbid, and/or lethal, and they have recently been associated with gut dysbiosis. The role of lung microbiota in post-HCT pulmonary complications is unknown. OBJECTIVES: To investigate the role of lung microbiota in post-HCT pulmonary complications using animal modeling and human BAL fluid. METHODS: For animal modeling, we used an established murine model of HCT with and without postengraftment herpes virus infection. For human studies, we characterized lung microbiota in BAL fluid from 43 HCT recipients. Lung bacteria were characterized using 16S ribosomal RNA gene sequencing and were compared with lung histology (murine) and with alveolar inflammation and pulmonary function testing (human). MEASUREMENTS AND MAIN RESULTS: Both HCT and viral infection independently altered the composition of murine lung microbiota, but they had no effect on lung microbial diversity. By contrast, combined HCT and viral infection profoundly altered lung microbiota, decreasing community diversity with an associated pneumonitis. Among human HCT recipients, increased relative abundance of the Proteobacteria phylum was associated with impaired pulmonary function, and lung microbiota were significantly associated with alveolar concentrations of inflammatory cytokines. CONCLUSIONS: In animal models and human subjects, lung dysbiosis is a prominent feature of HCT. Lung dysbiosis is correlated with histologic, immunologic, and physiologic features of post-HCT pulmonary complications. Our findings suggest the lung microbiome may be an unappreciated target for the prevention and treatment of post-HCT pulmonary complications.

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

This corrects the article DOI: 10.1038/srep46560.

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.