Summary Chronic obstructive pulmonary disease (COPD) is a common, complex, and heterogeneous disorder that is responsible for substantial and growing morbidity, mortality, and health-care expense ...worldwide. Of imperative importance to decipher the complexity of COPD is to identify groups of patients with similar clinical characteristics, prognosis, or therapeutic needs, the so-called clinical phenotypes. This strategy is logical for research but might be of little clinical value because clinical phenotypes can overlap in the same patient and the same clinical phenotype could result from different biological mechanisms. With the goal to match assessment with treatment choices, the latest iteration of guidelines from the Global Initiative for Chronic Obstructive Lung Disease reorganised treatment objectives into two categories: to improve symptoms (ie, dyspnoea and health status) and to decrease future risk (as predicted by forced expiratory volume in 1 s level and exacerbations history). This change thus moves treatment closer to individualised medicine with available bronchodilators and anti-inflammatory drugs. Yet, future treatment options are likely to include targeting endotypes that represent subtypes of patients defined by a distinct pathophysiological mechanism. Specific biomarkers of these endotypes would be particularly useful in clinical practice, especially in patients in which clinical phenotype alone is insufficient to identify the underlying endotype. A few series of potential COPD endotypes and biomarkers have been suggested. Empirical knowledge will be gained from proof-of-concept trials in COPD with emerging drugs that target specific inflammatory pathways. In every instance, specific endotype and biomarker efforts will probably be needed for the success of these trials, because the pathways are likely to be operative in only a subset of patients. Network analysis of human diseases offers the possibility to improve understanding of disease pathobiological complexity and to help with the development of new treatment alternatives and, importantly, a reclassification of complex diseases. All these developments should pave the way towards personalised treatment of patients with COPD in the clinic.
Background Eosinophilic airway inflammation is heterogeneous in asthmatic patients. We recently described a distinct subtype of asthma defined by the expression of genes inducible by TH 2 cytokines ...in bronchial epithelium. This gene signature, which includes periostin, is present in approximately half of asthmatic patients and correlates with eosinophilic airway inflammation. However, identification of this subtype depends on invasive airway sampling, and hence noninvasive biomarkers of this phenotype are desirable. Objective We sought to identify systemic biomarkers of eosinophilic airway inflammation in asthmatic patients. Methods We measured fraction of exhaled nitric oxide (F eno ), peripheral blood eosinophil, periostin, YKL-40, and IgE levels and compared these biomarkers with airway eosinophilia in asthmatic patients. Results We collected sputum, performed bronchoscopy, and matched peripheral blood samples from 67 asthmatic patients who remained symptomatic despite maximal inhaled corticosteroid treatment (mean FEV1 , 60% of predicted value; mean Asthma Control Questionnaire ACQ score, 2.7). Serum periostin levels are significantly increased in asthmatic patients with evidence of eosinophilic airway inflammation relative to those with minimal eosinophilic airway inflammation. A logistic regression model, including sex, age, body mass index, IgE levels, blood eosinophil numbers, F eno levels, and serum periostin levels, in 59 patients with severe asthma showed that, of these indices, the serum periostin level was the single best predictor of airway eosinophilia ( P = .007). Conclusion Periostin is a systemic biomarker of airway eosinophilia in asthmatic patients and has potential utility in patient selection for emerging asthma therapeutics targeting TH 2 inflammation.
With novel therapies in development, there is an opportunity to consider asthma remission as a treatment goal. In this Rostrum, we present a generalized framework for clinical and complete remission ...in asthma, on and off treatment, developed on the basis of medical literature and expert consensus. A modified Delphi survey approach was used to ascertain expert consensus on core components of asthma remission as a treatment target. Phase 1 identified other chronic inflammatory diseases with remission definitions. Phase 2 evaluated components of those definitions as well as published definitions of spontaneous asthma remission. Phase 3 evaluated a remission framework created using consensus findings. Clinical remission comprised 12 or more months with (1) absence of significant symptoms by validated instrument, (2) lung function optimization/stabilization, (3) patient/provider agreement regarding remission, and (4) no use of systemic corticosteroids. Complete remission was defined as clinical remission plus objective resolution of asthma-related inflammation and, if appropriate, negative bronchial hyperresponsiveness. Remission off treatment required no asthma treatment for 12 or more months. The proposed framework is a first step toward developing asthma remission as a treatment target and should be refined through future research, patient input, and clinical study.
A large body of experimental evidence supports the hypothesis that T‐helper 2 (Th2) cytokines orchestrate allergic airway inflammation in animal models. However, human asthma is heterogeneous with ...respect to clinical features, cellular sources of inflammation, and response to common therapies. This disease heterogeneity has been investigated using sputum cytology as well as unbiased clustering approaches using cellular and clinical data. Important differences in cytokine‐driven inflammation may underlie this heterogeneity, and studies in human subjects with asthma have begun to elucidate these molecular differences. This molecular heterogeneity may be assessed by existing biomarkers (induced sputum evaluation or exhaled nitric oxide testing) or may require novel biomarkers. Effective testing and application of emerging therapies that target Th2 cytokines will depend on accurate and easily obtained biomarkers of this molecular heterogeneity in asthma. Furthermore, whether other non‐Th2 cytokine pathways underlie airway inflammation in specific subsets of patients with asthma is an unresolved question and an important goal of future research using both mouse models and human studies.
Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and likely includes a subgroup that is biologically comparable to asthma. Studying asthma-associated gene expression changes in ...COPD could add insight into COPD pathogenesis and reveal biomarkers that predict a favorable response to corticosteroids.
To determine whether asthma-associated gene signatures are increased in COPD and associated with asthma-related features.
We compared disease-associated airway epithelial gene expression alterations in an asthma cohort (n = 105) and two COPD cohorts (n = 237, 171). The T helper type 2 (Th2) signature (T2S) score, a gene expression metric induced in Th2-high asthma, was evaluated in these COPD cohorts. The T2S score was correlated with asthma-related features and response to corticosteroids in COPD in a randomized, placebo-controlled trial, the Groningen and Leiden Universities study of Corticosteroids in Obstructive Lung Disease (GLUCOLD; n = 89).
The 200 genes most differentially expressed in asthma versus healthy control subjects were enriched among genes associated with more severe airflow obstruction in these COPD cohorts (P < 0.001), suggesting significant gene expression overlap. A higher T2S score was associated with decreased lung function (P < 0.001), but not asthma history, in both COPD cohorts. Higher T2S scores correlated with increased airway wall eosinophil counts (P = 0.003), blood eosinophil percentage (P = 0.03), bronchodilator reversibility (P = 0.01), and improvement in hyperinflation after corticosteroid treatment (P = 0.019) in GLUCOLD.
These data identify airway gene expression alterations that can co-occur in asthma and COPD. The association of the T2S score with increased severity and "asthma-like" features (including a favorable corticosteroid response) in COPD suggests that Th2 inflammation is important in a COPD subset that cannot be identified by clinical history of asthma.
Type 2 (T2) inflammation drives airway dysfunction in many patients with asthma; yet, we lack a comprehensive understanding of the airway immune cell types and networks that sustain this ...inflammation. Moreover, defects in the airway immune system in patients with asthma without T2 inflammation are not established.
To determine the gene networks that sustain T2 airway inflammation in T2-high asthma and to explore the gene networks that characterize T2-low asthma.
Network analysis of sputum cell transcriptome expression data from 84 subjects with asthma and 27 healthy control subjects was used to identify immune cell type-enriched networks that underlie asthma subgroups.
Sputum T2 gene expression was characterized by an immune cell network derived from multiple innate immune cells, including eosinophils, mast cells/basophils, and inflammatory dendritic cells. Clustering of subjects within this network stratified subjects into T2-high and T2-low groups, but it also revealed a subgroup of T2-high subjects with uniformly higher expression of the T2 network. These "T2-ultrahigh subjects" were characterized clinically by older age and more severe airflow obstruction and pathologically by a second T2 network derived from T2-skewed, CD11b
/CD103
/IRF4
classical dendritic cells. Subjects with T2-low asthma were differentiated from healthy control subjects by lower expression of a cytotoxic CD8
T-cell network, which was negatively correlated with body mass index and plasma IL-6 concentrations.
Persistent airway T2 inflammation is a complex construct of innate and adaptive immunity gene expression networks that are variable across individuals with asthma and persist despite steroid treatment. Individuals with T2-low asthma exhibit an airway deficiency in cytotoxic T cells associated with obesity-driven inflammation.
Chronic obstructive pulmonary disease (COPD) is now well recognized to be a phenotypically heterogeneous disease, and this heterogeneity is underpinned by biological heterogeneity. An "endotype" is a ...group of patients who share the same observed characteristic(s) because of shared underlying biology, and the "endotype" concept has emerged as one way of bringing order to this phenotypic heterogeneity by focusing on its biological underpinnings. In principle, biomarkers can help identify endotypes and mark these specific groups of patients as suitable candidates for targeted biological therapies. Among the better-described endotypes of COPD are alpha-1 antitrypsin deficiency and eosinophilic COPD. Both of these endotypes have biomarkers and at least some evidence of preferential benefit from targeted therapy. Other biological pathways that may define endotypes of COPD include more general pathways of type 2 inflammation, IL-17-driven inflammation (due to autoimmunity or deposition of nanoparticulate carbon black), bacterial colonization, pathological alterations of the airway mucus gel, and others that are beyond the scope of this review. Whether these biological pathways ultimately are found to segregate patients into very distinct endotypes or subsets (like alpha-1 antitrypsin deficiency) or, instead, are present as "treatable traits" in various combinations is uncertain. However imperfect, the endotype concept forces a focus on heterogeneity at a biological level, and the development of biomarkers of biological heterogeneity should help advance the goal of developing new therapies for COPD.
Extracellular microRNAs (miRNAs) and other small RNAs are implicated in cellular communication and may be useful as disease biomarkers. We systematically compared small RNAs in 12 human biofluid ...types using RNA sequencing (RNA-seq). miRNAs and tRNA-derived RNAs (tDRs) accounted for the majority of mapped reads in all biofluids, but the ratio of miRNA to tDR reads varied from 72 in plasma to 0.004 in bile. miRNA levels were highly correlated across all biofluids, but levels of some miRNAs differed markedly between biofluids. tDR populations differed extensively between biofluids. Y RNA fragments were seen in all biofluids and accounted for >10% of reads in blood plasma, serum, and cerebrospinal fluid (CSF). Reads mapping exclusively to Piwi-interacting RNAs (piRNAs) were very rare, except in seminal plasma. These results demonstrate extensive differences in small RNAs between human biofluids and provide a useful resource for investigating extracellular RNA biology and developing biomarkers.
Multidetector row computed tomography (MDCT) is increasingly taking a central role in identifying subphenotypes within chronic obstructive pulmonary disease (COPD), asthma, and other lung-related ...disease populations, allowing for the quantification of the amount and distribution of altered parenchyma along with the characterization of airway and vascular anatomy. The embedding of quantitative CT (QCT) into a multicenter trial with a variety of scanner makes and models along with the variety of pressures within a clinical radiology setting has proven challenging, especially in the context of a longitudinal study. SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study), sponsored by the National Institutes of Health, has established a QCT lung assessment system (QCT-LAS), which includes scanner-specific imaging protocols for lung assessment at total lung capacity and residual volume. Also included are monthly scanning of a standardized test object and web-based tools for subject registration, protocol assignment, and data transmission coupled with automated image interrogation to assure protocol adherence. The SPIROMICS QCT-LAS has been adopted and contributed to by a growing number of other multicenter studies in which imaging is embedded. The key components of the SPIROMICS QCT-LAS along with evidence of implementation success are described herein. While imaging technologies continue to evolve, the required components of a QCT-LAS provide the framework for future studies, and the QCT results emanating from SPIROMICS and the growing number of other studies using the SPIROMICS QCT-LAS will provide a shared resource of image-derived pulmonary metrics.