Multidimensional endotypes of asthma: topological data analysis of cross-sectional clinical, pathological, and immunological data

Novel dimensionality reduction method, Taelcore, enhances lung transplantation risk prediction

In this work, we present a new approach to predict the risk of acute cellular rejection (ACR) after lung transplantation by using machine learning algorithms, such as Multilayer Perceptron (MLP) or Autoencoder (AE), and combining them with topological data analysis (TDA) tools. Our proposed method, named topological autoencoder with best linear combination for optimal reduction of embeddings (Taelcore), effectively reduces the dimensionality of high-dimensional datasets and yields better results compared to other models. We validate the effectiveness of Taelcore in reducing the prediction error rate on four datasets. Furthermore, we demonstrate that Taelcore's topological improvements have a positive effect on the majority of the machine learning algorithms used. By providing a new way to diagnose patients and detect complications early, this work contributes to improved clinical outcomes in lung transplantation.

Examining Outcomes in Patients Admitted With Comorbid Peripheral Artery Disease and Microvascular Disease

BACKGROUND

Peripheral artery disease (PAD) and microvascular disease (MVD) are highly prevalent conditions that share common risk factors. This observational study aimed to characterize patients with both conditions and determine the impact of comorbid PAD/MVD on outcomes.

METHODS AND RESULTS

Patients admitted across 31 states January 2011 through December 2018 with a primary or secondary diagnosis of PAD or MVD were included from the National Readmissions Database and weighted to approximate a national sample. Those age <18 years or with nonatherosclerotic leg injuries were excluded. Patients were divided into 3 groups: PAD-only, MVD-only, or comorbid PAD/MVD. Multiple logistic regression was used to evaluate associations with major and minor amputations, major adverse cardiac events, and in-hospital mortality. Cox regression was used to evaluate associations with readmission within 1 year. The PAD group was used as reference. The final cohort included 33 972 772 admissions: 9.1 million with PAD, 21.3 million with MVD, and 3.6 million with both. Annual admissions for PAD/MVD increased to >500 000 in 2018. Major and minor amputations increased ≈50% for PAD/MVD between 2011 and 2018. Compared with PAD-only, PAD/MVD was associated with a higher risk for major amputation (odds ratio [OR], 1.30 [95% CI, 1.28-1.32]), minor amputation (OR, 2.15 [95% CI, 2.12-2.18]), major adverse cardiac events (OR, 1.04 [95% CI, 1.03-1.04]), in-hospital mortality (OR, 1.07 [95% CI, 1.05-1.09]), and readmission (hazard ratio, 1.02 [95% CI, 1.02-1.02]) after adjustment for baseline factors.

CONCLUSIONS

Comorbid MVD is present in a large and growing number of patients with PAD and is associated with augmented risk for adverse outcomes. Further prospective research is merited to understand this vulnerable population.

IL-33 Induces an Antiviral Signature in Mast Cells but Enhances Their Permissiveness for Human Rhinovirus Infection

Mast cells (MCs) are classically associated with allergic asthma but their role in antiviral immunity is unclear. Human rhinoviruses (HRVs) are a major cause of asthma exacerbations and can infect and replicate within MCs. The primary site of HRV infection is the airway epithelium and MCs localise to this site with increasing asthma severity. The asthma susceptibility gene, IL-33, encodes an epithelial-derived cytokine released following HRV infection but its impact on MC antiviral responses has yet to be determined. In this study we investigated the global response of LAD2 MCs to IL-33 stimulation using RNA sequencing and identified genes involved in antiviral immunity. In spite of this, IL-33 treatment increased permissiveness of MCs to HRV16 infection which, from the RNA-Seq data, we attributed to upregulation of ICAM1. Flow cytometric analysis confirmed an IL-33-dependent increase in ICAM1 surface expression as well as LDLR, the receptors used by major and minor group HRVs for cellular entry. Neutralisation of ICAM1 reduced the IL-33-dependent enhancement in HRV16 replication and release in both LAD2 MCs and cord blood derived MCs. These findings demonstrate that although IL-33 induces an antiviral signature in MCs, it also upregulates the receptors for HRV entry to enhance infection. This highlights the potential for a gene-environment interaction involving IL33 and HRV in MCs to contribute to virus-induced asthma exacerbations.

Measurement of Exhaled Volatile Organic Compounds as a Biomarker for Personalised Medicine: Assessment of Short-Term Repeatability in Severe Asthma

The measurement of exhaled volatile organic compounds (VOCs) in exhaled breath (breathomics) represents an exciting biomarker matrix for airways disease, with early research indicating a sensitivity to airway inflammation. One of the key aspects to analytical validity for any clinical biomarker is an understanding of the short-term repeatability of measures. We collected exhaled breath samples on 5 consecutive days in 14 subjects with severe asthma who had undergone extensive clinical characterisation. Principal component analysis on VOC abundance across all breath samples revealed no variance due to the day of sampling. Samples from the same patients clustered together and there was some separation according to T2 inflammatory markers. The intra-subject and between-subject variability of each VOC was calculated across the 70 samples and identified 30.35% of VOCs to be erratic: variable between subjects but also variable in the same subject. Exclusion of these erratic VOCs from machine learning approaches revealed no apparent loss of structure to the underlying data or loss of relationship with salient clinical characteristics. Moreover, cluster evaluation by the silhouette coefficient indicates more distinct clustering. We are able to describe the short-term repeatability of breath samples in a severe asthma population and corroborate its sensitivity to airway inflammation. We also describe a novel variance-based feature selection tool that, when applied to larger clinical studies, could improve machine learning model predictions.

The Emerging Roles of T Helper Cell Subsets and Cytokines in Severe Neutrophilic Asthma

Neutrophilic asthma (NA) is a severe type of steroid resistant asthma, and so far the immune mechanisms underlying NA are not clear. In this article, we performed a comprehensive assessment of Th-cell subsets and cytokines in severe NA patients. A total of 13 healthy individuals and 31 severe asthma patients were enrolled in this study. Refractory asthma patients were defined as those with eosinophilic asthma (EA, accounted for 32% of asthmatic patients) or NA (68%) according to sputum neutrophil/eosinophil counts or blood eosinophils. Th-cell subsets in peripheral blood mononuclear cells (PBMCs) were analyzed by flow cytometry, and cytokines were detected by cytometric bead array (CBA). The results showed significant differences were observed in Th-cell phenotypes, where the number of Th1 cells were reduced and the numbers of Th2 cells were increased in NA and EA groups, respectively, when compared with healthy controls. Th17 cells were not strongly associated with severe neutrophilic asthma. The frequencies of mucosal-associated invariant T (MAIT) cells were strikingly reduced in severe asthma patients, especially in the NA group. This NA group also showed increased levels of IL-17A, IL-17F, TNF-α, and IL-6 in serum and increased levels of IL-17A, IL-17F, IFN-γ, TNF-α, IL-1β, IL-5, IL-6, and IL-8 in sputum. In addition, sputum IL-6 was positively correlated with TNF-α, IFN-γ, IL-17A, and IL-8. Our results uncovered a controversial role for Th17 cells, which were reduced in severe asthma patients. Severe neutrophilic asthma was associated with a striking deficiency of MAIT cells and high pro-inflammatory cytokine levels.

Mathematical-based microbiome analytics for clinical translation

Traditionally, human microbiology has been strongly built on the laboratory focused culture of microbes isolated from human specimens in patients with acute or chronic infection. These approaches primarily view human disease through the lens of a single species and its relevant clinical setting however such approaches fail to account for the surrounding environment and wide microbial diversity that exists in vivo. Given the emergence of next generation sequencing technologies and advancing bioinformatic pipelines, researchers now have unprecedented capabilities to characterise the human microbiome in terms of its taxonomy, function, antibiotic resistance and even bacteriophages. Despite this, an analysis of microbial communities has largely been restricted to ordination, ecological measures, and discriminant taxa analysis. This is predominantly due to a lack of suitable computational tools to facilitate microbiome analytics. In this review, we first evaluate the key concerns related to the inherent structure of microbiome datasets which include its compositionality and batch effects. We describe the available and emerging analytical techniques including integrative analysis, machine learning, microbial association networks, topological data analysis (TDA) and mathematical modelling. We also present how these methods may translate to clinical settings including tools for implementation. Mathematical based analytics for microbiome analysis represents a promising avenue for clinical translation across a range of acute and chronic disease states.

Contemporary Trends in Hospital Admissions and Outcomes in Patients With Critical Limb Ischemia: An Analysis From the National Inpatient Sample Database

BACKGROUND

Critical limb ischemia (CLI) morbidity and mortality rates have historically been disproportionately higher than for other atherosclerotic diseases, however, recent trends have not been reported. In patients admitted with CLI, we aimed to examine trends in in-hospital mortality, major amputations, length of stay, and cost of hospitalizations overall and stratified by type of revascularization procedures.

METHODS

Using 2011 to 2017 National Inpatient Sample data, we identified CLI-related admissions based on International Classification of Diseases, Ninth and Tenth Edition, Clinical Modification codes. Primary outcomes of interest were in-hospital mortality and major amputations. Secondary outcomes were the length of stay and cost of hospitalization. We stratified outcomes based on endovascular or open surgical interventions. We also performed hierarchical multivariable regression analyses of outcomes based on age, sex, race, hospital size, type, and location.

RESULTS

We identified 2 643 087 CLI-related admissions between 2011 and 2017. CLI admissions increased from 0.9% to 1.4% P_trend<0.0001 as well as overall peripheral artery disease admissions (4.5%-8.9%, P_trend<0.0001). In-hospital mortality for the entire CLI cohort decreased from 3.3% to 2.7%, P_trend<0.0001, and major amputations decreased from 10.9% to 7%, P_trend<0.0001. A decline was also noted for the length of stay from 5.7 (3.1-10.1) to 5.4 (3.0-9.2) days (P_trend<0.0001), whereas admission costs increased from USD $11 791 ($6676-$21 712) to $12 597 ($7248-$22 748; P_trend<0.0001). Endovascular interventions increased (P_trend<0.0001) against a decline in surgical interventions (P_trend<0.0001). Black race, female sex, and age ≥60 years were associated with higher in-hospital mortality, whereas Black race, male sex, and age<60 years were associated with higher major amputations.

CONCLUSIONS

A relatively small decrease in absolute numbers for mortality and major amputations were observed against a backdrop of increasing CLI admissions over recent years. Patients with CLI received more endovascular interventions than surgical interventions over time. However, admissions for endovascular interventions were characterized by higher risk patient profiles and a higher risk of major amputations as compared with surgical interventions.

Antigen presentation, autoantibody production, and therapeutic targets in autoimmune liver disease

The liver is an important immunological organ that controls systemic tolerance. The liver harbors professional and unconventional antigen-presenting cells that are crucial for tolerance induction and maintenance. Orchestrating the immune response in homeostasis depends on a healthy and well-toned immunological liver microenvironment, which is maintained by the crosstalk of liver-resident antigen-presenting cells and intrahepatic and liver-infiltrating leukocytes. In response to pathogens or autoantigens, tolerance is disrupted by unknown mechanisms. Intrahepatic parenchymal and nonparenchymal cells exhibit unique antigen-presenting properties. The presentation of microbial and endogenous lipid-, metabolite- and peptide-derived antigens from the gut via conventional and nonconventional mechanisms can educate intrahepatic immune cells and elicit effector responses or tolerance. Perturbation of this balance results in autoimmune liver diseases, such as autoimmune hepatitis, primary biliary cholangitis, and primary sclerosing cholangitis. Although the exact etiologies of these autoimmune liver diseases are unknown, it is thought that the disruption of tolerance towards self-antigens and microbial metabolites and lipids, as well as alterations in bile acid composition, may result in changes in effector cell activation and polarization and may reduce or impair protective anti-inflammatory regulatory T and B cell responses. Additionally, the canonical and noncanonical transmission of antigens and antigen:MHC complexes via trogocytosis or extracellular vesicles between different (non) immune cells in the liver may play a role in the induction of hepatic inflammation and tolerance. Here, we summarize emerging aspects of antigen presentation, autoantibody production, and the application of novel therapeutic approaches in the characterization and treatment of autoimmune liver diseases.

MAIT Cell Activation and Functions

Mucosal associated invariant T (MAIT) cells are striking in their abundance and their strict conservation across 150 million years of mammalian evolution, implying they must fulfill critical immunological function(s). MAIT cells are defined by their expression of a semi-invariant αβ TCR which recognizes biosynthetic derivatives of riboflavin synthesis presented on MR1. Initial studies focused on their role in detecting predominantly intracellular bacterial and mycobacterial infections. However, it is now recognized that there are several modes of MAIT cell activation and these are related to activation of distinct transcriptional programmes, each associated with distinct functional roles. In this minireview, we summarize current knowledge from human and animal studies of MAIT cell activation induced (1) in an MR1-TCR dependent manner in the context of inflammatory danger signals and associated with antibacterial host defense; (2) in an MR1-TCR independent manner by the cytokines interleukin(IL)-12/-15/-18 and type I interferon, which is associated with antiviral responses; and (3) a recently-described TCR-dependent “tissue repair” programme which is associated with accelerated wound healing in the context of commensal microbiota. Because of this capability for diverse functional responses in diverse immunological contexts, these intriguing cells now appear to be multifunctional effectors central to the interface of innate and adaptive immunity.

Interpatient Similarities in Cardiac Function: A Platform for Personalized Cardiovascular Medicine

OBJECTIVES

The authors applied unsupervised machine-learning techniques for integrating echocardiographic features of left ventricular (LV) structure and function into a patient similarity network that predicted major adverse cardiac event(s) (MACE) in an individual patient.

BACKGROUND

Patient similarity analysis is an evolving paradigm for precision medicine in which patients are clustered or classified based on their similarities in several clinical features.

METHODS

A retrospective cohort of 866 patients was used to develop a network architecture using 9 echocardiographic features of LV structure and function. The data for 468 patients from 2 prospective cohort registries were then added to test the model's generalizability.

RESULTS

The map of cross-sectional data in the retrospective cohort resulted in a looped patient network that persisted even after the addition of data from the prospective cohort registries. After subdividing the loop into 4 regions, patients in each region showed unique differences in LV function, with Kaplan-Meier curves demonstrating significant differences in MACE-related rehospitalization and death (both p < 0.001). Addition of network information to clinical risk predictors resulted in significant improvements in net reclassification, integrated discrimination, and median risk scores for predicting MACE (p < 0.05 for all). Furthermore, the network predicted the cardiac disease cycle in each of the 96 patients who had second echocardiographic evaluations. An improvement or remaining in low-risk regions was associated with lower MACE-related rehospitalization rates than worsening or remaining in high-risk regions (3% vs. 37%; p < 0.001).

CONCLUSIONS

Patient similarity analysis integrates multiple features of cardiac function to develop a phenotypic network in which patients can be mapped to specific locations associated with specific disease stage and clinical outcomes. The use of patient similarity analysis may have relevance for automated staging of cardiac disease severity, personalized prediction of prognosis, and monitoring progression or response to therapies.

A low-cost texture-based pipeline for predicting myocardial tissue remodeling and fibrosis using cardiac ultrasound

Background

Maturation of ultrasound myocardial tissue characterization may have far-reaching implications as a widely available alternative to cardiac magnetic resonance (CMR) for risk stratification in left ventricular (LV) remodeling.

Methods

We extracted 328 texture-based features of myocardium from still ultrasound images. After we explored the phenotypes of myocardial textures using unsupervised similarity networks, global LV remodeling parameters were predicted using supervised machine learning models. Separately, we also developed supervised models for predicting the presence of myocardial fibrosis using another cohort who underwent cardiac magnetic resonance (CMR). For the prediction, patients were divided into a training and test set (80:20).

Findings

Texture-based tissue feature extraction was feasible in 97% of total 534 patients. Interpatient similarity analysis delineated two patient groups based on the texture features: one group had more advanced LV remodeling parameters compared to the other group. Furthermore, this group was associated with a higher incidence of cardiac deaths (p = 0.001) and major adverse cardiac events (p < 0.001). The supervised models predicted reduced LV ejection fraction (<50%) and global longitudinal strain (<16%) with area under the receiver-operator-characteristics curves (ROC AUC) of 0.83 and 0.87 in the hold-out test set, respectively. Furthermore, the presence of myocardial fibrosis was predicted from only ultrasound myocardial texture with an ROC AUC of 0.84 (sensitivity 86.4% and specificity 83.3%) in the test set.

Interpretation

Ultrasound texture-based myocardial tissue characterization identified phenotypic features of LV remodeling from still ultrasound images. Further clinical validation may address critical barriers in the adoption of ultrasound techniques for myocardial tissue characterization.

Funding

None.

Beyond type 2 cytokines in asthma - new insights from old clinical trials

Introduction: Human asthma is a heterogeneous disorder on molecular, pathological, and clinical levels. The paradigm of asthma as an allergic process driven by type 2 cytokines and mediators has led to targeted biologic therapies resulting in some clinical benefit in patient subsets. However, some patient subsets and clinical manifestations do not benefit from these interventions, thus redefining unmet needs. Clinical studies of type 2 directed therapies have identified new targets under investigation in clinical development; these include epithelial alarmins, non-type 2 cytokines, cytokine receptor signaling, mast cells and neuroinflammation.Areas covered: We consider lessons learned concerning asthma pathogenesis from observational studies and clinical trials of biologic agents that target type 2 mediators. We also provide a perspective on emerging therapeutic hypotheses to target processes independent of or orthogonal to type 2 inflammation in asthma.Expert opinion: Type 2 inflammation is continuous, not discrete, and is likely a modifier of underlying dysregulated airway physiology. Non-type 2 inflammatory mediators (e.g., IL17, IL6, IFNs), microbiome, alarmins (e.g., TSLP, IL33), mast cells and sensory neurons may represent orthogonal targets to type 2 mediators. There is a need to better match targets and outcome measures in biologically defined patient populations to appropriately test hypotheses in the clinic.

Systemic levels of anti-PAD4 autoantibodies correlate with airway obstruction in cystic fibrosis

Cystic fibrosis (CF) airway disease is characterized by the long-term presence of neutrophil granulocytes. Formation of neutrophil extracellular traps (NETs) and/or autoantibodies directed against extracellular components of NETs are possible contributors to neutrophil-mediated lung damage in CF. The goal of this study was to measure their levels in CF adults compared to healthy controls and subjects with rheumatologic diseases known to develop NET-related autoantibodies and pathologies, rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). Sera were analyzed from the following number of subjects: 37 CF, 23 healthy controls (HC), 20 RA, and 21 SLE. CF had elevated serum myeloperoxidase (MPO) concentrations (347.5±56.1 ng/ml, mean+/-S.E.M., p = .0132) compared to HC (144.5±14.6 ng/ml) but not of neutrophil elastase (NE) complexed with alpha-1-antitrypsin, cell-free DNA or NE-DNA complexes. The peptidylarginine deiminase 4 (PAD4) enzyme is required for NET formation and associated DNA release in neutrophils. Serum levels of anti-PAD4 antibodies (Ab) were elevated in CF (p = .0147) compared to HC and showed an inverse correlation with a measure of lung function, FEV1% predicted (r = -0.5020, p = .015), as did MPO levels (r = -0.4801, p = .0026). Anti-PAD4 Ab levels in CF sera associated with lung infection by P. aeruginosa, but not that by S. aureus, age, sex, CF-related diabetes or the presence of musculoskeletal pain. Serum levels of anti-citrullinated protein Abs (ACPAs) and anti-nucleosome Abs were not elevated in CF compared to HC (p = .7498, p = .0678). In summary, adult CF subjects develop an autoimmune response against NET components that correlates with worsening lung disease.

Artificial Intelligence in Cardiovascular Medicine

PURPOSE OF REVIEW

The ripples of artificial intelligence are being felt in various sectors of human life. Machine learning, a subset of artificial intelligence, extracts information from large databases of information and is gaining traction in various fields of cardiology. In this review, we highlight noteworthy examples of machine learning utilization in echocardiography, nuclear cardiology, computed tomography, and magnetic resonance imaging over the past year.

RECENT FINDINGS

In the past year, machine learning (ML) has expanded its boundaries in cardiology with several positive results. Some studies have integrated clinical and imaging information to further augment the accuracy of these ML algorithms. All the studies mentioned in this review have clearly demonstrated superior results of ML in relation to conventional approaches for identifying obstructions or predicting major adverse events in reference to conventional approaches. As the influx of data arriving from gradually evolving technologies in health care and wearable devices continues to be more complex, ML may serve as the bridge to transcend the gap between health care and patients in the future. In order to facilitate a seamless transition between both, a few issues must be resolved for a successful implementation of ML in health care.

Low mucosal-associated invariant T-cell number in peripheral blood of patients with immune thrombocytopenia and their response to prednisolone

Mucosal-associated invariant T (MAIT) cells help protect against certain infections and are related to some autoimmune diseases. Immune thrombocytopenia (ITP) is a relatively rare hematological autoimmune disease associated with low platelet count. We designed a cross-sectional study wherein we examined peripheral blood samples of patients with ITP for the number of MAIT cells (CD3+TCR-Vα7.2+CD161+IL-18Rα+ lymphocytes) and their CD4/8 subsets (by flow cytometry) and levels of cytokines (by multiplex assays). The study cohort included 18 patients with ITP and 20 healthy controls (HCs). We first compared the number of MAIT cells between HCs and patients with ITP and then performed subgroup analysis in patients with ITP. The number of total MAIT cells in patients with ITP was significantly lower than that in HCs (p < 0.0001), and the CD4-CD8+ subset of MAIT cells showed the same trend. Moreover, patients with ITP refractory to prednisolone exhibited a significantly lower number of total MAIT and CD4-CD8+ MAIT cells than patients sensitive to prednisolone. The number of total MAIT and CD4-CD8+ MAIT cells was not correlated with the response to thrombopoietin receptor agonist treatment or with Helicobacter pylori infection. We found no relation between cytokine levels and response to prednisolone treatment, although the levels of IP-10 and RANTES showed a correlation with the number of total MAIT and CD4-CD8+ MAIT cells. In conclusion, total MAIT and CD4-CD8+ MAIT cells in peripheral blood were decreased in patients with ITP, correlating with their response to prednisolone.

Insights into myalgic encephalomyelitis/chronic fatigue syndrome phenotypes through comprehensive metabolomics

The pathogenesis of ME/CFS, a disease characterized by fatigue, cognitive dysfunction, sleep disturbances, orthostatic intolerance, fever, irritable bowel syndrome (IBS), and lymphadenopathy, is poorly understood. We report biomarker discovery and topological analysis of plasma metabolomic, fecal bacterial metagenomic, and clinical data from 50 ME/CFS patients and 50 healthy controls. We confirm reports of altered plasma levels of choline, carnitine and complex lipid metabolites and demonstrate that patients with ME/CFS and IBS have increased plasma levels of ceramide. Integration of fecal metagenomic and plasma metabolomic data resulted in a stronger predictive model of ME/CFS (cross-validated AUC = 0.836) than either metagenomic (cross-validated AUC = 0.745) or metabolomic (cross-validated AUC = 0.820) analysis alone. Our findings may provide insights into the pathogenesis of ME/CFS and its subtypes and suggest pathways for the development of diagnostic and therapeutic strategies.

Role of sputum biomarkers in the management of asthma

PURPOSE OF REVIEW

Airway inflammation is considered to be a cardinal feature of asthma. However, the type of airway inflammation is heterogeneous and airway inflammation may even be absent. Biomarkers may help to identify the inflammatory phenotype or endotype, especially now the time has come that targeted therapies enter daily practice.

RECENT FINDINGS

Sputum biomarkers have increased our insights into the different inflammatory asthma phenotypes, their response to treatment and their association with progression of disease. New endotypes of type 2 driven inflammation were identified using a multidimensional approach. A specific mast cell subtype has been linked with type 2 driven inflammation and response to inhaled corticosteroids. Advances have been made with regard to sputum cytokine analysis and might also help to guide future treatment of severe asthma.

SUMMARY

Identifying the target population for biological therapies will not be possible without the use of biomarkers. Optimized, easy-to-apply, automated methods for sputum analysis (cellular content or soluble markers) need to be developed for implementation of sputum biomarkers in daily clinical practice.

Pathogenic CD4+ T cells in patients with asthma

Asthma encompasses a variety of clinical phenotypes that involve distinct T cell-driven inflammatory processes. Improved understanding of human T-cell biology and the influence of innate cytokines on T-cell responses at the epithelial barrier has led to new asthma paradigms. This review captures recent knowledge on pathogenic CD4+ T cells in asthmatic patients by drawing on observations in mouse models and human disease. In patients with allergic asthma, TH2 cells promote IgE-mediated sensitization, airway hyperreactivity, and eosinophilia. Here we discuss recent discoveries in the myriad molecular pathways that govern the induction of TH2 differentiation and the critical role of GATA-3 in this process. We elaborate on how cross-talk between epithelial cells, dendritic cells, and innate lymphoid cells translates to T-cell outcomes, with an emphasis on the actions of thymic stromal lymphopoietin, IL-25, and IL-33 at the epithelial barrier. New concepts on how T-cell skewing and epitope specificity are shaped by multiple environmental cues integrated by dendritic cell "hubs" are discussed. We also describe advances in understanding the origins of atypical TH2 cells in asthmatic patients, the role of TH1 cells and other non-TH2 types in asthmatic patients, and the features of T-cell pathogenicity at the single-cell level. Progress in technologies that enable highly multiplexed profiling of markers within a single cell promise to overcome barriers to T-cell discovery in human asthmatic patients that could transform our understanding of disease. These developments, along with novel T cell-based therapies, position us to expand the assortment of molecular targets that could facilitate personalized treatments.

Steroid-induced Deficiency of Mucosal-associated Invariant T Cells in the Chronic Obstructive Pulmonary Disease Lung. Implications for Nontypeable Haemophilus influenzae Infection

RATIONALE

Mucosal-associated invariant T (MAIT) cells are a recently described abundant, proinflammatory T-cell subset with unknown roles in pulmonary immunity. Nontypeable Haemophilus influenzae (NTHi) is the leading bacterial pathogen during chronic obstructive pulmonary disease (COPD) exacerbations and is a plausible target for MAIT cells.

OBJECTIVES

To investigate whether MAIT cells respond to NTHi and the effects of inhaled corticosteroids (ICS) on their frequency and function in COPD.

METHODS

Eleven subjects with COPD receiving ICS, 8 steroid-naive subjects with COPD, and 21 healthy control subjects underwent phlebotomy, sputum induction, bronchoalveolar lavage, and endobronchial biopsy. Pulmonary and monocyte-derived macrophages were cultured in vitro with NTHi.

MEASUREMENTS AND MAIN RESULTS

Frequencies of Vα7.2⁺CD161⁺ MAIT cells, surface expression of the major histocompatibility complex-related protein 1 (MR1), and intracellular IFN-γ expression were measured by flow cytometry. MAIT-cell frequencies were reduced in peripheral blood of ICS-treated subjects with COPD (median 0.38%; interquartile range [IQR], 0.25-0.96) compared with healthy control subjects (1.8%; IQR, 1.4-2.5; P = 0.001) or steroid-naive patients with COPD (1.8%; IQR, 1.2-2.3; P = 0.04). MAIT cells were reduced in bronchial biopsies from subjects with COPD treated with steroids (0.73%; IQR, 0.46-1.3) compared with healthy control subjects (4.0%; IQR, 1.6-5.0; P = 0.02). Coculture of live NTHi increased macrophage surface expression of MR1 and induced IFN-γ from CD4 cells and CD8 cells, but most potently from MAIT cells (median IFN-γ-positive frequencies, 2.9, 8.6, and 27.6%, respectively). In vitro fluticasone and budesonide reduced MR1 surface expression twofold and decreased NTHi-induced IFN-γ secretion eightfold.

CONCLUSIONS

MAIT cells are deficient in blood and bronchial tissue in steroid-treated, but not steroid-naive, COPD. NTHi constitutes a target for pulmonary MAIT-cell immune responses, which are significantly impaired by corticosteroids.

Enabling Precision Cardiology Through Multiscale Biology and Systems Medicine

The traditional paradigm of cardiovascular disease research derives insight from large-scale, broadly inclusive clinical studies of well-characterized pathologies. These insights are then put into practice according to standardized clinical guidelines. However, stagnation in the development of new cardiovascular therapies and variability in therapeutic response implies that this paradigm is insufficient for reducing the cardiovascular disease burden. In this state-of-the-art review, we examine 3 interconnected ideas we put forth as key concepts for enabling a transition to precision cardiology: 1) precision characterization of cardiovascular disease with machine learning methods; 2) the application of network models of disease to embrace disease complexity; and 3) using insights from the previous 2 ideas to enable pharmacology and polypharmacology systems for more precise drug-to-patient matching and patient-disease stratification. We conclude by exploring the challenges of applying a precision approach to cardiology, which arise from a deficit of the required resources and infrastructure, and emerging evidence for the clinical effectiveness of this nascent approach.

Altered expression of regulatory T and Th17 cells in murine bronchial asthma

Alteration of the careful balance of the ratio of Th1/Th2 cell subsets impacts immune function and plays an important role in the pathogenesis of asthma. There is little research on the impact of changes on the balance of the regulatory T (Treg)/Th17 subset ratio and its possible repercussions for asthma. This investigation used a murine model of asthma to measure the expression levels of Treg and Th17 cells and the levels of their transcription factors Foxp3 and retinoic acid receptor-related orphan nuclear receptor (ROR)γt in bronchial asthma while assessing indexes of airway inflammation. Thirty female SPF BALB/c mice were divided into three equally numbered groups: a normal control, an asthma and a dexamethasone treatment group. All the airway inflammation indexes measured were more prominent in the asthma group and less so in the control group. The percentage of the lymphocyte subset CD4⁺CD25⁺Foxp3⁺ cells in the CD4⁺ cells in the asthma group was significantly lower than that in the normal control group (P<0.01). The percentage of the lymphocyte subset CD4⁺IL-17⁺ cells in the CD4⁺ cells in the asthma group was significantly higher than that in the normal control group (P<0.01). The ratio of CD4⁺CD25⁺Foxp3⁺ cells/CD4⁺IL-17⁺ cells in the asthma group decreased compared with that in the normal control group (P<0.01). The expression level of Foxp3 of the mice in the asthma group was significantly lower than that in the control group (P<0.01). The expression intensity of RORγt in the asthma group was higher than that in the normal control group (P<0.01). Finally, the Foxp3/RORγt protein expression ratio in the asthma group was significantly lower than that in the normal control group (P<0.01). The Foxp3/RORγt protein expression ratio and the airway responsiveness were negatively correlated. The average levels of inflammation markers in the dexamethasone group were intermediate between the other groups. During the course of bronchial asthma the unbalanced expression of Treg and Th17 affects mostly the expression of Foxp3/RORγt, leading to inflammation of the airways. Dexamethasone may inhibit airway inflammation by regulating the balance between Treg and Th17.

Topological data analysis (TDA) applied to reveal pedogenetic principles of European topsoil system

Recent developments in applied mathematics are bringing new tools that are capable to synthesize knowledge in various disciplines, and help in finding hidden relationships between variables. One such technique is topological data analysis (TDA), a fusion of classical exploration techniques such as principal component analysis (PCA), and a topological point of view applied to clustering of results. Various phenomena have already received new interpretations thanks to TDA, from the proper choice of sport teams to cancer treatments. For the first time, this technique has been applied in soil science, to show the interaction between physical and chemical soil attributes and main soil-forming factors, such as climate and land use. The topsoil data set of the Land Use/Land Cover Area Frame survey (LUCAS) was used as a comprehensive database that consists of approximately 20,000 samples, each described by 12 physical and chemical parameters. After the application of TDA, results obtained were cross-checked against known grouping parameters including five types of land cover, nine types of climate and the organic carbon content of soil. Some of the grouping characteristics observed using standard approaches were confirmed by TDA (e.g., organic carbon content) but novel subtle relationships (e.g., magnitude of anthropogenic effect in soil formation), were discovered as well. The importance of this finding is that TDA is a unique mathematical technique capable of extracting complex relations hidden in soil science data sets, giving the opportunity to see the influence of physicochemical, biotic and abiotic factors on topsoil formation through fresh eyes.

Treatable traits and therapeutic targets: Goals for systems biology in infectious disease

Among the many medical applications of systems biology, we contend that infectious disease is one of the most important and tractable targets. We take the view that the complexity of the immune system is an inevitable consequence of its evolution, and this complexity has frustrated reductionist efforts to develop host-directed therapies for infection. However, since hosts vary widely in susceptibility and tolerance to infection, host-directed therapies are likely to be effective, by altering the biology of a susceptible host to induce a response more similar to a host who survives. Such therapies should exert minimal selection pressure on organisms, thus greatly decreasing the probability of pathogen resistance developing.

A systems medicine approach to infection has the potential to provide new solutions to old problems: to identify host traits that are potentially amenable to therapeutic intervention, and the host immune factors that could be targeted by host-directed therapies. Furthermore, undiscovered sub-groups with different responses to treatment are almost certain to exist among patients presenting with life-threatening infection, since this population is markedly clinically heterogeneous. A major driving force behind high-throughput clinical phenotyping studies is the aspiration that these subgroups, hitherto opaque to observation, may be observed in the data generated by new technologies. Subgroups of patients are unlikely to be static – serial clinical and biological phenotyping may reveal different trajectories through the pathophysiology of disease, in which different therapeutic approaches are required.

We suggest there are two major goals for systems biology in infection medicine: (1) to identify subgroups of patients that share treatable features; and, (2) to integrate high-throughput data from clinical and in vitro sources in order to predict tractable therapeutic targets with the potential to alter disease trajectories for individual patients.

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High throughput technologies can reveal clinical patterns in infection that were previously opaque.

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Host-targeted therapies have conceptual advantages but are difficult to develop.

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Key clinically-relevant objectives are identification of disease endotypes and treatable traits.

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Mechanistic understanding will reveal opportunities for drug design, repurposing and better targeting.

Fecal metagenomic profiles in subgroups of patients with myalgic encephalomyelitis/chronic fatigue syndrome

BACKGROUND

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is characterized by unexplained persistent fatigue, commonly accompanied by cognitive dysfunction, sleeping disturbances, orthostatic intolerance, fever, lymphadenopathy, and irritable bowel syndrome (IBS). The extent to which the gastrointestinal microbiome and peripheral inflammation are associated with ME/CFS remains unclear. We pursued rigorous clinical characterization, fecal bacterial metagenomics, and plasma immune molecule analyses in 50 ME/CFS patients and 50 healthy controls frequency-matched for age, sex, race/ethnicity, geographic site, and season of sampling.

RESULTS

Topological analysis revealed associations between IBS co-morbidity, body mass index, fecal bacterial composition, and bacterial metabolic pathways but not plasma immune molecules. IBS co-morbidity was the strongest driving factor in the separation of topological networks based on bacterial profiles and metabolic pathways. Predictive selection models based on bacterial profiles supported findings from topological analyses indicating that ME/CFS subgroups, defined by IBS status, could be distinguished from control subjects with high predictive accuracy. Bacterial taxa predictive of ME/CFS patients with IBS were distinct from taxa associated with ME/CFS patients without IBS. Increased abundance of unclassified Alistipes and decreased Faecalibacterium emerged as the top biomarkers of ME/CFS with IBS; while increased unclassified Bacteroides abundance and decreased Bacteroides vulgatus were the top biomarkers of ME/CFS without IBS. Despite findings of differences in bacterial taxa and metabolic pathways defining ME/CFS subgroups, decreased metabolic pathways associated with unsaturated fatty acid biosynthesis and increased atrazine degradation pathways were independent of IBS co-morbidity. Increased vitamin B6 biosynthesis/salvage and pyrimidine ribonucleoside degradation were the top metabolic pathways in ME/CFS without IBS as well as in the total ME/CFS cohort. In ME/CFS subgroups, symptom severity measures including pain, fatigue, and reduced motivation were correlated with the abundance of distinct bacterial taxa and metabolic pathways.

CONCLUSIONS

Independent of IBS, ME/CFS is associated with dysbiosis and distinct bacterial metabolic disturbances that may influence disease severity. However, our findings indicate that dysbiotic features that are uniquely ME/CFS-associated may be masked by disturbances arising from the high prevalence of IBS co-morbidity in ME/CFS. These insights may enable more accurate diagnosis and lead to insights that inform the development of specific therapeutic strategies in ME/CFS subgroups.

Airway and serum biochemical correlates of refractory neutrophilic asthma

Background

Despite progress in the diagnosis and management of asthma, many patients have poorly controlled or refractory asthma (RA). The mechanism of this RA is not well understood.

Objective

We sought to explore the relationship between neutrophils and other biomarkers of RA.

Method

Sixty patients with RA, 30 patients with nonrefractory asthma (NRA), and 20 healthy subjects were enrolled. We performed a comprehensive characterization of these study subjects, which included laboratory and pulmonary function studies, chest computed tomography, and bronchoscopy with bronchoalveolar lavage (BAL). We analyzed BAL fluid and serum for a total of 244 biomolecules using a multiplex assay and correlated them with clinical and other laboratory parameters.

Results

RA was significantly different from NRA with regard to pulmonary function indices, bronchial basement membrane thickness, and BAL fluid neutrophil and lymphocyte counts but not eosinophil counts. BAL fluid neutrophil counts negatively and positively correlated with forced vital capacity and age, respectively. Of the 244 biomolecules studied, 52 and 14 biomolecules from BAL fluid and serum, respectively, were significantly different among the study groups. Thirteen of these 52 molecules correlated with BAL fluid neutrophil counts. BAL fluid from 40% of patients with RA was positive for a pathogenic microbe. Infection-negative neutrophilic RA was associated with an increase in levels of select biomarkers of inflammation in the serum, suggesting the presence of systemic inflammation.

Conclusions

RA was associated with increased numbers of neutrophils and proneutrophilic biomolecules in the airways. Subclinical infection was present in 40% of patients with RA, which likely contributed to neutrophilic inflammation. A subgroup of patients with noninfected neutrophilic RA was associated with systemic inflammation.

Endotypes of allergic diseases and asthma: An important step in building blocks for the future of precision medicine

Discoveries from basic science research in the last decade have brought significant progress in knowledge of pathophysiologic processes of allergic diseases, with a compelling impact on understanding of the natural history, risk prediction, treatment selection or mechanism-specific prevention strategies. The view of the pathophysiology of allergic diseases developed from a mechanistic approach, with a focus on symptoms and organ function, to the recognition of a complex network of immunological pathways. Several subtypes of inflammation and complex immune-regulatory networks and the reasons for their failure are now described, that open the way for the development of new diagnostic tools and innovative targeted-treatments. An endotype is a subtype of a disease condition, which is defined by a distinct pathophysiological mechanism, whereas a disease phenotype defines any observable characteristic of a disease without any implication of a mechanism. Another key word linked to disease endotyping is biomarker that is measured and evaluated to examine any biological or pathogenic processes, including response to a therapeutic intervention. These three keywords will be discussed more and more in the future with the upcoming efforts to revolutionize patient care in the direction of precision medicine and precision health. The understanding of disease endotypes based on pathophysiological principles and their validation across clinically meaningful outcomes in asthma, allergic rhinitis, chronic rhinosinusitis, atopic dermatitis and food allergy will be crucial for the success of precision medicine as a new approach to patient management.

New Developments in Mast Cell Biology: Clinical Implications

Mast cells (MCs) are present in connective tissue and at mucosal surfaces in all classes of vertebrates. In health, they contribute to tissue homeostasis, host defense, and tissue repair via multiple receptors regulating the release of a vast stockpile of proinflammatory mediators, proteases, and cytokines. However, these potentially protective cells are a double-edged sword. When there is a repeated or long-term stimulus, MC activation leads to tissue damage and dysfunction. Accordingly, MCs are implicated in the pathophysiologic aspects of numerous diseases covering all organs. Understanding the biology of MCs, their heterogeneity, mechanisms of activation, and signaling cascades may lead to the development of novel therapies for many diseases for which current treatments are lacking or are of poor efficacy. This review will focus on updates and developments in MC biology and their clinical implications, with a particular focus on their role in respiratory diseases.

How Many Parameters Does It Take to Describe Disease Tolerance?

The study of infectious disease has been aided by model organisms, which have helped to elucidate molecular mechanisms and contributed to the development of new treatments; however, the lack of a conceptual framework for unifying findings across models, combined with host variability, has impeded progress and translation. Here, we fill this gap with a simple graphical and mathematical framework to study disease tolerance, the dose response curve relating health to microbe load; this approach helped uncover parameters that were previously overlooked. Using a model experimental system in which we challenged Drosophila melanogaster with the pathogen Listeria monocytogenes, we tested this framework, finding that microbe growth, the immune response, and disease tolerance were all well represented by sigmoid models. As we altered the system by varying host or pathogen genetics, disease tolerance varied, as we would expect if it was indeed governed by parameters controlling the sensitivity of the system (the number of bacteria required to trigger a response) and maximal effect size according to a logistic equation. Though either the pathogen or host immune response or both together could theoretically be the proximal cause of pathology that killed the flies, we found that the pathogen, but not the immune response, drove damage in this model. With this new understanding of the circuitry controlling disease tolerance, we can now propose better ways of choosing, combining, and developing treatments.

Experiments using fruit flies infected with Listeria monocytogenes show that changes in the shape of a disease tolerance curve can reveal the source of pathology for an infectious system.

It is an intuitive assumption that the severity of symptoms suffered during an infection must be linked to pathogen loads. However, the dose–response relationship explaining how health varies with respect to pathogen load is non-linear and can be described as a “disease tolerance curve;” this relationship can vary in response to the genetic properties of the host or pathogen as well as environmental conditions. We studied what changes in the shape of this curve can teach us about the underlying circuitry of the immune response. Using a model system in which we infected fruit flies with the bacterial pathogen Listeria monocytogenes, we observed an S-shaped disease tolerance curve. This type of curve can be described by three or four parameters in a standard manner, which allowed us to develop a simple mathematical model to explain how the curve is expected to change shape as the immune response changes. After observing the variation in curve shape due to host and pathogen genetic variation, we conclude that the damage caused by Listeria infection does not result from an over-exuberant immune response but rather is caused more directly by the pathogen.

Mucosal-associated invariant T cells in autoimmunity, immune-mediated diseases and airways disease

Mucosal-associated invariant T (MAIT) cells are a novel class of innate-like T cells, expressing a semi-invariant T-cell receptor (TCR) and able to recognize small molecules presented on the non-polymorphic MHC-related protein 1. Their intrinsic effector-memory phenotype, enabling secretion of pro-inflammatory cytokines, and their relative abundance in humans imply a significant potential to contribute to autoimmune processes. However, as MAIT cells were unknown until recently and specific immunological tools were unavailable, little is known of their roles in disease. Here I review observations from clinical studies and animal models of autoimmune and immune-mediated diseases including the roles of MAIT cells in systemic lupus erythematosus, rheumatoid arthritis, multiple sclerosis, inflammatory bowel disease and airways diseases. MAIT cell deficiencies are frequently observed in peripheral blood, and at sites of disease such as the airways in asthma. However, MAIT cells have a specific sensitivity to suppression by therapeutic corticosteroids that may confound many of these observations, as may the tendency of the surface marker CD161 to activation-induced down-regulation. Nonetheless, the dependence on bacteria for the development of MAIT cells suggests a potentially important protective role linking the influences of early life microbial exposures and subsequent development of autoimmunity. Conversely, MAIT cells could contribute to chronic inflammation either through TCR-independent activation, or potentially by TCR recognition of as yet undiscovered ligands. Future research will be greatly facilitated by the immunological tools that are now available, including murine genetic models and human and murine specific tetramers.

Allergen immunotherapy for allergic asthma: protocol for a systematic review

Background

The European Academy of Allergy and Clinical Immunology (EAACI) is in the process of developing the EAACI Guidelines for Allergen Immunotherapy (AIT) for Allergic Asthma. We seek to critically assess the effectiveness, cost-effectiveness and safety of AIT in the management of allergic asthma.

Methods

We will undertake a systematic review, which will involve searching international biomedical databases for published, in progress and unpublished evidence. Studies will be independently screened against pre-defined eligibility criteria and critically appraised using established instruments. Data will be descriptively and, if possible and appropriate, quantitatively synthesised.

Discussion

The findings from this review will be used to inform the development of recommendations for EAACI’s Guidelines on AIT.

Electronic supplementary material

The online version of this article (doi:10.1186/s13601-016-0094-y) contains supplementary material, which is available to authorized users.