The basic immunology of asthma.

In many asthmatics, chronic airway inflammation is driven by IL-4-, IL-5-, and IL-13-producing Th2 cells or ILC2s. Type 2 cytokines promote hallmark features of the disease such as eosinophilia, mucus hypersecretion, bronchial hyperresponsiveness (BHR), IgE production, and susceptibility to exacerbations. However, only half the asthmatics have this "type 2-high" signature, and "type 2-low" asthma is more associated with obesity, presence of neutrophils, and unresponsiveness to corticosteroids, the mainstay asthma therapy. Here, we review the underlying immunological basis of various asthma endotypes by discussing results obtained from animal studies as well as results generated in clinical studies targeting specific immune pathways.

Are We Meeting the Promise of Endotypes and Precision Medicine in Asthma?

While the term asthma has long been known to describe heterogeneous groupings of patients, only recently have data evolved which enable a molecular understanding of the clinical differences. The evolution of transcriptomics (and other 'omics platforms) and improved statistical analyses in combination with large clinical cohorts opened the door for molecular characterization of pathobiologic processes associated with a range of asthma patients. When linked with data from animal models and clinical trials of targeted biologic therapies, emerging distinctions arose between patients with and without elevations in type 2 immune and inflammatory pathways, leading to the confirmation of a broad categorization of type 2-Hi asthma. Differences in the ratios, sources, and location of type 2 cytokines and their relation to additional immune pathway activation appear to distinguish several different (sub)molecular phenotypes, and perhaps endotypes of type 2-Hi asthma, which respond differently to broad and targeted anti-inflammatory therapies. Asthma in the absence of type 2 inflammation is much less well defined, without clear biomarkers, but is generally linked with poor responses to corticosteroids. Integration of "big data" from large cohorts, over time, using machine learning approaches, combined with validation and iterative learning in animal (and human) model systems is needed to identify the biomarkers and tightly defined molecular phenotypes/endotypes required to fulfill the promise of precision medicine.

Lung Tissue Multi-Layer Network Analysis Uncovers the Molecular Heterogeneity of COPD.

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous condition. We hypothesized that the unbiased integration of different COPD lung omics using a novel multi-layer approach may unravel mechanisms associated with clinical characteristics. METHODS: We profiled mRNA, miRNA and methylome in lung tissue samples from 135 former smokers with COPD. For each omic (layer) we built a patient network based on molecular similarity. The three networks were used to build a multi-layer network, and optimization of multiplex-modularity was employed to identify patient communities across the three distinct layers. Uncovered communities were related to clinical features. RESULTS: We identified five patient communities in the multi-layer network which were molecularly distinct and related to clinical characteristics, such as FEV1 and blood eosinophils. Two communities (C#3 and C#4) had both similarly low FEV1 values and emphysema, but were molecularly different: C#3, but not C#4, presented B and T cell signatures and a downregulation of secretory (SCGB1A1/SCGB3A1) and ciliated cells. A machine learning model was set up to discriminate C#3 and C#4 in our cohort, and to validate them in an independent cohort. Finally, using spatial transcriptomics we characterized the small airway differences between C#3 and C#4, identifying an upregulation of T/B cell homing chemokines, and bacterial response genes in C#3. CONCLUSIONS: A novel multi-layer network analysis is able to identify clinically relevant COPD patient communities. Patients with similarly low FEV1 and emphysema can have molecularly distinct small airways and immune response patterns, indicating that different endotypes can lead to similar clinical presentation.

Recognizing depression as an inflammatory disease: the search for endotypes.

Major depressive disorder (MDD) affects millions of individuals worldwide, leading to considerable social and economic costs. Despite advancements in pharmacological treatments, achieving remission remains a key challenge, with a substantial number of patients showing resistance to existing therapies. This resistance is often associated with elevated levels of proinflammatory cytokines, suggesting a connection between inflammation, MDD pathophysiology, and treatment efficacy. The observation of increased immune activation in about a quarter of patients with MDD resulted in the distinction between inflammatory and noninflammatory endotypes. Although anti-inflammatory treatments show promise in alleviating depression-like symptoms, responses are heterogeneous, thus highlighting the importance of identifying distinct inflammatory endotypes to tailor effective therapeutic strategies. The intestinal microbiome emerges as a crucial modulator of mental health, mediating its effects partially through different immune pathways. Microbiota-derived short-chain fatty acids (SCFAs) significantly impact innate and adaptive immune cells, regulating their differentiation, function, and cellular response. Furthermore, gut-educated immune cells reach the border regions of the central nervous system (CNS), regulating glial cell functions. Although the CNS modulates immune responses via efferent parts of the vagus nerve, afferent tracts concurrently transport information on peripheral inflammation back to the brain. This bidirectional communication is particularly relevant in depression, allowing for therapeutic stimulation of the vagus nerve in the context of inflammatory depression endotypes. In this review, we explore the intricate relationship between inflammation and depression, discuss how inflammatory signals are translated into depressive-like symptoms, and highlight immune-modulating therapeutic avenues.

Data-driven patient stratification of UK Biobank cohort suggests five endotypes of multimorbidity.

Multimorbidity generally refers to concurrent occurrence of multiple chronic conditions. These patients are inherently at high risk and often lead a poor quality of life due to delayed treatments. With the emergence of personalized medicine and stratified healthcare, there is a need to stratify patients right at the primary care setting. Here we developed multimorbidity analysis pipeline (MulMorPip), which can stratify patients into multimorbid subgroups or endotypes based on their lifetime disease diagnosis and characterize them based on demographic features and underlying disease-disease interaction networks. By implementing MulMorPip on UK Biobank cohort, we report five distinct molecular subclasses or endotypes of multimorbidity. For each patient, we calculated the existence of broad disease classes defined by Charlson's comorbidity classification using the International Classification of Diseases-10 encoding. We then applied multiple correspondence analysis in 77 524 patients from UK Biobank, who had multimorbidity of more than one disease, which resulted in five multimorbid clusters. We further validated these clusters using machine learning and were able to classify 20% model-blind test set patients with an accuracy of 97% and an average Jaccard similarity of 84%. This was followed by demographic characterization and development of interlinking disease network for each cluster to understand disease-disease interactions. Our identified five endotypes of multimorbidity draw attention to dementia, stroke and paralysis as important drivers of multimorbidity stratification. Inclusion of such patient stratification at the primary care setting can help general practitioners to better observe patients' multiple chronic conditions, their risk stratification and personalization of treatment strategies.

Type 1 diabetes: A new vision of the disease based on endotypes.

Diagnosis and management of type 1 diabetes (T1D) have remained largely unchanged for the last several years. The management of the disease remains primarily focused on its phenotypical presentation and less on endotypes, namely the specific biological mechanisms behind the development of the disease. Furthermore, the treatment of T1D is essentially universal and indiscriminate-with patients administering insulin at varying dosages and frequencies to maintain adequate glycaemic control. However, it is now well understood that T1D is a heterogeneous disease with many different biological mechanisms (i.e. endotypes) behind its complex pathophysiology. A range of factors, including age of onset, immune system regulation, rate of ß-cell destruction, autoantibodies, body weight, genetics and the exposome are recognised to play a role in the development of the condition. Patients can be classified into distinct diabetic subtypes based on these factors, which can be used to categorise patients into specific endotypes. The classification of patients into endotypes allows for a greater understanding of the natural progression of the disease, giving rise to more accurate and patient-centred therapies and follow-up monitoring, specifically for other autoimmune diseases. This review proposes 6 unique endotypes of T1D based on the current literature. The recognition of these endotypes could then be used to direct therapeutic modalities based on patients' individual pathophysiology.

Biomarker Enrichment in Sepsis-Associated Acute Kidney Injury: Finding High-Risk Patients in the Intensive Care Unit.

BACKGROUND: Sepsis-associated acute kidney injury (AKI) is a leading comorbidity in admissions to the intensive care unit. While a gold standard definition exists, it remains imperfect and does not allow for the timely identification of patients in the setting of critical illness. This review will discuss the use of biochemical and electronic biomarkers to allow for prognostic and predictive enrichment of patients with sepsis-associated AKI over and above the use of serum creatinine and urine output. SUMMARY: Current data suggest that several biomarkers are capable of identifying patients with sepsis at risk for the development of severe AKI and other associated morbidity. This review discusses these data and these biomarkers in the setting of sub-phenotyping and endotyping sepsis-associated AKI. While not all these tests are widely available and some require further validation, in the near future we anticipate several new tools to help nephrologists and other providers better care for patients with sepsis-associated AKI. KEY MESSAGES: Predictive and prognostic enrichment using both traditional biomarkers and novel biomarkers in the setting of sepsis can identify subsets of patients with either similar outcomes or similar pathophysiology, respectively. Novel biomarkers can identify kidney injury in patients without consensus definition AKI (e.g., changes in creatinine or urine output) and can predict other adverse outcomes (e.g., severe consensus definition AKI, inpatient mortality). Finally, emerging artificial intelligence and machine learning-derived risk models are able to predict sepsis-associated AKI in critically ill patients using advanced learning techniques and several laboratory and vital sign measurements.

Transitions of blood immune endotypes and improved outcome by anakinra in COVID-19 pneumonia: an analysis of the SAVE-MORE randomized controlled trial.

BACKGROUND: Endotype classification may guide immunomodulatory management of patients with bacterial and viral sepsis. We aimed to identify immune endotypes and transitions associated with response to anakinra (human interleukin 1 receptor antagonist) in participants in the SAVE-MORE trial. METHODS: Adult patients hospitalized with radiological findings of PCR-confirmed severe pneumonia caused by SARS-CoV-2 and plasma-soluble urokinase plasminogen activator receptor levels of ≥ 6 ng/ml in the SAVE-MORE trial (NCT04680949) were characterized at baseline and days 4 and 7 of treatment using a previously defined 33-messenger RNA classifier to assign an immunological endotype in blood. Endpoints were changes in endotypes and progression to severe respiratory failure (SRF) associated with anakinra treatment. RESULTS: At baseline, 23.2% of 393 patients were designated as inflammopathic, 41.1% as adaptive, and 35.7% as coagulopathic. Only 23.9% were designated as the same endotype at days 4 and 7 compared to baseline, while all other patients transitioned between endotypes. Anakinra-treated patients were more likely to remain in the adaptive endotype during 7-day treatment (24.4% vs. 9.9%; p < 0.001). Anakinra also protected patients with coagulopathic endotype at day 7 against SRF compared to placebo (27.8% vs. 55.9%; p = 0.013). CONCLUSION: We identify an association between endotypes defined using blood transcriptome and anakinra therapy for COVID-19 pneumonia, with anakinra-treated patients shifting toward endotypes associated with a better outcome, mainly the adaptive endotype. Trial registration ClinicalTrials.gov, NCT04680949, December 23, 2020.

Endotypes of chronic rhinosinusitis based on inflammatory and remodeling factors.

BACKGROUND: Previous studies on the endotyping of chronic rhinosinusitis (CRS) that were based on inflammatory factors have broadened our understanding of the disease. However, the endotype of CRS combined with inflammatory and remodeling features has not yet been clearly elucidated. OBJECTIVE: We sought to identify the endotypes of patients with CRS according to inflammatory and remodeling factors. METHODS: Forty-eight inflammatory and remodeling factors in the nasal mucosal tissues of 128 CRS patients and 24 control subjects from northern China were analyzed by Luminex, ELISA, and ImmunoCAP. Sixteen factors were used to perform the cluster analysis. The characteristics of each cluster were analyzed using correlation analysis and validated by immunofluorescence staining. RESULTS: Patients were classified into 5 clusters. Clusters 1 and 2 showed non-type 2 signatures with low biomarker concentrations, except for IL-19 and IL-27. Cluster 3 involved a low type 2 endotype with the highest expression of neutrophil factors, such as granulocyte colony-stimulating factor, IL-8, and myeloperoxidase, and remodeling factors, such as matrix metalloproteinases and fibronectin. Cluster 4 exhibited moderate type 2 inflammation. Cluster 5 exhibited high type 2 inflammation, which was associated with relatively higher levels of neutrophil and remodeling factors. The proportion of CRS with nasal polyps, asthma, allergies, anosmia, aspirin sensitivity, and the recurrence of CRS increased from clusters 1 to 5. CONCLUSION: Diverse inflammatory mechanisms result in distinct CRS endotypes and remodeling profiles. The explicit differentiation and accurate description of these endotypes will guide targeted treatment decisions.

Bronchial epithelial cell transcriptome shows endotype heterogeneity of asthma in patients with NSAID-exacerbated respiratory disease.

BACKGROUND: Nonsteroidal anti-inflammatory drugs-exacerbated respiratory disease (N-ERD) is currently classified as a type-2 (T2) immune-mediated disease characterized by asthma, chronic rhinosinusitis, and hypersensitivity to cyclooxygenase-1 inhibitors. OBJECTIVES: The aim of this study was to characterize immunological endotypes of N-ERD based on the gene expression profile in the bronchial epithelium. METHODS: mRNA transcriptome (mRNA-sequencing) was analyzed in bronchial brushings from patients with N-ERD (n = 22), those with nonsteroidal anti-inflammatory drug-tolerant asthma (NTA, n = 21), and control subjects (n = 11). Additionally, lipid and protein mediators were measured in bronchoalveolar lavage fluid (BALF). RESULTS: Initial analysis of the entire asthma group revealed 2 distinct gene expression signatures: "T2-high" with increased expression of T2-related genes (eg, CLCA1, CST1), and "proinflammatory" characterized by the expression of innate immunity (eg, FOSB, EGR3) and IL-17A response genes. These endotypes showed similar prevalence in N-ERD and NTA (eg, T2-high: 33% and 32%, respectively). T2-high asthma was characterized by increased expression of mast cell and eosinophil markers, goblet cell hyperplasia, and elevated LTE4 and PGD2 in BALF. Patients with a proinflammatory endotype showed mainly neutrophilic inflammation and increased innate immunity mediators in BALF. Furthermore, the proinflammatory signature was associated with a more severe course of asthma and marked airway obstruction. These signatures could be recreated in vitro by exposure of bronchial epithelial cells to IL-13 (T2-high) and IL-17A (proinflammatory). CONCLUSIONS: T2-high signature was found only in one-third of patients with N-ERD, which was similar to what was found in patients with NTA. The proinflammatory endotype, which also occurred in N-ERD, suggests a novel mechanism of severe disease developing on a non-T2 background.

Multidimensional endotyping using nasal proteomics predicts molecular phenotypes in the asthmatic airways.

BACKGROUND: Unsupervised clustering of biomarkers derived from noninvasive samples such as nasal fluid is less evaluated as a tool for describing asthma endotypes. OBJECTIVE: We sought to evaluate whether protein expression in nasal fluid would identify distinct clusters of patients with asthma with specific lower airway molecular phenotypes. METHODS: Unsupervised clustering of 168 nasal inflammatory and immune proteins and Shapley values was used to stratify 43 patients with severe asthma (endotype of noneosinophilic asthma) using a 2 "modeling blocks" machine learning approach. This algorithm was also applied to nasal brushings transcriptomics from U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes). Feature reduction and functional gene analysis were used to compare proteomic and transcriptomic clusters. Gene set variation analysis provided enrichment scores of the endotype of noneosinophilic asthma protein signature within U-BIOPRED sputum and blood. RESULTS: The nasal protein machine learning model identified 2 severe asthma endotypes, which were replicated in U-BIOPRED nasal transcriptomics. Cluster 1 patients had significant airway obstruction, small airways disease, air trapping, decreased diffusing capacity, and increased oxidative stress, although only 4 of 18 were current smokers. Shapley identified 20 cluster-defining proteins. Forty-one proteins were significantly higher in cluster 1. Pathways associated with proteomic and transcriptomic clusters were linked to TH1, TH2, neutrophil, Janus kinase-signal transducer and activator of transcription, TLR, and infection activation. Gene set variation analysis of the nasal protein and gene signatures were enriched in subjects with sputum neutrophilic/mixed granulocytic asthma and in subjects with a molecular phenotype found in sputum neutrophil-high subjects. CONCLUSIONS: Protein or gene analysis may indicate molecular phenotypes within the asthmatic lower airway and provide a simple, noninvasive test for non-type 2 immune response asthma that is currently unavailable.

Biomarkers in atopic dermatitis.

Atopic dermatitis (AD) is a complex and highly heterogeneous inflammatory skin disease. Given the highly heterogeneous character of AD, it is unlikely that every patient will respond equally to a particular treatment. The recent introduction of novel targeted therapies for AD has driven the need for patient stratification based on immunologic biomarkers. We have reviewed the use of different types of biomarkers as potential tools in the movement toward personalized medicine in AD, comprising different ways of endotyping patients with AD based on immunologic profiles and predictive biomarkers. The application of biomarkers will result in better characterization and stratification of patients and allow better comparison of current and new treatments. The ultimate goal will be to switch from the current generalized "one-drug-fits-all" management to more personalized "patient endotype-specific" management.

Type 1 diabetes and inborn errors of immunity: Complete strangers or 2 sides of the same coin?

Type 1 diabetes (T1D) is a polygenic disease and does not follow a mendelian pattern. Inborn errors of immunity (IEIs), on the other hand, are caused by damaging germline variants, suggesting that T1D and IEIs have nothing in common. Some IEIs, resulting from mutations in genes regulating regulatory T-cell homeostasis, are associated with elevated incidence of T1D. The genetic spectrum of IEIs is gradually being unraveled; consequently, molecular pathways underlying human monogenic autoimmunity are being identified. There is an appreciable overlap between some of these pathways and the genetic variants that determine T1D susceptibility, suggesting that after all, IEI and T1D are 2 sides of the same coin. The study of monogenic IEIs with a variable incidence of T1D has the potential to provide crucial insights into the mechanisms leading to T1D. These insights contribute to the definition of T1D endotypes and explain disease heterogeneity. In this review, we discuss the interconnected pathogenic pathways of autoimmunity, ß-cell function, and primary immunodeficiency. We also examine the role of environmental factors in disease penetrance as well as the circumstantial evidence of IEI drugs in preventing and curing T1D in individuals with IEIs, suggesting the repositioning of these drugs also for T1D therapy.

Endotypes of Chronic Rhinosinusitis with Primary and Recurring Nasal Polyps in the Latvian Population.

Chronic rhinosinusitis (CRS) is a complex syndrome with various inflammatory mechanisms resulting in different patterns of inflammation that correlate with the clinical phenotypes of CRS. Our aim was to use detected IL-1, IL-4, IL-6, IL-7, IL-8, IL-10, IL-12, Ki 67, HBD-2, HBD-3, and LL-37 to classify specific inflammatory endotypes in chronic rhinosinusitis with the tissue of nasal polyps (CRSwNP). Samples from 35 individuals with primary and recurrent CRSwNP were taken during surgery. The tissues were stained for the previously mentioned biomarkers immunohistochemically. A hierarchical cluster analysis was performed. The clinical parameters were compared between clusters. Five clusters had significantly different biomarkers between groups. There were no significant differences in the clinical parameters, except for the Lund-Mackay score, which was significantly higher in cluster 4 compared to that of cluster 1 (p = 0.024). Five endotypes of (CRSwNP) are characterized by different combinations of type 1, type 2, and type 3 tissue inflammation patterns. In the Latvian population, endotypes associated with neutrophilic inflammation or a combination of neutrophilic inflammation and type 2 inflammation are predominant. Increased proliferation marker Ki 67 values are not associated with more severe inflammation in the tissue samples of chronic rhinosinusitis with nasal polyps.

Characterization of High and Low IFNG-Expressing Subgroups in Atopic Dermatitis.

Atopic dermatitis (AD) is one of the most common chronic inflammatory skin diseases, with an increasing number of targeted therapies available. While biologics to treat AD exclusively target the key cytokines of type 2 immunity, Janus kinase inhibitors target a broad variety of cytokines, including IFN-γ. To better stratify patients for optimal treatment outcomes, the identification and characterization of subgroups, especially with regard to their IFNG expression, is of great relevance, as the role of IFNG in AD has not yet been fully clarified. This study aims to define AD subgroups based on their lesional IFNG expression and to characterize them based on their gene expression, T cell secretome and clinical attributes. RNA from the lesional and non-lesional biopsies of 48 AD patients was analyzed by RNA sequencing. Based on IFNG gene expression and the release of IFN-γ by lesional T cells, this cohort was categorized into three IFNG groups (high, medium, and low) using unsupervised clustering. The low IFNG group showed features of extrinsic AD with a higher prevalence of atopic comorbidities and impaired epidermal lipid synthesis. In contrast, patients in the high IFNG group had a higher average age and an activation of additional pro-inflammatory pathways. On the cellular level, higher amounts of M1 macrophages and natural killer cell signaling were detected in the high IFNG group compared to the low IFNG group by a deconvolution algorithm. However, both groups shared a common dupilumab response gene signature, indicating that type 2 immunity is the dominant immune shift in both subgroups. In summary, high and low IFNG subgroups correspond to intrinsic and extrinsic AD classifications and might be considered in the future for evaluating therapeutic efficacy or non-responders.

Severe Asthma or Chronic Obstructive Pulmonary Disease with Eosinophilic Inflammation? From Uncertainty to Remission under Anti IL-5R Therapy.

Background and Objectives: Severe adult-onset eosinophilic asthma and COPD with eosinophilic inflammation are two entities with a similar clinical course and are sometimes difficult to differentiate in clinical practice, especially in patients with a history of smoking. Anti-IL-5 or -IL-5R biological therapy has been shown to be highly effective in severe eosinophilic asthma but has not demonstrated significant benefit in patients with COPD with the eosinophilic phenotype. Our aim was to illustrate this issue in the form of a case report. Materials and Methods: We present the case of a 67-year-old patient who is a former smoker with late-onset severe uncontrolled asthma (ACT score < 15) who experienced frequent exacerbations requiring treatment with systemic corticosteroids. The patient's lung function gradually worsened to a nadir FEV1 = 18%, despite a high dose of ICS in combination with a LABA and intermittent courses of OCS, with negative allergic skin-tests, but with high blood eosinophils level. Biological treatment with an anti-IL5R monoclonal antibody (benralizumab) was initiated, despite the difficulty in the differential diagnosis between asthma and COPD with eosinophilic inflammation. Results: The patient's evolution was favorable; clinical remission was effectively achieved with significant improvement in lung function (FEV1 > 100%), but with persistence of residual mild fixed airway obstructive dysfunction (FEV1/FVC < 0.7). The therapeutic response has been maintained to date. Conclusions: Benralizumab was shown to be very effective in a patient with late-onset severe eosinophilic asthma presenting features of chronic obstructive disease-habitual exposure to tobacco and inhaled noxious substances, and persistent airflow limitation on spirometry.

[Features of inflammatory endotypes and phenotypes in chronic rhinosinusitis]. / Osobennosti endotipov i fenotipov vospaleniya pri khronicheskom rinosinusite.

Recently, significant progress has been made in identifying the cellular and molecular mechanisms responsible for the pathogenesis of chronic rhinosinusitis (CRS). Cohort studies of CRS have led to advances in the clinical understanding of this disease. New therapeutic agents have been approved or are undergoing clinical trials to expand treatment options for this disease. One of the promising areas in medicine is the provision of personalized clinical care. From this perspective, CRS can be divided into three different endotypes depending on the type of underlying inflammatory response. In the United States, CRS with and without nasal polyps is predominantly characterized as the second inflammatory endotype. CRS with nasal polyps (about 17%) and without nasal polyps (up to 20%) belongs to the 1st and 3rd inflammatory endotypes, respectively. And if for the second inflammatory endotype the effectiveness of targeted biological therapy is beyond doubt, then for the first and third inflammatory endotypes the principles of such conservative therapy are under active development. Moreover, large validated studies to confirm associations between CRS phenotypes and endotypes, as well as to find effective biological markers of inflammatory endotypes, remain to be performed.

Genetic determinants of type 1 diabetes in individuals with weak evidence of islet autoimmunity at disease onset.

AIMS/HYPOTHESIS: Islet autoantibodies (AAbs) are detected in >90% of individuals with clinically suspected type 1 diabetes at disease onset. A single AAb, sometimes at low titre, is often detected in some individuals, making their diagnosis uncertain. Type 1 diabetes genetic risk scores (GRS) are a useful tool for discriminating polygenic autoimmune type 1 diabetes from other types of diabetes, particularly the monogenic forms, but testing is not routinely performed in the clinic. Here, we used a type 1 diabetes GRS to screen for monogenic diabetes in individuals with weak evidence of autoimmunity, i.e. with a single AAb at disease onset. METHODS: In a pilot study, we genetically screened 142 individuals with suspected type 1 diabetes, 42 of whom were AAb-negative, 27 of whom had a single AAb (single AAb-positive) and 73 of whom had multiple AAbs (multiple AAb-positive) at disease onset. Next-generation sequencing (NGS) was performed in 41 AAb-negative participants, 26 single AAb-positive participants and 60 multiple AAb-positive participants using an analysis pipeline of more than 200 diabetes-associated genes. RESULTS: The type 1 diabetes GRS was significantly lower in AAb-negative individuals than in those with a single and multiple AAbs. Pathogenetic class 4/5 variants in MODY or monogenic diabetes genes were identified in 15/41 (36.6%) AAb-negative individuals, while class 3 variants of unknown significance were identified in 17/41 (41.5%). Residual C-peptide levels at diagnosis were higher in individuals with mutations compared to those without pathogenetic variants. Class 3 variants of unknown significance were found in 11/26 (42.3%) single AAb-positive individuals, and pathogenetic class 4/5 variants were present in 2/26 (7.7%) single AAb-positive individuals. No pathogenetic class 4/5 variants were identified in multiple AAb-positive individuals, but class 3 variants of unknown significance were identified in 19/60 (31.7%) patients. Several patients across the three groups had more than one class 3 variant. CONCLUSIONS/INTERPRETATION: These findings provide insights into the genetic makeup of patients who show weak evidence of autoimmunity at disease onset. Absence of islet AAbs or the presence of a single AAb together with a low type 1 diabetes GRS may be indicative of a monogenic form of diabetes, and use of NGS may improve the accuracy of diagnosis.

AOSD endotypes based on immune cell profiles: patient stratification with hierarchical clustering analysis.

OBJECTIVES: This study aimed to analyse the immune cell profiles of adult-onset Still's disease (AOSD) and to stratify disease-associated endotypes. METHODS: We included 95 cases of treatment-naïve patients with AOSD and 66 cases of healthy controls. Patients with AOSD were classified via an unbiased hierarchical cluster analysis based on circulating immune cells. Their clinical and laboratory characteristics, treatment management, systemic scores and outcomes were then analysed. RESULTS: The proportions of neutrophils and CD8+ T cells were significantly higher while monocytes and natural killer and CD4+ T cells were decreased in patients with AOSD (all P < 0.005). Unbiased hierarchical cluster analysis classified 95 AOSD into three endotype-based groups: group 1 had the highest percentage of neutrophils (neu-dominant group), group 2 had the highest percentage of monocytes (mono-dominant group) and group 3 had the highest percentage of CD8+ T cells (CD8-dominant group). Patients in group 3 had the highest systemic score at diagnosis and were more likely to have pulmonary infiltrates, pericarditis, splenomegaly and poorer treatment responses. A correlation study revealed that the CD4 to CD8 ratio was negatively correlated with the systemic score and positively correlated with treatment response in patients with AOSD (P = 0.001 and P = 0.0091). During the 24.6 (15.2) months of follow-up, the highest total number of disease flares occurred in group 3 (P < 0.0001). CONCLUSION: Hierarchical cluster analysis of peripheral immune cells classified AOSD into three disease-related endotypes. Group 3 showed higher systemic score and poorer treatment responses.

Biomarkers of asthma relapse and lung function decline in adults with spontaneous asthma remission: A population-based cohort study.

BACKGROUND: The extent to which biomarkers of asthma activity persist in spontaneous asthma remission and whether such markers are associated with future respiratory outcomes remained unclear. We investigated the association between sub-clinical inflammation in adults with spontaneous asthma remission and future asthma relapse and lung function decline. METHODS: The Tasmanian Longitudinal Health Study is a population-based cohort (n = 8583). Biomarkers of systemic inflammation were measured on participants at age 45, and latent profile analysis was used to identify cytokine profiles. Bronchial hyperresponsiveness (BHR) and nitric oxide products in exhaled breath condensate (EBC NOx) were measured at age 50. Participants with spontaneous asthma remission at ages 45 (n = 466) and 50 (n = 318) were re-evaluated at age 53, and associations between baseline inflammatory biomarkers and subsequent asthma relapse and lung function decline were assessed. RESULTS: We identified three cytokine profiles in adults with spontaneous asthma remission: average (34%), Th2-high (42%) and Th2-low (24%). Compared to the average profile, a Th2-high profile was associated with accelerated decline in post-BD FEV1 /FVC (MD -0.18% predicted per-year; 95% CI -0.33, -0.02), while a Th2-low profile was associated with accelerated decline in both post-BD FEV1 (-0.41%; -0.75, -0.06) and post-BD FVC (-0.31%; -0.62, 0.01). BHR and high TNF-α during spontaneous remission were associated with an increased risk of asthma relapse. In contrast, we found no evidence of association between EBC NOx and either asthma relapse or lung function decline. CONCLUSION: BHR and serum inflammatory cytokines have prognostic value in adults with spontaneous asthma remission. At-risk individuals with BHR, Th2-high or Th2-low cytokine profiles may benefit from closer monitoring and on-going follow-up.