Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Burden of Uncontrolled Severe Asthma With and Without Elevated Type-2 Inflammatory Biomarkers

Background: Many patients with asthma have type-2 airway inflammation, identified by the presence of biomarkers, including history of allergy, high blood eosinophil (EOS) count, and high fractional exhaled nitric oxide levels. Objective: To assess disease burden in relation to type-2 inflammatory biomarker status (history of allergy, blood EOS count, and fractional exhaled nitric oxide level) in patients with uncontrolled and controlled severe asthma in the NOVEL observational longiTudinal studY (NOVELTY) (NCT02760329). Methods: Asthma diagnosis and severity were physician-reported. Control was defined using Asthma Control Test score (uncontrolled <20, controlled ≥20) and/or 1 or more severe physician-reported exacerbation in the previous year. Biomarker distribution (history of allergy, blood EOS count, and fractional exhaled nitric oxide level), symptom burden (Asthma Control Test score, modified Medical Research Council dyspnea scale), health status (St George's Respiratory Questionnaire score), exacerbations, and health care resource utilization were assessed. Results: Of 647 patients with severe asthma, 446 had uncontrolled and 123 had controlled asthma. Among those with uncontrolled asthma, 196 (44%) had 2 or more positive biomarkers, 187 (42%) had 1 positive biomarker, 325 (73%) had low blood EOS, and 63 (14%) were triple-negative. Disease burden was similarly high across uncontrolled subgroups, irrespective of biomarker status, with poor symptom control (Asthma Control Test score 14.9-16.6), impaired health status (St George's Respiratory Questionnaire total score 46.7-49.4), clinically important breathlessness (modified Medical Research Council grade ≥2 in 47.3%-57.1%), and 1 or more severe exacerbation (70.6%-76.2%). Conclusions: Type-2 inflammatory biomarkers did not differentiate disease burden in patients with severe asthma. Patients with low type-2 inflammatory biomarker levels have few biologic therapy options; their needs should be addressed

Cluster Analyses From the Real-World NOVELTY Study: Six Clusters Across the Asthma-COPD Spectrum

Background: Asthma and chronic obstructive pulmonary disease (COPD) are complex diseases, the definitions of which overlap. Objective: To investigate clustering of clinical/physiological features and readily available biomarkers in patients with physician-assigned diagnoses of asthma and/or COPD in the NOVEL observational longiTudinal studY (NOVELTY; NCT02760329). Methods: Two approaches were taken to variable selection using baseline data: approach A was data-driven, hypothesis-free and used the Pearson dissimilarity matrix; approach B used an unsupervised Random Forest guided by clinical input. Cluster analyses were conducted across 100 random resamples using partitioning around medoids, followed by consensus clustering. Results: Approach A included 3796 individuals (mean age, 59.5 years; 54% female); approach B included 2934 patients (mean age, 60.7 years; 53% female). Each identified 6 mathematically stable clusters, which had overlapping characteristics. Overall, 67% to 75% of patients with asthma were in 3 clusters, and approximately 90% of patients with COPD were in 3 clusters. Although traditional features such as allergies and current/ex-smoking (respectively) were higher in these clusters, there were differences between clusters and approaches in features such as sex, ethnicity, breathlessness, frequent productive cough, and blood cell counts. The strongest predictors of the approach A cluster membership were age, weight, childhood onset, prebronchodilator FEV1, duration of dust/fume exposure, and number of daily medications. Conclusions: Cluster analyses in patients from NOVELTY with asthma and/or COPD yielded identifiable clusters, with several discriminatory features that differed from conventional diagnostic characteristics. The overlap between clusters suggests that they do not reflect discrete underlying mechanisms and points to the need for identification of molecular endotypes and potential treatment targets across asthma and/or COPD

Burden of Uncontrolled Severe Asthma With and Without Elevated Type-2 Inflammatory Biomarkers

Background: Many patients with asthma have type-2 airway inflammation, identified by the presence of biomarkers, including history of allergy, high blood eosinophil (EOS) count, and high fractional exhaled nitric oxide levels. Objective: To assess disease burden in relation to type-2 inflammatory biomarker status (history of allergy, blood EOS count, and fractional exhaled nitric oxide level) in patients with uncontrolled and controlled severe asthma in the NOVEL observational longiTudinal studY (NOVELTY) (NCT02760329). Methods: Asthma diagnosis and severity were physician-reported. Control was defined using Asthma Control Test score (uncontrolled = 20) and/or 1 or more severe physician-reported exacerbation in the previous year. Biomarker distribution (history of allergy, blood EOS count, and fractional exhaled nitric oxide level), symptom burden (Asthma Control Test score, modified Medical Research Council dyspnea scale), health status (St George's Respiratory Questionnaire score), exacerbations, and health care resource utilization were assessed. Results: Of 647 patients with severe asthma, 446 had uncontrolled and 123 had controlled asthma. Among those with uncontrolled asthma, 196 (44%) had 2 or more positive biomarkers, 187 (42%) had 1 positive biomarker, 325 (73%) had low blood EOS, and 63 (14%) were triple-negative. Disease burden was similarly high across uncontrolled subgroups, irrespective of biomarker status, with poor symptom control (Asthma Control Test score 14.9-16.6), impaired health status (St George's Respiratory Questionnaire total score 46.7-49.4), clinically important breathlessness (modified Medical Research Council grade >= 2 in 47.3%-57.1%), and 1 or more severe exacerbation (70.6%-76.2%). Conclusions: Type-2 inflammatory biomarkers did not differentiate disease burden in patients with severe asthma. Patients with low type-2 inflammatory biomarker levels have few biologic therapy options; their needs should be addressed

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Marqueurs de sévérité et marqueurs prédictifs de réponse au traitement dans l’asthme sévère

International audienceAsthma is a multifactorial disease with complex pathophysiology. Knowledge of its immunopathology and inflammatory mechanisms is progressing and has led to the development over recent years of increasingly targeted therapeutic strategies. The objective of this review is to pinpoint the different predictive markers of asthma severity and therapeutic response. Obesity, nasal polyposis, gastroesophageal reflux disease and intolerance to aspirin have all been considered as clinical markers associated with asthma severity, as have functional markers such as bronchial obstruction, low FEV1, small daily variations in FEV1, and high FeNO. While sinonasal polyposis and allergic comorbidities are associated with better response to omalizumab, nasal polyposis or long-term systemic steroid use are associated with better response to antibodies targeting the IL5 pathway. Elevated total IgE concentrations and eosinophil counts are classic biological markers regularly found in severe asthma. Blood eosinophils are predictive biomarkers of response to anti-IgE, anti-IL5, anti-IL5R and anti-IL4R biotherapies. Dupilumab is particularly effective in a subgroup of patients with marked type 2 inflammation (long-term systemic corticosteroid therapy, eosinophilia≥150/μl or FENO>20 ppb). Chest imaging may help to identify severe patients by seeking out bronchial wall thickening and bronchial dilation. Study of the patient's environment is crucial insofar as exposure to tobacco, dust mites and molds, as well as outdoor and indoor air pollutants (cleaning products), can trigger asthma exacerbation. Wider and more systematic use of markers of severity or response to treatment could foster increasingly targeted and tailored approaches to severe asthma.L’asthme est une maladie multifactorielle dont la physiopathologie est complexe. Les connaissances de l’immunopathologie et des mécanismes inflammatoires ont progressé permettant ces dernières années, le développement de stratégies thérapeutiques de plus en plus ciblées.L’objectif de cette revue est de décrire les différents marqueurs prédictifs de la sévérité de l’asthme et de la réponse thérapeutique. Sur le plan clinique, l’obésité, la polypose nasale, le reflux gastro-œsophagien, l’intolérance à l’aspirine ont été décrits comme des marqueurs associés à la sévérité de l’asthme.Des marqueurs fonctionnels tels qu’une obstruction bronchique, un VEMS bas, de faibles variations journalières de VEMS et une FeNO élevé ont également été décrits comme associés à la sévérité de l’asthme. La polypose naso-sinusienne et les comorbidités allergiques sont associées à une meilleure réponse à l’omalizumab alors que la polypose nasale ou l’utilisation d’une corticothérapie systémique au long cours est associée à une meilleure réponse aux anticorps dirigés contre la voie de l’IL5. Des concentrations d’IgE totales et un taux d’éosinophiles élevés sont des marqueurs biologiques classiquement retrouvés dans l’asthme sévère. L’éosinophilie sanguine est un biomarqueur permettant de prédire la réponse aux biothérapies anti-IgE, anti-IL5, anti-IL5R et anti-IL4R. Le dupilumab s’est révélé efficace en particulier dans le sous-groupe de patients présentant une inflammation de type 2 marquée (corticothérapie systémique au long cours, éosinophilie≥150/μl ou FENO>20 ppb). L’imagerie thoracique pourrait également contribuer à identifier des patients sévères par la recherche d’un épaississement de la paroi bronchique et une dilatation des bronches. L’étude de l’environnement est cruciale puisque des allergènes et des polluants aggravent la maladie asthmatique.Une utilisation plus large et systématique des marqueurs de sévérité ou de réponse au traitement pourrait permettre une approche de plus en plus précise et personnalisée

Characterisation of human mesenchymal stem cells following differentiation into Schwann cell-like cells

Cell-based therapies provide a clinically applicable and available alternative to nerve autografts. Our previous studies have characterised rat-derived mesenchymal stem cells (MSC) and here we have investigated the phenotypic, molecular and functional characteristics of human-derived MSC (hMSC) differentiated along a Schwann cell lineage. The hMSC were isolated from healthy human donors and the identity of the undifferentiated hMSC was confirmed by the detection of MSC specific cells surface markers. The hMSC were differentiated along a glial cell lineage using an established cocktail of growth factors including glial growth factor-2. Following differentiation, the hMSC expressed the key Schwann cell (SC) markers at both the transcriptional and translational level. More importantly, we show the functional effect of hMSC on neurite outgrowth using an in vitro co-culture model system with rat-derived primary sensory neurons. The number of DRG sprouting neurites was significantly enhanced in the presence of differentiated hMSC; neurite length and density (branching) were also increased. These results provide evidence that hMSC can undergo molecular, morphological and functional changes to adopt a SC-like behaviour and, therefore, could be suitable as SC substitutes for nerve repair in clinical applications.</p