ABSTRACT
Primary Sjögren disease (pSD) is an autoimmune disease characterized by lymphoid infiltration of exocrine glands leading to dryness of the mucosal surfaces and by the production of autoantibodies. The pathophysiology of pSD remains elusive and no treatment with demonstrated efficacy is available yet. To better understand the biology underlying pSD heterogeneity, we aimed at identifying Consensus gene Modules (CMs) that summarize the high-dimensional transcriptomic data of whole blood samples in pSD patients. We performed unsupervised gene classification on four data sets and identified thirteen CMs. We annotated and interpreted each of these CMs as corresponding to cell type abundances or biological functions by using gene set enrichment analyses and transcriptomic profiles of sorted blood cell subsets. Correlation with independently measured cell type abundances by flow cytometry confirmed these annotations. We used these CMs to reconcile previously proposed patient stratifications of pSD. Importantly, we showed that the expression of modules representing lymphocytes and erythrocytes before treatment initiation is associated with response to hydroxychloroquine and leflunomide combination therapy in a clinical trial. These consensus modules will help the identification and translation of blood-based predictive biomarkers for the treatment of pSD.
Subject(s)
Biomarkers , Sjogren's Syndrome , Humans , Sjogren's Syndrome/genetics , Sjogren's Syndrome/blood , Biomarkers/blood , Transcriptome , Gene Expression Profiling/methods , Hydroxychloroquine/therapeutic use , Female , Gene Regulatory Networks , Lymphocytes/metabolismABSTRACT
BACKGROUND: Temocillin is a narrow spectrum ß-lactam active against MDR Enterobacterales. Mechanisms of acquired resistance to temocillin are poorly understood. We analysed resistance mechanisms in clinical isolates of Escherichia coli and evaluated their impact on temocillin efficacy in vitro and in a murine peritonitis model. METHODS: Two sets of isogenic clinical E. coli strains were studied: a susceptible isolate (MLTEM16S) and its resistant derivative, MLTEM16R (mutation in nmpC porin gene); and temocillin-resistant derivatives of E. coli CFT073: CFT-ΔnmpC (nmpC deletion), CFTbaeS-TP and CFTbaeS-AP (two different mutations in the baeS efflux-pump gene).Fitness cost, time-kill curves and phenotypic expression of resistance were determined. Temocillin efficacy was assessed in a murine peritonitis model. RESULTS: MICs of temocillin were 16 and 64 mg/L for MLTEM16S and MLTEM16R, respectively, and 8, 128, 256 and 256 mg/L for E. coli-CFT073, CFT-ΔnmpC, CFTbaeS-TP and CFTbaeS-AP, respectively. No fitness cost of resistance was evidenced. All resistant strains showed heteroresistant profiles, except for CFTbaeS-AP, which displayed a homogeneous pattern. In vitro, temocillin was bactericidal against MLTEM16R, CFT-ΔnmpC, CFTbaeS-TP and CFTbaeS-AP at 128, 256, 512 and 512 mg/L, respectively. In vivo, temocillin was as effective as cefotaxime against MLTEM16R, CFT-ΔnmpC and CFTbaeS-TP, but inefficient against CFTbaeS-AP (100% mortality). CONCLUSIONS: Heteroresistant NmpC porin alteration and active efflux modification do not influence temocillin efficacy despite high MIC values, unfavourable pharmacokinetic/pharmacodynamic conditions and the absence of fitness cost, whereas homogeneously expressed BaeS efflux pump alteration yielding similar MICs leads to temocillin inefficacy. MIC as sole predictor of temocillin efficacy should be used with caution.
Subject(s)
Anti-Bacterial Agents , Disease Models, Animal , Escherichia coli Infections , Escherichia coli , Microbial Sensitivity Tests , Penicillins , Peritonitis , Animals , Peritonitis/microbiology , Peritonitis/drug therapy , Penicillins/pharmacology , Anti-Bacterial Agents/pharmacology , Anti-Bacterial Agents/therapeutic use , Escherichia coli/drug effects , Escherichia coli/genetics , Escherichia coli Infections/drug therapy , Escherichia coli Infections/microbiology , Mice , Drug Resistance, Bacterial/genetics , Female , Treatment Outcome , Phenotype , HumansABSTRACT
Background: Temocillin is a ß-lactam that is not hydrolysed by ESBLs. Objectives: To describe the real-life use of temocillin, to assess its effectiveness in infections caused by ESBL-producing Enterobacterales, and to identify risk factors for treatment failure. Methods: Retrospective multicentric study in eight tertiary care hospitals in the Greater Paris area, including patients who received at least one dose of temocillin for ESBL infections from 1 January to 31 December 2018. Failure was a composite criterion defined within 28â day follow-up by persistence or reappearance of signs of infection, and/or switch to suppressive antibiotic treatment and/or death from infection. A logistic regression with univariable and multivariable analysis was performed to identify risks associated with failure. Results: Data on 130 infection episodes were collected; 113 were due to ESBL-producing Enterobacterales. Mean age was 65.2â±â15.7â years and 68.1% patients were male. Indications were mostly urinary tract infections (UTIs) (85.8%), bloodstream infections (11.5%), respiratory tract infections (RTIs) (3.5%) and intra-abdominal infections (3.5%). Bacteria involved were Escherichia coli (49.6%), Klebsiella pneumoniae (44.2%) and Enterobacter cloacae (8.8%). Polymicrobial infections occurred in 23.0% of cases. Temocillin was mostly used in monotherapy (102/113, 90.3%). Failure was found in 13.3% of cases. Risk factors for failure in multivariable analysis were: RTI (aOR 23.3, 95% CI 1.5-358.2) and neurological disease (aOR 5.3, 95% CI 1.5-18.6). Conclusions: The main use of temocillin was UTI due to ESBL-producing E. coli and K. pneumoniae, with a favourable clinical outcome. The main risk factor for failure was neurological disease.
ABSTRACT
Background: Mycobacterium xenopi is one of the most common pathogens responsible for non-tuberculosis mycobacteria (NTM) pulmonary diseases, which are associated with poor prognosis in immunocompromised patients. Case presentation: We report the unusual case of a 44-year-old kidney transplant recipient with multiple pulmonary nodules revealing M. xenopi pulmonary disease with atypical presentation. A three drug-regimen containing moxifloxacin, ethambutol and azithromycin was prescribed, with careful monitoring of the immunosuppressive therapy. The outcome was favorable. Discussion and conclusion: Although infrequent in kidney transplant recipients, NTM can cause pulmonary infection several years after transplantation. Treatment of M. xenopi infection relies on a multidrug regimen with at least 3 antimycobacterial drugs. Drug-drug interactions between immunosuppressive treatments and rifamycins require careful dose adjustment and monitoring to avoid graft rejection.
ABSTRACT
INTRODUCTION: As a mid-size international pharmaceutical company, we initiated 4 years ago the launch of a dedicated high-throughput computing platform supporting drug discovery. The platform named 'Patrimony' was built up on the initial predicate to capitalize on our proprietary data while leveraging public data sources in order to foster a Computational Precision Medicine approach with the power of artificial intelligence. AREAS COVERED: Specifically, Patrimony is designed to identify novel therapeutic target candidates. With several successful use cases in immuno-inflammatory diseases, and current ongoing extension to applications to oncology and neurology, we document how this industrial computational platform has had a transformational impact on our R&D, making it more competitive, as well time and cost effective through a model-based educated selection of therapeutic targets and drug candidates. EXPERT OPINION: We report our achievements, but also our challenges in implementing data access and governance processes, building up hardware and user interfaces, and acculturing scientists to use predictive models to inform decisions.
Subject(s)
Artificial Intelligence , Drug Discovery , Humans , Precision MedicineABSTRACT
While establishing worldwide collective immunity with anti SARS-CoV-2 vaccines, COVID-19 remains a major health issue with dramatic ensuing economic consequences. In the transition, repurposing existing drugs remains the fastest cost-effective approach to alleviate the burden on health services, most particularly by reducing the incidence of the acute respiratory distress syndrome associated with severe COVID-19. We undertook a computational repurposing approach to identify candidate therapeutic drugs to control progression towards severe airways inflammation during COVID-19. Molecular profiling data were obtained from public sources regarding SARS-CoV-2 infected epithelial or endothelial cells, immune dysregulations associated with severe COVID-19 and lung inflammation induced by other respiratory viruses. From these data, we generated a protein-protein interactome modeling the evolution of lung inflammation during COVID-19 from inception to an established cytokine release syndrome. This predictive model assembling severe COVID-19-related proteins supports a role for known contributors to the cytokine storm such as IL1ß, IL6, TNFα, JAK2, but also less prominent actors such as IL17, IL23 and C5a. Importantly our analysis points out to alarmins such as TSLP, IL33, members of the S100 family and their receptors (ST2, RAGE) as targets of major therapeutic interest. By evaluating the network-based distances between severe COVID-19-related proteins and known drug targets, network computing identified drugs which could be repurposed to prevent or slow down progression towards severe airways inflammation. This analysis confirmed the interest of dexamethasone, JAK2 inhibitors, estrogens and further identified various drugs either available or in development interacting with the aforementioned targets. We most particularly recommend considering various inhibitors of alarmins or their receptors, currently receiving little attention in this indication, as candidate treatments for severe COVID-19.
Subject(s)
Alarmins/immunology , Antiviral Agents/pharmacology , COVID-19/complications , Drug Repositioning , Pneumonia/complications , Pneumonia/drug therapy , Antiviral Agents/immunology , Antiviral Agents/therapeutic use , Humans , Pneumonia/immunologyABSTRACT
OBJECTIVE: To assess post-discharge persistent symptoms and health-related quality of life (HRQoL) of patients hospitalized in a COVID-19 ward unit more than 100 days after their admission. METHODS: All eligible patients were contacted by phone by trained physicians and were asked to answer to a dedicated questionnaire. Patients managed in hospital ward without needing intensive care were compared with those who were transferred in intensive care units (ICU). RESULTS: We included 120 patients after a mean (±SD) of 110.9 (±11.1) days following admission. The most frequently reported persistent symptoms were fatigue (55%), dyspnoea (42%), loss of memory (34%), concentration and sleep disorders (28% and 30.8%, respectively). Comparisons between ward- and ICU patients led to no statistically significant differences regarding those symptoms. In both group, EQ-5D (mobility, self-care, pain, anxiety or depression, usual activity) was altered with a slight difference in pain in the ICU group. CONCLUSION: Most patients requiring hospitalization for COVID-19 still have persistent symptoms. While there were few differences between HRQoL between ward and ICU patients, our findings must be confirmed in larger cohorts, including more severe patients.