Evaluating the Immune Response in Treatment-Naive Hospitalised Patients With Influenza and COVID-19

The worldwide COVID-19 pandemic has claimed millions of lives and has had a profound effect on global life. Understanding the body’s immune response to SARS-CoV-2 infection is crucial in improving patient management and prognosis. In this study we compared influenza and SARS-CoV-2 infected patient cohorts to identify distinct blood transcript abundances and cellular composition to better understand the natural immune response associated with COVID-19, compared to another viral infection being influenza, and identify a prognostic signature of COVID-19 patient outcome. Clinical characteristics and peripheral blood were acquired upon hospital admission from two well characterised cohorts, a cohort of 88 patients infected with influenza and a cohort of 80 patients infected with SARS-CoV-2 during the first wave of the pandemic and prior to availability of COVID-19 treatments and vaccines. Gene transcript abundances, enriched pathways and cellular composition were compared between cohorts using RNA-seq. A genetic signature between COVID-19 survivors and non-survivors was assessed as a prognostic predictor of COVID-19 outcome. Contrasting immune responses were detected with an innate response elevated in influenza and an adaptive response elevated in COVID-19. Additionally ribosomal, mitochondrial oxidative stress and interferon signalling pathways differentiated the cohorts. An adaptive immune response was associated with COVID-19 survival, while an inflammatory response predicted death. A prognostic transcript signature, associated with circulating immunoglobulins, nucleosome assembly, cytokine production and T cell activation, was able to stratify COVID-19 patients likely to survive or die. This study provides a unique insight into the immune responses of treatment naïve patients with influenza or COVID-19. The comparison of immune response between COVID-19 survivors and non-survivors enables prognostication of COVID-19 patients and may suggest potential therapeutic strategies to improve survival

Des yeux et du regard : proverbes et expressions

Les yeux et le regard participent de façon majeure à notre langage non verbal, avant même l’apparition du verbe. Depuis la Bible jusqu’au langage contemporain, en passant par la mythologie grecque, le théâtre, la littérature ou le langage parlé, une multitude d’expressions et de proverbes mettent en scène l’œil, ce qu’il voit et ce qu’il symbolise. Cet article parcourt les champs sémantiques de l’œil et du regard, leur évolution dans le temps, et leur étonnante richesse. En définitive, une revue de notre humanité

Severe neurodevelopmental phenotype, diagnostic and treatment challenges in patients with SECISBP2 deficiency

Purpose:Defects in the gene encoding selenocysteine insertion sequence binding protein 2, SECISBP2, result in global impaired selenoprotein synthesis manifesting a complex syndrome with characteristic serum thyroid function tests due to impaired thyroid hormone metabolism. Knowledge about this multisystemic defect remains limited. Methods:Genetic and laboratory investigations were performed in affected members from six families presenting with short stature, failure to thrive. Results:Four probands presented a complex neurodevelopmental profile, including absent speech, autistic features, and seizures. Pediatric neurological evaluation prompted genetic investigations leading to the identification of SECISBP2 variants before knowing the characteristic thyroid tests in two cases. Thyroid hormone treatment improved motor development, while speech and intellectual impairments persisted. This defect poses great diagnostic and treatment challenges for clinicians, as illustrated by a case that escaped detection for 20years, as SECISBP2 was not included in the neurodevelopmental genetic panel, and his complex thyroid status prompted anti-thyroid treatment instead. Conclusion:This syndrome uncovers the role of selenoproteins in humans. The severe neurodevelopmental disabilities manifested in four patients with SECISBP2 deficiency highlight an additional phenotype in this multisystem disorder. Early diagnosis and treatment are required, and long-term evaluation will determine the full spectrum of manifestations and the impact of therapy

Distinct immune responses in patients infected with influenza or SARS-CoV-2, and in COVID-19 survivors, characterised by transcriptomic and cellular abundance differences in blood

Background: the worldwide pandemic caused by SARS-CoV-2 has claimed millions of lives and has had a profound effect on global life. Understanding the pathogenicity of the virus and the body’s response to infection is crucial in improving patient management, prognosis, and therapeutic strategies. To address this, we performed functional transcriptomic profiling to better understand the generic and specific effects of SARS-CoV-2 infection.Methods: whole blood RNA sequencing was used to profile a well characterised cohort of patients hospitalised with COVID-19, during the first wave of the pandemic prior to the availability of approved COVID-19 treatments and who went on to survive or die of COVID-19, and patients hospitalised with influenza virus infection between 2017 and 2019. Clinical parameters between patient groups were compared, and several bioinformatic tools were used to assess differences in transcript abundances and cellular composition.Results: the analyses revealed contrasting innate and adaptive immune programmes, with transcripts and cell subsets associated with the innate immune response elevated in patients with influenza, and those involved in the adaptive immune response elevated in patients with COVID-19. Topological analysis identified additional gene signatures that differentiated patients with COVID-19 from patients with influenza, including insulin resistance, mitochondrial oxidative stress and interferon signalling. An efficient adaptive immune response was furthermore associated with patient survival, while an inflammatory response predicted death in patients with COVID-19. A potential prognostic signature was found based on a selection of transcript abundances, associated with circulating immunoglobulins, nucleosome assembly, cytokine production and T cell activation, in the blood transcriptome of COVID-19 patients, upon admission to hospital, which can be used to stratify patients likely to survive or die.Conclusions: the results identified distinct immunological signatures between SARS-CoV-2 and influenza, prognostic of disease progression and indicative of different targeted therapies. The altered transcript abundances associated with COVID-19 survivors can be used to predict more severe outcomes in patients with COVID-19

Blood gene expression predicts intensive care unit admission in hospitalised patients with COVID-19

Background: The COVID-19 pandemic has created pressure on healthcare systems worldwide. Tools that can stratify individuals according to prognosis could allow for more efficient allocation of healthcare resources and thus improved patient outcomes. It is currently unclear if blood gene expression signatures derived from patients at the point of admission to hospital could provide useful prognostic information.Methods: Gene expression of whole blood obtained at the point of admission from a cohort of 78 patients hospitalised with COVID-19 during the first wave was measured by high resolution RNA sequencing. Gene signatures predictive of admission to Intensive Care Unit were identified and tested using machine learning and topological data analysis, TopMD.RResults: The best gene expression signature predictive of ICU admission was defined using topological data analysis with an accuracy: 0.72 and ROC AUC: 0.76. The gene signature was primarily based on differentially activated pathways controlling epidermal growth factor receptor (EGFR) presentation, Peroxisome proliferator-activated receptor alpha (PPAR-α) signalling and Transforming growth factor beta (TGF-β) signalling.Conclusions: Gene expression signatures from blood taken at the point of admission to hospital predicted ICU admission of treatment naïve patients with COVID-19

DataSheet_1_Blood gene expression predicts intensive care unit admission in hospitalised patients with COVID-19.docx

BackgroundThe COVID-19 pandemic has created pressure on healthcare systems worldwide. Tools that can stratify individuals according to prognosis could allow for more efficient allocation of healthcare resources and thus improved patient outcomes. It is currently unclear if blood gene expression signatures derived from patients at the point of admission to hospital could provide useful prognostic information.MethodsGene expression of whole blood obtained at the point of admission from a cohort of 78 patients hospitalised with COVID-19 during the first wave was measured by high resolution RNA sequencing. Gene signatures predictive of admission to Intensive Care Unit were identified and tested using machine learning and topological data analysis, TopMD.ResultsThe best gene expression signature predictive of ICU admission was defined using topological data analysis with an accuracy: 0.72 and ROC AUC: 0.76. The gene signature was primarily based on differentially activated pathways controlling epidermal growth factor receptor (EGFR) presentation, Peroxisome proliferator-activated receptor alpha (PPAR-α) signalling and Transforming growth factor beta (TGF-β) signalling.ConclusionsGene expression signatures from blood taken at the point of admission to hospital predicted ICU admission of treatment naïve patients with COVID-19.</p

Recent outcome of liver transplantation for Budd Chiari syndrome - analysis of the european liver transplant registry (ELTR) and affiliated centres

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