Genome-wide bidirectional CRISPR screens identify mucins as host factors modulating SARS-CoV-2 infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes a range of symptoms in infected individuals, from mild respiratory illness to acute respiratory distress syndrome. A systematic understanding of host factors influencing viral infection is critical to elucidate SARS-CoV-2–host interactions and the progression of Coronavirus disease 2019 (COVID-19). Here, we conducted genome-wide CRISPR knockout and activation screens in human lung epithelial cells with endogenous expression of the SARS-CoV-2 entry factors ACE2 and TMPRSS2. We uncovered proviral and antiviral factors across highly interconnected host pathways, including clathrin transport, inflammatory signaling, cell-cycle regulation, and transcriptional and epigenetic regulation. We further identified mucins, a family of high molecular weight glycoproteins, as a prominent viral restriction network that inhibits SARS-CoV-2 infection in vitro and in murine models. These mucins also inhibit infection of diverse respiratory viruses. This functional landscape of SARS-CoV-2 host factors provides a physiologically relevant starting point for new host-directed therapeutics and highlights airway mucins as a host defense mechanism

Evolution of the nutritional status of COVID-19 critically-ill patients: A prospective observational study from ICU admission to three months after ICU discharge

International audienceBackground & aims: Malnutrition following intensive care unit (ICU) stay is frequent and could be especially prominent in critically ill Coronavirus Disease 2019 (COVID-19) patients as they present prolonged inflammatory state and long length stay. We aimed to determine the prevalence of malnutrition in critically ill COVID-19 patients both at the acute and recovery phases of infection.Methods: We conducted a prospective observational study including critically ill COVID-19 patients requiring invasive mechanical ventilation discharged alive from a medical ICU of a university hospital. We collected demographic, anthropometric and ICU stay data (SAPS2, recourse to organ support and daily energy intake). Nutritional status and nutritional support were collected at one month after ICU discharge (M1) by phone interview and at 3 months after ICU discharge (M3) during a specialized and dedicated consultation conducted by a dietitian. Malnutrition diagnosis was based on weight loss and body mass index (BMI) criteria following the Global Leadership Initiative on Malnutrition. Primary outcome was the prevalence of malnutrition at M3 and secondary outcomes were the evolution of nutritional status from ICU admission to M3 and factors associated with malnutrition at M3.Results: From march 13th to may 15th, 2020, 38 patients were discharged alive from the ICU, median [IQR] age 66 [59-72] years, BMI 27.8 [25.5-30.7] kg/m2 and SAPS2 47 [35-55]. Thirty-three (86%) patients were followed up to M3. Prevalence of malnutrition increased during the ICU stay, from 18% at ICU admission to 79% at ICU discharge and then decreased to 71% at M1 and 53% at M3. Severe malnutrition prevailed at ICU discharge with a prevalence of 55% decreasing 32% at M3. At M3, the only factors associated with malnutrition in univariate analysis were the length of invasive mechanical ventilation and length of ICU stay (28 [18-44] vs. 13 [11-24] days, P = 0.011 and 32 [22-48] vs. 17 [11-21] days, P = 0.006, respectively), while no ICU preadmission and admission factors, nor energy and protein intakes distinguished the two groups. Only 35% of undernourished patients at M3 had benefited from a nutritional support.Conclusion: Malnutrition is frequent, protracted and probably underrecognized among critically ill Covid-19 patients requiring invasive mechanical ventilation with more than half patients still being undernourished three months after ICU discharge. A particular attention should be paid to the nutritional status of these patients not only during their ICU stay but also following ICU discharge

Identification of symbol digit modality test score extremes in Huntington's disease

Studying individuals with extreme phenotypes could facilitate the understanding of disease modification by genetic or environmental factors. Our aim was to identify Huntington's disease (HD) patients with extreme symbol digit modality test (SDMT) scores. We first examined in HD the contribution of cognitive measures of the Unified Huntington's Disease Rating Scale (UHDRS) in predicting clinical endpoints. The language-independent SDMT was used to identify patients performing very well or very poorly relative to their CAG and age cohort. We used data from REGISTRY and COHORT observational study participants (5,603 HD participants with CAG repeats above 39 with 13,868 visits) and of 1,006 healthy volunteers (with 2,241 visits), included to identify natural aging and education effects on cognitive measures. Separate Cox proportional hazards models with CAG, age at study entry, education, sex, UHDRS total motor score and cognitive (SDMT, verbal fluency, Stroop tests) scores as covariates were used to predict clinical endpoints. Quantile regression for longitudinal language-independent SDMT data was used for boundary (2.5% and 97.5% quantiles) estimation and extreme score analyses stratified by age, education, and CAG repeat length. Ten percent of HD participants had an extreme SDMT phenotype for at least one visit. In contrast, only about 3% of participants were consistent SDMT extremes at two or more visits. The thresholds for the one-visit and two-visit extremes can be used to classify existing and new individuals. The identification of these phenotype extremes can be useful in the search for disease modifiers.Neurological Motor Disorder