We performed next-generation sequencing in patients with familial steroid-sensitive nephrotic syndrome (SSNS) and identified a homozygous segregating variant (p.H310Y) in the gene encoding clavesin-1 ( CLVS1 ) in a consanguineous family with 3 affected individuals. Knockdown of the clavesin gene in zebrafish (clvs2) produced edema phenotypes due to disruption of podocyte structure and loss of glomerular filtration barrier integrity that could be rescued by WT CLVS1 but not the p.H310Y variant. Analysis of cultured human podocytes with CRISPR/Cas9-mediated CLVS1 knockout or homozygous H310Y knockin revealed deficits in clathrin-mediated endocytosis and increased susceptibility to apoptosis that could be rescued with corticosteroid treatment, mimicking the steroid responsiveness observed in patients with SSNS. The p.H310Y variant also disrupted binding of clavesin-1 to α -tocopherol transfer protein, resulting in increased reactive oxygen species (ROS) accumulation in CLVS1 -deficient podocytes. Treatment of CLVS1 -knockout or homozygous H310Y-knockin podocytes with pharmacological ROS inhibitors restored viability to control levels. Taken together, these data identify CLVS1 as a candidate gene for SSNS, provide insight into therapeutic effects of corticosteroids on podocyte cellular dynamics, and add to the growing evidence of the importance of endocytosis and oxidative stress regulation to podocyte function.

Background: SARS-CoV-2 infection has a high mortality rate and continues to be a global threat, which warrants the identification of all mortality risk factors in critically ill patients. Methods: This is a retrospective multicenter cohort study conducted in five hospitals in the Kingdom of Saudi Arabia (KSA). We enrolled patients with confirmed SARS-COV-2 infection admitted to any of the intensive care units from the five hospitals between March 2020 and July 2020, corresponding to the peak of recorded COVID-19 cases in the KSA. Results: In total, 229 critically ill patients with confirmed SARS-CoV-2 infection were included in the study. The presenting symptoms and signs of patients who died during hospitalization were not significantly different from those observed among patients who survived. The baseline comorbidities that were significantly associated with in-hospital mortality were diabetes (62% vs. 48% among patients who died and survived (p = 0.046)), underlying cardiac disease (38% vs. 19% (p = 0.001)), and underlying kidney disease (32% vs. 12% (p < 0.001)). Conclusion: In our cohort, the baseline comorbidities that were significantly associated with in-hospital mortality were diabetes, underlying cardiac disease, and underlying kidney disease. Additionally, the factors that independently influenced mortality among critically ill COVID-19 patients were high Activated Partial Thromboplastin Time (aPTT )and international normalization ratio (INR), acidosis, and high ferritin.

Background: COVID-19 is a respiratory disease that eventually became a pandemic, with 300 million people infected around the world. Alongside the improvement in COVID-19 management and vaccine development, identifying biomarkers for COVID-19 has recently been reported to help in early prediction and managing severe cases, which might improve outcomes. Our study aimed to find out if there is any correlation between clinical severity and elevated hematological and biochemical markers in COVID-19 patients and its effect on the outcome. Methods: We have collected retrospective data on socio-demographics, medical history, biomarkers, and disease outcomes from five hospitals and health institutions in the Kingdom of Saudi Arabia. Results: Pneumonia was the most common presentation of COVID-19 in our cohort. The presence of abnormal inflammatory biomarkers (D-dimer, CRP, troponin, LDH, ferritin, and t white blood cells) was significantly associated with unstable COVID-19 disease. In addition, patients with evidence of severe respiratory disease, particularly those who required mechanical ventilation, had higher biomarkers when compared to those with stable respiratory conditions (p < 0.001). Conclusion: Identifying biomarkers predicts outcomes for COVID-19 patients and may significantly help in their management.

Background: COVID-19 is a respiratory disease that eventually became pandemic with 300 million people infected around the world. Alongside the improvement in COVID-19 management and vaccine development, identifying biomarkers for COVID-19 has recently reported to help in early prediction and managing severe cases which might improve outcome. The Aim of our study was to find out if there is any correlation between clinical severity and elevated hematological and biochemical markers in Covid-19 patients and its effect on the outcome Methods: We have collected data retrospectively of socio-demographic, medical history, biomarkers, and diseases outcome from five hospitals and health institutions in the Kingdom of Saudi Arabia. Results: Pneumonia was the most common presentation of COVID 19 in our cohort. All biomarkers (D-Dimer, CRP, troponin, LDH and ferritin) except for the mean lowest white blood cells were found to have significant correlation (p<0.05) with worse COVID-19 disease outcomes. There was a sig-nificant association between the inflammatory biomarkers and the disease severity of COVID 19 patients (p<0.001). Patients with evidence of severe respiratory disease particularly who required mechanical ventilation (MV) had higher biomarkers, when compared to those with stable respiratory condition (p<0.001). Conclusion: Identifying biomarkers predicts outcome for COVID-19 patients and may significantly help in the management.