Erratum: Author Correction: Identification of genes required for eye development by high-throughput screening of mouse knockouts.

[This corrects the article DOI: 10.1038/s42003-018-0226-0.]

A large scale hearing loss screen reveals an extensive unexplored genetic landscape for auditory dysfunction

The developmental and physiological complexity of the auditory system is likely reflected in the underlying set of genes involved in auditory function. In humans, over 150 non-syndromic loci have been identified, and there are more than 400 human genetic syndromes with a hearing loss component. Over 100 non-syndromic hearing loss genes have been identified in mouse and human, but we remain ignorant of the full extent of the genetic landscape involved in auditory dysfunction. As part of the International Mouse Phenotyping Consortium, we undertook a hearing loss screen in a cohort of 3006 mouse knockout strains. In total, we identify 67 candidate hearing loss genes. We detect known hearing loss genes, but the vast majority, 52, of the candidate genes were novel. Our analysis reveals a large and unexplored genetic landscape involved with auditory function

Identification of genes required for eye development by high-throughput screening of mouse knockouts.

Despite advances in next generation sequencing technologies, determining the genetic basis of ocular disease remains a major challenge due to the limited access and prohibitive cost of human forward genetics. Thus, less than 4,000 genes currently have available phenotype information for any organ system. Here we report the ophthalmic findings from the International Mouse Phenotyping Consortium, a large-scale functional genetic screen with the goal of generating and phenotyping a null mutant for every mouse gene. Of 4364 genes evaluated, 347 were identified to influence ocular phenotypes, 75% of which are entirely novel in ocular pathology. This discovery greatly increases the current number of genes known to contribute to ophthalmic disease, and it is likely that many of the genes will subsequently prove to be important in human ocular development and disease

Identification of genes required for eye development by high-throughput screening of mouse knockouts

International audienc

Identification of clinical features associated with mortality in COVID-19 patients

Summary Background To prevent infectious diseases, it is necessary to understand how they are spread and their clinical features. Early identification of risk factors and clinical features is needed to identify critically ill patients, provide suitable treatments, and prevent mortality. Methods We conducted a prospective study on COVID-19 patients referred to a tertiary hospital in Iran between March and November 2020. Of the 3008 patients (mean age 59.3±18.7 years, range 1 to 100 years), 1324 were women. We investigated COVID-19 related mortality and its association with clinical features including headache, chest pain, symptoms on CT, hospitalization, time to infection, history of neurological disorders, having a single or multiple risk factors, fever, myalgia, dizziness, seizure, abdominal pain, nausea, vomiting, diarrhoea and anorexia. Findings There was a significant association between COVID-19 mortality and old age, headache, chest pain, respiratory distress, low respiratory rate, oxygen saturation less than 93%, need for a mechanical ventilator, having symptoms on CT, hospitalization, time to infection, history of hypertension, neurological disorders, cardiovascular diseases and having a risk factor or multiple risk factors. In contrast, there was no significant association between mortality and gender, fever, myalgia, dizziness, seizure, abdominal pain, nausea, vomiting, diarrhoea and anorexia. Interpretation Our results might help identify early symptoms related to COVID-19 and better manage patients clinically

Factors associated with mortality in hospitalized cardiovascular disease patients infected with COVID-19

INTRODUCTION: To reduce mortality in hospitalized patients with COVID-19 and cardiovascular disease (CVD), it is necessary to understand the relationship between patient's symptoms, risk factors, and comorbidities with their mortality rate. To the best of our knowledge, this paper is the first which take into account the determinants like risk factors, symptoms, and comorbidities leading to mortality in CVD patients who are hospitalized with COVID-19. METHODS: This study was conducted on 660 hospitalized patients with CVD and COVID-19 recruited between January 2020 and January 2021 in Iran. All patients were diagnosed with the previous history of CVD like angina, myocardial infarction, heart failure, cardiomyopathy, abnormal heart rhythms, and congenital heart disease before they were hospitalized for COVID-19. We collected data on patient's signs and symptoms, clinical and paraclinical examinations, and any underlying comorbidities. t test was used to determine the significant difference between the two deceased and alive groups. In addition, the relation between pairs of symptoms and pairs of comorbidities has been determined via correlation computation. RESULTS: Our findings suggest that signs and symptoms such as fever, cough, myalgia, chest pain, chills, abdominal pain, nausea, vomiting, diarrhea, and anorexia had no impact on patients' mortality. There was a significant correlation between COVID-19 cardiovascular patients' mortality rate and symptoms such as headache, loss of consciousness (LOC), oxygen saturation less than 93%, and need for mechanical ventilation. CONCLUSIONS: Our results might help physicians identify early symptoms, comorbidities, and risk factors related to mortality in CVD patients hospitalized for COVID-19

Extensive identification of genes involved in congenital and structural heart disorders and cardiomyopathy

Clinical presentation of congenital heart disease is heterogeneous, making identification of the disease-causing genes and their genetic pathways and mechanisms of action challenging. By using in vivo electrocardiography, transthoracic echocardiography and microcomputed tomography imaging to screen 3,894 single-gene-null mouse lines for structural and functional cardiac abnormalities, here we identify 705 lines with cardiac arrhythmia, myocardial hypertrophy and/or ventricular dilation. Among these 705 genes, 486 have not been previously associated with cardiac dysfunction in humans, and some of them represent variants of unknown relevance (VUR). Mice with mutations in Casz1, Dnajc18, Pde4dip, Rnf38 or Tmem161b genes show developmental cardiac structural abnormalities, with their human orthologs being categorized as VUR. Using UK Biobank data, we validate the importance of the DNAJC18 gene for cardiac homeostasis by showing that its loss of function is associated with altered left ventricular systolic function. Our results identify hundreds of previously unappreciated genes with potential function in congenital heart disease and suggest causal function of five VUR in congenital heart disease