An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge

BACKGROUND: There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data was donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Facing the Challenge of Genetic Counselors\u27 Need for Rapid Continuing Education About Genomic Technologies

The last couple of decades have seen the rapid advancement of genomic technologies (GT) and their equally rapid adoption into clinical testing. Regardless of specialty, all genetic counselors are unified by the fundamental goal to aid in diagnosing patient\u27s genetic disease underscoring the importance for genetic counselors to maintain an in-depth understanding of GT. The National Society of Genetic Counselors’ (NSGC) GT Special Interest Group conducted an online survey of NSGC members to assess current genomic technologies knowledge gaps. A total of 171 individuals from a variety of primary work settings completed the survey sufficiently to be included in the analysis. The majority of respondents received their degree in genetic counseling in more recent years (2000–2015). On average across all technologies, \u3e70% of respondents deemed knowledge of GTs as important for successful job performance, 55% responded that additional job training in GTs is needed to successfully perform job functions, and only 28% responded that graduate training in GTs was good. Overall, the data show that participating genetic counselors perceive that their knowledge of GTs is inadequate while it is a key component of their jobs. These results have implications both for training programs and for continuing education efforts. These data can be used as a starting point for additional research into GT educational needs of genetic counselors

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3–7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease

Assessment of 2q23.1 Microdeletion Syndrome Implicates MBD5 as a Single Causal Locus of Intellectual Disability, Epilepsy, and Autism Spectrum Disorder

Persons with neurodevelopmental disorders or autism spectrum disorder (ASD) often harbor chromosomal microdeletions, yet the individual genetic contributors within these regions have not been systematically evaluated. We established a consortium of clinical diagnostic and research laboratories to accumulate a large cohort with genetic alterations of chromosomal region 2q23.1 and acquired 65 subjects with microdeletion or translocation. We sequenced translocation breakpoints; aligned microdeletions to determine the critical region; assessed effects on mRNA expression; and examined medical records, photos, and clinical evaluations. We identified a single gene, methyl-CpG-binding domain 5 (MBD5), as the only locus that defined the critical region. Partial or complete deletion of MBD5 was associated with haploinsufficiency of mRNA expression, intellectual disability, epilepsy, and autistic features. Fourteen alterations, including partial deletions of noncoding regions not typically captured or considered pathogenic by current diagnostic screening, disrupted MBD5 alone. Expression profiles and clinical characteristics were largely indistinguishable between MBD5-specific alteration and deletion of the entire 2q23.1 interval. No copy-number alterations of MBD5 were observed in 7878 controls, suggesting MBD5 alterations are highly penetrant. We surveyed MBD5 coding variations among 747 ASD subjects compared to 2043 non-ASD subjects analyzed by whole-exome sequencing and detected an association with a highly conserved methyl-CpG-binding domain missense variant, p.79Gly>Glu (c.236G>A) (p = 0.012). These results suggest that genetic alterations of MBD5 cause features of 2q23.1 microdeletion syndrome and that this epigenetic regulator significantly contributes to ASD risk, warranting further consideration in research and clinical diagnostic screening and highlighting the importance of chromatin remodeling in the etiology of these complex disorders