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.

Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative.

Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

Uncovering the burden of hidden ciliopathies in the 100 000 Genomes Project: a reverse phenotyping approach.

BACKGROUND: The 100 000 Genomes Project (100K) recruited National Health Service patients with eligible rare diseases and cancer between 2016 and 2018. PanelApp virtual gene panels were applied to whole genome sequencing data according to Human Phenotyping Ontology (HPO) terms entered by recruiting clinicians to guide focused analysis. METHODS: We developed a reverse phenotyping strategy to identify 100K participants with pathogenic variants in nine prioritised disease genes (BBS1, BBS10, ALMS1, OFD1, DYNC2H1, WDR34, NPHP1, TMEM67, CEP290), representative of the full phenotypic spectrum of multisystemic primary ciliopathies. We mapped genotype data 'backwards' onto available clinical data to assess potential matches against phenotypes. Participants with novel molecular diagnoses and key clinical features compatible with the identified disease gene were reported to recruiting clinicians. RESULTS: We identified 62 reportable molecular diagnoses with variants in these nine ciliopathy genes. Forty-four have been reported by 100K, 5 were previously unreported and 13 are new diagnoses. We identified 11 participants with unreportable, novel molecular diagnoses, who lacked key clinical features to justify reporting to recruiting clinicians. Two participants had likely pathogenic structural variants and one a deep intronic predicted splice variant. These variants would not be prioritised for review by standard 100K diagnostic pipelines. CONCLUSION: Reverse phenotyping improves the rate of successful molecular diagnosis for unsolved 100K participants with primary ciliopathies. Previous analyses likely missed these diagnoses because incomplete HPO term entry led to incorrect gene panel choice, meaning that pathogenic variants were not prioritised. Better phenotyping data are therefore essential for accurate variant interpretation and improved patient benefit.

Molecular diagnoses in the congenital malformations caused by ciliopathies cohort of the 100,000 Genomes Project.

BACKGROUND: Primary ciliopathies represent a group of inherited disorders due to defects in the primary cilium, the 'cell's antenna'. The 100,000 Genomes Project was launched in 2012 by Genomics England (GEL), recruiting National Health Service (NHS) patients with eligible rare diseases and cancer. Sequence data were linked to Human Phenotype Ontology (HPO) terms entered by recruiting clinicians. METHODS: Eighty-three prescreened probands were recruited to the 100,000 Genomes Project suspected to have congenital malformations caused by ciliopathies in the following disease categories: Bardet-Biedl syndrome (n=45), Joubert syndrome (n=14) and 'Rare Multisystem Ciliopathy Disorders' (n=24). We implemented a bespoke variant filtering and analysis strategy to improve molecular diagnostic rates for these participants. RESULTS: We determined a research molecular diagnosis for n=43/83 (51.8%) probands. This is 19.3% higher than previously reported by GEL (n=27/83 (32.5%)). A high proportion of diagnoses are due to variants in non-ciliopathy disease genes (n=19/43, 44.2%) which may reflect difficulties in clinical recognition of ciliopathies. n=11/83 probands (13.3%) had at least one causative variant outside the tiers 1 and 2 variant prioritisation categories (GEL's automated triaging procedure), which would not be reviewed in standard 100,000 Genomes Project diagnostic strategies. These include four structural variants and three predicted to cause non-canonical splicing defects. Two unrelated participants have biallelic likely pathogenic variants in LRRC45, a putative novel ciliopathy disease gene. CONCLUSION: These data illustrate the power of linking large-scale genome sequence to phenotype information. They demonstrate the value of research collaborations in order to maximise interpretation of genomic data.

A Unique Mitochondrial Gene Block Inversion in Antarctic Trematomin Fishes: A Cautionary Tale.

Many Antarctic notothenioid fishes have major rearrangements in their mitochondrial (mt) genomes. Here, we report the complete mt genomes of 3 trematomin notothenioids: the bald notothen (Trematomus (Pagothenia) borchgrevinki), the spotted notothen (T. nicolai), and the emerald notothen (T. bernacchii). The 3 mt genomes were sequenced using next-generation Illumina technology, and the assemblies verified by Sanger sequencing. When compared with the canonical mt gene order of the Antarctic silverfish (Pleuragramma antarctica), we found a large gene inversion in the 3 trematomin mt genomes that included tRNAIle, ND1, tRNALeu2, 16S, tRNAVal, 12S, tRNAPhe, and the control region. The trematomin mt genomes contained 3 intergenic spacers, which are thought to be the remnants of previous gene and control region duplications. All control regions included the characteristic conserved regulatory sequence motifs. Although short-read next-generation DNA sequencing technology has allowed the rapid and cost-effective sequencing of a large number of complete mt genomes, it is essential in all cases to verify the assembly in order to prevent the publication and use of erroneous data.

Evaluation of variable flip angle, MOLLI, SASHA, and IR-SNAPSHOT pulse sequences for T1 relaxometry and extracellular volume imaging of the pancreas and liver.

PURPOSE: Compare fourT1-mapping pulse sequences for T1 relaxometry and extracellular volume (ECV) fraction of the pancreas and liver MATERIALS AND METHODS: In vitro phase of this prospective study was performed on a T1 phantom, followed by imaging 22 patients. Variable flip angle (VFA), modified Look-Locker inversion recovery (MOLLI), prototype saturation recovery single-shot acquisition (SASHA), and prototype inversion recovery (IR-SNAPSHOT) pulse sequences were used to obtain T1 and ECV maps on the same 1.5 T MR scanner using the same imaging protocol. RESULTS: In vitro tests showed almost perfect precision of MOLLI (ρc = 0.9998), SASHA (ρc = 0.9985), and IR-SNAPSHOT (ρc = 0.9976), while VFA showed relatively less, however, substantial precision (ρc = 0.9862). Results of patient scans showed similar ECV fraction of the liver (p = 0.08), pancreas (p = 0.43), and T1 of the liver (p = 0.08) with all pulse sequences. T1 of the pancreas with MOLLI, SASHA, and IR-SNAPSHOT was statistically similar (p > 0.05). CONCLUSION: MOLLI, SASHA, and IR-SNAPSHOT provided almost perfect in vitro precision and similar T1 during in vivo scans. Similar ECV fractions of the liver and pancreas were obtained with all sequences. More refinement of pulse sequences to provide sufficient spatial coverage in one breath hold together with high precision would be desirable in abdominal imaging.