GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19.

Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte-macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

Development of New SNP Genotyping Assays to Discriminate the Omicron Variant of SARS-CoV-2.

The World Health Organization designated Omicron (B.1.1.529 lineage) of SARS-CoV-2 as a new variant of concern on November 26, 2021. The risk to public health conferred by the Omicron variant is still not completely clear, although its numerous gene mutations have raised concerns regarding its potential for increased transmissibility and immune escape. In this study, we describe the development of two single-nucleotide polymorphism genotyping assays targeting the G339D or T547K mutations of the spike protein to screen for the Omicron variant. A specificity test revealed that the two assays successfully discriminated the Omicron variant from the Delta and Alpha variants, each with a single nucleotide mismatch. In addition, a sensitivity test showed that the G339D and T547K assays detected at least 2.60 and 3.36 RNA copies of the Omicron variant, respectively, and 1.59 RNA copies of the Delta variant. These results demonstrate that both assays could be useful for detecting and discriminating the Omicron variant from other strains. In addition, because of the rapid and unpredictable evolution of SARS-CoV-2, combining our assays with previously developed assays for detecting other mutations may lead to a more accurate diagnostic system.

Study on SARS-CoV-2 strains in Iran reveals potential contribution of co-infection with and recombination between different strains to the emergence of new strains.

We aimed to describe SARS-CoV-2 strains in Iranians from nine distributed cities infected during two months expanding late 2020 and early 2021 by genotyping known informative single nucleotide in five PCR amplicons. Two variants associated with haplotype H1 (clade G) and nine additional variants associated with other haplotypes were genotyped, respectively, in RNA isolates of 244 and 85 individuals. The variants associated with the H1a (GR) and H1b (GH) haplotypes were most prevalent, indicating a significant change in infection pattern with passage of time. The most important findings were that recombinant genomes and co-infection, respectively, were surmised in 44.7% and 12.9% of the samples extensively genotyped. Partners of many of the recombinations were relatively common strains. Co-existing viruses were among those currently circulating in Iran. In addition to random mutations, co-infection with different existing strains and recombination between their genomes may significantly contribute to the emergence of new SARS-CoV-2 strains.

Development of a genotyping platform for SARS-CoV-2 variants using high-resolution melting analysis.

INTRODUCTION: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus causing coronavirus disease 2019 (COVID-19), has been expanding globally since late 2019. SARS-CoV-2, an RNA virus, has a genome sequence that can easily undergo mutation. Several mutated SARS-CoV-2 strains, including those with higher infectivity than others, have been reported. To reduce SARS-CoV-2 transmission, it is crucial to trace its infection sources. Here, we developed a simple, easy-to-use genotyping method to identify SARS-CoV-2 variants using a high-resolution melting (HRM) analysis. METHODS: We investigated five mutation sites, A23403G, G25563T, G26144T, T28144C, and G28882A, which are known strain determinants according to GISAID clades (L, S, V, G, GH, and GR). RESULTS: We first employed synthetic DNA fragments containing the five characteristic sites for HRM analysis. All sequences clearly differentiated wild-type from mutant viruses. We then confirmed that RNA fragments were suitable for HRM analysis following reverse transcription. Human saliva did not negatively affect the HRM analysis, which supports the absence of a matrix effect. CONCLUSIONS: Our results indicate that this HRM-based genotyping method can identify SARS-CoV-2 variants. This novel assay platform potentially paves the way for accurate and rapid identification of SARS-CoV-2 infection sources.

Angiotensin-converting enzyme-1 gene insertion/deletion polymorphism may be associated with COVID-19 clinical severity: a prospective cohort study.

BACKGROUND: Angiotensin-converting enzyme (ACE) insertion/deletion (I/D) polymorphism may play a role in the pathogenesis of coronavirus-19 disease (COVID-19). OBJECTIVES: Investigate the relationship between ACE I/D polymorphism and the clinical severity of COVID-19. DESIGN: Prospective cohort study. SETTING: Tertiary care hospital. PATIENTS AND METHODS: The study included COVID-19 patients with asymptomatic, mild, and severe disease with clinical data and whole blood samples collected from 1 April 2020 to 1 July 2020. ACE I/D genotypes were determined by polymerase chain reaction and agarose gel electrophoresis. MAIN OUTCOME MEASURE: ACE DD, DI and II genotypes frequencies. SAMPLE SIZE: 90 cases, 30 in each disease severity group. RESULTS: Age and the frequency of general comorbidity increased significantly from the asymptomatic disease group to the severe disease group. Advanced age, diabetes mellitus and presence of ischemic heart disease were independent risk factors for severe COVID-19 [OR and 95 % CI: 1.052 (1.021-1.083), 5.204 (1.006-26.892) and 5.922 (1.109-31.633), respectively]. The ACE II genotype was the dominant genotype (50%) in asymptomatic patients, while the DD genotype was the dominant genotype (63.3 %) in severe disease. The ACE II geno-type was protective against severe COVID-19 [OR and 95% CI: .323 (.112-.929)]. All nine patients (8.9%) who died had severe disease. CONCLUSIONS: The clinical severity of COVID-19 infection may be associated with the ACE I/D polymorphism. LIMITATIONS: Small sample size and single center. CONFLICT OF INTEREST: None.

Genotyping of the Major SARS-CoV-2 Clade by Short-Amplicon High-Resolution Melting (SA-HRM) Analysis.

The genome of the SARS-CoV-2 virus, the causal agent of the COVID-19 pandemic, has diverged due to multiple mutations since its emergence as a human pathogen in December 2019. Some mutations have defined several SARS-CoV-2 clades that seem to behave differently in terms of regional distribution and other biological features. Next-generation sequencing (NGS) approaches are used to classify the sequence variants in viruses from individual human patients. However, the cost and relative scarcity of NGS equipment and expertise in developing countries prevent studies aimed to associate specific clades and variants to clinical features and outcomes in such territories. As of March 2021, the GR clade and its derivatives, including the B.1.1.7 and B.1.1.28 variants, predominate worldwide. We implemented the post-PCR small-amplicon high-resolution melting analysis to genotype SARS-CoV-2 viruses isolated from the saliva of individual patients. This procedure was able to clearly distinguish two groups of samples of SARS-CoV-2-positive samples predicted, according to their melting profiles, to contain GR and non-GR viruses. This grouping of the samples was validated by means of amplification-refractory mutation system (ARMS) assay as well as Sanger sequencing.

Detecting SARS-CoV-2 variants with SNP genotyping.

Tracking genetic variations from positive SARS-CoV-2 samples yields crucial information about the number of variants circulating in an outbreak and the possible lines of transmission but sequencing every positive SARS-CoV-2 sample would be prohibitively costly for population-scale test and trace operations. Genotyping is a rapid, high-throughput and low-cost alternative for screening positive SARS-CoV-2 samples in many settings. We have designed a SNP identification pipeline to identify genetic variation using sequenced SARS-CoV-2 samples. Our pipeline identifies a minimal marker panel that can define distinct genotypes. To evaluate the system, we developed a genotyping panel to detect variants-identified from SARS-CoV-2 sequences surveyed between March and May 2020 and tested this on 50 stored qRT-PCR positive SARS-CoV-2 clinical samples that had been collected across the South West of the UK in April 2020. The 50 samples split into 15 distinct genotypes and there was a 61.9% probability that any two randomly chosen samples from our set of 50 would have a distinct genotype. In a high throughput laboratory, qRT-PCR positive samples pooled into 384-well plates could be screened with a marker panel at a cost of < £1.50 per sample. Our results demonstrate the usefulness of a SNP genotyping panel to provide a rapid, cost-effective, and reliable way to monitor SARS-CoV-2 variants circulating in an outbreak. Our analysis pipeline is publicly available and will allow for marker panels to be updated periodically as viral genotypes arise or disappear from circulation.

Array-based dynamic allele specific hybridization (Array-DASH): Optimization-free microarray processing for multiple simultaneous genomic assays.

We report proof-of-principle experiments regarding a dynamic microarray protocol enabling accurate and semi-quantitative DNA analysis for re-sequencing, fingerprinting and genotyping. Single-stranded target molecules hybridise to surface-bound probes during initial gradual cooling with high-fidelity. Real-time tracking of target denaturation (via fluorescence) during a 'dynamic' gradual heating phase permits 'melt-curve' analysis. The probe most closely matching the target sequence is identified based on the highest melting temperature. We demonstrated a >99% re-sequencing accuracy and a potential detection rate of 1% for SNPs. Experiments employing Hypericum ribosomal ITS regions and HIV genomes illustrated a reliable detection level of 5% plus simultaneous re-sequencing and genotyping. Such performance suggests a range of potential real-world applications involving rapid sequence interrogation, for example, in the Covid-19 pandemic. Guidance is offered towards the development of a commercial platform and dedicated software required to bring this technique into mainstream science.

Mutations on COVID-19 diagnostic targets.

Effective, sensitive, and reliable diagnostic reagents are of paramount importance for combating the ongoing coronavirus disease 2019 (COVID-19) pandemic when there is neither a preventive vaccine nor a specific drug available for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It will cause a large number of false-positive and false-negative tests if currently used diagnostic reagents are undermined. Based on genotyping of 31,421 SARS-CoV-2 genome samples collected up to July 23, 2020, we reveal that essentially all of the current COVID-19 diagnostic targets have undergone mutations. We further show that SARS-CoV-2 has the most mutations on the targets of various nucleocapsid (N) gene primers and probes, which have been widely used around the world to diagnose COVID-19. To understand whether SARS-CoV-2 genes have mutated unevenly, we have computed the mutation rate and mutation h-index of all SARS-CoV-2 genes, indicating that the N gene is one of the most non-conservative genes in the SARS-CoV-2 genome. We show that due to human immune response induced APOBEC mRNA (C > T) editing, diagnostic targets should also be selected to avoid cytidines. Our findings might enable optimally selecting the conservative SARS-CoV-2 genes and proteins for the design and development of COVID-19 diagnostic reagents, prophylactic vaccines, and therapeutic medicines. AVAILABILITY: Interactive real-time online Mutation Tracker.

Angiotensin-converting enzymes (ACE, ACE2) gene variants and COVID-19 outcome.

The Angiotensin system is implicated in the pathogenesis of COVID-19. First, ACE2 is the cellular receptor for SARS-CoV-2, and expression of the ACE2 gene could regulate the individuals susceptibility to infection. In addition, the balance between ACE1 and ACE2 activity has been implicated in the pathogenesis of respiratory diseases and could play a role in the severity of COVID-19. Functional ACE1/ACE2 gene polymorphisms have been associated with the risk of cardiovascular and pulmonary diseases, and could thus also contribute to the outcome of COVID-19. We studied 204 COVID-19 patients (137 non-severe and 67 severe-ICU cases) and 536 age-matched controls. The ACE1 insertion/deletion and ACE2 rs2285666 polymorphism were determined. Variables frequencies were compared between the groups by logistic regression. We also sequenced the ACE2 coding nucleotides in a group of patients. Severe COVID-19 was associated with hypertension male gender (p < 0.001), hypertension (p = 0.006), hypercholesterolaemia (p = 0.046), and the ACE1-DD genotype (p = 0.049). In the multiple logistic regression hypertension (p = 0.02, OR = 2.26, 95%CI = 1.12-4.63) and male gender (p = 0.002; OR = 3.15, 95%CI = 1.56-6.66) remained as independent significant predictors of severity. The ACE2 polymorphism was not associated with the disease outcome. The ACE2 sequencing showed no coding sequence variants that could explain an increased risk of developing COVID-19. In conclusion, an adverse outcome of COVID-19 was associated with male gender, hypertension, hypercholesterolemia and the ACE1 genotype. Our work suggested that the ACE1-I/D might influence COVID-19 severity, but the effect was dependent on the hypertensive status. This result requires further validation in other large cohorts.

Genotyping coronavirus SARS-CoV-2: methods and implications.

The emerging global infectious COVID-19 disease by novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) presents critical threats to global public health and the economy since it was identified in late December 2019 in China. The virus has gone through various pathways of evolution. To understand the evolution and transmission of SARS-CoV-2, genotyping of virus isolates is of great importance. This study presents an accurate method for effectively genotyping SARS-CoV-2 viruses using complete genomes. The method employs the multiple sequence alignments of the genome isolates with the SARS-CoV-2 reference genome. The single-nucleotide polymorphism (SNP) genotypes are then measured by Jaccard distances to track the relationship of virus isolates. The genotyping analysis of SARS-CoV-2 isolates from the globe reveals that specific multiple mutations are the predominated mutation type during the current epidemic. The proposed method serves an effective tool for monitoring and tracking the epidemic of pathogenic viruses in their global and local genetic variations. The genotyping analysis shows that the genes encoding the S proteins and RNA polymerase, RNA primase, and nucleoprotein, undergo frequent mutations. These mutations are critical for vaccine development in disease control.