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Review 1: "Host genome analysis of structural variations by Optical Genome Mapping provides clinically valuable insights into genes implicated in critical immune, viral infection, and viral replication pathways in patients with severe COVID-19"

This preprint identifies associations between genomic structural variants and COVID-19 severity uses Optical Genome Mapping. Reviewers find the work unreliable due to control arm demographics and lack of experiments confirming causative, rather than correlative, association.

Published onFeb 23, 2021
Review 1: "Host genome analysis of structural variations by Optical Genome Mapping provides clinically valuable insights into genes implicated in critical immune, viral infection, and viral replication pathways in patients with severe COVID-19"
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key-enterThis Pub is a Review of
Host genome analysis of structural variations by Optical Genome Mapping provides clinically valuable insights into genes implicated in critical immune, viral infection, and viral replication pathways in patients with severe COVID-19

AbstractBackgroundThe varied clinical manifestations and outcomes in patients with SARS-CoV-2 infections implicate a role of host-genetics in the predisposition to disease severity. This is supported by evidence that is now emerging, where initial reports identify common risk factors and rare genetic variants associated with high risk for severe/ life-threatening COVID-19. Impressive global efforts have focused on either identifying common genetic factors utilizing short-read sequencing data in Genome-Wide Association Studies (GWAS) or whole-exome and genome studies to interrogate the human genome at the level of detecting single nucleotide variants (SNVs) and short indels. However, these studies lack the sensitivity to accurately detect several classes of variants, especially large structural variants (SVs) including copy number variants (CNVs), which account for a substantial proportion of variation among individuals. Thus, we investigated the host genomes of individuals with severe/life-threatening COVID-19 at the level of large SVs (500bp-Mb level) to identify events that might provide insight into the inter-individual clinical variability in clinical course and outcomes of COVID-19 patients.MethodsOptical genome mapping using Bionano’s Saphyr® system was performed on thirty-seven severely ill COVID-19 patients admitted to intensive care units (ICU). To extract candidate SVs, three distinct analyses were undertaken. First, an unbiased whole-genome analysis of SVs was performed to identify rare/unique genic SVs in these patients that did not appear in population datasets to determine candidate loci as decisive predisposing factors associated with severe COVID-19. Second, common SVs with a population frequency filter was interrogated for possible association with severe COVID-19 based on literature surveys. Third, genome-wide SV enrichment in severely ill patients versus the general population was investigated by calculating odds ratios to identify top-ranked genes/loci. Candidate SVs were confirmed using qPCR and an independent bioinformatics tool (FaNDOM).ResultsOur patient-centric investigation identified 11 SVs involving 38 genes implicated in three key host-viral interaction pathways: (1) innate immunity and inflammatory response, (2) airway resistance to pathogens, and (3) viral replication, spread, and RNA editing. These included seven rare/unique SVs (not present in the control dataset), identified in 24.3% (9/37) of patients, impacting up to 31 genes, of which STK26 and DPP4 are the most promising candidates. A duplication partially overlapping STK26 was corroborated with data showing upregulation of this gene in severely ill patients. Further, using a population frequency filter of less than 20% in the Bionano control dataset, four SVs involving seven genes were identified in 56.7% (21/37) of patients.ConclusionThis study is the first to systematically assess and highlight SVs’ potential role in the pathogenesis of COVID-19 severity. The genes implicated here identify novel SVs, especially STK26, and extend previous reports involving innate immunity and type I interferon response in the pathogenesis of COVID-19. Our study also shows that optical genome mapping can be a powerful tool to identify large SVs impacting disease outcomes with split survival and add valuable genomic information to the existing sequencing-based technology databases to understand the inter-individual variability associated with SARS-CoV-2 infections and COVID-19 mortality.

RR:C19 Evidence Scale rating by reviewer:

  • Potentially informative. The main claims made are not strongly justified by the methods and data, but may yield some insight. The results and conclusions of the study may resemble those from the hypothetical ideal study, but there is substantial room for doubt. Decision-makers should consider this evidence only with a thorough understanding of its weaknesses, alongside other evidence and theory. Decision-makers should not consider this actionable unless the weaknesses are clearly understood and there are other theory and evidence to further support it.


Strength of Evidence Rating Reasoning:

Potentially informative

This paper demonstrates the first speculation about the role of structural variants(SVs) in susceptibility to severe COVID-19 in 37 patients. However, gene expression studies should confirm the effect of SVs on gene expression level and be compared with asymptomatic or mild COVID-19 patients. Additionally, in vitro studies are needed using cells derived from patients, cell cultures, or animal models to study knock out and knock-in of those genes and study the effect on viral replication, interferon and cytokine levels, and severity of manifestations.


The overall conclusion of the investigators is that optical genome mapping can be utilized to discover large structural genome variants (> 500 bp) that impact COVID-19 severity and survival. While genome structural variants (SVs) are involved in neurodegenerative or cancer. This is the first time to study large structural variants as a cause of severe COVID-19. Next-generation sequencing can discover single nucleotide variants (SNVs) or small structural variants but won’t be able to discover large structural variants or repetitive elements variation in the human genome.

However, there are many limitations to this study. Investigators used a single arm to study SVs involved in severe COVID-19 without the inclusion of a control arm of mild or asymptomatic COVID-19 patients. The control arm in the study was a dataset of Bionano genomics but they did not tell us about the demographic characteristics of their control arm and whether they are healthy individuals or patients and if their number(267 controls) is sufficient to call the SVs unique. Hence, the inclusion of a control arm of mild or asymptomatic COVID-19 patients and studying structural variants in them is essential and this control arm should be of sufficient size to make statistically significant conclusions. Moreover, the number of patients is limited to 37 patients and the rare variants are found in only one or two patients. Family studies of SVs can be useful here especially in related family members with mild or asymptomatic COVID-19. To report a rare variant in a single patient to be the cause of a disease, you need rigorous lab validation to confirm the effect of this variant in susceptibility to severe viral infection. Validation of the effect of SVs was done only for a single gene(STK26) which proved that this gene is differentially expressed in severe COVID-19 patients. STK26 inhibits TRAF6( a gene essential for TLR3 and TLR7 signaling to produce inflammatory cytokines and interferon). Differential gene expression of STK26 was studied in a sample of 12 severe COVID-19 patients and a control of 11 asymptomatic or mild COVID-19 patients. Investigators did not provide demographics of those patients and if the 12 severe COVID-19 patients were drawn from the original sample of 37 patients from the main study.

Additionally, gene expression does not provide a causative implication. In vitro studies are needed to prove its implication in severe COVID-19 using cell culture or animal models knocking in and out this gene using different techniques as CRISPR or siRNA The higher expression of STK26 might be a consequence not a cause of severe COVID-19. Besides, for the common four SVs in candidate loci previously associated with severe COVID-19, they used a cutoff of 20%. There was no clear explanation for this cutoff. Besides, I expected a cutoff of 5% because critical (ICU admission) COVID-19 occurs in around 5% of the population hence 5% cutoff seems more reasonable. Finally, patients admitted to the study have different comorbidities that predispose to severe COVID-19 including diabetes mellitus(16 patients), hypertension(22 patients), chronic kidney disease(9 patients), and asthma(2 patients). Ideally, case report studies of monogenic causes of inborn errors of immunity recruit healthy patients because comorbidities are confounding factors for severe viral diseases.

Confirmation of the role of genes reported in this paper in susceptibility to severe COVID-19 is needed through in vitro studies using cells derived from patients, cell cultures, and animal studies using CRISPR,siRNA, or RNAseq technologies.

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