Proteome-wide Mendelian randomization implicates nephronectin as an actionable mediator of the effect of obesity on COVID-19 severity

Obesity is a major risk factor for COVID-19 severity; however, the underlying mechanism is not fully understood. Considering that obesity influences the human plasma proteome, we sought to identify circulating proteins mediating the effects of obesity on COVID-19 severity. We first screened 4,907 plasma proteins to identify proteins influenced by body mass index (BMI) using Mendelian randomization (MR). This yielded 1,216 proteins, whose effects on COVID-19 severity were assessed, again using MR. This two-step approach identified nephronectin (NPNT), for which a one standard deviation increase was associated with severe COVID-19 (odds ratio = 1.71, 95% CI: 1.45-2.02, P = 1.63 x 10-10). Colocalization analyses indicated that an NPNT splice isoform drove this effect. Overall, NPNT mediates 3.7% of the total effect of BMI on severe COVID-19. Finally, we found that decreasing body fat mass and increasing fat-free mass can lower NPNT levels and thus may improve COVID-19 outcomes. These findings provide actionable insights into how obesity influences COVID-19 severity.

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. Author SummaryCOVID-19 clinical outcomes vary immensely, but a patients genetic make-up is an important determinant of how they will fare against the virus. While many genetic variants commonly found in the populations were previously found to be contributing to more severe disease by the COVID-19 Host Genetics Initiative, it isnt clear if more rare variants found in less individuals could also play a role. This is important because genetic variants with the largest impact on COVID-19 severity are expected to be rarely found in the population, and these rare variants require different technologies to be studies (usually whole-exome or whole-genome sequencing). Here, we combined sequencing results from 21 cohorts across 12 countries to perform a rare variant association study. In an analysis comprising 5,085 participants with severe COVID-19 and 571,737 controls, we found that the gene for toll-like receptor 7 (TLR7) on chromosome X was an important determinant of severe COVID-19. Importantly, despite being found on a sex chromosome, this observation was consistent across both sexes.

Remdesivir for the Treatment of COVID-19: An Updated Systematic Review and Meta-Analysis

BackgroundThe benefits of remdesivir in the treatment of hospitalized patients with Covid-19 remain debated with the National Institutes of Health and the World Health Organization providing contradictory recommendations for and against use. MethodsWe performed a systematic review of randomized controlled trials (RCTs) of remdesivir for the treatment of hospitalized patients with COVID-19. The primary outcome was mortality, stratified by oxygen use (none, supplemental oxygen without mechanical ventilation, and mechanical ventilation). We conducted a frequentist random effects meta-analysis on the risk ratio (RR) scale and, to better contextualize the probabilistic benefits, we also performed a bayesian random effects meta-analysis on the risk difference scale. ResultsWe identified 8 randomized trials, totaling 9157 participants. The RR for mortality comparing remdesivir versus control was 0.71 (95% confidence interval [CI] 0.42-1.22; I2=0.0%) in the patients who did not require supplemental oxygen; 0.83 (95%CI 0.73-0.95; I2=0.0%) for nonventilated patients requiring oxygen; and 1.19 (95%CI 0.98-1.44 I2=0.0%) in the setting of mechanical ventilation. Using neutral priors, the probabilities that remdesivir reduces mortality were 74.7%, 96.9% and 8.9%, respectively. The probability that remdesivir reduced mortality by more than 1% was 88.1% for nonventilated patients requiring oxygen. ConclusionBased on this meta-analysis, there is a high probability that remdesivir reduces mortality for nonventilated patients with COVID-19 requiring supplemental oxygen therapy.

Circulating proteins to predict adverse COVID-19 outcomes

Predicting COVID-19 severity is difficult, and the biological pathways involved are not fully understood. To approach this problem, we measured 4,701 circulating human protein abundances in two independent cohorts totaling 986 individuals. We then trained prediction models including protein abundances and clinical risk factors to predict adverse COVID-19 outcomes in 417 subjects and tested these models in a separate cohort of 569 individuals. For severe COVID-19, a baseline model including age and sex provided an area under the receiver operator curve (AUC) of 65% in the test cohort. Selecting 92 proteins from the 4,701 unique protein abundances improved the AUC to 88% in the training cohort, which remained relatively stable in the testing cohort at 86%, suggesting good generalizability. Proteins selected from different adverse COVID-19 outcomes were enriched for cytokine and cytokine receptors, but more than half of the enriched pathways were not immune-related. Taken together, these findings suggest that circulating proteins measured at early stages of disease progression are reasonably accurate predictors of adverse COVID-19 outcomes. Further research is needed to understand how to incorporate protein measurement into clinical care.

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity.

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole exome sequencing data of about 4,000 SARS-CoV-2-positive individuals were used to define an interpretable machine learning model for predicting COVID-19 severity. Firstly, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthly, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

Integrated immunovirological profiling validates plasma SARS-CoV-2 RNA as an early predictor of COVID-19 mortality

Despite advances in COVID-19 management, it is unclear how to recognize patients who evolve towards death. This would allow for better risk stratification and targeting for early interventions. However, the explosive increase in correlates of COVID-19 severity complicates biomarker prioritisation. To identify early biological predictors of mortality, we performed an immunovirological assessment (SARS-CoV-2 viral RNA, cytokines and tissue injury markers, antibody responses) on plasma samples collected from 144 hospitalised COVID-19 patients 11 days after symptom onset and used to test models predicting mortality within 60 days of symptom onset. In the discovery cohort (n=61, 13 fatalities), high SARS-CoV-2 vRNA, low RBD-specific IgG levels, low SARS-CoV-2-specific antibody-dependent cellular cytotoxicity, and elevated levels of several cytokines and lung injury markers were strongly associated with increased mortality in the entire cohort and the subgroup on mechanical ventilation. Model selection revealed that a three-variable model of vRNA, age and sex was very robust at identifying patients who will succumb to COVID-19 (AUC=0.86, adjusted HR for log-transformed vRNA=3.5; 95% CI: 2.0-6.0). This model remained robust in an independent validation cohort (n=83, AUC=0.85). Quantification of plasma SARS-CoV-2 RNA can help understand the heterogeneity of disease trajectories and identify patients who may benefit from new therapies.

Alternative splicing of OAS1 alters the risk for severe COVID-19

A locus containing OAS1/2/3 has been identified as a risk locus for severe COVID-19 among Europeans ancestry individuals, with a protective haplotype of [~]75 kilobases derived from Neanderthals. Here, we show that among several potentially causal variants at this locus, a splice variant of OAS1 occurs in people of African ancestry independently of the Neanderthal haplotype and confers protection against COVID-19 of a magnitude similar to that seen in individuals without African ancestry.

Age-dependent impact of the major common genetic risk factor for COVID-19 on severity and mortality

BackgroundThere is considerable variability in COVID-19 outcomes amongst younger adults--and some of this variation may be due to genetic predisposition. We characterized the clinical implications of the major genetic risk factor for COVID-19 severity, and its age-dependent effect, using individual-level data in a large international multi-centre consortium. MethodThe major common COVID-19 genetic risk factor is a chromosome 3 locus, tagged by the marker rs10490770. We combined individual level data for 13,424 COVID-19 positive patients (N=6,689 hospitalized) from 17 cohorts in nine countries to assess the association of this genetic marker with mortality, COVID-19-related complications and laboratory values. We next examined if the magnitude of these associations varied by age and were independent from known clinical COVID-19 risk factors. FindingsWe found that rs10490770 risk allele carriers experienced an increased risk of all-cause mortality (hazard ratio [HR] 1{middle dot}4, 95% confidence interval [CI] 1{middle dot}2-1{middle dot}6) and COVID-19 related mortality (HR 1{middle dot}5, 95%CI 1{middle dot}3-1{middle dot}8). Risk allele carriers had increased odds of several COVID-19 complications: severe respiratory failure (odds ratio [OR] 2{middle dot}0, 95%CI 1{middle dot}6-2{middle dot}6), venous thromboembolism (OR 1{middle dot}7, 95%CI 1{middle dot}2-2{middle dot}4), and hepatic injury (OR 1{middle dot}6, 95%CI 1{middle dot}2-2{middle dot}0). Risk allele carriers [≤] 60 years had higher odds of death or severe respiratory failure (OR 2{middle dot}6, 95%CI 1{middle dot}8-3{middle dot}9) compared to those > 60 years OR 1{middle dot}5 (95%CI 1{middle dot}3-1{middle dot}9, interaction p-value=0{middle dot}04). Amongst individuals [≤] 60 years who died or experienced severe respiratory COVID-19 outcome, we found that 31{middle dot}8% (95%CI 27{middle dot}6-36{middle dot}2) were risk variant carriers, compared to 13{middle dot}9% (95%CI 12{middle dot}6-15{middle dot}2%) of those not experiencing these outcomes. Prediction of death or severe respiratory failure among those [≤] 60 years improved when including the risk allele (AUC 0{middle dot}82 vs 0{middle dot}84, p=0{middle dot}016) and the prediction ability of rs10490770 risk allele was similar to, or better than, most established clinical risk factors. InterpretationThe major common COVID-19 risk locus on chromosome 3 is associated with increased risks of morbidity and mortality--and these are more pronounced amongst individuals [≤] 60 years. The effect on COVID-19 severity was similar to, or larger than most established risk factors, suggesting potential implications for clinical risk management. FundingFunding was obtained by each of the participating cohorts individually.

Failure to replicate the association of rare loss-of-function variants in type I IFN immunity genes with severe COVID-19

A recent report found that rare predicted loss-of-function (pLOF) variants across 13 candidate genes in TLR3- and IRF7-dependent type I IFN pathways explain up to 3.5% of severe COVID-19 cases. We performed whole-exome or whole-genome sequencing of 1,934 COVID-19 cases (713 with severe and 1,221 with mild disease) and 15,251 ancestry-matched population controls across four independent COVID-19 biobanks. We then tested if rare pLOF variants in these 13 genes were associated with severe COVID-19. We identified only one rare pLOF mutation across these genes amongst 713 cases with severe COVID-19 and observed no enrichment of pLOFs in severe cases compared to population controls or mild COVID-19 cases. We find no evidence of association of rare loss-of-function variants in the proposed 13 candidate genes with severe COVID-19 outcomes.

Genetic association analysis of SARS-CoV-2 infection in 455,838 UK Biobank participants

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease-19 (COVID-19), a respiratory illness that can result in hospitalization or death. We investigated associations between rare genetic variants and seven COVID-19 outcomes in 543,213 individuals, including 8,248 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome-wide or when specifically focusing on (i) 14 interferon pathway genes in which rare deleterious variants have been reported in severe COVID-19 patients; (ii) 167 genes located in COVID-19 GWAS risk loci; or (iii) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, with results publicly browsable at https://rgc-covid19.regeneron.com.

Circulating Proteins Influencing COVID-19 Susceptibility and Severity: a Mendelian Randomization Study

Proteins detectable in peripheral blood may influence COVID-19 susceptibility or severity. However, understanding which circulating proteins are etiologically involved is difficult because their levels may be influenced by COVID-19 itself and are also subject to confounding factors. To identify circulating proteins influencing COVID-19 susceptibility and severity we undertook a large-scale two-sample Mendelian randomization (MR) study, since this study design can rapidly scan hundreds of circulating proteins and reduces bias due to reverse causation and confounding. We identified genetic determinants of 931 circulating proteins in 28,461 SARS-CoV-2 uninfected individuals, retaining only single nucleotide polymorphism near the gene encoding the circulating protein. We found that a standard deviation increase in OAS1 levels was associated with reduced COVID-19 death or ventilation (N = 4,336 cases / 623,902 controls; OR = 0.54, P = 7x10-8), COVID-19 hospitalization (N = 6,406 / 902,088; OR = 0.61, P = 8x10-8) and COVID-19 susceptibility (N = 14,134 / 1,284,876; OR = 0.78, P = 8x10-6). Results were consistent in multiple sensitivity analyses. We then measured OAS1 levels in 504 patients with repeated plasma samples (N=1039) with different COVID-19 outcomes and found that increased OAS1 levels in a non-infectious state were associated with protection against very severe COVID-19, hospitalization and susceptibility. Further analyses suggested that a Neanderthal isoform of OAS1 affords this protection. Thus, evidence from MR and a case-control study supported a protective role for OAS1 in COVID-19 outcomes. Available medicines, such as phosphodiesterase-12 inhibitors, increase OAS1 and could be explored for their effect on COVID-19 susceptibility and severity.

Vitamin D and Covid-19 Susceptibility and Severity: a Mendelian Randomization Study

BackgroundIncreased vitamin D levels, as reflected by 25OHD measurements, have been proposed to protect against COVID-19 disease based on in-vitro, observational, and ecological studies. However, vitamin D levels are associated with many confounding variables and thus associations described to date may not be causal. Vitamin D Mendelian randomization (MR) studies have provided results that are concordant with large-scale vitamin D randomized trials. Here, we used two-sample MR to assess evidence supporting a causal effect of circulating 25OHD levels on COVID-19 susceptibility and severity. Methods and findingsGenetic variants strongly associated with 25OHD levels in a genome-wide association study (GWAS) of 443,734 participants of European ancestry (including 401,460 from the UK Biobank) were used as instrumental variables. GWASs of COVID-19 susceptibility, hospitalization, and severe disease from the COVID-19 Host Genetics Initiative were used as outcome GWASs. These included up to 14,134 individuals with COVID-19, and 1,284,876 without COVID-19, from 11 countries. SARS-CoV-2 positivity was determined by laboratory testing or medical chart review. Population controls without COVID-19 were also included in the control groups for all outcomes, including hospitalization and severe disease. Analyses were restricted to individuals of European descent when possible. Using inverse-weighted MR, genetically increased 25OHD levels by one standard deviation on the logarithmic scale had no clear association with COVID-19 susceptibility (OR = 0.97; 95% CI: 0.95, 1.10; P=0.61), hospitalization (OR = 1.11; 95% CI: 0.91, 1.35; P=0.30), and severe disease (OR = 0.93; 95% CI: 0.73, 1.17; P=0.53). We used an additional 6 meta-analytic methods, as well as sensitivity analyses after removal of variants at risk of horizontal pleiotropy and obtained similar results. These results may be limited by weak instrument bias in some analyses. Further, our results do not apply to individuals with vitamin D deficiency. ConclusionIn this two-sample MR study, we did not observe evidence to support an association between 25OHD levels and COVID-19 susceptibility, severity, or hospitalization. Hence, vitamin D supplementation as a mean of protecting against worsened COVID-19 outcomes is not supported by genetic evidence. Other therapeutic or preventative avenues should be given higher priority for COVID-19 randomized controlled trials. Author SummaryO_LIWhy was this study done? - Vitamin D levels have been associated with COVID-19 outcomes in multiple observational studies, though confounders are likely to bias these associations. - By using genetic instruments which limit such confounding, Mendelian randomization studies have consistently obtained results concordant with vitamin D supplementation randomized trials. This provides rationale to undertake vitamin D Mendelian randomization studies for COVID-19 outcomes. C_LIO_LIWhat did the researchers do and find? - We used the genetic variants obtained from the largest consortium of COVID-19 cases and controls, and the largest study on genetic determinants of vitamin D levels. We used Mendelian randomization to estimate the effect of increased vitamin D on COVID-19 outcomes, while limiting confounding. - In multiple analyses, our results consistently showed no evidence for an association between genetically predicted vitamin D levels and COVID-19 susceptibility, hospitalization, or severe disease. C_LIO_LIWhat do these findings mean? - Vitamin D is a highly confounded variable, and traditional observational studies are at high risk of biased estimates. - We did not find evidence that vitamin D supplementation would improve COVID-19 outcomes. - Given Mendelian randomizations past track-record of anticipating the results of vitamin D randomized controlled trials, other therapeutic and preventative avenues should be prioritized for COVID-19 trials. C_LI