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

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 5,048 severe disease cases and 571,009 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). 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.

An Australian Conundrum: Genomic Technology, Data, and the COVIDSafe App (preprint)

This paper examines the difficulties that have arisen in Australia in the use of its contact-tracing app. We examine the privacy implications around the use of the app, the wider economic imperative, and the balancing of those concerns against the health threat of the COVID-19 pandemic. We posit that default options are superior in times of emergency and rather than begging for the adoption of lifesaving technology, we suggest that the evidence gathered by behavioral economists provides an apposite and powerful alternative worthy of consideration.

Circulating proteins to predict adverse COVID-19 outcomes (preprint)

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.

Redeveloping Courses for Online Learning: A Short Paper for Sharing Ideas (preprint)

This document sets out guidance on the re-design of courses from face-to-face teaching to online asynchronous and synchronous1 learning in response to circumstances of COVID-19. We created these guidelines to help us in our thinking before we began to re-develop the courses we lead. In our case, these courses were hosted on the Moodle VLE. We had to keep our redesign do-able. We knew it would involve significant amounts of work, but by focusing effort on the points below prior to undertaking the redesign, we were able to redevelop existing courses effectively, putting students and their learning at the heart of the process. We read, talked to those with expertise in online learning, reflected on our own understandings of effective online learning and the nature of what it was we wanted our students to learn. From this, we created a set of guiding principles (Section 1) and some associated practical considerations (Section 2). We then deepened this by identifying some key messages from published evidence about online learning which we summarised in a table (Section 3). In redesigning our courses, the summary points in the table have been central.

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

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.

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

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 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 confounding and reverse causation. We began by identifying the genetic determinants of 955 circulating proteins in up to 10,708 SARS-CoV-2 uninfected individuals, retaining only single nucleotide polymorphisms near the gene encoded by the circulating protein. We then undertook an MR study to estimate the effect of these proteins on COVID-19 susceptibility and severity using the Host Genetics Initiative. We found that a standard deviation increase in OAS1 levels was associated with reduced COVID-19 death or ventilation (N = 2,972 cases / 284,472 controls; OR = 0.48, P = 7x10-8), COVID-19 hospitalization (N = 6,492 / 1,012,809; OR = 0.60, P = 2x10-7) and COVID-19 susceptibility (N = 17,607 / 1,345,334; OR = 0.81, P = 6x10-5). Results were consistent despite multiple sensitivity analyses probing MR assumptions. OAS1 is an interferon-stimulated gene that promotes viral RNA degradation. Other potentially implicated proteins included IL10RB. Available medicines, such as interferon-beta-1b, increase OAS1 and could be explored for their effect on COVID-19 susceptibility and severity.

Sampling SARS-CoV-2 proteomes for predicted CD8 T-cell epitopes as a tool for understanding immunogenic breadth and rationale vaccine design (preprint)

Predictive models for vaccine design have become a powerful and necessary resource for the expeditiousness design of vaccines to combat the ongoing SARS-CoV-2 global pandemic. Here we use the power of these predicted models to assess the sequence diversity of circulating SARS-CoV-2 proteomes in the context of an individuals CD8 T-cell immune repertoire to identify potential. defined regions of immunogenicity. Using this approach of expedited and rational CD8 T-cell vaccine design, it may be possible to develop a therapeutic vaccine candidate with the potential for both global and local coverage.