Colocalization of expression transcripts with COVID-19 outcomes is rare across cell states, cell types and organs. (preprint)

Identifying causal genes at GWAS loci can help pinpoint targets for therapeutic interventions. Expression studies can disentangle such loci but signals from expression quantitative trait loci (eQTLs) often fail to colocalize-which means that the genetic control of measured expression is not shared with the genetic control of disease risk. This may be because gene expression is measured in the wrong cell type, physiological state, or organ. We tested whether Mendelian randomization (MR) could identify genes at loci influencing COVID-19 outcomes and whether the colocalization of genetic control of expression and COVID-19 outcomes was influenced by cell type, cell stimulation, and organ. We conducted MR of cis-eQTLs from single cell (scRNA-seq) and bulk RNA sequencing. We then tested variables that could influence colocalization, including cell type, cell stimulation, RNA sequencing modality, organ, symptoms of COVID-19, and SARS-CoV-2 status among individuals with symptoms of COVID-19. The outcomes used to test colocalization were COVID-19 severity and susceptibility as assessed in the Host Genetics Initiative release 7. Most transcripts identified using MR did not colocalize when tested across cell types, cell state and in different organs. Most that did colocalize likely represented false positives due to linkage disequilibrium. In general, colocalization was highly variable and at times inconsistent for the same transcript across cell type, cell stimulation and organ. While we identified factors that influenced colocalization for select transcripts, identifying 33 that mediate COVID-19 outcomes, our study suggests that colocalization of expression with COVID-19 outcomes is partially due to noisy signals even after following quality control and sensitivity testing. These findings illustrate the present difficulty of linking expression transcripts to disease outcomes and the need for skepticism when observing eQTL MR results, even accounting for cell types, stimulation state and different organs.

Alternative splicing in the lung influences COVID-19 severity and respiratory diseases. (preprint)

Hospital admission for COVID-19 remains common despite the successful development of vaccines and treatments. Thus, there is an ongoing need to identify targets for new COVID-19 therapies. Alternative splicing is an essential mechanism for generating functional diversity in protein isoforms and influences immune response to infection. However, the causal role of alternative splicing in COVID-19 severity and its potential therapeutic relevance is not fully understood. In this study, we evaluated the causal role of alternative splicing in COVID-19 severity and susceptibility using Mendelian randomization (MR). To do so, we performed two-sample MR to assess whether cis-sQTLs spanning 8,172 gene splicing in 5,295 genes were associated with COVID-19 outcomes in the COVID-19 Host Genetics Initiative, including up to 158,840 COVID-19 cases and 2,782,977 population controls. We identified that alternative splicing in lungs, rather than total RNA expression of OAS1, ATP11A, DPP9 and NPNT, was associated with COVID-19 severity. MUC1 splicing was associated with COVID-19 susceptibility. Further colocalization analyses supported a shared genetic mechanism between COVID-19 severity with idiopathic pulmonary fibrosis at ATP11A and DPP9 loci, and with chronic obstructive lung diseases at NPNT. We lastly showed that ATP11A, DPP9, NPNT, and MUC1 were highly expressed in lung alveolar epithelial cells, both in COVID-19 uninfected and infected samples. Taken together, these findings clarify the importance of alternative splicing of proteins in the lung for COVID-19 and other respiratory diseases, providing isoform-based targets for drug discovery.

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

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.

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.