#mendelian randomization

A Mendelian Randomization (MR) study published in Nature Medicine reports a causal association between blood levels of OAS1 and susceptibility to COVID-19 infection. I liked many things in this study, of which I’d like to highlight three.

First, I liked that the authors performed the MR analysis using not just pQTLs, but also eQTLs and sQTLs as genetic instruments. In doing so, the authors reveal the mechanism underlying the association between the genetic variant and the OAS1 protein level in the blood, which, in turn, offers protection against COVID-19 infection.

In a typical scenario, one would expect a genetic variant to increase the protein level by increasing the mRNA level, considering the central dogma of biology (i.e. we expect an increased translation as a consequence of an increased transcription). But often the scenario is not that simple. Many of the pQTL studies published so far have shown that often pQTLs are not eQTLs. That is, often genetic variants influence protein levels without influencing the mRNA levels. The current study’s finding is one such example.

Here, the genetic variant increases the OAS1 protein level not by increasing the OAS1 transcription, but by favoring the OAS1 splicing towards one particular isoform. This is a scenario where a pQTL is not an eQTL but an sQTL. So, this finding teaches us that genetic variants can influence protein levels without influencing the transcription, but instead by influencing the splicing.  The authors have provided a table of posterior probabilities for pairwise colocalizations across eQTLs, sQTLs, pQTLs, and COVID-19 genetic associations, which clearly shows that there is no colocalization between eQTLs and pQTLs or between eQTLs and COVID-19 genetic associations.

The second thing I liked about this study is it draws a clear causal pathway from genetic variant to mRNA to protein to disease risk. This means it is an opportunity to explore how the effect sizes change as we move from one end of a causal pathway to its other end. For e.g. I’d expect that the effect size of the genetic variant’s association with splicing should be larger than its association with protein levels, which in turn should be larger than its association with disease risk (assuming that the genetic variant’s effect on disease risk is mediated entirely via its effect on the protein levels). However, I wasn’t able to retrieve the eQTL’s and pQTL’s effect sizes, which were disappointingly not reported in the study, and the reference pQTL study has not released the summary statistics publicly.

Thirdly, the authors report that the phenotypic association between OAS1 blood level and COVID-19 risk reverses between infectious and non-infectious states. While the non-infectious state OAS1 levels decrease the risk, the infectious state OAS1 levels increase the risk for COVID-19. This is expected as the viral infection itself causally increases the OAS1 levels in the blood. So, here, by using MR, we are able to dissociate the effect of OAS1 levels on COVID-19 risk from the effect of COVID-19 infection on the blood OAS1 levels, which, I think, is a great example of the wonderful things that we can do using human genetics.