Exploring diseases/traits and blood proteins causally related to expression of ACE2, the putative receptor of 2019-nCov: A Mendelian Randomization analysis

Shitao Rao; Alexandria Lau; Hon-Cheong So

To perform the phenome-study, we made use of the latest IEU GWAS database (https://gwas.mrcieu.ac.uk/), which contains up to 111,908,636,549 genetic associations from 31,773 GWAS summary datasets (as at 26 th Feb 2020). The database was retrieved via the R package "TwoSampleMR" (ver 0.5.1). MR analysis was conducted with the same package. Due to the extremely huge number of traits in the database, we performed some pre-selection to the list of traits/diseases before full analysis. Briefly, we selected the following categories of traits: (1) Traits listed as priority 1 (high priority) and labelled as "Disease" or "Risk factor" (81 and 71 items respectively); (2) traits labelled as "protein" as described above (3371 items); (3) (selected) traits from the UK Biobank, as it is one of the largest source of GWAS data worldwide (with sample size ~ 500,000). We consider that a proportion of traits have presumably low prior probability of association with respiratory infections, and others are less directly clinically relevant. To reduce computational burden and for ease of interpretation, a proportion of UK Biobank (UKBB) traits were filtered. More specifically, we excluded GWAS data of diseases or traits related to the following: eye or hearing problems, orthopedic and trauma-related conditions (except autoimmune diseases), skin problems (except systemic or autoimmune diseases), perinatal and obstetric problems, operation history, medication history (as confounding by indication is common and may affect the validity of results 22 ), diet/exercise habit (as accuracy of information . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.