Sclerostin pQTL MR

Author

Affiliation

James Staley

UCB Pharma

Published

January 31, 2024

1 Introduction

This code book contains the code used in our comment on “Lowering of Circulating Sclerostin May Increase Risk of Atherosclerosis and its Risk Factors: Evidence From a Genome-Wide Association Meta-Analysis Followed by Mendelian Randomization” by Zheng et al. (2023). These analyses use genetic variants in cis of the SOST gene (the gene that encodes sclerostin) that are associated with circulating sclerostin protein levels, known as protein quantitative trait loci (pQTL). We visualize the SOST gene region for each phenotype and perform Mendelian randomization (MR) and colocalization analyses for the cardiovascular events and risk factors tested using results from the same (or equivalent) genome-wide association studies (GWAS) as used by Zheng et al. (2023). Sensitivity Mendelian randomization analyses using European only samples where possible (Section 8.1) and cis sclerostin pQTLs from UK Biobank (Sun et al. 2023) (Section 8.2) were also performed.

All of the code was written in (version 4.3.1). This code book was written using Quarto (version 1.3.433).

1.1 Installation

The data.table and tidyverse packages were used to reading and processing data. The Rsamtools and genetics packages were used to query and process the 1000 Genomes data (1000 Genomes Project Consortium et al. 2015). The geni.plots, heatmaply and reactable packages are used to plot and present the results.

install.packages("data.table", dependencies = TRUE)
install.packages("tidyverse")
install.packages("genetics")
install.packages("ieugwasr")
install.packages("BiocManager")
BiocManager::install("Rsamtools")
install.packages("remotes")
remotes::install_github("jrs95/geni.plots")
install.packages("heatmaply")
install.packages("reactable")
install.packages("downloadthis")
install.packages("tippy")

1.2 Libraries

The libraries used throughout the code book are dplyr, data.table, geni.plots and reactable. Functions from other libraries are imported as and when needed. Additional functions used in the analyses are stored in ./scripts/00_functions.R and are called using source.

library(data.table)
library(dplyr)
library(geni.plots)
library(reactable)

1.3 Citation

Staley JR et al. Genetic data do not provide evidence that lower sclerostin is associated with increased risk of atherosclerosis: comment on the article by Zheng et al. Arthritis Rheumatol 2023; DOI: 10.1002/art.42751

1.4 Licenses

The code is available under the GPL-3 license and the analysis results are available under the CC-BY-4.0 license.

# Introduction This code book contains the code used in our comment on "Lowering of Circulating Sclerostin May Increase Risk of Atherosclerosis and its Risk Factors: Evidence From a Genome-Wide Association Meta-Analysis Followed by Mendelian Randomization" by @zheng2023. These analyses use genetic variants in *cis* of the *SOST* gene (the gene that encodes sclerostin) that are associated with circulating sclerostin protein levels, known as protein quantitative trait loci (pQTL). We visualize the *SOST* gene region for each phenotype and perform Mendelian randomization (MR) and colocalization analyses for the cardiovascular events and risk factors tested using results from the same (or equivalent) genome-wide association studies (GWAS) as used by @zheng2023. Sensitivity Mendelian randomization analyses using European only samples where possible ([@sec-mr-eur]) and *cis* sclerostin pQTLs from UK Biobank [@sun2023] ([@sec-mr-ukbb]) were also performed. All of the code was written in `r fontawesome::fa(name = "r-project", fill = "#2468BB", height = "1em")` (version 4.3.1). This code book was written using Quarto (version 1.3.433). ## Installation The `data.table` and `tidyverse` packages were used to reading and processing data. The `Rsamtools` and `genetics` packages were used to query and process the 1000 Genomes data [@genomes2015]. The `geni.plots`, `heatmaply` and `reactable` packages are used to plot and present the results. ```{r} #| label: install #| eval: false install.packages("data.table", dependencies = TRUE) install.packages("tidyverse") install.packages("genetics") install.packages("ieugwasr") install.packages("BiocManager") BiocManager::install("Rsamtools") install.packages("remotes") remotes::install_github("jrs95/geni.plots") install.packages("heatmaply") install.packages("reactable") install.packages("downloadthis") install.packages("tippy") ``` ## Libraries The libraries used throughout the code book are `dplyr`, `data.table`, `geni.plots` and `reactable`. Functions from other libraries are imported as and when needed. Additional functions used in the analyses are stored in `./scripts/00_functions.R` and are called using `source`. ```{r} #| label: setup #| eval: false library(data.table) library(dplyr) library(geni.plots) library(reactable) ``` ## Citation Staley JR *et al*. Genetic data do not provide evidence that lower sclerostin is associated with increased risk of atherosclerosis: comment on the article by Zheng *et al*. Arthritis Rheumatol 2023; DOI: [10.1002/art.42751](https://acrjournals.onlinelibrary.wiley.com/doi/10.1002/art.42751) ## Licenses The code is available under the GPL-3 license and the analysis results are available under the CC-BY-4.0 license. [![](https://img.shields.io/badge/Code-GPL--3-BD0000.svg)](https://www.gnu.org/licenses/gpl-3.0.en.html) [![](https://img.shields.io/badge/Data-CC--BY--4.0-00AFD4.svg)](https://creativecommons.org/licenses/by/4.0/)