Exploring the Causal Effect of Omega-3 Fatty acid Levels on Risk of Type 1 Diabetes: A Mendelian Randomization Study
Type 1 diabetes mellitus (T1D) is a chronic autoimmune disease characterized by the destruction of insulin-producing pancreatic beta cells and an ensuing lack of or low insulin. The burden of T1D is vast and as of 2021, an estimated 8.4 million people were living with the disease across the globe. It is predicted that by 2040, this number could increase to up to 17.4 million people. Despite nearly a century of insulin therapy for alleviating hyperglycaemia and the accompanying symptoms of T1D, no therapies exist to treat the underlying etiopathology of the disease. As evidenced by several studies, dietary interventions could offer a cost-effective approach to lowering the risk of T1D. The role of fatty acid status in the development of T1D has been of notable interest to researchers. Particularly, adequate dietary intake of omega-3 fatty acids (ω-3) has been reported to be associated with reduced risk of developing T1D. Given the inconclusive evidence from observational studies and RCTs, we conducted a Mendelian randomization (MR) study to explore the relationship between omega-3 fatty acids intake and T1D.
This project uses MR to investigate the causal effect of omega-3 levels on risk of Type 1 diabetes mellitus using genetic variants from Genome-wide association study (GWAS) summary statistics.
These instructions will get you a copy of the project up and running on your local machine for your own analysis.
To run this project, you will need:
- R software (version 4.0 or later)
- RStudio (version 1.2 or later)
- R packages
- TwoSampleMR version 0.5.6
- plyr
- Clone this repository to your local machine.
- Open RStudio and set the working directory to the cloned repository.
- Install the required packages by running "install.packages('plyr', repos = "http://cran.us.r-project.org") remotes::install_github("MRCIEU/TwoSampleMR")".
This project uses publicly available genetic data from the IEU OpenGWAS project. The data can be obtained from the OpenGWAS website (https://gwas.mrcieu.ac.uk/) using the dataset IDs indicated in the file named "GWAS_Summary_data.txt" in the data folder.
- Open the MR_Omega3_T1d.Rmd file in the scripts folder in RStudio.
- Knit the file to generate the analysis report (Omega3_T1d.pdf).
- View the report to see the results of the MR analysis.
This repository is structured as follows:
- data: Contains the raw data files used in the analysis.
- docs: Contains the project presentation and links to papers some papers used for this project.
- figures: Contains plots generated to aid interpretation of the MR analysis.
- output: Contains the MR analysis results and supplementary material.
- scripts: Contains the instrumental variable selection and statistical analysis scripts.
- README.md: Contains a summary of the project documentation.
- Joachim Ssenkaali
- Onan Mulumba
- Lydia Abolo
- Awe Olaitan
We thank the MRC Integrative Epidemiology Unit (IEU) at the University of Bristol for availing open source data that was used for this study. We also acknowledge the African Society for Bioinformatics and Computational Biology and the NIH Office of Data Science Strategy for their support.
- Smith GD, Ebrahim S. Mendelian randomization: prospects, potentials, and limitations. Int J Epidemiol. 2004;33(1):30-42.
- Burgess S, Thompson SG. Mendelian randomization: methods for using genetic variants in causal estimation. Chapman & Hall/CRC Press; 2015.
- Pierce, Brandon L, and Stephen Burgess. 2013. “Efficient design for Mendelian randomization studies: subsample and 2-sample instrumental variable estimators.” American Journal of Epidemiology 178 (7): 1177–84. https://doi.org/10.1093/aje/kwt084.
- https://github.com/MRCIEU/ieugwasr/blob/master/README.md#authentication