Programme(s) to which this project applies:
|☒ MPhil/PhD||☑ MRes[Med]||☒ URIS|
Objective and Significance:
Cardiovascular diseases and type 2 diabetes are important contributors to global burden of diseases.1 However, the causes of these diseases are not clearly understood.2 The use of observational studies to identify causes are prone to biases and confounding, given the contradictory findings from randomized controlled trials on topics such as hormone replacement therapy and vitamins.3,4 Without credible sources to form the evidence base, it would be difficult for policy makers and clinicians alike to make informative judgement to improve health outcomes. Mendelian randomization is a design which makes use of genetics to infer causal relation.5 Given genetic makeup is randomly allocated at conception, this makes the design less susceptible to confounding. The findings from this design is also consistent with trial results, such as vitamins and blood pressure. Better use of this design will undoubtedly improve our understanding of disease causes, and hence identify potential targets of interventions. The objective of this project is to use Mendelian randomization to examine the impact of a potential risk factor on coronary artery disease and type 2 diabetes, using summary statistics from relevant genome wide association studies (GWAS).
Research Plan and Methodology:
This will be a 2 sample Mendelian randomization study.6 Genetic instruments will be extracted from the largest GWAS on relevant exposures of interest, and applied to the GWAS on coronary artery disease (CAD) and type 2 diabetes.7,8 F statistics of each instrument will be approximated to assess potential weak instrument bias.9 The causal estimate from each genetic instrument will be calculated based on the Wald ratio and then meta-analyzed, using inverse variance weighting (IVW), to obtain the causal effect of exposures on health outcomes. However, IVW relies on no overall horizonal pleiotropy, which is difficult to test. To assess the robustness of the results, sensitivity analyses will be conducted, which rely on different assumptions.10 Consistencies in the results across different sensitivity analyses would strengthen the certainty of evidence. These include MR-Egger,11 weighted median,12 MR-PRESSO,13 and exclusion of pleiotropic instruments (based on PhenoScanner14). Analysis will be done using R Version 3.5.2 (R Development Core Team, Vienna, Austria) using R packages (“TwoSampleMR”),15 and (“MRPRESSO”).13
This study will only use published or publicly-available data. No original data will be collected for the MR study. Ethical approval for each of the studies included in the investigation can be found in the original publications (including informed consent from each participant).
For more information or to express interest for this project, please email the supervisor or the specified contact point in the project description. Interested candidates are advised to enclose with your email:
Information on the research programme, funding support and admission documentations could be referenced online at the Research Postgraduate Admissions website. General admission enquiries should be directed to firstname.lastname@example.org.
HKUMed MBBS students interested in the Master of Research in Medicine (MRes[Med]) programme may visit the programme website for more information.
HKUMed UG students interested in the Undergraduate Research Internship Scheme (URIS) may visit the scheme’s website for more information.