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Approved Research

Linear and Nonlinear Mendelian Randomization Analyses of the Causal Association Between Lipid Profiles and Cardiovascular Events

Principal Investigator: Miss Kui Zhang
Approved Research ID: 96286
Approval date: December 23rd 2022

Lay summary

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality around the world. Blood lipids such as Cholesterol play an essential role in the development of CVD. Cholesterol lowering therapy and management have been highly recommended in clinical guidelines. However, the associations between some specific kinds of cholesterol, like high density lipoprotein cholesterol, and CVD remains controversial. There is still a need to study and confirm whether those kinds of lipids lead to incident CVD or CVD death.

Therefore, we are very interested in the following questions in this study:

Q1: Does specific components of blood lipids increase the risk of incident CVD or CVD death, and what are their quantitative associations?

Q2: For the public, what are the ideal ranges of different components of blood lipids?

Using the UK Biobank data, we will first explore the associations of lipids profiles and CVD incidence and mortality. By comprehensively evaluating what roles of the lipids components play on CVD incidence and progression, our findings will provide potentially important evidence for clinical practice in lipids management. In addition, this study will also identify the ideal levels of blood lipids components and improve the prevention of cardiovascular diseases in the general population.

We plan to complete this project in 36 months.