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MRC Biostatistics Unit

“Mendelian randomization for cardiovascular diseases: principles and applications”, is number 1 in the European Heart Journal Top Cited Articles for 2023. The paper, co-authored by Stephen Burgess at the MRC Biostatistics Unit, Susanna C. Larsson, and Adam Butterworth at the Department of Public Health and Primary Care, describes how Mendelian Randomization (MR) might be used to identify causal risk factors for cardiovascular disease.


Cardiovascular disease (CVD) is currently the leading cause of morbidity and premature death worldwide, which makes identifying causal risk factors for CVD crucial from both an individual and a societal perspective. Randomized Controlled Trials (RCTs) are often considered to be the gold standard for inferring causality. However, poor long-term compliance and ethical issues around random treatment allocation make conducting them difficult for CVD. MR has been applied to predict the efficacy and safety of existing and novel drugs targeting cardiovascular risk factors and to explore the repurposing potential of available drugs.

Drawing on the wealth of genetic data now available for potential risk factors, the paper explores how an MR study design can be used to identify which factors are causal in a similar way to an RCT, if certain assumptions are justified.

Since its publication in November 2023, the paper has gained widespread attention, amassing 211 citations in just over 12 months. In light of this, the paper has now been highlighted by the European Society of Cardiology for its contribution to cardiovascular research, and has earned first place in the Top Cited Articles on their website: https://www.escardio.org/Journals/ESC-Journal-Family/esc-journals-top-cited-articles-2023.


Stephen said:

“The increasing availability of genetic data means that Mendelian Randomization is becoming a key source of evidence on the causal status of modifiable risk factors for diseases. However, the approach needs to be used correctly to obtain meaningful results. Our paper helps researchers understand the principles of the approach in order to use it with precision.”