Mendelian Randomisation
In plain English
AI plain-English summaryMendelian randomization uses genetic data as a natural experiment to determine whether one thing actually causes another—for example, whether low vitamin D causes depression, or whether inflammation drives heart disease. The problem is that standard observational studies often confuse correlation with causation. Two things may appear linked—people who exercise more live longer—but the real cause could be something else, like income or diet. Mendelian randomization sidesteps this by using genetic variants as stand-ins for the exposure, because genes are assigned randomly at conception and aren’t altered by lifestyle or environment. However, as genetic studies balloon to millions of samples and new data types emerge, the statistical methods haven’t kept pace. Flawed methods can produce misleading causal claims. This project will develop better statistical tools to handle these massive datasets, including family-based data and genetic influences that change with age. It will also create new approaches to model the molecular causes of disease, feeding directly into pharmaceutical collaborations for drug development. If successful, the work could identify time-critical windows for disease prevention and reveal factors that influence prognosis and survival—not just disease onset—opening routes to novel therapies.
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