Completed Genetics & Molecular Biology Pregnancy, Children & Inherited Conditions

Mendelian randomization to hypothesis-free causal inference

In plain English

AI plain-English summary

A genetic technique called Mendelian randomization is being refined to help researchers tell whether a specific factor actually causes a disease, rather than just being associated with it. The core problem is that observational studies—where scientists simply watch what happens to people over time—are easily fooled. If people who drink coffee have less heart disease, it might be the coffee, or it might be that coffee drinkers tend to be wealthier, exercise more, or have other healthy habits. Mendelian randomization sidesteps this by using genetic variants as stand-ins for the factor of interest. Because genes are assigned randomly at conception and aren't altered by lifestyle, they act like a natural randomised trial. This programme will strengthen the reliability of that approach. The researchers will investigate how to apply it to identify treatments for existing disease—not just causes of new disease. If successful, the work could make drug development more efficient by flagging which biological targets are genuinely worth pursuing, reducing the number of clinical trials that fail because they were based on misleading observational evidence. This is primarily a methodological project: it does not aim to discover a specific new treatment, but to improve the statistical toolkit that other researchers use to find them.

View original technical description
Obtaining reliable evidence on causes of disease and influences on disease progression is problematic, since many other factors than the ones under study may influence the outcomes. Using genetic variants that mimic potentially modifiable factors that may cause disease or influence its course has become a widely-used approach to improving such understanding. Known as “Mendelian randomization” the methodology is still under development. This programme of work will contribute to strengthening the reliability of the approach, and, in particular, investigate the application to identifying treatments for existing disease.

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Researchers

George Davey Smith (Principal Investigator)

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Original classification

Intramural

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