The role of estimation in Mendelian randomization: should Mendelian randomization investigations provide estimates?

Benjamin Woolf1,2,3, Stephen Burgess3,4

  • 1MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.

Insights

Mendelian randomization (MR) uses genetic variation to infer causality, but estimates reflect lifelong exposure changes, not specific interventions. MR strengthens causal hypotheses rather than quantifying precise intervention effects.

Area of Science:

  • Epidemiology
  • Genetics
  • Biostatistics

Background:

  • Mendelian randomization (MR) employs genetic variants as instrumental variables to investigate causal relationships.
  • MR is conceptually similar to a randomized encouragement design, where genetic predisposition influences exposure liability.

Purpose of the Study:

  • To clarify the interpretation of Mendelian randomization (MR) estimates.
  • To advocate for MR's role in assessing causal hypotheses rather than quantifying specific causal effects.

Main Methods:

  • The study reviews the principles of Mendelian randomization (MR) and its analogy to randomized encouragement designs.
  • It discusses the interpretation of MR estimates in the context of lifelong exposure trajectories.

Main Results:

  • MR estimates reflect the impact of a lifelong shift in exposure, not a precisely defined intervention effect.
  • MR estimates are valuable for synthesizing evidence, assessing instrument validity, and comparing results across outcomes.

Conclusions:

  • Mendelian randomization (MR) provides valuable evidence for causal inference but should not be over-interpreted for quantifying specific causal effects.
  • The primary value of MR lies in strengthening or weakening confidence in a causal hypothesis, complementing other evidence sources.

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