Mendelian Randomization and Infection: Pitfalls and Promises.

Area of Science:

• Epidemiology
• Genetics
• Infectious Diseases

Background:

• Mendelian randomization (MR) is increasingly used in infectious diseases (ID).
• MR shows promise for identifying infection causes/consequences and drug targets (e.g., COVID-19 treatments).
• Current MR applications in ID often yield limited insights due to assumption violations.

Purpose of the Study:

• Review MR principles, assumptions, and challenges specific to infectious diseases.
• Highlight examples of violated assumptions in MR studies.
• Discuss appropriate application of MR for causal inference in ID.

Main Methods:

• Review of Mendelian randomization principles and assumptions.
• Analysis of existing MR studies in infectious diseases.
• Discussion of bias in MR studies with infection as exposure versus outcome.

Main Results:

• MR studies in ID are susceptible to bias, especially when infection is the exposure.
• Violations of core MR assumptions limit the interpretability of results.
• Successful MR applications exist, demonstrating potential for drug target identification.

Conclusions:

• Appropriate application of MR is crucial for addressing complex causal questions in infectious diseases.
• Future MR research in ID should focus on methodological rigor and valid assumption adherence.
• MR offers unique insights into infectious disease etiology and treatment when applied correctly.