Clinical Scorecard: Mendelian Randomization in Infectious Diseases: Challenges and Opportunities

At a Glance

Key Highlights

• Mendelian randomization (MR) can identify causal risk factors and drug targets in infectious diseases, exemplified by COVID-19 therapies baricitinib and tocilizumab.
• Many MR studies in infection violate core assumptions, especially when using infection as an exposure, leading to biased or uninterpretable results.
• Genetic variants strongly affecting infection incidence are rare; antibody response variants are mostly in the complex HLA region, complicating causal inference.

Guideline-Based Recommendations

Diagnosis

• Use MR to estimate causal effects only when genetic instruments meet core assumptions (relevance, independence, exclusion restriction).
• Avoid using infection as an exposure unless strong, specific genetic instruments are available and assumptions can be validated.

Management

• Leverage MR findings to identify plausible drug targets for infectious diseases, as demonstrated in COVID-19 treatment development.
• Interpret MR results cautiously, especially when genetic variants relate to antibody response or vaccine-induced immunity.

Monitoring & Follow-up

• Continuously assess validity of MR assumptions in infectious disease studies, particularly regarding pleiotropy and linkage disequilibrium in HLA region.
• Monitor emerging genetic data to improve instrument selection and causal inference accuracy.

Risks

• Violation of MR assumptions can lead to invalid conclusions and misdirected clinical or research efforts.
• Using genetic variants associated with vaccine-induced antibodies may not reflect causal effects of infection itself.
• Temporal mismatch between pathogen emergence and study data can invalidate MR analyses (e.g., COVID-19 studies using pre-2019 data).

Patient & Prescribing Data

Patients with infectious diseases, particularly COVID-19

MR identified TYK2 expression as causal for severe COVID-19, guiding successful use of baricitinib; highlights MR's role in drug target validation.

Clinical Best Practices

• Ensure genetic instruments are biologically plausible and specific to the exposure of interest in infectious disease MR studies.
• Avoid conflating antibody response (including vaccine-induced) with infection exposure in causal inference.
• Recognize the complex interplay of genetics and environment in infection acquisition and progression when designing MR analyses.
• Use MR to address causal questions that cannot be answered by conventional epidemiology, with careful attention to assumptions and limitations.

References

• Mendelian randomization principles and assumptions
• Baricitinib and tocilizumab in COVID-19 trials
• Challenges in MR studies using infection as exposure