Abstract
Mendelian randomization (MR) investigates the causal effect of modifiable exposures on health outcomes within the Instrumental variable (IV) framework, using genetic variants as instruments. Therefore, a genetic variant should satisfy the IV assumptions to be considered as a valid instrument. MR analyses performed on summary data from large genetic association studies are increasingly being used and characterized by an increasing number of potential candidate instruments and a greater power. But, when multiple instruments are available, IV assumptions can be questionable and findings might highly depend on how those instruments are selected [1]. The present study aims at evaluating how MR estimates are sensitive to sets of instruments selected using different criteria. Applying different genetic data sources, the causal role of inflammation on Parkinson’s disease (PD) is investigated as a motivating example.
Considering two-sample MR methods available for summary genetic data, two main practical issues related to the instruments’ selection were explored: the Linkage Disequilibrium (LD) threshold and the pleiotropy strategy. Regarding LD, three sets of instruments were identified according to different thresholds of correlation among IVs. To rule out the presence of pleiotropy, two sets of instruments were derived excluding: (i) IVs with extreme Q-statistic; (ii) IVs identified as outliers by the Radial plot method. Causal effects were estimated using both fixed and random effects Inverse Variance Weighted methods and nine robust MR estimators [2]. The inflammation marker C-reactive Protein was used as exposure and PD as the outcome.
When different LD thresholds were set, no important differences in MR estimates were observed within each method. And there was no consensus between results obtained with different methods. Moreover, a different exclusion strategy for reducing pleiotropic IVs led to opposite effect estimates.
In MR studies, the findings can be sensitive to the choice of the instruments. Identification of appropriate strategies for selecting genetic variants is necessary and potential study-specific issues that may arise when different sets of instruments are considered should be accounted for.