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A practical problem with Egger regression in Mendelian randomization.

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  • 1Division of Biostatistics, University of Minnesota, Minneapolis, Minnesota, United States of America.

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Mendelian randomization (MR) using Egger regression is sensitive to the coding of genetic variants (SNPs). Different SNP orientations can violate key assumptions, potentially invalidating causal inference in genetic association studies.

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Area of Science:

  • Epidemiology
  • Statistical Genetics

Background:

  • Mendelian randomization (MR) is a powerful instrumental variable (IV) method for causal inference.
  • Egger regression is a popular MR method, often considered robust to pleiotropy.
  • Valid causal conclusions in MR depend on three core IV assumptions.

Purpose of the Study:

  • To investigate the robustness of Egger regression to the orientation (coding) of single nucleotide polymorphisms (SNPs).
  • To assess the impact of SNP orientation on the instrument strength independent of direct effect (InSIDE) assumption.

Main Methods:

  • Utilized numerical examples with real and simulated data.
  • Performed analytical derivations to examine Egger regression's dependence on SNP orientation.
  • Evaluated the impact of different SNP coding schemes on the InSIDE assumption.

Main Results:

  • Egger regression demonstrates significant dependence on SNP orientation.
  • Default SNP orientation practices in MR software can lead to violations of the InSIDE assumption.
  • Alternative SNP orientations often result in InSIDE assumption violations, even if it holds for one specific orientation.

Conclusions:

  • Cautions are necessary when applying Egger regression due to its sensitivity to SNP orientation.
  • Related MR and IV regression methods may share similar vulnerabilities.
  • Further research is needed to understand and mitigate the impact of SNP orientation in MR studies.