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Editorial
. 2023 Mar 9:12:e86416.
doi: 10.7554/eLife.86416.

The next step in Mendelian randomization

Matthias Weith  1 , Andreas Beyer  2
Affiliations
Editorial

The next step in Mendelian randomization

Matthias Weith et al. Elife. .

Abstract

Expanding a statistical approach called Mendelian randomization to include multiple variables may help researchers to identify new molecular causes of specific traits.

Keywords: causal inference; gene expression; genetics; genomics; human; metabolomics; multiomics.

PubMed Disclaimer

Conflict of interest statement

MW, AB No competing interests declared

Figures

Figure 1.
Figure 1.. Mendelian randomization with multiple variables.
In the first step, Mendelian randomization calculations establish causal links between: (i) transcripts (T; pink chains) and metabolites (M; green hexagons) using eQTL and mQTL as instrumental variables (IV; first row); (ii) metabolites and various phenotypes (Y, such as height), using mQTL and the genetic variants associated with the traits as instrumental variables (second row). These causal links are then overlapped to establish causal triplets (third row). These causal triplets are subsequently analyzed in another Mendelian randomization-based calculation, which evaluates the effect of the respective mQTL on the levels of the transcripts, metabolites and traits of the triplet (fourth row). From this multivariate Mendelian randomization (MWMR), the proportion of transcript changes that directly effect a trait, and the proportion that cause an effect via metabolites, can be inferred. eQTL: expression quantitative trait loci; mQTL: metabolite quantitative trait loci.
See this image and copyright information in PMC

Comment on

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