Fig. 2: Typical scenarios of pleiotropy in causal inference of gene expression changes as an exposure. | Nature Communications

Fig. 2: Typical scenarios of pleiotropy in causal inference of gene expression changes as an exposure.

From: Mendelian randomization while jointly modeling cis genetics identifies causal relationships between gene expression and lipids

Fig. 2

Typical scenarios to consider when performing causal inference in gene expression: a expression quantitative trait locus (eQTL) single nucleotide polymorphisms (SNPs) used as instrumental variables (IVs) for the same gene (exposure) are in linkage disequilibrium (LD) and pleiotropic effects are absent, b pleiotropy is present through LD between IVs for different exposures (pleiotropy through LD), and c pleiotropy is present through overlap of the IVs (pleiotropy through overlap). In each panel, the left image shows the genomic context while the right image is a schematic diagram of the corresponding causal effects. Please note that the unobserved exposure trait does not necessarily need to be a protein product: it could be any measured or unmeasured phenotype that is regulated by the genetic locus.

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