Using genetics to understand the causal influence of higher BMI on depression

Figures

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  Figure 1.. The principles of Mendelian randomization and key MR assumptions which are: (i) the genetic instrument (Z) is robustly related to the risk factor of interest (X); (ii) Z is not associated with confounders (C) of the X-outcome (Y) association; and (iii) there is no path from Z to Y other than through X (part a). Part b shows how this may be violated.

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  Figure 2.. Flow chart explaining the derivation of depression cases and controls in the UK Biobank.

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  Figure 3.. Forest plot of the observational and genetic associations between a 1-SD higher BMI and the odds of depression. The plots display the observational association (Observational) and the genetic association using the two-step instrumental variable analysis with the BMI genetic risk score (Genetic 1-sample).

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  Figure 4.. Plot of the individual BMI variant—BMI associations from the primary GWAS that did not include UK Biobank22 against the BMI variant—depression associations on natural log scale (LN(OH)) from related Europeans in the UK Biobank, in: A) all individuals; B) males only; and C) females only. The beta regression coefficients for inverse variance weighted (IVW) instrumental analysis (black solid), Egger-MR (black dash),33 median-IV (grey solid) and the penalized weight median IV (grey dash) are plotted. The Egger intercept P-value is also given on the plots.

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  Figure 5.. Plot of the individual BMI variant—BMI associations from the primary GWAS that did not include UK Biobank22 against the BMI variant—depression associations on natural log scale (LN(OR)) from the PGC GWAS data excluding the UK Biobank. The beta regression coefficients for inverse variance weighted (IVW) instrumental analysis (black solid), Egger-MR (black dash),33 median-IV (grey solid) and the penalized weight median IV (grey dash) are plotted.