Table 3.

Ranking of risk factors and models (sets of risk factors) for type 2 diabetes^a

Risk factor or model	Ranking by MIP	MIP	$\widehat{\theta }$ CE	Ranking by PP	PP	$\widehat{\theta }$ λ
Model averaging using 12 SNVs (including rs1800562, rs1799945, rs855791, rs8177240, rs7385804, rs744653, rs651007, rs411988, rs9990333, rs4921915, rs6486121, rs174577)
Iron	4	0.177	0.008	4	0.17	0.05
Ferritin	1	0.305	0.023	1	0.293	0.082
Transferrin saturation	3	0.266	0.017	3	0.254	0.061
Transferrin	2	0.27	–0.015	2	0.264	–0.056
Model averaging using 9 SNVs (excluding invalid instruments rs651007, rs174577, rs4921915 with Q statistic > 10)
Iron	4	0.089	0.004	4	0.08	0.052
Ferritin	1	0.532	0.074	1	0.519	0.14
Transferrin saturation	2	0.268	0.015	2	0.257	0.055
Transferrin	3	0.131	–0.006	3	0.125	–0.043
Model averaging using 8 SNVs (excluding influential instrument rs1800562 with Cook’s distance exceeding the threshold)
Iron	4	0.15	0.002	4	0.143	0.017
Ferritin	1	0.488	0.04	1	0.477	0.083
Transferrin saturation	2	0.214	0.008	2	0.206	0.035
Transferrin	3	0.164	–0.004	3	0.158	–0.026

Abbreviations: MIP, marginal inclusion probability; MR, mendelian randomization; MR-BMA, MR based on Bayesian model averaging; PP, posterior probability; SNV, single-nucleotide variation (formerly single-nucleotide polymorphism [SNP]); T2D, type 2 diabetes.

^a Results were generated using the MR-BMA approach. In total, 4 genetically instrumented biomarkers of systemic iron status were assessed as risk factors. All the risk factors and the best individual models with a PP value greater than 0.02 were presented. A negative causal estimate ($\widehat{\theta }$MACE or $\widehat{\theta }$λ) indicates a protective effect as suggested by the model, whereas a positive value indicates a risk factor. $\widehat{\theta }$λ is the causal effect estimate for a specific model and $\widehat{\theta }$MACE is the model averaged causal effect of a risk factor.