Regional plots of non-overlapping loci that were more significantly associated with fibrinogen in the 1000G GWA study, including variants from both the HapMap (red) and 1000G (green) GWA studies.

<p>Regional plots of non-overlapping loci that were more significantly associated with fibrinogen in the 1000G GWA study, including variants from both the HapMap (red) and 1000G (green) GWA studies.</p

Regional plot of 6p21.3, a non-overlapping locus that was more significantly associated with fibrinogen in the HapMap GWA study, including variants from both the HapMap (red) and 1000G (green) GWA studies.

<p>Regional plot of 6p21.3, a non-overlapping locus that was more significantly associated with fibrinogen in the HapMap GWA study, including variants from both the HapMap (red) and 1000G (green) GWA studies.</p

Summary of the differences between HapMap and 1000G imputation for the seven non-overlapping loci.

<p>Summary of the differences between HapMap and 1000G imputation for the seven non-overlapping loci.</p

Overlapping loci that were significant in both the HapMap and 1000G GWA studies.

<p>Overlapping loci that were significant in both the HapMap and 1000G GWA studies.</p

Non-overlapping loci that were significant in either the HapMap or 1000G GWA studies.

<p>Non-overlapping loci that were significant in either the HapMap or 1000G GWA studies.</p

Summary of the differences between HapMap and 1000G imputation for the 29 overlapping loci.

<p>Summary of the differences between HapMap and 1000G imputation for the 29 overlapping loci.</p

Meta-analysis results of Mendelian randomization analyses on effect of <i>FTO</i>-derived adiposity on cardiovascular and metabolic disease: quantitative phenotypes.

a<p>Beta coefficient corresponds to one-unit increase in BMI (kg/m²).</p>b<p>Beta coefficient corresponds to per-allele change.</p>c<p>Values were transformed to natural logarithm scale prior to analysis.</p

Comparison of our study with previous Mendelian randomization studies of adiposity on cardiometabolic phenotypes.

a<p>No formal MR study, although the association of <i>FTO</i> and T2D is well known.</p><p>N.A, not applicable.</p

Meta-analysis results of Mendelian randomization analyses on effect of <i>FTO</i>-derived adiposity on cardiovascular and metabolic disease: dichotomous outcomes.

a<p>OR/HR corresponds to one-unit increase in BMI (kg/m²).</p>b<p>OR/HR corresponds to per-allele change.</p>c<p>Only one study; meta-analysis not performed.</p><p>HR, hazard ratio.</p

In a Mendelian randomization framework, genotype–phenotype association is assumed to be independent of confounding factors.

<p>(A) In an example from our study, the IV estimator is calculated as the beta coefficient from the association of <i>FTO</i> with systolic blood pressure divided by the beta coefficient from the association of <i>FTO</i> with BMI (IV estimator = 0.32/0.36 = 0.89 mm Hg/BMI unit). The IV estimator is equivalent to what is seen when systolic blood pressure is regressed on BMI. These results are supportive of a causal, non-confounded relationship. For binary traits, the calculation of the IV estimator is done on the log-odds scale. (B) The relationship of BMI with T2D, where the IV estimator is ln(OR_IV) = ln(1.12)/0.36, which equals a causal OR of BMI for T2D of 1.37. This is larger than what is seen in the standard age- and sex-adjusted logistic regression of T2D on BMI (<i>p</i> = 0.001), indicating that confounding or reverse causation may be present or that BMI measured once in adulthood does not fully reflect the effect of lifetime adiposity.</p