Chunk #51 — 6.0 How Do Electrophysiological Endophenotypes Compare with Other Quantitative Traits? — 6.1 Are endophenotype effect sizes larger than those of other phenotypes?
To further illustrate the differences in effect sizes between endophenotype-like measures and regular phenotypes, we reviewed the complex trait GWAS meta-analysis studies described above for total cholesterol (Teslovich et al., 2010); BMI (Locke et al., 2015); height (Wood et al., 2014); brain volumes (Stein et al., 2012); resting heart rate (Eijgelsheim et al., 2010); and antisaccade error (Vaidyanathan, Isen, et al., 2014) plus GWAS results for two metabolites (Kottgen et al., 2013; Ware et al., 2016); bone mineral density (Estrada et al., 2012); diabetes (Scott et al., 2012); depressive symptoms , subjective well-being, and neuroticism (Okbay Baselmans, et al., 2016); and education level (Okbay Beauchamp, et al., 2016). We then plotted effect sizes of GWAS-significant variants from these studies in Figure 1 on the r2 metric (variance accounted for in the phenotype). For quantitative trait studies that did not directly report variance accounted for but did report standardized effects, we computed an approximation using the formula: r2 = 2β2(1 – MAF)MAF, where β is a standardized effect size estimate of the variant when the residual variance is ~1, and MAF
