Chunk #94 — 7.0 Recommendations to Advance Endophenotype Genetics — 7.3 Adequate power to detect individual effects is crucial but almost never attained in existing endophenotype genetic association studies — 7.3.1. Power and sampling schemes in GWAS
it used the best and most expensive measures collected in-person over the course of days in multiple waves on a very special sample of phenotypically extreme individuals from a population that is very hard to access and has not been studied. This argument can be extended then to rebut later failed replications because the replication study was not—in some cases, could not be—designed in the same way. This argument can be reformulated as an argument about statistical power: extreme sampling of a special population increases variance of the predictor, or MAF of the variant in question; measurement accuracy, time-consuming in-person assessments, and multiple waves of assessment serve to decrease measurement error; and the “best” measures are expected to have large effect sizes associated with them. However, as we have shown, even in the most unrealistically optimistic of such scenarios, it is very difficult or even impossible to overcome the inherent limitations of small samples to discover variants with the effect sizes we now expect for complex traits including endophenotypes. GWAS of complex traits, even in a unique sample assessed in the best way imaginable, will not be powerful without thousands of individuals and, more likely, tens to hundreds of thousands
