Discovery requires large patient groups. The large number of hypotheses tested in a typical genome-wide experiment poses a substantial multiple-testing problem. Patients who suffer rare adverse events may not be represented in small clinical trials. Treatment-responsive subgroups may comprise only a minority of patients grouped by current diagnostic categories. Such problems can be overcome with large sample sizes, but these can be expensive to collect and study. The STAR*D, CATIE, and STEP*BD projects were the first to provide samples large enough for genome-wide searches. Each of these studies collected a large group of patients with a common diagnosis (major depression, schizophrenia, and bipolar disorder, respectively), and assessed outcomes prospectively after relatively standardized treatment with one or more established psychotropic agents. These studies were not designed as pharmacogenetic studies, but did collect DNA on many participants, thus enabling later pharmacogenetic studies that would not have otherwise been possible. However, we now need additional large samples. One approach might be to aggregate samples from the large numbers of ongoing clinical trials, as discussed further below.
