False positives in imaging genetics

Imaging genetics provides an enormous amount of functional-structural data on gene effects in living brain, but the sheer quantity of potential phenotypes raises concerns about false discovery. Here, we provide the first empirical results on false positive rates in imaging genetics. We analyzed 720 frequent coding SNPs without significant association with schizophrenia and a subset of 492 of these without association with cognitive function. Effects on brain structure (using voxel-based morphometry, VBM) and brain function, using two archival imaging tasks, the n-back working memory task and an emotional face matching task, were studied in whole brain and regions of interest and corrected for multiple comparisons using standard neuroimaging procedures. Since these variants are unlikely to impact relevant brain function, positives obtained provide an upper empirical estimate of the false positive association rate. In a separate analysis, we randomly permuted genotype labels across subjects, removing any true genotype-phenotype association in the data, to derive a lower empirical estimate. At a set correction level of 0.05, in each region of interest and data set used, the rate of positive findings was well below 5% (0.2-4.1%). There was no relationship between the region of interest and the false positive rate. Permutation results were in the same range as empirically derived rates. The observed low rates of positives provide empirical evidence that the type I error rate is well controlled by current commonly used correction procedures in imaging genetics, at least in the context of the imaging paradigms we have used. In fact, our observations indicate that these statistical thresholds are conservative. Published by Elsevier Inc.