This issue is particularly salient for exonic variation. Humans carry a huge pool of phenotypically-neutral background variation that adds noise to genetic analyses (for example, each person has ~100 loss-of-function variants, most of which are rare in a population), 152,153 and the presence of such variation complicates identification of disease-relevant variants. Thus, owing to chance, a researcher would expect to find a functional exonic mutation – possibly in a gene with intriguing biology – in one case sample and none of their control samples. More quantitatively, if 1% of cases are caused by fully penetrant mutations in a single gene with no background confounding variation, then observing 10 deleterious mutations in 1,000 cases and 0 in 1,000 controls would not stand out in test statistics from 20,000 genes. More realistic scenarios (including locus heterogeneity, incomplete penetrance, and background variation) will substantially erode the signal. The published results for ASD 83–85 and unpublished data on SCZ suggest these issues will be important and underscore the need for sequencing studies to have the same emphasis on statistical rigor and large sample sizes that has enabled GWAS to realize success for multiple psychiatric disorders. 154
