GWAS are designed to identify common polymorphisms responsible for variation between individuals, and identification of common loci with small effects on personality traits could be possible by assembling very large sample sizes. For example, GWAS of blood pressure have identified replicated associations at genome-wide significance but only once sample sizes in excess of 60 000 individuals were available for meta-analysis.39 There are substantial obstacles to amassing a sample of such size for meta-analyses of personality, which do not exist for traits such as blood pressure. Blood pressure is a relatively direct biological measure, which is assessed in an objective and standardized way throughout the world. It is therefore straightforward to combine data across studies. In sharp contrast, personality trait assessment relies on self-report instruments, such as the TCI and NEO-PI-R, which pose two potential problems. First, while test–retest correlation for HA, RD and NS range from 0.58 to 0.84, for measures collected an average of 2 years apart,26 it is possible that self-report biases and differences in subjective interpretation of questionnaire items may introduce error in the assessment of traits.
