 First, all modern approaches to heritability estimation are constructed from empirical data on Single Nucleotide Polymorphisms (SNPs). In effect, SNPs are the fundamental units of genetic differences that occur between individuals. While genetic sequences between humans are greater than 99% identical, SNPs are the points that differ. From a blood or saliva sample, ‘SNP chips’ allow researchers to acquire a large set of SNPs for an individual. Early SNP chips tracked 500,000 variants across the genome; recent technology allows SNP detection in the excess of millions. With the development of fast and cheap SNP chips within the past ten years, one now has the ability to assess large populations of minute DNA-based differences between individuals, which confers a new approach to estimating heritability. Through a large family of approaches, Genome Wide Association Studies (GWAS) identify statistical associations between SNPs and thousands of phenotypes, from physical traits (e.g., height, weight, BMI, etc.) to behavioral and psychiatric traits (e.g., IQ, schizophrenia, depression, etc.). Historically, GWAS are conducted as case-control studies: SNP profiles are collected from one population of individuals who share a trait (such as high ADHD or macular degeneration) and are compared to SNP profiles of a control population lacking in the trait under investigation. If it turns out that populations, on average, with the trait of interest also share genetic similarities, then GWAS will flag the relevant SNPs as statistically significant.