Such inconsistent linkage data is consistent with the idea that most of the genetic architecture for human addiction vulnerability is polygenic in most populations. There is now an increasing consensus that genome-wide association (GWA; also termed “whole genome association” or “association genome scanning”) is more likely than linkage approaches to yield positive results in polygenic complex disorders, such as addictions [1, 3, 10–12, 33–37]. Association asks how addiction phenotypes and genetic markers (genotyped approximately every 1/500,000th to every 1/1,000,000th of the genome in current datasets) are found together in nominally-unrelated individuals (although we are all distantly related to each other, of course). We and others have developed these methods, relying on the increasing densities of single nucleotide polymorphism (SNP) markers that can be assessed using “SNP chip” microarrays of increasing sophistication [10–12, 33, 34, 36, 37]. Genome wide association gains power as densities of genomic markers increase. Association identifies much smaller chromosomal regions than linkage-based approaches. Association thus allows us to identify variants in specific genes rather than in large chromosomal regions. Genome wide association fosters pooling strategies that preserve
