A major lesson from GWAS is that the initial studies of almost all complex traits were underpowered to detect significant associations given the small effects of individual risk loci and the stringent genome-wide significance threshold. Collaborative efforts will be needed to assemble the large samples necessary for GWAS to identify replicable loci and pathways associated with AD risk. Meta- and mega-analyses have elucidated the genetic architecture and identified variants associated with complex traits like type 2 diabetes (Morris et al., 2012), height (Lango Allen et al., 2010; Wood et al., 2014), schizophrenia (Ripke et al., 2011; Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014), and bipolar disorder (Sklar et al., 2011). Although no large-scale meta-analyses of AD have yet been performed, the Psychiatric Genomics Consortium (PGC) has assembled a working group to conduct mega-analyses of alcohol and illicit drug phenotypes. Another collaborative group, the GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN), has also formed to conduct GWAS and exome meta-analyses and whole genome sequencing studies of alcohol and nicotine use.
