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\section{2009: The rebirth of Alzheimer's disease genetics}  Early attempts to perform a GWAS of LOAD suffered from small sample numbers and were insufficiently powered to detect genetic risk factors other than the strong \textit{APOE} association. Finally, in 2009 two European consortia, each with a case-control series of over 5000 samples, published three new genes in LOAD; \textit{CLU}, \textit{PICALM} and \textit{CR1} \cite{19734902}\cite{19734903}. This was swiftly followed by a fourth US led effort, \textit{BIN1}, in 2010 \cite{20460622}. Data pooling and meta-analysis between the US and European consortia resulted in the discovery of a further five genes; \textit{ABCA7}, \textit{EPHA1}, \textit{MS4A} locus, \textit{CD2AP}, \textit{CD33} \cite{21460840} \cite{21460841}. The final traunch of genes came in 2013 as a result of international collaboration under the IGAP (International Genomics of Alzheimer's Disease Project) consortia; \textit{PTK2$\beta$}, \textit{SORL1}, \textit{HLA-DRB5/1}, \textit{SLC24A4}, \textit{CASS4}, \textit{CELF1}, \textit{ZCWPW1}, \textit{INPP5D}, \textit{MEF2C}, \textit{NME8} and \textit{FERMT2} \cite{24162737}. This was the largest LOAD GWAS to date (n=74,046) and, due to genotype imputation with 1000 Genomes Project reference haplotypes, tested over 7 million genetic variants.  In the space of only five years GWAS has given the field twenty new genetic loci. However, GWAS was not without its critics.  \section{Interprating GWAS}  Allele Of the twenty LOAD-associated SNPs  discovered in LOAD, as in other complex disease, typically by GWAS, each  only impart a small influence on disease risk (Table 2). This is consistent with other complex diseases.  Critics have argued this renders them GWAS discoveries largely  uninformative for presymptomatic screening, and not a viable target nonviable  for theraputic intervention. However GWAS is not scattershot; the value of GWAS is in identifying the identification of  multiplealleles or  genes that influencea  common biological pathway. The twenty-one genetic pathways. Genetic  risk factors for LOAD cluster into three discrete biological pathways; innate immunity, endocytic vesicle recyclingpathways  and cholesterol homeostasis \cite{21486313}. The importance of this cannot be overstated; GWAS has enabled researcher to peer beyond the established dogma of the 'Amyloid Cascade Hypothesis', and nominate novel biological pathways for further exploation. In this sense GWAS is able to instigate a key change in our understanding of disease processes.  Translating GWAS findings 'to the bench' will be required to understand the mechanistic role of these genes in disease pathogenesis. disease.  Pathogenic mutations are typically coding and rare whereas, by design, GWAS identifies common, non-coding changes. For example, of the twenty-one loci involved in LOAD, all are either intronic or intragenic (Table ?). At each loci, it may be that the tag-SNP is in linkage with one or more functional alleles that are readily 'actionable' at the bench. For example the intronic \textit{CD33} tag-SNPs, rs3865444, is in complete linkage (R^2 = 1) with a splice-site mutation (rs12459419). The minor T  allele results in a CD33 isoform lacking exon 2, which encodes the sialic acid binding domain\cite{23946390}. This illustrates that GWAS tag-SNPs can be taken to the bench. Next-generation sequencing technology has allowed LOAD risk loci to be sequenced in large case-control series. These 'fine-mapping' studies have unearthed rare coding variants in \textit{ABCA7} and \textit{TREM2} that impart significantly more risk than the common tag-SNP that nominated the locus in the first place\cite{25807283}\cite{23150908}.