Alzheimer’s disease (AD) is the most common type of dementia. It is estimated that more than 35 million people worldwide will suffer from dementia in 2010. Without effective therapies, this epidemic is expected to affect more than 115 million patients worldwide by 2050. Genetic studies can help us understand the disease pathophysiology, thereby providing potential therapeutic, presymptomatic predictive and preventative avenues. Since 1990, there has been evidence for a substantial genetic component underlying the risk for AD. Three genes with autosomal dominant mutations lead to early-onset familial AD, which explains less than 1% of all AD. Apolipoprotein ε4, the only widely accepted genetic risk factor for late-onset AD, accounts for only a portion of this risk. Genetic linkage and association studies have identified multiple candidate gene regions, although many resulting candidate genes suffer from lack of replication, at least partially due to underpowered studies in the setting of genetic heterogeneity and small-tomoderate effect size. Genome-wide association studies that assess hundreds of thousands of single-nucleotide polymorphisms (SNPs) in thousands of subjects have been viewed as a potentially powerful approach in uncovering common risk variations for genetically complex diseases such as AD. To date, 11 independent genome-wide association studies have been completed in late-onset AD (LOAD) that led to candidate regions and genes for follow-up. These studies provide evidence for novel, plausible genetic risk factors for AD, but still fail to account for all of the estimated risk. Additional genetic risk factors of even smaller effect size, rare variants and/or structural DNA polymorphisms may exist, which may escape detection by conventional methods. Alternative approaches such as nextgeneration sequencing, use of quantitative endophenotypes, copy number variation analyses, and meta-analyses may be required. This review summarizes the current knowledge on the genetics of AD and suggests a framework for future genetic studies utilizing the lessons learned over the past two decades