Abstract
The use of quantitative endophenotypes in genetic studies may provide greater power, allowing for the use of powerful statistical methods and a biological model for the effects of the disease-associated genetic variation. Cerebrospinal fluid (CSF) amyloid beta (Abeta) levels are promising endophenotypes for late-onset Alzheimer's disease (LOAD) and show correlation with LOAD status and Abeta deposition. In this study, we investigated 29 single nucleotide polymorphisms (SNPs) positive in AlzGene ( http://www.alzgene.org ) meta-analyses, for association with CSF Abeta levels in 313 individuals. This study design makes it possible to replicate reported LOAD risk alleles while contributing novel information about the mechanism by which they might affect that risk. Alleles in ACE, APOE, BDNF, DAPK1, and TF are significantly associated with CSF Abeta levels. In vitro analysis of the TF SNP showed a change in secreted Abeta consistent with the CSF phenotype and known Alzheimer's disease variants, demonstrating the utility of this approach in identifying SNPs that influence risk for disease via an Abeta-related mechanism.