P1-359

Mutations causing familial Alzheimer's disease (AD) shift APP metabolism towards pro–amyloidogenic processing, either elevating total Aβ secretion or changing the ratio of Aβ 40/Aβ 42. Thus undiscovered genetic risk factors might also alter the ratio of pro–versus non–amyloidogenic processing of APP in late–onset AD. Identify candidate LOAD genes that modulate the pro–amyloidogenic processing of APP. We used siRNA technology to assess 15,200 human genes for their effects on secreted metabolites of APP. HEK293 cells stably expressing an optimized APP construct were transiently transfected with pools of three siRNA molecules, each targeting a single human transcript, and Aβ 40, Aβ 42, sAPPα, and sAPPβ were measured in the culture medium. Additional experiments were performed to control for effects on cell viability and non–specific effects on transgene expression or general secretion. We identified over 800 siRNAs that significantly altered the levels of secreted APP metabolites. Although many of these altered the preference for α– or β–site cleavage, none produced changes in the ratio of Aβ 40/Aβ 42 more than 2–fold, suggesting that genes controlling γ –secretase site specificity are rare. In contrast 80 siRNAs both raised sAPPα and lowered β– site cleavage products similar to siRNAs targeting the secretases responsible for Aβ production. Two of these genes, LRRTM3 and RUFY2, map to the region on chromosome 10 (10q21.3) associated with both elevated plasma Aβ42 and disease incidence. Both genes are expressed nearly exclusively in specific brain regions, including those affected during AD, and siRNAs to either significantly inhibit amyloidogenic processing of APP in SH–SY5Y neuroblastoma cells and neurons. Interestingly, LRRTM3 shares homology with the NOGO receptor (RTN4R), a gene involved in axonal sprouting and a cofactor for APP processing, whereas RUFY2 domain structure suggests a role in endosomal trafficking, which might be an obligate step in amyloidogenic processing of APP. LRRTM3 and RUFY2 are novel candidate genes for late–onset AD identified by functional screening.