LAUSR

Relatively few studies have addressed how aging contributes to late-onset Alzheimer's disease (LOAD) development and the mechanisms remain largely unknown. Here the authors integrate gene expression data from ∼1000 brains, comparing normal aging with LOAD individuals across different brain regions and identify normal aging-specific and LOAD-specific gene expression signatures. They also identify a subgroup of normal-aging samples highly similar to LOAD, representing individuals with high risk for developing LOAD. This high-risk gene expression signature contains excellent candidates for future studies on the early molecular mechanisms of LOAD development. The systems biology approach used can and should be more widely applied to study other diseases using previously available databases.