Modeling human disease in Drosophila has proven to be a useful and versatile approach to understanding the cause, progression and mechanism of human disease. To assess the potential of Drosophila to analyze clinically graded aspects of human disease, we developed a transgenic fly model to characterize Presenilin ( PS ) gene mutations that cause early onset familial Alzheimer's disease (FAD). FAD is an aggressive autosomal dominant inherited form of Alzheimer's disease that has been genetically linked to mutations in three genes. These mutations, the majority of which are found in PS, result in a wide range in disease severity most readily defined by ages of onset from 24 to 65 years. PS FAD mutants have been analyzed in mammalian cell culture, but conflicting data emerged concerning correlations between age of onset and PS biochemical activity. These mutations have been controversially defined as either gain- or loss-of-function. To examine the activity of PS FAD mutations we have established a close approximate physiological transgenic expression of a collection of PS FAD mutations in the context of the Drosophila protein. Choosing from over 130 known mutations in Presenilin-1 , we introduced 14 corresponding mutations at conserved residues in Drosophila Presenilin (Psn), and assessed their biological activity in transgenic flies. By monitoring genetic, molecular and biochemical readouts of an endogenous substrate of Psn we are able to demonstrate a graded range of loss-of-function phenotypes in flies which statistically correlate to the severity of disease caused by the analogous FAD mutations in patients. This linkage of Presenilin mutant activities in Drosophila with human age of onset values provides evidence that disease severity in humans primarily reflects differences in PS mutant lesions rather than contributions from unlinked genetic or environmental modifiers. To our knowledge this is the first demonstration of a transgenic model organism that convincingly recapitulates the severity of a human disease.
