Multi-compartmental modeling of SORLA’s influence on amyloidogenic processing in Alzheimer’s disease

In this study, we developed a multi-compartment model to simulate the complexity of APP processing in neurons and to accurately describe the effects of SORLA on these processes. Based on dose–response data, our study concludes that SORLA specifically impairs processing of APP dimers, the preferred secretase substrate. In addition, SORLA alters the dynamic behavior of β-secretase, the enzyme responsible for the initial step in the amyloidogenic processing cascade.Our multi-compartment model represents a major conceptual advance over single-compartment models previously used to simulate APP processing; and it identified APP dimers and β-secretase as the two distinct targets of the inhibitory action of SORLA in Alzheimer’s disease.The amyloid precursor protein (APP) is a type-1 membrane protein expressed in neurons, which is closely linked to the etiology and pathology of Alzheimer’s disease (AD) [1]. APP undergoes two mutually exclusive processing pathways resulting in the formation of multiple soluble and membrane-associated fragments from this precursor polypeptide. Of particular relevance to AD is the amyloidogenic pathway whereby APP is first cleaved by β-secretase and subsequently by γ-secretase to produce the amyloid-β peptide (Aβ), a 40 to 42 amino acid fragment derived from part of the extracellular and the transmembrane domains of APP. According to the amyloid hypothesis, neurotoxic oligomers and senile plaques formed by Aβ cause neuronal dysfunction and cell loss in AD [2,3]. In the alternative pathway, APP is first cleaved by α-secretase, instead of β-secretase, resulting in the destruction of the Aβ peptide sequence in APP (non-amyloidogenic pathway). Adding to the complexity of APP processing is the distinct trafficking route of the precursor through intracellular compartments where the various secretases reside [4,5]. Thus, newly synthesized APP molecules move through the constitutive secretory pathway from the trans-Golgi network (TGN) to the cell surfa