A Proteomic Comparison of Sporadic Early-Onset, Late-Onset, and Autosomal Dominant Alzheimer's Disease

Emory University, Atlanta GA

Investigators

Abstract

PROJECT SUMMARY Alzheimer’s disease (AD) is commonly considered a disease exclusive to the elderly. While aging is the largest risk factor for the development of AD, approximately 5 to 10 percent of AD develops in people younger than age 65. In most early-onset AD cases there is no clearly identifiable genetic mutation that causes the disease, and therefore such cases have been termed sporadic early-onset AD (sEOAD). Compared to late-onset AD (LOAD) or autosomal dominant forms of AD (ADAD), little is known about the pathophysiology of sEOAD. In contrast to LOAD and ADAD, sEOAD more often presents with clinical syndromes that affect visual-spatial, language, executive and behavioral cognitive domains, and on average has a more rapidly progressive course compared to LOAD. Whether the underlying pathophysiology and biological pathway alterations, and biofluid biomarkers that reflect these changes, are the same in sEOAD as those in LOAD and ADAD is unknown. Our previous brain proteomic studies on LOAD through the Accelerating Medicines Partnership for AD (AMP-AD) have revealed many different pathological changes in LOAD beyond amyloid-β and tau dyshomeostasis. The goal of this project is to apply a similar proteomic approach to sEOAD to advance our understanding of sEOAD pathophysiology and how it is similar or distinct from LOAD and ADAD pathophysiology. We hypothesize that sEOAD will have more severe changes in mitochondrial, proteostasis, complement, and RNA-associated protein pathways compared to LOAD and ADAD. We will leverage a multi-platform discovery proteomic approach to analyze sEOAD and LOAD cerebrospinal fluid (CSF) and plasma to determine whether differences in EOAD brain pathophysiology can be observed in biofluids, and how these changes are related between CSF and plasma compartments. From our cross-tissue proteomic data we will assess which brain-linked biomarkers in sEOAD are most predictive of cognitive decline. These studies will significantly increase our understanding of the protein network changes that characterize sEOAD and how they are similar or unique to those observed in LOAD and ADAD. Such knowledge will be critical to ensuring that therapies and biomarkers developed for LOAD are applicable to those with early-onset forms of AD.