Traditionally, the hallmarks of Alzheimer’s disease (AD) have been primarily plaques arising from the deposition of the β-amyloid peptide (Aβ) and neurofibrillary degeneration signified by neurofibrillary tangles (NFTs) comprising aggregates of hyperphosphorylated tau protein. However, recent studies have also highlighted the role of inflammation in the central nervous system (CNS) in AD pathogenesis. Like in many other diseases, genetic discoveries lead the way in the identification of disease mechanisms. Genome-wide association studies (GWAS) have identified multiple immune-related genes associated with AD, such as TREM2, CD33, and CR1, all of which are expressed in microglia and other myeloid cells. Microglia can be activated by CNS inflammatory signals, Aβ pathology, or even macrophages from the periphery (due to higher blood-brain barrier (BBB) leakage in AD-risk patients). However, dysregulation of microglia activation fuels a pro-inflammatory cycle and eventual neurodegeneration. Other myeloid cells are also implicated, such as reactive astrocytes. Multiple immune cytokines and chemokines likely mediate activities in the cycle, such as IL-1, IL-6, TNF-α, and more. 

The hope of blood-based biomarkers is that they reflect brain changes of AD; however, they have proven elusive. Our approach was to determine whether acquired or inherited traits (discovered by GWAS) shared between peripheral blood mononuclear cells (PBMCs) and brain cells may provide peripheral biomarkers of neuroinflammation. Using a high-throughput and machine learning technique, we successfully identified proteins in the periphery that are predictive of AD diagnosis from a cohort of 122 participants. Now, we are looking to validate these blood-based biomarkers in a larger cohort, and to test if they can predict conversion to AD. Additionally, we will also study the biomarkers’ correlation to other AD indicators, including cognitive test scores and neuropathology, to obtain a deeper understanding of these biomarkers’ role in AD.