Alzheimer’s Disease-Like Brain Pattern Biomarker: Capturing Risks and Predicting Disease Onset

Preventing Alzheimer’s disease (AD) requires early-warning biomarkers. We developed a Regional Vulnerability Index (RVI) that quantifies individual brain similarity to AD patients' expected brain deficit patterns. We calculated regional effect sizes to establish brain deficit patterns in amyloid-positive AD cases compared to amyloid-negative healthy controls. The RVI-AD was calculated as a linear index of individual similarity to this established brain pattern in AD. Initially, we demonstrated RVI-AD elevation associated with risk factors in 335 participants (mean age: 49±13 years) in the Amish Connectome Project, followed by an independent sample consisting of 26,010 participants (mean age: 64±7 years) from the UK Biobank. Genetic and cardiovascular risks were evaluated using APOE-e4 genotype and Framingham Cardiovascular Risk Scores (FCVRS), respectively. Additionally, we assessed the risk of converting from MCI to dementia in N=1,932 participants (mean age: ~74) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Participants with the APOE-e4 allele had significantly elevated RVI-AD indices (p<0.05); FCVRS significantly contributed to higher RVI-AD in an APOE-e4-specific manner (p<0.01), replicable across the samples. In the ADNI cohort, RVI-AD significantly predicted conversion from MCI to dementia in the next decade, particularly within the first 3 years (AUC=74%). In healthy individuals, the RVI-AD index detected the insidious impact of APOE-ε4 and cardiovascular risks in otherwise normally aging cohorts. Elevated RVI-AD also predicted conversion to dementia within 10 years in the older, high-risk cohort. Further development of this brain-pattern similarity-based approach may yield a noninvasive, clinically accessible biomarker to aid early detection of the subtle to more imminent effects of AD risks.