AD Resemblance Atrophy Index of Brain Magnetic Resonance Imaging in Predicting the Progression of Mild Cognitive Impairment Carrying Apolipoprotein E-e4 Allele

Background and ObjectiveEarly identification is important for timely Alzheimer's disease (AD) treatment. Apolipoprotein E epsilon 4 allele (APOE-epsilon 4) is an important genetic risk factor for sporadic AD. The AD-Resemblance Atrophy Index (RAI)-a structural magnetic resonance imaging-derived composite index-was found to predict the risk of progression from mild cognitive impairment (MCI) to AD. Therefore, we investigated whether the AD-RAI can predict cognitive decline and progression to AD in patients with MCI carrying APOE epsilon 4.& nbsp;Methods:& nbsp;We included 733 participants with MCI from the Alzheimer's Disease Neuroimaging Initiative Database (ADNI). Their APOE genotypes, cognitive performance, and levels of AD-RAI were assessed at baseline and follow-up. Linear regression models were used to test the correlations between the AD-RAI and baseline cognitive measures, and linear mixed models with random intercepts and slopes were applied to investigate whether AD-RAI and APOE-epsilon 4 can predict the level of cognitive decline. Cox proportional risk regression models were used to test the association of AD-RAI and APOE status with the progression from MCI to AD.& nbsp;Results:& nbsp;The baseline AD-RAI was higher in the MCI converted to AD group than in the MCI stable group (P < 0.001). The AD-RAI was significantly correlated with cognition, and had a synergistic effect with APOE-epsilon 4 to predict the rate of cognitive decline. The AD-RAI predicted the risk and timing of MCI progression to AD. Based on the MCI population carrying APOE-epsilon 4, the median time to progression from MCI to AD was 24 months if the AD-RAI > 0.5, while the median time to progression from MCI to AD was 96 months for patients with an AD-RAI <= 0.5.& nbsp;Conclusion:& nbsp;The AD-RAI can predict the risk of progression to AD in people with MCI carrying APOE epsilon 4, is strongly correlated with cognition, and can predict cognitive decline.