Receive a weekly summary and discussion of the top papers of the week by leading researchers in the field.

In Alzheimer's & dementia : the journal of the Alzheimer's Association

INTRODUCTION : A data-driven index of dementia risk based on magnetic resonance imaging (MRI), the Alzheimer's Disease Pattern Similarity (AD-PS) score, was estimated for participants in the Atherosclerosis Risk in Communities (ARIC) study.

METHODS : AD-PS scores were generated for 839 cognitively non-impaired individuals with a mean follow-up of 4.86 years. The scores and a hypothesis-driven volumetric measure based on several brain regions susceptible to AD were compared as predictors of incident cognitive impairment in different settings.

RESULTS : Logistic regression analyses suggest the data-driven AD-PS scores to be more predictive of incident cognitive impairment than its counterpart. Both biomarkers were more predictive of incident cognitive impairment in participants who were White, female, and apolipoprotein E gene (APOE) ε4 carriers. Random forest analyses including predictors from different domains ranked the AD-PS scores as the most relevant MRI predictor of cognitive impairment.

CONCLUSIONS : Overall, the AD-PS scores were the stronger MRI-derived predictors of incident cognitive impairment in cognitively non-impaired individuals.

Casanova Ramon, Hsu Fang-Chi, Barnard Ryan T, Anderson Andrea M, Talluri Rajesh, Whitlow Christopher T, Hughes Timothy M, Griswold Michael, Hayden Kathleen M, Gottesman Rebecca F, Wagenknecht Lynne E

2021-Jul-26

AD-PS, ARIC, “Alzheimers disease”, MRI, machine learning, random forest