Estimating the preclinical Alzheimer's disease course with multimodal data.

ABSTRACT:

Introduction

In observational studies of preclinical AD, an arbitrary "baseline" can obscure where an individual is located along a theoretical continuum. Optimizing longitudinal trajectories can distill multiple, non-linearly distributed observations into a single metric and inform where an individual may be along the disease course.

Methods

We developed a cognitive time (c-time) metric based on longitudinal cognitive data (mean = 7.4 years, range = 1.7-11.6) from 316 participants from the Harvard Aging Brain Study using non-linear least-squares optimization. We examined path analyses between a published time-to-amyloid beta (Aβ)+ metric (longitudinal Aβ positron emission tomography [PET]: mean = 6.3 years, range = 4.2-9.7) and c-time, including demographics, brain volume,

SUBMITTER: Townsend DL 

PROVIDER: S-EPMC12405800 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature