Amyloid pathology and modifiable risk factors in cognitive decline among cognitively unimpaired older adults

Alzheimer's disease (AD) pathology, particularly amyloid-β (Aβ) deposition, occurs years before clinical symptoms. Modifiable risk factors may influence cognitive trajectories during this preclinical stage, but whether amyloid status alters their effects remains unclear.

To investigate interactions between amyloid pathology and modifiable risk factors in predicting longitudinal cognitive decline among cognitively unimpaired older adults.

This study was a secondary analysis of data derived from two large multicenter longitudinal cohort studies, the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease (A4) Study and the Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) Study.

A total of 1707 cognitively unimpaired adults aged 65-85 years were included, comprising 1169 amyloid-positive participants from the A4 Study (Aβ+) and 538 amyloid-negative participants from the LEARN Study (Aβ-).

Cognitive function was assessed every six months using the Preclinical Alzheimer's Cognitive Composite (PACC) over a mean follow-up of 4.9 years. Eight established modifiable risk factors-low education, alcohol use, diabetes, high cholesterol, high blood pressure, obesity, depressive symptoms, and physical inactivity-were evaluated. Linear mixed-effects models were applied to examine associations between each risk factor and longitudinal PACC decline, and to test interactions with amyloid status, adjusting for demographic and genetic covariates.

Significant interactions between amyloid status and modifiable risk factors were observed for diabetes (adjusted β = -0.206, p = 0.032), high cholesterol (adjusted β = -0.155, p < 0.001), and physical inactivity (adjusted β = -0.161, p = 0.046), indicating combined effects rather than additive effects on cognitive decline among Aβ+ individuals. In the A4 study (Aβ+), low education, diabetes, high cholesterol, and physical inactivity were independently associated with accelerated cognitive decline, whereas obesity was linked to slower decline. In contrast, in the LEARN study (Aβ-), these associations were not statistically significant.

In conclusion, the significant interactions with amyloid status were observed for diabetes, high cholesterol, and physical inactivity, indicating that these risk factors were associated with faster cognitive decline specifically in Aβ+ individuals. The results suggest that consideration of amyloid status may be important when evaluating the potential role of metabolic and lifestyle risk factors in preclinical cognitive decline. In Aβ+ individuals, obesity was associated with slower cognitive decline, while low education was linked to lower baseline cognition or a reduced symptom threshold, without a significant interaction with amyloid status. Future studies should incorporate amyloid status and longitudinal biomarkers to assess whether modifying these factors can slow preclinical cognitive decline.