Beau M. Ances

This study evaluates how biomarker variability affects individualized amyloid time estimation in Alzheimer's disease, finding that inter-individual variability is the main source of error.

This study finds that a history of traumatic brain injury with loss of consciousness (TBI-LOC) increases late-life amyloid PET burden, especially in APOE ε4 carriers with no clinical dementia.

This study identifies structural brain differences associated with cognitive performance in middle and late adulthood using data from the Human Connectome Project.

This study uses multimodal normative modeling on ATN biomarkers to analyze Alzheimer Disease heterogeneity, finding greater intra-group variation in more severe stages and a correlation between disease severity index and cognitive decline.

This paper evaluates the polygenic risk score for Alzheimer's disease in Japanese individuals, showing its utility despite genetic differences from European populations.

This study shows hub disruption in ADAD follows a targeted attack pattern, detectable pre-clinically and linked to amyloid beta changes and neuronal activity.

This study examines how brain age estimates from different MRI modalities relate to Alzheimer's disease biomarkers and cognition in early stages.

The paper describes MRI and PET protocols used in the DIAN study to investigate preclinical Alzheimer's disease and reports key imaging findings.

This paper introduces griPEER, a regularization method that uses structural brain connectivity to improve regression coefficient estimation in generalized linear models, and applies it to classify HIV+ and HIV- individuals.

This study uses an epidemic spreading model to show that tau spreads through neuronal connections in Alzheimer's disease, with beta-amyloid accelerating this process in some brain regions.

This study compares whole hippocampus and subfield biomarkers for Alzheimer’s disease detection and prediction using multimodal MRI data, finding subiculum biomarkers improve prediction accuracy.

This study finds smaller limbic brain volumes are associated with greater immunosuppression in HIV+ adults across five continents.

This paper develops a blood-based machine learning model to predict cerebral spinal fluid Aβ1-42 levels, showing high accuracy in identifying Alzheimer's disease risk.