Towards precision medicine for dementia: a biopsychosocial approach

Abstract

Dementia is a progressive brain disorder marked by a decline in cognitive functions and overall quality of life. Its prevalence is expected to triple by 2050, posing a significant public health challenge. This research aimed to investigate the intricate relationship between two primary drivers of dementia: amyloid-beta accumulation and vascular pathology, particularly during the early stages before a formal diagnosis. The second objective was to explore potential connections between these biomarkers for dementia and psychosocial markers. Finally, the third objective sought to integrate both biological and psychosocial aspects into a comprehensive biopsychosocial framework. This was achieved through clustering techniques and the development of a machine learning model for prediction.

The study involved an extensive examination of multiple biomarkers and psychosocial factors and their interplay before the onset of dementia. Key findings included the potential utility of certain plasma biomarkers in monitoring neurodegeneration and vascular pathology. Additionally, the study revealed that adverse life events, particularly in early life, had enduring negative effects on hippocampal volume, a brain region crucial for memory and learning. Conversely, strong social support exhibited a protective influence on hippocampal volume, particularly in regions sensitive to stress.

Ultimately, employing a multimodal approach—considering both internal factors (biomarkers) and external factors (psychosocial aspects)—proved most effective for clustering and predicting dementia outcomes. These findings underscore the importance of comprehensively evaluating both physiological and psychosocial factors in understanding the causes, prevention, and treatment of dementia in future research.