Depressive symptom dimensions and their association with hippocampal and entorhinal cortex volumes in community dwelling older adults

Congratulations Dr. John Williamson on the publication of “Depressive symptom dimensions and their association with hippocampal and entorhinal cortex volumes in community dwelling older adults.”  This article was accepted in Frontiers in Aging Neuroscience and will be published soon.

 

Abstract

Objective:

Research has shown that depression is a risk factor for Alzheimer’s disease (AD) and subsequent cognitive decline. This is compounded by evidence showing an association between depression and reduced hippocampal volumes; a primary structure implicated in the pathogenesis of the disease. Less is known about the relationship between depression and other AD vulnerable regions such as the entorhinal cortex. Given the heterogeneity of depressive symptom presentation, we examined whether symptom dimensions were associated with hippocampal and entorhinal cortex volumes in community dwelling older adults.

Methods:

Eighty one community dwelling adults completed the Beck Depression Inventory – 2nd edition and underwent structural neuroimaging. Measures of hippocampal and entorhinal cortex volumes were using obtained FreeSurfer software. Linear regression models included regions of interest as dependent variables, with depressive symptom dimensions, as independent variables, controlling for total intracranial volumes, age, education and gender.

Results:

Somatic symptoms were negatively associated with total, right and left hippocampal volumes. Affective symptoms were negatively associated with total entorhinal cortex volumes, with a marginal main effect on left entorhinal cortex volumes.

Conclusions:

Our findings provide support for examining depressive symptoms and their association with AD vulnerable regions along sub-dimensions of affective, cognitive and somatic symptoms to better understand profiles of symptoms most associated with these regions. Conceptualizing depressive symptoms in this way may also better inform treatment approaches in terms of targeting types of symptoms that may be more closely linked to poorer brain and cognitive health outcomes.