Introduction: Late-life cognitive impairment and depression frequently co-occur and share many symptoms. However, the specific neural and clinical factors contributing to both their common and distinct profiles in older adults remain unclear.
Methods: We investigated resting-state correlates of cognitive and depressive symptoms in older adults (n = 248 and n = 95) using clinical, blood, and neuroimaging data. We computed a connectivity matrix across default mode, executive control, and salience networks. Cross-validated elastic net regression identified features reflecting cognitive function and depressive symptoms. These features were validated on a held-out dataset.
Results: We discovered that white matter hyperintensities and nine overlapping nodes spanning all three networks are associated with both cognitive function and depressive symptoms, including left amygdala, left hippocampus, and bilateral ventral tegmental area.
Discussion: Our findings reveal intertwined neural nodes influencing cognitive impairment and depressive symptoms in late life, offering insights into shared characteristics and potential therapeutic targets.
Highlights: Resting-state neuroimaging markers are associated with symptoms of cognitive decline and late-life depression. Symptom-associated connectivity alterations were present across three major brain networks of interest, including the salience, default mode, and executive control networks. Some regions of interest are associated with both cognitive function and depressive symptoms, including the left amygdala, left hippocampus, and bilateral ventral tegmental area.
Keywords: Alzheimer's disease; depression; machine learning; resting state connectivity.
© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.