Late-life depression (LLD) increases risk for dementia and brain pathology, but possibly this is only true for one or more symptom profiles of LLD. In 4354 participants (76 ± 5 years; 58% female) from the Age, Gene/Environment Susceptibility (AGES)-Reykjavik Study, recently published in the journal Neurobiology of Aging, researchers identified five LLD symptom profiles, based on the Geriatric Depression Scale-15 (no LLD (57%); apathy (31%); apathy with emptiness (2%), mild LLD (8%) and severe LLD (2%)). Cox regression analyses showed that severe LLD, mild LLD and apathy increased risk of dementia up to 12 years, compared to no LLD. Additionally, hippocampal volume loss and white matter lesion increase, were assessed on 1.5 T MR images, at baseline and after 5 years follow-up. Only severe LLD showed increased WML volume over time, but not on hippocampal volume loss. WML increase over time mediated partially the relation between mild LLD and dementia but not for the other symptom profiles. It appears that hippocampal atrophy and LLD are independent predictors for dementia incidence, whereas for mild LLD the risk for dementia is partially mediated by WML changes. (PsycInfo Database Record (c) 2022 APA, all rights reserved)
Identifying individuals with subtle cognitive decline
August 18, 2022
Dementia is a devastating neurological disease that may be better managed if diagnosed earlier when subclinical neurodegenerative changes are already present, including subtle cognitive decline and mild cognitive impairment. In a new study published in the journal Neuropsychology, researchers used item-level performance on the Montreal Cognitive Assessment (MoCA) to identify individuals with subtle cognitive decline. Method: Individual MoCA item data from the Alzheimer’s Disease Neuroimaging Initiative was grouped using k-modes cluster analysis. These clusters were validated and examined for association with convergent neuropsychological tests. The clusters were then compared and characterized using multinomial logistic regression. Results: A three-cluster solution had 77.3% precision, with Cluster 1 (high performing) displaying no deficits in performance, Cluster 2 (memory deficits) displaying lower memory performance, and Cluster 3 (compound deficits) displaying lower performance on memory and executive function. Age at MoCA (older in compound deficits), gender (more females in memory deficits), and marital status (fewer married in compound deficits) were significantly different among clusters. Age was not associated with increased odds of membership in the high-performing cluster compared to the others. Conclusions: We identified three clusters of individuals classified as cognitively unimpaired using cluster analysis. Individuals in the compound deficits cluster performed lower on the MoCA and were older and less often married than individuals in other clusters. Demographic analyses suggest that cluster identity was due to a combination of both cognitive and clinical factors. Identifying individuals at risk for future cognitive decline using the MoCA could help them receive earlier evidence-based interventions to slow further cognitive decline. (PsycInfo Database Record (c) 2022 APA, all rights reserved)