Ronat L, Hanganu A. Neuropsychiatric and cognitive features of major depressive disorder in aging, based on the data from the US National Alzheimer's Coordinating Center (NACC).
Encephale 2024;
50:130-136. [PMID:
37088582 DOI:
10.1016/j.encep.2023.01.010]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 01/03/2023] [Accepted: 01/12/2023] [Indexed: 04/25/2023]
Abstract
OBJECTIVE
The diagnosis of Major Depressive Disorder (MDD) is based on the DSM-V criteria and is established by a clinician. This allows quantifying depression based on clinical criteria. As such, MDD differs from other types of depressions that are measured by subjective scales. Here, we evaluated the MDD risk factor on other neuropsychiatric symptoms (NPS) as well as MDD association with cognitive performance in Alzheimer's disease (AD), Mild Cognitive Impairment (MCI) and Healthy Controls (HC).
METHODS
Data of 208 patients with AD, 291 patients with MCI and 647 HC were extracted from the National Alzheimer's Coordinating Center database. All participants included in this study were assessed by a physician for the MDD criteria, underwent an NPS evaluation using the NeuroPsychiatric Inventory, and a comprehensive cognitive assessment. Participants were classified as being with and without MDD. We performed logistic regression and MANCOVA models respectively with NPS and cognitive performance as variables of interest and MDD as fixed factors within each group. The MANCOVA was controlled for the effects of age, sex, and education.
RESULTS
MDD increased the risk for psychotic, affective and behavioral NPS in MCI, as well as affective and behavioral NPS in HC and AD. Also, MCI with MDD had lower performance on selective attention and mental flexibility.
CONCLUSIONS
MDD seems to increase the probability of a prevalence of NPS in all groups (HC, MCI and AD). Longitudinal data processing would help to understand the neuropsychiatric evolution of elderly subjects with MDD.
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