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OBJECTIVE: To establish whether, in a cohort with normal cognition, severity of depressive symptoms at baseline was related to the time taken for conversion to mild cognitive impairment (MCI) and whether this interacted with other potential risk factors, including APOE ε4 status and demographic and cognitive variables. METHODS: In a population-based cohort study, 126 cognitively normal subjects were assessed for depressive symptoms at baseline using the Geriatric Depression Scale (GDS) and were then followed over 20 years with regular cognitive assessments. The interval-censored accelerated failure time model was used to establish whether GDS and other factors, including APOE ε4 status, predicted the median time to development of MCI. RESULTS: Fifty subjects developed MCI. In APOE ε4 noncarriers, the degree of depressive symptoms at baseline predicted the time to development of MCI: An increase in GDS of 1 standard deviation (3.85) was associated with shortening of the median time to conversion to MCI by 25.4% (p = 0.0024, z = -5.6). This relationship remained statistically significant after controlling for cognitive and other confounding variables. The relationship was not significant in APOE ε4 carriers. CONCLUSION: Depressive symptoms (measured by GDS) predict time to conversion to MCI in cognitively normal people who do not carry the APOE ε4 allele. This may explain conflicting results of previous studies where APOE ε4 status was not taken into account when exploring the relationship between depression and MCI. It may also have a clinical application in helping to identify people at greater risk of developing MCI.

Original publication

DOI

10.1016/j.jagp.2012.12.025

Type

Journal article

Journal

Am J Geriatr Psychiatry

Publication Date

07/2014

Volume

22

Pages

727 - 734

Keywords

ApoE, MCI, depression, mild cognitive impairment, Aged, Aged, 80 and over, Apolipoprotein E4, Cognitive Dysfunction, Cohort Studies, Depression, Female, Heterozygote, Humans, Male, Middle Aged, Neuropsychological Tests, Risk Factors, Time Factors