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Latent Classes of Cognitive Functioning among Depressed Older Adults Without Dementia

Morin, Ruth T. (author)
San Francisco Veterans Administration Medical Center
Insel, Philip (author)
Lund University,Lunds universitet,Klinisk minnesforskning,Forskargrupper vid Lunds universitet,Clinical Memory Research,Lund University Research Groups,San Francisco Veterans Administration Medical Center
Nelson, Craig (author)
University of California, San Francisco
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Butters, Meryl (author)
University of Pittsburgh
Bickford, David (author)
University of California, San Francisco
Landau, Susan (author)
University of California, Berkeley
Saykin, Andrew (author)
Indiana University
Weiner, Michael (author)
University of California, San Francisco
Mackin, R. Scott (author)
University of California, San Francisco,San Francisco Veterans Administration Medical Center
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 (creator_code:org_t)
2019
2019
English.
In: Journal of the International Neuropsychological Society. - 1355-6177. ; 25:8, s. 811-820
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Objective:Use latent class analysis (LCA) to identify patterns of cognitive functioning in a sample of older adults with clinical depression and without dementia and assess demographic, psychiatric, and neurobiological predictors of class membership.Method:Neuropsychological assessment data from 121 participants in the Alzheimer's Disease Neuroimaging Initiative-Depression project (ADNI-D) were analyzed, including measures of executive functioning, verbal and visual memory, visuospatial and language functioning, and processing speed. These data were analyzed using LCA, with predictors of class membership such as depression severity, depression and treatment history, amyloid burden, and APOE e4 allele also assessed.Results:A two-class model of cognitive functioning best fit the data, with the Lower Cognitive Class (46.1% of the sample) performing approximately one standard deviation below the Higher Cognitive Class (53.9%) on most tests. When predictors of class membership were assessed, carrying an APOE e4 allele was significantly associated with membership in the Lower Cognitive Class. Demographic characteristics, age of depression onset, depression severity, history of psychopharmacological treatment for depression, and amyloid positivity did not predict class membership.Conclusion:LCA allows for identification of subgroups of cognitive functioning in a mostly cognitively intact late life depression (LLD) population. One subgroup, the Lower Cognitive Class, more likely to carry an APOE e4 allele, may be at a greater risk for subsequent cognitive decline, even though current performance on neuropsychological testing is within normal limits. These findings have implications for early identification of those at greatest risk, risk factors, and avenues for preventive intervention.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Neurologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Neurology (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Psykiatri (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Psychiatry (hsv//eng)

Keyword

Aging
Cognitive functioning
Late life depression
Latent class analysis
Major depression
Neuropsychology

Publication and Content Type

art (subject category)
ref (subject category)

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