Latent Classes of Cognitive Functioning among Depressed Older Adults Without Dementia

Ruth T. Morin, Philip Insel, Craig Nelson, Meryl Butters, David Bickford, Susan Landau, Andrew Saykin, Michael Weiner, R. Scott Mackin

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
JournalJournal of the International Neuropsychological Society
DOIs
StatePublished - Jan 1 2019

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Dementia
Depression
Alleles
Amyloid
Demography
Age of Onset
Neuroimaging
Psychiatry
Alzheimer Disease
Language
History
Population

Keywords

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

ASJC Scopus subject areas

  • Neuroscience(all)
  • Clinical Psychology
  • Clinical Neurology
  • Psychiatry and Mental health

Cite this

Latent Classes of Cognitive Functioning among Depressed Older Adults Without Dementia. / Morin, Ruth T.; Insel, Philip; Nelson, Craig; Butters, Meryl; Bickford, David; Landau, Susan; Saykin, Andrew; Weiner, Michael; Mackin, R. Scott.

In: Journal of the International Neuropsychological Society, 01.01.2019.

Research output: Contribution to journalArticle

Morin, Ruth T. ; Insel, Philip ; Nelson, Craig ; Butters, Meryl ; Bickford, David ; Landau, Susan ; Saykin, Andrew ; Weiner, Michael ; Mackin, R. Scott. / Latent Classes of Cognitive Functioning among Depressed Older Adults Without Dementia. In: Journal of the International Neuropsychological Society. 2019.
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abstract = "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.",
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