Cognitive phenotypes in late-life depression

Int Psychogeriatr. 2023 Apr;35(4):193-205. doi: 10.1017/S1041610222000515. Epub 2022 Jun 29.

Abstract

Objective: To identify cognitive phenotypes in late-life depression (LLD) and describe relationships with sociodemographic and clinical characteristics.

Design: Observational cohort study.

Setting: Baseline data from participants recruited via clinical referrals and community advertisements who enrolled in two separate studies.

Participants: Non-demented adults with LLD (n = 120; mean age = 66.73 ± 5.35 years) and non-depressed elders (n = 56; mean age = 67.95 ± 6.34 years).

Measurements: All completed a neuropsychological battery, and individual cognitive test scores were standardized across the entire sample without correcting for demographics. Five empirically derived cognitive domain composites were created, and cluster analytic approaches (hierarchical, k-means) were independently conducted to classify cognitive patterns in the depressed cohort only. Baseline sociodemographic and clinical characteristics were then compared across groups.

Results: A three-cluster solution best reflected the data, including "High Normal" (n = 47), "Reduced Normal" (n = 35), and "Low Executive Function" (n = 37) groups. The "High Normal" group was younger, more educated, predominantly Caucasian, and had fewer vascular risk factors and higher Mini-Mental Status Examination compared to "Low Executive Function" group. No differences were observed on other sociodemographic or clinical characteristics. Exploration of the "High Normal" group found two subgroups that only differed in attention/working memory performance and length of the current depressive episode.

Conclusions: Three cognitive phenotypes in LLD were identified that slightly differed in sociodemographic and disease-specific variables, but not in the quality of specific symptoms reported. Future work on these cognitive phenotypes will examine relationships to treatment response, vulnerability to cognitive decline, and neuroimaging markers to help disentangle the heterogeneity seen in this patient population.

Keywords: aging; cluster analysis; cognition; depression; geriatric; neuropsychological testing.

Publication types

  • Observational Study
  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Cognition
  • Cognitive Dysfunction* / diagnosis
  • Depression* / diagnosis
  • Depression* / psychology
  • Executive Function / physiology
  • Humans
  • Neuropsychological Tests
  • Phenotype