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Anxiety in late-life depression: Associations with brain volume, amyloid beta, white matter lesions, cognition, and functional ability

Published online by Cambridge University Press:  25 January 2024

Maria Kryza-Lacombe*
Affiliation:
Mental Illness Research Education and Clinical Centers, Veterans Affairs Medical Center, San Francisco, CA, USA Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
Michelle T. Kassel
Affiliation:
Mental Illness Research Education and Clinical Centers, Veterans Affairs Medical Center, San Francisco, CA, USA Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
Philip S. Insel
Affiliation:
Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
Emma Rhodes
Affiliation:
Mental Illness Research Education and Clinical Centers, Veterans Affairs Medical Center, San Francisco, CA, USA Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
David Bickford
Affiliation:
Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
Emily Burns
Affiliation:
Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
Meryl A. Butters
Affiliation:
Department of Psychiatry Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
Duygu Tosun
Affiliation:
Veterans Affairs Medical Center, San Francisco, CA, USA Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
Paul Aisen
Affiliation:
University of Southern California, Los Angeles, CA, USA Keck School of Medicine, Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
Rema Raman
Affiliation:
University of Southern California, Los Angeles, CA, USA Keck School of Medicine, Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
Susan Landau
Affiliation:
Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
Andrew J. Saykin
Affiliation:
Department of Radiology and Imaging Sciences and the Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
Arthur W. Toga
Affiliation:
Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
Clifford R. Jack Jr
Affiliation:
Department of Radiology, Mayo Clinic, Rochester, MN, USA
Robert Koeppe
Affiliation:
Department of Radiology, University of Michigan, Ann Arbor, USA
Michael W. Weiner
Affiliation:
Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA Veterans Affairs Medical Center, San Francisco, CA, USA Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
Craig Nelson
Affiliation:
Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
R. Scott Mackin
Affiliation:
Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA Veterans Affairs Medical Center, San Francisco, CA, USA
*
Correspondence should be addressed to: M. Kryza-Lacombe, Mental Illness Research Education and Clinical Centers, San Francisco VA Health Care System, San Francisco, CA 94121, USA. Tel: (415) 221-4810 x23114. E-mail: maria.kryza-lacombe@ucsf.edu.

Abstract

Objectives:

Late-life depression (LLD) is common and frequently co-occurs with neurodegenerative diseases of aging. Little is known about how heterogeneity within LLD relates to factors typically associated with neurodegeneration. Varying levels of anxiety are one source of heterogeneity in LLD. We examined associations between anxiety symptom severity and factors associated with neurodegeneration, including regional brain volumes, amyloid beta (Aβ) deposition, white matter disease, cognitive dysfunction, and functional ability in LLD.

Participants and Measurements:

Older adults with major depression (N = 121, Ages 65–91) were evaluated for anxiety severity and the following: brain volume (orbitofrontal cortex [OFC], insula), cortical Aβ standardized uptake value ratio (SUVR), white matter hyperintensity (WMH) volume, global cognition, and functional ability. Separate linear regression analyses adjusting for age, sex, and concurrent depression severity were conducted to examine associations between anxiety and each of these factors. A global regression analysis was then conducted to examine the relative associations of these variables with anxiety severity.

Results:

Greater anxiety severity was associated with lower OFC volume (β = −68.25, t = −2.18, p = .031) and greater cognitive dysfunction (β = 0.23, t = 2.46, p = .016). Anxiety severity was not associated with insula volume, Aβ SUVR, WMH, or functional ability. When examining the relative associations of cognitive functioning and OFC volume with anxiety in a global model, cognitive dysfunction (β = 0.24, t = 2.62, p = .010), but not OFC volume, remained significantly associated with anxiety.

Conclusions:

Among multiple factors typically associated with neurodegeneration, cognitive dysfunction stands out as a key factor associated with anxiety severity in LLD which has implications for cognitive and psychiatric interventions.

Information

Type
Original Research Article
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of International Psychogeriatric Association
Figure 0

Table 1. Demographic and clinical characteristics (N = 121)

Figure 1

Figure 1. Associations of anxiety with insula (a) and orbitofrontal cortex (b) volumes.

Figure 2

Table 2. Summary of demographic and clinical predictors of orbitofrontal cortex volume and cognitive impairment

Figure 3

Table 3. Regression analysis predicting anxiety severity in LLD

Figure 4

Figure 2. Partial regression plot of the association between anxiety severity and cognitive functioning, controlling for age, gender, level of education, concurrent depression severity, and orbitofrontal volume.

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