The Neural Substrates Underlying different subgroups across Apathy Depression Anhedonia and Fatigue
Poster No:
1208
Submission Type:
Abstract Submission
Authors:
Jing Tian1, Maiya Geddes1
Institutions:
1Montreal Neurological Institute, McGill University, Montreal, Canada
First Author:
Co-Author:
Introduction:
Depression, apathy, anhedonia, and fatigue are common neuropsychiatric symptoms in Alzheimer's disease and have a profound impact on health-related quality of life[1]. However, because of the high correlation of these symptoms, analyzing them independently is limited[2]. Therefore, this study aims to conduct a comprehensive cross-sectional analysis of the performance differences and associated brain structural variances of these neuropsychiatric symptoms in older adults at a high risk of AD dementia.
Methods:
We collected 119 at high-risk of developing AD dementia subjects from the PRe-symptomatic Evaluation of Experimental or Novel Treatments for Alzheimer's Disease (PREVENT-AD) cohort[3] with the same year of available clinical data and structural MRI data. We implemented a hierarchical clustering model on the clinical scores from four scales, identified two distinct groups. Lower scores across all items characterized subtype 1, while higher scores across all items characterized subtype 2. Specifically, the four scales include the Geriatric Depression Scale (GDS), a 15-item questionnaire assessing depressive symptoms in older adults; the Apathy Evaluation Scale (AES), an 18-item questionnaire evaluating the presence and severity of apathy; the Snaith-Hamilton Pleasure Scale (SHAPS), a 14-item questionnaire designed to assess an individual's ability to experience pleasure or enjoyment; and the Modified Fatigue Impact Scale (MFIS), a 21-item questionnaire designed to assess the impact of fatigue on various aspects of daily functioning. Subsequently, we combined cortical and subcortical gray matter volume (GMV) based on the structural MRI data of the same 119 subjects. Applied Logistic regression to match brain features with subtypes. We then applied the bootstrap technique to identify significant brain regions with a 90% confidence interval (Fig 2). Prior to classification, we controlled for age, sex, education year, APOE4 states, and eTIV (Estimated Total Intracranial Volume) through regression.
Results:
In our clustering analysis, we find two groups (subtype 1 refers to the lower scores across the items; subtype 2 refers to the higher scores across the items.) shown in Fig 1A. Here, lower scores indicate higher levels of apathy, anhedonia, depression, and fatigue. Group 1 exhibits lower motivation, less pleasure, increased depression, and greater fatigue compare to group 2. Figure 1B presents the mean scores for each item in these two subtypes. Left nucleus accumbens, right pericalarine, right hippocampal, and left frontal are associated with the amotivational performances, which were shown on Figure 2. Specifically, compared to subtype 2, left accumbens, right pericalarine, and left frontal shows larger GMV in subtype 1, while right hippocampal shows smaller GMV in subtype 1.
·Fig 2. Distinct brain features of the two subtypes.
Conclusions:
In our study, we identified significant associations between motivational factors, blood pressure levels, depression, and fatigue, and the gray matter volumes in specific brain regions. Notably, larger gray matter volumes were observed in the nucleus accumbens, a crucial component of the reward system, suggesting a potential link between reduced motivation, lower pressure, elevated depression, and fatigue. This finding aligns with research indicating that frequent Facebook use on smartphones is associated with smaller gray matter volumes in the nucleus accumbens, indicative of a heightened motivation for self-reward[3]. Additionally, individuals in this group exhibited reduced volumes in the hippocampal region, a key network hub involved in various cognitive functions, including memory, executive functions, and emotional regulation[4]. Above all, by identifying the subtype of motivational states, our study shed light on the neurobiology of different motivational states of aging people.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s)
Psychiatric (eg. Depression, Anxiety, Schizophrenia)
Emotion, Motivation and Social Neuroscience:
Emotion and Motivation Other 2
Lifespan Development:
Aging 1
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Anatomy and Functional Systems
Keywords:
Aging
MRI
Psychiatric
Structures
1|2Indicates the priority used for review
Provide references using author date format
[2] L. Daumas et al., “Associations, overlaps and dissociations between apathy and fatigue,” Sci. Rep., vol. 12, no. 1, Art. no. 1, May 2022, doi: 10.1038/s41598-022-11071-5.
[3] J. Tremblay-Mercier et al., “Open science datasets from PREVENT-AD, a longitudinal cohort of pre-symptomatic Alzheimer’s disease,” NeuroImage Clin., vol. 31, p. 102733, Jan. 2021, doi: 10.1016/j.nicl.2021.102733.
[4] C. Montag et al., “Facebook usage on smartphones and gray matter volume of the nucleus accumbens,” Behav. Brain Res., vol. 329, pp. 221–228, Jun. 2017, doi: 10.1016/j.bbr.2017.04.035.
[5] K. Brosch et al., “Reduced hippocampal gray matter volume is a common feature of patients with major depression, bipolar disorder, and schizophrenia spectrum disorders,” Mol. Psychiatry, vol. 27, no. 10, Art. no. 10, Oct. 2022, doi: 10.1038/s41380-022-01687-4.