Brain-cognition relationships in late-life depression: a systematic review of structural magnetic resonance imaging studies

Cognitive Profiles in Treatment-Resistant Late-Life Depression and their Impact on Treatment Outcomes

BACKGROUND

Late-life depression (LLD) is associated with cognitive impairment, yet substantial heterogeneity exists among patients. Data on the extent of cognitive impairments is inconclusive, particularly in patients with treatment-resistant depression (TRD). We investigated the cognitive profiles of patients with treatment-resistant vs. nonresistant LLD and aimed to identify distinct cognitive subgroups. Additionally, we examined whether cognitive subgroups differentially responded to treatment with bilateral repetitive transcranial magnetic stimulation (rTMS).

METHODS

165 patients with LLD were divided into treatment-resistant and nonresistant groups and compared to healthy controls (HC) on measures of executive function, information processing speed, verbal learning, and memory. Cluster analysis identified subgroups based on cognitive scores. Demographic and clinical variables, as well as outcomes with bilateral rTMS, were compared between cognitive subgroups.

RESULTS

Patients with LLD, particularly TRD, exhibited significantly worse cognitive performance than HC. A three-cluster solution was found, including "Cognitively Intact" (n = 89), "Cognitively Diminished" (n = 29), and "Impaired Memory" (n = 47) subgroups. Both the "Cognitively Diminished" and "Impaired Memory" subgroups had more anxiety symptoms and a higher proportion of patients with TRD than the "Cognitively Intact" group, though the latter did not survive multiple comparison correction. No significant differences were observed in outcomes to rTMS treatment.

CONCLUSIONS

Patients with LLD exhibited impairments across cognitive domains, which were more pronounced in TRD. Three identified cognitive subgroups responded similarly to rTMS treatment, indicating its effectiveness across cognitive profiles, especially when medications are not tolerated. Future research should examine the relationship among cognitive subgroups, cognitive decline, and neurodegeneration.

Novel insights into the activating transcription factor 4 in Alzheimer's disease and associated aging-related diseases: Mechanisms and therapeutic implications

Ageing is inherent to all human beings, most mechanistic explanations of ageing results from the combined effects of various physiological and pathological processes. Additionally, aging pivotally contributes to several chronic diseases. Activating transcription factor 4 (ATF4), a member of the ATF/cAMP response element-binding protein family, has recently emerged as a pivotal player owing to its indispensable role in the pathophysiological processes of Alzheimer's disease and aging-related diseases. Moreover, ATF4 is integral to numerous biological processes. Therefore, this article aims to comprehensively review relevant research on the role of ATF4 in the onset and progression of aging-related diseases, elucidating its potential mechanisms and therapeutic approaches. Our objective is to furnish scientific evidence for the early identification of risk factors in aging-related diseases and pave the way for new research directions for their treatment. By elucidating the signaling pathway network of ATF4 in aging-related diseases, we aspire to gain a profound understanding of the molecular and cellular mechanisms, offering novel strategies for addressing aging and developing related therapeutics.

Heterogeneity of Cognition in Older Adults with Remitted Major Depressive Disorder: A Latent Profile Analysis

OBJECTIVES

To identify data-driven cognitive profiles in older adults with remitted major depressive disorder (rMDD) with or without mild cognitive impairment (MCI) and examine how the profiles differ regarding demographic, clinical, and neuroimaging measures.

DESIGN

Secondary cross-sectional analysis using latent profile analysis.

SETTING

Multisite clinical trial in Toronto, Canada.

PARTICIPANTS

One hundred seventy-eight participants who met DSM-5 criteria for rMDD without MCI (rMDD-MCI; n = 60) or with MCI (rMDD + MCI; n = 118).

MEASUREMENTS

Demographic, clinical, neuroimaging measures, and domain scores from a neuropsychological battery assessing verbal memory, visuospatial memory, processing speed, working memory, language, and executive function.

RESULTS

We identified three latent profiles: Profile 1 (poor cognition; n = 75, 42.1%), Profile 2 (intermediate cognition; n = 75, 42.1%), and Profile 3 (normal cognition; n = 28, 15.7%). Compared to participants with Profile 3, those with Profile 1 or 2 were older, had lower education, experienced a greater burden of medical comorbidities, and were more likely to have MCI. The profiles did not differ on the severity of residual symptoms, age of onset of rMDD, number of depressive episodes, psychotropic medication, cerebrovascular risk, ApoE4 carrier status, or family history of depression, dementia, or Alzheimer's disease. The profiles differed in cortical thickness of 15 regions, with the most prominent effects for left precentral and pars opercularis, and right inferior parietal and supramarginal.

CONCLUSION

Older patients with rMDD can be grouped cross-sectionally based on data-driven cognitive profiles that differ from the absence or presence of a diagnosis of MCI. Future research should determine the differential risk for dementia of these data-driven subgroups.

Depressive symptoms and cognitive decline in older adults

OBJECTIVES

Few studies have examined the impact of late-life depression trajectories on specific domains of cognitive function. This study aims to delineate how different depressive symptom trajectories specifically affect cognitive function in older adults.

DESIGN

Prospective longitudinal cohort study.

SETTING

Australia and the United States of America.

PARTICIPANTS

In total, 11,035 community-dwelling older adults with a mean age of 75 years.

MEASUREMENTS

Depressive trajectories were modelled from depressive symptoms according to annual Centre for Epidemiological Studies Depression Scale 10 (CES-D-10) surveys. Four trajectories of depressive symptoms were identified: low ("nondepressed"), consistently mild ("subthreshold depression"), consistently moderate ("persistent depression"), and initially low but increasing ("emerging depression"). Global cognition (Modified Mini-Mental State Examination [3MS]), verbal fluency (Controlled Oral Word Association Test [COWAT]), processing speed (Symbol Digit Modalities Test [SDMT]), episodic memory (Hopkins Verbal Learning Test - Revised [HVLT-R]), and a composite z-score were assessed over a subsequent median 2 years.

RESULTS

Subthreshold depression predicted impaired performance on the SDMT (Cohen's d -0.04) and composite score (-0.03); emerging depression predicted impaired performance on the SDMT (-0.13), HVLT-R (-0.09), 3 MS (-0.08) and composite score (-0.09); and persistent depression predicted impaired performance on the SDMT (-0.08), 3 MS (-0.11), and composite score (-0.09).

CONCLUSIONS

Depressive symptoms are associated with later impaired processing speed. These effects are small. Diverse depression trajectories have different impacts on cognitive function.

Challenges in Identifying Individualized Brain Biomarkers of Late Life Depression

Research into neuroimaging biomarkers for Late Life Depression (LLD) has identified neural correlates of LLD including increased white matter hyperintensities and reduced hippocampal volume. However, studies into neuroimaging biomarkers for LLD largely fail to converge. This lack of replicability is potentially due to challenges linked to construct variability, etiological heterogeneity, and experimental rigor. We discuss suggestions to help address these challenges, including improved construct standardization, increased sample sizes, multimodal approaches to parse heterogeneity, and the use of individualized analytical models.