Comparison of Functional and Structural Neural Network Features in Older Adults With Depression With vs Without Apathy and Association With Response to Escitalopram: Secondary Analysis of a Nonrandomized Clinical Trial

Treatment resistant late-life depression: A narrative review of psychosocial risk factors, non-pharmacological interventions, and the role of clinical phenotyping

BACKGROUND

Treatment resistant depression (TRD) is a subset of major depressive disorder (MDD) in which symptoms do not respond to front line therapies. In older adults, the assessment and treatment of TRD is complicated by psychosocial risk factors unique to this population, as well as a relative paucity of research.

METHODS

Narrative review aimed at (1) defining TRLLD for clinical practice and research; (2) describing psychosocial risk factors; (3) reviewing psychological and non-pharmacological treatments; (4) discussing the role of clinical phenotyping for personalized treatment; and (5) outlining research priorities.

RESULTS

Our definition of TRLLD centers on response to medication and neuromodulation in primary depressive disorders. Psychosocial risk factors include trauma and early life adversity, chronic physical illness, social isolation, personality, and barriers to care. Promising non-pharmacological treatments include cognitive training, psychotherapy, and lifestyle interventions. The utility of clinical phenotyping is highlighted by studies examining the impact of comorbidities, symptom dimensions (e.g., apathy), and structural/functional brain changes.

LIMITATIONS

There is a relative paucity of TRLLD research. This limits the scope of empirical data from which to derive reliable patterns and complicates efforts to evaluate the literature quantitatively.

CONCLUSIONS

TRLLD is a complex disorder that demands further investigation given our aging population. While this review highlights the promising breadth of TRLLD research to date, more research is needed to help elucidate, for example, the optimal timing for implementing risk mitigation strategies, the value of collaborative care approaches, specific treatment components associated with more robust response, and phenotyping to help inform treatment decisions.

A review of diffusion MRI in mood disorders: mechanisms and predictors of treatment response

By measuring the molecular diffusion of water molecules in brain tissue, diffusion MRI (dMRI) provides unique insight into the microstructure and structural connections of the brain in living subjects. Since its inception, the application of dMRI in clinical research has expanded our understanding of the possible biological bases of psychiatric disorders and successful responses to different therapeutic interventions. Here, we review the past decade of diffusion imaging-based investigations with a specific focus on studies examining the mechanisms and predictors of therapeutic response in people with mood disorders. We present a brief overview of the general application of dMRI and key methodological developments in the field that afford increasingly detailed information concerning the macro- and micro-structural properties and connectivity patterns of white matter (WM) pathways and their perturbation over time in patients followed prospectively while undergoing treatment. This is followed by a more in-depth summary of particular studies using dMRI approaches to examine mechanisms and predictors of clinical outcomes in patients with unipolar or bipolar depression receiving pharmacological, neurostimulation, or behavioral treatments. Limitations associated with dMRI research in general and with treatment studies in mood disorders specifically are discussed, as are directions for future research. Despite limitations and the associated discrepancies in findings across individual studies, evolving research strongly indicates that the field is on the precipice of identifying and validating dMRI biomarkers that could lead to more successful personalized treatment approaches and could serve as targets for evaluating the neural effects of novel treatments.

Personality traits as predictors for treatment response to sertraline among unmedicated obsessive-compulsive Disorder: A 12-weeks retrospective longitudinal study

The effectiveness of selective serotonin reuptake inhibitors (SSRIs) as a primary treatment for obsessive-compulsive disorder (OCD) remains uncertain. Even after undergoing standard SSRIs treatment, 40%-60% of individuals with OCD persistently endure symptoms. Recent studies proposed that personality traits may influence the diversity of OCD treatment results. Thus, in this retrospective study, we evaluated the Eysenck Personality Questionnaire (EPQ) scores of 51 untreated patients with OCD and 35 healthy controls. The Yale-Brown Obsessive Compulsive Scale (Y-BOCS) was employed to assess OCD symptom severity at weeks 0, 2, 4, 8, and 12 of sertraline treatment. The primary outcome focused on the reduction rate of Y-BOCS scores (response: ≥25%; marked response: ≥50%). Our findings revealed that individuals with OCD demonstrated a significantly higher neuroticism score compared to healthy controls. Correlation analyses exposed a positive link between psychoticism and the duration of the disease. Moreover, family history strongly correlated with both obsessive thoughts and the total Y-BOCS score. Subsequent univariate Cox proportional analyses indicated that both low neuroticism and high extraversion traits could forecast the response to sertraline. Furthermore, only a high extraversion trait was linked to a marked response. Our results support the idea that personality traits may contribute to OCD vulnerability and predict sertraline treatment outcomes.

Connectivity patterns of the core resting-state networks associated with apathy in late-life depression

BACKGROUND

Apathy is associated with reduced antidepressant response and dementia in late-life depression (LLD). However, the functional cerebral basis of apathy is understudied in LLD. We investigated the functional connectivity of 5 resting-state networks (RSN) hypothesized to underlie apathy in LLD.

METHODS

Resting-state functional MRI data were collected from individuals with LLD who did not have dementia as well as healthy older adults between October 2019 and April 2022. Apathy was evaluated using the diagnostic criteria for apathy (DCA), the Apathy Evaluation Scale (AES) and the Apathy Motivation Index (AMI). Subnetworks whose connectivity was significantly associated with each apathy measure were identified via the threshold-free network-based statistics. Regions that were consistently associated with apathy across the measures were reported as robust findings.

RESULTS

Our sample included 39 individuals with LLD who did not have dementia and 26 healthy older adults. Compared with healthy controls, individuals with LLD had an altered intra-RSN and inter-RNS connectivity in the default mode, the cingulo-opercular and the frontoparietal networks. All 3 apathy measurements showed associations with modified intra-RSN connectivity in these networks, except for the DCA in the cingulo-opercular network. The AMI scores showed stronger associations with the cingulo-opercular and frontoparietal networks, whereas the AES had stronger associations with the default mode network and the goal-oriented behaviour network.

LIMITATIONS

The study was limited by the small number of participants without apathy according to the DCA, which may have reduced the statistical power of between-group comparisons. Additionally, the reliance on specific apathy measures may have influenced the observed overlap in brain regions.

CONCLUSION

Our findings indicate that apathy in LLD is consistently associated with changes in both intra-RSN and inter-RSN connectivity of brain regions implicated in goal-oriented behaviours. These results corroborate previous findings of altered functional RSN connectivity in severe LLD.

Deficits in Key Brain Network for Social Interaction in Individuals with Schizophrenia

Individuals with schizophrenia (SZ) show impairment in social functioning. The reward network and the emotional salience network are considered to play important roles in social interaction. The current study investigated alterations in the resting-state (rs-) amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo) and functional connectivity (fc) in the reward network and the emotional salience network in SZ patients. MRI scans were collected from 60 subjects, including 30 SZ patients and 30 matched healthy controls. SZ symptoms were measured using the Positive and Negative Syndrome Scale (PANSS). We analyzed the ALFF, fALFF and ReHo in key brain regions in the reward network and emotional salience network as well as rs-fc among the bilateral amygdala, lateral orbitofrontal cortex (OFC), medial OFC and insula between groups. The SZ patients demonstrated increased ALFF in the right caudate and right putamen, increased fALFF and ReHo in the bilateral caudate, putamen and pallidum, along with decreased fALFF in the bilateral insula. Additionally, reduced rs-fc was found between the right lateral OFC and the left amygdala, which simultaneously belong to the reward network and the emotional salience network. These findings highlight the association between impaired social functioning in SZ patients and aberrant resting-state ALFF, fALFF, ReHo and fc. Future studies are needed to conduct network-based statistical analysis and task-state fMRI, reflecting live social interaction to advance our understanding of the mechanism of social interaction deficits in SZ.

[Late-life depression and frailty-Epidemiological, clinical and neurobiological associations]

BACKGROUND

Depression is the most common mental disorder in older adults and is influenced by age-related processes. Frailty is a well-established clinical expression of ageing that implies a state of increased vulnerability to stressor events as well as increased risks of disability, hospitalization and death. Neurobiological findings will disentangle the comorbidity of frailty and depression and may inform future management of depression in old age.

OBJECTIVE

This narrative review provides an overview of the comorbidity of late-life depression and frailty, with a focus on neuroscientific findings that are organized within the research domain criteria (RDoC) framework.

RESULTS

More than one third of old people with depression are affected by frailty, which results in more chronic depression and in poorer efficacy and tolerability of antidepressant medication. Depression and frailty share motivational and psychomotor characteristics, particularly apathy, decreased physical activity and fatigue. In patients with frailty, altered activity of the supplementary motor cortex is associated with motor performance deficits. Patients with late-life depression and apathy are characterized by abnormal structure and altered functional connectivity of the reward network and the salience network, along with altered functional connectivity of these networks with premotor brain areas.

CONCLUSION

Identifying frailty in older adults with depression is relevant for prognostic assessment and treatment. A better understanding of the neuronal mechanisms of comorbidity will provide potential targets for future personalized therapeutic interventions.

The neurobiology of apathy in depression and neurocognitive impairment in older adults: a review of epidemiological, clinical, neuropsychological and biological research

Apathy is a common condition that involves diminished initiative, diminished interest and diminished emotional expression or responsiveness. It is highly prevalent in the context of a variety of neuropsychiatric disorders and is related to poor health outcomes. Presence of apathy is associated with cognitive and functional decline in dementia. Despite its negative impact on health, there is no definitive treatment for apathy, a clinical reality that may be due in part to lack of knowledge about assessment, neuropsychological features and neurobiological underpinnings. Here, we review and synthesize evidence from clinical, epidemiological, neuropsychological, peripheral biomarker and neuroimaging research. Apathy is a common feature of depression and cognitive disorders and is associated with impairment in executive function. Neuropsychological and neuroimaging studies point to dysfunction of brain circuitry involving the prefrontal cortex, especially the dorsolateral prefrontal cortex circuit, the dorsomedial prefrontal cortex circuit, and the ventromedial prefrontal cortex circuit. However, inconsistent findings, particularly in neuroimaging may be due to heterogeneity of apathy symptoms (with a need to better elucidate subtypes), neuropsychiatric comorbidities, the severity of cognitive impairment and other factors. These factors need to be accounted for in future studies so that biomarker research can make progress. On the whole, the literature on apathy has identified likely neurocognitive, peripheral biomarker and neuroimaging targets for understanding apathy, but also points to the need to address methodological issues that will better inform future studies. In turn, as we learn more about the underpinning of apathy and its subtypes, subsequent research can focus on new neurally based interventions that will strengthen the clinical management of apathy in the context of its comorbidities.