Aberrant Default Mode Network Underlying the Cognitive Deficits in the Patients With Late-Onset Depression

Depression in Alzheimer's Disease: Epidemiology, Mechanisms, and Treatment

Depression and Alzheimer's disease (AD) are substantial public health concerns. In the past decades, a link between the 2 disease entities has received extensive acknowledgment, yet the complex nature of this relationship demands further clarification. Some evidence indicates that midlife depression may be an AD risk factor, while a chronic course of depression in late life may be a precursor to or symptom of dementia. Recently, multiple pathophysiological mechanisms have been proposed to underlie the bidirectional relationship between depression and AD, including genetic predisposition, immune dysregulation, accumulation of AD-related biomarkers (e.g., amyloid-β and tau), and alterations in brain structure. Accordingly, numerous therapeutic approaches, such as pharmacology treatments, psychotherapy, and lifestyle interventions, have been suggested as potential means of interfering with these pathways. However, the current literature on this topic remains fragmented and lacks a comprehensive review characterizing the association between depression and AD. In this review, we aim to address these gaps by providing an overview of the co-occurrence and temporal relationship between depression and AD, as well as exploring their underlying mechanisms. We also examine the current therapeutic regimens for depression and their implications for AD management and outline key challenges facing the field.

Increasing variance of rich-club nodes distribution in early onset depression according to dynamic network

Early onset depression (EOD) and late onset depression (LOD) are thought to have different pathogeneses, but lack of pathological evidence. In the current study we describe the dynamic rich-club properties of patients with EOD and LOD to address this question indirectly. We recruited 82 patients with late life depression (EOD 40, LOD 42) and 90 healthy controls. Memory, executive function and processing speed were measured, and resting-stage functional MRI was performed with all participants. We constructed a dynamic functional connectivity network and carried out rich-club and modularity analyses. Normalized mutual information (NMI) was applied to describe the variance in rich-club nodes distribution and partitioning. The NMI coefficient of rich club nodes distribution among the three groups was the lowest in the EOD patients (F = 4.298; P = 0.0151, FDR = 0.0231), which was positively correlated with rich-club connectivity (R = 0.886, P < 0.001) and negatively correlated with memory (R = -0.347, P = 0.038) in the EOD group. In the LOD patients, non-rich-club connectivity was positively correlated with memory (R = 0.353, P = 0.030 and R = 0.420, P = 0.009). Furthermore, local connectivity was positively correlated with processing speed in the LOD patients (R = 0.374, P = 0.021). The modular partition was different between the EOD patients and the HCs (P = 0.0013 < 0.05/3). The temporal instability of rich-club nodes was found in the EOD patients, but not the LOD patients, supporting the hypothesis that EOD and LOD result from different pathogenesis, and showing that the instability of the rich-club nodes across time might disrupt rich-club connectivity.

Moving from phenomenological to predictive modelling: Progress and pitfalls of modelling brain stimulation in-silico

Brain stimulation is an increasingly popular neuromodulatory tool used in both clinical and research settings; however, the effects of brain stimulation, particularly those of non-invasive stimulation, are variable. This variability can be partially explained by an incomplete mechanistic understanding, coupled with a combinatorial explosion of possible stimulation parameters. Computational models constitute a useful tool to explore the vast sea of stimulation parameters and characterise their effects on brain activity. Yet the utility of modelling stimulation in-silico relies on its biophysical relevance, which needs to account for the dynamics of large and diverse neural populations and how underlying networks shape those collective dynamics. The large number of parameters to consider when constructing a model is no less than those needed to consider when planning empirical studies. This piece is centred on the application of phenomenological and biophysical models in non-invasive brain stimulation. We first introduce common forms of brain stimulation and computational models, and provide typical construction choices made when building phenomenological and biophysical models. Through the lens of four case studies, we provide an account of the questions these models can address, commonalities, and limitations across studies. We conclude by proposing future directions to fully realise the potential of computational models of brain stimulation for the design of personalized, efficient, and effective stimulation strategies.

Altered intrinsic default mode network functional connectivity in patients with remitted geriatric depression and amnestic mild cognitive impairment

OBJECTIVES

Patients with geriatric depression exhibit a spectrum of symptoms ranging from mild to severe cognitive impairment which could potentially lead to the development of Alzheimer's disease (AD). The aim of the study is to assess the alterations of the default mode network (DMN) in remitted geriatric depression (RGD) patients and whether it could serve as an underlying neuropathological mechanism associated with the risk of progression of AD.

DESIGN

Cross-sectional study.

PARTICIPANTS

A total of 154 participants, comprising 66 RGD subjects (which included 27 patients with comorbid amnestic mild cognitive impairment [aMCI] and 39 without aMCI [RGD]), 45 aMCI subjects without a history of depression (aMCI), and 43 matched healthy comparisons (HC), were recruited.

MEASUREMENTS

All participants completed neuropsychological tests and underwent resting-state functional magnetic resonance imaging (fMRI). Posterior cingulate cortex (PCC)-seeded DMN functional connectivity (FC) along with cognitive function were compared among the four groups, and correlation analyses were conducted.

RESULTS

In contrast to HC, RGD, aMCI, and RGD-aMCI subjects showed significant impairment across all domains of cognitive functions except for attention. Furthermore, compared with HC, there was a similar and significant decrease in PCC-seed FC in the bilateral medial superior frontal gyrus (M-SFG) in the RGD, aMCI, and RGD-aMCI groups.

CONCLUSIONS

The aberrations in rsFC of the DMN were associated with cognitive deficits in RGD patients and might potentially reflect an underlying neuropathological mechanism for the increased risk of developing AD. Therefore, altered connectivity in the DMN could serve as a potential neural marker for the conversion of geriatric depression to AD.

Altered large-scale brain network interactions associated with HIV infection and error processing

Altered activity within and between large-scale brain networks has been implicated across various neuropsychiatric conditions. However, patterns of network dysregulation associated with human immunodeficiency virus (HIV), and further impacted by cannabis (CB) use, remain to be delineated. We examined the impact of HIV and CB on resting-state functional connectivity (rsFC) between brain networks and associations with error awareness and error-related network responsivity. Participants (N = 106), stratified into four groups (HIV+/CB+, HIV+/CB-, HIV-/CB+, HIV-/CB-), underwent fMRI scanning while completing a resting-state scan and a modified Go/NoGo paradigm assessing brain responsivity to errors and explicit error awareness. We examined separate and interactive effects of HIV and CB on resource allocation indexes (RAIs), a measure quantifying rsFC strength between the default mode network (DMN), central executive network (CEN), and salience network (SN). We observed reduced RAIs among HIV+ (vs. HIV-) participants, which was driven by increased SN-DMN rsFC. No group differences were detected for SN-CEN rsFC. Increased SN-DMN rsFC correlated with diminished error awareness, but not with error-related network responsivity. These outcomes highlight altered network interactions among participants with HIV and suggest such rsFC dysregulation may persist during task performance, reflecting an inability to disengage irrelevant mental operations, ultimately hindering error processing.

Transcriptome Profiling of the Dorsomedial Prefrontal Cortex in Suicide Victims

The default mode network (DMN) plays an outstanding role in psychiatric disorders. Still, gene expressional changes in its major component, the dorsomedial prefrontal cortex (DMPFC), have not been characterized. We used RNA sequencing in postmortem DMPFC samples to investigate suicide victims compared to control subjects. 1400 genes differed using log2FC > ±1 and adjusted p-value < 0.05 criteria between groups. Genes associated with depressive disorder, schizophrenia and impaired cognition were strongly overexpressed in top differentially expressed genes. Protein−protein interaction and co-expressional networks coupled with gene set enrichment analysis revealed that pathways related to cytokine receptor signaling were enriched in downregulated, while glutamatergic synaptic signaling upregulated genes in suicidal individuals. A validated differentially expressed gene, which is known to be associated with mGluR5, was the N-terminal EF-hand calcium-binding protein 2 (NECAB2). In situ hybridization histochemistry and immunohistochemistry proved that NECAB2 is expressed in two different types of inhibitory neurons located in layers II-IV and VI, respectively. Our results imply extensive gene expressional alterations in the DMPFC related to suicidal behavior. Some of these genes may contribute to the altered mental state and behavior of suicide victims.

Differences in Odor Identification in Early-Onset and Late-Onset Depression

(1) Background: Odor identification (OI) dysfunction is a potential predictor of developing dementia in late life depression (LLD). However, it is not clear whether patients with early onset depression (EOD) and late onset depression (LOD) may exhibit different OI dysfunctions. The aim of this study was to compare OI between EOD patients and LOD patients and its relationship with cognitive function. (2) Methods: A total of 179 patients with LLD and 189 normal controls were recruited. Participants underwent clinical assessment, olfactory testing, and comprehensive neuropsychological assessment. The OI scores of EOD patients and LOD patients were compared, and correlation analyses and mediation analyses were used to explore the relationship between OI and cognition. (3) Result: LOD patients exhibited lower OI scores than EOD patients and normal controls (NCs). Additionally, the LOD patients exhibited a higher percentage of OI dysfunction than the EOD patients. Moreover, OI scores were associated with global cognition, memory, language, and visuospatial ability in the EOD group (p < 0.05) but were not associated with any cognitive score in the LOD patients (p > 0.05). Finally, the scores of the Auditory Verbal Learning Test Immediate recall and Boston Naming Test exhibited a partially mediating effect on the difference in OI scores between the EOD and LOD patients. (4) Conclusions: LOD patients exhibited worse OI than EOD patients, and their difference in OI was mediated by their memory and language function.

Susceptibility to chronic immobilization stress-induced depressive-like behaviour in middle-aged female mice and accompanying changes in dopamine D1 and GABAA receptors in related brain regions

Background

Middle-aged females, especially perimenopausal females, are vulnerable to depression, but the potential mechanism remains unclear. Dopaminergic and GABAergic system dysfunction is involved in the pathophysiology of depression. In the current study, we used 2-month-old and 11-month-old C57BL/6 mice as young and middle-aged mice, respectively. Chronic immobilization stress (CIS) was used to induce depressive-like behaviour, and the sucrose preference test (SPT), tail suspension test (TST) and forced swim test (FST) were used to assess these behaviours. We then measured the mRNA levels of dopamine receptor D1 (DRD1) and the GABA_A receptors GABRA1, GABRB2 and GABRG2 in the nucleus accumbens (NAc) and prefrontal cortex (PFC).

Results

We found that immobility time in the FST was significantly increased in the middle-aged mice compared with the middle-aged control mice and the young mice. In addition, the preference for sucrose water was reduced in the middle-aged mice compared with the middle-aged control mice. However, CIS did not induce obvious changes in the performance of the young mice in our behavioural tests. Moreover, the middle-aged mice exhibited equal immobility times as the young mice in the absence of stress. Decreases in the mRNA levels of DRD1, GABRA1, and GABRB2 but not GABRG2 were found in the NAc and PFC in the middle-aged mice in the absence of stress. Further decreases in the mRNA levels of DRD1 in the NAc and GABRG2 in the NAc and PFC were found in the middle-aged mice subjected to CIS.

Conclusions

Our results suggested that ageing could not directly induce depression in the absence of stress. However, ageing could induce susceptibility to depression in middle-aged mice in the presence of stress. CIS-induced decreases in DRD1 and GABRG2 levels might be involved in the increase in susceptibility to depression in this context.

Predicting conversion to Alzheimer's disease among individual high-risk patients using the Characterizing AD Risk Events index model

AIMS

Both amnestic mild cognitive impairment (aMCI) and remitted late-onset depression (rLOD) confer a high risk of developing Alzheimer's disease (AD). This study aims to determine whether the Characterizing AD Risk Events (CARE) index model can effectively predict conversion in individuals at high risk for AD development either in an independent aMCI population or in an rLOD population.

METHODS

The CARE index model was constructed based on the event-based probabilistic framework fusion of AD biomarkers to differentiate individuals progressing to AD from cognitively stable individuals in the aMCI population (27 stable subjects, 6 progressive subjects) and rLOD population (29 stable subjects, 10 progressive subjects) during the follow-up period.

RESULTS

AD diagnoses were predicted in the aMCI population with a balanced accuracy of 80.6%, a sensitivity of 83.3%, and a specificity of 77.8%. They were also predicted in the rLOD population with a balanced accuracy of 74.5%, a sensitivity of 80.0%, and a specificity of 69.0%. In addition, the CARE index scores were observed to be negatively correlated with the composite Z scores for episodic memory (R2  = .17, P < .001) at baseline in the combined high-risk population (N = 72).

CONCLUSIONS

The CARE index model can be used for the prediction of conversion to AD in both aMCI and rLOD populations effectively. Additionally, it can be used to monitor the disease severity of patients.

Aspirin and Risk of Dementia in Patients with Late-Onset Depression: A Population-Based Cohort Study

Background

Late onset depression (LOD) often occurs in the context of vascular disease and may be associated with risk of dementia. Aspirin is widely used to reduce the risk of cardiovascular disease and stroke. However, its role in patients with LOD and risk of dementia remains inconclusive. Materials and Methods. A population-based study was conducted using data from National Health Insurance of Taiwan during 1996–2009. Patients fulfil diagnostic criteria for LOD with or without subsequent dementia (incident dementia) and among whom users of aspirin (75 mg daily for at least 6 months) were identified. The time-dependent Cox proportional hazards model was applied for multivariate analyses. Propensity scores with the one-to-one nearest-neighbor matching model were used to select matching patients. Cumulative incidence of incident dementia after diagnosis of LOD was calculated by Kaplan–Meier Method.

Results

A total of 6028 (13.4%) and 40,411 (86.6%) patients were defined as, with and without diagnosis of LOD, among whom 2,424 (41.9%) were aspirin users. Patients with LOD had more comorbidities such as cardiovascular diseases, diabetes, and hypertension comparing to those without LOD. Among patients with LOD, aspirin users had lower incidence of subsequent incident dementia than non-users (Hazard Ratio = 0.734, 95% CI 0.641–0.841, p < 0.001). After matching aspirin users with non-users by propensity scores-matching method, the cumulative incidence of incident dementia was significantly lower in aspirin users of LOD patients (p < 0.001). After matching aspirin users with non-users by propensity scores-matching method, the cumulative incidence of incident dementia was significantly lower in aspirin users of LOD patients (

Conclusions

Aspirin may be associated with a lower risk of incident dementia in patients with LOD. This beneficial effect of aspirin in LOD patients needs validation in prospective clinical trials and our results should be interpreted with caution.

ABCA7 polymorphisms correlate with memory impairment and default mode network in patients with APOEε4-associated Alzheimer's disease

Background

Since both APOE and ABCA7 protein expression may independently reduce neuritic plaque burden and reorganize fibrillar amyloid burden-mediated disruption of functional connectivity in the default mode network, we aimed to investigate the effect of the APOE-ABCA7 interaction on default mode network in Alzheimer’s disease.

Methods

Two hundred and eighty-seven individuals with a diagnosis of typical Alzheimer’s disease were included in this study. Memory was characterized and compared between APOE-ε4+ carriers and APOE-ε4 non-carriers within ABCA7 rs3764650T allele homozygous carriers and ABCA7 rs3764650G allele carriers, respectively. Two-way analysis of variance was used to identify a significant interaction effect between APOE (APOE-ε4+ carriers versus APOE-ε4 non-carriers) and ABCA7 (ABCA7 rs3764650T allele homozygous versus ABCA7 rs3764650G allele carriers) on memory scores and functional connectivity in each default mode network subsystem.

Results

In ABCA7 rs3764650G allele carriers, APOE-ε4+ carriers had lower memory scores (t (159) = − 4.879; P < 0.001) compared to APOE-ε4 non-carriers, but APOE-ε4+ carriers and APOE-ε4 non-carriers did not have differences in memory (P > 0.05) within ABCA7 rs3764650T allele homozygous carriers. There was a significant APOE-ABCA7 interaction effect on the memory (F3, 283 = 4.755, P = 0.030). In the default mode network anchored by the entorhinal seed, the peak neural activity of the cluster that was significantly associated with APOE-ABCA7 interaction effects (P = 0.00002) was correlated with the memory (ρ = 0.129, P = 0.030).

Conclusions

Genetic-biological systems may impact disease presentation and therapy. Clarifying the effect of APOE-ABCA7 interactions on the default mode network and memory is critical to exploring the complex pathogenesis of Alzheimer’s disease and refining a potential therapy.

Diagnosing and Treating Depression in Patients with Alzheimer's Disease

Although cognitive and functional impairment are the hallmark features of Alzheimer's disease (AD), neuropsychiatric symptoms associated with AD account for increased rates of disability and profoundly impact the quality of life of both patients and their caregivers. This narrative review of current evidence provides practical guidance in diagnosing and managing depression in patients with AD using pharmacological and nonpharmacological interventions. After apathy, depression is the second most common neuropsychiatric symptom in AD. Diagnosing late-life depression (LLD), particularly in those affected by AD, is complicated because older patients may not meet the criteria for a major depressive disorder. Clinically, late-life depression and dementia can be indistinguishable. Although these two entities are now thought to be related, the pathologic mechanisms remain unclear. Evidence suggests that LLD may be a prodromal symptom of neurodegenerative disease. The various geropsychiatric measures currently used to diagnose, rate the severity of, and monitor the progress of treatment for depression are imperfect. Neuroimaging represents a promising avenue toward understanding the complex pathophysiologic relationships between dementia and LLD, and will support the pursuit of biomarker-driven diagnosis and treatment. Nonpharmacologic interventions to relieve depression in persons with cognitive impairment and dementia include emotion-oriented therapies, behavioral and cognitive-behavioral modification programs, and structured activity programs. Sensory-stimulation therapies and multisensory approaches show some promise for successfully treating depression in patients with dementia, but further rigorous research is needed to establish their validity. Clinical consensus and research appear to support selective serotonin reuptake inhibitors as a first choice for the pharmacological treatment of depression in patients with dementia. However, initial support for these therapies remains variable, and further investigation is needed. Extra care is required in prescribing to this population because of the generally high level of medical and psychiatric comorbidity and the potential difficulty in assessing the cognitively impaired patient's response.

The Neural Mechanisms of Associative Memory Revisited: fMRI Evidence from Implicit Contingency Learning

The literature describes a basic neurofunctional antagonism between episodic memory encoding and retrieval with opposed patterns of neural activation and deactivation, particularly in posterior midline regions. This has been coined the encoding/retrieval (E/R) flip. The present fMRI study uses an innovative task paradigm to further elucidate neurofunctional relations of encoding and retrieval in associative memory. Thereby, memory encoding is implemented as implicit (non-deliberate) cognitive process, whereas the prior literature focused mainly on explicit encoding. Moreover, instead of defining brain activations related to successful (vs. unsuccessful) memory performance, the task paradigm provides proper no-memory baseline conditions. More specifically, the encoding task includes trials with non-contingent (not learnable) stimulus combinations, while the retrieval task uses trials with a simple matching exercise with no mnemonic requirements. The analyses revealed circumscribed activation in the posterior middle cingulate cortex (pMCC) together with prominent deactivation in the anterior insula cortex (aIC) as core neural substrate of implicit memory encoding. Thereby, the pMCC exhibited positive functional connectivity to the hippocampus. Memory retrieval was related to an activation pattern exactly opposed to memory encoding with deactivation in the pMCC and activation in the aIC, while the aIC additionally exhibited a negative (i.e., arguably inhibitive) functional connectivity to the pMCC. Important to note, the observed pattern of activations/de-activations in the pMCC appears to conflict with prevalent E/R flip findings. The outlined results and their (alleged) discrepancies with prior study reports are discussed primarily in the context of the default mode network's functioning and its context-sensitive regulation. Finally, we point out the relevance of the present work for the understanding and further investigation of the neurofunctional aberrations occurring during normal and pathological aging.