Neuroanatomy of Alzheimer's Disease and Late-Life Depression: A Coordinate-Based Meta-Analysis of MRI Studies

Hippocampal volume maximally modulates the relationship between subsyndromal symptomatic depression and cognitive impairment in non-demented older adults

BACKGROUND

Subsyndromal symptomatic depression (SSD) is associated with an elevated risk of cognitive impairment in non-demented older adults. Given that hippocampal and middle temporal gyrus atrophy have been shown to cause SSD, our study aimed to investigate the effect of hippocampal volume on the association between SSD and cognitive impairment.

METHODS

338 non-demented older adults from the ADNI (Alzheimer's Disease Neuroimaging Initiative) cohort who underwent cognitive assessments, questionnaires on depressive symptoms and MRI brain were studied. SSD group is defined as a score of 1-5 based on Geriatric Depression Scale scores. We conducted causal mediation analyses to investigate the effect of hippocampal volume on cognitive performance cross-sectionally.

RESULTS

The SSD group displayed lower left and right hippocampal volume (p<0.01) than the non-SSD group. SSD was linked to poorer cognition and smaller hippocampal volume. We found that hippocampal volume partially mediated the effect of SSD on cognitive performance including the global cognition and the cognitive section of Alzheimer's Disease Assessment Scale, with mediation percentages ranging from 6.45 % to 30.46 %. In addition, we found that the thickness of the left middle temporal, right entorhinal and right fusiform gyrus, brain regions linked to AD, mediate the relationship between SSD and cognition with mediation percentages ranging from 8.67 % to 21.44 %.

LIMITATIONS

Our article didn't differentiate between mild cognitive impairment and normal population.

CONCLUSION

The associations of SSD and cognitive impairment are linked to alterations in Alzheimer's Disease related brain regions.

Preliminary evidence for preserved synaptic density in late-life depression

Late-life depression has been consistently associated with lower gray matter volume, the origin of which remains largely unexplained. Recent in-vivo PET findings in early-onset depression and Alzheimer's Disease suggest that synaptic deficits contribute to the pathophysiology of these disorders and may therefore contribute to lower gray matter volume in late-life depression. Here, we investigate synaptic density in vivo for the first time in late-life depression using the synaptic vesicle glycoprotein 2A receptor radioligand 11C-UCB-J. We included 24 currently depressed adults with late-life depression (73.0 ± 6.2 years, 16 female, geriatric depression scale = 19.5 ± 6.8) and 36 age- and gender-matched healthy controls (70.4 ± 6.2 years, 21 female, geriatric depression scale = 2.7 ± 2.9) that underwent simultaneous 11C-UCB-J positron emission tomography (PET) and 3D T1- and T2-FLAIR weighted magnetic resonance (MR) imaging on a 3-tesla PET-MR scanner. We used analyses of variance to test for 11C-UCB-J binding and gray matter volumes differences in regions implicated in depression. The late-life depression group showed a trend in lower gray matter volumes in the hippocampus (p = 0.04), mesial temporal (p = 0.02) and prefrontal cortex (p = 0.02) compared to healthy control group without surviving correction for multiple comparison. However, no group differences in 11C-UCB-J binding were found in these regions nor were any associations between 11C-UCB-J and depressive symptoms. Our data suggests that, in contrast to Alzheimer's Disease, lower gray matter volume in late-life depression is not associated with synaptic density changes. From a therapeutic standpoint, preserved synaptic density in late-life depression may be an encouraging finding.

Sex and Sleep Disruption as Contributing Factors in Alzheimer's Disease

Alzheimer's disease (AD) affects more women than men, with women throughout the menopausal transition potentially being the most under researched and at-risk group. Sleep disruptions, which are an established risk factor for AD, increase in prevalence with normal aging and are exacerbated in women during menopause. Sex differences showing more disrupted sleep patterns and increased AD pathology in women and female animal models have been established in literature, with much emphasis placed on loss of circulating gonadal hormones with age. Interestingly, increases in gonadotropins such as follicle stimulating hormone are emerging to be a major contributor to AD pathogenesis and may also play a role in sleep disruption, perhaps in combination with other lesser studied hormones. Several sleep influencing regions of the brain appear to be affected early in AD progression and some may exhibit sexual dimorphisms that may contribute to increased sleep disruptions in women with age. Additionally, some of the most common sleep disorders, as well as multiple health conditions that impair sleep quality, are more prevalent and more severe in women. These conditions are often comorbid with AD and have bi-directional relationships that contribute synergistically to cognitive decline and neuropathology. The association during aging of increased sleep disruption and sleep disorders, dramatic hormonal changes during and after menopause, and increased AD pathology may be interacting and contributing factors that lead to the increased number of women living with AD.

Age-Related Alterations in Gray Matter Microstructure in Older People With Remitted Major Depression at Risk for Dementia

Background

Major depressive disorder (MDD) in late life is a risk factor for mild cognitive impairment (MCI) and Alzheimer's disease. However, studies of gray matter changes have produced varied estimates of which structures are implicated in MDD and dementia. Changes in gray matter volume and cortical thickness are macrostructural measures for the microstructural processes of free water accumulation and dendritic spine loss.

Methods

We conducted multishell diffusion imaging to assess gray matter microstructure in 244 older adults with remitted MDD (n = 44), MCI (n = 115), remitted MDD+MCI (n = 61), or without psychiatric disorders or cognitive impairment (healthy control participants; n = 24). We estimated measures related to neurite density, orientation dispersion, and free water (isotropic volume fraction) using a biophysically plausible model (neurite orientation dispersion and density imaging).

Results

Results showed that increasing age was correlated with an increase in isotropic volume fraction and a decrease in orientation dispersion index, which is consistent with neuropathology dendritic loss. In addition, this relationship between age and increased isotropic volume fraction was more disrupted in the MCI group than in the remitted MDD or healthy control groups. However, the association between age and orientation dispersion index was similar for all 3 groups.

Conclusions

The findings suggest that the neurite orientation dispersion and density imaging measures could be used to identify biological risk factors for Alzheimer's disease, signifying both conventional neurodegeneration observed with MCI and dendritic loss seen in MDD.

The contribution of being physically active to successful aging

Growing old involves changes in physical, psychological, and cognitive functions. Promoting physical and mental health has become one of the priorities for an aging population. Studies have demonstrated the benefits of engaging in regular physical activity. Here, we aimed to understand the relationships between physical activity and working memory complaints in attention, memory storage, and executive functions. We hypothesized that physical activity was negatively associated with complaints in working memory domains after controlling for socio-demographics and distress factors, such as anxiety, stress, and depression. Two hundred and twenty-three individuals aged between 65 and 100 years (74.84; SD = 7.74; 133 males) without self-reported neurological and/or psychiatric disorders completed a questionnaire on socio-demographic, with questions on physical activity and the Italian version of the working memory questionnaire (WMQ) and the DASS-21 measuring anxiety, stress, and depression. Results from three linear regression models showed that low physical activity was associated with complaints in attention (R2 = 0.35) and executive functions (R2 = 0.37) but not in memory storage (R2 = 0.28). Notably, age, gender, and total emotional distress (DASS score) were significant in all regression models. Our results suggested regular physical activity, even just walking, is crucial for maintaining efficient cognitive function. Theoretical and practical implications for engaging in physical activity programs and social aggregation during exercise are considered. Limitations are also presented.

Physical Exercise as Disease-Modifying Alternative against Alzheimer's Disease: A Gut-Muscle-Brain Partnership

Alzheimer's disease (AD) is a common cause of dementia characterized by neurodegenerative dysregulations, cognitive impairments, and neuropsychiatric symptoms. Physical exercise (PE) has emerged as a powerful tool for reducing chronic inflammation, improving overall health, and preventing cognitive decline. The connection between the immune system, gut microbiota (GM), and neuroinflammation highlights the role of the gut-brain axis in maintaining brain health and preventing neurodegenerative diseases. Neglected so far, PE has beneficial effects on microbial composition and diversity, thus providing the potential to alleviate neurological symptoms. There is bidirectional communication between the gut and muscle, with GM diversity modulation and short-chain fatty acid (SCFA) production affecting muscle metabolism and preservation, and muscle activity/exercise in turn inducing significant changes in GM composition, functionality, diversity, and SCFA production. This gut-muscle and muscle-gut interplay can then modulate cognition. For instance, irisin, an exercise-induced myokine, promotes neuroplasticity and cognitive function through BDNF signaling. Irisin and muscle-generated BDNF may mediate the positive effects of physical activity against some aspects of AD pathophysiology through the interaction of exercise with the gut microbial ecosystem, neural plasticity, anti-inflammatory signaling pathways, and neurogenesis. Understanding gut-muscle-brain interconnections hold promise for developing strategies to promote brain health, fight age-associated cognitive decline, and improve muscle health and longevity.

The role of semantic assessment in the differential diagnosis between late-life depression and Alzheimer's disease or amnestic mild cognitive impairment: systematic review and meta-analysis

OBJECT

The cognitive complaints encountered in late-life depression (LLD) make it difficult to distinguish from amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD) based on an analysis of neurocognitive disorders. The hypothesis of the early impairment of semantic memory in AD and aMCI is considered a potential differential cognitive clue, but the absence of this impairment has not yet been confirmed in  LLD.

METHOD

Based on the PRISMA method, we systematically seek neuropsychological assessments of individuals with LLD, the present study included 31 studies representing 3291 controls and 2820 people with LLD. Wherever possible, studies that tested simultaneously groups with LLD, AD (or aMCI) were also included. The results of the group of neuropsychological tasks relying on semantic memory were analyzed in two groups of tasks with high- or low-executive demand. The mean average effect of LLD was calculated and compared to the incremental effect of aMCI or AD on the scores. Linear regressions including education, age, and severity and type of depression were run to seek their power of prediction for the mean average effects.

RESULTS

LLD has a medium effect on scores at semantic and phonemic fluency and naming and a small average effect on the low-executive demand tasks. Differences in education is a predictor of the effect of LLD on phonemic fluency and naming but not on semantic fluency or on low-executive demand tasks. Except for semantic fluency, aMCI did not demonstrate an incremental effect on the scores compared to LLD, while AD did, for all the tasks except phonemic fluency.

CONCLUSION

Assessment of semantic memory can be a discriminating clue for the distinction between depression and Alzheimer's disease but some methodological variables are highly influential to the scores, especially education. However, high-executive semantic tasks alone do not allow us to clearly distinguish LLD from AD or aMCI, as both pathologies seem to have a largely dialectical influential relationship, but low-executive semantic tasks appear as more sensible to this pathological distinction.

Neuroimaging study of electroconvulsive therapy for depression

Electroconvulsive therapy (ECT) is an important treatment for depression. Although it is known as the most effective acute treatment for severe mood disorders, its therapeutic mechanism is still unclear. With the rapid development of neuroimaging technology, various neuroimaging techniques have been available to explore the alterations of the brain by ECT, such as structural magnetic resonance imaging, functional magnetic resonance imaging, magnetic resonance spectroscopy, positron emission tomography, single photon emission computed tomography, arterial spin labeling, etc. This article reviews studies in neuroimaging on ECT for depression. These findings suggest that the neurobiological mechanism of ECT may regulate the brain functional activity, and neural structural plasticity, as well as balance the brain's neurotransmitters, which finally achieves a therapeutic effect.

The heterogeneity of late-life depression and its pathobiology: a brain network dysfunction disorder

Depression is frequent in older individuals and is often associated with cognitive impairment and increasing risk of subsequent dementia. Late-life depression (LLD) has a negative impact on quality of life, yet the underlying pathobiology is still poorly understood. It is characterized by considerable heterogeneity in clinical manifestation, genetics, brain morphology, and function. Although its diagnosis is based on standard criteria, due to overlap with other age-related pathologies, the relationship between depression and dementia and the relevant structural and functional cerebral lesions are still controversial. LLD has been related to a variety of pathogenic mechanisms associated with the underlying age-related neurodegenerative and cerebrovascular processes. In addition to biochemical abnormalities, involving serotonergic and GABAergic systems, widespread disturbances of cortico-limbic, cortico-subcortical, and other essential brain networks, with disruption in the topological organization of mood- and cognition-related or other global connections are involved. Most recent lesion mapping has identified an altered network architecture with "depressive circuits" and "resilience tracts", thus confirming that depression is a brain network dysfunction disorder. Further pathogenic mechanisms including neuroinflammation, neuroimmune dysregulation, oxidative stress, neurotrophic and other pathogenic factors, such as β-amyloid (and tau) deposition are in discussion. Antidepressant therapies induce various changes in brain structure and function. Better insights into the complex pathobiology of LLD and new biomarkers will allow earlier and better diagnosis of this frequent and disabling psychopathological disorder, and further elucidation of its complex pathobiological basis is warranted in order to provide better prevention and treatment of depression in older individuals.

Source connectivity patterns in the default mode network differ between elderly golf-novices and non-golfers

Learning to play golf has high demands on attention and therefore may counteract age-related changes of functional brain networks. This cross-sectional study compared source connectivity in the Default Mode Network (DMN) between elderly golf novices and non-golfers. Four-minute resting-state electroencephalography (128 channels) from 22 elderly people (mean age 67 ± 4.3 years, 55% females) were recorded after completing a 22-week golf learning program or after having continued with normal life. Source connectivity was assessed after co-registration of EEG data with native MRI within pre-defined portions of the DMN in the beta band (14-25 Hz). Non-golfers had significantly higher source connectivity values in the anterior DMN compared to non-golfers. Exploratory correlation analyses did not indicate an association to cognitive performance in either group. Inverse correlations between a marker of external attention with source connectivity of the anterior DMN may suggest a trend in the golf group only, but have to be replicated in future studies. Clinical relevance of these findings remains to be elucidated, but the observed difference in the anterior DMN may provide a starting point to further investigate if and how learning golf may have an impact on physiological age-related cognitive changes.

Automatic diagnosis of late-life depression by 3D convolutional neural networks and cross-sample Entropy analysis from resting-state fMRI

Resting-state fMRI has been widely used in investigating the pathophysiology of late-life depression (LLD). Unlike the conventional linear approach, cross-sample entropy (CSE) analysis shows the nonlinear property in fMRI signals between brain regions. Moreover, recent advances in deep learning, such as convolutional neural networks (CNNs), provide a timely application for understanding LLD. Accurate and prompt diagnosis is essential in LLD; hence, this study aimed to combine CNN and CSE analysis to discriminate LLD patients and non-depressed comparison older adults based on brain resting-state fMRI signals. Seventy-seven older adults, including 49 patients and 28 comparison older adults, were included for fMRI scans. Three-dimensional CSEs with volumes corresponding to 90 seed regions of interest of each participant were developed and fed into models for disease classification and depression severity prediction. We obtained a diagnostic accuracy > 85% in the superior frontal gyrus (left dorsolateral and right orbital parts), left insula, and right middle occipital gyrus. With a mean root-mean-square error (RMSE) of 2.41, three separate models were required to predict depressive symptoms in the severe, moderate, and mild depression groups. The CSE volumes in the left inferior parietal lobule, left parahippocampal gyrus, and left postcentral gyrus performed best in each respective model. Combined complexity analysis and deep learning algorithms can classify patients with LLD from comparison older adults and predict symptom severity based on fMRI data. Such application can be utilized in precision medicine for disease detection and symptom monitoring in LLD.

An optimized MRI and PET based clinical protocol for improving the differential diagnosis of geriatric depression and Alzheimer's disease

Amyloid positron emission tomography (PET) and hippocampal volume derived from magnetic resonance imaging may be useful clinical biomarkers for differentiating between geriatric depression and Alzheimer's disease (AD). Here we investigated the incremental value of using hippocampal volume and 18F-flutemetmol amyloid PET measures in tandem and sequentially to improve discrimination in unclassified participants. Two approaches were compared in 41 participants with geriatric depression and 27 participants with probable AD: (1) amyloid and hippocampal volume combined in one model and (2) classification based on hippocampal volume first and then subsequent stratification using standardized uptake value ratio (SUVR)-determined amyloid positivity. Hippocampal volume and amyloid SUVR were significant diagnostic predictors of depression (sensitivity: 95%, specificity: 89%). 51% of participants were correctly classified according to clinical diagnosis based on hippocampal volume alone, increasing to 87% when adding amyloid data (sensitivity: 94%, specificity: 78%). Our results suggest that hippocampal volume may be a useful gatekeeper for identifying depressed individuals at risk for AD who would benefit from additional amyloid biomarkers when available.

Alteration of Whole Brain ALFF/fALFF and Degree Centrality in Adolescents With Depression and Suicidal Ideation After Electroconvulsive Therapy: A Resting-State fMRI Study

Major depressive disorder (MDD) is one of the most widespread mental disorders and can result in suicide. Suicidal ideation (SI) is strongly predictive of death by suicide, and electroconvulsive therapy (ECT) is effective for MDD, especially in patients with SI. In the present study, we aimed to determine differences in resting-state functional magnetic resonance imaging (rs-fMRI) in 14 adolescents aged 12–17 with MDD and SI at baseline and after ECT. All participants were administered the Hamilton Depression Scale (HAMD) and Beck Scale for Suicide Ideation (BSSI) and received rs-fMRI scans at baseline and after ECT. Following ECT, the amplitude of low frequency fluctuation (ALFF) and fractional ALFF (fALFF) significantly decreased in the right precentral gyrus, and the degree centrality (DC) decreased in the left triangular part of the inferior frontal gyrus and increased in the left hippocampus. There were significant negative correlations between the change of HAMD (ΔHAMD) and ALFF in the right precentral gyrus at baseline, and between the change of BSSI and the change of fALFF in the right precentral gyrus. The ΔHAMD was positively correlated with the DC value of the left hippocampus at baseline. We suggest that these brain regions may be indicators of response to ECT in adolescents with MDD and SI.

Systematic Review of Different Neuroimaging Correlates in Mild Cognitive Impairment and Alzheimer's Disease

Alzheimer's disease (AD) is a heterogeneous progressive neurocognitive disorder. Although different neuroimaging modalities have been used for the identification of early diagnostic and prognostic factors of AD, there is no consolidated view of the findings from the literature. Here, we aim to provide a comprehensive account of different neural correlates of cognitive dysfunction via magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), functional MRI (fMRI) (resting-state and task-related), positron emission tomography (PET) and magnetic resonance spectroscopy (MRS) modalities across the cognitive groups i.e., normal cognition, mild cognitive impairment (MCI), and AD. A total of 46 meta-analyses met the inclusion criteria, including relevance to MCI, and/or AD along with neuroimaging modality used with quantitative and/or functional data. Volumetric MRI identified early anatomical changes involving transentorhinal cortex, Brodmann area 28, followed by the hippocampus, which differentiated early AD from healthy subjects. A consistent pattern of disruption in the bilateral precuneus along with the medial temporal lobe and limbic system was observed in fMRI, while DTI substantiated the observed atrophic alterations in the corpus callosum among MCI and AD cases. Default mode network hypoconnectivity in bilateral precuneus (PCu)/posterior cingulate cortices (PCC) and hypometabolism/hypoperfusion in inferior parietal lobules and left PCC/PCu was evident. Molecular imaging revealed variable metabolite concentrations in PCC. In conclusion, the use of different neuroimaging modalities together may lead to identification of an early diagnostic and/or prognostic biomarker for AD.

Structural and functional neuroimaging of late-life depression: a coordinate-based meta-analysis

Several neuroimaging studies have investigated localized aberrations in brain structure, function or connectivity in late-life depression, but the ensuing results are equivocal and often conflicting. Here, we provide a quantitative consolidation of neuroimaging in late-life depression using coordinate-based meta-analysis by searching multiple databases up to March 2020. Our search revealed 3252 unique records, among which we identified 32 eligible whole-brain neuroimaging publications comparing 674 patients with 568 controls. The peak coordinates of group comparisons between the patients and the controls were extracted and then analyzed using activation likelihood estimation method. Our sufficiently powered analysis on all the experiments, and more homogenous subsections of the data (patients > controls, controls > patients, and functional imaging experiments) revealed no significant convergent regional abnormality in late-life depression. This inconsistency might be due to clinical and biological heterogeneity of LLD, as well as experimental (e.g., choice of tasks, image modalities) and analytic flexibility (e.g., preprocessing and analytic parameters), and distributed patterns of neural abnormalities. Our findings highlight the importance of clinical/biological heterogeneity of late-life depression, in addition to the need for more reproducible research by using pre-registered and standardized protocols on more homogenous populations to identify potential consistent brain abnormalities in late-life depression.

Genetic Overlap Between Alzheimer's Disease and Depression Mapped Onto the Brain

Background: Alzheimer's disease (AD) and depression are debilitating brain disorders that are often comorbid. Shared brain mechanisms have been implicated, yet findings are inconsistent, reflecting the complexity of the underlying pathophysiology. As both disorders are (partly) heritable, characterising their genetic overlap may provide aetiological clues. While previous studies have indicated negligible genetic correlations, this study aims to expose the genetic overlap that may remain hidden due to mixed directions of effects. Methods: We applied Gaussian mixture modelling, through MiXeR, and conjunctional false discovery rate (cFDR) analysis, through pleioFDR, to genome-wide association study (GWAS) summary statistics of AD (n = 79,145) and depression (n = 450,619). The effects of identified overlapping loci on AD and depression were tested in 403,029 participants of the UK Biobank (UKB) (mean age 57.21, 52.0% female), and mapped onto brain morphology in 30,699 individuals with brain MRI data. Results: MiXer estimated 98 causal genetic variants overlapping between the 2 disorders, with 0.44 concordant directions of effects. Through pleioFDR, we identified a SNP in the TMEM106B gene, which was significantly associated with AD (B = -0.002, p = 9.1 × 10-4) and depression (B = 0.007, p = 3.2 × 10-9) in the UKB. This SNP was also associated with several regions of the corpus callosum volume anterior (B > 0.024, p < 8.6 × 10-4), third ventricle volume ventricle (B = -0.025, p = 5.0 × 10-6), and inferior temporal gyrus surface area (B = 0.017, p = 5.3 × 10-4). Discussion: Our results indicate there is substantial genetic overlap, with mixed directions of effects, between AD and depression. These findings illustrate the value of biostatistical tools that capture such overlap, providing insight into the genetic architectures of these disorders.

Depression in Alzheimer's Disease: An Alternative Role for Selective Serotonin Reuptake Inhibitors?

Depression is a common co-morbidity seen in people with Alzheimer's disease (AD). However, the successful treatment of depressive symptoms in people with AD is rarely seen. In fact, multiple randomized controlled trials have shown selective serotonin reuptake inhibitors (SSRIs), the current best recommended treatment for depression, to be ineffective in treating depressive symptoms in people with AD. One explanation for this lack of treatment effect may be that depressive symptoms can reflect the progression of AD, rather than clinical depression and are a consequence of more severe neurodegeneration. This raises several questions regarding not only the efficacy of SSRIs in the treatment of depression in people with AD but also regarding the accuracy of diagnosis of depression in AD. However, there may be a rationale for the prescription of SSRIs in early AD. Even in the absence of depression, SSRIs have been shown to slow the conversion from mild cognitive impairment to AD. This may be attributed to the effect of SSRIs on the processing of amyloid-β precursor protein, which may cause a reduction in the accumulation of amyloid-β. Thus, although SSRIs may lack efficacy in treating depression in people with AD, they may hold therapeutic potential for treating and delaying the progression of AD especially if treatment begins in the early stages of AD. This article reviews the current consensus for SSRI treatment of depression in people with AD and highlights the possibility of SSRIs being a treatment option for delaying the progression of AD.

Is Losing One's Way a Sign of Cognitive Decay? Topographical Memory Deficit as an Early Marker of Pathological Aging

Spatial navigation tasks reveal small differences between normal and pathological aging and may thus disclose potential neuropsychological predictors of neurodegenerative diseases. The aim of our study was to investigate which navigational skills are compromised in the early phase of pathological aging as well as the extent to which they are compromised. We performed an extensive neuropsychological evaluation based on working memory and learning tasks (i.e., Corsi Block-Tapping Test and Walking Corsi Test) involving both reaching and navigational vista spaces. We also assessed spatial navigation skills in the real world by asking participants to perform route-learning and landmark-recognition tasks. We conducted a cross-sectional study on nineteen patients with a diagnosis of mild cognitive impairment (MCI) who displayed either an isolated memory deficit (single-domain amnestic MCI, MCIsd; N = 3) or a memory deficit associated with deficits in other cognitive functions (multi-domain MCI, MCImd; N = 16) as well as on nineteen healthy control participants. The groups' performances were compared by means of mixed factorial ANOVA and two-sample t-tests. We found that patients with MCI performed worse than controls, especially when they were required to learn spatial positions within the navigational vista space. Route-learning within the real environment was also impaired whereas landmark-recognition was spared. The same pattern of results emerged in the MCImd subgroup. Moreover, single case analyses on MCIsd patients revealed a dissociation between learning of spatial positions within navigational vista space and within reaching space. These results suggest that topographical learning is compromised in the early phase of MCIsd and MCImd and that spatial navigation tasks may be used to better characterize topographical disorientation in MCI patients as well as for the early diagnosis of pathological aging.

Evidence for Structural and Functional Alterations of Frontal-Executive and Corticolimbic Circuits in Late-Life Depression and Relationship to Mild Cognitive Impairment and Dementia: A Systematic Review

Depression is a risk factor for developing Alzheimer's disease and Related Dementia (ADRD). We conducted a systematic review between 2008 and October 2018, to evaluate the evidence for a conceptual mechanistic model linking depression and ADRD, focusing on frontal-executive and corticolimbic circuits. We focused on two neuroimaging modalities: diffusion-weighted imaging measuring white matter tract disruptions and resting-state functional MRI measuring alterations in network dynamics in late-life depression (LLD), mild cognitive impairment (MCI), and LLD+MCI vs. healthy control (HC) individuals. Our data synthesis revealed that in some but not all studies, impairment of both frontal-executive and corticolimbic circuits, as well as impairment of global brain topology was present in LLD, MCI, and LLD+MCI vs. HC groups. Further, posterior midline regions (posterior cingulate cortex and precuneus) appeared to have the most structural and functional alterations in all patient groups. Future cohort and longitudinal studies are required to address the heterogeneity of findings, and to clarify which subgroups of people with LLD are at highest risk for developing MCI and ADRD.

Linking late life depression and Alzheimer's disease: mechanisms and resilience

PURPOSE OF REVIEW

This review summarizes recent literature linking Alzheimer's disease (AD) and late life depression (LLD). It describes shared neurobiological features associated with both conditions, as well as factors that may increase resilience to onset and severity of cognitive decline and AD. Finally, we pose a number of future research directions toward improving detection, management, and treatment of both conditions.

RECENT FINDINGS

Epidemiological studies have consistently shown a significant relationship between LLD and AD, with support for depression as a prodromal feature of AD, a risk factor for AD, and observation of some shared risk factors underlying both disease processes. Three major neurobiological features shared by LLD and AD include neurodegeneration, disruption to cerebrovascular functioning, and increased levels of neuroinflammation. There are also potentially modifiable factors that can increase resilience to AD and LLD, including social support, physical and cognitive engagement, and cognitive reserve.

SUMMARY

We propose that, in the context of depression, neurobiological events, such as neurodegeneration, cerebrovascular disease, and neuroinflammation result in a brain that is more vulnerable to the consequences of the pathophysiological features of AD, lowering the threshold for the onset of the behavioral presentation of AD (i.e., cognitive decline and dementia). We discuss factors that can increase resilience to AD and LLD, including social support, physical and cognitive engagement, and cognitive reserve. We conclude with a discussion of future research directions.

The power of sample size through a multi-scanner approach in MR neuroimaging regression analysis: evidence from Alzheimer's disease with and without depression

The inconsistency of volumetric results often seen in MR neuroimaging studies can be partially attributed to small sample sizes and variable data analysis approaches. Increased sample size through multi-scanner studies can tackle the former, but combining data across different scanner platforms and field-strengths may introduce a variability factor capable of masking subtle statistical differences. To investigate the sample size effect on regression analysis between depressive symptoms and grey matter volume (GMV) loss in Alzheimer's disease (AD), a retrospective multi-scanner investigation was conducted. A cohort of 172 AD patients, with or without comorbid depressive symptoms, was studied. Patients were scanned with different imaging protocols in four different MRI scanners operating at either 1.5 T or 3.0 T. Acquired data were uniformly analyzed using the computational anatomy toolbox (CAT12) of the statistical parametric mapping (SPM12) software. Single- and multi-scanner regression analyses were applied to identify the anatomical pattern of correlation between GM loss and depression severity. A common anatomical pattern of correlation between GMV loss and increased depression severity, mostly involving sensorimotor areas, was identified in all patient subgroups imaged in different scanners. Analysis of the pooled multi-scanner data confirmed the above finding employing a more conservative statistical criterion. In the retrospective multi-scanner setting, a significant correlation was also exhibited for temporal and frontal areas. Increasing the sample size by retrospectively pooling multi-scanner data, irrespective of the acquisition platform and parameters employed, can facilitate the identification of anatomical areas with a strong correlation between GMV changes and depression symptoms in AD patients.

Behavioral and psychological symptoms in Alzheimer's dementia and vascular dementia

Behavioral and psychological symptoms of dementia (BPSD) are highly prevalent and represent a significant burden for patients and their caregivers. Early recognition and management of these symptoms is crucial as they are associated with increased risk of institutionalization, impairments in daily functioning, reduced quality of life, and more rapid progression to severe dementia. This chapter will discuss the pathophysiology, proposed diagnostic criteria, clinical features, and management of BPSD, including apathy, depression, agitation/aggression, psychosis, and sleep disturbances. Apathy and depression are the most common overall, and apathy is associated with high symptom severity likely because of its greater persistence. Symptoms such as agitation, aggression, hallucinations, and delusions may be especially distressing and dangerous to patients and caregivers. Nonpharmacologic management should be considered first-line therapy in most cases due to the modest and inconsistent evidence base for pharmacologic agents and greater risk of harm. However, the judicious use of pharmacologic agents may be warranted when symptoms are dangerous and/or severely distressing.

A supplementary functional connectivity microstate attached to the default mode network in depression revealed by resting-state magnetoencephalography

Default mode network (DMN) has discernable involvement in the representation of negative, self-referential information in depression. Both increased and decreased resting-state functional connectivity between the anterior and posterior DMN have been observed in depression. These conflicting connectivity differences necessitated further exploration of the resting-state DMN dysfunction in depression. Hence, we investigated the time-varying dynamic interactions within the DMN via functional connectivity microstates in a sub-second level. 25 patients with depression and 25 matched healthy controls were enrolled in the MEG analysis. Spherical K-means algorithms embedded within an iterative optimization frame were applied to sliding windowed correlation matrices, resulting in sub-second alternations of two functional connectivity microstates for groups and highlighting the presence of functional variability. In the power dominant state, depressed patients showed a transient decreased pattern that reflected inter/intra-subnetwork deregulation. A supplementary negatively correlated state simultaneously presented with increased connectivity between the ventromedial prefrontal cortex (vmPFC) and the posterior cingulate cortex (PCC), two core nodes for the anterior and posterior DMN respectively. Additionally, depressed patients stayed longer in the supplementary microstate compared to healthy controls. During the time spent in the supplementary microstate, an attempt to compensate for the aberrant effect of vmPFC on PCC across DMN subnetworks was possibly made to balance the self-related processes disturbed by the dominant pattern. The functional compensation mechanism of the supplementary microstate attached to the dominant disrupted one provided a possible explanation to the existing inconsistent findings between the anterior and posterior DMN in depression.

Separating Symptomatic Alzheimer's Disease from Depression based on Structural MRI

Older patients with depression or Alzheimer’s disease (AD) at the stage of early dementia or mild cognitive impairment may present with objective cognitive impairment, although the pathology and thus therapy and prognosis differ substantially. In this study, we assessed the potential of an automated algorithm to categorize a test set of 65 T1-weighted structural magnetic resonance images (MRI). A convenience sample of elderly individuals fulfilling clinical criteria of either AD (n = 28) or moderate and severe depression (n = 37) was recruited from different settings to assess the potential of the pattern recognition method to assist in the differential diagnosis of AD versus depression. We found that our algorithm learned discriminative patterns in the subject’s grey matter distribution reflected by an area under the receiver operator characteristics curve of up to 0.83 (confidence interval ranged from 0.67 to 0.92) and a balanced accuracy of 0.79 for the separation of depression from AD, evaluated by leave-one-out cross validation. The algorithm also identified consistent structural differences in a clinically more relevant scenario where the data used during training were independent from the data used for evaluation and, critically, which included five possible diagnoses (specifically AD, frontotemporal dementia, Lewy body dementia, depression, and healthy aging). While the output was insufficiently accurate to use it directly as a means for classification when multiple classes are possible, the continuous output computed by the machine learning algorithm differed between the two groups that were investigated. The automated analysis thus could complement, but not replace clinical assessments.

Factors associated with brain volume in major depression in older adults without dementia: results from a large autopsy study

OBJECTIVE

We examined brain volume and atrophy in individuals with major depressive disorder (MDD) without dementia that were referred to a large autopsy service. We also examined potential risk factors for brain atrophy, including demographics and clinical variables.

METHODS

In this study, 1373 participants (787 male) aged 50 years or older who died from natural causes were included. Participants with no reliable informant, with cognitive impairment or dementia, with a medical history of severe chronic disease, or with prolonged agonal state were excluded. Presence of MDD at least once in their lifetime was defined according to the Structured Clinical Interview for DSM. Brain volume was measured immediately after removal from the skull.

RESULTS

Mean age at death was 68.6 ± 11.6, and MDD was present in 185 (14%) individuals. Smaller brain volume was associated with older age (p < 0.001), lower education (years; p < 0.001), hypertension (p = 0.001), diabetes (p = 0.006), and female gender (p < 0.001). In the multivariate analysis adjusted for sociodemographics and cardiovascular risk factors, smaller brain volume was not associated with major depression (β = -0.86, 95% CI = -26.50 to 24.77, p = 0.95).

CONCLUSIONS

In this large autopsy study of older adults, MDD was not associated with smaller brain volumes. Regardless of the presence of MDD, in this sample of older adults without dementia, we found that smaller brain volumes were associated with risk factors for brain neurodegeneration such as older age, diabetes, hypertension, and lower education. Copyright © 2017 John Wiley & Sons, Ltd.

A specific pattern of gray matter atrophy in Alzheimer's disease with depression

Considering the high incidence of depressive symptoms in Alzheimer's disease (AD), we conducted a large-sample study to investigate the pattern of gray matter (GM) abnormalities that differentiates depressive from non-depressive AD patients. We included 201 AD patients who underwent MRI assessment and categorized them into depressive and non-depressive subgroups based on the Geriatric Depression Scale (GDS; cut-off score: ≤9). We performed whole-brain voxel-based morphometry analysis in 173 patients after MRI quality control and used between-group comparisons and regression analysis models to analyze the volumetric data controlling for nuisance variables. Depressive AD patients had extensive GM volume loss mainly in the paracentral region, specifically in post- and pre-central gyrus, supplementary motor areas and thalamus compared to non-depressive patients. Similar findings were obtained for the group of 173 patients using regression analysis and GDS score as predictor variable. We provided the first clear demonstration of a unique pattern of GM atrophy that characterizes AD patients with depression which is consistent with regions implicated in the phenomenon of psychomotor retardation that characterizes depression.

Distinguishing Depressive Pseudodementia from Alzheimer Disease: A Comparative Study of Hippocampal Volumetry and Cognitive Tests

Background and Aim

Depressive pseudodementia (DPD) is a condition which may develop secondary to depression. The aim of this study was to contribute to the differential diagnosis between Alzheimer disease (AD) and DPD by comparing the neurocognitive tests and hippocampal volume.

Materials and Methods

Patients who met criteria of AD/DPD were enrolled in the study. All patients were assessed using the Wechsler Memory Scale (WMS), clock-drawing test, Stroop test, Benton Facial Recognition Test (BFRT), Boston Naming Test, Mini-Mental State Examination (MMSE), and Geriatric Depression Scale (GDS). Hippocampal volume was measured by importing the coronal T1-weighted magnetic resonance images to the Vitrea 2 workstation.

Results

A significant difference was found between the AD and DPD groups on the WMS test, clock-drawing test, Stroop test, Boston Naming Test, MMSE, GDS, and left hippocampal volume. A significant correlation between BFRT and bilateral hippocampal volumes was found in the AD group. No correlation was found among parameters in DPD patients.

Conclusions

Our results suggest that evaluation of facial recognition and left hippocampal volume may provide more reliable evidence for distinguishing DPD from AD. Further investigations combined with functional imaging techniques including more patients are needed.

The Global ECT-MRI Research Collaboration (GEMRIC): Establishing a multi-site investigation of the neural mechanisms underlying response to electroconvulsive therapy

Major depression, currently the world's primary cause of disability, leads to profound personal suffering and increased risk of suicide. Unfortunately, the success of antidepressant treatment varies amongst individuals and can take weeks to months in those who respond. Electroconvulsive therapy (ECT), generally prescribed for the most severely depressed and when standard treatments fail, produces a more rapid response and remains the most effective intervention for severe depression. Exploring the neurobiological effects of ECT is thus an ideal approach to better understand the mechanisms of successful therapeutic response. Though several recent neuroimaging studies show structural and functional changes associated with ECT, not all brain changes associate with clinical outcome. Larger studies that can address individual differences in clinical and treatment parameters may better target biological factors relating to or predictive of ECT-related therapeutic response. We have thus formed the Global ECT-MRI Research Collaboration (GEMRIC) that aims to combine longitudinal neuroimaging as well as clinical, behavioral and other physiological data across multiple independent sites. Here, we summarize the ECT sample characteristics from currently participating sites, and the common data-repository and standardized image analysis pipeline developed for this initiative. This includes data harmonization across sites and MRI platforms, and a method for obtaining unbiased estimates of structural change based on longitudinal measurements with serial MRI scans. The optimized analysis pipeline, together with the large and heterogeneous combined GEMRIC dataset, will provide new opportunities to elucidate the mechanisms of ECT response and the factors mediating and predictive of clinical outcomes, which may ultimately lead to more effective personalized treatment approaches.

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A global collaboration for longitudinal neuroimaging of ECT was established.

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A secure data portal with individual-patient level data.

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The feasibility of a standardized image analysis pipeline is demonstrated.

Left frontal cortex connectivity underlies cognitive reserve in prodromal Alzheimer disease

OBJECTIVE

To test whether higher global functional connectivity of the left frontal cortex (LFC) in Alzheimer disease (AD) is associated with more years of education (a proxy of cognitive reserve [CR]) and mitigates the association between AD-related fluorodeoxyglucose (FDG)-PET hypometabolism and episodic memory.

METHODS

Forty-four amyloid-PET-positive patients with amnestic mild cognitive impairment (MCI-Aβ+) and 24 amyloid-PET-negative healthy controls (HC) were included. Voxel-based linear regression analyses were used to test the association between years of education and FDG-PET in MCI-Aβ+, controlled for episodic memory performance. Global LFC (gLFC) connectivity was computed through seed-based resting-state fMRI correlations between the LFC (seed) and each voxel in the gray matter. In linear regression analyses, education as a predictor of gLFC connectivity and the interaction of gLFC connectivity × FDG-PET hypometabolism on episodic memory were tested.

RESULTS

FDG-PET metabolism in the precuneus was reduced in MCI-Aβ+ compared to HC (p = 0.028), with stronger reductions observed in MCI-Aβ+ with more years of education (p = 0.006). In MCI-Aβ+, higher gLFC connectivity was associated with more years of education (p = 0.021). At higher levels of gLFC connectivity, the association between precuneus FDG-PET hypometabolism and lower memory performance was attenuated (p = 0.027).

CONCLUSIONS

Higher gLFC connectivity is a functional substrate of CR that helps to maintain episodic memory relatively well in the face of emerging FDG-PET hypometabolism in early-stage AD.

Disrupted Interhemispheric Synchrony in Default Mode Network Underlying the Impairment of Cognitive Flexibility in Late-Onset Depression

The intuitive association between cognitive impairment and aberrant functional activity in the brain network has prompted interest in exploring the role of functional connectivity in late-onset depression (LOD). The relationship of altered voxel-mirrored homotopic connectivity (VMHC) and cognitive dysfunction in LOD is not yet well understood. This study was designed to examine the implicit relationship between the disruption of interhemispheric functional coordination and cognitive impairment in LOD. LOD patients (N = 31) and matched healthy controls (HCs; N = 37) underwent neuropsychological tests and functional magnetic resonance imaging (fMRI) in this study. The intergroup difference of interhemispheric coordination was determined by calculating VMHC value in the whole brain. The neuro-behavioral relevancy approach was applied to explore the association between disrupted VMHC and cognitive measures. Receiver operating characteristic (ROC) curve analysis was used to determine the capability of disrupted regional VMHC to distinguish LOD. Compared to the HC group, significantly attenuated VMHC in the superior frontal gyrus (SFG), superior temporal gyrus (STG), posterior cerebellar lobe (CePL) and post- and precentral gyri were observed in the bilateral brain of LOD patients. The interhemispheric asynchrony in bilateral CePLs was positively correlated with the performance of trail making test B (TMT-B) in LOD patients (r = 0.367, P = 0.040). ROC analysis revealed that regions with abnormal VMHC could efficiently distinguish LOD from HCs (Area Under Curve [AUC] = 0.90, P < 0.001). Altered linkage patterns of intrinsic homotopic connectivity and impaired cognitive flexibility was first investigated in LOD, and it would provide a novel clue for revealing the neural substrates underlying cognitive impairment in LOD.

Resting-state abnormalities in amnestic mild cognitive impairment: a meta-analysis

Amnestic mild cognitive impairment (aMCI) is a prodromal stage of Alzheimer's disease (AD). As no effective drug can cure AD, early diagnosis and intervention for aMCI are urgently needed. The standard diagnostic procedure for aMCI primarily relies on subjective neuropsychological examinations that require the judgment of experienced clinicians. The development of other objective and reliable aMCI markers, such as neural markers, is therefore required. Previous neuroimaging findings revealed various abnormalities in resting-state activity in MCI patients, but the findings have been inconsistent. The current study provides an updated activation likelihood estimation meta-analysis of resting-state functional magnetic resonance imaging (fMRI) data on aMCI. The authors searched on the MEDLINE/PubMed databases for whole-brain resting-state fMRI studies on aMCI published until March 2015. We included 21 whole-brain resting-state fMRI studies that reported a total of 156 distinct foci. Significant regional resting-state differences were consistently found in aMCI patients relative to controls, including the posterior cingulate cortex, right angular gyrus, right parahippocampal gyrus, left fusiform gyrus, left supramarginal gyrus and bilateral middle temporal gyri. Our findings support that abnormalities in resting-state activities of these regions may serve as neuroimaging markers for aMCI.

Multilevel Deficiency of White Matter Connectivity Networks in Alzheimer's Disease: A Diffusion MRI Study with DTI and HARDI Models

Alzheimer's disease (AD) is the most common form of dementia in elderly people. It is an irreversible and progressive brain disease. In this paper, we utilized diffusion-weighted imaging (DWI) to detect abnormal topological organization of white matter (WM) structural networks. We compared the differences between WM connectivity characteristics at global, regional, and local levels in 26 patients with probable AD and 16 normal control (NC) elderly subjects, using connectivity networks constructed with the diffusion tensor imaging (DTI) model and the high angular resolution diffusion imaging (HARDI) model, respectively. At the global level, we found that the WM structural networks of both AD and NC groups had a small-world topology; however, the AD group showed a significant decrease in both global and local efficiency, but an increase in clustering coefficient and the average shortest path length. We further found that the AD patients had significantly decreased nodal efficiency at the regional level, as well as weaker connections in multiple local cortical and subcortical regions, such as precuneus, temporal lobe, hippocampus, and thalamus. The HARDI model was found to be more advantageous than the DTI model, as it was more sensitive to the deficiencies in AD at all of the three levels.

Mood disorders in the elderly: prevalence, functional impact, and management challenges

Despite the lower prevalence of severe mood disorders in the elderly as compared to younger adults, late-life depression and bipolar disorder (BD) are more strongly associated with negative outcomes related to the presence of medical comorbidities, cognitive deficits, and increased suicide risk and overall mortality. The mechanisms that contribute to these associations are probably multifactorial, involving pathological factors related directly and indirectly to the disease itself, ranging from biological to psychosocial factors. Most of the accumulated knowledge on the nature of these associations derives from naturalistic and observational studies, and controlled data are still scarce. Nonetheless, there has clearly been a recent growth of the scientific interest on late-life BD and geriatric depression. In the present study, we review the most relevant studies on prevalence, clinical presentation, and cognitive/functional impact of mood disorders in elderly. Several clinical-epidemiological studies were dedicated to the study of the prevalence of mood disorders in old age in distinct settings; however, fewer studies investigated the underlying neurobiological findings and treatment specificities in late-life depression and BD. In the present study, we further discuss the implications of these findings on the management of mood disorders in older adults.