Depressive Symptoms and Small Hippocampal Volume Accelerate the Progression to Dementia from Mild Cognitive Impairment

Depression and Agitation Factors Are Related to Regional Brain Atrophy and Faster Longitudinal Cognitive Decline in Mild Cognitive Impairment

BACKGROUND

Neuropsychiatric symptoms (NPS) are a common aspect of Alzheimer's disease (AD). Multiple studies have investigated its brain correlates, but it still remains unclear how they relate with brain atrophy in mild cognitive impairment (MCI).

OBJECTIVE

Our objective was to investigate brain volume in MCI patients as a function of NPS.

METHODS

We measured grey matter volume, neuropsychological status and NPS (Neuropsychiatric Inventory, NPI), in a sample of 81 MCI patients (43 females). Participants were divided in groups depending on presence (NPS+) or absence (NPS-) of NPS and on type of NPS.

RESULTS

We found lower volume of left temporal pole in patients with depression compared to NPS- (p = 0.012), and in patients with agitation compared to NPS- in the right middle occipital gyrus (p = 0.003). We also found a significant correlation between volume of left temporal pole and MMSE (r (78)  = 0.232, p = 0.019). Finally, NPS+ presented lower cross-sectional cognitive level than NPS- (t (79)  = 1.79, p = 0.038), and faster cognitive decline (t (48)  = -1.74, p = 0.044).

CONCLUSIONS

Our results support the colocalization of structural damage as a possible mechanism underlying the relationship between MCI and depression and provide novel evidence regarding agitation. Moreover, our longitudinal evidence highlights the relevance of an adequate identification of NPS in MCI patients to identify those at risk of faster cognitive decline.

Structural and functional differences in the brains of patients with MCI with and without depressive symptoms and their relations with Alzheimer's disease: an MRI study

Background

The mild cognitive impairment (MCI) stage among elderly individuals is very complex, and the level of diagnostic accuracy is far from ideal. Some studies have tried to improve the 'MCI due to Alzheimer's disease (AD)' classification by further stratifying these patients into subgroups. Depression-related symptoms may play an important role in helping to better define the MCI stage in elderly individuals.

Objective

In this work, we explored functional and structural differences in the brains of patients with nondepressed MCI (nDMCI) and patients with MCI with depressive symptoms (DMCI), and we examined how these groups relate to AD atrophy patterns and cognitive functioning.

Methods

Sixty-five participants underwent MRI exams and were divided into four groups: cognitively normal, nDMCI, DMCI, and AD. We compared the regional brain volumes, cortical thickness, and white matter microstructure measures using diffusion tensor imaging among groups. Additionally, we evaluated changes in functional connectivity using fMRI data.

Results

In comparison to the nDMCI group, the DMCI patients had more pronounced atrophy in the hippocampus and amygdala. Additionally, DMCI patients had asymmetric damage in the limbic-frontal white matter connection. Furthermore, two medial posterior regions, the isthmus of cingulate gyrus and especially the lingual gyrus, had high importance in the structural and functional differentiation between the two groups.

Conclusion

It is possible to differentiate nDMCI from DMCI patients using MRI techniques, which may contribute to a better characterization of subtypes of the MCI stage.

Cortical thinning in relation to impaired insight into illness in patients with treatment resistant schizophrenia

Impaired insight into illness is a common element of schizophrenia that contributes to treatment nonadherence and negative clinical outcomes. Previous studies suggest that impaired insight may arise from brain abnormalities. However, interpretations of these findings are limited due to small sample sizes and inclusion of patients with a narrow range of illness severity and insight deficits. In a large sample of patients with schizophrenia, the majority of which were designated as treatment-resistant, we investigated the associations between impaired insight and cortical thickness and subcortical volumes. A total of 94 adult participants with a schizophrenia spectrum disorder were included. Fifty-six patients (60%) had treatment-resistant schizophrenia. The core domains of insight were assessed with the VAGUS insight into psychosis scale. We obtained 3T MRI T1-weighted images, which were analysed using CIVET and MAGeT-Brain. Whole-brain vertex-wise analyses revealed impaired insight, as measured by VAGUS average scores, was related to cortical thinning in left frontotemporoparietal regions. The same analysis in treatment-resistant patients showed thinning in the same regions, even after controlling for age, sex, illness severity, and chlorpromazine antipsychotic dose equivalents. No association was found in non-treatment-resistant patients. Region-of-interest analyses revealed impaired general illness awareness was associated with cortical thinning in the left supramarginal gyrus when controlling for covariates. Reduced right and left thalamic volumes were associated with VAGUS symptom attribution and awareness of negative consequences subscale scores, respectively, but not after correction for multiple testing. Our results suggest impaired insight into illness is related to cortical thinning in left frontotemporoparietal regions in patients with schizophrenia, particularly those with treatment resistance where insight deficits may be more chronic.

Assessing the Role of Past Depression in Patients with Mild Cognitive Impairment, with and without Biomarkers for Alzheimer's Disease

Major depressive disorder (MDD) is a risk factor for Alzheimer's disease (AD). Cerebrovascular disease (CVD) is implicated in MDD and AD. Our study compared participants with AD positive and negative cerebrospinal fluid (CSF) biomarkers on neuropsychological performance, remitted MDD status, and CVD burden. Next, we compared AD-CSF biomarkers and white matter hyperintensities (WMH) burden among three groups: mild cognitive impairment (MCI) (n = 12), MCI with remitted MDD (MDD+MCI) (n = 12), and remitted MDD alone (MDD) (n = 7). Few participants (18%) with MCI+MDD exhibited AD(+) biomarkers. Nearly all participants had moderate-severe WMH. WMH may contribute to cognitive impairment or depression in MCI patients with AD(-) biomarkers.

(S)-N-Benzyl-1-phenyl-3,4-dihydroisoqunoline-2(1H)-carboxamide Derivatives, Multi-Target Inhibitors of Monoamine Oxidase and Cholinesterase: Design, Synthesis, and Biological Activity

A series of (S)-1-phenyl-3,4-dihydroisoquinoline-2(1H)-carboxamide derivatives was synthesized and evaluated for inhibitory activity against monoamine oxidase (MAO)-A and-B, acetylcholine esterase (AChE), and butyrylcholine esterase (BChE). Four compounds (2i, 2p, 2t, and 2v) showed good inhibitory activity against both MAO-A and MAO-B, and two compounds (2d and 2j) showed selective inhibitory activity against MAO-A, with IC₅₀ values of 1.38 and 2.48 µM, respectively. None of the compounds showed inhibitory activity against AChE; however, 12 compounds showed inhibitory activity against BChE. None of the active compounds showed cytotoxicity against L929cells. Molecular docking revealed several important interactions between the active analogs and amino acid residues of the protein receptors. This research paves the way for further study aimed at designing MAO and ChE inhibitors for the treatment of depression and neurodegenerative disorders.

Impact of migration status on incidence of depression in the middle-aged and elderly population in China: Exploring healthy migrant and salmon bias hypotheses from a mental health perspective

BACKGROUND

The healthy migrant and salmon bias hypotheses stipulate that those who are healthier are more likely to migrate (a selection effect) and unhealthy migrants have a greater tendency to return to their origin communities than healthier migrants. It remains unclear whether the hypotheses are relevant for mental health, although they have robust evidence for physical health. The current study expands the theoretical foundation underlying these hypotheses by exploring the impact of migration status on depression among the middle-aged and older population in China.

METHOD

Longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS) in 2011, 2013, 2015 and 2018 were used. Participants were divided into three groups, non-migrants, permanent migrants, and return-migrants according to their migration status. The Chinese version of 10-item Center for Epidemiologic Studies Depression Scale was used to assess clinically relevant depressive symptoms. Incidence were estimated by each migration status and compared across strata using log-rank tests. Cox regression models were fit to assess the relationship between migration status and depression incidence.

RESULTS

A total of 9264 middle-aged and elderly participants were included, of whom 7047 (76.1 %) were non-migrants, 1065 (11.5 %) were permanent migrants, and 1152 (12.4 %) were return-migrants, respectively. Incidence rates of depression by different migration statuses were 76.6/10³ person-years (73.7/10³-79.7/10³) in non-migrants, 62.9/10³ person-years (55.9/10³-70.6/10³) in permanent migrants, and 67.3/10³ person-years (60.7/10³-74.5/10³) in return-migrants. After controlling for covariates, only permanent migrants had significantly lower incidence of depression than non-migrants (HR: 0.85 (0.75, 0.96)). After stratifying by current place of residence, urban-permanent-migrants had a lower risk of depression than both rural and urban non-migrants, and the HRs and 95%CIs were 0.62 (0.52-0.74) and 0.81 (0.68-0.97).

LIMITATIONS

Migration statuses of participants may have changed over time, but due to the lack of raw data on migration status in 2013 and 2015, we used migration status at baseline. We were also not able to contextualize the migration experiences among those who migrated, and these trajectories may be heterogeneous.

CONCLUSION

Using depression as an indicator of mental health, the healthy migrant hypothesis was supported among middle-aged and elderly permanent migrants living in urban areas while the salmon bias hypothesis was not. Significant urban-rural inequities in mental health existed among different types of migrants. Especially among permanent migrants who have migrated and converted Hukou from their original registration place to their current residence.

Depression symptoms moderate the relationship between gray matter volumes and cognitive function in patients with mild cognitive impairment

Previous studies have demonstrated that decreased gray matter volume (GMV) correlates with cognitive function in elderly patients with mild cognitive impairment (MCI). However, it is unclear whether those correlations are present in MCI patients with depressive symptoms (MCID). This study investigated the association among depressive symptoms, GMV and cognitive function. We included 210 participants, namely, 70 elderly MCID patients, 70 MCI patients without depressive symptoms (MCIND) and 70 healthy controls (HCs). Voxel-based morphometry (VBM) was used to investigate the structural disruptions among the patients in the three groups, and correlation analysis was performed between the GMV of regions showing group differences and cognitive function. Moderation analyses were conducted to verify the conditional effect of depressive symptoms on the relationship between structural changes and cognitive function. We found decreased GMV in the bilateral fusiform gyrus, inferior temporal gyrus, parahippocampal gyrus, and hippocampus in the MCIND group compared to the HC group. Moreover, we identified decreased GMV in the bilateral fusiform gyrus in the elderly MCID patients compared with the elderly MCIND patients, which provides further insights into the neural mechanisms of depressive symptoms in patients with MCID. Most importantly, the severity of depressive symptoms moderated the positive correlation between the GMV of abnormal brain regions and cognitive function. Furthermore, this study is the first report of the moderating effect of depressive symptoms on the GMV of abnormal brain areas and cognitive function in patients with MCID, indicating the significance of clinical intervention in elderly MCI patients with depressive symptoms.

Neuroimaging-derived brain age is associated with life satisfaction in cognitively unimpaired elderly: A community-based study

With the widespread increase in elderly populations, the quality of life and mental health in old age are issues of great interest. The human brain changes with age, and the brain aging process is biologically complex and varies widely among individuals. In this cross-sectional study, to clarify the effects of mental health, as well as common metabolic factors (e.g., diabetes) on healthy brain aging in late life, we analyzed structural brain MRI findings to examine the relationship between predicted brain age and life satisfaction, depressive symptoms, resilience, and lifestyle-related factors in elderly community-living individuals with unimpaired cognitive function. We extracted data from a community-based cohort study in Arakawa Ward, Tokyo. T1-weighted images of 773 elderly participants aged ≥65 years were analyzed, and the predicted brain age of each subject was calculated by machine learning from anatomically standardized gray-matter images. Specifically, we examined the relationships between the brain-predicted age difference (Brain-PAD: real age subtracted from predicted age) and life satisfaction, depressive symptoms, resilience, alcohol consumption, smoking, diabetes, hypertension, and dyslipidemia. Brain-PAD showed significant negative correlations with life satisfaction (Spearman's rs= -0.102, p = 0.005) and resilience (rs= -0.105, p = 0.004). In a multiple regression analysis, life satisfaction (p = 0.038), alcohol use (p = 0.040), and diabetes (p = 0.002) were independently correlated with Brain-PAD. Thus, in the cognitively unimpaired elderly, higher life satisfaction was associated with a 'younger' brain, whereas diabetes and alcohol use had negative impacts on life satisfaction. Subjective life satisfaction, as well as the prevention of diabetes and alcohol use, may protect the brain from accelerated aging.

Beneficial effects of QTC-4-MeOBnE in an LPS-induced mouse model of depression and cognitive impairments: The role of blood-brain barrier permeability, NF-κB signaling, and microglial activation

Clinical and preclinical investigations have suggested a possible biological link betweenmajor depressive disorder (MDD) and Alzheimer's disease (AD). Therefore, a pharmacologic approach to treating MDD could be envisioned as a preventative therapy for some AD cases. In line with this, 1-(7-chloroquinolin-4-yl)-N-(4-methoxybenzyl)-5-methyl-1H-1,2,3-triazole-4 carboxamide (QTC-4-MeOBnE) is characterized as an inhibitor of β-secretase, glycogen synthase kinase 3β, and acetylcholinesterase and has also shown secondary effects underlying the modulation of neurogenesis and synaptic plasticity pathways. Therefore, we investigated the effects of QTC-4-MeOBnE treatment (0.1 or 1 mg/kg) on depressive-like behavior and cognitive impairments elicited by repeated injections of lipopolysaccharide (LPS; 250 μg/kg) in mice. Injections of LPS for seven days led to memory impairments and depressive-like behavior, as evidenced in the Y-maze/object recognition test and forced swimming/splash tests, respectively. However, these impairments were prevented in mice that, after the last LPS injection, were also treated with QTC-4-MeOBnE (1 mg/kg). This effect was associated with restoring blood-brain barrier permeability, reducing oxidative/nitrosative biomarkers, and decreasing neuroinflammation mediated NF-κB signaling in the hippocampus and cortex of the mice. To further investigate the involvement with NF-κB signaling, we evaluated the effects of QTC-4-MeOBnE on microglial cell activation through canonical and non-canonical pathways and the modulation of the involved components. Together, our findings highlight the pharmacological benefits of QTC-4-MeOBnE in a mouse model of sickness behavior and memory impairments, supporting the novel concept that since this molecule produces anti-depressant activity, it could also be beneficial for preventing AD onset and related dementias in subjects suffering from MDD through inflammatory pathway modulation.

Cortical thickness predicts remission of depression with antidepressants in patients with late-life depression and cognitive impairment

BACKGROUND

Depression (DEP) and cognitive impairment (CI) share etiological risk factors, anatomical underpinnings, and interact to produce deleterious treatment outcomes. Both DEP and CI exhibit altered patterns of cortical thickness which may impact the course of antidepressant treatment, though inconsistencies in directionality and affected brain regions have been reported. In this study, we examined the relationship between cortical thickness and treatment outcome in older adults with comorbid DEP-CI.

METHODS

55 patients with DEP-CI received baseline MRI scans as part of a larger clinical trial at NYSPI/Columbia University Medical Center and Duke University Medical Center. Mood was assessed using the Hamilton Depression Rating Scale. Patients received open antidepressant treatment for 8 weeks followed by another 8 weeks of the same medication or switch to another antidepressant for a total of 16 weeks. Cortical thickness was extracted using an automated brain segmentation program (FreeSurfer). Vertex-wise analyses evaluated the relationship between cortical thickness and treatment outcome.

RESULTS

Remitters exhibited diffuse clusters of greater cortical thickness and reduced cortical thickness compared to non-remitters. Thicker baseline middle frontal gyrus most consistently predicted greater likelihood and faster rate of remission. White matter hyperintensities and hippocampal volume were not associated with antidepressant treatment outcome.

LIMITATIONS

MRI was conducted at baseline only and sample size was small.

DISCUSSION

Cortical thickness predicts treatment remission and magnitude of early improvement. Results indicate that individuals with DEP-CI exhibit unique patterns of structural abnormalities compared to their depressed peers without CI that have consequences for their recovery with antidepressant treatment.

Using CatBoost algorithm to identify middle-aged and elderly depression, national health and nutrition examination survey 2011-2018

Depression is one of the most common mental health problems in middle-aged and elderly people. The establishment of risk factor-based depression risk assessment model is conducive to early detection and early treatment of high-risk groups of depression. Five machine learning models (logistic regression (LR); back propagation (BP); random forest (RF); support vector machines (SVM); category boosting (CatBoost) were used to evaluate the depression among 8374 middle-aged people and 4636 elderly people in the NHANES database from 2011 to 2018. In the 2011-2018 cycle, the estimated prevalence of depression was 8.97% in the middle-aged participants and 8.02% in the elderly participants. Among the middle-aged and elderly participants, CatBoost was the best model to identify depression, and its area under the working characteristic curve (AUC) reaches the highest. The second is LR model and SVM model, while the performance of BP and RF model was slightly worse. The primary influencing factor of depression in middle-aged male is alanine aminotransferase. All five machine learning models can identify the occurrence of depression in the NHANES data set through social demographics, lifestyle, laboratory data and other data of middle-aged and elderly people, and among five models, the CatBoost model performed best.

GPR39 protects against corticosterone-induced neuronal injury in hippocampal cells through the CREB-BDNF signaling pathway

BACKGROUND

The release of zinc from glutamatergic terminals in the hippocampal CA3 region can activate postsynaptic GPR39 receptors and regulate cognition and depression. However, the role and mechanism of GPR39 in the stress-induced depression is still poorly understood.

METHODS

In this study, hippocampal cells (HT-22) were treated with corticosterone (CORT). Then the effects of stress on the activity, mitochondrial function and apoptosis of HT-22 cells were observed. The effects of GPR39 on CORT-induced stress injury were analyzed by both siRNA and agonist (TC-G-1008).

RESULTS

Compared with the 500 nM CORT group, the cell viability, apoptosis, mitochondrial membrane potential, and expression levels of BCL-2, CREB and BDNF mRNA were significantly decreased in the GPR39 siRNA+500 nM CORT group, while the expression levels of caspase3, caspase9, AIF and BAX mRNA were significantly increased in the GPR39 siRNA+500 nM CORT group. Compared with the 1 μM CORTgroup, the cell viability, apoptosis, mitochondrial membrane potential, and expression levels of BCL-2, CREB and BDNF were significantly increased in the GPR39 agonist+1 μΜ CORT group, while the expression levels of caspase3, caspase9, AIF and BAX mRNA were significantly decreased in the GPR39 siRNA+500 nM CORT group. Compared with the control group, the mRNA and protein levels of GPR39, CREB and BDNF were significantly increased, and the mRNA and protein levels of CREB and BDNF were significantly decreased after 50 μM zinc sulfate treatment for 6 h.

CONCLUSIONS

GPR39 may play a neuroprotective role in CORT-induced cell injury via the improvement of CREB-BDNF expression, by inhibiting pro-apoptotic proteins and by upregulating anti-apoptotic proteins.

Prediction of Cognitive Decline in Temporal Lobe Epilepsy and Mild Cognitive Impairment by EEG, MRI, and Neuropsychology

Cognitive decline is a severe concern of patients with mild cognitive impairment. Also, in patients with temporal lobe epilepsy, memory problems are a frequently encountered problem with potential progression. On the background of a unifying hypothesis for cognitive decline, we merged knowledge from dementia and epilepsy research in order to identify biomarkers with a high predictive value for cognitive decline across and beyond these groups that can be fed into intelligent systems. We prospectively assessed patients with temporal lobe epilepsy (N = 9), mild cognitive impairment (N = 19), and subjective cognitive complaints (N = 4) and healthy controls (N = 18). All had structural cerebral MRI, EEG at rest and during declarative verbal memory performance, and a neuropsychological assessment which was repeated after 18 months. Cognitive decline was defined as significant change on neuropsychological subscales. We extracted volumetric and shape features from MRI and brain network measures from EEG and fed these features alongside a baseline testing in neuropsychology into a machine learning framework with feature subset selection and 5-fold cross validation. Out of 50 patients, 27 had a decline over time in executive functions, 23 in visual-verbal memory, 23 in divided attention, and 7 patients had an increase in depression scores. The best sensitivity/specificity for decline was 72%/82% for executive functions based on a feature combination from MRI volumetry and EEG partial coherence during recall of memories; 95%/74% for visual-verbal memory by combination of MRI-wavelet features and neuropsychology; 84%/76% for divided attention by combination of MRI-wavelet features and neuropsychology; and 81%/90% for increase of depression by combination of EEG partial directed coherence factor at rest and neuropsychology. Combining information from EEG, MRI, and neuropsychology in order to predict neuropsychological changes in a heterogeneous population could create a more general model of cognitive performance decline.

Neuroanatomical profiles of treatment-resistance in patients with schizophrenia spectrum disorders

Widespread structrual abnormalities in subcortical brain regions have been identified in patients with schizophrenia. However, only a few studies have examined the neuroanatomical profiles of patients with treatment-resistant schizophrenia. The aim of this study was to compare differences in subcortical and hippocampal volumes between: (i) treatment-resistant patients who are non-responders to both first-line antipsychotics and clozapine (URS), (ii) treatment-resistant patients who are non-responders to first-line antipsychotics but are responders to clozapine (CLZ-Resp), (iii) responders to first-line antipsychotics (FL-Resp), and (iv) healthy controls. T1-weighted images of 103 participants (27 URS, 29 CLZ-Resp, 21 FL-Resp, and 26 healthy controls) were obtained. Group differences in striatal, thalamic, globus pallidus, amygdala, and hippocampus volumes were examined. Multiple regression analyses were performed to examine the associations between subcortical and hippocampal volumes and participant characteristics. The FL-Resp group showed larger striatal and globus pallidus volumes compared to the URS group and larger post-commissural putamen and globus pallidus volumes compared to healthy controls. The URS group showed smaller thalamic volume compared to healthy controls. There were no subcortical or hippocampal volume differences between the URS and CLZ-Resp groups. Differences in subcortical and hippocampal structural volumes were not related to symptom severity or chlorpromazine antipsychotic dose equivalents. Our findings suggest different structural volume alterations in subcortical brain regions between treatment-resistant schizophrenia and responders to first-line antipsychotics. Whether subcortical structure compromise is a distinct pathophysiological marker of treatment-resistant schizophrenia, or a result of antipsychotic exposure, remains to be explored.

Structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with mild cognitive impairment

BACKGROUND

Mild cognitive impairment (MCI) due to Alzheimer's disease is the symptomatic predementia phase of Alzheimer's disease dementia, characterised by cognitive and functional impairment not severe enough to fulfil the criteria for dementia. In clinical samples, people with amnestic MCI are at high risk of developing Alzheimer's disease dementia, with annual rates of progression from MCI to Alzheimer's disease estimated at approximately 10% to 15% compared with the base incidence rates of Alzheimer's disease dementia of 1% to 2% per year.

OBJECTIVES

To assess the diagnostic accuracy of structural magnetic resonance imaging (MRI) for the early diagnosis of dementia due to Alzheimer's disease in people with MCI versus the clinical follow-up diagnosis of Alzheimer's disease dementia as a reference standard (delayed verification). To investigate sources of heterogeneity in accuracy, such as the use of qualitative visual assessment or quantitative volumetric measurements, including manual or automatic (MRI) techniques, or the length of follow-up, and age of participants. MRI was evaluated as an add-on test in addition to clinical diagnosis of MCI to improve early diagnosis of dementia due to Alzheimer's disease in people with MCI.

SEARCH METHODS

On 29 January 2019 we searched Cochrane Dementia and Cognitive Improvement's Specialised Register and the databases, MEDLINE, Embase, BIOSIS Previews, Science Citation Index, PsycINFO, and LILACS. We also searched the reference lists of all eligible studies identified by the electronic searches.

SELECTION CRITERIA

We considered cohort studies of any size that included prospectively recruited people of any age with a diagnosis of MCI. We included studies that compared the diagnostic test accuracy of baseline structural MRI versus the clinical follow-up diagnosis of Alzheimer's disease dementia (delayed verification). We did not exclude studies on the basis of length of follow-up. We included studies that used either qualitative visual assessment or quantitative volumetric measurements of MRI to detect atrophy in the whole brain or in specific brain regions, such as the hippocampus, medial temporal lobe, lateral ventricles, entorhinal cortex, medial temporal gyrus, lateral temporal lobe, amygdala, and cortical grey matter.

DATA COLLECTION AND ANALYSIS

Four teams of two review authors each independently reviewed titles and abstracts of articles identified by the search strategy. Two teams of two review authors each independently assessed the selected full-text articles for eligibility, extracted data and solved disagreements by consensus. Two review authors independently assessed the quality of studies using the QUADAS-2 tool. We used the hierarchical summary receiver operating characteristic (HSROC) model to fit summary ROC curves and to obtain overall measures of relative accuracy in subgroup analyses. We also used these models to obtain pooled estimates of sensitivity and specificity when sufficient data sets were available.

MAIN RESULTS

We included 33 studies, published from 1999 to 2019, with 3935 participants of whom 1341 (34%) progressed to Alzheimer's disease dementia and 2594 (66%) did not. Of the participants who did not progress to Alzheimer's disease dementia, 2561 (99%) remained stable MCI and 33 (1%) progressed to other types of dementia. The median proportion of women was 53% and the mean age of participants ranged from 63 to 87 years (median 73 years). The mean length of clinical follow-up ranged from 1 to 7.6 years (median 2 years). Most studies were of poor methodological quality due to risk of bias for participant selection or the index test, or both. Most of the included studies reported data on the volume of the total hippocampus (pooled mean sensitivity 0.73 (95% confidence interval (CI) 0.64 to 0.80); pooled mean specificity 0.71 (95% CI 0.65 to 0.77); 22 studies, 2209 participants). This evidence was of low certainty due to risk of bias and inconsistency. Seven studies reported data on the atrophy of the medial temporal lobe (mean sensitivity 0.64 (95% CI 0.53 to 0.73); mean specificity 0.65 (95% CI 0.51 to 0.76); 1077 participants) and five studies on the volume of the lateral ventricles (mean sensitivity 0.57 (95% CI 0.49 to 0.65); mean specificity 0.64 (95% CI 0.59 to 0.70); 1077 participants). This evidence was of moderate certainty due to risk of bias. Four studies with 529 participants analysed the volume of the total entorhinal cortex and four studies with 424 participants analysed the volume of the whole brain. We did not estimate pooled sensitivity and specificity for the volume of these two regions because available data were sparse and heterogeneous. We could not statistically evaluate the volumes of the lateral temporal lobe, amygdala, medial temporal gyrus, or cortical grey matter assessed in small individual studies. We found no evidence of a difference between studies in the accuracy of the total hippocampal volume with regards to duration of follow-up or age of participants, but the manual MRI technique was superior to automatic techniques in mixed (mostly indirect) comparisons. We did not assess the relative accuracy of the volumes of different brain regions measured by MRI because only indirect comparisons were available, studies were heterogeneous, and the overall accuracy of all regions was moderate.

AUTHORS' CONCLUSIONS

The volume of hippocampus or medial temporal lobe, the most studied brain regions, showed low sensitivity and specificity and did not qualify structural MRI as a stand-alone add-on test for an early diagnosis of dementia due to Alzheimer's disease in people with MCI. This is consistent with international guidelines, which recommend imaging to exclude non-degenerative or surgical causes of cognitive impairment and not to diagnose dementia due to Alzheimer's disease. In view of the low quality of most of the included studies, the findings of this review should be interpreted with caution. Future research should not focus on a single biomarker, but rather on combinations of biomarkers to improve an early diagnosis of Alzheimer's disease dementia.

Affective symptoms and AT(N) biomarkers in mild cognitive impairment and Alzheimer's disease: A systematic literature review

INTRODUCTION

Alzheimer's disease (AD) biomarkers such as amyloid, p-tau and neuronal injury markers have been associated with affective symptoms in cognitively impaired individuals, but results are conflicting.

METHODS

CINAHL, Embase, PsycINFO and PubMed were searched for studies evaluating AD biomarkers with affective symptoms in mild cognitive impairment and AD dementia. Studies were classified according to AT(N) research criteria.

RESULT

Forty-five abstracts fulfilled eligibility criteria, including in total 8,293 patients (41 cross-sectional studies and 7 longitudinal studies). Depression and night-time behaviour disturbances were not related to AT(N) markers. Apathy was associated with A markers (PET, not CSF). Mixed findings were reported for the association between apathy and T(N) markers; anxiety and AT(N) markers; and between agitation and irritability and A markers. Agitation and irritability were not associated with T(N) markers.

DISCUSSION

Whereas some AD biomarkers showed to be associated with affective symptoms in AD, most evidence was inconsistent. This is likely due to differences in study design or heterogeneity in affective symptoms. Directions for future research are given.

Evaluation of hippocampal volume and serum brain-derived neurotrophic factor as potential diagnostic markers of conversion from amnestic mild cognitive impairment to Alzheimer disease: A STROBE-compliant article

Amnestic mild cognitive impairment (aMCI) is a transitional stage between normal aging and Alzheimer disease (AD), and is associated with an increased risk of AD. Many studies have shown that apolipoprotein E epsilon 4 (APOE ε4) genotype is a major genetic predictor of AD progression, especially in patients with aMCI. However, the application of APOE genotyping in the diagnosis of MCI progressing to AD is limited by its low sensitivity and specificity, which often leads to high false-positive rate. The aim of this study was to evaluate serum brain-derived neurotrophic factor (BDNF) and hippocampal volume as predictors of aMCI to AD transition in APOE ε4 genotype patients.A total of 178 subjects were diagnosed with aMCI. The patients with aMCI that progressed to AD within 2 years were included in the MCI-AD group (n = 86), those maintaining an aMCI diagnosis after 2 years were placed in the MCI-MCI group (n = 92), and neurologically healthy age-matched individuals were set as controls (n = 90). APOE genotypes were determined. Blood samples from all subjects were drawn at baseline, 12 months, and 24 months for serum BNDF assessments. Hippocampal delineations were monitored by magnetic resonance imaging.Compared to control group, aMCI-AD patients (the patients with aMCI that progressed to AD within 2 years) exhibited worse performance on cognitive and neuropsychological batteries. Meanwhile, we found that aMCI-AD patients were associated with abnormally low serum BDNF level and greater hippocampal volume loss than MCI-MCI patients (patients maintaining an aMCI diagnosis after 2 years). Moreover, patients with aMCI who were carriers of APOE ε4 showed a notable decrease in serum BDNF and a significant reduction in hippocampal volume, especially in those who progressed to AD.The present study demonstrates that aMCI that evolves into AD in patients with the APOE ε4 genotype may be predicted by hippocampal volume and serum BDNF.

Clinical and radiological characteristics of early versus late mild cognitive impairment in patients with comorbid depressive disorder

OBJECTIVE

The classification of mild cognitive impairment (MCI) continues to be debated though it has recently been subtyped into late (LMCI) versus early (EMCI) stages. Older adults presenting with both a depressive disorder (DEP) and cognitive impairment (CI) represent a unique, understudied population. Our aim was to examine baseline characteristics of DEP-CI patients in the DOTCODE trial, a randomized controlled trial of open antidepressant treatment for 16 weeks followed by add-on donepezil or placebo for 62 weeks.

METHODS/DESIGN

Key inclusion criteria were diagnosis of major depression or dysthymic disorder with Hamilton Depression Rating Scale (HAM-D) score >14, and cognitive impairment defined by MMSE score ≥21 and impaired performance on the WMS-R Logical Memory II test. Patients were classified as EMCI or LMCI based on the 1.5 SD cutoff on tests of verbal memory, and compared on baseline clinical, neuropsychological, and anatomical characteristics.

RESULTS

Seventy-nine DEP-CI patients were recruited of whom 39 met criteria for EMCI and 40 for LMCI. The mean age was 68.9, and mean HAM-D was 23.0. Late mild cognitive impairment patients had significantly worse ADAS-Cog (P < .001), MMSE (P = .004), Block Design (P = .024), Visual Rep II (P = .006), CFL Animal (P = .006), UPSIT (P = .051), as well as smaller right hippocampal volume (P = .037) compared to EMCI patients. MRI indices of cerebrovascular disease did not differ between EMCI and LMCI patients.

CONCLUSIONS

Cognitive and neuronal loss markers differed between EMCI and LMCI among patients with DEP-CI, with LMCI being more likely to have the clinical and neuronal loss markers known to be associated with Alzheimer's disease.

Influence of Baseline Psychological Health on Muscle Pain During Atorvastatin Treatment

BACKGROUND

3-hydroxy-3-methylglutaryl coenzyme A reductase reductase inhibitors (statins) are generally well tolerated, with statin-associated muscle symptoms (SAMS) the most common side effect (~10%) seen in statin users. However, studies and clinical observations indicate that many of the self-reported SAMS appear to be nonspecific (ie, potentially not attributable to statins).

OBJECTIVE

Mental health and well-being influence self-perception of pain, so we sought to assess the effect of baseline well-being and depression on the development of muscle pain with 6 months of atorvastatin 80 mg/d (ATORVA) or placebo in healthy, statin-naive adults.

METHODS

The Psychological General Well-being Index (n = 83) and Beck Depression Inventory (n = 55) questionnaires were administered at baseline in participants (aged 59.5 ± 1.2 years) from the effect of Statins on Skeletal Muscle Function and Performance (STOMP) trial (NCT00609063). Muscle pain (Short-Form McGill Pain Questionnaire [SF-MPQ]), pain that interferes with daily life (Brief Pain Inventory [BPI]), and pain severity (BPI) were then measured before, throughout, and after treatment.

RESULTS

At baseline, there were no differences in well-being (Psychological General Well-being Index), depression (Beck Depression Inventory), or pain measures (SF-MPQ and BPI) (P values ≥ .05) between the placebo and ATORVA groups. Baseline well-being correlated negatively with baseline BPI pain severity (r = -0.290, P = .008). Baseline depression correlated with baseline pain (SF-MPQ; r = 0.314, P = .020). Baseline well-being and depression did not predict the change in pain severity or interference after 6 months among the total sample or between groups (P values ≥ .05).

CONCLUSION

Baseline well-being and depression were not significant predictors of pain after 6 months of ATORVA (P values ≥ .05). Thus, they do not appear to increase the risk of SAMS in otherwise healthy adults.

Depressive Symptoms are Associated with Progression to Dementia in Patients with Amyloid-Positive Mild Cognitive Impairment

BACKGROUND

Depressive symptoms are prevalent in patients with mild cognitive impairment (MCI) and are considered to be a risk factor for progression to dementia.

OBJECTIVE

The purpose of this study was to evaluate whether depressive symptoms in MCI promote disease progression in a manner related to amyloid status, and to determine the relationship between depressive symptoms and longitudinal cerebral structural changes.

METHODS

Baseline data for 336 patients with MCI (75 with depression and 261 without) from the Alzheimer's Disease Neuroimaging Initiative study were analyzed. All participants underwent comprehensive cognitive testing, volumetric magnetic resonance imaging (MRI), and [18F]AV45 positron emission tomography amyloid imaging. Depressive symptoms were measured using the Neuropsychiatric Inventory Questionnaire. A voxel-based morphometric analysis using volumetric brain MRI data was used to compare longitudinal structural changes related to depressive symptoms.

RESULTS

The conversion rate to dementia was different between patients with and without depression in amyloid-positive MCI (40.8% versus 19.7%, respectively; p = 0.006). Patients who were amyloid-positive at baseline also exhibited a greater degree of 2-year cognitive decline. Depression in amyloid-positive MCI was associated with longitudinal cortical atrophy in the left cingulate gyrus.

CONCLUSION

Our study indicates that the presence of depressive symptoms in patients with amyloid-positive MCI is associated with higher progression to dementia and longitudinal cortical atrophy.

A Review on the General Stability of Mood Disorder Diagnoses Along the Lifetime

PURPOSE OF REVIEW

The purpose of this review is to review the most recent literature regarding diagnostic stability of mood disorders, focusing on epidemiological, clinical-psychopathological, and neurobiological data for unipolar and bipolar affective disorders.

RECENT FINDINGS

Unipolar depression follows a chronic course in at least half of all cases and presents a considerable diagnostic stability across all age ranges. Studies using latent class analysis are allowing improved profiling of depressive subtypes and assessment of their prevalence. Advances have been made in our understanding of the neurobiological underpinnings of depression, with data highlighting the roles of amyloid deposits, the ApoE4 allele, and atrophy of the anterior hippocampus or frontal cortex. The diagnostic instability of bipolar disorder is manifest in the early years, seen in both the extent of diagnostic delay and the high rate of diagnostic conversion from unipolar depression. Regarding disruptive mood dysregulation disorder, we have little data to date, but those which exist indicate a high rate of comorbidity and minimal diagnostic stability for this disorder. Diagnostic stability varies substantially among mood disorders, which would be related to the validity of current diagnostic categories and our diagnostic accuracy.

Hippocampal and Clinical Trajectories of Mild Cognitive Impairment with Suspected Non-Alzheimer's Disease Pathology

Suspected non-Alzheimer's disease pathology (SNAP) characterizes individuals showing neurodegeneration (e.g., hypometabolism) without amyloid-β (Aβ). Findings from previous studies regarding clinical and structural trajectories of SNAP are inconsistent. Using data from the Alzheimer's Disease Neuroimaging Initiative, patients with amnestic mild cognitive impairment (MCI) were categorized into four groups: amyloid positive with hypometabolism (Aβ+ND+), amyloid only (Aβ+ND-), neither amyloid nor hypometabolism (Aβ-ND-), and SNAP (Aβ-ND+). Aβ+ND+(n = 33), Aβ+ND-(n = 32), and Aβ-ND-(n = 36) were matched to SNAP for age, gender, apolipoprotein E4 (apoE4) genotype, and scores on the Montreal Cognitive Assessment. Elderly controls (n = 40) were also matched to SNAP for age, gender, and apoE4 genotype. Longitudinal changes were compared across groups in terms of hippocampal volume, clinical symptoms, daily functioning, and cognitive functioning over a 2-year period. At baseline, no difference in cognition and functioning was observed between SNAP and Aβ+groups. SNAP showed worse clinical symptoms and impaired functioning at baseline compared to Aβ-ND-and controls. Two years of follow-up showed no differences in hippocampal volume changes between SNAP and any of the comparison groups. SNAP showed worse functional deterioration in comparison to Aβ-ND-and controls. However, Aβ+ND+ showed more severe changes in clinical symptoms in comparison to SNAP. Thus, patients with MCI and SNAP showed 1) more severe functional deterioration compared to Aβ-ND-and controls, 2) no differences with Aβ+ND-, and 3) less cognitive deterioration than Aβ+ND+. Future studies should investigate what causes SNAP, which is different from typical AD pathology and biomarker cascades.

Thioredoxin is not a marker for treatment-resistance depression but associated with cognitive function: An rTMS study

Elevated oxidative stress is known to play an important role in development of depression and cognitive dysfunction. To date, thioredoxin (TRX), an antioxidant protein, has been investigated as a marker for psychiatric disorders such as schizophrenia, bipolar disorder and autism but its relationship with depression is yet to be unknown. The aim of this study is to detect the TRX levels in patients with treatment-resistant depression (TRD), analyse the effect of rTMS (repetitive transcranial magnetic stimulation) application on TRX levels and display the relationship of TRX with cognitive areas. This study included 27 treatment-resistant unipolar depression patients and 29 healthy subjects. Patients were evaluated by Hamilton Depression Scale (HDRS), Hamilton Anxiety Scale (HARS) and Montreal Cognitive Assessment (MoCA) before and after rTMS application. 23 of TRD patients were applied high-frequency rTMS over left DLPFC for 2 to 4weeks and plasma TRX levels of patients and healthy subjects were measured. No significant difference was determined between the TRX levels of patients and healthy subjects (p>0.05). After rTMS application there were significant decrease in severity of depression (p<0.001) and anxiety (p<0.001), and explicit improvement in cognitive areas (delayed memory, visual-spatial/executive abilities and language points) (all p<0.05). No difference was detected in TRX levels of the patients after rTMS application (p>0.005). High language scores of the patients were found to be associated with high TRX levels (p<0.005). Our study indicates that TRX levels cannot be used as a marker for TRD or rTMS treatment in TRD. In spite of this TRX levels have a positive correlation with language functions of the patients of TRD. More extensive studies are required to clarify the mechanism of action of TRX and the effect of TRX on cognitive functions.

Combining SPECT and Quantitative EEG Analysis for the Automated Differential Diagnosis of Disorders with Amnestic Symptoms

Single photon emission computed tomography (SPECT) and Electroencephalography (EEG) have become established tools in routine diagnostics of dementia. We aimed to increase the diagnostic power by combining quantitative markers from SPECT and EEG for differential diagnosis of disorders with amnestic symptoms. We hypothesize that the combination of SPECT with measures of interaction (connectivity) in the EEG yields higher diagnostic accuracy than the single modalities. We examined 39 patients with Alzheimer's dementia (AD), 69 patients with depressive cognitive impairment (DCI), 71 patients with amnestic mild cognitive impairment (aMCI), and 41 patients with amnestic subjective cognitive complaints (aSCC). We calculated 14 measures of interaction from a standard clinical EEG-recording and derived graph-theoretic network measures. From regional brain perfusion measured by 99mTc-hexamethyl-propylene-aminoxime (HMPAO)-SPECT in 46 regions, we calculated relative cerebral perfusion in these patients. Patient groups were classified pairwise with a linear support vector machine. Classification was conducted separately for each biomarker, and then again for each EEG- biomarker combined with SPECT. Combination of SPECT with EEG-biomarkers outperformed single use of SPECT or EEG when classifying aSCC vs. AD (90%), aMCI vs. AD (70%), and AD vs. DCI (100%), while a selection of EEG measures performed best when classifying aSCC vs. aMCI (82%) and aMCI vs. DCI (90%). Only the contrast between aSCC and DCI did not result in above-chance classification accuracy (60%). In general, accuracies were higher when measures of interaction (i.e., connectivity measures) were applied directly than when graph-theoretical measures were derived. We suggest that quantitative analysis of EEG and machine-learning techniques can support differentiating AD, aMCI, aSCC, and DCC, especially when being combined with imaging methods such as SPECT. Quantitative analysis of EEG connectivity could become an integral part for early differential diagnosis of cognitive impairment.

The Effects of Cortical Hypometabolism and Hippocampal Atrophy on Clinical Trajectories in Mild Cognitive Impairment with Suspected Non-Alzheimer's Pathology: A Brief Report

The clinical and structural trajectories of suspected non-Alzheimer' pathology (SNAP) remain elusive due to its heterogeneous etiology. Baseline and longitudinal clinical (global cognition, daily functioning, symptoms of dementia, and learning memory) and hippocampal volume trajectories over two years were compared between patients with amnestic mild cognitive impairment (aMCI) with SNAP with reduced hippocampal volumes (SNAP+HIPPO) and aMCI patients with SNAP without reduced hippocampal volumes. SNAP+HIPPO showed overall worse baseline cognitive functions. Longitudinally, SNAP+HIPPO showed faster deterioration of clinical symptoms of dementia. Having both hippocampal atrophy and cortical hypometabolism without amyloid pathology may exacerbate symptoms of dementia in aMCI.

Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials

INTRODUCTION

The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued development and standardization of methodologies for biomarkers and has provided an increased depth and breadth of data available to qualified researchers. This review summarizes the over 400 publications using ADNI data during 2014 and 2015.

METHODS

We used standard searches to find publications using ADNI data.

RESULTS

(1) Structural and functional changes, including subtle changes to hippocampal shape and texture, atrophy in areas outside of hippocampus, and disruption to functional networks, are detectable in presymptomatic subjects before hippocampal atrophy; (2) In subjects with abnormal β-amyloid deposition (Aβ+), biomarkers become abnormal in the order predicted by the amyloid cascade hypothesis; (3) Cognitive decline is more closely linked to tau than Aβ deposition; (4) Cerebrovascular risk factors may interact with Aβ to increase white-matter (WM) abnormalities which may accelerate Alzheimer's disease (AD) progression in conjunction with tau abnormalities; (5) Different patterns of atrophy are associated with impairment of memory and executive function and may underlie psychiatric symptoms; (6) Structural, functional, and metabolic network connectivities are disrupted as AD progresses. Models of prion-like spreading of Aβ pathology along WM tracts predict known patterns of cortical Aβ deposition and declines in glucose metabolism; (7) New AD risk and protective gene loci have been identified using biologically informed approaches; (8) Cognitively normal and mild cognitive impairment (MCI) subjects are heterogeneous and include groups typified not only by "classic" AD pathology but also by normal biomarkers, accelerated decline, and suspected non-Alzheimer's pathology; (9) Selection of subjects at risk of imminent decline on the basis of one or more pathologies improves the power of clinical trials; (10) Sensitivity of cognitive outcome measures to early changes in cognition has been improved and surrogate outcome measures using longitudinal structural magnetic resonance imaging may further reduce clinical trial cost and duration; (11) Advances in machine learning techniques such as neural networks have improved diagnostic and prognostic accuracy especially in challenges involving MCI subjects; and (12) Network connectivity measures and genetic variants show promise in multimodal classification and some classifiers using single modalities are rivaling multimodal classifiers.

DISCUSSION

Taken together, these studies fundamentally deepen our understanding of AD progression and its underlying genetic basis, which in turn informs and improves clinical trial design.

Overlay of Late-Life Depression and Cognitive Impairment

This article appraises several facets of the linkage between depression and cognitive impairment, including dementia, mild cognitive impairment, and vascular dementia. Potential mechanisms for this association are examined. This review was crafted to be extensive but not exhaustive. The authors searched PubMed, using the terms depression, late-life depression, cognitive impairment, and dementia. Articles included are seminal articles from the field as well as representative, heuristic studies. A link between depression and cognitive impairment was found. Depression likely serves as both a risk factor and a prodromal symptom of dementia. Mechanisms whereby depression could induce cognitive impairment include hippocampal atrophy, alterations in glucocorticoid secretion, cerebrovascular compromise, deposition of β-amyloid plaques, chronic inflammation, apolipoprotein E status, and deficits of nerve growth factors. This article will benefit the practicing clinician by increasing awareness of the links between depression and dementia and encouraging greater emphasis on screening for cognitive impairment among individuals with depression or a history of depression.

Risk Factors for Cognitive Impairment in Fragile X-Associated Tremor/Ataxia Syndrome

Fragile X-associated tremor/ataxia syndrome (FXTAS) is a late-onset neurodegenerative disease with motor, psychiatric, and cognitive manifestations that occurs in carriers of the fragile X mental retardation 1 ( FMR1) gene premutations. This was a retrospective chart review of 196 individuals (127 men and 69 women) with FXTAS. Forty-six (23%) participants were cognitively impaired, of whom 19 (10%) had dementia. Risk factors for dementia were examined (CGG repeat size; alcohol, benzodiazepine, and opioid use; diabetes; hyperlipidemia; hypertension; hypothyroidism; obesity; sleep apnea; surgeries with general anesthesia; depression; family history of dementia). Thirteen individuals with FXTAS and dementia were then compared to 13 cognitively intact individuals matched on age, gender, and FXTAS stage. CGG repeat size was significantly higher (mean = 98.5, standard deviation [SD] = 22.2) in the dementia group, compared to the cognitively intact group (mean = 81.6, SD = 11.5; P = .0256). These results show that CGG repeat size is a risk factor for FXTAS dementia.