Parietal-hippocampal rTMS improves cognitive function in Alzheimer's disease and increases dynamic functional connectivity of default mode network.

Parietal-hippocampal repetitive transcranial magnetic stimulation (rTMS) improves cognitive function in Alzheimer's disease (AD), however, the underlying therapeutic mechanism has not been elucidated. A double-blind, randomized, sham-controlled parietal-hippocampal rTMS trial (five sessions/week for a total of 10 sessions) of mild-to-moderate AD patients was conducted in the study. High-frequency rTMS was applied to a subject-specific left lateral parietal region with the highest functional connectivity with the hippocampus based on resting-state fMRI. A multimodal MRI scan and a complete neuropsychological battery of tests were conducted at baseline, immediately after the intervention and 12-week follow-up after the rTMS treatment. Compared to sham treatment (n = 27), patients undergoing active rTMS treatment (n = 29) showed higher Mini Mental State Examination (MMSE) score and dynamic functional connectivity (dFC) magnitude of the default mode network (DMN) after two weeks of rTMS treatment, but not at 12-week follow-up. A significant positive correlation was observed between changes in MMSE and changes in the dFC magnitude of DMN in patients who underwent active-rTMS treatment, but not in those who received sham-rTMS treatment. The findings of the current study indicate that fMRI-guided rTMS treatment improves cognitive function of AD patients in the short term, and DMN functional connectivity contributes to therapeutic effectiveness of rTMS.

Reduced nucleus accumbens functional connectivity in reward network and default mode network in patients with recurrent major depressive disorder.

The nucleus accumbens (NAc) is considered a hub of reward processing and a growing body of evidence has suggested its crucial role in the pathophysiology of major depressive disorder (MDD). However, inconsistent results have been reported by studies on reward network-focused resting-state functional MRI (rs-fMRI). In this study, we examined functional alterations of the NAc-based reward circuits in patients with MDD via meta- and mega-analysis. First, we performed a coordinated-based meta-analysis with a new SDM-PSI method for all up-to-date rs-fMRI studies that focused on the reward circuits of patients with MDD. Then, we tested the meta-analysis results in the REST-meta-MDD database which provided anonymous rs-fMRI data from 186 recurrent MDDs and 465 healthy controls. Decreased functional connectivity (FC) within the reward system in patients with recurrent MDD was the most robust finding in this study. We also found disrupted NAc FCs in the DMN in patients with recurrent MDD compared with healthy controls. Specifically, the combination of disrupted NAc FCs within the reward network could discriminate patients with recurrent MDD from healthy controls with an optimal accuracy of 74.7%. This study confirmed the critical role of decreased FC in the reward network in the neuropathology of MDD. Disrupted inter-network connectivity between the reward network and DMN may also have contributed to the neural mechanisms of MDD. These abnormalities have potential to serve as brain-based biomarkers for individual diagnosis to differentiate patients with recurrent MDD from healthy controls.

A novel joint index based on peripheral blood CD4+/CD8+ T cell ratio, albumin level, and monocyte count to determine the severity of major depressive disorder.

BACKGROUND: Inflammation and immune status are correlated with the severity of major depressive disorder (MDD).The purpose of this study was to establish an optimization model of peripheral blood parameters to predict the severity of MDD. METHODS: MDD severity in the training and validation cohorts (n = 99 and 97) was classified using the Hamilton Depression Scale, Thirty-eight healthy individuals as controls. Significant severity-associated factors were identified using a multivariate logistic model and combined to develop a joint index through binary logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to identify the optimal model and evaluate the discriminative performance of the index. RESULTS: In the training cohort, lower CD4+/CD8+ T cell ratio, albumin level, and a higher monocyte percentage (M%) were significant as operating sociated with severe disease (P < 0.05 for all). The index was developed using these factors and calculated as CD4+/CD8+ T cell ratio, albumin level, and M%, with a sensitivity and specificity of 90 and 70%, respectively. The AUC values for the index in the training and validation cohorts were 0.85 and 0.75, respectively, indicating good discriminative performance. CONCLUSION: We identified disease severity-associated joint index that could be easily evaluated: CD4+/CD8+ T cell ratio, albumin level, and M%.

The DIRECT consortium and the REST-meta-MDD project: towards neuroimaging biomarkers of major depressive disorder.

Despite a growing neuroimaging literature on the pathophysiology of major depressive disorder (MDD), reproducible findings are lacking, probably reflecting mostly small sample sizes and heterogeneity in analytic approaches. To address these issues, the Depression Imaging REsearch ConsorTium (DIRECT) was launched. The REST-meta-MDD project, pooling 2428 functional brain images processed with a standardized pipeline across all participating sites, has been the first effort from DIRECT. In this review, we present an overview of the motivations, rationale, and principal findings of the studies so far from the REST-meta-MDD project. Findings from the first round of analyses of the pooled repository have included alterations in functional connectivity within the default mode network, in whole-brain topological properties, in dynamic features, and in functional lateralization. These well-powered exploratory observations have also provided the basis for future longitudinal hypothesis-driven research. Following these fruitful explorations, DIRECT has proceeded to its second stage of data sharing that seeks to examine ethnicity in brain alterations in MDD by extending the exclusive Chinese original sample to other ethnic groups through international collaborations. A state-of-the-art, surface-based preprocessing pipeline has also been introduced to improve sensitivity. Functional images from patients with bipolar disorder and schizophrenia will be included to identify shared and unique abnormalities across diagnosis boundaries. In addition, large-scale longitudinal studies targeting brain network alterations following antidepressant treatment, aggregation of diffusion tensor images, and the development of functional magnetic resonance imaging-guided neuromodulation approaches are underway. Through these endeavours, we hope to accelerate the translation of functional neuroimaging findings to clinical use, such as evaluating longitudinal effects of antidepressant medications and developing individualized neuromodulation targets, while building an open repository for the scientific community.

Disrupted intrinsic functional brain topology in patients with major depressive disorder.

Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patients from the REST-meta-MDD Project, including 821 MDD patients and 765 normal controls (NCs) from 16 sites. Using the Dosenbach 160 node atlas, we examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency, and degree) using graph theory-based methods. Linear mixed-effect models were used for group comparisons to control for site variability; robustness of results was confirmed (e.g., multiple topological parameters, different node definitions, and several head motion control strategies were applied). We found decreased global and local efficiency in patients with MDD compared to NCs. At the nodal level, patients with MDD were characterized by decreased nodal degrees in the somatomotor network (SMN), dorsal attention network (DAN) and visual network (VN) and decreased nodal efficiency in the default mode network (DMN), SMN, DAN, and VN. These topological differences were mostly driven by recurrent MDD patients, rather than first-episode drug naive (FEDN) patients with MDD. In this highly powered multisite study, we observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks.

Precision Repetitive Transcranial Magnetic Stimulation Over the Left Parietal Cortex Improves Memory in Alzheimer's Disease: A Randomized, Double-Blind, Sham-Controlled Study.

OBJECTIVE: We aim to study the effect of precision repetitive transcranial magnetic stimulation (rTMS) over the left parietal cortex on the memory and cognitive function in Alzheimer's disease (AD). METHODS: Based on the resting-state functional magnetic resonance imaging, the left parietal cortex site with the highest functional connectivity to the hippocampus was selected as the target of rTMS treatment. Sixty-nine AD patients were randomized to either rTMS or sham treatment (five sessions/week for a total of 10 sessions). The Mini-Mental State Examination (MMSE), 12-Word Philadelphia Verbal Learning Test (PVLT), and Clinical Dementia Rating (CDR) were assessed at baseline and after the last session. RESULTS: After a 2-week treatment, compared to patients in the sham group, those in the rTMS group scored significantly higher on PVLT total score and its immediate recall subscale score. Moreover, in the rTMS group, there were significant improvements after the 2-week treatment, which were manifested in MMSE total score and its time orientation and recall subscale scores, as well as PVLT total score and its immediate recall and short delay recall subscale scores. In the sham group, the PVLT total score was significantly improved. CONCLUSION: The target site of the left parietal cortex can improve AD patients' cognitive function, especially memory, providing a potential therapy.

Brain structural alterations in MDD patients with gastrointestinal symptoms: Evidence from the REST-meta-MDD project.

OBJECTIVE: While gastrointestinal (GI) symptoms are very common in patients with major depressive disorder (MDD), few studies have investigated the neural basis behind these symptoms. In this study, we sought to elucidate the neural basis of GI symptoms in MDD patients by analyzing the changes in regional gray matter volume (GMV) and gray matter density (GMD) in brain structure. METHOD: Subjects were recruited from 13 clinical centers and categorized into three groups, each of which is based on the presence or absence of GI symptoms: the GI symptoms group (MDD patients with at least one GI symptom), the non-GI symptoms group (MDD patients without any GI symptoms), and the healthy control group (HCs). Structural magnetic resonance images (MRI) were collected of 335 patients in the GI symptoms group, 149 patients in the non-GI symptoms group, and 446 patients in the healthy control group. The 17-item Hamilton Depression Rating Scale (HAMD-17) was administered to all patients. Correlation analysis and logistic regression analysis were used to determine if there was a correlation between the altered brain regions and the clinical symptoms. RESULTS: There were significantly higher HAMD-17 scores in the GI symptoms group than that of the non-GI symptoms group (P < 0.001). Both GMV and GMD were significant different among the three groups for the bilateral superior temporal gyrus, bilateral middle temporal gyrus, left lingual gyrus, bilateral caudate nucleus, right Fusiform gyrus and bilateral Thalamus (GRF correction, cluster-P < 0.01, voxel-P < 0.001). Compared to the HC group, the GI symptoms group demonstrated increased GMV and GMD in the bilateral superior temporal gyrus, and the non-GI symptoms group demonstrated an increased GMV and GMD in the right superior temporal gyrus, right fusiform gyrus and decreased GMV in the right Caudate nucleus (GRF correction, cluster-P < 0.01, voxel-P < 0.001). Compared to the non-GI symptoms group, the GI symptoms group demonstrated significantly increased GMV and GMD in the bilateral thalamus, as well as decreased GMV in the bilateral superior temporal gyrus and bilateral insula lobe (GRF correction, cluster-P < 0.01, voxel-P < 0.001). While these changed brain areas had significantly association with GI symptoms (P < 0.001), they were not correlated with depressive symptoms (P > 0.05). Risk factors for gastrointestinal symptoms in MDD patients (p < 0.05) included age, increased GMD in the right thalamus, and decreased GMV in the bilateral superior temporal gyrus and left Insula lobe. CONCLUSION: MDD patients with GI symptoms have more severe depressive symptoms. MDD patients with GI symptoms exhibited larger GMV and GMD in the bilateral thalamus, and smaller GMV in the bilateral superior temporal gyrus and bilateral insula lobe that were correlated with GI symptoms, and some of them and age may contribute to the presence of GI symptoms in MDD patients.

The coupling of BOLD signal variability and degree centrality underlies cognitive functions and psychiatric diseases.

Brain signal variability has been consistently linked to functional integration; however, whether this coupling is associated with cognitive functions and/or psychiatric diseases has not been clarified. Using multiple multimodality datasets, including resting-state functional magnetic resonance imaging (rsfMRI) data from the Human Connectome Project (HCP: N = 927) and a Beijing sample (N = 416) and cerebral blood flow (CBF) and rsfMRI data from a Hangzhou sample (N = 29), we found that, compared with the existing variability measure (i.e., SDBOLD), the mean-scaled (standardized) fractional standard deviation of the BOLD signal (mfSDBOLD) maintained very high test-retest reliability, showed greater cross-site reliability and was less affected by head motion. We also found strong reproducible couplings between the mfSDBOLD and functional integration measured by the degree centrality (DC), both cross-voxel and cross-subject, which were robust to scanning and preprocessing parameters. Moreover, both mfSDBOLD and DC were correlated with CBF, suggesting a common physiological basis for both measures. Critically, the degree of coupling between mfSDBOLD and long-range DC was positively correlated with individuals' cognitive total composite scores. Brain regions with greater mismatches between mfSDBOLD and long-range DC were more vulnerable to brain diseases. Our results suggest that BOLD signal variability could serve as a meaningful index of local function that underlies functional integration in the human brain and that a strong coupling between BOLD signal variability and functional integration may serve as a hallmark of balanced brain networks that are associated with optimal brain functions.

Disrupted hemispheric connectivity specialization in patients with major depressive disorder: Evidence from the REST-meta-MDD Project.

BACKGROUND: Functional specialization is a feature of human brain for understanding the pathophysiology of major depressive disorder (MDD). The degree of human specialization refers to within and cross hemispheric interactions. However, most previous studies only focused on interhemispheric connectivity in MDD, and the results varied across studies. Hence, brain functional connectivity asymmetry in MDD should be further studied. METHODS: Resting-state fMRI data of 753 patients with MDD and 451 healthy controls were provided by REST-meta-MDD Project. Twenty-five project contributors preprocessed their data locally with the Data Processing Assistant State fMRI software and shared final indices. The parameter of asymmetry (PAS), a novel voxel-based whole-brain quantitative measure that reflects inter- and intrahemispheric asymmetry, was reported. We also examined the effects of age, sex and clinical variables (including symptom severity, illness duration and three depressive phenotypes). RESULTS: Compared with healthy controls, patients with MDD showed increased PAS scores (decreased hemispheric specialization) in most of the areas of default mode network, control network, attention network and some regions in the cerebellum and visual cortex. Demographic characteristics and clinical variables have significant effects on these abnormalities. LIMITATIONS: Although a large sample size could improve statistical power, future independent efforts are needed to confirm our results. CONCLUSIONS: Our results highlight the idea that many brain networks contribute to broad clinical pathophysiology of MDD, and indicate that a lateralized, efficient and economical brain information processing system is disrupted in MDD. These findings may help comprehensively clarify the pathophysiology of MDD in a new hemispheric specialization perspective.

Altered resting-state dynamic functional brain networks in major depressive disorder: Findings from the REST-meta-MDD consortium.

BACKGROUND: Major depressive disorder (MDD) is known to be characterized by altered brain functional connectivity (FC) patterns. However, whether and how the features of dynamic FC would change in patients with MDD are unclear. In this study, we aimed to characterize dynamic FC in MDD using a large multi-site sample and a novel dynamic network-based approach. METHODS: Resting-state functional magnetic resonance imaging (fMRI) data were acquired from a total of 460 MDD patients and 473 healthy controls, as a part of the REST-meta-MDD consortium. Resting-state dynamic functional brain networks were constructed for each subject by a sliding-window approach. Multiple spatio-temporal features of dynamic brain networks, including temporal variability, temporal clustering and temporal efficiency, were then compared between patients and healthy subjects at both global and local levels. RESULTS: The group of MDD patients showed significantly higher temporal variability, lower temporal correlation coefficient (indicating decreased temporal clustering) and shorter characteristic temporal path length (indicating increased temporal efficiency) compared with healthy controls (corrected p < 3.14×10-3). Corresponding local changes in MDD were mainly found in the default-mode, sensorimotor and subcortical areas. Measures of temporal variability and characteristic temporal path length were significantly correlated with depression severity in patients (corrected p < 0.05). Moreover, the observed between-group differences were robustly present in both first-episode, drug-naïve (FEDN) and non-FEDN patients. CONCLUSIONS: Our findings suggest that excessive temporal variations of brain FC, reflecting abnormal communications between large-scale bran networks over time, may underlie the neuropathology of MDD.

Biotypes of major depressive disorder: Neuroimaging evidence from resting-state default mode network patterns.

BACKGROUND: Major depressive disorder (MDD) is heterogeneous disorder associated with aberrant functional connectivity within the default mode network (DMN). This study focused on data-driven identification and validation of potential DMN-pattern-based MDD subtypes to parse heterogeneity of the disorder. METHODS: The sample comprised 1397 participants including 690 patients with MDD and 707 healthy controls (HC) registered from multiple sites based on the REST-meta-MDD Project in China. Baseline resting-state functional magnetic resonance imaging (rs-fMRI) data was recorded for each participant. Discriminative features were selected from DMN between patients and HC. Patient subgroups were defined by K-means and principle component analysis in the multi-site datasets and validated in an independent single-site dataset. Statistical significance of resultant clustering were confirmed. Demographic and clinical variables were compared between identified patient subgroups. RESULTS: Two MDD subgroups with differing functional connectivity profiles of DMN were identified in the multi-site datasets, and relatively stable in different validation samples. The predominant dysfunctional connectivity profiles were detected among superior frontal cortex, ventral medial prefrontal cortex, posterior cingulate cortex and precuneus, whereas one subgroup exhibited increases of connectivity (hyperDMN MDD) and another subgroup showed decreases of connectivity (hypoDMN MDD). The hyperDMN subgroup in the discovery dataset had age-related severity of depressive symptoms. Patient subgroups had comparable demographic and clinical symptom variables. CONCLUSIONS: Findings suggest the existence of two neural subtypes of MDD associated with different dysfunctional DMN connectivity patterns, which may provide useful evidence for parsing heterogeneity of depression and be valuable to inform the search for personalized treatment strategies.

Reduced default mode network functional connectivity in patients with recurrent major depressive disorder.

Major depressive disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). Data were preprocessed locally with a standardized protocol before aggregated group analyses. We focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD. Instead, we found decreased DMN FC when we compared 848 patients with MDD to 794 NCs from 17 sites after data exclusion. We found FC reduction only in recurrent MDD, not in first-episode drug-naïve MDD. Decreased DMN FC was associated with medication usage but not with MDD duration. DMN FC was also positively related to symptom severity but only in recurrent MDD. Exploratory analyses also revealed alterations in FC of visual, sensory-motor, and dorsal attention networks in MDD. We confirmed the key role of DMN in MDD but found reduced rather than increased FC within the DMN. Future studies should test whether decreased DMN FC mediates response to treatment. All R-fMRI indices of data contributed by the REST-meta-MDD consortium are being shared publicly via the R-fMRI Maps Project.

Connectome analysis of functional and structural hemispheric brain networks in major depressive disorder.

Neuroimaging studies have shown topological disruptions of both functional and structural whole-brain networks in major depressive disorder (MDD). This study examined common and specific alterations between these two types of networks and whether the alterations were differentially involved in the two hemispheres. Multimodal MRI data were collected from 35 MDD patients and 35 healthy controls, whose functional and structural hemispheric networks were constructed, characterized, and compared. We found that functional brain networks were profoundly altered at multiple levels, while structural brain networks were largely intact in patients with MDD. Specifically, the functional alterations included decreases in intra-hemispheric (left and right) and inter-hemispheric (heterotopic) functional connectivity; decreases in local, global and normalized global efficiency for both hemispheric networks; increases in normalized local efficiency for the left hemispheric networks; and decreases in intra-hemispheric integration and inter-hemispheric communication in the dorsolateral superior frontal gyrus, anterior cingulate gyrus and hippocampus. Regarding hemispheric asymmetry, largely similar patterns were observed between the functional and structural networks: the right hemisphere was over-connected and more efficient than the left hemisphere globally; the occipital and partial regions exhibited leftward asymmetry, and the frontal and temporal sites showed rightward lateralization with regard to regional connectivity profiles locally. Finally, the functional-structural coupling of intra-hemispheric connections was significantly decreased and correlated with the disease severity in the patients. Overall, this study demonstrates modality- and hemisphere-dependent and invariant network alterations in MDD, which are helpful for understanding elaborate and characteristic patterns of integrative dysfunction in this disease.

Spatiotemporal, metabolic, and therapeutic characterization of altered functional connectivity in major depressive disorder.

Although imbalanced functional integration has been increasingly reported in major depressive disorder (MDD), there still lacks a general framework to characterize common characteristic and origin shared by the integrative disturbances. Here we examined spatial selectivity, temporal uniqueness, metabolic basis, and therapeutic response of altered functional connectivity (FC) in MDD by analyzing both cross-sectional and longitudinal multimodal functional magnetic resonance imaging data from 35 patients and 34 demographically matched healthy controls. First, based on a voxel-wise, data-driven, graph-based degree centrality approach, the bilateral anterior cingulate gyri, middle frontal gyri and superior frontal gyri, and the right parahippocampal gyrus were robustly identified to show decreased FC in MDD. Further spatiotemporal analyses revealed that these regions exhibited hub-like features and were selectively located in limbic and default mode networks spatially and, relative to other areas in the brain, exhibited unique, frequency-dependent oscillation power (stronger within 0.01-0.027 Hz and weaker within 0.027-0.073 Hz) and less dynamical variability of whole-brain FC profiles temporally. Moreover, a cross-modality fusion analysis showed that all MDD-related FC impairments were associated with reduced cerebral blood flow (CBF); however, there existed multiple regions that showed reduced CBF but had intact FC in the patients, which resulted in a decreased FC-CBF coupling and implied an earlier emergence of reduced CBF than impaired FC in MDD. Finally, the disrupted FC in MDD gradually recovered over the course of drug treatment (2 and 12 weeks). Altogether, these findings could help establish a general framework to provide mechanistic insights into integrative dysfunctions in MDD.

(1)H-MRS asymmetry changes in the anterior and posterior cingulate gyrus in patients with mild cognitive impairment and mild Alzheimer's disease.

Alzheimer's disease (AD) is the most common cause of dementia worldwide. Amnestic mild cognitive impairment (aMCI) is often the prodromal stage to AD. Most patients with aMCI harbor the pathologic changes of AD and demonstrate transition to AD at a rate of 10%-15% per year. Patients with AD and aMCI experience progressive brain metabolite changes. Accumulating evidence indicates that the asymmetry changes of left and right brain happen in the early stage of AD. However, the features of asymmetry changes in both anterior cingulate gyrus (ACG) and posterior cingulate gyrus (PCG) are still unclear. Here, we examine the left-right asymmetry changes of metabolites in ACG and PCG. Fifteen cases of mild AD patients meeting criteria for probable AD of NINDS-ADRDA, thirteen cases of aMCI according to the Mayo Clinic Alzheimer's Disease Research Center criteria, and sixteen cases of age-matched normal controls (NC) received Proton magnetic resonance spectroscopy ((1)H-MRS) for measurement of NAA/mI, NAA/Cr, Cho/Cr, and mI/Cr ratios in the PCG and ACG bilaterally. We analyzed (1)H-MRS data by paired t-test to validate the left-right asymmetry of (1)H-MRS data in the PCG and ACG. In AD, there was a significant difference in mI/Cr between the left and right ACG (P<0.001) and the left and right PCG (P=0.007). In aMCI, there was a significant difference in mI/Cr between the left and right ACG (P<0.001). In NC, there were no differences in the ratio value of metabolites NAA/mI, NAA/Cr, Cho/Cr, and mI/Cr between the left and right ACG and PCG. Thus, the left-right asymmetry of mI/Cr in the ACG and PCG may be an important biological indicator of mild AD.

Neurometabolic characteristics in the anterior cingulate gyrus of Alzheimer's disease patients with depression: a (1)H magnetic resonance spectroscopy study.

BACKGROUND: Depression is a common comorbid psychiatric symptom in patients with Alzheimer's disease (AD), and the prevalence of depression is higher among people with AD compared with healthy older adults. Comorbid depression in AD may increase the risk of cognitive decline, impair patients' function, and reduce their quality of life. However, the mechanisms of depression in AD remain unclear. Here, our aim was to identify neurometabolic characteristics in the brain that are associated with depression in patients with mild AD. METHODS: Thirty-seven patients were evaluated using the Neuropsychiatric Inventory (NPI) and Hamilton Depression Rating Scale (HAMD-17), and divided into two groups: 17 AD patients with depression (D-AD) and 20 non-depressed AD patients (nD-AD). Using proton magnetic resonance spectroscopy, we characterized neurometabolites in the anterior cingulate gyrus (ACG) of D-AD and nD-AD patients. RESULTS: Compared with nD-AD patients, D-AD patients showed lower N-acetylaspartate/creatine (NAA/Cr) and higher myo-inositol/creatine (mI/Cr) in the left ACG. NPI score correlated with NAA/Cr and mI/Cr in the left ACG, while HAMD correlated with NAA/Cr. CONCLUSIONS: Our findings show neurometabolic alterations in D-AD patients. Thus, D-AD pathogenesis may be attributed to abnormal activity of neurons and glial cells in the left ACG.

Regional Coherence Changes in Alzheimer's Disease Patients with Depressive Symptoms: A Resting-State Functional MRI Study.

Alzheimer's disease (AD) is characterized by progressive cognitive decline along with neuropsychiatric symptoms including depression and psychosis. Depression is a common psychiatric disorder occurring in people across the lifespan. Accumulating evidence indicates that depression may be a prodrome and/or a "risk factor" for AD. However, whether AD and depression share a common pathophysiological pathway is still unclear. The aim of this study was to identify regional alterations in brain function associated with depressive symptoms in mild AD patients. Thirty-two mild AD patients were evaluated using the Neuropsychiatric Inventory and Hamilton Depression Rating Scale, and were divided into two groups: 15 AD patients with depressive symptoms (D-AD) and 17 non-depressed AD (nD-AD) patients. Using the approach of regional homogeneity (ReHo), we characterized resting-state regional brain activity in D-AD and nD-AD patients. Compared with nD-AD patients, D-AD patients showed decreased ReHo in the right precentral gyrus, right superior frontal gyrus, right middle frontal gyrus, and right inferior frontal cortex. Our findings show regional brain activity alterations in D-AD patients. Thus, D-AD pathogenesis may be attributed to abnormal neural activity in multiple brain regions.

Sub-hubs of baseline functional brain networks are related to early improvement following two-week pharmacological therapy for major depressive disorder.

Accumulating evidence suggests that early improvement after two-week antidepressant treatment is predictive of later outcomes of patients with major depressive disorder (MDD); however, whether this early improvement is associated with baseline neural architecture remains largely unknown. Utilizing resting-state functional MRI data and graph-based network approaches, this study calculated voxel-wise degree centrality maps for 24 MDD patients at baseline and linked them with changes in the Hamilton Rating Scale for Depression (HAMD) scores after two weeks of medication. Six clusters exhibited significant correlations of their baseline degree centrality with treatment-induced HAMD changes for the patients, which were mainly categorized into the posterior default-mode network (i.e., the left precuneus, supramarginal gyrus, middle temporal gyrus, and right angular gyrus) and frontal regions. Receiver operating characteristic curve and logistic regression analyses convergently revealed excellent performance of these regions in discriminating the early improvement status for the patients, especially the angular gyrus (sensitivity and specificity of 100%). Moreover, the angular gyrus was identified as the optimal regressor as determined by stepwise regression. Interestingly, these regions possessed higher centrality than others in the brain (P < 10(-3)) although they were not the most highly connected hubs. Finally, we demonstrate a high reproducibility of our findings across several factors (e.g., threshold choice, anatomical distance, and temporal cutting) in our analyses. Together, these preliminary exploratory analyses demonstrate the potential of neuroimaging-based network analysis in predicting the early therapeutic improvement of MDD patients and have important implications in guiding earlier personalized therapeutic regimens for possible treatment-refractory depression.

Caspase-8 Mediates Amyloid-ß-induced Apoptosis in Differentiated PC12 Cells.

The pathogenesis of Alzheimer's disease (AD) is very complex and there are currently no significant treatments for the disease. Caspase-8 is known to be involved in neuronal apoptosis. To explore a possible molecular mechanisms involved in AD pathology, this study investigated the effect of caspase-8 knockdown on amyloid-ß 1-40 (Aß1-40)-induced apoptosis in PC12 cells. The proliferation of PC12 cells was significantly inhibited in Aß-treated cells, and a high fraction of the cells underwent apoptosis in a dose- and time-dependent manner. Transfection of caspase-8 small interfering RNA (siRNA) resulted in reduced apoptosis following Aß1-40 treatment. The activation of caspase-3, caspase-8, and caspase-9 was stimulated by Aß1-40, an effect that was also significantly reduced by caspase-8 siRNA. Knockdown of caspase-8 increased the phosphorylation of the signaling molecules AKT and ERK1/2 relative to cells treated with Aß1-40 alone. Caspase-8 is an important effector molecule involved in apoptosis induced by Aß1-40 and is likely involved in AD pathology. This study suggests that targeted inhibition of caspase-8 may be a new therapeutic for preventing neuronal apoptosis and inhibiting the progression of AD.

Relationship between personality disorder functioning styles and the emotional states in bipolar I and II disorders.

BACKGROUND: Bipolar disorder types I (BD I) and II (BD II) behave differently in clinical manifestations, normal personality traits, responses to pharmacotherapies, biochemical backgrounds and neuroimaging activations. How the varied emotional states of BD I and II are related to the comorbid personality disorders remains to be settled. METHODS: We therefore administered the Plutchick - van Praag Depression Inventory (PVP), the Mood Disorder Questionnaire (MDQ), the Hypomanic Checklist-32 (HCL-32), and the Parker Personality Measure (PERM) in 37 patients with BD I, 34 BD II, and in 76 healthy volunteers. RESULTS: Compared to the healthy volunteers, patients with BD I and II scored higher on some PERM styles, PVP, MDQ and HCL-32 scales. In BD I, the PERM Borderline style predicted the PVP scale; and Antisocial predicted HCL-32. In BD II, Borderline, Dependent, Paranoid (-) and Schizoid (-) predicted PVP; Borderline predicted MDQ; Passive-Aggressive and Schizoid (-) predicted HCL-32. In controls, Borderline and Narcissistic (-) predicted PVP; Borderline and Dependent (-) predicted MDQ. CONCLUSION: Besides confirming the different predictability of the 11 functioning styles of personality disorder to BD I and II, we found that the prediction was more common in BD II, which might underlie its higher risk of suicide and poorer treatment outcome.