Connectome gradient dysfunction in major depression and its association with gene expression profiles and treatment outcomes.

Patients with major depressive disorder (MDD) exhibit concurrent deficits in both sensory and higher-order cognitive processing. Connectome studies have suggested a principal primary-to-transmodal gradient in functional brain networks, supporting the spectrum from sensation to cognition. However, whether this gradient structure is disrupted in patients with MDD and how this disruption associates with gene expression profiles and treatment outcome remain unknown. Using a large cohort of resting-state fMRI data from 2227 participants (1148 MDD patients and 1079 healthy controls) recruited at nine sites, we investigated MDD-related alterations in the principal connectome gradient. We further used Neurosynth, postmortem gene expression, and an 8-week antidepressant treatment (20 MDD patients) data to assess the meta-analytic cognitive functions, transcriptional profiles, and treatment outcomes related to MDD gradient alterations, respectively. Relative to the controls, MDD patients exhibited global topographic alterations in the principal primary-to-transmodal gradient, including reduced explanation ratio, gradient range, and gradient variation (Cohen's d = 0.16-0.21), and focal alterations mainly in the primary and transmodal systems (d = 0.18-0.25). These gradient alterations were significantly correlated with meta-analytic terms involving sensory processing and higher-order cognition. The transcriptional profiles explained 53.9% variance of the altered gradient pattern, with the most correlated genes enriched in transsynaptic signaling and calcium ion binding. The baseline gradient maps of patients significantly predicted symptomatic improvement after treatment. These results highlight the connectome gradient dysfunction in MDD and its linkage with gene expression profiles and clinical management, providing insight into the neurobiological underpinnings and potential biomarkers for treatment evaluation in this disorder.

AI-based dimensional neuroimaging system for characterizing heterogeneity in brain structure and function in major depressive disorder: COORDINATE-MDD consortium design and rationale.

BACKGROUND: Efforts to develop neuroimaging-based biomarkers in major depressive disorder (MDD), at the individual level, have been limited to date. As diagnostic criteria are currently symptom-based, MDD is conceptualized as a disorder rather than a disease with a known etiology; further, neural measures are often confounded by medication status and heterogeneous symptom states. METHODS: We describe a consortium to quantify neuroanatomical and neurofunctional heterogeneity via the dimensions of novel multivariate coordinate system (COORDINATE-MDD). Utilizing imaging harmonization and machine learning methods in a large cohort of medication-free, deeply phenotyped MDD participants, patterns of brain alteration are defined in replicable and neurobiologically-based dimensions and offer the potential to predict treatment response at the individual level. International datasets are being shared from multi-ethnic community populations, first episode and recurrent MDD, which are medication-free, in a current depressive episode with prospective longitudinal treatment outcomes and in remission. Neuroimaging data consist of de-identified, individual, structural MRI and resting-state functional MRI with additional positron emission tomography (PET) data at specific sites. State-of-the-art analytic methods include automated image processing for extraction of anatomical and functional imaging variables, statistical harmonization of imaging variables to account for site and scanner variations, and semi-supervised machine learning methods that identify dominant patterns associated with MDD from neural structure and function in healthy participants. RESULTS: We are applying an iterative process by defining the neural dimensions that characterise deeply phenotyped samples and then testing the dimensions in novel samples to assess specificity and reliability. Crucially, we aim to use machine learning methods to identify novel predictors of treatment response based on prospective longitudinal treatment outcome data, and we can externally validate the dimensions in fully independent sites. CONCLUSION: We describe the consortium, imaging protocols and analytics using preliminary results. Our findings thus far demonstrate how datasets across many sites can be harmonized and constructively pooled to enable execution of this large-scale project.

Emotional intelligence mediates the protective role of the orbitofrontal cortex spontaneous activity measured by fALFF against depressive and anxious symptoms in late adolescence.

As a stable personality construct, trait emotional intelligence (TEI) refers to a battery of perceived emotion-related skills that make individuals behave effectively to adapt to the environment and maintain well-being. Abundant evidence has consistently shown that TEI is important for the outcomes of many mental health issues, particularly depression and anxiety. However, the neural substrates involved in TEI and the underlying neurobehavioral mechanism of how TEI reduces depression and anxiety symptoms remain largely unknown. Herein, resting-state functional magnetic resonance imaging and a group of behavioral measures were applied to examine these questions among a large sample comprising 231 general adolescent students aged 16-20 years (52% female). Whole-brain correlation analysis and prediction analysis demonstrated that TEI was negatively linked with spontaneous activity (measured with the fractional amplitude of low-frequency fluctuations) in the bilateral medial orbitofrontal cortex (OFC), a critical site implicated in emotion-related processes. Furthermore, structural equation modeling analysis found that TEI mediated the link of OFC spontaneous activity to depressive and anxious symptoms. Collectively, the current findings present new evidence for the neurofunctional bases of TEI and suggest a potential "brain-personality-symptom" pathway for alleviating depressive and anxious symptoms among students in late adolescence.

Altered intrinsic brain activity in patients with hepatic encephalopathy.

Neuropsychiatric deficits are common in patients with liver cirrhosis (LC), especially in those with hepatic encephalopathy (HE). Previous studies reveal abnormalities in brain activity underlying the neuropsychiatric deficits in LC patients; however, the results are inconsistent. We conducted a meta-analysis of resting-state functional magnetic resonance imaging studies using anisotropic effect-size signed differential mapping software on LC patients to characterize the most consistent regional activity alterations, and to evaluate the potential effect of liver transplantation (LT) on brain function. Meta-regression analyses were performed to explore the relationship between brain alterations and clinical variables. Compared with healthy controls, the typical patterns of increased regional activity in the fronto-striato-cerebellar network and decreased activity in the visuo-sensorimotor network and cingulate gyrus were identified in LC patients, which remained significant in the subgroup meta-analyses of minimal HE (MHE) and overt HE (OHE) patients. Functional deficits in the default mode network (DMN) were found in OHE patients compared with MHE patients. Ammonia level positively correlated with brain activity in the right middle temporal gyrus, and the completion time of number connection test A negatively correlated with brain activity in the left anterior cingulate gyrus. In addition, patients showed increased activity in the visuo-sensorimotor network and precuneus after LT. Our study suggests that alterations in the fronto-striato-cerebellar and visuo-sensorimotor networks may be the potential pathophysiological mechanisms underlying HE, and deficits in the DMN may indicate the progression of HE. LT may improve brain function in the visuo-sensorimotor network. This study has registered in the PROSPERO (CRD42020212758).

White Matter-Based Structural Brain Network of Major Depression.

Major depressive disorder (MDD) is frequently characterized as a disorder of the disconnection syndrome. Diffusion tensor imaging (DTI) has played a critical role in supporting this view, with much investigation providing a large amount of evidence of structural connectivity abnormalities in the disorder. Recent research on the human connectome combined neuroimaging techniques with graph theoretic methods to highlight the disrupted topological properties of large-scale structural brain networks under depression, involving global metrics (e.g., global and local efficiencies), and local nodal properties (e.g., degree and betweenness), as well as other related metrics, including a modular structure, assortativity, and (rich) hubs. Here, we review the studies of white matter networks in the case of MDD with the application of these techniques, focusing principally on the consistent findings and the clinical significance of DTI-based network research, while discussing the key methodological issues that frequently arise in the field. The already published literature shows that MDD is associated with a widespread structural connectivity deficit. Topological alteration of structural brain networks in the case of MDD points to decreased overall connectivity strength and reduced global efficiency as well as decreased small-worldness and network resilience. These structural connectivity disturbances entail potential functional consequences, although the relationship between the two is very sophisticated and requires further investigation. In summary, the present study comprehensively maps the structural connectomic disturbances in patients with MDD across the entire brain, which adds important weight to the view suggesting connectivity abnormalities of this disorder and highlights the potential of network properties as diagnostic biomarkers in the psychoradiology field. Several common methodological issues of the study of DTI-based networks are discussed, involving sample heterogeneity and fiber crossing problems and the tractography algorithms. Finally, suggestions for future perspectives, including imaging multimodality, a longitudinal study and computational connectomics, in the further study of white matter networks under depression are given. Surmounting these challenges and advancing the research methods will be required to surpass the simple mapping of connectivity changes to illuminate the underlying psychiatric pathological mechanism.

The prevalence of mental distress and association with social changes among postgraduate students in China: a cross-temporal meta-analysis.

OBJECTIVE: This study aims to estimate the mental distress prevalence of Chinese postgraduate students and the association with the social changes based on the data between 2000 and 2019. STUDY DESIGN: This is a cross-temporal meta-analysis study. METHODS: The literature was retrieved with both English and Chinese electronic databases, including articles published from 2002 to 2019. Statistical analyses were performed with R 3.6.1 and SPSS 22. RESULTS: Eighty-nine primary studies with 99 reports were included in our meta-analysis, totaling 54,722 Chinese postgraduate students. The result showed that: (a) the prevalence of mental distress was 28% (95% confidence interval [CI]: 25%-31%), and the prevalence of moderately positive symptoms was 9% (95% CI: 7%-11%); (b) the prevalence of positive symptoms was negatively correlated with the years of data collection and the prevalence of mental distress decreased by at least 16% from 2000 to 2019; and (c) social changes, particularly the policies of mental health and the educational environment had a significant contribution to these changes. CONCLUSIONS: More than a quarter of postgraduate students have mental illness in China, whereas the prevalence of their mental distress has been decreasing. Social changes are shown to play an important role in contributing to this change.

Neural substrates of the emotion-word and emotional counting Stroop tasks in healthy and clinical populations: A meta-analysis of functional brain imaging studies.

The emotional Stroop task (EST) is among the most influential paradigms used to probe attention-related or cognitive control-related emotional processing in healthy subjects and clinical populations. The neuropsychological mechanism underlying the emotional Stroop effect has attracted extensive and long-lasting attention in both cognitive and clinical psychology and neuroscience; however, a precise characterization of the neural substrates underlying the EST in healthy and clinical populations remains elusive. Here, we implemented a coordinate-based meta-analysis covering functional imaging studies that employed the emotion-word or emotional counting Stroop paradigms to determine the underlying neural networks in healthy subjects and the trans-diagnostic alterations across clinical populations. Forty-six publications were identified that reported relevant contrasts (negative > neutral; positive > neutral) for healthy or clinical populations as well as for hyper- or hypo-activation of patients compared to controls. We demonstrate consistent involvement of the vlPFC and dmPFC in healthy subjects and consistent involvement of the vlPFC in patients. We further identify a trans-diagnostic pattern of hyper-activation in the prefrontal and parietal regions. These findings underscore the critical roles of cognitive control processes in the EST and implicate trans-diagnostic cognitive control deficits. Unlike the current models that emphasize the roles of the amygdala and rACC, our findings implicate novel mechanisms underlying the EST for both healthy and clinical populations.

Neuroanatomical correlates of grit: Growth mindset mediates the association between gray matter structure and trait grit in late adolescence.

There is a long-standing interest in exploring the factors related to student achievement. As a newly explored personality trait, grit is defined as a person's tendency to pursue long-term goals with continual perseverance and passion, and grit plays a critical role in student achievement. Increasing evidence has shown that growth mindset, the belief that one's basic abilities are malleable and can be developed through effort, is a potential factor for cultivating grit. However, less is known about the association between grit and the brain and the role of growth mindset in this association. Here, we utilized voxel-based morphometry to examine the neuroanatomical correlates of grit in 231 healthy adolescent students by performing structural magnetic resonance imaging. The whole-brain regression analyses revealed that the regional gray matter volume (rGMV) in the left dorsolateral prefrontal cortex (DLPFC) negatively predicted grit. In contrast, the rGMV in the right putamen positively predicted grit. Furthermore, mediating analyses suggested that growth mindset served as a mediator in the association between left DLPFC volume and grit. Our results persisted even after controlling for the influences of self-control and delayed gratification. Overall, our study presents novel evidence for the neuroanatomical basis of grit and highlights that growth mindset might play an essential role in cultivating a student's grit level.

The optimistic brain: Trait optimism mediates the influence of resting-state brain activity and connectivity on anxiety in late adolescence.

As a hot research topic in the field of psychology and psychiatry, trait optimism reflects the tendency to expect positive outcomes in the future. Consistent evidence has demonstrated the role of trait optimism in reducing anxiety among different populations. However, less is known about the neural bases of trait optimism and the underlying mechanisms for how trait optimism protects against anxiety in the healthy brain. In this investigation, we examined these issues in 231 healthy adolescent students by assessing resting-state brain activity (i.e., fractional amplitude of low-frequency fluctuations, fALFF) and connectivity (i.e., resting-state functional connectivity, RSFC). Whole-brain correlation analyses revealed that higher levels of trait optimism were linked with decreased fALFF in the right orbitofrontal cortex (OFC) and increased RSFC between the right OFC and left supplementary motor cortex (SMC). Mediation analyses further showed that trait optimism mediated the influence of the right OFC activity and the OFC-SMC connectivity on anxiety. Our results remained significant even after excluding the impact of head motion, positive and negative affect and depression. Taken together, this study reveals that fALFF and RSFC are functional neural markers of trait optimism and provides a brain-personality-symptom pathway for protection against anxiety in which fALFF and RSFC affect anxiety through trait optimism.

Verbal responses, depressive symptoms, reminiscence functions and cognitive emotion regulation in older women receiving individual reminiscence therapy.

AIMS AND OBJECTIVES: To examine the effectiveness of individual reminiscence therapy in community-dwelling older women with depressive symptoms and to explore the characteristics of participants' verbalisation in the process. BACKGROUND: Previous studies have found reminiscence was related to depression and anxiety. Although reminiscence therapy is widely used to reduce depression, little is known about how it works, and the content of verbalisations might provide one explanation. DESIGN: The study employed a one-group pretest-post-test design. METHODS: Twenty-seven participants underwent 6-week interventions of individual reminiscence therapy at home that were conducted by one nurse and induced through seeing old photographs. The Geriatric Depression Scale, Zung Self-rating Anxiety Scale, Reminiscence Functions Scale and Cognitive Emotion Regulation Questionnaire were used to measure the emotional states, reminiscence functions and cognitive emotion regulation strategies. Participants' verbalisations were categorised using the Client Behavior System. RESULTS: Reminiscence therapy relieved depression and anxiety. Both the reminiscence function and cognitive emotion regulation became more favourable after interventions. Furthermore, higher frequencies of recounting, cognitive-behavioural exploration and affective exploration were noted in the process. Participants with more severe depressive symptoms tended to display a higher frequency of affective exploration. The reduction in depression, self-negative reminiscence and negative-focused emotion regulation were respectively associated with verbalisations. CONCLUSIONS: Individual reminiscence therapy might relieve negative emotion and improve reminiscence function and cognitive emotion regulation. The participants' verbalisation is worthy of our attention, due to its correlation with the severity of depression and its mitigating effects on the depression, anxiety, self-negative reminiscence and negative-focused regulation in older women. The results contribute to our understanding of the therapeutic procedure and suggest a need for more research on the therapeutic processes. RELEVANCE TO CLINICAL PRACTICE: Study on processes could help training novice clinical interveners so that reminiscence therapy can work better on emotional disorders in clinical practice.

[Pathological Analysis of Endoscopic Submucosal Dissection Specimen of Esophageal Superficial Infiltrating Squamous Cell Carcinoma].

OBJECTIVE: To analyze the pathological characteristics of superficial infiltrating squamous cell carcinoma of endoscopic submucosal dissection (ESD). METHODS: 187 cases of invasive squamous cell carcinoma after ESD operation were collected from 2016 Jan 31 to 2017 Dec 31. The tumor differentiation, invasion depth, infiltrative growth pattern (INF), tumor budding, angiovascular lymphatic invasion and margin were determined. The pathological diagnosis of endoscopic biopsy and surgical operation after ESD were searched. RESULTS: The patients were aged from 42 to 83 years old, including 147 males and 40 females. 9.1% patients had carcinoma/intraepithelial neoplasia in other sites, among which gastric adenocarcinoma was the most common one. Well, moderately and poorly differentiated squamous cell carcinoma accounted for 0.5%, 41.7% and 15.0%, respectively, while the remaining 42.8% cases were microinvasion and were difficult to be graded. Mucosa lamina propria, muscularis mucosa and submucosa invasion accounted for 39.6%, 32.6% and 27.8%, respectively. Submucosa infiltration <200 µm (SM1) accounted for 9.1% and submucosa infiltration ≥200 µm (SM2) accounted for 18.7%. Lymphatic vessel invasion was related to the depth of tumor invasion, tumor budding, INF. The invasion rate of lymphatic vessels increased with the increase of infiltration depth and the grade of tumor budding. The lymphatic invasion rate in INFb/c group was higher than that in INFa group. There was no statistical difference in the incidence of lymphatic vessel invasion between well/moderately differentiated squamous cell carcinoma and poorly differentiated squamous cell carcinoma. Multivariate analysis showed that tumor budding was an independent risk factor for lymphatic vessel invasion. The complete resection occupied 69.5% (130 cases), while most of incomplete resection cases (57 cases) were involved by low-grade intraepithelial neoplasia. 69 cases had biopsy after ESD, among which there were 46 cases (66.67%) with no recurrence, 19 cases (27.54%) with recurrence, and 4 cases (5.80%) occurring in other sites. There was no statistical difference in recurrent rate between the complete resection (28.3%, 13/46) and the incomplete resection (31.6%, 6/19, P>0.05). CONCLUSIONS: Tumor invasion depth, INF, tumor budding andlymphatic vessel invasion should all be disclosed for the ESD specimen pathological report. Tumor budding was an independent risk factor for lymphatic vessel invasion.

Hope and the brain: Trait hope mediates the protective role of medial orbitofrontal cortex spontaneous activity against anxiety.

As a central research topic in the field of positive psychology, hope refers to an individual's goal-oriented expectations that include both agency thinking (i.e., the motivation to initiate and sustain actions to achieve goals) and pathway thinking (i.e., the capacity to find ways toward goals). Evidence from many previous studies has shown the role of hope in protecting against anxiety. However, little is known about the neurobiological basis of hope and the underlying mechanism that how hope reduces anxiety in the brain. Here, we employed fractional amplitude of low-frequency fluctuations (fALFF) to investigate these issues in 231 high school students using resting-state functional magnetic resonance imaging (RS-fMRI). The whole-brain correlation analyses revealed that higher trait hope was related to lower fALFF in the bilateral medial orbitofrontal cortex (mOFC), which is involved in reward-related processing, motivation production, problem solving and goal-directed behaviors. Furthermore, mediation analyses suggested that trait hope acted as a mediator in the association between mOFC spontaneous activity and anxiety. These results persisted even after adjusting for the effects of positive and negative affect. Overall, this study provides the first evidence for functional brain substrates underlying trait hope and reveals a potential mechanism that trait hope mediates the protective role of spontaneous brain activity against anxiety.

Brain Structure Linking Delay Discounting and Academic Performance.

As a component of self-discipline, delay discounting refers to the ability to wait longer for preferred rewards and plays a pivotal role in shaping students' academic performance. However, the neural basis of the association between delay discounting and academic performance remains largely unknown. Here, we examined the neuroanatomical substrates underlying delay discounting and academic performance in 214 adolescents via voxel-based morphometry (VBM) by performing structural magnetic resonance imaging (S-MRI). Behaviorally, we confirmed the significant correlation between delay discounting and academic performance. Neurally, whole-brain regression analyses indicated that regional gray matter volume (rGMV) of the left dorsolateral prefrontal cortex (DLPFC) was associated with both delay discounting and academic performance. Furthermore, delay discounting partly accounted for the association between academic performance and brain structure. Differences in the rGMV of the left DLPFC related to academic performance explained over one-third of the impact of delay discounting on academic performance. Overall, these results provide the first evidence for the common neural basis linking delay discounting and academic performance. Hum Brain Mapp 38:3917-3926, 2017. © 2017 Wiley Periodicals, Inc.

Anomalous single-subject based morphological cortical networks in drug-naive, first-episode major depressive disorder.

Major depressive disorder (MDD) has been associated with disruptions in the topological organization of brain morphological networks in group-level data. Such disruptions have not yet been identified in single-patients, which is needed to show relations with symptom severity and to evaluate their potential as biomarkers for illness. To address this issue, we conducted a cross-sectional structural brain network study of 33 treatment-naive, first-episode MDD patients and 33 age-, gender-, and education-matched healthy controls (HCs). Weighted graph-theory based network models were used to characterize the topological organization of brain networks between the two groups. Compared with HCs, MDD patients exhibited lower normalized global efficiency and higher modularity in their whole-brain morphological networks, suggesting impaired integration and increased segregation of morphological brain networks in the patients. Locally, MDD patients exhibited lower efficiency in anatomic organization for transferring information predominantly in default-mode regions including the hippocampus, parahippocampal gyrus, precuneus and superior parietal lobule, and higher efficiency in the insula, calcarine and posterior cingulate cortex, and in the cerebellum. Morphological connectivity comparisons revealed two subnetworks that exhibited higher connectivity strength in MDD mainly involving neocortex-striatum-thalamus-cerebellum and thalamo-hippocampal circuitry. MDD-related alterations correlated with symptom severity and differentiated individuals with MDD from HCs with a sensitivity of 87.9% and specificity of 81.8%. Our findings indicate that single subject grey matter morphological networks are often disrupted in clinically relevant ways in treatment-naive, first episode MDD patients. Circuit-specific changes in brain anatomic network organization suggest alterations in the efficiency of information transfer within particular brain networks in MDD. Hum Brain Mapp 38:2482-2494, 2017. © 2017 Wiley Periodicals, Inc.

Social intelligence mediates the protective role of resting-state brain activity in the social cognition network against social anxiety.

Background: Social intelligence refers to an important psychosocial skill set encompassing an array of abilities, including effective self-expression, understanding of social contexts, and acting wisely in social interactions. While there is ample evidence of its importance in various mental health outcomes, particularly social anxiety, little is known on the brain correlates underlying social intelligence and how it can mitigate social anxiety. Objective: This research aims to investigate the functional neural markers of social intelligence and their relations to social anxiety. Methods: Data of resting-state functional magnetic resonance imaging and behavioral measures were collected from 231 normal students aged 16 to 20 years (48% male). Whole-brain voxel-wise correlation analysis was conducted to detect the functional brain clusters related to social intelligence. Correlation and mediation analyses explored the potential role of social intelligence in the linkage of resting-state brain activities to social anxiety. Results: Social intelligence was correlated with neural activities (assessed as the fractional amplitude of low-frequency fluctuations, fALFF) among two key brain clusters in the social cognition networks: negatively correlated in left superior frontal gyrus (SFG) and positively correlated in right middle temporal gyrus. Further, the left SFG fALFF was positively correlated with social anxiety; brain-personality-symptom analysis revealed that this relationship was mediated by social intelligence. Conclusion: These results indicate that resting-state activities in the social cognition networks might influence a person's social anxiety via social intelligence: lower left SFG activity → higher social intelligence → lower social anxiety. These may have implication for developing neurobehavioral interventions to mitigate social anxiety.

Disrupted small-world white matter networks in patients with major depression and recent suicide plans or attempts.

Suicide is a major concern for health, and depression is an established proximal risk factor for suicide. This study aimed to investigate white matter features associated with suicide. We constructed white matter structural networks by deterministic tractography via diffusion tensor imaging in 51 healthy controls, 47 depressed patients without suicide plans or attempts and 56 depressed patients with suicide plans or attempts. Then, graph theory analysis was used to measure global and nodal network properties. We found that local efficiency was decreased and path length was increased in suicidal depressed patients compared to healthy controls and non-suicidal depressed patients; moreover, the clustering coefficient was decreased in depressed patients compared to healthy controls; and the global efficiency and normalized characteristic path length was increased in suicidal depressed patients compared to healthy controls. Similarly, compared with those in non-suicidal depressed patients, nodal efficiency in the thalamus, caudate, medial orbitofrontal cortex, hippocampus, olfactory cortex, supplementary motor area and Rolandic operculum was decreased. In summary, compared with those of non-suicidal depressed patients, the structural connectome of suicidal depressed patients exhibited weakened integration and segregation and decreased nodal efficiency in the fronto-limbic-basal ganglia-thalamic circuitry. These alterations in the structural networks of depressed suicidal brains provide insights into the underlying neurobiology of brain features associated with suicide.

Transcriptional Patterns of Brain Structural Covariance Network Abnormalities Associated With Suicidal Thoughts and Behaviors in Major Depressive Disorder.

BACKGROUND: Although brain structural covariance network (SCN) abnormalities have been associated with suicidal thoughts and behaviors (STBs) in individuals with major depressive disorder (MDD), previous studies have reported inconsistent findings based on small sample sizes, and underlying transcriptional patterns remain poorly understood. METHODS: Using a multicenter magnetic resonance imaging dataset including 218 MDD patients with STBs, 230 MDD patients without STBs, and 263 healthy control participants, we established individualized SCNs based on regional morphometric measures and assessed network topological metrics using graph theoretical analysis. Machine learning methods were applied to explore and compare the diagnostic value of morphometric and topological features in identifying MDD and STBs at the individual level. Brainwide relationships between STBs-related connectomic alterations and gene expression were examined using partial least squares regression. RESULTS: Group comparisons revealed that SCN topological deficits associated with STBs were identified in the prefrontal, anterior cingulate, and lateral temporal cortices. Combining morphometric and topological features allowed for individual-level characterization of MDD and STBs. Topological features made a greater contribution to distinguishing between patients with and without STBs. STBs-related connectomic alterations were spatially correlated with the expression of genes enriched for cellular metabolism and synaptic signaling. CONCLUSIONS: These findings revealed robust brain structural deficits at the network level, highlighting the importance of SCN topological measures in characterizing individual suicidality and demonstrating its linkage to molecular function and cell types, providing novel insights into the neurobiological underpinnings and potential markers for prediction and prevention of suicide.

Neuroanatomical dimensions in medication-free individuals with major depressive disorder and treatment response to SSRI antidepressant medications or placebo.

Major depressive disorder (MDD) is a heterogeneous clinical syndrome with widespread subtle neuroanatomical correlates. Our objective was to identify the neuroanatomical dimensions that characterize MDD and predict treatment response to selective serotonin reuptake inhibitor (SSRI) antidepressants or placebo. In the COORDINATE-MDD consortium, raw MRI data were shared from international samples (N = 1,384) of medication-free individuals with first-episode and recurrent MDD (N = 685) in a current depressive episode of at least moderate severity, but not treatment-resistant depression, as well as healthy controls (N = 699). Prospective longitudinal data on treatment response were available for a subset of MDD individuals (N = 359). Treatments were either SSRI antidepressant medication (escitalopram, citalopram, sertraline) or placebo. Multi-center MRI data were harmonized, and HYDRA, a semi-supervised machine-learning clustering algorithm, was utilized to identify patterns in regional brain volumes that are associated with disease. MDD was optimally characterized by two neuroanatomical dimensions that exhibited distinct treatment responses to placebo and SSRI antidepressant medications. Dimension 1 was characterized by preserved gray and white matter (N = 290 MDD), whereas Dimension 2 was characterized by widespread subtle reductions in gray and white matter (N = 395 MDD) relative to healthy controls. Although there were no significant differences in age of onset, years of illness, number of episodes, or duration of current episode between dimensions, there was a significant interaction effect between dimensions and treatment response. Dimension 1 showed a significant improvement in depressive symptoms following treatment with SSRI medication (51.1%) but limited changes following placebo (28.6%). By contrast, Dimension 2 showed comparable improvements to either SSRI (46.9%) or placebo (42.2%) (ß = -18.3, 95% CI (-34.3 to -2.3), P = 0.03). Findings from this case-control study indicate that neuroimaging-based markers can help identify the disease-based dimensions that constitute MDD and predict treatment response.

Metabolite Profiling of External and Internal Petals in Three Different Colors of Tea Flowers (Camellia sinensis) Using Widely Targeted Metabolomics.

The flower is the reproductive organ of the tea plant, while it is also processed into different kinds of products and thus of great significance to be utilized. In this study, the non-volatile secondary metabolites in the internal and external petals of white, white and pink, and pink tea flowers were studied using a widely targeted metabolomics method with ultra-high liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). A total of 429 metabolites were identified, including 195 flavonoids, 121 phenolic acids, 40 alkaloids, 29 lignans and coumarins, 19 tannins, 17 terpenoids, and 8 other metabolites. The metabolites in the internal and external petals of different colored flowers showed great changes in flavonoids. Most flavonoids and all tannins in the internal petals were higher compared with the external petals. Some phenolic acids were more accumulated in the external petals, while others showed opposite trends. The pink tea flower contained more flavonoids, alkaloids, lignans, coumarins, terpenoids, and tannins compared with white tea flowers. In addition, cyanidin-3-O-glucoside was more accumulated in the external petals of the pink flower, indicating that anthocyanin may be the main reason for the color difference between the pink and white tea flower. The enriched metabolic pathways of different colored flowers were involved in flavonoid biosynthesis, glycine, serine and threonine metabolism, glycerophospholipid metabolism, and phenylpropanoid biosynthesis. The findings of this study broaden the current understanding of non-volatile compound changes in tea plants. It is also helpful to lay a theoretical foundation for integrated applications of tea flowers.

Resting-state functional connectivity of the raphe nuclei in major depressive Disorder: A Multi-site study.

Accumulating evidence showed that major depressive disorder (MDD) is characterized by a dysfunction of serotonin neurotransmission. Raphe nuclei are the sources of most serotonergic neurons that project throughout the brain. Incorporating measurements of activity within the raphe nuclei into the analysis of connectivity characteristics may contribute to understanding how neurotransmitter synthesized centers are involved in thepathogenesisof MDD. Here, we analyzed the resting-state functional magnetic resonance imaging (RS-fMRI) dataset from 1,148 MDD patients and 1,079 healthy individuals recruited across nine centers. A seed-based analysis with the dorsal raphe and median raphe nuclei was performed to explore the functional connectivity (FC) alterations. Compared to controls, for dorsal raphe, the significantly decreased FC linking with the right precuneus and median cingulate cortex were found; for median raphe, the increased FC linking with right superior cerebellum (lobules V/VI) was found in MDD patients. In further exploratory analyzes, MDD-related connectivity alterations in dorsal and median raphe nuclei in different clinical factors remained highly similar to the main findings, indicating these abnormal connectivities are a disease-related alteration. Our study highlights a functional dysconnection pattern of raphe nuclei in MDD with multi-site big data. These findings help improve our understanding of the pathophysiology of depression and provide evidence of the theoretical foundation for the development of novel pharmacotherapies.