Exercise improves surrogate measures of liver histological response in metabolic dysfunction-associated steatotic liver disease.

BACKGROUND AND AIMS: Exercise is recommended for the management of metabolic dysfunction-associated steatotic liver disease (MASLD), yet effects on liver histology remain unknown, especially without significant weight loss. We aimed to examine changes in surrogate measures of liver histological response with exercise training. METHODS: We conducted a post hoc pooled analysis of three randomised controlled trials (duration: 12-20 weeks) comparing aerobic exercise interventions with controls. The primary outcome measure was a ≥30% relative reduction in (MRI-measured) liver fat, as a surrogate measure of liver histological response (the threshold necessary for fibrosis improvement). Secondary outcome measures were changes in other biomarkers of liver fibrosis, anthropometry, body composition and aerobic fitness. RESULTS: Eighty-eight adults (exercise: 54, control: 34; male: 67%) were included with mean (SD) age 51 (11) years and body mass index 33.3 (5.2) kg/m2. Following the intervention, exercise had ~5-fold (OR [95%CI]: 4.86 [1.72, 13.8], p = .002) greater odds of ≥30% relative reduction in MRI-measured liver fat compared with control. This paralleled the improvements in anthropometry (waist and hip circumference reduction), body composition (body fat, visceral and subcutaneous adipose tissue) and aerobic fitness (V̇O2peak, ventilatory threshold and exercise capacity). Importantly, these effects were independent of clinically significant body weight loss (<3% body weight). CONCLUSION: Exercise training led to clinically meaningful improvements in surrogate serum- and imaging-based measures of liver histological change, without clinically meaningful body weight reduction. These data reinforce the weight-neutral benefit of exercise training and suggest that aerobic training may improve liver fibrosis in patients with MASLD.

Quantitative imaging reveals steatosis and fibro-inflammation in multiple organs in people with type 2 diabetes: a real-world study.

We aimed to determine the extent of multi-organ fat accumulation and fibro-inflammation in individuals living with type 2 diabetes. We deeply phenotyped individuals with type 2 diabetes (134 from secondary care, 69 from primary care) with multi-organ, quantitative multi-parametric MRI and compared with 134 matched controls and 92 normal weight controls. We examined the impact of diabetes duration, obesity status and glycemic control. Ninety-three of the individuals with type 2 diabetes were re-evaluated at 7 months (median). Multi-organ abnormalities were more common in individuals with type 2 diabetes (94%) than in age, BMI-matched healthy or healthy normal weight people. We demonstrated a high burden of combined steatosis and fibro-inflammation, within the liver, pancreas and kidneys (41, 17 and 10%), associated with visceral adiposity (73%) and poor vascular health (82%). Obesity was most closely associated with advanced liver disease, renal and visceral steatosis, and multi-organ abnormalities whilst poor glycaemic control was associated with pancreatic fibro-inflammation. Pharmacological therapies with proven cardiorenal protection improved liver and vascular health unlike conventional glucose-lowering treatments, whilst weight loss or improved glycaemic control reduced multi-organ adiposity (p≤0.01). Quantitative imaging in people with type 2 diabetes highlights widespread organ abnormalities and may provide useful risk and treatment stratification.

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.

Whole brain morphologic features improve the predictive accuracy of IDH status and VEGF expression levels in gliomas.

Glioma is a systemic disease that can induce micro and macro alternations of whole brain. Isocitrate dehydrogenase and vascular endothelial growth factor are proven prognostic markers and antiangiogenic therapy targets in glioma. The aim of this study was to determine the ability of whole brain morphologic features and radiomics to predict isocitrate dehydrogenase status and vascular endothelial growth factor expression levels. This study recruited 80 glioma patients with isocitrate dehydrogenase wildtype and high vascular endothelial growth factor expression levels, and 102 patients with isocitrate dehydrogenase mutation and low vascular endothelial growth factor expression levels. Virtual brain grafting, combined with Freesurfer, was used to compute morphologic features including cortical thickness, LGI, and subcortical volume in glioma patient. Radiomics features were extracted from multiregional tumor. Pycaret was used to construct the machine learning pipeline. Among the radiomics models, the whole tumor model achieved the best performance (accuracy 0.80, Area Under the Curve 0.86), while, after incorporating whole brain morphologic features, the model had a superior predictive performance (accuracy 0.82, Area Under the Curve 0.88). The features contributed most in predicting model including the right caudate volume, left middle temporal cortical thickness, first-order statistics, shape, and gray-level cooccurrence matrix. Pycaret, based on morphologic features, combined with radiomics, yielded highest accuracy in predicting isocitrate dehydrogenase mutation and vascular endothelial growth factor levels, indicating that morphologic abnormalities induced by glioma were associated with tumor biology.

Shared and differing functional connectivity abnormalities of the default mode network in mild cognitive impairment and Alzheimer's disease.

Alzheimer's disease (AD) and mild cognitive impairment (MCI) both show abnormal resting-state functional connectivity (rsFC) of default mode network (DMN), but it is unclear to what extent these abnormalities are shared. Therefore, we performed a comprehensive meta-analysis, including 31 MCI studies and 20 AD studies. MCI patients, compared to controls, showed decreased within-DMN rsFC in bilateral medial prefrontal cortex/anterior cingulate cortex (mPFC/ACC), precuneus/posterior cingulate cortex (PCC), right temporal lobes, and left angular gyrus and increased rsFC between DMN and left inferior temporal gyrus. AD patients, compared to controls, showed decreased rsFC within DMN in bilateral mPFC/ACC and precuneus/PCC and between DMN and left inferior occipital gyrus and increased rsFC between DMN and right dorsolateral prefrontal cortex. Conjunction analysis showed shared decreased rsFC in mPFC/ACC and precuneus/PCC. Compared to MCI, AD had decreased rsFC in left precuneus/PCC and between DMN and left inferior occipital gyrus and increased rsFC in right temporal lobes. MCI and AD share a decreased within-DMN rsFC likely underpinning episodic memory deficits and neuropsychiatric symptoms, but differ in DMN rsFC alterations likely related to impairments in other cognitive domains such as language, vision, and execution. This may throw light on neuropathological mechanisms in these two stages of dementia.

Association of insulin resistance with the accumulation of saturated intramyocellular lipid: A comparison with other fat stores.

It has been shown using proton magnetic resonance spectroscopy (1 H MRS) that, in a group of females, whole-body insulin resistance was more closely related to accumulation of saturated intramyocellular lipid (IMCL) than to IMCL concentration alone. This has not been investigated in males. We investigated whether age- and body mass index-matched healthy males differ from the previously reported females in IMCL composition (measured as CH2 :CH3 ) and IMCL concentration (measured as CH3 ), and in their associations with insulin resistance. We ask whether saturated IMCL accumulation is more strongly associated with insulin resistance than other ectopic and adipose tissue lipid pools and remains a significant predictor when these other pools are taken into account. In this group of males, who had similar overall insulin sensitivity to the females, IMCL was similar between sexes. The males demonstrated similar and even stronger associations of IMCL with insulin resistance, supporting the idea that a marker reflecting the accumulation of saturated IMCL is more strongly associated with whole-body insulin resistance than IMCL concentration alone. However, this marker ceased to be a significant predictor of whole-body insulin resistance after consideration of other lipid pools, which implies that this measure carries no more information in practice than the other predictors we found, such as intrahepatic lipid and visceral adipose tissue. As the marker of saturated IMCL accumulation appears to be related to these two predictors and has a much smaller dynamic range, this finding does not rule out a role for it in the pathogenesis of insulin resistance.

Multivariate patterns of brain functional connectome associated with COVID-19-related negative affect symptoms.

Severe mental health problems with the representation of negative affect symptoms (NAS) have been increasingly reported during the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to explore the multivariate patterns of brain functional connectome predicting COVID-19-related NAS. This cohort study encompassed a group of university students to undergo neuroimaging scans before the pandemic, and we re-contacted participants for 1-year follow-up COVID-related NAS evaluations during the pandemic. Regularized canonical correlation analysis was used to identify connectome-based dimensions of NAS to compute pairs of canonical variates. The predictive ability of identified functional connectome to NAS dimensional scores was examined with a nested cross-validation. Two dimensions (i.e. mode stress and mode anxiety) were related to distinct patterns of brain functional connectome (r2 = 0.911, PFDR = 0.048; r2 = 0.901, PFDR = 0.037, respectively). Mode anxiety was characterized by high loadings in connectivity between affective network (AFN) and visual network (VN), while connectivity of the default mode network with dorsal attention network (DAN) were remarkably prominent in mode stress. Connectivity patterns within the DAN and between DAN and VN, ventral attention network, and AFN was common for both dimensions. The identified functional connectome can reliably predict mode stress (r = 0.37, MAE = 5.1, p < 0.001) and mode anxiety (r = 0.28, MAE = 5.4, p = 0.005) in the cross-validation. Our findings provide new insight into multivariate dimensions of COVID-related NAS, which may have implications for developing network-based biomarkers in psychological interventions for vulnerable individuals in the pandemic.

Multilayer analysis of dynamic network reconfiguration in pediatric posttraumatic stress disorder.

Neuroimage studies have reported functional connectome abnormalities in posttraumatic stress disorder (PTSD), especially in adults. However, these studies often treated the brain as a static network, and time-variance of connectome topology in pediatric posttraumatic stress disorder remain unclear. To explore case-control differences in dynamic connectome topology, resting-state functional magnetic resonance imaging data were acquired from 24 treatment-naïve non-comorbid pediatric posttraumatic stress disorder patients and 24 demographically matched trauma-exposed non-posttraumatic stress disorder controls. A graph-theoretic analysis was applied to construct time-varying modular structure of whole-brain networks by maximizing the multilayer modularity. Network switching rate at the global, subnetwork, and nodal levels were calculated and compared between posttraumatic stress disorder and trauma-exposed non-posttraumatic stress disorder groups, and their associations with posttraumatic stress disorder symptom severity and sex interactions were explored. At the global level, individuals with posttraumatic stress disorder exhibited significantly lower network switching rates compared to trauma-exposed non-posttraumatic stress disorder controls. This difference was mainly involved in default-mode and dorsal attention subnetworks, as well as in inferior temporal and parietal brain nodes. Posttraumatic stress disorder symptom severity was negatively correlated with switching rate in the global network and default mode network. No significant differences were observed in the interaction between diagnosis and sex/age. Pediatric posttraumatic stress disorder is associated with dynamic reconfiguration of brain networks, which may provide insights into the biological basis of this disorder.

Effects of PRRT2 mutation on brain gray matter networks in paroxysmal kinesigenic dyskinesia.

Although proline-rich transmembrane protein 2 is the primary causative gene of paroxysmal kinesigenic dyskinesia, its effects on the brain structure of paroxysmal kinesigenic dyskinesia patients are not yet clear. Here, we explored the influence of proline-rich transmembrane protein 2 mutations on similarity-based gray matter morphological networks in individuals with paroxysmal kinesigenic dyskinesia. A total of 51 paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 mutations, 55 paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 non-mutation, and 80 healthy controls participated in the study. We analyzed the structural connectome characteristics across groups by graph theory approaches. Relative to paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 non-mutation and healthy controls, paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 mutations exhibited a notable increase in characteristic path length and a reduction in both global and local efficiency. Relative to healthy controls, both patient groups showed reduced nodal metrics in right postcentral gyrus, right angular, and bilateral thalamus; Relative to healthy controls and paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 non-mutation, paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 mutations showed almost all reduced nodal centralities and structural connections in cortico-basal ganglia-thalamo-cortical circuit including bilateral supplementary motor area, bilateral pallidum, and right caudate nucleus. Finally, we used support vector machine by gray matter network matrices to classify paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 mutations and paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 non-mutation, achieving an accuracy of 73%. These results show that proline-rich transmembrane protein 2 related gray matter network deficits may contribute to paroxysmal kinesigenic dyskinesia, offering new insights into its pathophysiological mechanisms.

Distinct pre-COVID brain structural signatures in COVID-19-related post-traumatic stress symptoms and post-traumatic growth.

Post-traumatic stress symptoms and post-traumatic growth are common co-occurring psychological responses following exposure to traumatic events (such as COVID-19 pandemic), their mutual relationship remains unclear. To explore this relationship, structural magnetic resonance imaging data were acquired from 115 general college students before the COVID-19 pandemic, and follow-up post-traumatic stress symptoms and post-traumatic growth measurements were collected during the pandemic. Voxel-based morphometry was conducted and individual structural covariance networks based on gray matter volume were further analyzed using graph theory and partial least squares correlation. Behavioral correlation found no significant relationship between post-traumatic stress symptoms and post-traumatic growth. Voxel-based morphometry analyses showed that post-traumatic stress symptoms were positively correlated with gray matter volume in medial prefrontal cortex/dorsal anterior cingulate cortex, and post-traumatic growth was negatively correlated with gray matter volume in left dorsolateral prefrontal cortex. Structural covariance network analyses found that post-traumatic stress symptoms were negatively correlated with the local efficiency and clustering coefficient of the network. Moreover, partial least squares correlation showed that post-traumatic stress symptoms were correlated with pronounced nodal properties patterns in default mode, sensory and motor regions, and a marginal correlation of post-traumatic growth with a nodal property pattern in emotion regulation-related regions. This study advances our understanding of the neurobiological substrates of post-traumatic stress symptoms and post-traumatic growth, and suggests that they may have different neuroanatomical features.

Pre-COVID brain network topology prospectively predicts social anxiety alterations during the COVID-19 pandemic.

Background: Social anxiety (SA) is a negative emotional response that can lead to mental health issues, which some have experienced during the coronavirus disease 2019 (COVID-19) pandemic. Little attention has been given to the neurobiological mechanisms underlying inter-individual differences in SA alterations related to COVID-19. This study aims to identify neurofunctional markers of COVID-specific SA development. Methods: 110 healthy participants underwent resting-state magnetic resonance imaging and behavioral tests before the pandemic (T1, October 2019 to January 2020) and completed follow-up behavioral measurements during the pandemic (T2, February to May 2020). We constructed individual functional networks and used graph theoretical analysis to estimate their global and nodal topological properties, then used Pearson correlation and partial least squares correlations examine their associations with COVID-specific SA alterations. Results: In terms of global network parameters, SA alterations (T2-T1) were negatively related to pre-pandemic brain small-worldness and normalized clustering coefficient. In terms of nodal network parameters, SA alterations were positively linked to a pronounced degree centrality pattern, encompassing both the high-level cognitive networks (dorsal attention network, cingulo-opercular task control network, default mode network, memory retrieval network, fronto-parietal task control network, and subcortical network) and low-level perceptual networks (sensory/somatomotor network, auditory network, and visual network). These findings were robust after controlling for pre-pandemic general anxiety, other stressful life events, and family socioeconomic status, as well as by treating SA alterations as categorical variables. Conclusions: The individual functional network associated with SA alterations showed a disrupted topological organization with a more random state, which may shed light on the neurobiological basis of COVID-related SA changes at the network level.

No evidence of compensatory changes in energy balance, despite reductions in body weight and liver fat, during dapagliflozin treatment in type 2 diabetes mellitus: A randomized, double-blind, placebo-controlled, cross-over trial (ENERGIZE).

AIM: This study assessed the impact of dapagliflozin on food intake, eating behaviour, energy expenditure, magnetic resonance imaging (MRI)-determined brain response to food cues and body composition in patients with type 2 diabetes mellitus (T2D). MATERIALS AND METHODS: Patients were given dapagliflozin 10 mg once daily in a randomized, double-blind, placebo-controlled trial with short-term (1 week) and long-term (12 weeks) cross-over periods. The primary outcome was the difference in test meal food intake between long-term dapagliflozin and placebo treatment. Secondary outcomes included short-term differences in test meal food intake, short- and long-term differences in appetite and eating rate, energy expenditure and functional MRI brain activity in relation to food images. We determined differences in glycated haemoglobin, weight, liver fat (by 1 H magnetic resonance spectroscopy) and subcutaneous/visceral adipose tissue volumes (by MRI). RESULTS: In total, 52 patients (43% were women) were randomized; with the analysis of 49 patients: median age 58 years, weight 99.1 kg, body mass index 35 kg/m2 , glycated haemoglobin 49 mmol/mol. Dapagliflozin reduced glycated haemoglobin by 9.7 mmol/mol [95% confidence interval (CI) 3.91-16.27, p = .004], and body weight (-2.84 vs. -0.87 kg) versus placebo. There was no short- or long-term difference in test meal food intake between dapagliflozin and placebo [mean difference 5.7 g (95% CI -127.9 to 139.3, p = .933); 15.8 g (95% CI -147.7 to 116.1, p = .813), respectively] nor in the rate of eating, energy expenditure, appetite, or brain responses to food cues. Liver fat (median reduction -4.7 vs. 1.95%), but not subcutaneous/visceral adipose tissue, decreased significantly with 12 weeks of dapagliflozin. CONCLUSIONS: The reduction in body weight and liver fat with dapagliflozin was not associated with compensatory adaptations in food intake or energy expenditure.

Shared and distinct abnormalities of brain magnetization transfer ratio in schizophrenia and major depressive disorder: a comparative voxel-based meta-analysis.

BACKGROUND: Patients with schizophrenia (SCZ) and major depressive disorder (MDD) share significant clinical overlap, although it remains unknown to what extent this overlap reflects shared neural profiles. To identify the shared and specific abnormalities in SCZ and MDD, we performed a whole-brain voxel-based meta-analysis using magnetization transfer imaging, a technique that characterizes the macromolecular structural integrity of brain tissue in terms of the magnetization transfer ratio (MTR). METHODS: A systematic search based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was conducted in PubMed, EMBASE, International Scientific Index (ISI) Web of Science, and MEDLINE for relevant studies up to March 2022. Two researchers independently screened the articles. Rigorous scrutiny and data extraction were performed for the studies that met the inclusion criteria. Voxel-wise meta-analyses were conducted using anisotropic effect size-signed differential mapping with a unified template. Meta-regression was used to explore the potential effects of demographic and clinical characteristics. RESULTS: A total of 15 studies with 17 datasets describing 365 SCZ patients, 224 MDD patients, and 550 healthy controls (HCs) were identified. The conjunction analysis showed that both disorders shared higher MTR than HC in the left cerebellum ( P =0.0006) and left fusiform gyrus ( P =0.0004). Additionally, SCZ patients showed disorder-specific lower MTR in the anterior cingulate/paracingulate gyrus, right superior temporal gyrus, and right superior frontal gyrus, and higher MTR in the left thalamus, precuneus/cuneus, posterior cingulate gyrus, and paracentral lobule; and MDD patients showed higher MTR in the left middle occipital region. Meta-regression showed no statistical significance in either group. CONCLUSIONS: The results revealed a structural neural basis shared between SCZ and MDD patients, emphasizing the importance of shared neural substrates across psychopathology. Meanwhile, distinct disease-specific characteristics could have implications for future differential diagnosis and targeted treatment.

Psychological resilience mediates the protective role of default-mode network functional connectivity against COVID-19 vicarious traumatization.

Vicarious traumatization (VT), a negative reaction to witnessing others' trauma, has been experienced by some people during the COVID-19 pandemic, and can lead to mental health problems. This study aimed to identify functional brain markers of COVID-specific VT and explore the psychological mechanism underlying the brain-VT link. One hundred healthy participants underwent resting-state functional magnetic resonance imaging before the pandemic (October 2019-January 2020) and completed VT measurement during the pandemic (February-April 2020). Whole-brain correlation analysis based on global functional connectivity density (FCD) mapping revealed that VT was negatively correlated with FCD in the right inferior temporal gyrus (ITG) (i.e., the lower FCD in ITG, the worse the VT), identified by mapping onto known large-scale networks as part of the default-mode network (DMN). Resting-state functional connectivity (RSFC) analysis using ITG as seed found that VT was predicted by lower functional connectivity between ITG and other DMN regions including left medial prefrontal cortex, left orbitofrontal cortex, right superior frontal gyrus, right inferior parietal lobule and bilateral precuneus (i.e., the lower the ITG-DMN connectivity, the worse the VT). Mediation analyses suggested that psychological resilience served as a mediator in these associations of ITG FCD and ITG-DMN RSFC with VT. Our results provide novel evidence on the brain basis of VT and emphasize psychological resilience as an important link from DMN functional connectivity to COVID-specific-VT. This may facilitate public health interventions by helping identify individuals at risk of stress- and trauma-related psychopathologies.

Disrupted brain gray matter connectome in social anxiety disorder: a novel individualized structural covariance network analysis.

Phenotyping approaches grounded in structural network science can offer insights into the neurobiological substrates of psychiatric diseases, but this remains to be clarified at the individual level in social anxiety disorder (SAD). Using a recently developed approach combining probability density estimation and Kullback-Leibler divergence, we constructed single-subject structural covariance networks (SCNs) based on multivariate morphometry (cortical thickness, surface area, curvature, and volume) and quantified their global/nodal network properties using graph-theoretical analysis. We compared network metrics between SAD patients and healthy controls (HC) and analyzed the relationship to clinical characteristics. We also used support vector machine analysis to explore the ability of graph-theoretical metrics to discriminate SAD patients from HC. Globally, SAD patients showed higher global efficiency, shorter characteristic path length, and stronger small-worldness. Locally, SAD patients showed abnormal nodal centrality mainly involving left superior frontal gyrus, right superior parietal lobe, left amygdala, right paracentral gyrus, right lingual, and right pericalcarine cortex. Altered topological metrics were associated with the symptom severity and duration. Graph-based metrics allowed single-subject classification of SAD versus HC with total accuracy of 78.7%. This finding, that the topological organization of SCNs in SAD patients is altered toward more randomized configurations, adds to our understanding of network-level neuropathology in SAD.

Gray matter alterations in adolescent major depressive disorder and adolescent bipolar disorder.

BACKGROUND: Gray matter volume (GMV) alterations in several emotion-related brain areas are implicated in mood disorders, but findings have been inconsistent in adolescents with major depressive disorder (MDD) or bipolar disorder (BD). METHODS: We conducted a comprehensive meta-analysis of 35 region-of-interest (ROI) and 18 whole-brain voxel-based morphometry (VBM) MRI studies in adolescent MDD and adolescent BD, and indirectly compared the results in the two groups. The effects of age, sex, and other demographic and clinical scale scores were explored using meta-regression analysis. RESULTS: In the ROI meta-analysis, right putamen volume was decreased in adolescents with MDD, while bilateral amygdala volume was decreased in adolescents with BD compared to healthy controls (HC). In the whole-brain VBM meta-analysis, GMV was increased in right middle frontal gyrus and decreased in left caudate in adolescents with MDD compared to HC, while in adolescents with BD, GMV was increased in left superior frontal gyrus and decreased in limbic regions compared with HC. MDD vs BD comparison revealed volume alteration in the prefrontal-limbic system. LIMITATION: Different clinical features limit the comparability of the samples, and small sample size and insufficient clinical details precluded subgroup analysis or meta-regression analyses of these variables. CONCLUSIONS: Distinct patterns of GMV alterations in adolescent MDD and adolescent BD could help to differentiate these two populations and provide potential diagnostic biomarkers.

Neural correlates of neuroticism: A coordinate-based meta-analysis of resting-state functional brain imaging studies.

Neuroticism is one of the most robust higher-order personality traits associated with negative emotionality and risk of mental disorders. Many studies have investigated relationships between neuroticism and the brain, but the results have been inconsistent. We conducted a meta-analysis of whole-brain resting-state functional neuroimaging studies to identify the most stable neurofunctional substrates of neuroticism. We found stable significant positive correlations between neuroticism and resting-state brain activity in the left middle temporal gyrus (MTG), left striatum, and right hippocampus. In contrast, resting-state brain activity in the left superior temporal gyrus (STG) and right supramarginal gyrus (SMG) was negatively associated with neuroticism. Additionally, meta-regression analysis revealed brain regions in which sex and age moderated the link of spontaneous activity with neuroticism. This is the first study to provide a comprehensive understanding of resting-state brain activity correlates of neuroticism, and the findings may be useful for the targeting of specific brain regions for interventions to decrease the risks of mental health problems.