Source-free collaborative domain adaptation via multi-perspective feature enrichment for functional MRI analysis.

Resting-state functional MRI (rs-fMRI) is increasingly employed in multi-site research to analyze neurological disorders, but there exists cross-site/domain data heterogeneity caused by site effects such as differences in scanners/protocols. Existing domain adaptation methods that reduce fMRI heterogeneity generally require accessing source domain data, which is challenging due to privacy concerns and/or data storage burdens. To this end, we propose a source-free collaborative domain adaptation (SCDA) framework using only a pretrained source model and unlabeled target data. Specifically, a multi-perspective feature enrichment method (MFE) is developed to dynamically exploit target fMRIs from multiple views. To facilitate efficient source-to-target knowledge transfer without accessing source data, we initialize MFE using parameters of a pretrained source model. We also introduce an unsupervised pretraining strategy using 3,806 unlabeled fMRIs from three large-scale auxiliary databases. Experimental results on three public and one private datasets show the efficacy of our method in cross-scanner and cross-study prediction.

Analysis of the risk factors of the radiation-induced encephalopathy in nasopharyngeal carcinoma: A retrospective cohort study.

To analyze the related factors of radiation-induced encephalopathy in nasopharyngeal carcinoma (NPC) to identify the risk factors and their clinical significance. This retrospective cohort study included 707 NPC patients. They had undergone conventional and enhanced computed tomography or magnetic resonance imaging scans. They were divided into the radiation-induced encephalopathy group and the no encephalopathy group according to the imaging examination. Detailed clinical information was collected. The incidence of radiation-induced encephalopathy in NPC was 22.2%, in which 124 were radiation-induced encephalopathy and 33 were reirradiation patients. We found that age, pathological type, radiation method, hypertension, radiation course, relapse, carotid/cerebral arteriosclerosis, clinical stage, and radiotherapy dose were statistically significant between the two groups (p < 0.05). Multiple logistic regression showed that clinical stage, age, radiotherapy method, hypertension, carotid/cerebral arteriosclerosis, and radiation courses after a reoccurrence of NPC were risk factors for radiation-induced encephalopathy. The more advanced the clinical stage was and the older the patient, the greater the risk. Radiotherapy method, radiation course, hypertension, carotid/cerebral arteriosclerosis, age, and clinical stage were the risk factors associated with radiation-induced encephalopathy in NPC.

Resting-state neural activity and cerebral blood flow alterations in type 2 diabetes mellitus: Insights from hippocampal subfields.

OBJECTIVE: In this study, multimodal magnetic resonance imaging (MRI) imaging was used to deeply analyze the changes of hippocampal subfields perfusion and function in patients with type 2 diabetes mellitus (T2DM), aiming to provide image basis for the diagnosis of hippocampal-related nerve injury in patients with T2DM. METHODS: We recruited 35 patients with T2DM and 40 healthy control subjects (HCs). They underwent resting-state functional MRI (rs-fMRI), arterial spin labeling (ASL) scans, and a series of cognitive tests. Then, we compared the differences of two groups in the cerebral blood flow (CBF) value, amplitude of low-frequency fluctuation (ALFF) value, and regional homogeneity (ReHo) value of the bilateral hippocampus subfields. RESULTS: The CBF values of cornu ammonis area 1 (CA1), dentate gyrus (DG), and subiculum in the right hippocampus of T2DM group were significantly lower than those of HCs. The ALFF values of left hippocampal CA3, subiculum, and bilateral hippocampus amygdala transition area (HATA) were higher than those of HCs in T2DM group. The ReHo values of CA3, DG, subiculum, and HATA in the left hippocampus of T2DM group were higher than those of HCs. In the T2DM group, HbAc1 and FINS were negatively correlated with imaging characteristics in some hippocampal subregions. CONCLUSION: This study indicates that T2DM patients had decreased perfusion in the CA1, DG, and subiculum of the right hippocampus, and the right hippocampus subiculum was associated with chronic hyperglycemia. Additionally, we observed an increase in spontaneous neural activity within the left hippocampal CA3, subiculum, and bilateral HATA regions, as well as an enhanced local neural coordination in the left hippocampal CA3, DG, HATA, and subiculum among patients with type 2 diabetes, which may reflect an adaptive compensation for cognitive decline. However, this compensation may decline with the exacerbation of metabolic disorders.

Meta-analysis of the value of dual-energy computed tomography in the diagnosis of anterior cruciate ligament injuries of the knee.

BACKGROUND: This meta-analysis assessed the efficacy of dual-energy computed tomography (DECT) in the diagnosis of anterior cruciate ligament (ACL) injuries. METHODS: The literature search was performed up to December 8, 2023, and included a comprehensive examination of several databases: PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang, and VIP. Diagnostic metrics sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and a summary receiver operating characteristic (SROC) were determined using a bivariate model analysis. Heterogeneity within the data was explored through subgroup analyses, which considered variables including geographical region, use of magnetic resonance imaging (MRI), arthroscopy, and study design. RESULTS: The analysis included ten studies encompassing 544 patients. DECT demonstrated substantial diagnostic utility for ACL injuries of the knee, with a sensitivity of 0.91 (95% confidence interval [CI]: 0.88-0.94), a specificity of 0.90 (95% CI: 0.81-0.95), a PLR of 9.20 (95% CI: 4.50-19.00), a NLR of 0.10 (95% CI: 0.06-0.14), a DOR of 97.00 (95% CI: 35.00-268.00), and an area under the curve (AUC) of 0.95 (95% CI: 0.93-0.97). The subgroup analyses consistently showed high diagnostic precision for ACL injuries across Asian population (sensitivity: 0.91, specificity: 0.91, PLR: 9.90, NLR: 0.09, DOR: 105.00, AUC: 0.96), in MRI subgroup (sensitivity: 0.85, specificity: 0.94, PLR: 9.57, NLR: 0.18, DOR: 56.00, AUC: 0.93), in arthroscopy subgroup (sensitivity: 0.92, specificity: 0.89, PLR: 8.40, NLR: 0.09, DOR: 94.00, AUC: 0.95), for prospective studies (sensitivity: 0.92, specificity: 0.88, PLR: 7.40, NLR: 0.09, DOR: 78.00, AUC: 0.95), and for retrospective studies (sensitivity: 0.91, specificity: 0.93, AUC: 0.93). CONCLUSION: DECT exhibits a high value in diagnosing ACL injuries. The significant diagnostic value of DECT provides clinicians with a powerful tool that enhances the accuracy and efficiency of diagnosis and optimizes patient management and treatment outcomes.

Cortical Morphological Networks Differ Between Gyri and Sulci.

This study explored how the human cortical folding pattern composed of convex gyri and concave sulci affected single-subject morphological brain networks, which are becoming an important method for studying the human brain connectome. We found that gyri-gyri networks exhibited higher morphological similarity, lower small-world parameters, and lower long-term test-retest reliability than sulci-sulci networks for cortical thickness- and gyrification index-based networks, while opposite patterns were observed for fractal dimension-based networks. Further behavioral association analysis revealed that gyri-gyri networks and connections between gyral and sulcal regions significantly explained inter-individual variance in Cognition and Motor domains for fractal dimension- and sulcal depth-based networks. Finally, the clinical application showed that only sulci-sulci networks exhibited morphological similarity reductions in major depressive disorder for cortical thickness-, fractal dimension-, and gyrification index-based networks. Taken together, these findings provide novel insights into the constraint of the cortical folding pattern to the network organization of the human brain.

Functional connectivity density aberrance in type 2 diabetes mellitus with and without mild cognitive impairment.

Purpose: The objective of this study was to investigate alterations in functional connectivity density (FCD) mapping and their impact on functional connectivity (FC) among individuals diagnosed with Type 2 diabetes mellitus (T2DM) across different cognitive states. Moreover, the study sought to explore the potential association between aberrant FCD/FC patterns and clinical or cognitive variables. Methods: A total of 211 participants were recruited for this study, consisting of 75 healthy controls (HCs), 89 T2DM patients with normal cognitive function (DMCN), and 47 T2DM patients with mild cognitive impairment (DMCI). The study employed FCD analysis to pinpoint brain regions exhibiting significant FCD alterations. Subsequently, these regions showing abnormal FCD served as seeds for FC analysis. Exploratory partial correlations were conducted to explore the relationship between clinical biochemical indicators, neuropsychological test scores, and altered FCD or FC. Results: The FCD analysis revealed an increased trend in global FCD (gFCD), local FCD (lFCD), and long-range FCD (lrFCD) within the bilateral supramarginal gyrus (SMG) among individuals with DMCN. Additionally, significant lFCD alterations were observed in the right inferior frontal gyrus and left precuneus when comparing DMCN to HCs and DMCI. Conclusion: When comparing individuals with T2DM and healthy controls (HCs), it was revealed that DMCN exhibited significant improvements in FCD. This suggests that the brain may employ specific compensatory mechanisms to maintain normal cognitive function at this stage. Our findings provide a novel perspective on the neural mechanisms involved in cognitive decline associated with T2DM.

A study on the association between prefrontal functional connectivity and non-suicidal self-injury in adolescents with depression.

Objective: Among adolescents with depression, the occurrence of non-suicidal self-injury (NSSI) behavior is prevalent, constituting a high-risk factor for suicide. However, there has been limited research on the neuroimaging mechanisms underlying adolescent depression and NSSI behavior, and the potential association between the two remains unclear. Therefore, this study aims to investigate the alterations in functional connectivity (FC) of the regions in the prefrontal cortex with the whole brain, and elucidates the relationship between these alterations and NSSI behavior in adolescents with depression. Methods: A total of 68 participants were included in this study, including 35 adolescents with depression and 33 healthy controls. All participants underwent assessments using the 17-item Hamilton Depression Rating Scale (17-HAMD) and the Ottawa Self-Harm Inventory. In addition, functional magnetic resonance imaging (fMRI) data of the participants' brains were collected. Subsequently, the FCs of the regions in the prefrontal cortex with the whole brain was calculated. The FCs showing significant differences were then subjected to correlation analyses with 17-HAMD scores and NSSI behavior scores. Result: Compared to the healthy control group, the adolescent depression group exhibited decreased FCs in several regions, including the right frontal eye field, left dorsolateral prefrontal cortex, right orbitofrontal cortex, left insula and right anterior cingulate coetex. The 17-HAMD score was positively correlated with the frequency of NSSI behavior within 1 year (rs = 0.461, p = 0.005). The FC between the right anterior cingulate cortex and the right precuneus showed a negative correlation with the 17-HAMD scores (rs = -0.401, p = 0.023). Additionally, the FC between the right orbitofrontal cortex and the right insula, demonstrated a negative correlation with the frequency of NSSI behavior within 1 year (rs = -0.438, p = 0.012, respectively). Conclusion: Adolescents with depression showed decreased FCs of the prefrontal cortex with multiple brain regions, and some of these FCs were associated with the NSSI frequency within 1 year. This study provided neuroimaging evidence for the neurophysiological mechanisms underlying adolescent depression and its comorbidity with NSSI behavior.

Cross-ancestry genome-wide association studies of brain imaging phenotypes.

Genome-wide association studies of brain imaging phenotypes are mainly performed in European populations, but other populations are severely under-represented. Here, we conducted Chinese-alone and cross-ancestry genome-wide association studies of 3,414 brain imaging phenotypes in 7,058 Chinese Han and 33,224 white British participants. We identified 38 new associations in Chinese-alone analyses and 486 additional new associations in cross-ancestry meta-analyses at P < 1.46 × 10-11 for discovery and P < 0.05 for replication. We pooled significant autosomal associations identified by single- or cross-ancestry analyses into 6,443 independent associations, which showed uneven distribution in the genome and the phenotype subgroups. We further divided them into 44 associations with different effect sizes and 3,557 associations with similar effect sizes between ancestries. Loci of these associations were shared with 15 brain-related non-imaging traits including cognition and neuropsychiatric disorders. Our results provide a valuable catalog of genetic associations for brain imaging phenotypes in more diverse populations.

Structural characteristics of amygdala subregions in type 2 diabetes mellitus.

Type 2 diabetes mellitus (T2DM) patients often suffer from depressive symptoms, which seriously affect cooperation in treatment and nursing. The amygdala plays a significant role in depression. This study aims to explore the microstructural alterations of the amygdala in T2DM and to investigate the relationship between the alterations and depressive symptoms. Fifty T2DM and 50 healthy controls were included. Firstly, the volumes of subcortical regions and subregions of amygdala were calculated by FreeSurfer. Covariance analysis (ANCOVA) was conducted between the two groups with covariates of age, sex, and estimated total intracranial volume to explore the differences in volume of subcortical regions and subregions of amygdala. Furthermore, the structural covariance within the amygdala subregions was performed. Moreover, we investigate the correlation between depressive symptoms and the volume of subcortical regions and amygdala subregions in T2DM. We observed a reduction in the volume of the bilateral cortico-amygdaloid transition area, left basal nucleus, bilateral accessory basal nucleus, left anterior amygdaloid area of amygdala, the left thalamus and left hippocampus in T2DM. T2DM patients showed decreased structural covariance connectivity between left paralaminar nucleus and the right central nucleus. Moreover, there was a negative correlation between self-rating depression scale scores and the volume of the bilateral cortico-amygdaloid transition area in T2DM. This study reveals extensive structural alterations in the amygdala subregions of T2DM patients. The reduction in the volume of the bilateral cortico-amygdaloid transition area may be a promising imaging marker for early recognition of depressive symptoms in T2DM.

Construction of a Female Sterility Maintaining System Based on a Novel Mutation of the MEL2 Gene.

BACKGROUND: Hybrid rice has significant yield advantage and stress tolerance compared with inbred rice. However, production of hybrid rice seeds requires extensive manual labors. Currently, hybrid rice seeds are produced by crosspollination of male sterile lines by fertile paternal lines. Because seeds from paternal lines can contaminate the hybrid seeds, mechanized production by mixed-seeding and mixed-harvesting is difficult. This problem can be solved if the paternal line is female sterile. RESULTS: Here we identified a female infertile mutant named h569 carrying a novel mutation (A1106G) in the MEL2 gene that was previously reported to regulate meiosis entry both in male and female organs. h569 mutant is female infertile but male normal, suggesting that MEL2 regulates meiosis entry in male and female organs through distinct pathways. The MEL2 gene and h569 mutant gave us tools to construct female sterility maintaining systems that can be used for propagation of female sterile lines. We connected the wild-type MEL2 gene with pollen-killer gene ZmAA1 and seed-marker gene DsRed2 in one T-DNA cassette and transformed it into ZZH1607, a widely used restorer line. Transgenic line carrying a single transgene inserted in an intergenic region was selected to cross with h569 mutant. F2 progeny carrying homozygous A1106G mutation and hemizygous transgene displayed 1:1 segregation of fertile and infertile pollen grains and 1:1 segregation of fluorescent and non-fluorescent seeds upon self-fertilization. All of the non-fluorescent seeds generated female infertile plants, while the fluorescent seeds generated fertile plants that reproduced in the way as their previous generation. CONCLUSIONS: These results indicated that the female sterility maintaining system constructed in the study can be used to breed and propagate paternal lines that are female infertile. The application of this system will enable mechanized production of hybrid rice seed by using the mixed-seeding and mixed harvesting approach, which will significantly reduce the cost in hybrid rice seed production.

Use of Computed Tomography-Based Texture Analysis to Differentiate Benign From Malignant Salivary Gland Lesions.

OBJECTIVE: Salivary gland lesions show overlapping morphological findings and types of time/intensity curves. This research aimed to evaluate the role of 2-phase multislice spiral computed tomography (MSCT) texture analysis in differentiating between benign and malignant salivary gland lesions. METHODS: In this prospective study, MSCT was carried out on 90 patients. Each lesion was segmented on axial computed tomography (CT) images manually, and 33 texture features and morphological CT features were assessed. Logistic regression analysis was used to confirm predictors of malignancy ( P < 0.05 was considered to be statistically significant), followed by receiver operating characteristics analysis to assess the diagnostic performance. RESULTS: Univariate logistic regression analysis revealed that morphological CT features (shape, size, and invasion of adjacent tissues) and 17 CT texture parameters had significant differences between benign and malignant lesions ( P < 0.05). Multivariate binary logistic regression demonstrated that shape, invasion of adjacent tissues, entropy, and inverse difference moment were independent factors for malignant tumors. The diagnostic accuracy values of multivariate binary logistic models based on morphological parameters, CT texture features, and a combination of both were 87.8%, 90%, and 93.3%, respectively. CONCLUSIONS: Two-phase MSCT texture analysis was conducive to differentiating between malignant and benign neoplasms in the salivary gland, especially when combined with morphological CT features.

Aberrant dynamic functional network connectivity in type 2 diabetes mellitus individuals.

An increasing number of recent brain imaging studies are dedicated to understanding the neuro mechanism of cognitive impairment in type 2 diabetes mellitus (T2DM) individuals. In contrast to efforts to date that are limited to static functional connectivity, here we investigate abnormal connectivity in T2DM individuals by characterizing the time-varying properties of brain functional networks. Using group independent component analysis (GICA), sliding-window analysis, and k-means clustering, we extracted thirty-one intrinsic connectivity networks (ICNs) and estimated four recurring brain states. We observed significant group differences in fraction time (FT) and mean dwell time (MDT), and significant negative correlation between the Montreal Cognitive Assessment (MoCA) scores and FT/MDT. We found that in the T2DM group the inter- and intra-network connectivity decreases and increases respectively for the default mode network (DMN) and task-positive network (TPN). We also found alteration in the precuneus network (PCUN) and enhanced connectivity between the salience network (SN) and the TPN. Our study provides evidence of alterations of large-scale resting networks in T2DM individuals and shed light on the fundamental mechanisms of neurocognitive deficits in T2DM.

Genome-wide association study of hippocampal blood-oxygen-level-dependent-cerebral blood flow correlation in Chinese Han population.

Correlation between blood-oxygen-level-dependent (BOLD) and cerebral blood flow (CBF) has been used as an index of neurovascular coupling. Hippocampal BOLD-CBF correlation is associated with neurocognition, and the reduced correlation is associated with neuropsychiatric disorders. We conducted the first genome-wide association study of the hippocampal BOLD-CBF correlation in 4,832 Chinese Han subjects. The hippocampal BOLD-CBF correlation had an estimated heritability of 16.2-23.9% and showed reliable genome-wide significant association with a locus at 3q28, in which many variants have been linked to neuroimaging and cerebrospinal fluid markers of Alzheimer's disease. Gene-based association analyses showed four significant genes (GMNC, CRTC2, DENND4B, and GATAD2B) and revealed enrichment for mast cell calcium mobilization, microglial cell proliferation, and ubiquitin-related proteolysis pathways that regulate different cellular components of the neurovascular unit. This is the first unbiased identification of the association of hippocampal BOLD-CBF correlation, providing fresh insights into the genetic architecture of hippocampal neurovascular coupling.

Functional connectome through the human life span.

The functional connectome of the human brain represents the fundamental network architecture of functional interdependence in brain activity, but its normative growth trajectory across the life course remains unknown. Here, we aggregate the largest, quality-controlled multimodal neuroimaging dataset from 119 global sites, including 33,809 task-free fMRI and structural MRI scans from 32,328 individuals ranging in age from 32 postmenstrual weeks to 80 years. Lifespan growth charts of the connectome are quantified at the whole cortex, system, and regional levels using generalized additive models for location, scale, and shape. We report critical inflection points in the non-linear growth trajectories of the whole-brain functional connectome, particularly peaking in the fourth decade of life. Having established the first fine-grained, lifespan-spanning suite of system-level brain atlases, we generate person-specific parcellation maps and further show distinct maturation timelines for functional segregation within different subsystems. We identify a spatiotemporal gradient axis that governs the life-course growth of regional connectivity, transitioning from primary sensory cortices to higher-order association regions. Using the connectome-based normative model, we demonstrate substantial individual heterogeneities at the network level in patients with autism spectrum disorder and patients with major depressive disorder. Our findings shed light on the life-course evolution of the functional connectome and serve as a normative reference for quantifying individual variation in patients with neurological and psychiatric disorders.

Covariation of preadult environmental exposures, adult brain imaging phenotypes, and adult personality traits.

Exposure to preadult environmental exposures may have long-lasting effects on mental health by affecting the maturation of the brain and personality, two traits that interact throughout the developmental process. However, environment-brain-personality covariation patterns and their mediation relationships remain unclear. In 4297 healthy participants (aged 18-30 years), we combined sparse multiple canonical correlation analysis with independent component analysis to identify the three-way covariation patterns of 59 preadult environmental exposures, 760 adult brain imaging phenotypes, and five personality traits, and found two robust environment-brain-personality covariation models with sex specificity. One model linked greater stress and less support to weaker functional connectivity and activity in the default mode network, stronger activity in subcortical nuclei, greater thickness and volume in the occipital, parietal and temporal cortices, and lower agreeableness, consciousness and extraversion as well as higher neuroticism. The other model linked higher urbanicity and better socioeconomic status to stronger functional connectivity and activity in the sensorimotor network, smaller volume and surface area and weaker functional connectivity and activity in the medial prefrontal cortex, lower white matter integrity, and higher openness to experience. We also conducted mediation analyses to explore the potential bidirectional mediation relationships between adult brain imaging phenotypes and personality traits with the influence of preadult environmental exposures and found both environment-brain-personality and environment-personality-brain pathways. We finally performed moderated mediation analyses to test the potential interactions between macro- and microenvironmental exposures and found that one category of exposure moderated the mediation pathways of another category of exposure. These results improve our understanding of the effects of preadult environmental exposures on the adult brain and personality traits and may facilitate the design of targeted interventions to improve mental health by reducing the impact of adverse environmental exposures.

Multimodal and multiscale evidence for network-based cortical thinning in major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is associated with widespread, irregular cortical thickness (CT) reductions across the brain. However, little is known regarding mechanisms that govern spatial distribution of the reductions. METHODS: We combined multimodal MRI and genetic, cytoarchitectonic and chemoarchitectonic data to examine structural covariance, functional synchronization, gene co-expression, cytoarchitectonic similarity and chemoarchitectonic covariance between regions atrophied in MDD. RESULTS: Regions atrophied in MDD were associated with significantly higher structural covariance, functional synchronization, gene co-expression and chemoarchitectonic covariance. These results were robust against methodological variations in brain parcellation and null model, reproducible in patients and controls, and independent of age at onset of MDD. Despite no significant differences in the cytoarchitectonic similarity, MDD-related CT reductions were susceptible to specific cytoarchitectonic class of association cortex. Further, we found that nodal shortest path lengths to disease epicenters derived from structural (right supramarginal gyrus) and chemoarchitectonic covariance (right sulcus intermedius primus) networks of healthy brains were correlated with the extent to which a region was atrophied in MDD, supporting the transneuronal spread hypothesis that regions closer to the epicenters are more susceptible to MDD. Finally, we showed that structural covariance and functional synchronization among regions atrophied in MDD were mainly related to genes enriched in metabolic and membrane-related processes, driven by genes in excitatory neurons, and associated with specific neurotransmitter transporters and receptors. CONCLUSIONS: Altogether, our findings provide empirical evidence for and genetic and molecular insights into connectivity-constrained CT thinning in MDD.

Mapping Neurophysiological Subtypes of Major Depressive Disorder Using Normative Models of the Functional Connectome.

BACKGROUND: Major depressive disorder (MDD) is a highly heterogeneous disorder that typically emerges in adolescence and can occur throughout adulthood. Studies aimed at quantitatively uncovering the heterogeneity of individual functional connectome abnormalities in MDD and identifying reproducibly distinct neurophysiological MDD subtypes across the lifespan, which could provide promising insights for precise diagnosis and treatment prediction, are still lacking. METHODS: Leveraging resting-state functional magnetic resonance imaging data from 1148 patients with MDD and 1079 healthy control participants (ages 11-93), we conducted the largest multisite analysis to date for neurophysiological MDD subtyping. First, we characterized typical lifespan trajectories of functional connectivity strength based on the normative model and quantitatively mapped the heterogeneous individual deviations among patients with MDD. Then, we identified neurobiological MDD subtypes using an unsupervised clustering algorithm and evaluated intersite reproducibility. Finally, we validated the subtype differences in baseline clinical variables and longitudinal treatment predictive capacity. RESULTS: Our findings indicated great intersubject heterogeneity in the spatial distribution and severity of functional connectome deviations among patients with MDD, which inspired the identification of 2 reproducible neurophysiological subtypes. Subtype 1 showed severe deviations, with positive deviations in the default mode, limbic, and subcortical areas and negative deviations in the sensorimotor and attention areas. Subtype 2 showed a moderate but converse deviation pattern. More importantly, subtype differences were observed in depressive item scores and the predictive ability of baseline deviations for antidepressant treatment outcomes. CONCLUSIONS: These findings shed light on our understanding of different neurobiological mechanisms underlying the clinical heterogeneity of MDD and are essential for developing personalized treatments for this disorder.

Cross-ancestry genome-wide association meta-analyses of hippocampal and subfield volumes.

The hippocampus is critical for memory and cognition and neuropsychiatric disorders, and its subfields differ in architecture and function. Genome-wide association studies on hippocampal and subfield volumes are mainly conducted in European populations; however, other ancestral populations are under-represented. Here we conduct cross-ancestry genome-wide association meta-analyses in 65,791 individuals for hippocampal volume and 38,977 for subfield volumes, including 7,009 individuals of East Asian ancestry. We identify 339 variant-trait associations at P < 1.13 × 10-9 for 44 hippocampal traits, including 23 new associations. Common genetic variants have similar effects on hippocampal traits across ancestries, although ancestry-specific associations exist. Cross-ancestry analysis improves the fine-mapping precision and the prediction performance of polygenic scores in under-represented populations. These genetic variants are enriched for Wnt signaling and neuron differentiation and affect cognition, emotion and neuropsychiatric disorders. These findings may provide insight into the genetic architectures of hippocampal and subfield volumes.

Abnormal cerebral blood flow and brain function in type 2 diabetes mellitus.

PURPOSE: Type 2 diabetes mellitus (T2DM) lead to impaired cerebral blood perfusion, which leads to changes in brain function and affects the cognitive function of patients. In this study, cerebral blood flow (CBF) was used to evaluate the effect of T2DM on cerebral perfusion, and functional connectivity (FC) analysis was further used to explore whether the FC between the abnormal CBF region and the whole brain was changed. In addition, amplitude of low-frequency fluctuation (ALFF) and degree centrality (DC) were used to investigate the changes in spontaneous activity and connectivity strength of the brain network. METHODS: We recruited 40 T2DM patients and 55 healthy controls (HCs). They underwent 3D-T1WI, rs-fMRI, arterial spin labeling (ASL) sequence scans and a series of cognitive tests. Cognitive test scores and brain imaging indicators were compared between the two groups, and the relationships among laboratory indicators, cognitive test scores, and brain imaging indicators were explored in the T2DM group. RESULTS: Compared to HCs, The CBF values of Calcarine_L and Precuneus_R in the T2DM group were lower. The DC value of Paracentral_Lobule_L and Precuneus_L, and the ALFF value of Hippocampus_L in the T2DM group were higher. In addition, the CBF values of Calcarine_L was negatively correlated with fasting insulin and HOMA_IR. CONCLUSION: This study found that there were regions of cerebral hypoperfusion in T2DM patients, which are associated with insulin resistance. In addition, we found abnormally elevated brain activity and enhanced functional connectivity in T2DM patients, which we speculated was the compensatory mechanism of brain neural activity.

Abnormal dynamic functional connectivity of thalamic subregions in patients with first-episode, drug-naïve major depressive disorder.

Background: Recent studies have shown that major depressive disorder (MDD) is associated with altered intrinsic functional connectivity (FC) of the thalamus; however, investigations of these alterations at a finer time scale and the level of thalamic subregions are still lacking. Methods: We collected resting-state functional MRI data from 100 treatment-naïve, first-episode MDD patients and 99 age-, gender- and education-matched healthy controls (HCs). Seed-based whole-brain sliding window-based dFC analyses were performed for 16 thalamic subregions. Between-group differences in the mean and variance of dFC were determined using threshold-free cluster enhancement algorithm. For significant alterations, there relationships with clinical and neuropsychological variables were further examined via bivariate and multivariate correlation analyses. Results: Of all thalamic subregions, only the left sensory thalamus (Stha) showed altered variance of dFC in the patients characterized by increases with the left inferior parietal lobule, left superior frontal gyrus, left inferior temporal gyrus, and left precuneus, and decreases with multiple frontal, temporal, parietal, and subcortical regions. These alterations accounted for, to a great extent, clinical, and neuropsychological characteristics of the patients as revealed by the multivariate correlation analysis. In addition, the bivariate correlation analysis revealed a positive correlation between the variance of dFC between the left Stha and right inferior temporal gurus/fusiform and childhood trauma questionnaires scores (r = 0.562, P < 0.001). Conclusion: These findings suggest that the left Stha is the most vulnerable thalamic subregion to MDD, whose dFC alterations may serve as potential biomarkers for the diagnosis of the disease.