Psychiatry Research: Neuroimaging最新文献_第3页

An effective alzheimer disease diagnosis using resting state fmri images and broad learning system 利用静息状态fmri图像和广泛学习系统有效诊断阿尔茨海默病

IF 2.1 4区医学

Psychiatry Research: Neuroimaging Pub Date : 2026-04-01 Epub Date: 2026-01-14 DOI: 10.1016/j.pscychresns.2025.112133

Sali Issa , Qi Wang , Ruinan Qi , Guangxi Peng , Shi Yin , Qinmu Peng

{"title":"An effective alzheimer disease diagnosis using resting state fmri images and broad learning system","authors":"Sali Issa , Qi Wang , Ruinan Qi , Guangxi Peng , Shi Yin , Qinmu Peng","doi":"10.1016/j.pscychresns.2025.112133","DOIUrl":"10.1016/j.pscychresns.2025.112133","url":null,"abstract":"<div><div>In this paper, a new multiclass Alzheimer diagnosis system is proposed using Broad Learning (BL) and the combination of Local Coherence (LCOR) and Intrinsic Connectivity Contrast (ICC) parameters. A public resting state fMRI database; including healthy elderly subjects (HC), Alzheimer Disease (AD) and Mild Cognitive Impairment (MCI) patients; was chosen in this study. All rs-fMRI pre-processing and analysis were performed by CONN toolbox. Three contrast cases of AD, MCI and HC were implemented within the group-level analysis, then both LCOR and ICC parameters of the effected brain clusters were combined and collected. For diagnosis system, Broad Learning (BL) classifier is trained to classify three stages of AD, MCI and HC, respectively. Referring to the experimental results and compared with other current studies, the proposed system achieved high average accuracy of 99.6% with low training time of 2 s. Furthermore, a mapping between effected brain regions and their functions is given to interprets the common symptoms for AD and MCI patients.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112133"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Impact of genetic variants on hippocampal volume among individuals with schizophrenia and bipolar disorders 基因变异对精神分裂症和双相情感障碍患者海马体积的影响

IF 2.1 4区医学

Psychiatry Research: Neuroimaging Pub Date : 2026-04-01 Epub Date: 2026-01-17 DOI: 10.1016/j.pscychresns.2026.112147

Tommaso Toffanin , Giulia Ida Perini , Halima Follador , Filippo Zonta , Giovanni Ferri , Giorgio Pigato , Mario Angelo Pagano , Nadia Scupola , Claudia Pinato , Davide Calosci , Maria Ferrara , Angela Muscettola , Giovanni Antonio De Bellis , Chiara Montemitro , Luigi Zerbinati , Maria Giulia Nanni , Rosangela Caruso , Andrea Escelsior , Alessandra Baratto , Nicola Martino , Martino Belvederi Murri

{"title":"Impact of genetic variants on hippocampal volume among individuals with schizophrenia and bipolar disorders","authors":"Tommaso Toffanin , Giulia Ida Perini , Halima Follador , Filippo Zonta , Giovanni Ferri , Giorgio Pigato , Mario Angelo Pagano , Nadia Scupola , Claudia Pinato , Davide Calosci , Maria Ferrara , Angela Muscettola , Giovanni Antonio De Bellis , Chiara Montemitro , Luigi Zerbinati , Maria Giulia Nanni , Rosangela Caruso , Andrea Escelsior , Alessandra Baratto , Nicola Martino , Martino Belvederi Murri","doi":"10.1016/j.pscychresns.2026.112147","DOIUrl":"10.1016/j.pscychresns.2026.112147","url":null,"abstract":"<div><h3>Background and Hypothesis</h3><div>Hippocampal volume reduction is a consistent finding in schizophrenia (SCZ) and bipolar disorder type I (BP-I), yet the role of genetic factors remains unclear. We investigated the influence of DISC1 (rs821616), AKT1 (rs1130233), COMT (rs4680), and GSK-3ꞵ(rs334558) polymorphisms on hippocampal morphology.</div></div><div><h3>Study Design</h3><div>Seventy-one participants (25 SCZ, 22 BP-I, 24 healthy controls, HC) underwent 1.5T MRI and genotyping. Bayesian multilevel models estimated associations between corrected hippocampal volume, diagnosis, hemisphere, and genetic variants.</div></div><div><h3>Study Results</h3><div>Both SCZ and BP-I showed significantly smaller hippocampal volumes compared with HC (Average Marginal Effects: SCZ vs HC = −1.38; BP-I vs HC = −1.46; probability of direction [PD] = 100%). Rightward asymmetry was preserved across groups. The COMT AA genotype was associated with lower hippocampal volume (AME = −0.67; PD = 99%), while DISC1 AT carriers showed moderate reductions (AME = −0.37; PD = 96%). GSK-3ꞵ contributed to variability but not mean volume, and AKT1 showed no clear effects.</div></div><div><h3>Conclusions</h3><div>Hippocampal atrophy is a shared marker of SCZ and BP-I, with preserved lateralization. COMT and DISC1 variations appear to modulate hippocampal volume, supporting their role in psychosis vulnerability.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112147"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep learning based treatment remission prediction to transcranial direct current stimulation in bipolar depression using EEG power spectral density 基于深度学习的双相抑郁症经颅直流电刺激治疗缓解预测脑电功率谱密度

IF 2.1 4区医学

Psychiatry Research: Neuroimaging Pub Date : 2026-04-01 Epub Date: 2025-12-22 DOI: 10.1016/j.pscychresns.2025.112115

Jijomon Chettuthara Moncy , Wenyi Xiao , Rachel D. Woodham , Ali-Reza Ghazi-Noori , Hakimeh Rezaei , Elvira Bramon , Philipp Ritter , Michael Bauer , Allan H. Young , Yong Fan , Cynthia H.Y. Fu

引用次数: 0

EEG-based schizophrenia classification using attention-integrated deep convolutional networks 基于脑电图的精神分裂症分类使用注意整合深度卷积网络。

IF 2.1 4区医学

Psychiatry Research: Neuroimaging Pub Date : 2026-04-01 Epub Date: 2026-01-08 DOI: 10.1016/j.pscychresns.2026.112138

Anjali Sagar Jangde, Gyanendra Kumar Verma

{"title":"EEG-based schizophrenia classification using attention-integrated deep convolutional networks","authors":"Anjali Sagar Jangde, Gyanendra Kumar Verma","doi":"10.1016/j.pscychresns.2026.112138","DOIUrl":"10.1016/j.pscychresns.2026.112138","url":null,"abstract":"<div><div>Schizophrenia is a complex psychiatric disorder marked by cognitive and perceptual disruptions, for which electroencephalography (EEG) provides a valuable non-invasive biomarker. In this study, we propose a convolutional attention-based deep learning framework for the automatic detection of schizophrenia from EEG signals. The model integrates spatial feature extraction via convolutional layers with an attention mechanism that adaptively focuses on discriminative temporal patterns within the EEG. We have conducted experiments on two publicly available datasets, the Moscow EEG dataset and the IBIB PAN dataset. Performance on the Moscow dataset was lower, with an accuracy of 73.98%, likely due to age-related neural variability and limited recording duration. The model achieved a classification accuracy of 98.45% on the IBIB PAN dataset, demonstrating strong generalization and discriminative capability. These results highlight the potential of attention-augmented convolutional networks for schizophrenia detection, while also underscoring the challenges of generalizing across datasets with differing demographic and acquisition characteristics.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112138"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145965986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessment of phase-locking factor with visual area-targeted transcranial magnetic stimulation-electroencephalography shows reduced connectivity in schizophrenia: A preliminary study 用目视区域靶向经颅磁刺激-脑电图评估锁相因子显示精神分裂症患者连通性降低：一项初步研究

IF 2.1 4区医学

Psychiatry Research: Neuroimaging Pub Date : 2026-04-01 Epub Date: 2026-01-21 DOI: 10.1016/j.pscychresns.2026.112153

Masayuki Ide , Akihiro Tadamura , Takehiro Miyazaki , Yoshiki Inoue , Aya Sekine , Takumi Takahashi , Masashi Tamura , Asaki Matsuzaki , Kiyotaka Nemoto , Hirokazu Tachikawa , Tetsuaki Arai , Masahiro Kawasaki

{"title":"Assessment of phase-locking factor with visual area-targeted transcranial magnetic stimulation-electroencephalography shows reduced connectivity in schizophrenia: A preliminary study","authors":"Masayuki Ide , Akihiro Tadamura , Takehiro Miyazaki , Yoshiki Inoue , Aya Sekine , Takumi Takahashi , Masashi Tamura , Asaki Matsuzaki , Kiyotaka Nemoto , Hirokazu Tachikawa , Tetsuaki Arai , Masahiro Kawasaki","doi":"10.1016/j.pscychresns.2026.112153","DOIUrl":"10.1016/j.pscychresns.2026.112153","url":null,"abstract":"<div><div>As pathophysiological mechanisms of schizophrenia remain unclear, the development of reliable biomarkers for the disease is highly anticipated. Electroencephalogram with transcranial magnetic stimulation (TMS-EEG) is a developing technique for assessing mental condition. Phase-locking factors (PLFs) are a parameter of phase synchronization, which can assess the brain connectivity of specific areas. Both visual processing impairments and aberrant brain connectivity are implicated in the pathophysiology of schizophrenia. Here, we compared motor area PLFs using visual area-targeted TMS-EEG between three groups: 15 patients with schizophrenia (SZ), 15 patients with major depressive disorder (MD), and 15 healthy controls (HC). The PLF of the SZ group showed a significant decrease in the theta band compared to the HC group without confounding effects from TMS click noises or antipsychotic medication. The reduction of PLF in the theta band between the visual and motor area could reflect visual processing impairments in schizophrenia. Further experiments with larger sample size and appropriate cognitive tasks are required to confirm our conclusion.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112153"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146078747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cerebral hemodynamics and functional connectivity in the stroop test in Parkinson’s disease patients: A machine learning approach to fNIRS features 帕金森病患者stroop试验中的脑血流动力学和功能连通性：fNIRS特征的机器学习方法

IF 2.1 4区医学

Psychiatry Research: Neuroimaging Pub Date : 2026-04-01 Epub Date: 2025-12-31 DOI: 10.1016/j.pscychresns.2025.112119

Liping Qi , Zi-Qian Shi , Yan-Zhi Liu , Jing-Wen Ni , Yong-Zhong Lin

{"title":"Cerebral hemodynamics and functional connectivity in the stroop test in Parkinson’s disease patients: A machine learning approach to fNIRS features","authors":"Liping Qi , Zi-Qian Shi , Yan-Zhi Liu , Jing-Wen Ni , Yong-Zhong Lin","doi":"10.1016/j.pscychresns.2025.112119","DOIUrl":"10.1016/j.pscychresns.2025.112119","url":null,"abstract":"<div><h3>Background</h3><div>Cognitive impairment is a core non-motor feature of Parkinson’s disease (PD). This study aimed to: (1) assess PD patients’ performance on the color-word Stroop task and characterize task-related neural activity; (2) develop PD diagnostic models using task-based functional near-infrared spectroscopy (fNIRS) features to link neuroimaging mechanisms with clinical translation.</div></div><div><h3>Methods</h3><div>Sixty-one participants (29 PD patients, 32 healthy controls [HC]) completed the Stroop task during fNIRS recording. Cerebral hemodynamic and brain network analyses were performed, and a two-way ANCOVA examined group (PD vs. HC) and task (congruent vs. incongruent stimuli) effects, adjusted for Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Machine learning frameworks were applied to construct diagnostic models using task-based fNIRS features.</div></div><div><h3>Results</h3><div>PD patients showed significantly higher omission rates than HC across both Stroop conditions, alongside enhanced dorsolateral prefrontal cortex and frontal eye field activation, and increased prefrontal interhemispheric functional connectivity. Logistic regression outperformed other models, achieving comparable accuracy with fewer features.</div></div><div><h3>Conclusion</h3><div>These findings advance our understanding of PD-related cognitive impairment and provide a framework for developing non-invasive, objective diagnostic tools.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112119"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145912802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Neural evidence for the influence of cognitive control by facial emotion under varying task difficulty in individuals with borderline personality disorder traits 不同任务难度下面部情绪对边缘型人格障碍个体认知控制影响的神经证据

IF 2.1 4区医学

Psychiatry Research: Neuroimaging Pub Date : 2026-04-01 Epub Date: 2026-01-21 DOI: 10.1016/j.pscychresns.2026.112150

Si Yang , Lijun Wang , Man Zheng , Suhao Peng

{"title":"Neural evidence for the influence of cognitive control by facial emotion under varying task difficulty in individuals with borderline personality disorder traits","authors":"Si Yang , Lijun Wang , Man Zheng , Suhao Peng","doi":"10.1016/j.pscychresns.2026.112150","DOIUrl":"10.1016/j.pscychresns.2026.112150","url":null,"abstract":"<div><div>Borderline personality disorder traits (BPD traits) represent subclinical characteristics associated with borderline personality disorder (BPD), which are marked by impaired cognitive control of emotion processing. Although the cognitive control deficit of negative emotions is a core feature of BPD, the characteristics and neural basis of this deficit in non-clinical BPD traits individuals remain unclear. The present study employed a novel facial majority function task (fMFT) combined with event-related potential (ERP) recording to explore the cognitive control of negative facial emotion under varying task difficulty in individuals with high BPD traits. We recruited 50 high BPD traits participants and 50 low BPD traits participants for the fMFT. The behavioral results showed that under low and medium task difficulty conditions, there were no significant differences in reaction time and accuracy between the two groups. However, under negative emotion-high task difficulty conditions, the reaction time of the high BPD traits group was significantly longer than that of the low BPD traits group, and the accuracy was significantly lower than that of the low BPD traits group. The ERP results showed that high BPD traits group exhibited reduced frontal N200 amplitudes and increased parietal P300 amplitudes compared to the low BPD traits group. Furthermore, both groups exhibited decreased LPP amplitudes with increasing task difficulty in positive emotion conditions, but this task difficulty effect was not significant in negative emotion conditions in the high BPD traits group. These findings demonstrate that BPD traits leads to selective deficits in cognitive control of emotion processing, and negative emotion leads to their impairment in the processing of conflict monitoring and inhibition with task difficulty increasing.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112150"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Structural connectivity correlates of response to electroconvulsive therapy in treatment-resistant depression 难治性抑郁症患者对电休克治疗反应的结构连通性相关。

IF 2.1 4区医学

Psychiatry Research: Neuroimaging Pub Date : 2026-04-01 Epub Date: 2026-01-09 DOI: 10.1016/j.pscychresns.2026.112141

María Eugenia Samman , Leticia Fiorentini , Delfina Lahitou Herlyn , Aki Tsuchiyagaito , Mariana N. Castro , Elsa Costanzo , Luis Ignacio Brusco , Joan A. Camprodon , Cecilia Forcato , Salvador M. Guinjoan , Mirta F. Villarreal

{"title":"Structural connectivity correlates of response to electroconvulsive therapy in treatment-resistant depression","authors":"María Eugenia Samman , Leticia Fiorentini , Delfina Lahitou Herlyn , Aki Tsuchiyagaito , Mariana N. Castro , Elsa Costanzo , Luis Ignacio Brusco , Joan A. Camprodon , Cecilia Forcato , Salvador M. Guinjoan , Mirta F. Villarreal","doi":"10.1016/j.pscychresns.2026.112141","DOIUrl":"10.1016/j.pscychresns.2026.112141","url":null,"abstract":"<div><div>Electroconvulsive therapy (ECT) remains the most effective intervention for treatment-resistant depression (TRD). We investigated whether cortico-limbic structural connectivity is associated with ECT response. Twenty-nine TRD patients underwent bifrontal ECT and baseline probabilistic tractography assessing connectivity between amygdala, anterior insula (aINS), orbitofrontal cortex (OFC), posterior cingulate cortex (PCC), posterior ventrolateral (VLPFC) and dorsolateral prefrontal cortex (DLPFC), subgenual cingulate cortex (SGCC) and thalamus. Stronger connectivity within a subnetwork comprising bilateral OFC, bilateral aINS, left SGCC and right DLPFC was associated with poorer ECT response showing predictive value for treatment outcome. Conversely, thalamus–PCC connectivity is related to greater baseline severity and better ECT response. In TRD, depressive symptom scores negatively correlated with fronto-limbic-thalamic connectivity. Our findings highlight a fronto-limbic subnetwork whose hyperconnectivity may reflect maladaptive regulation limiting neuromodulation efficacy. In contrast, thalamic connectivity may act as a hub linking fronto-limbic and default mode network circuits, potentially facilitating receptive pathways supporting therapeutic response and guiding anatomically precise neuromodulation strategies.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112141"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145998783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Distinct neural correlates between suicide attempters with major depressive disorder and other psychiatric disorders: a multimodal imaging study 自杀未遂者与重度抑郁症和其他精神疾病之间明显的神经关联：一项多模态成像研究

IF 2.1 4区医学

Psychiatry Research: Neuroimaging Pub Date : 2026-04-01 Epub Date: 2025-12-29 DOI: 10.1016/j.pscychresns.2025.112117

Woo-Sung Kim , Soyolsaikhan Odkhuu , Ariana Setiani , Ling Li , Ji-Young So , Shahida Nazir , Young-Chul Chung

{"title":"Distinct neural correlates between suicide attempters with major depressive disorder and other psychiatric disorders: a multimodal imaging study","authors":"Woo-Sung Kim , Soyolsaikhan Odkhuu , Ariana Setiani , Ling Li , Ji-Young So , Shahida Nazir , Young-Chul Chung","doi":"10.1016/j.pscychresns.2025.112117","DOIUrl":"10.1016/j.pscychresns.2025.112117","url":null,"abstract":"<div><h3>Background</h3><div>Suicide attempters (SA) with mild diagnoses other than major depressive disorder (MDD) are underexplored. This study aimed to investigate neuroimaging abnormalities in SA with MDD (SA-MDD), SA with other psychiatric disorders (OPD) (SA-OPD), and healthy controls (HC) using MRI data. Associations between altered findings in the patient groups and anger, negative schema, or rumination were further examined.</div></div><div><h3>Methods</h3><div>We recruited SA who visited the emergency department and divided them into two groups: SA-MDD (<em>n</em> = 52) and SA-OPD (<em>n</em> = 24). Age-, sex-, and education-matched HC) (<em>n</em> = 100) participated in the study. Cortical thickness, surface area, and subcortical volume were measured using structural magnetic resonance imaging (MRI). Regional analysis and seed-based functional connectivity (FC) analyses were performed using resting-state functional MRI. Partial Pearson or Spearman correlation with psychological variables was conducted.</div></div><div><h3>Results</h3><div>Widespread decreases in cortical thickness and larger cortical surface areas in some regions were observed in both SA-MDD and SA-OPD. However, decreased hippocampal volume was observed only in SA-MDD. Altered FC was more prominent in SA-MDD than in SA-OPD. In addition, significant associations between altered seed-based FC and negative schema were observed in both groups. Importantly, the associations with anger and rumination were evident only in SA-OPD.</div></div><div><h3>Conclusions</h3><div>These findings suggest that SA-OPD have similar alterations in brain morphometry to SA-MDD but show less prominent FC alterations. The clinical implications of anger and rumination in SA-OPD warrant further investigation.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112117"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145869102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Causal relationship between tractography-based brain white matter structural connectome and risk of psychiatric disorders: A bidirectional Mendelian randomization study 基于神经束图的脑白质结构连接体与精神疾病风险的因果关系：一项双向孟德尔随机研究

IF 2.1 4区医学

Psychiatry Research: Neuroimaging Pub Date : 2026-04-01 Epub Date: 2025-12-31 DOI: 10.1016/j.pscychresns.2025.112131

Xuhui Lin , Lu Tang , Zhao Hu

{"title":"Causal relationship between tractography-based brain white matter structural connectome and risk of psychiatric disorders: A bidirectional Mendelian randomization study","authors":"Xuhui Lin , Lu Tang , Zhao Hu","doi":"10.1016/j.pscychresns.2025.112131","DOIUrl":"10.1016/j.pscychresns.2025.112131","url":null,"abstract":"<div><h3>Aim</h3><div>This study sought to explore the causal link between 206 tractography-derived white matter connectivity metrics in the brain and the risk of nine psychiatric disorders, employing a bidirectional two-sample Mendelian randomization (MR) approach.</div></div><div><h3>Method</h3><div>Summary datasets of 9 psychiatric disorders including anxiety disorder, Alzheimer’s disease (AD), major depressive disorder (MDD), autism spectrum disorder (ASD), bipolar disorder (BD), schizophrenia, Tourette syndrome(TS), attention-deficit hyperactivity disorder (ADHD), and cannabis use disorder (CUD) were used. MR analyses were performed using the inverse variance weighted (IVW), weighted median, MR-Egger, MR-PRESSO, and MR-robust adjusted profile score (MR-RAPS) method.</div></div><div><h3>Results</h3><div>Forward MR analysis showed that the left-hemisphere dorsal attention network to the right-hemisphere limbic network connectome was causally associated with a 32 % higher risk of anxiety disorder [odds ratio(OR) = 1.32; 95 % confidence interval (CI): 1.16, 1.51). Reverse MR analysis indicated that AD was associated with a 7 % higher risk for the left-hemisphere limbic network to the right-hemisphere control network connectome(OR = 1.07; 95 % CI: 1.03, 1.10).</div></div><div><h3>Conclusions</h3><div>Our MR analysis reveals causal relationships between brain white matter structural connectivity and psychiatric disorders, advancing our knowledge of the neural mechanisms that contribute to psychiatric disorders and providing evidence for targeted interventions in psychiatric treatment.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112131"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0