Psychiatry Research: Neuroimaging最新文献

{"title":"Advancing precision psychiatry: Machine learning integration with neuroimaging for early detection and diagnosis of Obsessive-Compulsive Disorder","authors":"Wijdan S. Aljebreen ,&nbsp;Norah A. Alturaiqi ,&nbsp;Muna I. Almushyti ,&nbsp;Haifa F. Alhasson ,&nbsp;Shuaa S. Alharbi","doi":"10.1016/j.pscychresns.2026.112137","DOIUrl":"10.1016/j.pscychresns.2026.112137","url":null,"abstract":"<div><div>Early detection of Obsessive-Compulsive Disorder (OCD), a chronic mental health condition characterized by intrusive thoughts and repetitive behaviors, is crucial for improving patient outcomes. Traditional diagnostic methods rely heavily on subjective assessments, which are often delayed or inaccurate. This review explores recent advancements in machine learning (ML) models – particularly hybrid and explainable AI (XAI) approaches – integrated with neuroimaging modalities such as structural (sMRI) and functional MRI (fMRI), as well as biochemical and clinical biomarkers. Studies demonstrate that ML techniques, including support vector machines (SVM), convolutional neural networks (CNN), and deep learning hybrids, can achieve diagnostic accuracies exceeding 90%. XAI methods like SHAP enhance interpretability and clinical trust. Despite promising results, challenges such as dataset variability, limited generalizability, and ethical concerns remain. The review highlights the need for multimodal data integration, scalable models, and privacy-preserving frameworks to support clinical adoption. By shifting from subjective assessments to ML-driven diagnostics, this paradigm promotes earlier detection, personalized treatment, and improved outcomes—advancing precision psychiatry in OCD care.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112137"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145979169","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}

{"title":"Dysfunction of the superior occipital gyrus in individuals with subclinical social anxiety and its mediating effect on gray matter structure","authors":"Fangfang Huang ,&nbsp;Shuai Ren ,&nbsp;Yuan Huang ,&nbsp;Yuqi Chen ,&nbsp;MingZhu Wang ,&nbsp;Xiaoyi Chang ,&nbsp;Kaile Liu ,&nbsp;Siying Guo ,&nbsp;Xingnuo Liu","doi":"10.1016/j.pscychresns.2026.112140","DOIUrl":"10.1016/j.pscychresns.2026.112140","url":null,"abstract":"<div><div>The investigation of neuroimaging abnormalities of young adults with subclinical social anxiety will contribute to understand the brain mechanism of social anxiety during developing on early stage. In this study, we recruited twenty-six young adults with subclinical social anxiety and matched healthy controls to examine their resting-state brain functional changes reflected by amplitude of low-frequency fluctuation (ALFF), functional connectivity (FC) and effective connectivity (EC). Mediating effect models were used to investigate the mediation of brain functional alterations between gray matter structure and social anxiety. Subjects with subclinical social anxiety exhibited increased ALFF in the left superior occipital gyrus (SOG), heightened FC between the left SOG and the right orbital part inferior frontal gyrus, decreased EC from the left SOG to bilateral postcentral gyrus (PCG), and increased EC from bilateral PCG and the right precuneus to the left SOG. A complete mediating effect of gray matter volume in the left SOG on subclinical social anxiety through ALFF in the left SOG was observed. In conclusion, dysfunction of the left SOG plays an important role in subclinical social anxiety. Additionally, the spontaneous neural hyperactivities in the left SOG function on social anxiety as a complete mediation of gray matter structure.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112140"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145979168","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}

{"title":"Altered hippocampal shape morphology in schizophrenia and at-risk mental state","authors":"Yoichiro Takayanagi ,&nbsp;Dominic Padova ,&nbsp;Can Ceritoglu ,&nbsp;Daiki Sasabayashi ,&nbsp;Shimako Nishiyama ,&nbsp;Haruko Kobayashi ,&nbsp;Kazumi Sakamoto ,&nbsp;Mizuho Takayanagi ,&nbsp;Kyo Noguchi ,&nbsp;Noa Tsujii ,&nbsp;Michio Suzuki ,&nbsp;J. Tilak Ratnanather ,&nbsp;Tsutomu Takahashi","doi":"10.1016/j.pscychresns.2025.112130","DOIUrl":"10.1016/j.pscychresns.2025.112130","url":null,"abstract":"<div><h3>Background</h3><div>Structural and functional alterations of the hippocampus have been reported to be associated with prodromal symptoms of psychotic disorders in individuals with an at-risk mental state (ARMS), as well as with the pathophysiology and symptomatology of psychotic conditions such as schizophrenia (SZ).</div></div><div><h3>Methods</h3><div>In this study, 3-tesla 3D MRI scans were obtained from 81 SZ patients, 56 individuals with ARMS, and 90 healthy controls. We evaluated hippocampal surface morphology using large deformation diffeomorphic metric mapping and conducted cluster-wise comparisons of the hippocampal surfaces across the groups.</div></div><div><h3>Results</h3><div>A common surface expansion in the right cornu ammonis (CA)3 was observed in SZ and ARMS groups compared to healthy subjects. In SZ patients, additional surface expansions were noted in the right CA1, hippocampal tail, and presubiculum. A higher dosage of antipsychotic medication was associated with surface compression in the bilateral hippocampal tail.</div></div><div><h3>Conclusion</h3><div>Common hippocampal surface alterations may underlie vulnerability to psychosis. Further surface expansions may be associated with the manifestation of overt psychotic symptoms. Such surface changes may be affected by antipsychotic medications.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112130"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886472","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}

{"title":"Disrupted brain connectivity in postpartum depression: Insights from resting-state fMRI and machine learning","authors":"Can Liu ,&nbsp;Tong Zhu ,&nbsp;Mingke Liu ,&nbsp;Mingmeng Huang ,&nbsp;Yuting Jiang ,&nbsp;Yijia Zou ,&nbsp;Zixuan Cheng ,&nbsp;Jingwen Liu ,&nbsp;Yu Zhang ,&nbsp;Yuhang Yang ,&nbsp;Jingbo Zhang ,&nbsp;Kewei He ,&nbsp;Du Lei ,&nbsp;Liangbo Hu","doi":"10.1016/j.pscychresns.2025.112118","DOIUrl":"10.1016/j.pscychresns.2025.112118","url":null,"abstract":"<div><h3>Background</h3><div>Postpartum depression (PPD) is a common women’s psychological health issue. While studies have identified regional functional abnormalities, the global functional topological alterations associated with PPD remain to be fully characterized. This study aims to investigate the alteration of functional topological properties in PPD patients.</div></div><div><h3>Methods</h3><div>Resting-state functional MRI (rs-fMRI) was acquired from 30 PPD patients, 23 healthy pregnant women (HPW), and 26 healthy non-pregnant women (HC). Functional brain networks were constructed using inter-regional Pearson’s correlation coefficient and analyzed via graph theory. Machine learning was applied to the functional connectome to distinguish PPD from HPW.</div></div><div><h3>Results</h3><div>Compared to HC and HPW, the PPD group showed a shift toward a more regularized network topology in functional brain network. In comparison with HC, PPD had altered topological properties mainly in the salience network (SN, e.g., left insula) and associated subcortical regions (e.g., amygdala), while HPW exhibited functional differences mainly within the default mode network (DMN). Abnormal regions (e.g., pallidum, precuneus) between PPD and HPW correlated with depression severity. Combining machine learning with functional connectivity metrics predicted PPD with 88 % accuracy.</div></div><div><h3>Conclusion</h3><div>Pregnancy may alter the functional connectome in DMN, and postpartum depression may disrupt the connectivity in SN. The insula and precuneus are critical for identifying PPD and HPW. These findings suggest that functional connectome alterations are clinical significant and may facilitate the timely clinical detection of PPD.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112118"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928088","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}

{"title":"Effects of swLORETA Z-score neurofeedback in Z-coherence of the fronto-limbic circuit in patients with major depressive disorder","authors":"Min-Han Huang ,&nbsp;Yi-Chun Yeh ,&nbsp;Cheng-Fang Yen ,&nbsp;Chiao-Li Khale Ke ,&nbsp;Cian-Ruei Jian ,&nbsp;Chien-Wen Lin ,&nbsp;I-Mei Lin","doi":"10.1016/j.pscychresns.2026.112157","DOIUrl":"10.1016/j.pscychresns.2026.112157","url":null,"abstract":"<div><div>Patients with major depressive disorder (MDD) exhibit abnormal hypercoherence within the fronto-limbic circuit (FLC), involving core brain regions such as the ventrolateral, ventromedial, dorsolateral, dorsomedial prefrontal cortex (vlPFC, vmPFC, dlPFC, dmPFC), and the amygdala (AMY). This study examined the effects of standardized weighted low-resolution electromagnetic tomography Z-score neurofeedback (swLZNFB) on LFC coherence and emotional symptoms. Sixty-one MDD patients were assigned to either the swLZNFB or control groups. All participants completed the Beck Depression Inventory II (BDI-II), the Beck Anxiety Inventory (BAI), and a five-minute eyes-closed resting-state electroencephalography (EEG) assessment both at pre-test and post-test. EEG coherence values were processed and converted into Z-scores across five frequency bands (delta to high beta), using the NeuroGuide normalization database. Compared to the control group, the swLZNFB group exhibited significantly reduced theta and beta Z-coherence values between vlPFC-AMY and dmPFC-AMY at post-test. Within-group comparisons revealed significantly decreased in beta Z-coherence between vlPFC-AMY from pre-test to post-test. Moreover, the swLZNFB group demonstrated significant decreases in depression and anxiety symptoms, whereas the control group showed improvement in depression only. These findings suggest that swLZNFB effectively modulates FCL hyperconnectivity and alleviates emotional symptoms in MDD, supporting its potential as a non-pharmaceutical intervention targeting dysfunction emotion regulation networks.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112157"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146078745","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}

{"title":"Early effects of oral naltrexone on craving, resting state and cue-induced brain activation in opioid use disorder: a prospective fMRI study","authors":"Malsawmkima Kullai ,&nbsp;Sourav Khanra ,&nbsp;Justin Raj ,&nbsp;Chandramouli Roy","doi":"10.1016/j.pscychresns.2026.112139","DOIUrl":"10.1016/j.pscychresns.2026.112139","url":null,"abstract":"<div><h3>Background</h3><div>Opioid use disorder (OUD) is characterized by intense cue-induced craving and high relapse risk. This longitudinal fMRI study investigated whether oral naltrexone (50mg/day) (oral-NTX) modulates neural and behavioral responses to opioid cues, as well as resting-state brain connectivity.</div></div><div><h3>Methods</h3><div>Thirty male patients with moderate–severe OUD underwent fMRI during an opioid-versus-neutral image task at baseline and after 2 weeks of oral-NTX treatment. The DDQ and OCDUS were administered for craving assessment. Task fMRI data was analyzed with linear mixed-effects models (3dLME). Resting-state fMRI was analyzed for ROI-to-ROI functional connectivity changes in key craving-related regions.</div></div><div><h3>Results</h3><div>Oral_NTX significantly reduced both DDQ and OCDUS scores (p&lt;0.01). Task-based fMRI revealed significant reductions in cue-induced activation in the anterior cingulate cortex (ACC) and cerebellum (whole-brain p&lt;0.05, cluster-corrected). ROI analyses confirmed pre-to-post decreases in ACC and cerebellar activation (t&gt;3.5, p&lt;0.05). Larger craving reductions correlated with greater left superior temporal deactivation (t≈1.97, p&lt;0.05). Resting-state connectivity analysis showed significant attenuation of intrinsic functional coupling between ACC–insula, nucleus accumbens (NAc)–amygdala, and cerebellum–hippocampus (p&lt;0.05). These decreases complement task findings, indicating widespread dampening of salience and reward network interactions following oral-NTX.</div></div><div><h3>Conclusion</h3><div>Oral-NTX reduces cue-driven activation in cortical and cerebellar regions while dampening resting-state connectivity within craving circuits.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112139"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145979171","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}

{"title":"Beyond behavior: neural and cognitive alterations in eating disorders–a systematic review","authors":"Ernesta Panarello ,&nbsp;Francesco Monaco ,&nbsp;Annarita Vignapiano ,&nbsp;Benedetta Di Gruttola ,&nbsp;Stefania Landi ,&nbsp;Emanuela Ferrara ,&nbsp;Raffaele Malvone ,&nbsp;Stefania Palermo ,&nbsp;Valeria Di Stefano ,&nbsp;Martina D’Angelo ,&nbsp;Giulio Corrivetti ,&nbsp;Luca Steardo Jr","doi":"10.1016/j.pscychresns.2025.112132","DOIUrl":"10.1016/j.pscychresns.2025.112132","url":null,"abstract":"<div><h3>Background</h3><div>Eating disorders (EDs), particularly Anorexia Nervosa (AN) and Bulimia Nervosa (BN), are complex psychiatric conditions marked by alterations in cognition, emotional regulation, and interoception. Accumulating evidence suggests that these behavioral features are underpinned by structural and functional brain abnormalities.</div></div><div><h3>Objective</h3><div>This systematic review aims to synthesize recent neuroimaging findings, particularly resting-state functional MRI and functional connectivity studies on cognitive and neural alterations in eating disorders (EDs).</div></div><div><h3>Methods</h3><div>Following PRISMA guidelines (PROSPERO: CRD42025648023), we systematically searched PubMed and APA PsycINFO for studies published between 2014 and 2024. Twelve studies met inclusion criteria and were assessed for quality and risk of bias using GRADE, RoB 2.0, and ROBINS-I tools. The included studies investigated both adolescent and adult populations, allowing consideration of developmental and illness stage–related aspects.</div></div><div><h3>Results</h3><div>Altered brain activity and connectivity patterns were consistently reported in individuals with AN and BN, particularly in the cortico-striatal-thalamic system (CSTS), default mode network (DMN), and interhemispheric circuits. Cognitive flexibility deficits were associated with abnormal neural activation despite preserved behavioral performance, suggesting compensatory mechanisms. Insular dysfunction persisted after weight restoration, and altered responses to reward and social cues were linked to symptom persistence.</div></div><div><h3>Conclusion</h3><div>EDs are underpinned by widespread neural dysregulation involving not only circuits traditionally associated with food intake and reward, but also higher-order large-scale networks supporting cognitive control, interoception, self-referential processing, and emotion regulation. Multimodal neuroimaging studies underscore the necessity for individualized, neurobiologically informed interventions targeting the cognitive control, affect regulation, and reward processing deficits characteristic of EDs. Findings across adolescent and adult samples highlight both state-dependent and potentially developmentally mediated neural alterations, underscoring the relevance of large-scale network connectivity across illness stages.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112132"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145918342","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}

{"title":"Dual-representation structural MRI classification of psychiatric disorders using deep learning and large language models","authors":"Hidir Selcuk Nogay ,&nbsp;Hojjat Adeli","doi":"10.1016/j.pscychresns.2026.112146","DOIUrl":"10.1016/j.pscychresns.2026.112146","url":null,"abstract":"<div><div>Accurate differentiation among psychiatric disorders such as schizophrenia and bipolar disorder remains a significant clinical challenge due to overlapping symptoms and subtle neuroanatomical variations. This study proposes a dual‐representation structural MRI framework in which raw T1-weighted MRI slices and their corresponding color-coded tissue segmentation maps—both derived from the same imaging modality—are analyzed using two independently trained ResNet-18 CNNs. The four diagnostic groups examined include Healthy Controls, Schizophrenia Spectrum, Bipolar Disorder with Psychosis, and Bipolar Disorder without Psychosis. TL and DA techniques were employed to address the limited dataset (<em>N</em>= 103).</div><div>Following model training, a Large Language Model (LLM) was used as a post-hoc analysis tool to contextualize the CNN outputs and provide interpretative insights into the relative contributions of the two MRI-derived representations. The results indicate that the dual-representation approach improves four-way classification performance and enables systematic comparison of structural information captured by raw versus segmentation-based inputs. These findings highlight the potential of combining deep learning models with LLM-assisted interpretability to support more transparent and informative diagnostic tools in psychiatric neuroimaging.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112146"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023396","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}

{"title":"EEG biomarkers for a precision-medicine approach to noninvasive brain stimulation for major depressive disorder","authors":"Rubén Romero-Marín ,&nbsp;Davide Cappon ,&nbsp;Javier Solana-Sánchez ,&nbsp;David Bartrés-Faz ,&nbsp;Álvaro Pascual-Leone ,&nbsp;Gabriele Cattaneo","doi":"10.1016/j.pscychresns.2025.112121","DOIUrl":"10.1016/j.pscychresns.2025.112121","url":null,"abstract":"<div><div>Major depressive disorder (MDD) is a prevalent and disabling condition with high rates of treatment resistance. Non-invasive brain stimulation (NIBS), including transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES), has emerged as a promising option for individuals unresponsive to pharmacotherapy. However, many patients still fail to achieve meaningful improvement, underscoring the need for reliable biomarkers of treatment response. Electroencephalography (EEG) and combined TMS-EEG are increasingly explored as predictive tools because they index cortical excitability, connectivity and neuroplasticity. In this systematic review, we synthesize evidence from 18 high-quality studies evaluating EEG and TMS-EEG biomarkers of NIBS outcomes in MDD. Resting-state EEG studies highlight the relevance of spectral power alterations, frontal alpha asymmetry and connectivity measures, whereas TMS-EEG work emphasizes TMS-evoked potentials, particularly N100 and N45 components, in forecasting clinical response. Although results are encouraging, methodological heterogeneity, modest sample sizes and divergent stimulation protocols limit immediate clinical implementation. Nonetheless, converging findings indicate that pre-treatment EEG and TMS-EEG assessments can support a precision-medicine approach by informing target selection and stimulation parameters. Systematic integration of these neurophysiological markers could enhance personalization of NIBS, increase response rates and advance the development of mechanism-based interventions for depression across diverse patient profiles and clinical settings worldwide.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112121"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886455","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}

{"title":"Unraveling the neural underpinnings of major depressive disorder and pain: A mendelian randomization study and mediation analysis","authors":"Jingqi Jiang ,&nbsp;Shu Cui ,&nbsp;Jun Wang ,&nbsp;Pengfei Zhang ,&nbsp;Yang Liu ,&nbsp;Liang Zhou ,&nbsp;Zhuo Wang ,&nbsp;Fei Jia ,&nbsp;Zheng Cheng ,&nbsp;Hao Li ,&nbsp;Laiyang Ma ,&nbsp;Jing Zhang","doi":"10.1016/j.pscychresns.2026.112136","DOIUrl":"10.1016/j.pscychresns.2026.112136","url":null,"abstract":"<div><div>Major depressive disorder (MDD) frequently co-occurs with chronic pain, yet the underlying biological mechanisms remain unclear. This study employed a two-sample bidirectional mendelian randomization (MR) design to investigate the causal relationship between MDD and nine prevalent pain phenotypes, focusing on the mediating role of macro- and micro-structural brain changes. We selected 57 brain regions as potential mediators based on prior literature and performed a two-step MR mediation analysis, using multiple methods (IVW, MR-Egger, weighted median, MR-RAPS) to ensure robustness. Results showed MDD had a causal effect on all pain phenotypes (all <em>p_FDR</em> &lt; 0.05) with no reverse causality. MDD specifically reduced gray matter volume (GMV) in the right insular cortex (<em>p_FDR</em> = 0.02), with no significant effects in other regions. This GMV in the right insular cortex reduction mediated approximately 13.89% of MDD’s total effect on temporomandibular disorder (TMD)-related pain, although the direct association between right insular GMV and TMD-related pain did not survive multiple-testing correction (<em>p_FDR</em> = 0.07). These findings provide evidence for a unidirectional causal link from MDD to pain and suggest right insular cortex GMV may be a partial mediator for TMD-related pain, highlighting a potential therapeutic target for MDD-related pain conditions.</div></div>","PeriodicalId":20776,"journal":{"name":"Psychiatry Research: Neuroimaging","volume":"357 ","pages":"Article 112136"},"PeriodicalIF":2.1,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145978691","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}