Decreased gray matter volume and dynamic functional alterations in medicine-free obsessive-compulsive disorder.

BACKGROUND: Previous studies discovered the presence of abnormal structures and functions in the brain regions of patients with obsessive-compulsive disorder (OCD). Nevertheless, whether structural changes in brain regions are coupled with alterations in dynamic functional connectivity (dFC) at rest in medicine-free patients with OCD remains vague. METHODS: Three-dimensional T1-weighed magnetic resonance imaging (MRI) and resting-state functional MRI were performed on 50 medicine-free OCD and 50 healthy controls (HCs). Firstly, the differences in gray matter volume (GMV) between OCD and HCs were compared. Then, brain regions with aberrant GMV were used as seeds for dFC analysis. The relationship of altered GMV and dFC with clinical parameters in OCD was explored using partial correlation analysis. Finally, support vector machine was applied to examine whether altered multimodal imaging data might be adopted to distinguish OCD from HCs. RESULTS: Our findings indicated that GMV in the left superior temporal gyrus (STG) and right supplementary motor area (SMA) was reduced in OCD, and the dFC between the left STG and the left cerebellum Crus I and left thalamus, and between the right SMA and right dorsolateral prefrontal cortex (DLPFC) and left precuneus was decreased at rest in OCD. The brain regions both with altered GMV and dFC values could discriminate OCD from HCs with the accuracy of 0.85, sensitivity of 0.90 and specificity of 0.80. CONCLUSION: The decreased gray matter structure coupling with dynamic function in the left STG and right SMA at rest may be crucial in the pathophysiology of OCD. TRIAL REGISTRATION: Study on the mechanism of brain network in obsessive-compulsive disorder with multi-model magnetic resonance imaging (registration date: 08/11/2017; registration number: ChiCTR-COC-17,013,301).

Anatomical distance affects functional connectivity at rest in medicine-free obsessive-compulsive disorder.

BACKGROUND: Brain functional abnormalities at rest have been observed in obsessive-compulsive disorder (OCD). However, whether and how anatomical distance influences functional connectivity (FC) at rest is ambiguous in OCD. METHODS: Using resting-state functional magnetic resonance imaging data, we calculated the FC of each voxel in the whole-brain and divided FC into short- and long-range FCs in 40 medicine-free patients with OCD and 40 healthy controls (HCs). A support vector machine (SVM) was used to determine whether the altered short- and long-range FCs could be utilized to distinguish OCD from HCs. RESULTS: Patients had lower short-range positive FC (spFC) and long-range positive FC (lpFC) in the left precentral/postcentral gyrus (t = -5.57 and -5.43; P < 0.05, GRF corrected) and higher lpFC in the right thalamus/caudate, left thalamus, left inferior parietal lobule (IPL) and left cerebellum CrusI/VI (t = 4.59, 4.61, 4.41, and 5.93; P < 0.05, GRF corrected). Furthermore, lower spFC in the left precentral/postcentral gyrus might be used to distinguish OCD from HCs with an accuracy of 80.77%, a specificity of 81.58%, and a sensitivity of 80.00%. CONCLUSION: These findings highlight that anatomical distance has an effect on the whole-brain FC patterns at rest in OCD. Meanwhile, lower spFC in the left precentral/postcentral gyrus might be applied in distinguishing OCD from HCs.

Decreased Nucleus Accumbens Connectivity at Rest in Medication-Free Patients with Obsessive-Compulsive Disorder.

Background: Patients with obsessive-compulsive disorder (OCD) experience deficiencies in reward processing. The investigation of the reward circuit and its essential connectivity may further clarify the pathogenesis of OCD. Methods: The current research was designed to analyze the nucleus accumbens (NAc) functional connectivity at rest in medicine-free patients with OCD. Forty medication-free patients and 38 gender-, education-, and age-matched healthy controls (HCs) were recruited for resting-state functional magnetic resonance imaging. Seed-based functional connectivity (FC) was used to analyze the data. LIBSVM (library for support vector machines) was designed to identify whether altered FC could be applied to differentiate OCD. Results: Patients with OCD showed remarkably decreased FC values between the left NAc and the bilateral orbitofrontal cortex (OFC) and bilateral medial prefrontal cortex (MPFC) and between the right NAc and the left OFC at rest in the reward circuit. Moreover, decreased left NAc-bilateral MPFC connectivity can be deemed as a potential biomarker to differentiate OCD from HCs with a sensitivity of 80.00% and a specificity of 76.32%. Conclusion: The current results emphasize the importance of the reward circuit in the pathogenesis of OCD.

Altered Functional Connectivity Strength at Rest in Medication-Free Obsessive-Compulsive Disorder.

Background: Previous studies explored the whole-brain functional connectome using the degree approach in patients with obsessive-compulsive disorder (OCD). However, whether the altered degree values can be used to discriminate OCD from healthy controls (HCs) remains unclear. Methods: A total of 40 medication-free patients with OCD and 38 HCs underwent a resting-state functional magnetic resonance imaging (rs-fMRI) scan. Data were analyzed with the degree approach and a support vector machine (SVM) classifier. Results: Patients with OCD showed increased degree values in the left thalamus and left cerebellum Crus I and decreased degree values in the left dorsolateral prefrontal cortex, right precuneus, and left postcentral gyrus. SVM classification analysis indicated that the increased degree value in the left thalamus is a marker of OCD, with an acceptable accuracy of 88.46%, sensitivity of 87.50%, and specificity of 89.47%. Conclusion: Altered degree values within and outside the cortical-striatal-thalamic-cortical (CSTC) circuit may cocontribute to the pathophysiology of OCD. Increased degree values of the left thalamus can be used as a future marker for OCD understanding-classification.

Depression in youths with early life adversity: a systematic review and meta-analysis.

Background: Globally, early-life adversity (ELA) is linked to an increased risk of developing depression in adulthood; however, only a few studies have examined the specific effects of various types of ELA on depression in children and adolescents. This meta-analysis explores the association between the subtypes of ELA and the risk for youth-onset depression. Methods: We searched three electronic databases for reporting types of ELA, namely, emotional abuse, physical abuse, sexual abuse, emotional neglect, physical neglect, family conflict/violence, divorce, low socioeconomic status, and left-behind experience, associated with depression before the age of 18 years. Our meta-analysis utilized the odds ratio (OR) and relied on a random effects model. Large heterogeneous effects were detected. Some factors moderated the association between ELA and depression in youths. The homogeneity of variance test and meta-regression analysis were used to detect these relationships. Results: A total of 87 studies with 213,006 participants were ultimately identified via several strategies in this meta-analysis. Individuals who experienced ELA were more likely to develop depression before the age of 18 years old than those without a history of ELA (OR=2.14; 95% CI [1.93, 2.37]). The results of the subgroup analysis revealed a strong association between ELA and depression in youth, both in terms of specific types and dimensions. Specifically, emotional abuse (OR = 4.25, 95% CI [3.04, 5.94]) was more strongly related to depression in children and adolescents than other forms of ELA were. For both dimensions, threat (OR = 2.60, 95% CI [2.23, 3.02]) was more closely related to depression than deprivation was (OR = 1.76, 95% CI [1.55, 1.99]). Conclusion: This meta-analysis revealed that the adverse effects of a broader consideration of ELA on the risk of youth-onset depression vary according to the subtypes of ELA. Systematic review registation: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023405803, identifier 42023405803.

Reduced functional connectivity of the right dorsolateral prefrontal cortex at rest in obsessive-compulsive disorder.

BACKGROUND: Neuroimaging studies have revealed the role of the right dorsolateral prefrontal cortex (DLPFC) in the neurobiological mechanism of obsessive-compulsive disorder (OCD). However, only a few studies have examined the functional connectivity (FC) pattern of the right DLPFC at rest in OCD. OBJECTIVE: The aim of this research is to examine the FC patterns of the right DLPFC at rest in OCD. METHODS: Twenty-eight medication-free patients with OCD and 20 healthy controls underwent resting-state functional magnetic resonance imaging. Seed-based FC and support vector machine (SVM) were used to analyze the imaging data. RESULTS: The patients with OCD showed reduced FC values in the right middle temporal gyrus (MTG), right superior temporal gyrus, right ventral anterior cingulate cortex (vACC), and left Crus II. No brain regions showed a remarkable difference in FC values in patients with OCD after 8 weeks of medication treatment. The reduced right DLPFC-right MTG and right DLPFC-right vACC connectivities were correlated with the clinical symptoms of OCD. SVM results showed that reduced right DLPFC-right MTG connectivity at rest could predict the therapeutic response to OCD medication. CONCLUSIONS: The findings highlight the important role of the right DLPFC in the pathophysiological mechanism of OCD.

Abnormal structure and function of white matter in obsessive-compulsive disorder.

BACKGROUND: Abnormal structure and function of gray matter (GM) have been discovered in the cortico-striatal-thalamic-cortical (CSTC) circuit in obsessive-compulsive disorder (OCD). The GM structure and function may be influenced by the structure and function of the white matter (WM). Therefore, it is crucial to explore the characteristics of WM in OCD. METHODS: Diffusion tensor imaging and resting-state functional magnetic resonance imaging data of 52 patients with OCD and 39 healthy controls (HCs) were collected. The tract-based spatial statistics, amplitude of low-frequency fluctuations (ALFF), and structural-functional coupling approaches were utilized to explore the WM structure and function. Furthermore, the relationship between the abnormal WM structure and function and clinical symptoms of OCD was investigated using Pearson's correlation. Support vector machine was performed to evaluate whether patients with OCD could be identified with the changed WM structure and function. RESULTS: Compared to HCs, the lower fractional anisotropy (FA) values of four clusters including the superior corona radiata, anterior corona radiata, right superior longitudinal fasciculus, corpus callosum, left posterior corona radiata, fornix, and the right anterior limb of internal capsule, reduced ALFF/FA ratio in the left anterior thalamic radiation (ATR), and the decreased functional connectivity between the left ATR and the left dorsal lateral prefrontal cortex within CSTC circuit at rest were observed in OCD. The decreased ALFF/FA ratio in the left ATR negatively correlated with Yale-Brown Obsessive-Compulsive Scale obsessive thinking scores and Hamilton Anxiety Rating Scale scores in OCD. Furthermore, the features that combined the abnormal WM structure and function performed best in distinguishing OCD from HCs with the appropriate accuracy (0.80), sensitivity (0.82), as well as specificity (0.80). CONCLUSION: Current research discovered changed WM structure and function in OCD. Furthermore, abnormal WM structural-functional coupling may lead to aberrant GM connectivity within the CSTC circuit at rest in OCD. TRIAL REGISTRATION: Study on the mechanism of brain network in obsessive-compulsive disorder with multi-model magnetic resonance imaging (ChiCTR-COC-17013301).

Two multimodal neuroimaging subtypes of obsessive-compulsive disorder disclosed by semi-supervised machine learning.

BACKGROUND: Obsessive-compulsive disorder (OCD) is a highly heterogeneous mental condition with a diverse symptom. Existing studies classified OCD on the basis of conventional phenomenology-based taxonomy ignoring the fact that the same subtype identified in accordance with clinical symptom may have different mechanisms and treatment responses. METHODS: This research involved 50 medicine-free patients with OCD and 50 matched healthy controls (HCs). All the participants were subjected to structural and functional magnetic resonance imaging (MRI). Voxel-based morphometry (VBM) and amplitude of low frequency fluctuation (ALFF) were used to evaluate gray matter volume (GMV) and spontaneous neuronal activities at rest respectively. Similarity network fusion (SNF) was utilized to integrate GMVs and spontaneous neuronal activities, and heterogeneity by discriminant analysis was applied to characterise OCD subtypes. RESULTS: Two OCD subtypes were identified: Subtype 1 exhibited decreased GMVs (i.e., left inferior temporal gyrus, right supplementary motor area and right lingual gyrus) and increased ALFF value (i.e., right orbitofrontal cortex), whereas subtype 2 exhibited increased GMVs (i.e., left cuneus, right precentral gyrus, left postcentral gyrus and left hippocampus) and decreased ALFF value (i.e., right caudate nucleus). Furthermore, the altered GMVs was negatively correlated with abnormal ALFF values in both subtype 1 and 2. LIMITATIONS: This study requires further validation via a larger, independent dataset and should consider the potential influences of psychotropic medication on OCD patients' brain activities. CONCLUSIONS: Results revealed two reproducible subtypes of OCD based on underlying multimodal neuroimaging and provided new perspectives on the classification of OCD.

Altered dynamic neural activities in individuals with obsessive-compulsive disorder and comorbid depressive symptoms.

Objectives: Depressive symptoms are the most prevalent comorbidity in individuals with obsessive-compulsive disorder (OCD). The objective of this study was to investigate the dynamic characteristics of resting-state neural activities in OCD patients with depressive symptoms. Methods: We recruited 29 OCD patients with depressive symptoms, 21 OCD patients without depressive symptoms, and 27 healthy controls, and collected data via structural and functional magnetic resonance imaging (fMRI). We analyzed the fMRI results using the dynamic amplitude of low-frequency fluctuation (dALFF) and support vector machine (SVM) techniques. Results: Compared with OCD patients without depressive symptoms, OCD patients with depressive symptoms exhibited an increased dALFF in the left precuneus and decreased dALFF in the right medial frontal gyrus. The SVM indicated that the integration of aberrant dALFF values in the left precuneus and right medial frontal gyrus led to an overall accuracy of 80%, a sensitivity of 79%, and a specificity of 100% in detecting depressive symptoms among OCD patients. Conclusion: Therefore, our study reveals that OCD patients with depressive symptoms display neural activities with unique dynamic characteristics in the resting state. Accordingly, abnormal dALFF values in the left precuneus and right medial frontal gyrus could be used to identify depressive symptoms in OCD patients.

Exploring the key factors of schizophrenia relapse by integrating LC-MS/1H NMR metabolomics and weighted correlation network analysis.

BACKGROUND: Lack of comprehending key factors of schizophrenia relapse has impeded its effective treatment, indicating that the mechanism clarification and available intervention of schizophrenia relapse required further amelioration. METHOD: Based on the integration of LC-MS and 1H NMR metabolomics, a weighted correlation network was established to screen pivotal factors of accelerating schizophrenia relapse. Then, the cluster most correlated with schizophrenia relapse was explored, and the biological function of cluster was investigated. Next, the key biomarker related to schizophrenia relapse was obtained through multiple algorithms. Moreover, the Lilikoi algorithm and correlation analysis were implemented to reveal the association between key biomarker and schizophrenia relapse. RESULT: Results showed that 458 different forms of metabolites were identified for structuring the weighted correlation network. The module-trait correlation indicated that the turquoise module was the most highly correlated with schizophrenia relapse. Further, network analysis revealed that, in turquoise module, cluster 1 composed of 139 metabolites (involved in lipid metabolism and energy metabolism) was the most important subnetwork relevant to schizophrenia relapse. Finally, phenylalanylphenylalanine was recommended as the key biomarker related to schizophrenia relapse. Moreover, the correlation analysis indicated that phenylalanylphenylalanine might affect the progression of schizophrenia by intervening in energy metabolism. CONCLUSION: In summary, critical factors of schizophrenia relapse have been revealed in our research, expounding the schizophrenia progression more systemically, which could shed some light on improving the intervention of schizophrenia relapse.

An integrated pathological research for precise diagnosis of schizophrenia combining LC-MS/1H NMR metabolomics and transcriptomics.

BACKGROUND: Lack of clinically specific biomarkers has impeded the precise diagnosis of schizophrenia, meanwhile, limited comprehending of pathogenesis for schizophrenia has restricted the effective treatment. METHOD: An integrated multi-omic approach, combining metabolomic platform (LC-MS and 1H NMR) and transcriptomic platform, was established to differentiate healthy subjects from schizophrenia patients. Based on filtered metabolites and genes, characteristic spectrums were further built. Then, representative metabolites and genes were screened out through Boruta algorithm. Moreover, characteristic diagnostic formulas were established via LASSO regression analysis. RESULT: As a result, 86 differential metabolites (in line with amino acid metabolism, etc.) and 189 differential expression genes (involving in amino acid metabolic process, etc.) were obtained as potential biomarkers for schizophrenia. The latent interaction between metabolites with genes, such as HMGCLL1 with energy metabolism, etc., was further studied through the analysis of pathway-based integration. Moreover, fine predictive ability was attributed to characteristic metabolomic/transcriptomic diagnostic spectrums/formulas. CONCLUSION: The functional relationships of filtered metabolites and genes were studied, which could elaborate the pathological process of schizophrenia more systemically, supplying more precise information on mechanism description and diagnostic evidence of schizophrenia.

Altered Regional Activity and Network Homogeneity within the Fronto-Limbic Network at Rest in Medicine-Free Obsessive-Compulsive Disorder.

Functional abnormalities in brain areas within the fronto-limbic network have been widely reported in obsessive-compulsive disorder (OCD). However, region- and network-level brain activities of the fronto-limbic network at rest have not been simultaneously investigated in OCD. In this study, 40 medicine-free and non-comorbidity patients with OCD and 38 age-, education-, and gender-matched healthy controls (HCs) underwent a resting-state functional magnetic-resonance-imaging scan. Fractional amplitude of low-frequency fluctuations (fALFF), network homogeneity (NH), and support vector machine were used to analyze the data. Patients with OCD showed increased fALFF in the right orbital frontal cortex (OFC), increased NH in the left OFC, and decreased NH in the right putamen. Decreased NH of the right putamen was negatively correlated with the Y-BOCS total and compulsive behavior scores. Furthermore, a combination of NH in the left OFC and right putamen could be applied to differentiate OCD from HCs with optimum specificity and sensitivity. The current findings emphasize the crucial role of the fronto-limbic network in the etiology of OCD.

Disrupted Asymmetry of Inter- and Intra-Hemispheric Functional Connectivity at Rest in Medication-Free Obsessive-Compulsive Disorder.

Disrupted functional asymmetry of cerebral hemispheres may be altered in patients with obsessive-compulsive disorder (OCD). However, little is known about whether anomalous brain asymmetries originate from inter- and/or intra-hemispheric functional connectivity (FC) at rest in OCD. In this study, resting-state functional magnetic resonance imaging was applied to 40 medication-free patients with OCD and 38 gender-, age-, and education-matched healthy controls (HCs). Data were analyzed using the parameter of asymmetry (PAS) and support vector machine methods. Patients with OCD showed significantly increased PAS in the left posterior cingulate cortex, left precentral gyrus/postcentral gyrus, and right inferior occipital gyrus and decreased PAS in the left dorsolateral prefrontal cortex (DLPFC), bilateral middle cingulate cortex (MCC), left inferior parietal lobule, and left cerebellum Crus I. A negative correlation was found between decreased PAS in the left DLPFC and Yale-Brown Obsessive-compulsive Scale compulsive behavior scores in the patients. Furthermore, decreased PAS in the bilateral MCC could be used to distinguish OCD from HCs with a sensitivity of 87.50%, an accuracy of 88.46%, and a specificity of 89.47%. These results highlighted the contribution of disrupted asymmetry of intra-hemispheric FC within and outside the cortico-striato-thalamocortical circuits at rest in the pathophysiology of OCD, and reduced intra-hemispheric FC in the bilateral MCC may serve as a potential biomarker to classify individuals with OCD from HCs.