Two distinct subtypes of obsessive compulsive disorder revealed by heterogeneity through discriminative analysis

Decoding goal-habit brain networks of OCD from the structural and functional connectivity

Obsessive-Compulsive Disorder (OCD) may involve an imbalance between goal-directed and habitual learning systems, and this study investigates the structural and functional brain networks underpinning these systems in OCD. Using predefined brain regions, structural and functional connectivity networks were constructed, and methods such as network-based statistics, average connectivity strength, structural-functional coupling, and partial least squares path modeling were employed to compare OCD patients and healthy controls. The results revealed that OCD patients showed increased structural connectivity within both the goal-directed and habitual learning networks, particularly in the subnetwork that connects these systems. However, functional connectivity strength was reduced in both the habitual learning network and the subnetwork connecting goal-directed and habitual learning systems. The symptoms of ordering and hoarding are, to some extent, correlated with the structural-functional coupling network and network characteristics. These findings suggest that alterations in both structural and functional brain networks underpin goal-directed and habitual learning in OCD, with increased structural connectivity potentially reflecting compensatory mechanisms, while reduced functional connectivity may contribute to the symptoms of OCD. Further research is required to better understand the complex interplay between these learning systems in OCD, considering symptom heterogeneity and disease's progression.

Common neuroanatomical differential factors underlying heterogeneous gray matter volume variations in five common psychiatric disorders

Multifaceted evidence has shown that psychiatric disorders share common neurobiological mechanisms. However, the tremendous inter-individual heterogeneity among patients with psychiatric disorders limits trans-diagnostic studies with case-control designs, aimed at identifying clinically promising neuroimaging biomarkers. This study aims to identify neuroanatomical differential factors (ND factors) underlying gray matter volume variations in five psychiatric disorders. We leverage 4 independent datasets of 878 patients diagnosed with psychiatric disorders and 585 healthy controls (HCs) to identify shared ND factors underlying individualized gray matter volume variations. Individualized gray matter volume variations are represented with the linear weighted sum of ND factors, and each case is assigned a unique factor composition, thus preserving interindividual variation. We identify four robust ND factors that can be generalized to unseen disorders. ND factors show significant association with group-level morphological abnormalities, reconciling individual- and group-level morphological abnormalities, and are characterized by dissociable cognitive processes, molecular signatures, and connectome-informed epicenters. Moreover, using factor compositions as features, we discover two robust transdiagnostic subtypes with opposite gray matter volume variations relative to HCs. In conclusion, we identify four reproducible and shared neuroanatomical factors that underlie the highly heterogeneous morphological abnormalities in psychiatric disorders.

Individualized resting-state functional connectivity abnormalities unveil two major depressive disorder subtypes with contrasting abnormal patterns of abnormality

Modern neuroimaging research has recognized that major depressive disorder (MDD) is a connectome disorder, characterized by altered functional connectivity across large-scale brain networks. However, the clinical heterogeneity, likely stemming from diverse neurobiological disturbances, complicates findings from standard group comparison methods. This variability has driven the search for MDD subtypes using objective neuroimaging markers. In this study, we sought to identify potential MDD subtypes from subject-level abnormalities in functional connectivity, leveraging a large multi-site dataset of resting-state MRI from 1276 MDD patients and 1104 matched healthy controls. Subject-level extreme functional connections, determined by comparing against normative ranges derived from healthy controls using tolerance intervals, were used to identify biological subtypes of MDD. We identified a set of extreme functional connections that were predominantly between the visual network and the frontoparietal network, the default mode network and the ventral attention network, with the key regions in the anterior cingulate cortex, bilateral orbitofrontal cortex, and supramarginal gyrus. In MDD patients, these extreme functional connections were linked to age of onset and reward-related processes. Using these features, we identified two subtypes with distinct patterns of functional connectivity abnormalities compared to healthy controls (p < 0.05, Bonferroni correction). When considering all patients together, no significant differences were found. These subtypes significantly enhanced case-control discriminability and showed strong internal discriminability between subtypes. Furthermore, the subtypes were reproducible across varying parameters, study sites, and in untreated patients. Our findings provide new insights into the taxonomy and have potential implications for both diagnosis and treatment of MDD.

Analysis of Two Neuroanatomical Subtypes of Parkinson's Disease and Their Motor Progression Based on Semi-Supervised Machine Learning

BACKGROUND

The high heterogeneity of Parkinson's disease (PD) hinders personalized interventions. Brain structure reflects damage and neuroplasticity and is one of the biological bases of symptomatology. Subtyping PD in the framework of brain structure helps in the prediction of disease trajectories and optimizes treatment strategies.

METHODS

The study included a total of 283 de novo PD and 141 healthy controls (HC). Structural heterogeneity between PD and HC was compared, and patients were classified using Heterogeneity through Discriminative Analysis. Gray matter volume (GMV), clinical symptoms, and substantia nigra free water (SNFW) among all subtypes were compared. These subtypes were followed for an average of 2.5 years to monitor motor impairment.

RESULTS

Early PD patients possessed higher GMV heterogeneity than HC, and two subtypes based on GMV patterns were identified. Subtype 1 showed widespread GMV reductions, while subtype 2 had an increased volume in the basal ganglia and parts of the cortex. Subtype 1 had more severe motor and non-motor symptoms, as well as higher posterior SNFW. The whole-brain GMV in the PD group was negatively correlated with posterior SNFW; basal ganglia volume in subtype 1 was negatively correlated with Unified Parkinson's Disease Rating Scale (UPDRS)-III scores, whereas no linear correlation was found in subtype 2. The UPDRS-III progression rate was higher in subtype 1 than in subtype 2 (2.52 vs 0.92 points/year).

CONCLUSION

The heterogeneity of PD patients reflected the changes in their brain structure. The identification of these changes helps the classification of patients into different subtypes, additionally supported by clinical manifestations and SNFW, with consequent benefits for clinical consultancy and precision medicine.

Common and distinct neural patterns of gray matter alterations in adults with anorexia nervosa and obsessive-compulsive disorder

Anorexia nervosa (AN) and obsessive-compulsive disorder (OCD) often share multiple similar symptoms and are highly comorbid; however, the common and distinct brain neuroanatomy of these two diseases are unclear. The current study attempted to identify the overlapping and different gray matter volume (GMV) between AN and OCD. We conducted a voxel-wise meta-analysis of GMV using the latest Seed-based d Mapping with Permutation of Subject Images Toolbox (SDM-PSI) software. Compared to healthy controls, patients with AN showed reduced GMV in supplementary motor areas, median cingulate cortices, the left cerebellum, right Rolandic operculum (RO), right insula, right superior temporal gyrus (STG), and right precuneus, while OCD patients were characterized by low GMV in the right insula, STG, RO, and inferior frontal gyrus (IFG). The conjunctional analysis indicated that these two disorders have overlapping structural abnormalities in the right insula, STG, RO and IFG. No distinct GMV alteration was found. These common structural brain abnormalities may underlie the neuropathology of the similar neuropsychological features and highly comorbid manifestations of AN and OCD.

Individualized gray matter morphological abnormalities unveil two neuroanatomical obsessive-compulsive disorder subtypes

Obsessive-compulsive disorder (OCD) is a highly heterogeneous disorder, with notable variations among cases in structural brain abnormalities. To address this heterogeneity, our study aimed to delineate OCD subtypes based on individualized gray matter morphological differences. We recruited 100 untreated, first-episode OCD patients and 106 healthy controls for structural imaging scans. Utilizing normative models of gray matter volume, we identified subtypes based on individual morphological abnormalities. Sensitivity analyses were conducted to validate the reproducibility of clustering outcomes. To gain deeper insights into the connectomic and molecular underpinnings of structural brain abnormalities in the identified subtypes, we investigated their associations with normal brain network architecture and the distribution of neurotransmitter receptors/transporters. Our findings revealed two distinct OCD subtypes exhibiting divergent patterns of structural brain abnormalities. Sensitivity analysis results confirmed the robustness of the identified subtypes. Subtype 1 displayed significantly increased gray matter volume in regions including the frontal gyrus, precuneus, insula, hippocampus, parahippocampal gyrus, amygdala, and temporal gyrus, while subtype 2 exhibited decreased gray matter volume in the frontal gyrus, precuneus, insula, superior parietal gyrus, temporal gyrus, and fusiform gyrus. When considering all patients collectively, structural brain abnormalities nullified. The identified subtypes were characterized by divergent disease epicenters. Specifically, subtype 1 showed disease epicenters in the middle frontal gyrus, while subtype 2 displayed disease epicenters in the striatum, thalamus and hippocampus. Furthermore, structural brain abnormalities in these subtypes displayed distinct associations with neurotransmitter receptors/transporters. The identified subtypes offer novel insights into nosology and the heterogeneous nature of OCD.

Neuroanatomical subtypes of tobacco use disorder and relationship with clinical and molecular features

BACKGROUND

Individual neurobiological heterogeneity among patients with tobacco use disorder (TUD) hampers the identification of neuroimaging phenotypes.

METHODS

The current study recruited 122 TUD individuals and 57 healthy controls, and obtained their 3D-T1 images. Heterogeneity through discriminative analysis (HYDRA) was applied to uncover the potential subtype of TUD where regional gray matter volume (GMV) was treated as the feature. Then we examined the clinical, neuroimaging and molecular characteristics of subtypes.

RESULTS

Two distinct neuroanatomical subtypes were found. In subtype 1, TUD individuals showed decreased GMV in right orbitofrontal cortex (OFC), while subtype 2 exhibited distributed pattern of widely GMV increase. Moreover, subtype 1 showed older initial smoking age, longer duration of smoking than Subtype 2. Persistent smoking behavior in subtype 1 is more likely caused by substance dependence/addiction rather than psychosocial factors. GMV correlated negatively with cumulative tobacco exposure in Subtype 1 but not in Subtype 2. Besides, neuroanatomical aberrance in subtype 1 was mainly associated with dopamine system, while neuroanatomical abnormalities in subtype 2 were primarily associated with GABAa.

CONCLUSIONS

Overall, our results revealed two opposite neuroanatomical subtypes of TUD, which largely overlapped with their clinical and molecular features respectively. TUD subtypes taxonomy based on objective anatomy could help to facilitate the development of individualized treatment for TUD.

Individualized functional connectome abnormalities obtained using two normative model unveil neurophysiological subtypes of obsessive compulsive disorder

The high heterogeneity observed among patients with obsessive-compulsive disorder (OCD) underscores the need to identify neurophysiological OCD subtypes to facilitate personalized diagnosis and treatment. In this study, our aim was to identify potential OCD subtypes based on individualized functional connectome abnormalities. We recruited a total of 99 patients with OCD and 104 healthy controls (HCs) matched for demographic characteristics. Individualized functional connectome abnormalities were obtained using normative models of functional connectivity strength (FCS) and used as features to unveil OCD subtypes. Sensitivity analyses were conducted to assess the reproducibility and robustness of the clustering outcomes. Patients exhibited significant intersubject heterogeneity in individualized functional connectome abnormalities. Two subtypes with distinct patterns of FCS abnormalities relative to HCs were identified. Subtype 1 patients primarily exhibited significantly decreased FCS in regions including the frontal gyrus, insula, hippocampus, and precentral/postcentral gyrus, whereas subtype 2 patients demonstrated increased FCS in widespread brain regions. When all patients were combined, no significant differences were observed. Additionally, the identified subtypes showed significant differences in age of onset. Furthermore, sensitivity analyses confirmed the reproducibility of our subtyping results. In conclusion, the identified OCD subtypes shed new light on the taxonomy and neurophysiological heterogeneity of OCD.

Individualized gray matter morphological abnormalities uncover two robust transdiagnostic biotypes

Psychiatric disorders exhibit a shared neuropathology, yet the diverse presentations among patients necessitate the identification of transdiagnostic subtypes to enhance diagnostic and treatment strategies. This study aims to unveil potential transdiagnostic subtypes based on personalized gray matter morphological abnormalities. A total of 496 patients with psychiatric disorders and 255 healthy controls (HCs) from three distinct datasets (one for discovery and two for validation) were enrolled. Individualized gray matter morphological abnormalities were determined using normative modeling to identify transdiagnostic subtypes. In the discovery dataset, two transdiagnostic subtypes with contrasting patterns of structural abnormalities compared to HCs were identified. Reproducibility and generalizability analyses demonstrated that these subtypes could be generalized to new patients and even to new disorders in the validation datasets. These subtypes were characterized by distinct disease epicenters. The gray matter abnormal pattern in subtype 1 was mainly linked to excitatory receptors, whereas subtype 2 showed a predominant association with inhibitory receptors. Furthermore, we observed that the gray matter abnormal pattern in subtype 2 was correlated with transcriptional profiles of inflammation-related genes, while subtype 1 did not show this association. Our findings reveal two robust transdiagnostic biotypes, offering novel insights into psychiatric nosology.

Metaanalysis of Repetitive Transcranial Magnetic Stimulation (rTMS) Efficacy for OCD Treatment: The Impact of Stimulation Parameters, Symptom Subtype and rTMS-Induced Electrical Field

Background: Repetitive transcranial magnetic stimulation (rTMS) has recently demonstrated significant potential in treating obsessive-compulsive disorder (OCD). However, its effectiveness depends on various parameters, including stimulation parameters, OCD subtypes and electrical fields (EFs) induced by rTMS in targeted brain regions that are less studied. Methods: Using the PRISMA approach, we examined 27 randomized control trials (RCTs) conducted from 1985 to 2024 using rTMS for the treatment of OCD and conducted several meta-analyses to investigate the role of rTMS parameters, including the EFs induced by each rTMS protocol, and OCD subtypes on treatment efficacy. Results: A significant, medium effect size was found, favoring active rTMS (gPPC = 0.59, p < 0.0001), which was larger for the obsession subscale. Both supplementary motor area (SMA) rTMS (gPPC = 0.82, p = 0.048) and bilateral dorsolateral prefrontal cortex (DLPFC) rTMS (gPPC = 1.14, p = 0.04) demonstrated large effect sizes, while the right DLPFC showed a significant moderate effect size for reducing OCD severity (gPPC = 0.63, p = 0.012). These protocols induced the largest EFs in dorsal cognitive, ventral cognitive and sensorimotor circuits. rTMS protocols targeting DLPFC produced the strongest electrical fields in cognitive circuits, while pre-supplementary motor area (pre-SMA) and orbitofrontal cortex (OFC) rTMS protocols induced larger fields in regions linked to emotional and affective processing in addition to cognitive circuits. The pre-SMA rTMS modulated more circuits involved in OCD pathophysiology-sensorimotor, cognitive, affective, and frontolimbic-with larger electrical fields than the other protocols. Conclusions: While rTMS shows moderate overall clinical efficacy, protocols targeting ventral and dorsal cognitive and sensorimotor circuits demonstrate the highest potential. The pre-SMA rTMS appears to induce electrical fields in more circuits relevant to OCD pathophysiology.

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.

Gray matter atrophy is constrained by normal structural brain network architecture in depression

BACKGROUND

There is growing evidence that gray matter atrophy is constrained by normal brain network (or connectome) architecture in neuropsychiatric disorders. However, whether this finding holds true in individuals with depression remains unknown. In this study, we aimed to investigate the association between gray matter atrophy and normal connectome architecture at individual level in depression.

METHODS

In this study, 297 patients with depression and 256 healthy controls (HCs) from two independent Chinese dataset were included: a discovery dataset (105 never-treated first-episode patients and matched 130 HCs) and a replication dataset (106 patients and matched 126 HCs). For each patient, individualized regional atrophy was assessed using normative model and brain regions whose structural connectome profiles in HCs most resembled the atrophy patterns were identified as putative epicenters using a backfoward stepwise regression analysis.

RESULTS

In general, the structural connectome architecture of the identified disease epicenters significantly explained 44% (±16%) variance of gray matter atrophy. While patients with depression demonstrated tremendous interindividual variations in the number and distribution of disease epicenters, several disease epicenters with higher participation coefficient than randomly selected regions, including the hippocampus, thalamus, and medial frontal gyrus were significantly shared by depression. Other brain regions with strong structural connections to the disease epicenters exhibited greater vulnerability. In addition, the association between connectome and gray matter atrophy uncovered two distinct subgroups with different ages of onset.

CONCLUSIONS

These results suggest that gray matter atrophy is constrained by structural brain connectome and elucidate the possible pathological progression in depression.

Elucidating Multimodal Imaging Patterns in Accelerated Brain Aging: Heterogeneity through a Discriminant Analysis Approach Using the UK Biobank Dataset

Accelerated brain aging (ABA) intricately links with age-associated neurodegenerative and neuropsychiatric diseases, emphasizing the critical need for a nuanced exploration of heterogeneous ABA patterns. This investigation leveraged data from the UK Biobank (UKB) for a comprehensive analysis, utilizing structural magnetic resonance imaging (sMRI), diffusion magnetic resonance imaging (dMRI), and resting-state functional magnetic resonance imaging (rsfMRI) from 31,621 participants. Pre-processing employed tools from the FMRIB Software Library (FSL, version 5.0.10), FreeSurfer, DTIFIT, and MELODIC, seamlessly integrated into the UKB imaging processing pipeline. The Lasso algorithm was employed for brain-age prediction, utilizing derived phenotypes obtained from brain imaging data. Subpopulations of accelerated brain aging (ABA) and resilient brain aging (RBA) were delineated based on the error between actual age and predicted brain age. The ABA subgroup comprised 1949 subjects (experimental group), while the RBA subgroup comprised 3203 subjects (control group). Semi-supervised heterogeneity through discriminant analysis (HYDRA) refined and characterized the ABA subgroups based on distinctive neuroimaging features. HYDRA systematically stratified ABA subjects into three subtypes: SubGroup 2 exhibited extensive gray-matter atrophy, distinctive white-matter patterns, and unique connectivity features, displaying lower cognitive performance; SubGroup 3 demonstrated minimal atrophy, superior cognitive performance, and higher physical activity; and SubGroup 1 occupied an intermediate position. This investigation underscores pronounced structural and functional heterogeneity in ABA, revealing three subtypes and paving the way for personalized neuroprotective treatments for age-related neurological, neuropsychiatric, and neurodegenerative diseases.

Gray matter volume abnormalities in obsessive-compulsive disorder correlate with molecular and transcriptional profiles

Neuroimaging studies have consistently established altered brain structure in obsessive-compulsive disorder (OCD). However, the molecular and genetic mechanisms underlying structural brain abnormalities remain unclear. In this study, we aimed to investigate altered gray matter volume and its underlying molecular and genetic mechanisms in patients with OCD. Gray matter morphological abnormalities measured with voxel based morphometry analysis were identified in patients with OCD in comparison to sex- and age-matched healthy controls (HCs). Spatial correlations between gray matter morphological abnormalities and neurotransmitter maps were calculated to identify neurotransmitters relating to structural abnormalities. Structural abnormalities related genes were identified by conducting transcriptome-neuroimaging spatial correlations. Compared with HCs, patients with OCD demonstrated significant morphological abnormalities in distributed brain areas, including gray matter atrophy in the anterior cingulate and increased gray matter volume in the thalamus, caudate and precentral and postcentral gyrus. The morphological abnormalities were significantly associated with dopamine synthesis capacity and expression profiles of 1110 genes enriched for trans-synaptic signaling, regulation of membrane potential, modulation of chemical synaptic transmission, brain development, synapse organization and regulation of neurotransmitter levels. These results elucidate the molecular and transcriptional basis of altered gray matter morphology and build linking between molecular, transcriptional and neuroimaging information facilitating an integrative understanding of OCD.

Two distinct neuroanatomical subtypes of migraine without aura revealed by heterogeneity through discriminative analysis

The neurobiological heterogeneity in migraine is poorly studied, resulting in conflicting neuroimaging findings. This study used a newly proposed method based on gray matter volumes (GMVs) to investigate objective neuroanatomical subtypes of migraine. Structural MRI and clinical measures of 31 migraine patients without aura and 33 matched healthy controls (HCs) were explored. Firstly, we investigated whether migraine patients exhibited higher interindividual variability than HCs in terms of GMVs. Then, heterogeneity through discriminative analysis (HYDRA) was applied to categorize migraine patients into distinct subtypes by regional volumetric measures of GMVs. Voxel-wise volume and clinical characteristics among different subtypes were also explored. Migraine patients without aura exhibited higher interindividual GMVs variability. Two distinct and reproducible neuroanatomical subtypes of migraine were revealed. These two subtypes exhibited opposite neuroanatomical aberrances compared to HCs. Subtype 1 showed widespread decreased GMVs, while Subtype 2 showed increased GMVs in limited regions. The total intracranial volume was significantly positively correlated with cognitive function in Subtype 2. Subtype 1 showed significantly longer illness duration and less cognitive scores compared to Subtype 2. The present study shows that migraine patients without aura have high structural heterogeneity and uncovers two distinct and robust neuroanatomical subtypes, which provide a possible explanation for conflicting neuroimaging findings.

A comprehensive review for machine learning on neuroimaging in obsessive-compulsive disorder

Obsessive-compulsive disorder (OCD) is a common mental disease, which can exist as a separate disease or become one of the symptoms of other mental diseases. With the development of society, statistically, the incidence rate of obsessive-compulsive disorder has been increasing year by year. At present, in the diagnosis and treatment of OCD, The clinical performance of patients measured by scales is no longer the only quantitative indicator. Clinical workers and researchers are committed to using neuroimaging to explore the relationship between changes in patient neurological function and obsessive-compulsive disorder. Through machine learning and artificial learning, medical information in neuroimaging can be better displayed. In this article, we discuss recent advancements in artificial intelligence related to neuroimaging in the context of Obsessive-Compulsive Disorder.

Identification of shared and distinct patterns of brain network abnormality across mental disorders through individualized structural covariance network analysis

BACKGROUND

Mental disorders, including depression, obsessive compulsive disorder (OCD), and schizophrenia, share a common neuropathy of disturbed large-scale coordinated brain maturation. However, high-interindividual heterogeneity hinders the identification of shared and distinct patterns of brain network abnormalities across mental disorders. This study aimed to identify shared and distinct patterns of altered structural covariance across mental disorders.

METHODS

Subject-level structural covariance aberrance in patients with mental disorders was investigated using individualized differential structural covariance network. This method inferred structural covariance aberrance at the individual level by measuring the degree of structural covariance in patients deviating from matched healthy controls (HCs). T1-weighted anatomical images of 513 participants (105, 98, 190 participants with depression, OCD and schizophrenia, respectively, and 130 age- and sex-matched HCs) were acquired and analyzed.

RESULTS

Patients with mental disorders exhibited notable heterogeneity in terms of altered edges, which were otherwise obscured by group-level analysis. The three disorders shared high difference variability in edges attached to the frontal network and the subcortical-cerebellum network, and they also exhibited disease-specific variability distributions. Despite notable variability, patients with the same disorder shared disease-specific groups of altered edges. Specifically, depression was characterized by altered edges attached to the subcortical-cerebellum network; OCD, by altered edges linking the subcortical-cerebellum and motor networks; and schizophrenia, by altered edges related to the frontal network.

CONCLUSIONS

These results have potential implications for understanding heterogeneity and facilitating personalized diagnosis and interventions for mental disorders.

Abnormal voxel-mirrored homotopic connectivity in first-episode, drug-naïve patients with obsessive-compulsive disorder

Prior studies suggest that obsessive-compulsive disorder (OCD) can cause both anatomical and functional variations in the brain, but to date, altered functional synchronization between two functional hemispheres remains unclear in OCD patients. Voxel-mirrored homotopic connectivity (VMHC) is defined as the temporal correlation of spontaneous low-frequency blood oxygenation level-dependent signal fluctuations across mirror regions of hemisphere revealing the homotopic connectivity between each voxel in one hemisphere and its mirrored counterpart in the contralateral hemisphere. To investigate the alterations of brain regional function and VMHC in patients with OCD, the current study enrolled 103 OCD patients and 118 healthy controls, undergoing resting-state functional magnetic resonance imaging. Compared to healthy controls (HCs), patients had decreased VMHC in bilateral cerebellum, lingual and fusiform gyrus; bilateral paracentral lobule, pre and postcentral gyrus; and bilateral superior and middle temporal gyrus, putamen and bilateral precuneus without global signal regression. And we found mostly similar results after regressing global signals; apart from the regions mentioned above, decreased in bilateral cuneus and calcarine was also showed. Furthermore, the mean VMHC values of the left cerebellum were negatively correlated with the obsession scores (ρ = -.204, π = .039). The decreased values in right fusiform and putamen were negatively correlated with duration of disease (ρ = -.205, π = .038; ρ = -.196, π = .047). We confirmed a significant VMHC reduction in OCD patients in broad areas. Our findings suggest that the patients tend to disconnect information exchange across hemispheres.

Mapping the neuroanatomical heterogeneity of OCD using a framework integrating normative model and non-negative matrix factorization

Obsessive-compulsive disorder (OCD) is a spectrum disorder with high interindividual heterogeneity. We propose a comprehensible framework integrating normative model and non-negative matrix factorization (NMF) to quantitatively estimate the neuroanatomical heterogeneity of OCD from a dimensional perspective. T1-weighted magnetic resonance images of 98 first-episode untreated patients with OCD and matched healthy controls (HCs, n = 130) were acquired. We derived individualized differences in gray matter morphometry using normative model and parsed them into latent disease factors using NMF. Four robust disease factors were identified. Each patient expressed multiple factors and exhibited a unique factor composition. Factor compositions of patients were significantly correlated with severity of symptom, age of onset, illness duration, and exhibited sex differences, capturing sources of clinical heterogeneity. In addition, the group-level morphological differences obtained with two-sample t test could be quantitatively derived from the identified disease factors, reconciling the group-level and subject-level findings in neuroimaging studies. Finally, we uncovered two distinct subtypes with opposite morphological differences compared with HCs from factor compositions. Our findings suggest that morphological differences of individuals with OCD are the unique combination of distinct neuroanatomical patterns. The proposed framework quantitatively estimating neuroanatomical heterogeneity paves the way for precision medicine in OCD.

Structural and functional deficits and couplings in severe and moderate OCD

Changes in gray matter volume and functional connections have been frequently observed in patients with obsessive compulsive disorder. However, different grouping may cause diverse volume alterations and could draw more adverse conclusions about the pathophysiology of obsessive compulsive disorder(OCD). Most of them preferred to divide subjects into patients and healthy controls, rather than a detailed subgroup. Moreover, multimodal neuroimaging studies about structural-functional defects and couplings are rather rare. Our aim was to explore gray matter volume(GMV) and functional networks abnormalities induced by structural deficits based on severity of Yale-Brown Obsessive Compulsive Scale(Y-BOCS) symptom including OCD patients with severe(S-OCD, n = 31) and moderate symptoms(M-OCD, n = 42) and healthy controls (HCs, n = 54); Voxel-based morphometry(VBM) method was used to detect GMV differences among three groups, then used as masks according to one-way analysis of variance(ANOVA) results for the subsequent resting-state functional connectivity(rs-FC) analysis. Besides, correlation and subgroup analysis were performed to detect the potential roles of structural deficits between every two groups. ANOVA analysis showed that both S-OCD and M-OCD had increased volume in anterior cingulate cortex(ACC), left precuneus(L-Pre) and paracentral lobule(PCL), postcentral gyrus, left inferior occipital gyrus(L-IOG) and right superior occipital gyrus(R-SOG) and bilateral cuneus, middle occipital gyrus(MOG), and calcarine. Additionally, increased connections between Pre and angular gyrus(AG) and inferior parietal lobule(IPL) have been found. Moreover, connections between the left cuneus and lingual gyrus, between IOG and left lingual gyrus, fusiform and between L-MOG and cerebellum were also included. Subgroup analysis showed that decreased GMV in left caudate was negatively correlated with compulsion and total score in patients with moderate symptom compared to HCs. Our findings indicated that altered GMV in occipital-related regions, Pre, ACC and PCL and the disrupted FC networks including MOG-cerebellum and Pre-AG and IPL. Moreover, subgroup GMV analysis furtherly revealed negative associations between GMV changes and Y-BOCS symptom, offering preparatory proof for the involvement of structural and functional deficits in cortical-subcortical circuitry. Thus, they could provide insights into the neurobiological basis.

Suicidal Ideation and Obsessive-Compulsive Disorder: Links and Knowledge

Suicidal ideation (SI) is understudied in obsessive-compulsive disorder (OCD). Nonetheless, evidence suggests increased risk for SI in individuals with OCD compared to the general population. Understanding the relationship between SI and OCD involves investigating risk factors associated with SI. Furthering knowledge of links is essential for enhancing outcomes and decreasing experiences of SI through improving treatment interventions. Additionally, increasing awareness of factors that lead SI to suicide attempts (SA) is vital. To best illustrate the current state of knowledge, this scoping review examines risk factors for SI, including symptom profiles or phenotypes, comorbid diagnoses, sociodemographic and lifestyle factors, childhood trauma, and genetic and familial contributions. Important treatment considerations for targeting SI within the context of OCD are detailed with respect to the current evidence for psychotherapy, pharmacology, brain stimulation, and neurosurgery. Gaps in the literature and future directions are identified, broadly with respect to studies examining the treatment of SI within the context of OCD, particular OCD phenotypes, and factors influencing SI in pediatric OCD. Due to the relative novelty of this area of exploration, many unknowns persist regarding onset of SI in OCD, factors contributing to the maintenance of SI in OCD, and relevant treatment protocols. Findings suggest that individuals with previous SI or SA, history of childhood trauma, significant life stress, and psychiatric comorbidities, particularly depression, should be closely monitored and screened for SI.

The therapeutic alliance in cognitive-behavioral therapy for obsessive-compulsive disorder: A systematic review and meta-analysis

Background

The therapeutic alliance has been recognized as one of the most researched key elements of treatment across different therapeutic approaches and diagnostic domains. Despite its importance, our current understanding of its clinical relevance in patients with obsessive-compulsive disorder (OCD) is still debated. This study aimed to examine empirical evidence on the effect of alliance on treatment outcomes in Cognitive Behavioral Therapy (CBT) in patients with OCD in a systematic review and meta-analysis.

Methods

Original peer-reviewed articles until March 2022 were included if they were (1) written in English; (2) included a clinical group with a current primary OCD diagnosis; (3) involved individual CBT; (4) used a validated therapeutic alliance scale that was related to the outcome measurement; (5) reported an effect size.

Results

Thirteen studies were included, six of which contained sufficient statistical information to be included in the meta-analysis. A total of 897 patients took part in all reviewed studies. We found a modest effect of alliance on post-treatment outcome [Tau 2 = -0.1562 (C.I. 95%: -0.2542 to -0.0582)].

Discussion

The results show the existence of considerable variability and methodological inconsistencies across studies. We discuss the role of methodological factors that could account for this divergence, the research limitations, and the implications for current research.

Systematic review registration

[https://osf.io/dxez5/?view_only=bc2deaa7f0794c8dbef440255b2d4b3b].

Structural and Functional Brain Changes in Patients With Classic Trigeminal Neuralgia: A Combination of Voxel-Based Morphometry and Resting-State Functional MRI Study

Objectives

Brain structural and functional abnormalities have been separately reported in patients with classic trigeminal neuralgia (CTN). However, whether and how the functional deficits are related to the structural alterations remains unclear. This study aims to investigate the anatomical and functional deficits in patients with CTN and explore their association.

Methods

A total of 34 patients with CTN and 29 healthy controls (HCs) with age- and gender-matched were recruited. All subjects underwent structural and resting-state functional magnetic resonance imaging (fMRI) scanning and neuropsychological assessments. Voxel-based morphometry (VBM) was applied to characterize the alterations of gray matter volume (GMV). The amplitude of low-frequency fluctuation (ALFF) method was used to evaluate regional intrinsic spontaneous neural activity. Further correlation analyses were performed between the structural and functional changes and neuropsychological assessments.

Results

Compared to the HCs, significantly reduced GMV was revealed in the right hippocampus, right fusiform gyrus (FFG), and temporal-parietal regions (the left superior/middle temporal gyrus, left operculo-insular gyrus, left inferior parietal lobule, and right inferior temporal gyrus) in patients with CTN. Increased functional activity measured by zALFF was observed mainly in the limbic system (the bilateral hippocampus and bilateral parahippocampal gyrus), bilateral FFG, basal ganglia system (the bilateral putamen, bilateral caudate, and right pallidum), left thalamus, left cerebellum, midbrain, and pons. Moreover, the right hippocampus and FFG were the overlapped regions with both functional and anatomical deficits. Furthermore, GMV in the right hippocampus was negatively correlated with pain intensity, anxiety, and depression. GMV in the right FFG was negatively correlated with illness duration. The zALFF value in the right FFG was positively correlated with anxiety.

Conclusion

Our results revealed concurrent structural and functional changes in patients with CTN, indicating that the CTN is a brain disorder with structural and functional abnormalities. Moreover, the overlapping structural and functional changes in the right hippocampus and FFG suggested that anatomical and functional changes might alter dependently in patients with CTN. These findings highlight the vital role of hippocampus and FFG in the pathophysiology of CTN.

Higher brain structural heterogeneity in schizophrenia

As a highly heterogeneous disorder, schizophrenia shows notable interindividual variation in clinical manifestations. On that account, an increasing number of studies begin to examine the interindividual variability in neuroimaging characterization in schizophrenia. However, whether schizophrenia demonstrates higher interindividual morphological variability than health controls (HCs) remains unknown. T1-weighted anatomical images were obtained from patients with schizophrenia (n = 61) and matched HCs (n = 73). For each subject, voxel-wise gray matter volume was obtained using voxel-based morphometry analysis. We first inquired whether patients with schizophrenia showed higher interindividual structural variation than HCs using the person based similarity index (PBSI). Then, we examined differences of voxel-wise morphological coefficient of variation (CV) between schizophrenia and HCs. To further associate identified regions showing higher variability in schizophrenia with cognitive/functional processes, functional annotation was performed. Patients with schizophrenia exhibited lower PBSIs than matched HCs, suggesting higher interindividual morphological variability in schizophrenia. The following results showed that patients with schizophrenia exhibited higher CVs than HCs in distributed brain regions including the striatum, hippocampus, thalamus, parahippocampa gyrus, frontal gyrus, and amygdala. Brain regions showing higher CVs in schizophrenia were significantly implicated in affective, incentive and reward related terms. These results provide a new insight into the high clinical heterogeneity and facilitate personalized diagnose and treatment in schizophrenia.

Distinct profiles of functional connectivity density aberrance in Alzheimer's disease and mild cognitive impairment

INTRODUCTION

Investigating the neuroimaging changes from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is of great significance. However, the details about the distinct functional characteristics of AD and MCI remain unknown.

METHODS

In this study, we investigated distinct profiles of functional connectivity density (FCD) differences between AD and MCI compared with the normal population, aiming to depict the progressive brain changes from MCI to AD. As a data-driven method, FCD measures the profiles of FC for the given voxel at different scales. Resting-state functional magnetic resonance imaging (fMRI) images were obtained from patients with AD and MCI and matched healthy controls (HCs). One-way ANCOVA was used to investigate (global, long-range, and local) FCD differences among the three groups followed by post-hoc analysis controlling age, sex, and head motion.

RESULTS

The three groups exhibited significant global FCD differences in the superior frontal gyrus. The post-hoc results further showed that patients with AD had a significant increase in global FCD values than those with MCI and HCs. Patients with MCI exhibited an increased trend compared with HCs. We further identified brain regions contributing to the observed global FCD differences by conducting seed-based FC analysis. We also identified that the observed global FCD differences were the additive effects of altered FC between the superior frontal gyrus and the posterior default model network.

DISCUSSION

These results depicted the global information communication capability impairment in AD and MCI providing a new insight into the progressive brain changes from MCI to AD.