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.

Resolving heterogeneity in obsessive-compulsive disorder through individualized differential structural covariance network analysis.

BACKGROUND: The high heterogeneity of obsessive-compulsive disorder (OCD) denies attempts of traditional case-control studies to derive neuroimaging biomarkers indicative of precision diagnosis and treatment. METHODS: To handle the heterogeneity, we uncovered subject-level altered structural covariance by adopting individualized differential structural covariance network (IDSCN) analysis. The IDSCN measures how structural covariance edges in a patient deviated from those in matched healthy controls (HCs) yielding subject-level differential edges. One hundred patients with OCD and 106 HCs were recruited and whose T1-weighted anatomical images were acquired. We obtained individualized differential edges and then clustered patients into subtypes based on these edges. RESULTS: Patients presented tremendously low overlapped altered edges while frequently shared altered edges within subcortical-cerebellum network. Two robust neuroanatomical subtypes were identified. Subtype 1 presented distributed altered edges while subtype 2 presented decreased edges between default mode network and motor network compared with HCs. Altered edges in subtype 1 predicted the total Yale-Brown Obsessive Compulsive Scale score while that in subtype 2 could not. CONCLUSIONS: We depict individualized structural covariance aberrance and identify that altered connections within subcortical-cerebellum network are shared by most patients with OCD. These 2 subtypes provide new insights into taxonomy and facilitate potential clues to precision diagnosis and treatment of OCD.

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.

Two distinct subtypes of obsessive compulsive disorder revealed by a framework integrating multimodal neuroimaging information.

Patients with obsessive compulsive disorder (OCD) exhibit tremendous heterogeneity in structural and functional neuroimaging aberrance. However, most previous studies just focus on group-level aberrance of a single modality ignoring heterogeneity and multimodal features. On that account, we aimed to uncover OCD subtypes integrating structural and functional neuroimaging features with the help of a multiview learning method and examined multimodal aberrance for each subtype. Ninety-nine first-episode untreated patients with OCD and 104 matched healthy controls (HCs) undergoing structural and functional MRI were included in this study. Voxel-based morphometric and amplitude of low-frequency fluctuation (ALFF) were adopted to assess gray matter volumes (GMVs) and the spontaneous neuronal fluctuations respectively. Structural/functional distance network was obtained by calculating Euclidean distance between pairs of regional GMVs/ALFF values across patients. Similarity network fusion, one of multiview learning methods capturing shared and complementary information from multimodal data sources, was used to fuse multimodal distance networks into one fused network. Then spectral clustering was adopted to categorize patients into subtypes. As a result, two robust subtypes were identified. These two subtypes presented opposite GMV aberrance and distinct ALFF aberrance compared with HCs while shared indistinguishable clinical and demographic features. In addition, these two subtypes exhibited opposite structure-function difference correlation reflecting distinct adaptive modifications between multimodal aberrance. Altogether, these results uncover two objective subtypes with distinct multimodal aberrance and provide a new insight into taxonomy of OCD.

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

Neurobiological heterogeneity in obsessive compulsive disorder (OCD) is understudied leading to conflicting neuroimaging findings. Therefore, we investigated objective neuroanatomical subtypes of OCD by adopting a newly proposed method based on gray matter volumes (GMVs). GMVs were derived from T1-weighted anatomical images of patients with OCD (n = 100) and matched healthy controls (HCs; n = 106). We first inquired whether patients with OCD presented higher interindividual variability HCs in terms of GMVs. Then, we identified distinct subtypes of OCD by adopting heterogeneity through discriminative analysis (HYDRA), where regional GMVs were treated as features. Patients with OCD presented higher interindividual variability than HCs, suggesting a high structural heterogeneity of OCD. HYDRA identified two distinct robust subtypes of OCD presenting opposite neuroanatomical aberrances compared with HCs, while sharing indistinguishable clinical and demographic features. Specifically, Subtype 1 exhibited widespread increased GMVs in cortical and subcortical regions, including the orbitofrontal gyrus, right anterior insula, bilateral hippocampus, and bilateral parahippocampus and cerebellum. Subtype 2 demonstrated overall decreased GMVs in regions such as the orbitofrontal gyrus, right anterior insula, and precuneus. When mixed together, none of patients presented significant differences compared with HCs. In addition, the total intracranial volume of Subtype 2 was significantly correlated with the total score of the Yale-Brown Obsessive Compulsive Scale while that of Subtype 1 was not. These results identified two distinct neuroanatomical subtypes, providing a possible explanation for conflicting neuroimaging findings, and proposed a potential objective taxonomy contributing to precise clinical diagnosis and treatment in OCD.

Effect of Escitalopram on Serum GDNF and BDNF Levels and 5-HT Level of Brain Tissue of Obsessive-Compulsive Disorder Rats.

The present study aims to discuss the effect of escitalopram in glial cell line-derived neurotrophic factor (GDNF), brain-derived neurotrophic factor (BDNF) levels, and 5-Hydroxytryptamine (5-HT) in obsessive-compulsive disorder rats. A total of 42 rats were divided into three groups randomly: control group (n = 14), model group (n = 14) (obsessive-compulsive disorder group), and escitalopram group (n = 14) (model + obsessive-compulsive disorder group + escitalopram treatment). The open-field method was used to test the rat behavior, enzyme-linked immunosorbent assay (ELISA) was used to determine the serum GDNF and BDNF levels. In addition, Western blot was used to determine the brain tissue protein levels of GDNF and BDNF and high-performance liquid chromatography + electrochemistry method to determine the 5-HT level of brain tissue. Visiting place was changed, rotational frequency and fixed duration enhanced in escitalopram group compared to model group (P < 0.05). Besides, GDNF and BDNF levels of serum and brain tissue were decreased in model group and escitalopram group compared to control group (P < 0.05), while GDNF and BDNF levels of serum and brain tissue were increased in escitalopram group compared to model group (P < 0.05). Moreover, the 5-HT level of brain tissue in escitalopram group was higher than that in model group (P < 0.05). Escitalopram could increase GDNF and BDNF levels and 5-HT content in serum and brain tissue in obsessive-compulsive disorder rats, which contributes to a function on the treatment of obsessive-compulsive disorder.

Gray matter morphological abnormities are constrained by normal structural covariance network in OCD.

A growing body of evidences reveal that abnormal gray matter morphology is constrained by normal brain network architecture in neurodegenerative and psychiatric disorders. However, whether this finding holds true in obsessive-compulsive disorder (OCD) remains unknown. In the current study, we aimed to investigate the association between gray matter morphological abnormities and normal structural covariance network architecture in OCD. First, gray matter morphological abnormities were obtained between 98 medicine-naive and first-episode patients with OCD and 130 healthy controls (HCs). Then, putative disease epicenters whose structural connectome profiles in HCs most resembled the morphological differences pattern were identified using a backfoward stepwise regression analysis. A set of brain regions were identified as putative disease epicenters whose structural connectome architecture significantly explained 59.94% variance of morphological abnormalities. These disease epicenters comprised brain regions implicated in high-order cognitive functions and sensory/motor processing. Other brain regions with stronger structural connections to disease epicenters exhibited greater vulnerability to disease. Together, these results suggest that gray matter abnormities are constrained by structural connectome and provide new insights into the possible pathological progression in OCD.

Prevalence of Lipoprotein(a) Measurement and its Association with Arteriosclerosis in Asymptomatic Individuals in China.

AIMS: Lipoprotein(a) [Lp(a)] is an independent risk factor for atherosclerotic cardiovascular disease (ASCVD), and its level is genetically determined. Although guidelines and consensuses in various cardiovascular fields have emphasized the importance of Lp(a), screening for Lp(a) in China has not been well studied. METHODS: A cross-sectional study was conducted using a random sample of 30,000 medical examiners from each of the five health check-up centres. The distribution of Lp(a) was described for those who completed Lp(a) testing, and logistic regression modelling was used to evaluate the relationship between Lp(a) levels and vascular structure and function in the population who underwent carotid ultrasound and brachial‒ankle pulse wave velocity (baPWV) measurements. RESULTS: Lp(a) was measured in only 4400 (3.02%) of the 150,000 participants. Among those tested for Lp(a), the median concentration was 15.85 mg/dL. The proportion of participants with Lp(a) levels ≥ 30 mg/dL was 15.00%. Multiple logistic regression analysis revealed a significant correlation between Lp(a) and cIMT ≥ 1.0 mm (OR: 1.008, 95% CI: 1.001-1.014, P=0.020) and carotid artery plaques (OR: 1.010, 95% CI: 1.004-1.016, P=0.001) but no correlation with baPWV ≥ 1400 (OR: 0.999, 95% CI: 0.993-1.005, P=0.788) or baPWV ≥ 1800 (OR: 1.002, 95% CI: 0.993-1.011, P=0.634). CONCLUSIONS: The detection rate of Lp(a) at health checkups is low, and Lp(a) is positively associated with cervical vascular sclerosis and plaque but not with baPWV. Therefore, the testing rate of Lp(a) and the awareness of the risk of vascular structural changes due to Lp(a) should be further improved.

A study on diffusion tensor imaging in patients with untreated first-episode obsessive-compulsive disorder.

OBJECTIVE: The present study provides an overview of studies investigating white matter (WM) integrity in patients with obsessive-compulsive disorder (OCD) using diffusion tensor imaging (DTI). Furthermore, it studies the correlation of fractional anisotropy (FA) in abnormal cerebral WM areas with the course and clinical signs of the disease. METHODS: The study subjects were divided into two groups, the OCD group (n=38) and the control group (n=40), based on the Diagnostic and Statistical Manual of Mental Disorders 5 (DSM-5) diagnostic criteria for OCD. Patients with untreated first-episode OCD were assigned to the OCD group, while healthy volunteers were assigned to the control group. The study group was evaluated in accordance with the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS), Self-Rating Depression Scale (SDS) and Self-Rating Anxiety Scale (SAS). Subjects who met the inclusion criteria underwent whole-brain scanning via 3.0 T structural magnetic resonance imaging (sMRI). The WM FA values in different brain areas were compared between the two groups using voxel-based analysis (VBA). Subsequently, the correlations of the patient Y-BOCS score and disorder course with the FA values in significantly improved encephalic areas were analyzed. RESULTS: (I) The FA values of the right precentral gyrus (PreCG.R), left insular lobe, left inferior frontal gyrus and right inferior occipital gyrus (Occipital_Inf_R) WM were significantly lower in the OCD group than in the control group (P<0.05). Elevated FA values were not observed in the OCD group. (II) FA values of PreCG.R, left insular lobe/left inferior frontal gyrus, and Occipital_Inf_R were not found in relation to the total Y-BOCS score (P=0.122; P=0.401; P=0.134), obsessional thoughts score (P=0.299; P=0.760; P=0.062), compulsive activities checklist (P=0.487; P=0.420; P=0.431), and disease course (P=0.604; P=0.380; P=0.182). CONCLUSIONS: Multiple microstructural cerebral WM changes were observed in the frontal lobe, occipital lobe, and insula in patients with untreated first-episode OCD, presenting the correlation of these changes with OCD occurrence.

Changes in the psychological defense mechanism and clinical features of patients with OCD - A four-year follow-up study.

OBJECTIVE: The present study aims to (1) follow up with 4-year changes in the efficacy outcome, defense style questionnaire (DSQ) score, and clinical features of patients with obsessive-compulsive disorder (OCD) and (2) analyze the relationship between different levels of efficacy and changes in the patients' psychological defense mechanisms. METHODS: The following data collection and 4-year follow-up were completed for 153 patients with OCD: (1) the treatment process, efficacy outcome, course of disease, and clinical features of OCD were collected using a self-made general information questionnaire and (2) the control method was used to analyze the changes in clinical symptoms (Yale-Brown obsessive compulsive scale [YBOCS], Hamilton anxiety score [HAMA], and Hamilton depression scale [HAMD]) in patients with OCD. Moreover, the changes in the psychological defense mechanism (measured by DSQ) and the relation between the prognosis and DSQ score were investigated. RESULTS: (1) The HAMA score (8.7 ±â€¯4.8 points), HAMD score (12.0 ±â€¯6.6 points) and YBOCS score (16.4 ±â€¯8.4 points) were significantly lower during the follow-up than at the time of enrollment (p < 0.01). In the two DSQ evaluations, there were no significant differences in the factors, with the exception of a significant decrease in the use of "reaction formation" (t = 2.533, p = 0.015). The changes of mature defense factors in the significant efficacy group significantly increased (p < 0.01). Which was mainly manifested in the significant increase in the score of "sublimation" item, and the difference was extremely significant (t = -3.093, p = 0.006). CONCLUSION: An abnormal psychological defense mechanism plays an important role in OCD, and the use of a mature defense mechanism is significantly related to the treatment efficacy.

The effectiveness of mindfulness-based cognitive therapy combined with medication therapy in preventing recurrence of major depressive disorder in convalescent patients.

Objective: This study aims to investigate the effectiveness of mindfulness-based cognitive therapy (MBCT) combined with medication therapy in preventing the recurrence of major depressive disorder (MDD) in convalescent patients. Methods: A total of 130 patients with convalescent MDD were enrolled in this prospective study. Sixty-five patients were assigned to the experimental group and received medication therapy combined with MBCT, and 65 patients were assigned to the control group and treated with medication alone. The recurrence rate and related hormonal changes were compared between the two groups. Results: After 1 year of MBCT intervention, eight patients experienced recurrence in the experimental group, a recurrence rate of 12.31%, and 19 patients experienced recurrence in the control group, a recurrence rate of 29.23%. The Hamilton Depression Rating Scale (HAM-D) and the World Health Organization Quality of Life Scale (WHOQOL-BREF) scores in both the experimental and the control groups were significantly improved after treatment (P < 0.05). The difference in the HAM-D scores before and after treatment in the experimental group was 16.74 ± 4.54; this was significantly higher than that of the control group (8 ± 3.89, P < 0.0001). The WHOQOL-BREF scores in the experimental group were significantly improved compared with those of the control group (P < 0.0001). The differences in the levels of corticotrophin-releasing hormone (CRH), adrenocorticotropic hormone, and cortisol before and after treatment in the experimental group and the control group were statistically significant (P < 0.05). The difference in CRH before and after treatment in the experimental group was 16.8 ± 7.2, which was higher than that of the control group (2.75 ± 9.27, P < 0.0001). The intervention with MBCT had a significant impact on the recurrence of MDD [ß = 1.206, P = 0.039, 95% (confidence interval) CI = 0.0790-1.229]. The difference in the HAM-D scores also had a significant impact on the recurrence of MDD (ß = 1.121, P = 0.0014, 95% CI = 0.805-0.976). Conclusion: Compared with medication therapy alone, the use of MBCT combined with medication therapy can effectively prevent the recurrence of MDD in convalescent patients.