Background. Cardiovascular diseases represent a major health issue in patients with schizophrenia (SCZ) and bipolar disorder (BD), but the exact nature of cardiometabolic (CM) abnormalities involved and the underlying mechanisms remain unclear. Psychiatric medications are known risk factors, but it is unclear whether there is a connection between the disorders (SCZ/BD) themselves and CM abnormalities. Methods. Using polygenic risk scores and linkage disequilibrium score regression, we investigated the shared genetic bases of SCZ and BD with 28 CM traits. We performed Mendelian randomization (MR) to elucidate causal relationships between the two groups of disorders. The analysis was based on large-scale meta-analyses of genome-wide association studies. We also identified the potential shared genetic variants and inferred the pathways involved. Results. We found tentative polygenic associations of SCZ with glucose metabolism abnormalities, adverse adipokine profiles, increased waist-to-hip ratio and visceral adiposity (false discovery rate or FDR<0.05). However, there was an inverse association with body mass index. For BD, we observed several polygenic associations with favorable CM profiles at FDR<0.05. MR analysis showed that SCZ may be causally linked to raised triglyceride and that lower fasting glucose may be linked to BD. We also identified numerous single nucleotide polymorphisms and pathways shared between SCZ/BD with CM traits, some of which are related to inflammation or the immune system. Conclusions. Our findings suggest that SCZ patients may be genetically predisposed to several CM abnormalities independent of medication side effects. On the other hand, CM abnormalities in BD may be more likely to be secondary. However, the findings require further validation.
Background. We hypothesize that the tumor necrosis factor-alpha (TNF-alpha) may play a role in disturbing the effect of selective serotonin reuptake inhibitor (SSRI) on the striatal connectivity in patients with major depressive disorder (MDD). Methods. We performed a longitudinal observation by combining resting-state functional magnetic resonance imaging (rs-fMRI) and biochemical analyses to identify the abnormal striatal connectivity in MDD patients, and to evaluate the effect of TNF-alpha level on these abnormal connectivities during SSRI treatment. Eighty-five rs-fMRI scans were collected from 25 MDD patients and 35 healthy controls, and the scans were repeated for all the patients before and after a 6-week SSRI treatment. Whole-brain voxel-wise functional connectivity (FC) was calculated by correlating the rs-fMRI time courses between each voxel and the striatal seeds (i.e. spherical regions placed at the striatums). The level of TNF-alpha in serum was evaluated by Milliplex assay. Factorial analysis was performed to assess the interaction effects of 'TNF-alpha x treatment' in the regions with between-group FC difference. Results. Compared with controls, MDD patients showed significantly higher striatal FC in the medial prefrontal cortex (MPFC) and bilateral middle/superior temporal cortices before SSRI treatment (p < 0.001, uncorrected). Moreover, a significant interaction effect of 'TNF-alpha x treatment' was found in MPFC-striatum FC in MDD patients (p = 0.002), and the significance remained after adjusted for age, gender, head motion, and episode of disease. Conclusion. These findings provide evidence that treatment-related brain connectivity change is dependent on the TNF-alpha level in MDD patients, and the MPFC-striatum connectivities possibly serve as an important target in the brain.
Altered resting-state functional connectivity (rsFC) has been noted in large-scale functional networks in attention-deficit/hyperactivity disorder (ADHD). However, identifying consistent abnormalities of functional networks is difficult due to varied methods and results across studies. To integrate rsFC alterations and search for coherent patterns of intrinsic functional network impairments in ADHD, this research conducts a coordinate-based meta-analysis of voxel-wise seed-based rsFC studies comparing rsFC between ADHD patients and healthy controls. A total of 25 datasets from 21 studies including 700 ADHD patients and 580 controls were analyzed. We extracted the coordinates of seeds and between-group effects. Each seed was then categorized into a seed-network by its location within priori 7-network parcellations. Then, pooled meta-analyses were conducted for the default mode network (DMN), frontoparietal network (FPN) and affective network (AN) separately, but not for the ventral attention network (VAN), dorsal attention network (DAN), somatosensory network (SSN) and visual network due to a lack of primary studies. The results showed that ADHD was characterized by hyperconnectivity between the FPN and regions of the DMN and AN as well as hypoconnectivity between the FPN and regions of the VAN and SSN. These findings not only support the triple-network model of pathophysiology associated with ADHD but also extend this model by highlighting the involvement of the SSN and AN in the mechanisms of network interactions that may account for motor hyperactivity and impulsive symptoms.
Background. Bipolar disorder (BD) has been associated with altered brain structural and functional connectivity. However, little is known regarding alterations of the structural brain connectome in BD. The present study aimed to use diffusion-tensor imaging (DTI) and graph theory approaches to investigate the rich club organization and white matter structural connectome in BD. Methods. Forty-two patients with unmedicated BD depression and 59 age-, sex- and handedness-matched healthy control participants underwent DTI. The whole-brain structural connectome was constructed by a deterministic fiber tracking approach. Graph theory analysis was used to examine the group-specific global and nodal topological properties, and rich club organizations, and then nonparametric permutation tests were used for group comparisons of network parameters. Results. Compared with healthy control participants, the patients with BD showed abnormal global properties, including increased characteristic path length, and decreased global efficiency and local efficiency. Locally, the patients with BD showed abnormal nodal parameters (nodal strength, nodal efficiency, and nodal betweenness) predominantly in the parietal, orbitofrontal, occipital, and cerebellar regions. Moreover, the patients with BD showed decreased rich club and feeder connectivity density. Conclusions. Our results may reflect the disrupted white matter topological organization in the whole-brain, and abnormal regional connectivity supporting cognitive and affective functioning in depressed BD, which, in part, be due to impaired rich club connectivity.
Background. Suicide rate among rural elderly is the highest among all age groups in China, yet little is known about the suicide risks in this rapidly growing vulnerable population. Methods. This matched case-control psychological autopsy study was conducted during June 2014 to September 2015. Consecutive samples of suicides aged 60 or above were identified in three provinces (Shandong, Hunan, and Guangxi) in China. Living comparisons were 1:1 matched with the suicides in age (3 years old), gender, and living location. Risk factors included demographic characteristics, being left-behind, mental disorder, depressive symptoms, stressful life events, and social support. Results. A total of 242 suicides and 242 comparisons were enrolled: 135 (55.8%) were male, mean (s.d.) age was 74 (8) years. The most frequently used suicide means were pesticides (125, 51.7%) and hanging (95, 39.3%). Independent risks of suicide included unstable marital status [odds ratio (OR) 4.19, 95% confidence interval (CI) 1.61-10.92], unemployed (compared with employed, OR 4.43, 95% CI 1.09-17.95), depressive symptoms (OR 1.34, 95% CI 1.21-1.48), and mental disorder (OR 6.28, 95% CI 1.75-22.54). Structural equation model indicated that the association between being left-behind and suicide was mediated by mental disorder, depressive symptoms, stressful life events, and social support. Conclusions. Unstable marital status, unemployed, depressive symptoms, and mental disorder are independent risk factors for suicide in rural elderly. Being left-behind can elevate the suicide risk through increasing life stresses, depressive symptoms, mental disorder, and decreasing social support. Elderly suicide may be prevented by restricting pesticides, training rural physicians, treating mental disorders, mitigating life stress, and enhancing social connection.
Background. The aim of this study was to explore the relationship between patient self-reported Patient Health Questionnaire-9 (PHQ-9) symptoms and doctor diagnosis of depression using a tree analysis approach. Methods. This was a secondary analysis on a dataset obtained from 10 179 adult primary care patients and 59 primary care physicians (PCPs) across Hong Kong. Patients completed a waiting room survey collecting data on socio-demographics and the PHQ-9. Blinded doctors documented whether they thought the patient had depression. Data were analyzed using multiple logistic regression and conditional inference decision tree modeling. Results. PCPs diagnosed 594 patients with depression. Logistic regression identified gender, age, employment status, past history of depression, family history of mental illness and recent doctor visit as factors associated with a depression diagnosis. Tree analyses revealed different pathways of association between PHQ-9 symptoms and depression diagnosis for patients with and without past depression. The PHQ-9 symptom model revealed low mood, sense of worthlessness, fatigue, sleep disturbance and functional impairment as early classifiers. The PHQ-9 total score model revealed cut-off scores of >12 and >15 were most frequently associated with depression diagnoses in patients with and without past depression. Conclusions. A past history of depression is the most significant factor associated with the diagnosis of depression. PCPs appear to utilize a hypothetical-deductive problem-solving approach incorporating pre-test probability, with different associated factors for patients with and without past depression. Diagnostic thresholds may be too low for patients with past depression and too high for those without, potentially leading to over and under diagnosis of depression.
Background Major depressive disorder (MDD) is associated with high risk of suicide. Conventional neuroimaging works showed abnormalities of static brain activity and connectivity in MDD with suicidal ideation (SI). However, little is known regarding alterations of brain dynamics. More broadly, it remains unclear whether temporal dynamics of the brain activity could predict the prognosis of SI. Methods We included MDD patients (n = 48) with and without SI and age-, gender-, and education-matched healthy controls (n = 30) who underwent resting-state functional magnetic resonance imaging. We first assessed dynamic amplitude of low-frequency fluctuation (dALFF) - a proxy for intrinsic brain activity (iBA) - using sliding-window analysis. Furthermore, the temporal variability (dynamics) of iBA was quantified as the variance of dALFF over time. In addition, the prediction of the severity of SI from temporal variability was conducted using a general linear model. Results Compared with MDD without SI, the SI group showed decreased brain dynamics (less temporal variability) in the dorsal anterior cingulate cortex, the left orbital frontal cortex, the left inferior temporal gyrus, and the left hippocampus. Importantly, these temporal variabilities could be used to predict the severity of SI (r = 0.43, p = 0.03), whereas static ALFF could not in the current data set. Conclusions These findings suggest that alterations of temporal variability in regions involved in executive and emotional processing are associated with SI in MDD patients. This novel predictive model using the dynamics of iBA could be useful in developing neuromarkers for clinical applications.
Background. Assertive Community Treatment (ACT) is an evidence-based treatment program for people with severe mental illness developed in high-income countries. We report the first randomized controlled trial of ACT in mainland China. Methods. Sixty outpatients with schizophrenia with severe functional impairments or frequent hospitalizations were randomly assigned to ACT (n = 30) or standard community treatment (n = 30). The severity of symptoms and level of social functioning were assessed at baseline and every 3 months during the 1-year study. The primary outcome was the duration of hospital readmission. Secondary outcomes included a pre-post change in symptom severity, the rates of symptom relapse and gainful employment, social and occupational functioning, and quality of life of family caregivers. Results. Based on a modified intention-to-treat analysis, the outcomes for ACT were significantly better than those of standard community treatment. ACT patients were less likely to be readmitted [3.3% (1/30) v. 25.0% (7/28), Fisher's exact test p = 0.023], had a shorter mean readmission time [2.4 (13.3) v. 30.7 (66.9) days], were less likely to relapse [6.7% (2/30) v. 28.6% (8/28), Fisher's exact test p = 0.038], and had shorter mean time in relapse [3.5 (14.6) v. 34.4 (70.6) days]. The ACT group also had significantly longer times re-employed and greater symptomatic improvement and their caregivers experienced a greater improvement in their quality of life. Conclusion. Our results show that culturally adapted ACT is both feasible and effective for individuals with severe schizophrenia in urban China. Replication studies with larger samples and longer duration of follow up are warranted.
BackgroundThe role of the cerebellum in obsessive-compulsive disorder (OCD) has drawn increasing attention. However, the functional connectivity between the cerebellum and the cerebral cortex has not been investigated in OCD, nor has the relationship between such functional connectivity and clinical symptoms.MethodsA total of 27 patients with OCD and 21 healthy controls (HCs) matched on age, sex and education underwent magnetic resonance imaging (MRI). Seed-based connectivity analyses were performed to examine differences in cerebellar-cerebral connectivity in patients with OCD compared with HCs. Associations between functional connectivity and clinical features in OCD were analyzed.ResultsCompared with HCs, OCD patients showed significantly decreased cerebellar-cerebral functional connectivity in executive control and emotion processing networks. Within the OCD group, decreased functional connectivity in an executive network spanning the right cerebellar Crus I and the inferior parietal lobule was positively correlated with symptom severity, and decreased connectivity in an emotion processing network spanning the left cerebellar lobule VI and the lingual gyrus was negatively correlated with illness duration.ConclusionsAltered functional connectivity between the cerebellum and cerebral networks involved in cognitive-affective processing in patients with OCD provides further evidence for the involvement of the cerebellum in the pathophysiology of OCD, and is consistent with impairment in executive control and emotion regulation in this condition.
Background. Electroconvulsive therapy (ECT), an effective antidepressive treatment, is frequently accompanied by cognitive impairment (predominantly memory), usually transient and self-limited. The hippocampus is a key region involved in memory and emotion processing, and in particular, the anterior-posterior hippocampal subregions has been shown to be associated with emotion and memory. However, less is known about the relationship between hippocampal-subregion alterations following ECT and antidepressant effects or cognitive impairments. Methods. Resting-state functional connectivity (RSFC) based on the seeds of hippocampal subregions were investigated in 45 pre- and post-ECT depressed patients. Structural connectivity between hippocampal subregions and corresponding functionally abnormal regions was also conducted using probabilistic tractography. Antidepressant effects and cognitive impairments were measured by the Hamilton Depressive Rating Scale (HDRS) and the Category Verbal Fluency Test (CVFT), respectively. Their relationships with hippocampal-subregions alterations were examined. Results. After ECT, patients showed increased RSFC in the hippocampal emotional subregion (HIPe) with the left middle occipital gyrus (LMOG) and right medial temporal gyrus (RMTG). Decreased HDRS was associated with increased HIPe-RMTG RSFC (r = -0.316, p = 0.035) significantly and increased HIPe-LMOG RSFC at trend level (r = -0.283, p = 0.060). In contrast, the hippocampal cognitive subregion showed decreased RSFC with the bilateral angular gyrus, and was correlated with decreased CVFT (r = 0.418, p = 0.015 for left; r = 0.356, p = 0.042 for right). No significant changes were found in structural connectivity. Conclusion. The hippocampal-subregions functional alterations may be specially associated with the antidepressant and cognitive effects of ECT.
Background. Suicide attempt (SA), which is one of the strongest predictors of completed suicide, is common in major depressive disorder (MDD) but its prevalence across epidemiological studies has been mixed. The aim of this comprehensive meta-analysis was to examine the pooled prevalence of SA in individuals with MDD. Methods. A systematic literature search was conducted in PubMed, Embase, PsycINFO, Web of Science and Cochrane Library from their commencement date until 27 December 2017. Original studies containing data on prevalence of SA in individuals with MDD were analyzed. Results. In all, 65 studies with a total of 27 340 individuals with MDD were included. Using the random effects model, the pooled lifetime prevalence of SA was 31% [95% confidence interval (CI) 27-34%], 1-year prevalence was 8% (95% CI 3-14%) and 1-month prevalence was 24% (95% CI 15-34%). Subgroup analyses revealed that the lifetime prevalence of SA was significantly associated with the patient setting, study region and income level, while the 1-month prevalence of SA was associated with only the patient setting. Conclusion. This meta-analysis confirmed that SA was common in individuals with MDD across the world. Careful screening and appropriate interventions should be implemented for SA in the MDD population.
Background Cognitive impairment is a core feature of schizophrenia and has been observed in both familial (FHR) and clinical high-risk (CHR) samples. Nonetheless, there is a paucity of research directly contrasting cognitive profiles in these two high-risk states and first-episode schizophrenia. This study aimed to compare cognitive functions in patients with first-episode schizophrenia-spectrum disorder (FES), their unaffected siblings (FHR), CHR individuals and healthy controls. Method A standardized battery of cognitive assessments was administered to 69 FES patients, 71 help-seeking CHR individuals without family history of psychotic disorder, 50 FHR participants and 68 controls. FES and CHR participants were recruited from territory-wide early intervention service for psychosis in Hong Kong. CHR status was ascertained using Comprehensive Assessment of At-Risk Mental State. Results Among four groups, FES patients displayed the largest global cognitive impairment and had medium-to-large deficits across all cognitive tests relative to controls. CHR and FHR participants significantly underperformed in most cognitive tests than controls. Among various cognitive tests, digit symbol coding demonstrated the greatest magnitude of impairment in FES and CHR groups compared with controls. No significant difference between two high-risk groups was observed in global cognition and all individual cognitive tests except digit symbol coding which showed greater deficits in CHR than in FHR participants. Conclusion Clinical and familial risk groups experienced largely comparable cognitive impairment that was intermediate between FES and controls. Digit symbol coding may have the greatest discriminant capacity in distinguishing FES and CHR from healthy controls, and between two high-risk samples.
Background Excessive worry is a defining feature of generalized anxiety disorder and is present in a wide range of other psychiatric conditions. Therefore, individualized predictions of worry propensity could be highly relevant in clinical practice, with respect to the assessment of worry symptom severity at the individual level. Methods We applied a multivariate machine learning approach to predict dispositional worry based on microstructural integrity of white matter (WM) tracts. Results We demonstrated that the machine learning model was able to decode individual dispositional worry scores from microstructural properties in widely distributed WM tracts (mean absolute error = 10.46, p < 0.001; root mean squared error = 12.82, p < 0.001; prediction R-2 = 0.17, p < 0.001). WM tracts that contributed to worry prediction included the posterior limb of internal capsule, anterior corona radiate, and cerebral peduncle, as well as the corticolimbic pathways (e.g. uncinate fasciculus, cingulum, and fornix) already known to be critical for emotion processing and regulation. Conclusions The current work thus elucidates potential neuromarkers for clinical assessment of worry symptoms across a wide range of psychiatric disorders. In addition, the identification of widely distributed pathways underlying worry propensity serves to better improve the understanding of the neurobiological mechanisms associated with worry.
Background This study aim to derive and validate a simple and well-performing risk calculator (RC) for predicting psychosis in individual patients at clinical high risk (CHR). Methods From the ongoing ShangHai-At-Risk-for-Psychosis (SHARP) program, 417 CHR cases were identified based on the Structured Interview for Prodromal Symptoms (SIPS), of whom 349 had at least 1-year follow-up assessment. Of these 349 cases, 83 converted to psychosis. Logistic regression was used to build a multivariate model to predict conversion. The area under the receiver operating characteristic (ROC) curve (AUC) was used to test the effectiveness of the SIPS-RC. Second, an independent sample of 100 CHR subjects was recruited based on an identical baseline and follow-up procedures to validate the performance of the SIPS-RC. Results Four predictors (each based on a subset of SIPS-based items) were used to construct the SIPS-RC: (1) functional decline; (2) positive symptoms (unusual thoughts, suspiciousness); (3) negative symptoms (social anhedonia, expression of emotion, ideational richness); and (4) general symptoms (dysphoric mood). The SIPS-RC showed moderate discrimination of subsequent transition to psychosis with an AUC of 0.744 (p < 0.001). A risk estimate of 25% or higher had around 75% accuracy for predicting psychosis. The personalized risk generated by the SIPS-RC provided a solid estimate of conversion outcomes in the independent validation sample, with an AUC of 0.804 [95% confidence interval (CI) 0.662-0.951]. Conclusion The SIPS-RC, which is simple and easy to use, can perform in the same manner as the NAPLS-2 RC in the Chinese clinical population. Such a tool may be used by clinicians to counsel appropriately their patients about clinical monitor v. potential treatment options.