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Evidence has demonstrated associations of bipolar disorder (BD) with cognitive impairment, dysregulated proinflammatory cytokines, and appetite hormones.
Aim
To compare executive dysfunction, proinflammatory cytokines, and appetite hormones between patients with first-episode and multiple-episode BDs.
Methods
This cross-sectional study included young adults aged 18 to 39 years who were diagnosed as having type 1 BD in the first or recurrent episode and a group of age-/sex-matched healthy controls. Data regarding patient characteristics, clinical symptoms, cytokines (C-reactive protein [CRP], interleukin-6, and tumor necrosis factor [TNF]-α), appetite hormones (leptin, adiponectin, ghrelin, and insulin), and executive function evaluated using the Wisconsin Card Sorting Test (WCST) were collected.
Results
A total of 112 participants (38 patients in the multiple-episode BD group, 31 patients in the first-episode BD group, and 43 in the control group) were included. Multivariate analysis revealed that patients in the multiple-episode BD group performed significantly worse in the WCST (P < .05) and had higher levels of ghrelin (P = .002), and lower levels of CRP (P = .040) than those in the first-episode BD group. Patients with BD had significantly higher TNF-α and ghrelin levels compared with the healthy controls. No significant associations of CRP, TNF-α, and ghrelin levels with executive function were observed.
Conclusions
Profiles in proinflammatory cytokines and appetite hormones as well as executive function significantly differed between patients with first-episode and multiple-episode BDs and controls, which may suggest their potential roles in the clinical stages and pathophysiology of type 1 BD.
Support vector machines (SVMs) based on brain-wise functional connectivity (FC) have been widely adopted for single-subject prediction of patients with schizophrenia, but most of them had small sample size. This study aimed to evaluate the performance of SVMs based on a large single-site dataset and investigate the effects of demographic homogeneity and training sample size on classification accuracy.
Methods
The resting functional Magnetic Resonance Imaging (fMRI) dataset comprised 220 patients with schizophrenia and 220 healthy controls. Brain-wise FCs was calculated for each participant and linear SVMs were developed for automatic classification of patients and controls. First, we evaluated the SVMs based on all participants and homogeneous subsamples of men, women, younger (18–30 years), and older (31–50 years) participants by 10-fold nested cross-validation. Then, we hold out a fixed test set of 40 participants (20 patients and 20 controls) and evaluated the SVMs based on incremental training sample sizes (N = 40, 80, …, 400).
Results
We found that the SVMs based on all participants had accuracy of 85.05%. The SVMs based on male, female, young, and older participants yielded accuracy of 84.66, 81.56, 80.50, and 86.13%, respectively. Although the SVMs based on older subsamples had better performance than those based on all participants, they generalized poorly to younger participants (77.24%). For incremental training sizes, the classification accuracy increased stepwise from 72.6 to 83.3%, with >80% accuracy achieved with sample size >240.
Conclusions
The findings indicate that SVMs based on a large dataset yield high classification accuracy and establish models using a large sample size with heterogeneous properties are recommended for single subject prediction of schizophrenia.
Neuroimaging- and machine-learning-based brain-age prediction of schizophrenia is well established. However, the diagnostic significance and the effect of early medication on first-episode schizophrenia remains unclear.
Aims
To explore whether predicted brain age can be used as a biomarker for schizophrenia diagnosis, and the relationship between clinical characteristics and brain-predicted age difference (PAD), and the effects of early medication on predicted brain age.
Method
The predicted model was built on 523 diffusion tensor imaging magnetic resonance imaging scans from healthy controls. First, the brain-PAD of 60 patients with first-episode schizophrenia, 60 healthy controls and 21 follow-up patients from the principal data-set and 40 pairs of individuals in the replication data-set were calculated. Next, the brain-PAD between groups were compared and the correlations between brain-PAD and clinical measurements were analysed.
Results
The patients showed a significant increase in brain-PAD compared with healthy controls. After early medication, the brain-PAD of patients decreased significantly compared with baseline (P < 0.001). The fractional anisotropy value of 31/33 white matter tract features, which related to the brain-PAD scores, had significantly statistical differences before and after measurements (P < 0.05, false discovery rate corrected). Correlation analysis showed that the age gap was negatively associated with the positive score on the Positive and Negative Syndrome Scale in the principal data-set (r = −0.326, P = 0.014).
Conclusions
The brain age of patients with first-episode schizophrenia may be older than their chronological age. Early medication holds promise for improving the patient's brain ageing. Neuroimaging-based brain-age prediction can provide novel insights into the understanding of schizophrenia.
Cognitive impairment is common in late-life depression, which may increase Alzheimer disease (AD) risk. Therefore, we aimed to investigate whether late-life major depressive disorder (MDD) has worse cognition and increases the characteristic AD neuropathology. Furthermore, we carried out a comparison between treatment-resistant depression (TRD) and non-TRD. We hypothesized that patients with late-life depression and TRD may have increased β-amyloid (Aβ) deposits in brain regions responsible for global cognition.
Methods
We recruited 81 subjects, including 54 MDD patients (27 TRD and 27 non-TRD) and 27 matched healthy controls (HCs). Neurocognitive tasks were examined, including Mini-Mental State Examination and Montreal Cognitive Assessment to detect global cognitive functions. PET with Pittsburgh compound-B and fluorodeoxyglucose were used to capture brain Aβ pathology and glucose use, respectively, in some patients.
Results
MDD patients performed worse in Montreal Cognitive Assessment (p = 0.003) and had more Aβ deposits than HCs across the brain (family-wise error-corrected p < 0.001), with the most significant finding in the left middle frontal gyrus. Significant negative correlations between global cognition and prefrontal Aβ deposits existed in MDD patients, whereas positive correlations were noted in HCs. TRD patients had significantly more deposits in the left-sided brain regions (corrected p < 0.001). The findings were not explained by APOE genotypes. No between-group fluorodeoxyglucose difference was detected.
Conclusions
Late-life depression, particularly TRD, had increased brain Aβ deposits and showed vulnerability to Aβ deposits. A detrimental role of Aβ deposits in global cognition in patients with late-onset or non-late-onset MDD supported the theory that late-life MDD could be a risk factor for AD.
Few studies have explored the complex relationship of pro- and anti-inflammatory cytokines with cognitive function in adolescents with first-episode schizophrenia, bipolar disorder, or major depressive disorder.
Methods
In total, 26, 35, and 29 adolescents with first-episode schizophrenia, bipolar disorder, and major depressive disorder, respectively, and 22 age- and sex-matched controls were included in the current study. Cytokines, namely interleukin (IL)-2, IL-6, tumor necrosis factor (TNF)-α, and C-reactive protein (CRP), were assessed. The Wisconsin Card Sorting Test (WCST) and the working memory task were administered to assess cognitive function.
Results
Using generalized linear models with adjustment for demographic data and clinical symptoms, patients with bipolar disorder were found to exhibit the highest levels of CRP (P = .023), IL-6 (P = .022), and TNF-α (P = .011), and had the lowest IL-2 levels (P = .034) among the four groups. According to the results of the WCST and working memory task, adolescents with schizophrenia exhibited the lowest performance in cognitive function. In addition, among the assessed cytokines, only CRP levels (P = .027) were negatively associated with WCST scores.
Discussion
Dysregulated pro- and anti-inflammatory cytokines and impaired cognitive functioning were observed in first-episode adolescent-onset schizophrenia, bipolar disorder, and major depressive disorder. The altered cytokine profiles may play important roles in the pathophysiology of schizophrenia, bipolar disorder, and major depressive disorder.
Dysregulated proinflammatory cytokines have been shown to be associated with suicidal behavior. Cognitive deficits in working memory and inhibitory control have been demonstrated in depressed patients and people with suicidal ideation (SI). However, the association between proinflammatory cytokines, SI, and cognitive deficits in patients with major depressive disorder (MDD) remains unclear.
Methods
A total of 77 patients with MDD and age-/sex-matched 60 healthy individuals were recruited. MDD patients were divided into two groups: with SI (n = 36) and no SI (n = 41). SI was defined by a score of ≥2 in item 3 of the 17-item Hamilton Rating Scale for Depression. Levels of proinflammatory cytokines, including soluble interleukin-6 receptor, soluble tumor necrosis factor-α receptor type 1, and C-reactive protein (CRP), were measured, and cognitive function was assessed using 2-back task and Go/No-Go task.
Results
Patients with SI had higher levels of CRP than those without SI and controls (P = .007). CRP was positively associated with SI (β = 0.21, P = .037), independent of cognitive function and depressive symptoms. Furthermore, SI was associated with cognitive deficits in working memory and inhibitory control after adjusting for confounding factors (P < .05).
Conclusion
Our findings suggest that higher levels of serum CRP and deficits in working memory and inhibitory control may be associated with higher SI among patients with MDD.
Altered immunity and metabolic profiles have been compared between bipolar depression (BD) and major depressive disorder (MDD). This study aimed at developing a composite predictor of appetite hormones and proinflammatory cytokines to differentiate BD from MDD.
Methods
This cross-sectional study enrolled patients with BD and those with MDD aged 20 to 59 years and displaying depressive episodes. Clinical characteristics (age, sex, body mass index, and depression severity), cytokines (C-reactive protein, interleukin [IL]-2, IL-6, tumor necrosis factor [TNF]-α, P-selectin, and monocyte chemoattractant protein), and appetite hormones (leptin, adiponectin, ghrelin, and insulin) were assessed as potential predictors using a classification and regression tree (CRT) model for differentiating BD from MDD.
Results
The predicted probability of a composite predictor of ghrelin and TNF-α was significantly greater (for BD: area under curve = 0.877; for MDD: area under curve = 0.914) than that of any one marker (all P > .05) to distinguish BD from MDD. The most powerful predictors for diagnosing BD were high ghrelin and TNF-α levels, whereas those for MDD were low ghrelin and TNF-α levels.
Conclusion
A composite predictor of ghrelin and TNF-α driven by CRT could assist in the differential diagnosis of BD from MDD with high specificity. Further clinical studies are warranted to validate our results and to explore underlying mechanisms.
Recent imaging studies of large datasets suggested that psychiatric disorders have common biological substrates. This study aimed to identify all the common neural substrates with connectomic abnormalities across four major psychiatric disorders by using the data-driven connectome-wide association method of multivariate distance matrix regression (MDMR).
Methods
This study analyzed a resting functional magnetic resonance imaging dataset of 100 patients with schizophrenia, 100 patients with bipolar I disorder, 100 patients with bipolar II disorder, 100 patients with major depressive disorder, and 100 healthy controls (HCs). We calculated a voxel-wise 4,330 × 4,330 matrix of whole-brain functional connectivity (FC) with 8-mm isotropic resolution for each participant and then performed MDMR to identify structures where the overall multivariate pattern of FC was significantly different between each patient group and the HC group. A conjunction analysis was performed to identify common neural regions with FC abnormalities across these four psychiatric disorders.
Results
The conjunction of the MDMR maps revealed that the four groups of patients shared connectomic abnormalities in distributed cortical and subcortical structures, which included bilateral thalamus, cerebellum, frontal pole, supramarginal gyrus, postcentral gyrus, lingual gyrus, lateral occipital cortex, and parahippocampus. The follow-up analysis based on pair-wise FC of these regions demonstrated that these psychiatric disorders also shared similar patterns of FC abnormalities characterized by sensory/subcortical hyperconnectivity, association/subcortical hypoconnectivity, and sensory/association hyperconnectivity.
Conclusions
These findings suggest that major psychiatric disorders share common connectomic abnormalities in distributed cortical and subcortical regions and provide crucial support for the common network hypothesis of major psychiatric disorders.
Studies have suggested an association between metabolic and cerebrocardiovascular diseases and major depressive disorder (MDD). However, the risk of metabolic and cerebrocardiovascular diseases in the unaffected siblings of patients with MDD remains uncertain. Using the Taiwan National Health Insurance Research Database, 22,438 unaffected siblings of patients with MDD and 89,752 age-/sex-matched controls were selected and followed up from 1996 to the end of 2011. Individuals who developed metabolic and cerebrocardiovascular diseases during the follow-up period were identified. Compared with the controls, the unaffected siblings of patients with MDD had a higher prevalence of metabolic diseases, such as hypertension (5.0% vs. 4.5%, p = 0.007), dyslipidemia (5.6% vs. 4.8%, p < 0.001), and obesity (1.7% vs. 1.5%, p = 0.028), and cerebrocardiovascular diseases, such as ischemic stroke (0.6% vs. 0.4%, p < 0.005) and ischemic heart disease (2.1% vs. 1.7%, p < 0.001). Logistic regression analyses revealed that the unaffected siblings of patients with MDD were more likely to develop hypertension, dyslipidemia, ischemic stroke, and ischemic heart diseases during the follow-up period than the controls. Our study revealed a familial coaggregation between MDD and metabolic and cerebrocardiovascular diseases. Additional studies are required to investigate the shared pathophysiology of MDD and metabolic and cerebrocardiovascular diseases.
Family coaggregation of attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD) and schizophrenia have been presented in previous studies. The shared genetic and environmental factors among psychiatric disorders remain elusive.
Methods
This nationwide population-based study examined familial coaggregation of major psychiatric disorders in first-degree relatives (FDRs) of individuals with ASD. Taiwan's National Health Insurance Research Database was used to identify 26 667 individuals with ASD and 67 998 FDRs of individuals with ASD. The cohort was matched in 1:4 ratio to 271 992 controls. The relative risks (RRs) and 95% confidence intervals (CI) of ADHD, ASD, BD, MDD and schizophrenia were assessed among FDRs of individuals with ASD and ASD with intellectual disability (ASD-ID).
Results
FDRs of individuals with ASD have higher RRs of major psychiatric disorders compared with controls: ASD 17.46 (CI 15.50–19.67), ADHD 3.94 (CI 3.72–4.17), schizophrenia 3.05 (CI 2.74–3.40), BD 2.22 (CI 1.98–2.48) and MDD 1.88 (CI 1.76–2.00). Higher RRs of schizophrenia (4.47, CI 3.95–5.06) and ASD (18.54, CI 16.18–21.23) were observed in FDRs of individuals with both ASD-ID, compared with ASD only.
Conclusions
The risk for major psychiatric disorders was consistently elevated across all types of FDRs of individuals with ASD. FDRs of individuals with ASD-ID are at further higher risk for ASD and schizophrenia. Our results provide leads for future investigation of shared etiologic pathways of ASD, ID and major psychiatric disorders and highlight the importance of mental health care delivered to at-risk families for early diagnoses and interventions.
Studies have suggested the detrimental effects of obesity and systemic inflammation on the cognitive function of patients with bipolar or major depressive disorder. However, the complex associations between affective disorder, obesity, systemic inflammation, and cognitive dysfunction remain unclear.
Methods
Overall, 110 patients with affective disorder (59 with bipolar I disorder and 51 with major depressive disorder) who scored ≥61 on the Global Assessment of Functioning and 51 age- and sex-matched controls were enrolled. Body mass index ≥25 kg/m2 was defined as obesity or overweight. Levels of proinflammatory cytokines—including interleukin-6, tumor necrosis factor (TNF)-α, and C-reactive protein (CRP)—were measured, and cognitive function was assessed using various methods, including the Wisconsin Card Sorting Test (WCST) and go/no-go task.
Results
Patients with bipolar I disorder or major depressive disorder were more likely to be obese or overweight, had higher CRP and TNF-α levels, and had greater executive dysfunction in the WCST than the controls. TNF-α level (P < .05) but not affective disorder diagnosis or obesity/overweight was significantly associated with cognitive function deficits, although obesity/overweight and diagnosis were significantly associated with increased TNF-α level.
Conclusions
Our findings may indicate that proinflammatory cytokines, but not obesity or overweight, have crucial effects on cognitive function in patients with bipolar I disorder or major depressive disorder, although proinflammatory cytokines and obesity or overweight were found to be strongly associated. The complex relationships between affective disorder diagnosis, proinflammatory cytokine levels, obesity or overweight, and cognitive function require further investigation.
The antidepressant effect of low-dose ketamine infusion on Taiwanese patients with anxious vs nonanxious treatment-resistant depression (ANX-TRD vs NANX-TRD) has remained unknown.
Methods
In total, 71 patients with TRD were randomized to three groups. Each group had participants who received saline infusions mixed with 0 (a normal saline infusion), 0.2, and 0.5 mg/kg of ketamine. Participants were followed up for 2 weeks. Anxious depression was defined as major depressive disorder with a total score of 7 or more on the 17-item Hamilton Depression Rating Scale Anxiety-Somatization factor. Generalized estimating equation models were used to investigate the effects of treatment (ketamine vs placebo) and depression type (ANX-TRD vs NANX-TRD) in the reduction of depressive symptoms during the follow-up period.
Results
Patients with ANX-TRD were less likely to respond to a single low-dose ketamine infusion than those with NANX-TRD. Among patients with NANX-TRD, low-dose ketamine infusion was significantly superior to placebo for reducing depressive symptoms. However, among patients with ANX-TRD, ketamine was not superior to placebo; nonetheless, approximately 30% of the patients responded to ketamine infusion compared to 13% who responded to the placebo.
Conclusions
Low-dose ketamine infusion was effective for Taiwanese patients with NANX-TRD but not so effective for those with ANX-TRD. A higher level of anxiety severity accompanying depression was related to greater depression severity. This may confound and reduce the antidepressant effect of ketamine infusion.
The core toroidal plasma intrinsic rotation has been studied by experiments and simulations in the Joint Texas Experimental Tokamak (J-TEXT). The direction of core intrinsic rotation in the J-TEXT plasma is counter-current. As the plasma density ramps up, the rotation velocity increases in the counter-current direction. By comparing four different electron densities, linear local gyrokinetic simulations have been performed by the Gyrokinetic Electromagnetic Numerical Experiment code for the first time on J-TEXT. It is found that the most dominant turbulence is the ion temperature gradient at $0.2a$, where $a$ is the minor radius of the plasma and this is unchanged during the plasma density ramp up. By scanning the radial wave vectors, it is found that the residual stress term reverses from negative to positive when the plasma density exceeds a certain threshold. The pinch term is larger than the residual stress term at all four electron densities, which means that the pinch term is always dominant in the core of a J-TEXT plasma.
Thermal barrier coating is a high-temperature protective technology widely used in industrial gas turbines. However, the failure of coating peeling because of the generation of thermally grown oxide (TGO) at the interface during service hinders its further application. In this study, Raman spectroscopy and wedge indentation are used to determine the TGO residual stress and the interface energy release rate, respectively. The effect of TGO on the interfacial fracture toughness during the growth process was discussed. Raman spectroscopy test results show that the residual stress of TGO is about 0.5 GPa. Wedge indentation test results illustrate that high-temperature heat treatment could accelerate the interface degradation of thermal barrier coatings. Stress analysis and test research demonstrate that the microcracks induced by compressive stress of TGO will propagate with increasing heating time, ending with failure of barrier coatings.
In recent years, there have been a significant influenza activity and emerging influenza strains in China, resulting in an increasing number of influenza virus infections and leading to public health concerns. The aims of this study were to identify the epidemiological and aetiological characteristics of influenza and establish seasonal autoregressive integrated moving average (SARIMA) models for forecasting the percentage of visits for influenza-like illness (ILI%) in urban and rural areas of Shenyang. Influenza surveillance data were obtained for ILI cases and influenza virus positivity from 18 sentinel hospitals. The SARIMA models were constructed to predict ILI% for January–December 2019. During 2010–2018, the influenza activity was higher in urban than in rural areas. The age distribution of ILI cases showed the highest rate in young children aged 0–4 years. Seasonal A/H3N2, influenza B virus and pandemic A/H1N1 continuously co-circulated in winter and spring seasons. In addition, the SARIMA (0, 1, 0) (0, 1, 2)12 model for the urban area and the SARIMA (1, 1, 1) (1, 1, 0)12 model for the rural area were appropriate for predicting influenza incidence. Our findings suggested that there were regional and seasonal distinctions of ILI activity in Shenyang. A co-epidemic pattern of influenza strains was evident in terms of seasonal influenza activity. Young children were more susceptible to influenza virus infection than adults. These results provide a reference for future influenza prevention and control strategies in the study area.
Whether the first-degree relatives (FDRs) of patients with obsessive-compulsive disorder (OCD) have an increased risk of the major psychiatric disorders, namely schizophrenia, bipolar disorder, OCD, major depressive disorder (MDD), autism spectrum disorder (ASD), and attention deficit hyperactivity disorder (ADHD), remains unclear.
Methods
Using the Taiwan National Health Insurance Research Database with the whole population sample size (n = 23 258 175), 89 500 FDRs, including parents, offspring, siblings, and twins, of patients with OCD were identified in our study. The relative risks (RRs) of major psychiatric disorders were assessed among FDRs of patients with OCD.
Results
FDRs of patients with OCD had higher RRs of major psychiatric disorders, namely OCD (RR 8.11, 95% confidence interval (CI) 7.68–8.57), bipolar disorder (RR 2.85, 95% CI 2.68–3.04), MDD (RR 2.67, 95% CI 2.58–2.76), ASD (RR 2.38, 95% CI 2.10–2.71), ADHD (RR 2.19, 95% CI 2.07–2.32), and schizophrenia (RR 1.97, 95% CI 1.86–2.09), compared with the total population. Different familial kinships of FDRs, such as parents, offspring, siblings, and twins consistently had increased risks for these disorders. In addition, a dose-dependent relationship was found between the numbers of OCD probands and the risk of each major psychiatric disorder.
Conclusions
The FDRs, including parents, offspring, siblings, and twins, of patients with OCD have a higher risk of OCD, schizophrenia, bipolar disorder, MDD, ADHD, and ASD. The familial co-aggregation of OCD with OCD and other major psychiatric disorders was existent in a dose-dependent manner. Given the increased risks of psychiatric disorders, medical practitioners should closely monitor the mental health of the FDRs of patients with OCD.
Research suggests an association between metabolic disorders, such as type 2 diabetes mellitus (T2DM), and schizophrenia. However, the risk of metabolic disorders in the unaffected siblings of patients with schizophrenia remains unclear.
Methods
Using the Taiwan National Health Insurance Research Database, 3135 unaffected siblings of schizophrenia probands and 12,540 age-/sex-matched control subjects were included and followed up to the end of 2011. Individuals who developed metabolic disorders during the follow-up period were identified.
Results
The unaffected siblings of schizophrenia probands had a higher prevalence of T2DM (3.4% vs. 2.6%, p = 0.010) than the controls. Logistic regression analyses with the adjustment of demographic data revealed that the unaffected siblings of patients with schizophrenia were more likely to develop T2DM (odds ratio [OR]: 1.39, 95% confidence interval [CI]: 1.10–1.75) later in life compared with the control group. Moreover, only female siblings of schizophrenia probands had an increased risk of hypertension (OR: 1.47, 95% CI: 1.07–2.01) during the follow-up compared with the controls.
Discussion
The unaffected siblings, especially sisters, of schizophrenia probands had a higher prevalence of T2DM and hypertension compared with the controls. Our study revealed a familial link between schizophrenia and T2DM in a large sample. Additional studies are required to investigate the shared pathophysiology of schizophrenia and T2DM.
Bipolar disorder is a highly heritable mental illness that transmits intergeneratively. Previous studies supported that first-degree relatives (FDRs), such as parents, offspring, and siblings, of patients with bipolar disorder, had a higher risk of bipolar disorder. However, whether FDRs of bipolar patients have an increased risk of schizophrenia, major depressive disorder (MDD), autism spectrum disorder (ASD), and attention deficit hyperactivity disorder (ADHD) remains unclear.
Methods
Among the entire population in Taiwan, 87 639 patients with bipolar disorder and 188 290 FDRs of patients with bipolar disorder were identified in our study. The relative risks (RRs) of major psychiatric disorders were assessed among FDRs of patients with bipolar disorder.
Results
FDRs of patients with bipolar disorder were more likely to have a higher risk of major psychiatric disorders, including bipolar disorder (RR 6.12, 95% confidence interval (CI) 5.95–6.30), MDD (RR 2.89, 95% CI 2.82–2.96), schizophrenia (RR 2.64, 95% CI 2.55–2.73), ADHD (RR 2.21, 95% CI 2.13–2.30), and ASD (RR 2.10, 95% CI 1.92–2.29), than the total population did. These increased risks for major psychiatric disorders were consistent across different familial kinships, such as parents, offspring, siblings, and twins. A dose-dependent relationship was also found between risk of each major psychiatric disorder and numbers of bipolar patients.
Conclusions
Our study was the first study to support the familial coaggregation of bipolar disorder with other major psychiatric disorders, including schizophrenia, MDD, ADHD, and ASD, in a Taiwanese (non-Caucasian) population. Given the elevated risks of major psychiatric disorders, the public health government should pay more attention to the mental health of FDRs of patients with bipolar disorder.
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.