Dynamicity of brain network organization & their community architecture as characterizing features for classification of common mental disorders from whole-brain connectome.

The urgency of addressing common mental disorders (bipolar disorder, attention-deficit hyperactivity disorder (ADHD), and schizophrenia) arises from their significant societal impact. Developing strategies to support psychiatrists is crucial. Previous studies focused on the relationship between these disorders and changes in the resting-state functional connectome's modularity, often using static functional connectivity (sFC) estimation. However, understanding the dynamic reconfiguration of resting-state brain networks with rich temporal structure is essential for comprehending neural activity and addressing mental health disorders. This study proposes an unsupervised approach combining spatial and temporal characterization of brain networks to classify common mental disorders using fMRI timeseries data from two cohorts (N = 408 participants). We employ the weighted stochastic block model to uncover mesoscale community architecture differences, providing insights into network organization. Our approach overcomes sFC limitations and biases in community detection algorithms by modelling the functional connectome's temporal dynamics as a landscape, quantifying temporal stability at whole-brain and network levels. Findings reveal individuals with schizophrenia exhibit less assortative community structure and participate in multiple motif classes, indicating less specialized network organization. Patients with schizophrenia and ADHD demonstrate significantly reduced temporal stability compared to healthy controls. This study offers insights into functional connectivity (FC) patterns' spatiotemporal organization and their alterations in common mental disorders, highlighting the potential of temporal stability as a biomarker.

Evidence from comprehensive independent validation studies for smooth pursuit dysfunction as a sensorimotor biomarker for psychosis.

Smooth pursuit eye movements are considered a well-established and quantifiable biomarker of sensorimotor function in psychosis research. Identifying psychotic syndromes on an individual level based on neurobiological markers is limited by heterogeneity and requires comprehensive external validation to avoid overestimation of prediction models. Here, we studied quantifiable sensorimotor measures derived from smooth pursuit eye movements in a large sample of psychosis probands (N = 674) and healthy controls (N = 305) using multivariate pattern analysis. Balanced accuracies of 64% for the prediction of psychosis status are in line with recent results from other large heterogenous psychiatric samples. They are confirmed by external validation in independent large samples including probands with (1) psychosis (N = 727) versus healthy controls (N = 292), (2) psychotic (N = 49) and non-psychotic bipolar disorder (N = 36), and (3) non-psychotic affective disorders (N = 119) and psychosis (N = 51) yielding accuracies of 65%, 66% and 58%, respectively, albeit slightly different psychosis syndromes. Our findings make a significant contribution to the identification of biologically defined profiles of heterogeneous psychosis syndromes on an individual level underlining the impact of sensorimotor dysfunction in psychosis.

Targeting inflammasome complexes as a novel therapeutic strategy for mood disorders.

INTRODUCTION: Inflammasome complexes, especially NLRP3, have gained great attention as a potential therapeutic target in mood disorders. NLRP3 triggers a caspase 1-dependent release of the inflammatory cytokines IL-1ß and IL-18, and seems to interact with purinergic and kynurenine pathways, all of which are implicated in mood disorders development and progression. AREAS COVERED: Emerging evidence supports NLRP3 inflammasome as a promising pharmacological target for mood disorders. We discussed the available evidence from animal models and human studies and provided a reflection on drawbacks and perspectives for this novel target. EXPERT OPINION: Several studies have supported the involvement of NLRP3 inflammasome in MDD. However, most of the evidence comes from animal models. The role of NLRP3 inflammasome in BD as well as its anti-manic properties is not very clear and requires further exploration. There is evidence of anti-manic effects of P2×R7 antagonists associated with reduction in the brain levels of IL-1ß and TNF-α in a murine model of mania. The involvement of other NLRP3 inflammasome expressing cells besides microglia, like astrocytes, and of other inflammasome complexes in mood disorders also deserves further investigation. Preclinical and clinical characterization of NLRP3 and other inflammasomes in mood disorders is needed before considering translational approaches, including clinical trials.

Normative modelling of molecular-based functional circuits captures clinical heterogeneity transdiagnostically in psychiatric patients.

Advanced methods such as REACT have allowed the integration of fMRI with the brain's receptor landscape, providing novel insights transcending the multiscale organisation of the brain. Similarly, normative modelling has allowed translational neuroscience to move beyond group-average differences and characterise deviations from health at an individual level. Here, we bring these methods together for the first time. We used REACT to create functional networks enriched with the main modulatory, inhibitory, and excitatory neurotransmitter systems and generated normative models of these networks to capture functional connectivity deviations in patients with schizophrenia, bipolar disorder (BPD), and ADHD. Substantial overlap was seen in symptomatology and deviations from normality across groups, but these could be mapped into a common space linking constellations of symptoms through to underlying neurobiology transdiagnostically. This work provides impetus for developing novel biomarkers that characterise molecular- and systems-level dysfunction at the individual level, facilitating the transition towards mechanistically targeted treatments.

Disrupted default mode network connectivity in bipolar disorder: a resting-state fMRI study.

BACKGROUND: Theoretical and empirical evidence indicates the critical role of the default mode network (DMN) in the pathophysiology of the bipolar disorder (BD). This study aims to identify the specific brain regions of the DMN that is impaired in patients with BD. METHODS: A total of 56 patients with BD and 71 healthy controls (HC) underwent resting-state functional magnetic resonance imaging. Three commonly used functional indices, i.e., fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and degree centrality (DC), were utilized to identify the brain region showing abnormal spontaneous brain activity in patients with BD. Then, this region served as the seed region for resting-state functional connectivity (rsFC) analysis. RESULTS: Compared to the HC group, the BD group showed reduced fALFF, ReHo, and DC values in the left precuneus. Moreover, patients exhibited decreased rsFCs within the left precuneus and between the left precuneus and the medial prefrontal cortex. Additionally, there was diminished negative connectivity between the left precuneus and the left putamen, extending to the left insula (putamen/insula). The abnormalities in DMN functional connectivity were confirmed through various analysis strategies. CONCLUSIONS: Our findings provide convergent evidence for the abnormalities in the DMN, particularly located in the left precuneus. Decreased functional connectivity within the DMN and the reduced anticorrelation between the DMN and the salience network are found in patients with BD. These findings suggest that the DMN is a key aspect for understanding the neural basis of BD, and the altered functional patterns of DMN may be a potential candidate biomarker for diagnosis of BD.

A machine learning approach for differentiating bipolar disorder type II and borderline personality disorder using electroencephalography and cognitive abnormalities.

This study addresses the challenge of differentiating between bipolar disorder II (BD II) and borderline personality disorder (BPD), which is complicated by overlapping symptoms. To overcome this, a multimodal machine learning approach was employed, incorporating both electroencephalography (EEG) patterns and cognitive abnormalities for enhanced classification. Data were collected from 45 participants, including 20 with BD II and 25 with BPD. Analysis involved utilizing EEG signals and cognitive tests, specifically the Wisconsin Card Sorting Test and Integrated Cognitive Assessment. The k-nearest neighbors (KNN) algorithm achieved a balanced accuracy of 93%, with EEG features proving to be crucial, while cognitive features had a lesser impact. Despite the strengths, such as diverse model usage, it's important to note limitations, including a small sample size and reliance on DSM diagnoses. The study suggests that future research should explore multimodal data integration and employ advanced techniques to improve classification accuracy and gain a better understanding of the neurobiological distinctions between BD II and BPD.

Investigational applications of transcranial magnetic stimulation (TMS) in Mood Disorders: Studies from a tertiary care center in India.

The investigational potential of TMS in psychiatry is largely underutilized. In the current article, we present the results of five studies with similar TMS protocols that looked at the investigative applications of TMS via measuring cortical reactivity as potential biomarkers in mood disorders. The first two studies, evaluate potential of TMS parameters and Motor neuron system (MNS) as state or trait markers of BD. Third and fourth studies evaluate these as endophenotypic markers of BD. The fifth study which is an RCT evaluating add-on yoga in UD, evaluates if markers of CI can index the therapeutic response of yoga. In study one MT1 was significantly greater in the SM (symptomatic-mania) group compared to HC (healthy-control) (P=0.032). The cortical inhibition measures SICI was reduced in SM(P=0.021) and BD (remitted Bipolar) (P=0.023) groups compared to HC. LICI was increased in the SM(0.021) and BD(P=0.06) groups compared to HC. In study two, a significant group x time interaction effect was observed indicating higher putative MNS-activity mediation in patients compared to HC on SlCl(P=0.024), LlCl(P=0.033). There were no significant group differences noted in the endophenotype studies. The fifth study showed a significant time X group interaction for CSP, favoring improvement in YG (yoga-group) (p<0.01).No significant change was observed for LICI(p=0.2), SICI(p=0.5). Limitations of these studies notwithstanding, we conclude that cortical reactivity measured using TMS is a potential biomarker across the course of mood disorders, starting from state and trait markers to understanding the therapeutic mechanism of a particular treatment modality in these disorders.

The association between maximal muscle strength, disease severity and psychopharmacotherapy among young to middle-aged inpatients with affective disorders - a prospective pilot study.

BACKGROUND: Motor alterations and lowered physical activity are common in affective disorders. Previous research has indicated a link between depressive symptoms and declining muscle strength primarily focusing on the elderly but not younger individuals. Thus, we aimed to evaluate the relationship between mood and muscle strength in a sample of N = 73 young to middle-aged hospitalized patients (18-49 years, mean age 30.7 years) diagnosed with major depressive, bipolar and schizoaffective disorder, with a focus on moderating effects of psychopharmacotherapy. The study was carried out as a prospective observational study at a German psychiatric university hospital between September 2021 and March 2022. METHODS: Employing a standardized strength circuit consisting of computerized strength training devices, we measured the maximal muscle strength (Fmax) using three repetitions maximum across four muscle regions (abdomen, arm, back, leg) at three time points (t1-t3) over four weeks accompanied by psychometric testing (MADRS, BPRS, YRMS) and blood lipid profiling in a clinical setting. For analysis of psychopharmacotherapy, medication was split into activating (AM) and inhibiting (IM) medication and dosages were normalized by the respective WHO defined daily dose. RESULTS: While we observed a significant decrease of the MADRS score and increase of the relative total Fmax (rTFmax) in the first two weeks (t1-t2) but not later (both p < .001), we did not reveal a significant bivariate correlation between disease severity (MADRS) and muscle strength (rTFmax) at any of the timepoints. Individuals with longer disease history displayed reduced rTFmax (p = .048). IM was significantly associated with decreased rTFmax (p = .032). Regression models provide a more substantial effect of gender, age, and IM on muscle strength than the depressive episode itself (p < .001). CONCLUSIONS: The results of the study indicate that disease severity and muscle strength are not associated in young to middle-aged inpatients with affective disorders using a strength circuit as observational measurement. Future research will be needed to differentiate the effect of medication, gender, and age on muscle strength and to develop interventions for prevention of muscle weakness, especially in younger patients with chronic affective illnesses.

Neurotrophic factor levels and executive functions in children of parents with bipolar disorder: A case controlled study.

BACKGROUND: In the current study, it was aimed to evaluate neurotrophic factor levels and their relationship with executive functions in high-risk children and adolescents (high-risk group) whose parents were diagnosed with bipolar disorder (BD) but not affected by any psychiatric disease,and in order to determine possible vulnerability factors related to the disease. METHODS: The study sample consisted of 32 high-risk group and 34 healthy controls. The Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version-Turkish Adaptation (KSADS-PL-T), Stroop Test, Serial Digit Learning Test (SDLT) and Cancellation Test to evaluate executive functions were administered to all participants by the clinician.Serum levels of neurotrophic factors were measured using commercial enzyme linked immunosorbent assay kits. RESULTS: Serum BDNF, NT-3, NT-4 levels and SDLT scores were significantly lower in the high-risk group for BD compared to the healthy control group. A moderate negative correlation was found between BDNF levels and the Cancellation Test scores in the high-risk group. In addition to these results, the odds ratios of age, NT-4, SDLT scores for being in the risky group in terms of BD diagnosis were 1.26, 0.99 and 0.86 respectively. LIMITATIONS: This was a cross-sectional study. Causality between study results is therefore difficult to establish. The relatively small sample size of the study is another limitation. CONCLUSION: The results of the present study suggest that BDNF, NT-3, NT-4 may play a role in the physiopathology of BD and may be associated with impaired executive function areas such as attention and response inhibition in the high-risk group.

Abnormal resting-state EEG phase dynamics distinguishes major depressive disorder and bipolar disorder.

Changes in EEG have been reported in both major depressive disorder (MDD) and bipolar disorder (BD). Specifically, power changes in EEG alpha and theta frequency bands during rest and task are known in both disorders. This leaves open whether there are changes in yet another component of the electrophysiological EEG signal, namely phase-related processes that may allow for distinguishing MDD and BD. For that purpose, we investigate EEG-based spontaneous phase in the resting state of MDD, BD and healthy controls. Our main findings show: (i) decreased spontaneous phase variability in frontal theta of both MDD and BD compared to HC; (ii) decreased spontaneous phase variability in central-parietal alpha in MDD compared to both BD and HC; (iii) increased delays or lags of alpha phase cycles in MDD (but not in BD), which (iv) correlate with the decreased phase variability in MDD. Together, we show similar (decreased frontal theta variability) and distinct (decreased central-parietal alpha variability with increased lags or delays) findings in the spontaneous phase dynamics of MDD and BD. This suggests potential relevance of theta and alpha phase dynamics in distinguishing MDD and BD in clinical differential-diagnosis.

Sex differences in neural responses to emotional facial expressions are associated with lifetime depression and mania risk.

INTRODUCTION: No studies systematically examined sex differences in neural mechanisms underlying depression and mania/hypomania risk. METHOD: 80 females and 35 males, n = 115(age21.6±1.90) were scanned using 3TfMRI during an implicit emotional-faces task. We examined neural activation to all emotional faces versus baseline, using an anatomical region-of-interest mask comprising regions supporting emotion and salience processing. Sex was a covariate. Extracted parameter estimates(FWE < 0.05,k > 15), age, IQ and their sex interactions were independent variables(IV) in two penalized regression models: dependent variable either MOODS-SR-lifetime, depressive or manic domain score as measures of mania and depression risk. Subsequent Poisson regression models included the non-zero variables identified in the penalized regression models. We tested each model in 2 independent samples. Test sample-I,n = 108(21.6 ± 2.09 years,males/females = 33/75); Test sample-II,n = 93(23.7 ± 2.9 years,males/females = 31/62). RESULTS: Poisson regression models yielded significant relationships with depression and mania risk: Positive correlations were found between right fusiform activity and depression(beta = 0.610) and mania(beta = 0.690) risk. There was a significant interaction between sex and right fusiform activity(beta = -0.609) related to depression risk, where females had a positive relationship than; and a significant interaction(beta = 0.743) between sex and left precuneus activity related to mania risk, with a more negative relationship in females than males. All findings were replicated in the test samples(qs < 0.05,FDR). LIMITATIONS: No longitudinal follow-up. CONCLUSION: Greater visual attention to emotional faces might underlie greater depression and mania risk, and confer greater vulnerability to depression in females, because of heightened visual attention to emotional faces. Females have a more negative relationship between mania risk and left precuneus activity, suggesting heightened empathy might be associated with reduced mania/hypomania risk in females more than males.

Mice with deficiency in Pcdh15, a gene associated with bipolar disorders, exhibit significantly elevated diurnal amplitudes of locomotion and body temperature.

Genetic factors significantly affect the pathogenesis of psychiatric disorders. However, the specific pathogenic mechanisms underlying these effects are not fully understood. Recent extensive genomic studies have implicated the protocadherin-related 15 (PCDH15) gene in the onset of psychiatric disorders, such as bipolar disorder (BD). To further investigate the pathogenesis of these psychiatric disorders, we developed a mouse model lacking Pcdh15. Notably, although PCDH15 is primarily identified as the causative gene of Usher syndrome, which presents with visual and auditory impairments, our mice with Pcdh15 homozygous deletion (Pcdh15-null) did not exhibit observable structural abnormalities in either the retina or the inner ear. The Pcdh15-null mice showed very high levels of spontaneous motor activity which was too disturbed to perform standard behavioral testing. However, the Pcdh15 heterozygous deletion mice (Pcdh15-het) exhibited enhanced spontaneous locomotor activity, reduced prepulse inhibition, and diminished cliff avoidance behavior. These observations agreed with the symptoms observed in patients with various psychiatric disorders and several mouse models of psychiatric diseases. Specifically, the hyperactivity may mirror the manic episodes in BD. To obtain a more physiological, long-term quantification of the hyperactive phenotype, we implanted nano tag® sensor chips in the animals, to enable the continuous monitoring of both activity and body temperature. During the light-off period, Pcdh15-null exhibited elevated activity and body temperature compared with wild-type (WT) mice. However, we observed a decreased body temperature during the light-on period. Comprehensive brain activity was visualized using c-Fos mapping, which was assessed during the activity and temperature peak and trough. There was a stark contrast between the distribution of c-Fos expression in Pcdh15-null and WT brains during both the light-on and light-off periods. These results provide valuable insights into the neural basis of the behavioral and thermal characteristics of Pcdh15-deletion mice. Therefore, Pcdh15-deletion mice can be a novel model for BD with mania and other psychiatric disorders, with a strong genetic component that satisfies both construct and surface validity.

Assessment of symptom severity in psychotic disorder patients based on heart rate variability and accelerometer mobility data.

BACKGROUND: Advancement in mental health care requires easily accessible, efficient diagnostic and treatment assessment tools. Viable biomarkers could enable objectification and automation of the diagnostic and treatment process, currently dependent on a psychiatric interview. Available wearable technology and computational methods make it possible to incorporate heart rate variability (HRV), an indicator of autonomic nervous system (ANS) activity, into potential diagnostic and treatment assessment frameworks as a biomarker of disease severity in mental disorders, including schizophrenia and bipolar disorder (BD). METHOD: We used a commercially available electrocardiography (ECG) chest strap with a built-in accelerometer, i.e. Polar H10, to record R-R intervals and physical activity of 30 hospitalized schizophrenia or BD patients and 30 control participants through ca. 1.5-2 h time periods. We validated a novel approach to data acquisition based on a flexible, patient-friendly and cost-effective setting. We analyzed the relationship between HRV and the Positive and Negative Syndrome Scale (PANSS) test scores, as well as the HRV and mobility coefficient. We also proposed a method of rest period selection based on R-R intervals and mobility data. The source code for reproducing all experiments is available on GitHub, while the dataset is published on Zenodo. RESULTS: Mean HRV values were lower in the patient compared to the control group and negatively correlated with the results of the PANSS general subcategory. For the control group, we also discovered the inversely proportional dependency between the mobility coefficient, based on accelerometer data, and HRV. This relationship was less pronounced for the treatment group. CONCLUSIONS: HRV value itself, as well as the relationship between HRV and mobility, may be promising biomarkers in disease diagnostics. These findings can be used to develop a flexible monitoring system for symptom severity assessment.

Behavioral evidence of impaired self-referential processing in patients with affective disorders and first-episode schizophrenia.

Despite the critical role of self-disturbance in psychiatric diagnosis and treatment, its diverse behavioral manifestations remain poorly understood. This investigation aimed to elucidate unique patterns of self-referential processing in affective disorders and first-episode schizophrenia. A total of 156 participants (41 first-episode schizophrenia [SZ], 33 bipolar disorder [BD], 44 major depressive disorder [MDD], and 38 healthy controls [HC]) engaged in a self-referential effect (SRE) task, assessing trait adjectives for self-descriptiveness, applicability to mother, or others, followed by an unexpected recognition test. All groups displayed preferential self- and mother-referential processing with no significant differences in recognition scores. However, MDD patients showed significantly enhanced self-referential recognition scores and increased bias compared to HC, first-episode SZ, and BD. The present study provides empirical evidence for increased self-focus in MDD and demonstrates that first-episode SZ and BD patients maintain intact self-referential processing abilities. These findings refine our understanding of self-referential processing impairments across psychiatric conditions, suggesting that it could serve as a supplementary measure for assessing treatment response in first-episode SZ and potentially function as a discriminative diagnostic criterion between MDD and BD.

Network analysis of comorbid aggressive behavior and testosterone among bipolar disorder patients: a cross-sectional study.

Testosterone has complex effects on psychological traits and behavior; it is associated with social dominance and competition and is a potential human sex pheromone. This study aimed to investigate the associations between testosterone levels, aggressive behavior, and manic symptoms using a network analysis among bipolar disorder (BD) patients in psychiatric emergency departments (PED). Data from January 2021 and March 2022 BD patients in PED were analyzed. Manic symptoms were assessed using the Young Mania Rating Scale (YMRS). Aggression was assessed with subscale of the PANSS scale (PANSS-AG). The undirected network structures of testosterone levels, aggressive behavior, and manic symptoms were estimated, and centrality and bridge centrality indices were examined. Network stability was examined using the case-dropping procedure. The Network Comparison Test (NCT) was conducted to evaluate whether network characteristics differed by gender. We recruited a total of 898 BD patients, with the mean YMRS score as 13.30 ± 9.58. The prevalence of level II aggression was 35.6% (95%CI = 32.5%-38.7%), level III aggression was 29.5% (95%CI = 26.3%-32.6%), and level VI aggression was 7.0% (95%CI = 5.4%-8.8%). The male participants had a mean testosterone level of 391.71 (Standard Deviation (SD):223.39) compared to 36.90 (SD:30.50) for female participants in the whole sample. Through network analysis, "Increased motor activity-energy" emerged as the central symptom, with the highest centrality expected influence, followed by "Emotional Instability" and "Disruptive/aggression behavior". Notably, "Emotional Instability" appeared to be the bridge symptom linking manic symptoms to aggressive behavior. Within the flow network model, "Speech rate and amount" exhibited the strongest positive correlation with testosterone levels, followed closely by "Disruptive/aggression behavior". The constructed network model demonstrated robust stability, with gender showing no significant impact on the structure. In this study, "Increased motor activity-energy" stood out as the most influential symptom, and "Speech rate and amount" acted as the main bridge symptom linking testosterone levels, aggressive behavior, and manic symptoms. Targeting the central and bridge symptoms may improve the outcomes of aggression interventions implemented among BD patients in psychiatric emergency care.

Chronotype and subjective sleep quality predict white matter integrity in young people with emerging mental disorders.

Protecting brain health is a goal of early intervention. We explored whether sleep quality or chronotype could predict white matter (WM) integrity in emerging mental disorders. Young people (N = 364) accessing early-intervention clinics underwent assessments for chronotype, subjective sleep quality, and diffusion tensor imaging. Using machine learning, we examined whether chronotype or sleep quality (alongside diagnostic and demographic factors) could predict four measures of WM integrity: fractional anisotropy (FA), and radial, axial, and mean diffusivities (RD, AD and MD). We prioritised tracts that showed a univariate association with sleep quality or chronotype and considered predictors identified by ≥80% of machine learning (ML) models as 'important'. The most important predictors of WM integrity were demographics (age, sex and education) and diagnosis (depressive and bipolar disorders). Subjective sleep quality only predicted FA in the perihippocampal cingulum tract, whereas chronotype had limited predictive importance for WM integrity. To further examine links with mood disorders, we conducted a subgroup analysis. In youth with depressive and bipolar disorders, chronotype emerged as an important (often top-ranking) feature, predicting FA in the cingulum (cingulate gyrus), AD in the anterior corona radiata and genu of the corpus callosum, and RD in the corona radiata, anterior corona radiata, and genu of corpus callosum. Subjective quality was not important in this subgroup analysis. In summary, chronotype predicted altered WM integrity in the corona radiata and corpus callosum, whereas subjective sleep quality had a less significant role, suggesting that circadian factors may play a more prominent role in WM integrity in emerging mood disorders.

The overlap across psychotic disorders: A functional network connectivity analysis.

Functional network connectivity (FNC) has previously been shown to distinguish patient groups from healthy controls (HC). However, the overlap across psychiatric disorders such as schizophrenia (SZ), bipolar (BP), and schizoaffective disorder (SAD) is not evident yet. This study focuses on studying the overlap across these three psychotic disorders in both dynamic and static FNC (dFNC/sFNC). We used resting-state fMRI, demographics, and clinical information from the Bipolar-Schizophrenia Network on Intermediate Phenotypes cohort (BSNIP). The data includes three groups of patients with schizophrenia (SZ, N = 181), bipolar (BP, N = 163), and schizoaffective (SAD, N = 130) and HC (N = 238) groups. After estimating each individual's dFNC, we group them into three distinct states. We evaluated two dFNC features, including occupancy rate (OCR) and distance travelled over time. Finally, the extracted features, including both sFNC and dFNC, are tested statistically across patients and HC groups. In addition, we explored the link between the clinical scores and the extracted features. We evaluated the connectivity patterns and their overlap among SZ, BP, and SAD disorders (false discovery rate or FDR corrected p < 0.05). Results showed dFNC captured unique information about overlap across disorders where all disorder groups showed similar pattern of activity in state 2. Moreover, the results showed similar patterns between SZ and SAD in state 1 which was different than BP. Finally, the distance travelled feature of SZ (average R = 0.245, p < 0.01) and combined distance travelled from all disorders was predictive of the PANSS symptoms scores (average R = 0.147, p < 0.01).

Comparing Symptoms of Major Depression in Youth with Confirmed Versus Suspected Bipolar Disorder.

Background: While numerous studies have compared symptoms of major depressive episodes (MDEs) associated with bipolar disorder (BD; i.e., bipolar depression) versus major depressive disorder (MDD; i.e., unipolar depression), little is known about this topic in youth. We compared MDE symptoms in youth with BD with youth with suspected BD who have similar clinical and familial characteristics aside from having BD. Methods: MDE symptoms based on Kiddie Schedule for Affective Disorders and Schizophrenia for School Age Children (K-SADS) Depression Rating Scale items for the most severe past episode were compared in youth, ages 13-21 years, with BD (n = 208) versus suspected BD (n = 165). Diagnoses were confirmed via semistructured interviews. Symptoms with between-group differences (p < 0.05) in univariate analyses were evaluated in a multivariate forward stepwise regression. All analyses controlled for age and sex. Results: Youth with BD had significantly higher (more severe) ratings on depressed mood (p = 0.001, η2 = 0.05), irritability (p = 0.037, η2 = 0.02), anhedonia (p = 0.004, η2 = 0.04), negative self-image (p < 0.001, η2 = 0.07), hopelessness (p = 0.04, η2 = 0.02), fatigue (p = 0.001, η2 = 0.05), hypersomnia (p = 0.001, η2 = 0.05), suicidal ideation (p = 0.04, η2 = 0.02), and recurrent thoughts of death (p < 0.001, η2 = 0.05). In regression analyses, the only symptom that remained significant in the BD group was depressed mood (p = 0.002). Conclusions: These findings demonstrate greater severity of depressive symptoms in youth with BD versus MDD across mood, and cognitive and neurovegetative symptom domains. These differences are especially noteworthy given that the MDD group was highly similar to the BD group, aside from BD diagnosis. Present findings emphasize the need for novel treatment approaches to bipolar depression in youth, and for studies examining potential mechanisms underlying the increased severity of bipolar depression.

Cerebellar dysconnectivity in schizophrenia and bipolar disorder is associated with cognitive and clinical variables.

BACKGROUND: Abnormal cerebellar functional connectivity (FC) has been implicated in the pathophysiology of schizophrenia (SCZ) and bipolar disorder (BD). However, the patterns of cerebellar dysconnectivity in these two disorders and their association with cognitive functioning and clinical symptoms have not been fully clarified. In this study, we examined cerebellar FC alterations in SCZ and BD-I and their association with cognition and psychotic symptoms. METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) data of 39 SCZ, 43 BD-I, and 61 healthy controls from the Consortium for Neuropsychiatric Phenomics dataset were examined. The cerebellum was parcellated into ten functional networks, and seed-based FC was calculated for each cerebellar system. Principal component analyses were used to reduce the dimensionality of the diagnosis-related FC and cognitive variables. Multiple regression analyses were used to assess the relationship between FC and cognitive and clinical data. RESULTS: We observed decreased cerebellar FC with the frontal, temporal, occipital, and thalamic areas in individuals with SCZ, and a more widespread decrease in cerebellar FC in individuals with BD-I, involving the frontal, cingulate, parietal, temporal, occipital, and thalamic regions. SCZ had increased within-cerebellum and cerebellar frontal FC compared to BD-I. In BD-I, memory and verbal learning performances, which were higher compared to SCZ, showed a greater interaction with cerebellar FC patterns. Additionally, patterns of increased cortico-cerebellar FC were marginally associated with positive symptoms in patients. CONCLUSIONS: Our findings suggest that shared and distinct patterns of cortico-cerebellar dysconnectivity in SCZ and BD-I could underlie cognitive impairments and psychotic symptoms in these disorders.

Causal dynamics of sleep, circadian rhythm, and mood symptoms in patients with major depression and bipolar disorder: insights from longitudinal wearable device data.

BACKGROUND: Sleep and circadian rhythm disruptions are common in patients with mood disorders. The intricate relationship between these disruptions and mood has been investigated, but their causal dynamics remain unknown. METHODS: We analysed data from 139 patients (76 female, mean age = 23.5 ± 3.64 years) with mood disorders who participated in a prospective observational study in South Korea. The patients wore wearable devices to monitor sleep and engaged in smartphone-delivered ecological momentary assessment of mood symptoms. Using a mathematical model, we estimated their daily circadian phase based on sleep data. Subsequently, we obtained daily time series for sleep/circadian phase estimates and mood symptoms spanning >40,000 days. We analysed the causal relationship between the time series using transfer entropy, a non-linear causal inference method. FINDINGS: The transfer entropy analysis suggested causality from circadian phase disturbance to mood symptoms in both patients with MDD (n = 45) and BD type I (n = 35), as 66.7% and 85.7% of the patients with a large dataset (>600 days) showed causality, but not in patients with BD type II (n = 59). Surprisingly, no causal relationship was suggested between sleep phase disturbances and mood symptoms. INTERPRETATION: Our findings suggest that in patients with mood disorders, circadian phase disturbances directly precede mood symptoms. This underscores the potential of targeting circadian rhythms in digital medicine, such as sleep or light exposure interventions, to restore circadian phase and thereby manage mood disorders effectively. FUNDING: Institute for Basic Science, the Human Frontiers Science Program Organization, the National Research Foundation of Korea, and the Ministry of Health & Welfare of South Korea.