The emotional and cognitive vulnerabilities that precede the development of bipolar disorder are poorly understood. The inferior frontal gyrus-a key cortical hub for the integration of cognitive and emotional processes-exhibits both structural and functional changes in bipolar disorder, and is also functionally impaired in unaffected first-degree relatives, showing diminished engagement during inhibition of threat-related emotional stimuli. We hypothesized that this functional impairment of the inferior frontal gyrus in those at genetic risk of bipolar disorder reflects the dysfunction of broader network dynamics underlying the coordination of emotion perception and cognitive control. To test this, we studied effective connectivity in functional magnetic resonance imaging data acquired from 41 first-degree relatives of patients with bipolar disorder, 45 matched healthy controls and 55 participants with established bipolar disorder. Dynamic causal modelling was used to model the neuronal interaction between key regions associated with fear perception (the anterior cingulate), inhibition (the left dorsolateral prefrontal cortex) and the region upon which these influences converge, namely the inferior frontal gyrus. Network models that embodied non-linear, hierarchical relationships were the most strongly supported by data from our healthy control and bipolar participants. We observed a marked difference in the hierarchical influence of the anterior cingulate on the effective connectivity from the dorsolateral prefrontal cortex to the inferior frontal gyrus that is unique to the at-risk cohort. Non-specific, non-hierarchical mechanisms appear to compensate for this network disturbance. We thus establish a specific network disturbance suggesting dysfunction in the processes that support hierarchical relationships between emotion and cognitive control in those at high genetic risk for bipolar disorder.
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http://dx.doi.org/10.1093/brain/awv261 | DOI Listing |
Eur Arch Psychiatry Clin Neurosci
December 2024
Department of Psychiatry, University of Muenster, Muenster, Germany.
Schizophrenia (SCZ), bipolar (BD) and major depression disorder (MDD) are severe psychiatric disorders that are challenging to treat, often leading to treatment resistance (TR). It is crucial to develop effective methods to identify and treat patients at risk of TR at an early stage in a personalized manner, considering their biological basis, their clinical and psychosocial characteristics. Effective translation of theoretical knowledge into clinical practice is essential for achieving this goal.
View Article and Find Full Text PDFCurr Issues Mol Biol
November 2024
Systems Biology Unit, Department of Experimental Biology, Faculty of Experimental Sciences, University of Jaén, 23071 Jaén, Spain.
Neurological disorders such as Autism Spectrum Disorder (ASD), Schizophrenia (SCH), Bipolar Disorder (BD), and Major Depressive Disorder (MDD) affect millions of people worldwide, yet their molecular mechanisms remain poorly understood. This study describes the application of the Comparative Analysis of Shapley values (CASh) to transcriptomic data from nine datasets associated with these complex disorders, demonstrating its effectiveness in identifying differentially expressed genes (DEGs). CASh, which combines Game Theory with Bootstrap resampling, offers a robust alternative to traditional statistical methods by assessing the contribution of each gene in the broader context of the complete dataset.
View Article and Find Full Text PDFJMIR Ment Health
December 2024
Otsuka Pharmaceutical Development & Commercialization, Inc, 508 Carnegie Center Drive, Princeton, NJ, 08540, United States, 1 609 535 9035.
Background: Sleep-wake patterns are important behavioral biomarkers for patients with serious mental illness (SMI), providing insight into their well-being. The gold standard for monitoring sleep is polysomnography (PSG), which requires a sleep lab facility; however, advances in wearable sensor technology allow for real-world sleep-wake monitoring.
Objective: The goal of this study was to develop a PSG-validated sleep algorithm using accelerometer (ACC) and electrocardiogram (ECG) data from a wearable patch to accurately quantify sleep in a real-world setting.
Lancet Reg Health Eur
December 2024
Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
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J Mol Histol
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Faculty of Engineering, Department of Chemistry, Istanbul University- Cerrahpaşa, Avcilar, Istanbul, Türkiye.
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