Bipolar Disorder is a severe disease characterized by pathological mood swings from major depressive episodes to manic ones and vice versa. The biological underpinnings of Bipolar Disorder have yet to be defined. As a consequence, pharmacological treatments are suboptimal. In the present paper we test the hypothesis that the molecular pathways involved with the direct targets of lithium, hold significantly more genetic variations associated with BD. A molecular pathway approach finds its rationale in the polygenic nature of the disease. The pathways were tested in a sample of ∼ 7,000 patients and controls. Data are available from the public NIMH database. The definition of the pathways was conducted according to the National Cancer Institute (http://pid.nci.nih.gov/). As a result, 3 out of the 18 tested pathways related to lithium action resisted the permutation analysis and were found to be associated with BD. These pathways were related to Reelin, Integrins and Aurora. A pool of genes selected from the ones linked with the above pathways was further investigated in order to identify the fine molecular mechanics shared by our significant pathways and also their link with lithium mechanism of action. The data obtained point out to a possible involvement of microtubule-related mechanics.
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http://dx.doi.org/10.1016/j.jad.2015.10.016 | DOI Listing |
Neuropsychiatr Dis Treat
January 2025
Unit of Bipolar Disorder, Tianjin Anding Hospital, Tianjin, People's Republic of China.
Purpose: We aimed to verify the impact of functional remediation (FR) on serum brain-derived neurotrophic factor (BDNF) and tyrosine kinase receptor B (TrkB) levels, to explore the biomechanism of FR intervention in patients with euthymic bipolar disorder (BD).
Patients And Methods: This is a randomized controlled, 12-week intervention study with participants randomized into the FR group (n=39) and the treatment as usual group (TAU, n=42) at the 1∶1 ratio. 17-Hamilton Depression Rating Scale-17 (HDRS-17), Young Mania Rating Scale (YMRS), and Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) were used to assess affective symptoms and cognitive functioning both at baseline and week 12, respectively.
Front Psychiatry
January 2025
Center of Research on Psychological Disorders and Somatic Diseases (CoRPS), Department of Medical and Clinical Psychology, Tilburg University, Tilburg, Netherlands.
Introduction: Clinical staging aims to refine psychiatric diagnosis by describing mental disorders on a continuum of disorder progression, with the pragmatic goal of improved treatment planning and outcome prediction. The first systematic review on this topic, published a decade ago, included 78 papers, and identified separate staging models for schizophrenia, unipolar depression, bipolar disorder, panic disorder, substance use disorder, anorexia, and bulimia nervosa. The current review updates this review by including new proposals for staging models and by systematically reviewing research based upon full or partial staging models since 2012.
View Article and Find Full Text PDFMol Psychiatry
January 2025
Department of Psychiatry, University of Oxford, Oxford, UK.
Cognitive and neural mechanisms underlying bipolar disorder (BD) and its treatment are still poorly understood. Here we examined the role of adaptations in risk-taking using a reward-guided decision-making task. We recruited volunteers with high (n = 40) scores on the Mood Disorder Questionnaire, MDQ, suspected of high risk for bipolar disorder and those with low-risk scores (n = 37).
View Article and Find Full Text PDFBrain Stimul
January 2025
Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada. Electronic address:
PLoS One
January 2025
Department of Psychiatry, University of California San Diego, La Jolla, CA, United States of America.
Background: Bipolar Disorder (BD) is a complex disease. It is heterogeneous, both at the phenotypic and genetic level, although the extent and impact of this heterogeneity is not fully understood. One way to assess this heterogeneity is to look for patterns in the subphenotype data.
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