PubMed · 8543550
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
S F Diaz. 1996. Mania associated with risperidone use.. https://pubmed.ncbi.nlm.nih.gov/8543550/
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
BACKGROUND: Current bipolar disorder (BD) therapies suffer from limited efficacy and adverse effects, necessitating mechanistically grounded targets. METHODS: We integrated BD genome-wide association study data (158,036 cases; 2,796,499 controls) with brain proteomics (ROSMAP and Banner dorsolateral prefrontal cortex, n = 376 and 152) to perform proteome-wide association studies (PWAS). Bayesian colocalization and summary-data-based Mendelian randomization (SMR) prioritized causal genes. Cell-type-specific transcriptomics validated dysregulation in iPSC-derived neurons, astrocytes, and postmortem hippocampus/prefrontal cortex. Weighted gene co-expression networks (WGCNAs), functional enrichment, and molecular docking assessed functional pathways and druggability. RESULTS: PWAS identified eight BD-associated genes (false discovery rate < 0.05), with DOC2A emerging as the top candidate. Colocalization (H4 > 0.8) and SMR supported a causal association of DOC2A with BD, with no pleiotropy (heterogeneity in dependent instruments P > 0.01); DOC2A expression decreased in BD across neurons (P = 4.26 × 10-2), astrocytes (P = 2.09 × 10-2), hippocampus (P = 9.80 × 10-3, t = -2.738), and prefrontal cortex (P = 1.44 × 10-2, t = -2.580); WGCNA positioned DOC2A as a key regulator (module membership/gene significance P < 0.05) of co-expression networks enriched for BD-associated processes including neurotransmitter secretion and postsynaptic actin cytoskeleton organization (P < 0.05); molecular docking revealed favorable-affinity binding (ΔG < -4 kcal/mol) between DOC2A and BD-related drugs and neuroprotective compounds. CONCLUSIONS: Our convergent multi-omics framework highlights DOC2A dysregulation as a key contributor to synaptic dysfunction in BD and nominates it as a promising therapeutic target. The demonstrated interaction with existing neuroactive compounds provides immediate translational avenues.
BACKGROUND: Bipolar disorder (BPD) is a kind of manic and depressive phase alternate episodes of serious mental illness, and it is correlated with well-documented cortical brain abnormalities. Emerging evidence supports that autophagy dysfunction in neuronal system contributes to pathophysiological changes in neurological disease. However, the role of autophagy in bipolar disorder has rarely been elucidated. This study aimed to identify the autophagy-related gene as a potential biomarker Correlated to immune infiltration in BPD. METHODS: The microarray dataset GSE23848 and autophagy-related genes (ARGs) were downloaded. Differentially expressed genes (DEGs) between normal and BPD samples were screened using the R software. Machine learning algorithms were performed to screen the significant candidate biomarker from autophagy-related differentially expressed genes (ARDEGs). The correlation between the screened ARDEGs and infiltrating immune cells was explored through correlation analysis. RESULTS: In this study, the autophagy pathway was abundantly enriched and activated in BPD, as indicated by Pathway enrichment analysis. We identified 16 ARDEGs in BPD compared to the normal group. A signature of 4 ARDEGs (ERN1, ATG3, CTSB, and EIF2AK3) was screened. ROC analysis showed that the above genes have good diagnostic performance. In addition, immune correlation analysis considered that the above four genes significantly correlated with immune cells in BPD. CONCLUSIONS: Autophagy - immune cell axis mediates pathophysiological changes in BPD. Four important ARDEGs are prospective to be potential biomarkers associated with immune infiltration in BPD and helpful for the prediction or diagnosis of BPD.
BACKGROUND: Current operational diagnostic systems have substantial limitations for lifetime diagnostic classification of bipolar spectrum disorders. Issues include: (1) It is difficult to operationalize the integration of diverse episodes of psychopathology, (2) Hierarchies lead to loss of information, (3) Boundaries between diagnostic categories are often arbitrary, (4) Boundaries between categories usually require a major element of subjective interpretation, (5) Available diagnostic categories are relatively unhelpful in distinguishing severity, (6) "Not Otherwise Specified (NOS)" categories are highly heterogeneous, (7) Subclinical cases are not accommodated usefully within the current diagnostic categories. This latter limitation is particularly pertinent in the context of the increasing evidence for the existence of a broader bipolar spectrum than has been acknowledged within existing classifications. METHOD: We have developed a numerical rating system, the Bipolar Affective Disorder Dimension Scale, BADDS, that can be used as an adjunct to conventional best-estimate lifetime diagnostic procedures. The scale definitions were informed by (a) the current concepts of mood syndrome recognized within DSMIV and ICD10, (b) the literature regarding severity of episodes, and (c) our own clinical experience. We undertook an iterative process in which we initially agreed scale definitions, piloted their use on sets of cases and made modifications to improve utility and reliability. RESULTS: BADDS has four dimensions, each rated as an integer on a 0 - 100 scale, that measure four key domains of lifetime psychopathology: Mania (M), Depression (D), Psychosis (P) and Incongruence (I). In our experience it is easy to learn, straightforward to use, has excellent inter-rater reliability and retains the key information required to make diagnoses according to DSMIV and ICD10. CONCLUSIONS: Use of BADDS as an adjunct to conventional categorical diagnosis provides a richer description of lifetime psychopathology that (a) can accommodate sub-clinical features, (b) discriminate between illness severity amongst individuals within a single conventional diagnostic category, and (c) demonstrate the similarity between the illness experience of individuals who have been classified into different disease categories but whose illnesses both fall near the boundaries between the two categories. BADDS may be useful for researchers and clinicians who are interested in description and classification of lifetime psychopathology of individuals with disorders lying on the bipolar spectrum.