PubMed · 8078955
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
K Lehmann. 1994. Endogenous lithium levels.. https://doi.org/10.1055/s-2007-1014293
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: More than 40 studies have been done on seasonal birth patterns for schizophrenia, but only two small studies have been done for DSM-III-R bipolar disorder and none for schizoaffective disorder. Two studies have also reported a significant relationship between schizophrenia births and stillbirths. METHODS: In the largest study to date, birth data from four states was obtained on 126,987 state psychiatric hospitals inpatients divided into 'process' schizophrenia (disorganized, catatonic, undifferentiated), paranoid schizophrenia, schizoaffective disorder, bipolar disorder and major depression. Time series analysis compared these births to all general births and to stillbirths. RESULTS: 'Process' schizophrenia, paranoid schizophrenia, schizoaffective disorder and bipolar disorder all had statistically significant seasonal excess births from December through March (p = 0.0000). The largest excess was 5.8% for bipolar disorder. Major depression had significant excess births from March through May. Time series analysis showed statistically significant coherences between major depression and bipolar disorder (0.995) and between schizoaffective disorder and both 'process' schizophrenia (0.977) and bipolar disorder (0.977). Unexpectedly, a significant coherence was also found between paranoid schizophrenia and bipolar disorder (0.972). Excess stillbirths were found for each month from January through June and a significant coherence was found between stillbirths and paranoid schizophrenia (0.998). CONCLUSIONS: This study demonstrates that DSM-III-R bipolar disorder and schizoaffective disorder both have an excess of winter births, similar to that found in schizophrenia. Time series analysis, however, suggests that the causes may not be identical. Major depression, by contrast, has an excess of spring births.