| Abstract | In this review, all papers relevant to the molecular genetics of bipolar disorder published from 2004 to the present (mid 2006) are reviewed, and major results on depression are summarized. Several candidate genes for schizophrenia may also be associated with bipolar disorder: G72, DISC1, NRG1, RGS4, NCAM1, DAO, GRM3, GRM4, GRIN2B, MLC1, SYNGR1, and SLC12A6. Of these, association with G72 may be most robust. However, G72 haplotypes and polymorphisms associated with bipolar disorder are not consistent with each other. The positional candidate approach showed an association between bipolar disorder and TRPM2 (21q22.3), GPR50 (Xq28), Citron (12q24), CHMP1.5 (18p11.2), GCHI (14q22-24), MLC1 (22q13), GABRA5 (15q11-q13), BCR (22q11), CUX2, FLJ32356 (12q23-q24), and NAPG (18p11). Studies that focused on mood disorder comorbid with somatic symptoms, suggested roles for the mitochondrial DNA (mtDNA) 3644 mutation and the POLG mutation. From gene expression analysis, PDLIM5, somatostatin, and the mtDNA 3243 mutation were found to be related to bipolar disorder. Whereas most previous positive findings were not supported by subsequent studies, DRD1 and IMPA2 have been implicated in follow-up studies. Several candidate genes in the circadian rhythm pathway, BmaL1, TIMELESS, and PERIOD3, are reported to be associated with bipolar disorder. Linkage studies show many new linkage loci. In depression, the previously reported positive finding of a gene-environmental interaction between HTTLPR (insertion/deletion polymorphism in the promoter of a serotonin transporter) and stress was not replicated. Although the role of the TPH2 mutation in depression had drawn attention previously, this has not been replicated either. Pharmacogenetic studies show a relationship between antidepressant response and HTR2A or FKBP5. New technologies for comprehensive genomic analysis have already been applied. HTTLPR and BDNF promoter polymorphisms are now found to be more complex than previously thought, and previous papers on these polymorphisms should be treated with caution. Finally, this report addresses some possible causes for the lack of replication in this field. |
| Abstract | We have previously reported evidence that variation at GABA(A) receptor genes is associated with susceptibility to bipolar disorder with schizophrenia-like psychotic features (Research Diagnostic Criteria (RDC) schizoaffective disorder, bipolar type) with gene-wide significance at GABRB1, GABRA4, GABRB3, GABRA5, and GABRR3. Here we provide suggestive evidence implicating a sixth member of the gene family, GABRR1 (gene-wide P?=?0.0058; experiment-wide corrected significance P?=?0.052). |
| Abstract | Alzheimer's disease (AD) and schizophrenia (SZ) are both accompanied by impaired learning and memory functions. This study aims to explore the expression profiles of learning or memory genes between AD and SZ. We downloaded 10 AD and 10 SZ datasets from GEO-NCBI for integrated analysis. These datasets were processed using RMA algorithm and a global renormalization for all studies. Then Empirical Bayes algorithm was used to find the differentially expressed genes between patients and controls. The results showed that most of the differentially expressed genes were related to AD whereas the gene expression profile was little affected in the SZ. Furthermore, in the aspects of the number of differentially expressed genes, the fold change and the brain region, there was a great difference in the expression of learning or memory related genes between AD and SZ. In AD, the CALB1, GABRA5, and TAC1 were significantly downregulated in whole brain, frontal lobe, temporal lobe, and hippocampus. However, in SZ, only two genes CRHBP and CX3CR1 were downregulated in hippocampus, and other brain regions were not affected. The effect of these genes on learning or memory impairment has been widely studied. It was suggested that these genes may play a crucial role in AD or SZ pathogenesis. The different gene expression patterns between AD and SZ on learning and memory functions in different brain regions revealed in our study may help to understand the different mechanism between two diseases. |