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Timothy Syndrome (TS) is caused by very rare exonic mutations of the CACNA1C gene that produce delayed inactivation of Cav1.2 voltage-gated calcium channels during cellular action potentials, with greatly increased influx of calcium into the activated cells. The major clinical feature of this syndrome is a long QT interval that results in cardiac arrhythmias. However, TS also includes cognitive impairment, autism and major developmental delays in many of the patients. We observed the appearance of bipolar disorder (BD) in a patient with a previously reported case of TS, who is one of the very few patients to survive childhood. This is most interesting because the common single-nucleotide polymorphism (SNP) most highly associated with BD is rs1006737, which we show here is a cis -expression quantitative trait locus for CACNA1C in human cerebellum, and the risk allele (A) is associated with decreased expression. To combine the CACNA1C perturbations in the presence of BD in this patient and in patients with the common CACNA1C SNP risk allele, we would propose that either increase or decrease in calcium influx in excitable cells can be associated with BD. In treatment of BD with calcium channel blocking drugs, we would predict better response in patients without the risk allele, because they have increased CACNA1C expression.

Badner and Gershon (2001) presented a technique of meta-analysis of linkage data that could be applied to published genome scans. It combines the reported P-values of individual studies, after correcting each value for the size of the region containing a minimum P-value. Simulations demonstrated that the type I error rate was at least as low as that for a single genome scan and thus genome-wide significance criteria may be applied. Power to detect linkage was at least as high as the power of pooling the data from all the studies. We applied this method to all the published genome scans for bipolar disorder and schizophrenia. We found the strongest evidence for susceptibility loci on 13q (P < 6 x 10(-6)) and 22q (P < 1 x 10(-5)) for bipolar disorder, and on 8p (P < 2 x 10(-4)), 13q (P < 7 x 10(-5)), and 22q (P < 9 x 10(-5)) for schizophrenia.

Schizophrenia (SCZ) and bipolar disorder (BD) are highly heritable psychiatric disorders. Associated genetic and gene expression changes have been identified, but many have not been replicated and have unknown functions. We identified groups of genes whose expressions varied together, that is co-expression modules, then tested them for association with SCZ. Using weighted gene co-expression network analysis, we show that two modules were differentially expressed in patients versus controls. One, upregulated in cerebral cortex, was enriched with neuron differentiation and neuron development genes, as well as disease genome-wide association study genetic signals; the second, altered in cerebral cortex and cerebellum, was enriched with genes involved in neuron protection functions. The findings were preserved in five expression data sets, including sets from three brain regions, from a different microarray platform, and from BD patients. From those observations, we propose neuron differentiation and development pathways may be involved in etiologies of both SCZ and BD, and neuron protection function participates in pathological process of the diseases.

We conducted a systematic study of top susceptibility variants from a genome-wide association (GWA) study of bipolar disorder to gain insight into the functional consequences of genetic variation influencing disease risk. We report here the results of experiments to explore the effects of these susceptibility variants on DNA methylation and mRNA expression in human cerebellum samples. Among the top susceptibility variants, we identified an enrichment of cis regulatory loci on mRNA expression (eQTLs), and a significant excess of quantitative trait loci for DNA CpG methylation, hereafter referred to as methylation quantitative trait loci (mQTLs). Bipolar disorder susceptibility variants that cis regulate both cerebellar expression and methylation of the same gene are a very small proportion of bipolar disorder susceptibility variants. This finding suggests that mQTLs and eQTLs provide orthogonal ways of functionally annotating genetic variation within the context of studies of pathophysiology in brain. No lymphocyte mQTL enrichment was found, suggesting that mQTL enrichment was specific to the cerebellum, in contrast to eQTLs. Separately, we found that using mQTL information to restrict the number of single-nucleotide polymorphisms studied enhances our ability to detect a significant association. With this restriction a priori informed by the observed functional enrichment, we identified a significant association ( rs12618769 , P bonferroni <0.05) from two other GWA studies (TGen+GAIN; 2191 cases and 1434 controls) of bipolar disorder, which we replicated in an independent GWA study (WTCCC). Collectively, our findings highlight the importance of integrating functional annotation of genetic variants for gene expression and DNA methylation to advance the biological understanding of bipolar disorder.

The FKBP5 gene product forms part of a complex with the glucocorticoid receptor and can modulate cortisol-binding affinity. Variations in the gene have been associated with increased recurrence of depression and with rapid response to antidepressant treatment. We sought to determine whether common FKBP5 variants confer risk for bipolar disorder. We genotyped seven tag single-nucleotide polymorphisms (SNPs) in FKBP5, plus two SNPs previously associated with illness, in 317 families with 554 bipolar offspring, derived primarily from two studies. Single marker and haplotypic analyses were carried out with FBAT and EATDT employing the standard bipolar phenotype. Association analyses were also conducted using 11 disease-related variables as covariates. Under an additive genetic model, rs4713902 showed significant overtransmission of the major allele ( P =0.0001), which was consistent across the two sample sets ( P =0.004 and 0.006). rs7757037 showed evidence of association that was strongest under the dominant model ( P =0.001). This result was consistent across the two datasets ( P =0.017 and 0.019). The dominant model yielded modest evidence for association ( P <0.05) for three additional markers. Covariate-based analyses suggested that genetic variation within FKBP5 may influence attempted suicide and number of depressive episodes in bipolar subjects. Our results are consistent with the well-established relationship between the hypothalamic–pituitary–adrenal (HPA) axis, which mediates the stress response through regulation of cortisol, and mood disorders. Ongoing whole-genome association studies in bipolar disorder and major depression should further clarify the role of FKBP5 and other HPA genes in these illnesses.

An overall burden of rare structural genomic variants has not been reported in bipolar disorder (BD), although there have been reports of cases with microduplication and microdeletion. Here, we present a genome-wide copy number variant (CNV) survey of 1001 cases and 1034 controls using the Affymetrix single nucleotide polymorphism (SNP) 6.0 SNP and CNV platform. Singleton deletions (deletions that appear only once in the dataset) more than 100 kb in length are present in 16.2% of BD cases in contrast to 12.3% of controls (permutation P =0.007). This effect was more pronounced for age at onset of mania ⩽18 years old. Our results strongly suggest that BD can result from the effects of multiple rare structural variants.

Eye movement deviations, particularly deficits of initial sensorimotor processing and sustained pursuit maintenance, and antisaccade inhibition errors, are established intermediate phenotypes for psychotic disorders. We here studied eye movement measures of 849 participants from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study (schizophrenia N =230, schizoaffective disorder N =155, psychotic bipolar disorder N =206 and healthy controls N =258) as quantitative phenotypes in relation to genetic data, while controlling for genetically derived ancestry measures, age and sex. A mixed-modeling genome-wide association studies approach was used including ~4.4 million genotypes (PsychChip and 1000 Genomes imputation). Across participants, sensorimotor processing at pursuit initiation was significantly associated with a single nucleotide polymorphism in IPO8 (12p11.21, P =8 × 10 −11 ), whereas suggestive associations with sustained pursuit maintenance were identified with SNPs in SH3GL2 (9p22.2, P =3 × 10 −8 ). In participants of predominantly African ancestry, sensorimotor processing was also significantly associated with SNPs in PCDH12 (5q31.3, P =1.6 × 10 −10 ), and suggestive associations were observed with NRSN1 (6p22.3, P =5.4 × 10 − 8 ) and LMO7 (13q22.2, P =7.3x10 − 8 ), whereas antisaccade error rate was significantly associated with a non-coding region at chromosome 7 ( P =6.5 × 10 −9 ). Exploratory pathway analyses revealed associations with nervous system development and function for 40 top genes with sensorimotor processing and pursuit maintenance ( P =4.9 × 10 − 2 –9.8 × 10 −4 ). Our findings suggest novel patterns of genetic variation relevant for brain systems subserving eye movement control known to be impaired in psychotic disorders. They include genes involved in nuclear trafficking and gene silencing ( IPO8 ), fast axonal guidance and synaptic specificity ( PCDH12 ), transduction of nerve signals ( NRSN1 ), retinal degeneration ( LMO7 ), synaptic glutamate release ( SH3GL2 ), and broader nervous system development and function.

The G72/G30 gene complex is a candidate gene for schizophrenia and bipolar disorder. However, G72 and G30 mRNAs are expressed at very low levels in human brain, with only rare splicing forms observed. We report here G72/G30 expression profiles and behavioral changes in a G72/G30 transgenic mouse model. A human BAC clone containing the G72/G30 genomic region was used to establish the transgenic mouse model, on which gene expression studies, western blot and behavioral tests were performed. Relative to their minimal expression in humans, G72 and G30 mRNAs were highly expressed in the transgenic mice, and had a more complex splicing pattern. The highest G72 transcript levels were found in testis, followed by cerebral cortex, with very low or undetectable levels in other tissues. No LG72 (the long putative isoform of G72) protein was detected in the transgenic mice. Whole-genome expression profiling identified 361 genes differentially expressed in transgenic mice compared with wild-type, including genes previously implicated in neurological and psychological disorders. Relative to wild-type mice, the transgenic mice exhibited fewer stereotypic movements in the open field test, higher baseline startle responses in the course of the prepulse inhibition test, and lower hedonic responses in the sucrose preference test. The transcriptome profile changes and multiple mouse behavioral effects suggest that the G72 gene may play a role in modulating behaviors relevant to psychiatric disorders.

Although the concept of meta-analysis of multiple linkage scans of a genetic trait is not new, it can be difficult to apply to published data given the lack of consistency in the presentation of linkage results. In complex inheritance common diseases, there are many instances where one or two studies meet genome-wide criteria for significant or suggestive linkage but several other studies do not show even nominally significant results with the same region. One possibility for resolving differences between study results would be to combine an available result parameter of several studies. We describe here a method of regional meta-analysis, the multiple-scan probability (MSP), which can be used on published results. It combines the reported P-values of individual studies, after correcting each value for the size of the region containing a minimum P-value. Analyses of the power of MSP and of its type I error rates are presented. The type I error rate is at least as low as that for a single genome scan and thus genome-wide significance criteria may be applied. We also demonstrate appropriate criteria for this type of meta-analysis when the most significant study is included, and when that study is used to define a region of interest and then excluded. In our simulations, meta-analysis is at least as powerful as pooling data. Finally, we apply this method of meta-analysis to the evidence for linkage of autism susceptibility loci and demonstrate evidence for a susceptibility locus at 7q.