Genome-wide expression profiling is a powerful tool for implicating novel gene ensembles in cellular mechanisms of health and disease. The most popular platform for genome-wide expression profiling is the Affymetrix GeneChip. However, its selection of probes relied on earlier genome and transcriptome annotation which is significantly different from current knowledge. The resultant informatics problems have a profound impact on analysis and interpretation the data. Here, we address these critical issues and offer a solution. We identified several classes of problems at the individual probe level in the existing annotation, under the assumption that current genome and transcriptome databases are more accurate than those used for GeneChip design. We then reorganized probes on more than a dozen popular GeneChips into gene-, transcript- and exon-specific probe sets in light of up-to-date genome, cDNA/EST clustering and single nucleotide polymorphism information. Comparing analysis results between the original and the redefined probe sets reveals ∼30–50% discrepancy in the genes previously identified as differentially expressed, regardless of analysis method. Our results demonstrate that the original Affymetrix probe set definitions are inaccurate, and many conclusions derived from past GeneChip analyses may be significantly flawed. It will be beneficial to re-analyze existing GeneChip data with updated probe set definitions.

Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17–29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn’s disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.

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We conducted a combined genome-wide association (GWAS) analysis of 7,481 individuals affected with bipolar disorder and 9,250 control individuals within the Psychiatric Genomewide Association Study Consortium Bipolar Disorder group (PGC-BD). We performed a replication study in which we tested 34 independent SNPs in 4,493 independent bipolar disorder cases and 42,542 independent controls and found strong evidence for replication. In the replication sample, 18 of 34 SNPs had P value < 0.05, and 31 of 34 SNPs had signals with the same direction of effect (P = 3.8 × 10−7). In the combined analysis of all 63,766 subjects (11,974 cases and 51,792 controls), genome-wide significant evidence for association was confirmed for CACNA1C and found for a novel gene ODZ4. In a combined analysis of non-overlapping schizophrenia and bipolar GWAS samples we observed strong evidence for association with SNPs in CACNA1C and in the region of NEK4/ITIH1,3,4. Pathway analysis identified a pathway comprised of subunits of calcium channels enriched in the bipolar disorder association intervals. The strength of the replication data implies that increasing samples sizes in bipolar disorder will confirm many additional loci.

Highlights d Three groups of highly genetically-related disorders among 8 psychiatric disorders d Identified 109 pleiotropic loci affecting more than one disorder d Pleiotropic genes show heightened expression beginning in 2 nd prenatal trimester d Pleiotropic genes play prominent roles in neurodevelopmental processes Authors Cross-Disorder Group of the Psychiatric Genomics Consortium

The prefrontal cortex of schizophrenics shows reduced expression for GAD in the absence of significant cell loss. This may be brought about by an activity-dependent down-regulation associated with the functional hypoactivity of the DLPFC. The lack of significant alterations in cell numbers in the DLPFC and frontal lobe volume in schizophrenics also implies that overall cortical neuronal migration had not been compromised in development. Previous reports of altered neuronal distribution in the subcortical white matter of schizophrenic brains in comparison with that of controls may indicate disturbances of migration or programmed cell death in the cortical subplate, leading to altered connection formation in the overlying cortex of schizophrenics and activity-dependent down-regulation of neurotransmitter-related gene expression.

A cardinal symptom of major depressive disorder (MDD) is the disruption of circadian patterns. However, to date, there is no direct evidence of circadian clock dysregulation in the brains of patients who have MDD. Circadian rhythmicity of gene expression has been observed in animals and peripheral human tissues, but its presence and variability in the human brain were difficult to characterize. Here, we applied time-of-death analysis to gene expression data from high-quality postmortem brains, examining 24-h cyclic patterns in six cortical and limbic regions of 55 subjects with no history of psychiatric or neurological illnesses (“controls”) and 34 patients with MDD. Our dataset covered ∼12,000 transcripts in the dorsolateral prefrontal cortex, anterior cingulate cortex, hippocampus, amygdala, nucleus accumbens, and cerebellum. Several hundred transcripts in each region showed 24-h cyclic patterns in controls, and >100 transcripts exhibited consistent rhythmicity and phase synchrony across regions. Among the top-ranked rhythmic genes were the canonical clock genes BMAL1(ARNTL), PER1-2-3, NR1D1(REV-ERBa), DBP, BHLHE40 (DEC1) , and BHLHE41(DEC2) . The phasing of known circadian genes was consistent with data derived from other diurnal mammals. Cyclic patterns were much weaker in the brains of patients with MDD due to shifted peak timing and potentially disrupted phase relationships between individual circadian genes. This transcriptome-wide analysis of the human brain demonstrates a rhythmic rise and fall of gene expression in regions outside of the suprachiasmatic nucleus in control subjects. The description of its breakdown in MDD suggests potentially important molecular targets for treatment of mood disorders.

Abnormalities in L-glutamic acid (glutamate) and GABA signal transmission have been postulated to play a role in depression, but little is known about the underlying molecular determinants and neural mechanisms. Microarray analysis of specific areas of cerebral cortex from individuals who had suffered from major depressive disorder demonstrated significant down-regulation of SLC1A2 and SLC1A3, two key members of the glutamate͞neutral amino acid transporter protein family, SLC1. Similarly, expression of L-glutamate-ammonia ligase, the enzyme that converts glutamate to nontoxic glutamine was significantly decreased. Together, these changes could elevate levels of extracellular glutamate considerably, which is potentially neurotoxic and can affect the efficiency of glutamate signaling. The astroglial distribution of the two glutamate transporters and L-glutamate-ammonia ligase strongly links glia to the pathophysiology of depression and challenges the conventional notion that depression is solely a neuronal disorder. The same cortical areas displayed concomitant up-regulation of several glutamate and GABA A receptor subunits, of which GABA A␣1 and GABAA␤3 showed selectivity for individuals who had died by suicide, indicating their potential utility as biomarkers of suicidality. These findings point to previously undiscovered molecular underpinnings of the pathophysiology of major depression and offer potentially new pharmacological targets for treating depression.bipolar disorder ͉ GABAA receptors ͉ glutamate transporters ͉ major depression ͉ suicide C linical depression, the phenotypic hallmark of the two leading mood disorders [major depressive disorder (MDD) and bipolar affective disorder (BPD)], is the most common psychiatric illness. It affects Ϸ121 million people worldwide, with 10-20% of women and 5-12% of men estimated to experience a depressive episode in any 1-year period, and with evidence of suicidality in 15% of those affected (ref.