Neuroanatomically precise, genome-wide maps of transcript distributions are critical resources to complement genomic sequence data and to correlate functional and genetic brain architecture. Here we describe the generation and analysis of a transcriptional atlas of the adult human brain, comprising extensive histological analysis and comprehensive microarray profiling of ~900 neuroanatomically precise subdivisions in two individuals. Transcriptional regulation varies enormously by anatomical location, with different regions and their constituent cell types displaying robust molecular signatures that are highly conserved between individuals. Analysis of differential gene expression and gene co-expression relationships demonstrates that brain-wide variation strongly reflects the distributions of major cell classes such as neurons, oligodendrocytes, astrocytes and microglia. Local neighbourhood relationships between fine anatomical subdivisions are associated with discrete neuronal subtypes and genes involved with synaptic transmission. The neocortex displays a relatively homogeneous transcriptional pattern, but with distinct features associated selectively with primary sensorimotor cortices and with enriched frontal lobe expression. Notably, the spatial topography of the neocortex is strongly reflected in its molecular topography— the closer two cortical regions, the more similar their transcriptomes. This freely accessible online data resource forms a high-resolution transcriptional baseline for neurogenetic studies of normal and abnormal human brain function.

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.

Conventional antidepressants require 2–8 weeks for a full clinical response. In contrast, two rapidly acting antidepressant interventions, low-dose ketamine and sleep deprivation (SD) therapy, act within hours to robustly decrease depressive symptoms in a subgroup of major depressive disorder (MDD) patients. Evidence that MDD may be a circadian-related illness is based, in part, on a large set of clinical data showing that diurnal rhythmicity (sleep, temperature, mood and hormone secretion) is altered during depressive episodes. In a microarray study, we observed widespread changes in cyclic gene expression in six regions of postmortem brain tissue of depressed patients matched with controls for time-of-death (TOD). We screened 12 000 transcripts and observed that the core clock genes, essential for controlling virtually all rhythms in the body, showed robust 24-h sinusoidal expression patterns in six brain regions in control subjects. In MDD patients matched for TOD with controls, the expression patterns of the clock genes in brain were significantly dysregulated. Some of the most robust changes were seen in anterior cingulate (ACC). These findings suggest that in addition to structural abnormalities, lesion studies, and the large body of functional brain imaging studies reporting increased activation in the ACC of depressed patients who respond to a wide range of therapies, there may be a circadian dysregulation in clock gene expression in a subgroup of MDDs. Here, we review human, animal and neuronal cell culture data suggesting that both low-dose ketamine and SD can modulate circadian rhythms. We hypothesize that the rapid antidepressant actions of ketamine and SD may act, in part, to reset abnormal clock genes in MDD to restore and stabilize circadian rhythmicity. Conversely, clinical relapse may reflect a desynchronization of the clock, indicative of a reactivation of abnormal clock gene function. Future work could involve identifying specific small molecules capable of resetting and stabilizing clock genes to evaluate if they can rapidly relieve symptoms and sustain improvement.

BackgroundPsychiatric disorders are multigenic diseases with complex etiology that contribute significantly to human morbidity and mortality. Although clinically distinct, several disorders share many symptoms, suggesting common underlying molecular changes exist that may implicate important regulators of pathogenesis and provide new therapeutic targets.MethodsWe performed RNA sequencing on tissue from the anterior cingulate cortex, dorsolateral prefrontal cortex, and nucleus accumbens from three groups of 24 patients each diagnosed with schizophrenia, bipolar disorder, or major depressive disorder, and from 24 control subjects. We identified differentially expressed genes and validated the results in an independent cohort. Anterior cingulate cortex samples were also subjected to metabolomic analysis. ChIP-seq data were used to characterize binding of the transcription factor EGR1.ResultsWe compared molecular signatures across the three brain regions and disorders in the transcriptomes of post-mortem human brain samples. The most significant disease-related differences were in the anterior cingulate cortex of schizophrenia samples compared to controls. Transcriptional changes were assessed in an independent cohort, revealing the transcription factor EGR1 as significantly down-regulated in both cohorts and as a potential regulator of broader transcription changes observed in schizophrenia patients. Additionally, broad down-regulation of genes specific to neurons and concordant up-regulation of genes specific to astrocytes was observed in schizophrenia and bipolar disorder patients relative to controls. Metabolomic profiling identified disruption of GABA levels in schizophrenia patients.ConclusionsWe provide a comprehensive post-mortem transcriptome profile of three psychiatric disorders across three brain regions. We highlight a high-confidence set of independently validated genes differentially expressed between schizophrenia and control patients in the anterior cingulate cortex and integrate transcriptional changes with untargeted metabolite profiling.Electronic supplementary materialThe online version of this article (doi:10.1186/s13073-017-0458-5) contains supplementary material, which is available to authorized users.

Gene expression profiles of postmortem brain tissue represent important resources for understanding neuropsychiatric illnesses. The impact(s) of quality covariables on the analysis and results of gene expression studies are important questions. This paper addressed critical variables which might affect gene expression in two brain regions. Four broad groups of quality indicators in gene expression profiling studies (clinical, tissue, RNA, and microarray quality) were identified. These quality control indicators were significantly correlated, however one quality variable did not account for the total variance in microarray gene expression. The data showed that agonal factors and low pH correlated with decreased integrity of extracted RNA in two brain regions. These three parameters also modulated the significance of alterations in mitochondrial-related genes. The average F-ratio summaries across all transcripts showed that RNA degradation from the AffyRNAdeg program accounted for higher variation than all other quality factors. Taken together, these findings confirmed prior studies, which indicated that quality parameters including RNA integrity, agonal factors, and pH are related to differences in gene expression profiles in postmortem brain. Individual candidate genes can be evaluated with these quality parameters in post hoc analysis to help strengthen the relevance to psychiatric disorders. We find that clinical, tissue, RNA, and microarray quality are all useful variables for collection and consideration in study design, analysis, and interpretation of gene expression results in human postmortem studies.