Original Article | Published:

Transcriptional regulation of neurodevelopmental and metabolic pathways by NPAS3

Molecular Psychiatry volume 17, pages 267279 (2012) | Download Citation


The basic helix-loop-helix PAS (Per, Arnt, Sim) domain transcription factor gene NPAS3 is a replicated genetic risk factor for psychiatric disorders. A knockout (KO) mouse model exhibits behavioral and adult neurogenesis deficits consistent with human illness. To define the location and mechanism of NPAS3 etiopathology, we combined immunofluorescent, transcriptomic and metabonomic approaches. Intense Npas3 immunoreactivity was observed in the hippocampal subgranular zone—the site of adult neurogenesis—but was restricted to maturing, rather than proliferating, neuronal precursor cells. Microarray analysis of a HEK293 cell line over-expressing NPAS3 showed that transcriptional targets varied according to circadian rhythm context and C-terminal deletion. The most highly up-regulated NPAS3 target gene, VGF, encodes secretory peptides with established roles in neurogenesis, depression and schizophrenia. VGF was just one of many NPAS3 target genes also regulated by the SOX family of transcription factors, suggesting an overlap in neurodevelopmental function. The parallel repression of multiple glycolysis genes by NPAS3 reveals a second role in the regulation of glucose metabolism. Comparison of wild-type and Npas3 KO metabolite composition using high-resolution mass spectrometry confirmed these transcriptional findings. KO brain tissue contained significantly altered levels of NAD+, glycolysis metabolites (such as dihydroxyacetone phosphate and fructose-1,6-bisphosphate), pentose phosphate pathway components and Kreb's cycle intermediates (succinate and α-ketoglutarate). The dual neurodevelopmental and metabolic aspects of NPAS3 activity described here increase our understanding of mental illness etiology, and may provide a mechanism for innate and medication-induced susceptibility to diabetes commonly reported in psychiatric patients.


Schizophrenia and bipolar disorder are common, lifelong psychiatric illnesses affecting mood, perception and cognition. A strong genetic contribution to these conditions is indicated by family and epidemiological studies.

A role for the NPAS3 gene in psychiatric illness risk was suggested through the study of a mother and daughter diagnosed with schizophrenia and mild learning disability who carried a chromosomal abnormality disrupting the gene.1, 2 Subsequent gene-specific and genome-wide case–control association studies have linked single nucleotide polymorphisms at the NPAS3 locus with increased risk of schizophrenia,3, 4 bipolar disorder3, 4, 5 and major depression.4 Three common NPAS3 exonic variants have also been recently associated with increased risk of schizophrenia.6 Genetic variation at the NPAS3 locus has also been linked with response to treatment with the antipsychotic drug, iloperidone.7

NPAS3 encodes a member of the bHLH-PAS (basic helix-loop-helix—Per, Arnt, Sim) domain transcription factor family that form functional heterodimers.8, 9 Npas3 knockout (KO) mice display neuroanatomical, memory and behavioral phenotypes typical of a model of human psychiatric disorders.10, 11 They also exhibit a deficit in adult hippocampal neurogenesis12—a potential cellular pathology of schizophrenia and depression.13, 14 Importantly, a novel compound acting on mitochondria, P7C3, reverses the neurogenesis, neuroanatomical, electrophysiological and behavioral phenotypes of the Npas3 KO.15

Here, we report results from parallel experimental approaches designed to identify the function of NPAS3 in health and mental illness. The hippocampal neurogenesis deficit associated with Npas3 deletion suggested that NPAS3 might directly regulate the developmental pathway associated with new neuron production and maturation and we describe an immunofluorescence study to determine NPAS3's spatio-temporal contribution to this process.

As a transcription factor, NPAS3 is particularly amenable to a transcriptomics approach because observed expression changes are likely to represent direct activity rather than secondary or homeostatic reactions. We employ an in vitro system; over-expression of full-length (FLNPAS3) and artificially truncated (ΔNPAS3) forms of NPAS3 in the human embryonic kidney cell line, HEK293, followed by microarray analysis not to model psychiatric illness but rather to efficiently identify target genes. We compare NPAS3 targets with those of a known family of neurodevelopmental regulators, the SOX family of transcription factors.16, 17, 18 We also describe an immunofluorescence study to determine NPAS3's spatio-temporal contribution to hippocampal neurogenesis. The observation that the related NPAS2 protein acts as a functional equivalent of the CLOCK circadian regulator in certain brain regions19 prompted us to examine NPAS3 targets in cells stimulated to commence synchronous circadian cycling. Finally, we assess the biological relevance of the in vitro microarray data to the in vivo pathologies in the Npas3 KO mouse. This was achieved by high-resolution mass spectrometry-based metabonomic comparison of wild-type and mutant brain tissue.

Our findings indicate that NPAS3 contributes to both neurodevelopmental transcription factor networks and the regulation of brain glucose metabolism.

Materials and methods


Immunofluorescence of frozen brain sections was carried out as previously described.20 Antibodies against Npas3, Gfap, Dcx and Nestin were all obtained from Santa Cruz Biotechnology (Santa Cruz, CA, USA). 1:400 donkey secondary antibodies against goat or rabbit IgG, conjugated to Alexa Fluor 594 were applied for red fluorescence, or to Alexa Fluor 488 or FITC for green fluorescence (Invitrogen Life Technologies, Paisley, UK). Sections were mounted with Prolong antifade reagent with DAPI (4′,6-diamidino-2-phenylindole) nuclear stain (Invitrogen).

NPAS3 and SOX expression constructs and standard/circadian cell culture

The full-length NPAS3 open reading frame (acc. NM_001164749) was cloned into a TET-inducible expression plasmid (pT-REx-DEST30; Invitrogen) using a restriction digest, Gateway (Invitrogen) cloning linker ligation and the BP/LR reactions (Invitrogen). The truncated form, ΔNPAS3, was generated by cleavage and removal of sequence between internal and multiple cloning site XhoI sites thus deleting the second PAS domain and the putative transactivation domain. Plasmids were stably integrated into HEK293 [T-REx-293] cells (Invitrogen), using Geneticin and Blasticidin. HEK293 cells were maintained in Dulbecco's Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum (‘standard culture conditions’).

SOX expression constructs were generously gifted by Chuanju Liu (SOX5/SOX6/SOX9) and Fabien Murisier/Friedrich Beerman (SOX10). SOX11 was cloned from human cDNA as described in Li et al. (submitted for publication, Acta Neuropsychiatr). All SOX microarray experiments were carried out as transient transfections of HEK293 cells using Optimem/Lipofectamine 2000/plasmid DNA (Invitrogen) incubation for 6 h followed by 24 h in standard culture conditions.

For circadian induction, cells were maintained in DMEM alone for 36 h. At the zero hour time point, the cell medium was replaced with DMEM supplemented with 50% horse serum plus tetracycline in order to induce circadian cycling/NPAS3 over-expression.21, 22 At +2 h, cells were washed with DMEM and then incubated with the same plus tetracycline for the remaining period of the experiment. At either +12 or +24 h, cells were removed, washed and frozen.

Illumina microarray analysis and data normalization

For baseline and circadian NPAS3 over-expression experiments, parental HEK293 [T-REx-293] cells were used as negative controls. Samples (n=2) were assessed for FLNPAS3 over-expression, ΔNPAS3 over-expression and parental negative controls. In the SOX microarray studies, DNA-free Lipofectamine2000 transfections (n=4) were used as shared negative controls compared with transfections with each of the SOX expression constructs (n=3). RNA extraction (RNeasy kit, Qiagen, Crawley, UK) and synthesized microarray probes (Illumina® TotalPrep RNA Amplification Kit, Ambion, Austin, TX, USA) were quantified and quality checked using an Agilent (Santa Clara, CA, USA) Bioanalyzer. An Illumina (San Diego, CA, USA) Beadstation platform was used in conjunction with Sentrix® HumanRef-8 v2 chips (24 500 gene transcripts) to detect gene expression profiles. This work was carried out in the Wellcome Trust Clinical Research Facility at the Western General Hospital, Edinburgh. Microarray data analysis was carried out using BRB-ArrayTools 3.8.0 freeware (Biometric Research Branch, National Cancer Institute, NIH, Bethesda, MA, USA). Regulated genes were categorized using IPA (Ingenuity Pathway Analysis) and GeneCodis2 for over-representation of particular gene ontologies or biological processes. ProSim Ternary Diagram freeware (http://www.prosim.net/en/resources/download.html) was used to visualize normalized/de-transformed microarray expression data.

Confirmation by QPCR

Oligo-dT-primed cDNA synthesis of microarray sample RNA was performed (Roche, Welwyn Garden City, UK) followed by triplicate QPCR with SYBR green QPCR Master Mix (Invitrogen) and a real-time QPCR machine (Bio-Rad, Hemel Hempstead, UK). For relative quantification of mRNA expression, geometric means were calculated using the comparative double delta method. Primers used in QPCR are included in Supplementary Table 9. The housekeeping gene (18sRNA) was selected as the endogenous references in this QPCR studies.

Dual luciferase assay

5′ human VGF sequence (2029 kb), containing promoter, exon1, intron1 and part of exon2, was amplified by PCR and cloned into digested pGL3 reporter vectors. HEK293 and SHSY-5Y cell samples were collected at 24 h after transfection. The activities of Firefly luciferase (expressed from all pGL3 reporter vectors) and Renilla luciferase (expressed from co-transfected pRL-TK vector) were measured sequentially from each sample by using the Dual luciferase reporter (DLR TM) Assay System with the Plate-reader (Synergy HT, BioTek, Potton, UK). For each sample, the Firefly luciferase activity was normalized by the Renilla luciferase activity and then compared with the mean value of control samples. Dual luciferase assay results were statistically analyzed using SigmaPlot© (Bruxton, Seattle, WA, USA). One-way analysis of variance test was used to compare the VGF promoter activity of different cells among treatment groups.


Extraction of polar metabolites from brain tissue homogenates for liquid chromatography–mass spectrometry (LC–MS) analysis

The deleted mouse Npas3 locus (on a 129S6/SvEvTac background) was backcrossed with mice from the C57BL/6J strain such that, at the stage of metabonomic analysis, the mice were on average 62.5% C57BL/6J. Sagitally dissected half-brains from homozygote Npas3 KO (n=4) and wild-type (n=4) littermates were snap frozen in isopentane and stored at −80 °C. A two-step metabolite extraction method using methanol, water and chloroform as extraction solvents produced a biphasic solution comprising polar and non-polar fractions.23 Only the polar fractions were analyzed in this study. In all, 200 μl of collected polar extract was added to 600 μl of 1:1 acetonitrile:water. Samples were diluted to combat salt interference and to prevent ion suppression. Samples were filtered using Acrodisc 13 mm syringe filters with 0.2 μm nylon membrane (Sigma Aldrich, Gillingham, UK) before LC–MS analysis.

LC–MS analysis of polar metabolites

Analysis was carried out using a Finnigan LTQ-Orbitrap fitted with a Surveyor HPLC pump (Thermo Fisher, Hemel Hempstead, UK) using 30 000 resolution. The software program XCalibur (version 2.0, Thermo Fisher, Hemel Hempstead, UK) was used to acquire the LC–MS data. Analyses were carried out in positive and negative modes over mass range of 60–1000 m/z. The capillary temperature was set at 250 °C and in positive ionization mode the ion spray voltage was 4.5 kV, the capillary voltage 30 V and the tube lens voltage was 105 V. In negative ionization mode, the ion spray voltage was −4.5 kV, the capillary voltage was −25 V, the tube lens voltage was −95.0 V. The sheath and auxiliary gas flow rates were 45 and 15, respectively (manufacturer units). A ZIC-HILIC column (5 μm, 150 × 4.6 mm2; HiChrom, Reading, UK) was used with a binary gradient. Solvent A was 0.1% v/v formic acid in HPLC water and B was 0.1% formic acid in acetonitrile. A flow rate of 0.3 ml per minute was used and injection volume was 10 μl. The gradient program used was 80% B at 0 min to 50% B at 12 min to 20% B at 28 min to 80% B at 37 min with total run time of 45 min. The instrument was externally calibrated before analysis and internally calibrated using lock masses at m/z 83.06037 and m/z 195.08625. Samples were analyzed sequentially and the vial tray temperature was set at a constant temperature of 4 °C. Raw XCalibur data files from wild-type and Npas3 KO samples were processed using Sieve™ version 1.2 (Thermo Fisher).


Npas3 expression in the dentate gyrus supports its role in neurogenesis

We observed the strongest NPAS3 immunofluorescence originating in the subgranular zone of the dentate gyrus with immunopositive processes radiating into the granule cell layer proper (Figure 1j). Additional expression included nuclear distribution in ependymal cells and axo-dendritic staining adjacent to the cell soma in many cortical neurons. To define the stage of Npas3 action in newly forming neurons, we co-stained with antibodies against Nestin, Gfap and Dcx (Figures 1a–i). Only Dcx showed an overlapping expression pattern, indicating that Npas3 acts during neuronal maturation/differentiation.

Figure 1
Figure 1

Npas3 expression in the mouse dentate gyrus. Npas3, Gfap, Nestin and Dcx protein expression was compared using immunofluorescence on frozen mouse brain sections. Npas3 (green; a, d, g) expression was mainly non-nuclear and localized to the inner face/subgranular zone of the dentate gyrus. Anti-Gfap, -Nestin and -Dcx/Doublecortin antibodies (red; b, e, h) were used in co-immunofluorescence studies (c, f, i). Only Dcx co-localized with Npas3 in the subgranular zone (yellow; i). A composite image (j) shows Npas3 immunoreactivity throughout the hippocampus.

Identifying NPAS3 target genes in standard culture conditions

Unsupervised hierarchical clustering of gene expression profiles using centered correlation and average linkage showed reproducible transcriptional changes after FLNPAS3 or ΔNPAS3 over-expression (Supplementary Figure 1a). Using the SAM algorithm (Significance Analysis of Microarrays) with a 0.01 target proportion of false discoveries and 100 permutations, 3476 genes were found to discriminate between FLNPAS3 and control. In all, 282 genes showed 1.5-fold up-regulation by FLNPAS3, and 359 genes were similarly down-regulated (Tables 1a and 1b; Figure 2a). NPAS3, as a consequence of experimental over-expression, was the most up-regulated gene (62-fold) but was only detected in FLNPAS3 arrays as the chip's oligonucleotide probe is complementary to 3′ sequence absent in ΔNPAS3.

Table 1: The 51 genes most up-regulated (a) and 50 most down-regulated (b) by FLNPAS3 in standard cell culture conditions
Figure 2
Figure 2

Scatter plots of microarray data. Diagonals represent equal expression in compared experimental groups. Genes in red show at least 1.5-fold expression difference between the two conditions. Control and FLNPAS3-expressing HEK293 cell lines are shown in (a). FLNPAS3 displayed predominantly inhibitory activity at +12 h after circadian induction (b) but not at +24 h (c). Only the +12 h time point exposed functional differences between FLNPAS3 and ΔNPAS3 (d). The arrowed gene indicates exogenous FLNPAS3.

There was substantial correlation of target gene fold-change between FLNPAS3 and ΔNPAS3 cells in standard culture conditions, with linear regression r2 values of 0.59 (up-regulated genes) and 0.78 (down-regulated genes) (Supplementary Figures 1b and c). A similar C-terminal deletion of a related bHLH transcription factor, ARNT (HIF1 β), also largely preserved regulatory function.24 QPCR directed against four selected regulated genes, VGF, HK2, ENO2 and SOX11 confirmed the microarray findings (Supplementary Figure 2a).

NPAS3 and SOX transcription factors share target genes, including VGF

The up-regulated set of genes (Table 1a) was analyzed for over-representation of particular biological processes using online tool GeneCodis2.25 Thirty-six of the 282 up-regulated genes (corrected hypergeometric P-value=2.07 × 10−8) were categorized by the gene ontology term ‘transcription’ (GO:0006350), being either transcription factors or DNA-binding proteins with regulatory function (Supplementary Table 3). The most highly up-regulated NPAS3 target gene was VGF (2.92-fold), which encodes a group of processed and secreted neuropeptides including TLQP-21. The human VGF promoter containing an ‘E box’ motif (consensus bHLH transcription factor binding site), was cloned into the pGL3 luciferase reporter plasmid. In HEK293 cells, luciferase activity linked to the VGF promoter was significantly increased upon FLNPAS3 or ΔNPAS3 co-expression compared with control vector transfection (Supplementary Figure 4a). In SH-SY5Y neuroblastoma cells, luciferase activity was only significantly increased after FLNPAS3 over-expression (Supplementary Figure 4b).

We compared microarray data from NPAS3 over-expression with those from SOX transcription factor over-expression (Supplementary Tables 11a–d) in order to identify shared neurodevelopmental pathways. SOX genes within the same functional group (SOX5/6; SOX D group, SOX9/10; SOX E group) displayed closely related target profiles, confirming their established functional conservation and redundancy. NPAS3 target profiles closely matched those of SOX5/6 with the VGF gene being most highly up-regulated by all three transcription factors. NPAS3–SOX target overlaps are summarized in Supplementary Figure 5. Three members of the SOX family of transcription factors, SOX3, SOX11 and SOX12 involved in neuronal proliferation and differentiation17, 26 were confirmed as directly down-regulated by NPAS3 over-expression, further supporting interaction of NPAS3 with SOX transcriptional networks (Supplementary Figure 2b).

The set of NPAS3 down-regulated genes is enriched for metabolic function

NPAS3-repressed genes were queried using IPA (Supplementary Table 6), GeneCodis2 (Supplementary Table 3) and a search for genomic clustering of targets (Supplementary Figure 7). A cluster of chromosome 1 histone genes was down-regulated by NPAS3, suggesting global alterations in chromatin state—potentially relating to the neuronal differentiation process. IPA identified significant enrichment of the glycolysis/gluconeogenesis pathway in the gene set (16 genes, P=6.14 × 10−6). The glycolysis link (eight genes) was confirmed using GeneCodis2 (corrected hypergeometric P-value=5.21 × 10−7). Additionally, 21 genes participating in the ‘oxidation:reduction’ biological process (GO:0055114) were also significantly down-regulated (P=6.30 × 10−7). Visual inspection and comparison with published data27, 28, 29, 30 suggested that many genes were targets for the hypoxia response pathway (Table 1b). Glycolysis regulation can also be considered part of the hypoxia response. Together, these findings strongly suggest that, in addition to a neurodevelopmental role, NPAS3 regulates the anaerobic catabolism of glucose into pyruvate and, more generally, enzymatic redox processes.

An interaction between NPAS3 activity and the circadian rhythm

A circadian rhythm was successfully induced in HEK293 cells (Supplementary Figure 8) in order to monitor NPAS3 activity in the context of a daily rhythm. A comparison of +12 and +24 h microarray data in control cells (no NPAS3) identified a set of genes (Supplementary Table 11e), showing putative circadian regulation including FOS, FOSB, EGR1, EGR2, EGR3 and PER2, all with established circadian rhythm roles.

Circadian microarray data were visualized using ternary plots to highlight the influence of FLNPAS3, ΔNPAS3 and control conditions on individual gene expression levels. Expression data assessed comprised: 109 randomly selected genes, 200 genes showing normal circadian regulation in the parental control cells (100 increasing and 100 decreasing in expression between +12 and +24 h), 14 NPAS3-regulated glycolysis genes and histone gene clusters located on chromosomes 1 and 6. The randomly selected genes showed no deviation, indicating no systemic bias between the three experimental conditions (Figure 3a). The circadian rhythm impacted on FLNPAS3 and ΔNPAS3 activities in three ways. First, global NPAS3 activity was almost completely inhibitory at +12 h unlike +24 h (Figures 2b and c). Second, significant differences between FLNPAS3 and ΔNPAS3 activities on circadian (and glycolysis, to a lesser extent) target genes were exposed at +12 h (Figures 3b and c; Supplementary Table 11f) but not at +24 h. This was evident as reduced ΔNPAS3 potency at +12 h as highlighted in Figure 2d. Third, the sets of genes regulated by FL/ΔNPAS3 at +12 h (Supplementary Table S11g) and +24 h (Supplementary Table 11h) showed considerable differences; for example, substantial down-regulation of the chromosome 1 histone cluster was observed at +12 but not +24 h (Figure 3d).

Figure 3
Figure 3

Ternary plots illustrate influences on target gene expression. In all, 109 randomly selected genes are plotted for +12 h (green) and +24 h (red) time points (a). The absence of substantial deviation from the center indicates the no systemic bias between the three conditions—arrows indicate how inhibitory action of an experimental condition would directionally skew the distribution of points. In all, 100 up-regulated genes (circles) and 100 down-regulated genes (squares) between +12 and +24 h (b). The substantially deviating group (green squares) reflects strong and specific inhibition by ΔNPAS3 of the group of circadian genes down-regulated between +12 h and +24 h (Supplementary Tables 11e and f). FLNPAS3 and ΔNPAS3 inhibit the expression of 15 glycolysis genes at +24 h (c), although FLNPAS3 activity is much stronger than ΔNPAS3 at +12 h (see Figure 2d). Chromosome 1 histones (squares), but not chromosome 6 histones (circles), are substantially inhibited by both FLNPAS3 and ΔNPAS3 at +12 h but not +24 h (d).

Altered metabolite levels in brain tissue from Npas3 KO mice

To determine the in vivo actions of Npas3, we applied high-resolution mass spectrometry to homozygote KO and wild-type littermate brain tissue. In both positive ionization mode (Supplementary Tables 10a and b) and negative ionization mode (Supplementary Tables 10c and d), statistically significant changes in multiple polar metabolites were observed. Of particular note were the decreased levels of dihydroxyacetone phosphate/glycerone phosphate and octulose-1,8-bisphosphate in the KO (6 and 5% of wild-type levels, respectively) and increased levels of NAD+ (nicotinamide adenine dinucleotide) (Supplementary Figure 9), cystathione and dTDP-glucose/galactose (12.4-, 3.7- and 3.4-fold increases, respectively). Many perturbations relate to glycolysis, the tricarboxylic acid cycle and the urea cycle (Figure 4).

Figure 4
Figure 4

Glycolysis, tricarboxylic acid cycle and urea cycle showing coincident findings from transcriptomic and metabonomic analyses. The enzyme or regulatory protein is displayed in italics with transcript fold down-regulation upon NPAS3 over-expression (standard culture conditions) shown in brackets. Large black arrows indicate metabolite abundance changes in the knockout mouse brain.


Our experimental approaches produced novel and complementary insights into the normal and pathological activity of NPAS3. We concede that NPAS3 over-expression in the HEK293 cell line will not fully replicate the in vivo neuronal state. However, it may avoid confounding in vivo factors such as developmental/homeostatic compensation, cell-type complexity and variable physiological states. An additional reason for the approach taken was the failure to identify, using the Gene Expression Atlas at ArrayExpress (http://www.ebi.ac.uk/arrayexpress/), a laboratory neuronal cell line expressing endogenous NPAS3 at levels high enough to warrant a ‘knockdown’ strategy. We believe that certain observations suggest the in vitro data are biologically relevant. First, overlaps in SOX target gene sets reflect evolutionary relatedness. Second, many up-regulated NPAS3/SOX targets are neuronal specific. The laboratory that originally derived the cell line in 1973 has speculated that HEK293 cells might actually be of neuronal origin (http://www.fda.gov/ohrms/dockets/ac/01/transcripts/3750t1_01.pdf). Finally, exogenous transcription factors (including SOX genes) can show dominant effects on cell gene transcription.31

The target similarity between NPAS3 and SOX5/6 may reflect a shared role in neuronal differentiation.16, 32 The co-localization of Npas3 and Doublecortin indicates participation in a later, post-proliferative, stage of neuronal differentiation33 matching the observations of Pieper et al.15 This may refine our understanding of the link between adult neurogenesis pathologies and psychiatric illness.13

The top NPAS3, SOX5 and SOX6 up-regulated gene, VGF, encodes a precursor for a number of processed and secreted signaling peptides such as TLQP-21. VGF is a highly relevant target gene as it shows; regulation by circadian rhythm,34 involvement in metabolic control,35, 36 contribution to activity-related adult neurogenesis,37 and association with neurological diseases38, 39, 40, 41 including depression37, 42 and psychosis.43 Importantly, VGF and the related SCG2 protein (up-regulated here by SOX9/10/11) have been identified as discriminating cerebrospinal fluid biomarkers for schizophrenia and depression,43, 44 suggesting they may be reporting neurogenic pathologies.

NPAS3 regulates hypoxia/glycolysis pathways in a circadian-dependent context. NPAS2 has also been implicated in the redox-sensitive transcription of a metabolic gene, lactate dehydrogenase.45, 46 NPAS3 target gene sets show substantial differences between +12 and +24 h. Binding partner combinations (via the bHLH domains that mediate DNA binding and dimerization) may underlie the ‘cross-talk’ between NPAS3, circadian and hypoxia pathways. The observed ΔNPAS3-specific regulation of circadian targets at +12 h suggests that truncation permits abnormal interaction with circadian transcription factor partners present at +12 h but absent at +24 h. Altered circadian biology, manifest as sleep or metabolic dysfunction, has been described in individuals diagnosed with depression and bipolar disorder.47

Despite differing experimental paradigms and contrasting detection technologies, the in vitro and in vivo actions of NPAS3 converged at the glycolysis pathway. Perhaps most striking was the 12-fold increase in abundance of oxidized coenzyme NAD+ (nicotinamide adenine dinucleotide). This may reflect a slow-down in glycolysis (which generates the reduced form, NADH) or abnormally oxidative conditions in the cell. The decrease in fructose-1,6-bisphosphate and dihydroxyacetone phosphate concentrations provides direct evidence for glycolysis abnormalities in the KO. Both glucose and the glycogen synthesis intermediate, Uridine diphosphate-glucose/-galactose, were increased in KO brain, potentially indicating glycogen storage in response to ineffective glycolysis (Thymidine diphosphate-glucose/-galactose level changes might be similarly explained). Altered concentrations of sedoheptulose and octulose-1,8-bisphosphate may also indicate a compensatory impact on the pentose phosphate pathway initiating from glucose-6-phosphate. We speculate that the proposed mitochondrial deficit in Npas3 KO mice15 may cause the increases in Kreb's cycle intermediates 2-oxoglutarate/α-ketoglutaric acid and Succinate and, additionally, may inhibit the mitochondrial G3P (glycerol-3-phosphate) shuttle (Figure 4) contributing to the altered dihydroxyacetone phosphate, G3P and NAD+ concentrations.

These findings may have bearing on the metabolic syndrome that can occur in psychiatric patients. This is most frequently encountered as a medication side-effect.48, 49 However, schizophrenia has been repeatedly associated with an increased predisposition to metabolic dysfunction and type II diabetes in medication-naive individuals.50 Studies suggest that glycolytic dysfunction,51, 52 mitochondrial failure and oxidative stress53 may be innate metabolic pathologies in schizophrenia and bipolar disorder.

We have revealed unsuspected global metabolic deficits in the Npas3 KO brain. Other rodent models of psychiatric illness merit similar biochemical profiling as a means to uncover novel pathologies and opportunities for rational therapeutic development.


  1. 1.

    , , , . Disruption of the neuronal PAS3 gene in a family affected with schizophrenia. J Med Genet 2003; 40: 325–332.

  2. 2.

    , , , , . Disruption of a brain transcription factor, NPAS3, is associated with schizophrenia and learning disability. Am J Med Genet B Neuropsychiatr Genet 2005; 136: 26–32.

  3. 3.

    , , , , , et al. Interacting haplotypes at the NPAS3 locus alter risk of schizophrenia and bipolar disorder. Mol Psychiatry 2009; 14: 874–884.

  4. 4.

    , , , , , et al. Cross-disorder genomewide analysis of schizophrenia, bipolar disorder, and depression. Am J Psychiatry 2010; 167: 1254–1263.

  5. 5.

    , , , , , et al. Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder. Nat Genet 2008; 40: 1056–1058.

  6. 6.

    , , , , , . Association of NPAS3 exonic variation with schizophrenia. Schizophr Res 2010; 120: 143–149.

  7. 7.

    , , , , , et al. Association of the NPAS3 gene and five other loci with response to the antipsychotic iloperidone identified in a whole genome association study. Mol Psychiatry 2009; 14: 804–819.

  8. 8.

    , , , . Characterization of npas3, a novel basic helix-loop-helix PAS gene expressed in the developing mouse nervous system. Mech Dev 1999; 88: 237–241.

  9. 9.

    , . Signal transduction by heme-containing PAS-domain proteins. J Appl Physiol 2004; 96: 774–783.

  10. 10.

    , , , , , et al. Abnormal neurodevelopment, neurosignaling and behaviour in Npas3-deficient mice. Eur J Neurosci 2005; 22: 1265–1276.

  11. 11.

    , , , , , et al. Behavioral and regulatory abnormalities in mice deficient in the NPAS1 and NPAS3 transcription factors. Proc Natl Acad Sci USA 2004; 101: 13648–13653.

  12. 12.

    , , , , , et al. The neuronal PAS domain protein 3 transcription factor controls FGF-mediated adult hippocampal neurogenesis in mice. Proc Natl Acad Sci USA 2005; 102: 14052–14057.

  13. 13.

    , , . The contribution of failing adult hippocampal neurogenesis to psychiatric disorders. Curr Opin Psychiatry 2008; 21: 290–295.

  14. 14.

    , , , . Neurogenesis and schizophrenia: dividing neurons in a divided mind? Eur Arch Psychiatry Clin Neurosci 2007; 257: 290–299.

  15. 15.

    , , , , , et al. Discovery of a proneurogenic, neuroprotective chemical. Cell 2010; 142: 39–51.

  16. 16.

    , , , . SOX6 controls dorsal progenitor identity and interneuron diversity during neocortical development. Nat Neurosci 2009; 12: 1238–1247.

  17. 17.

    , , , . Expression of Sox11 in adult neurogenic niches suggests a stage-specific role in adult neurogenesis. Eur J Neurosci 2009; 29: 2103–2114.

  18. 18.

    . The SoxD transcription factors -- Sox5, Sox6, and Sox13 -- are key cell fate modulators. Int J Biochem Cell Biol 2010; 42: 429–432.

  19. 19.

    , , , . NPAS2: an analog of clock operative in the mammalian forebrain. Science 2001; 293: 506–509.

  20. 20.

    , , , , , et al. A cytogenetic abnormality and rare coding variants identify ABCA13 as a candidate gene in schizophrenia, bipolar disorder, and depression. Am J Hum Genet 2009; 85: 833–846.

  21. 21.

    , , . A serum shock induces circadian gene expression in mammalian tissue culture cells. Cell 1998; 93: 929–937.

  22. 22.

    , , , , , . Induction of circadian rhythm in cultured human mesenchymal stem cells by serum shock and cAMP analogs in vitro. Chronobiol Int 2009; 26: 242–257.

  23. 23.

    , , , . High-throughput tissue extraction protocol for NMR- and MS-based metabolomics. Anal Biochem 2008; 372: 204–212.

  24. 24.

    , , , . Identification of functional domains of the aryl hydrocarbon receptor nuclear translocator protein (ARNT). Mol Cell Biol 1994; 14: 6075–6086.

  25. 25.

    , , , , , et al. GeneCodis: interpreting gene lists through enrichment analysis and integration of diverse biological information. Nucleic Acids Res 2009; 37(Web Server issue): W317–W322.

  26. 26.

    , , . A method for rapid derivation and propagation of neural progenitors from human embryonic stem cells. J Neurosci Methods 2009; 184: 275–284.

  27. 27.

    , , , , , . An integrative genomics approach identifies hypoxia inducible factor-1 (HIF-1)-target genes that form the core response to hypoxia. Nucleic Acids Res 2009; 37: 4587–4602.

  28. 28.

    , , , , , et al. Gene expression programs in response to hypoxia: cell type specificity and prognostic significance in human cancers. PLoS Med 2006; 3: e47.

  29. 29.

    , , , , , et al. Up-regulation of gene expression by hypoxia is mediated predominantly by hypoxia-inducible factor 1 (HIF-1). J Pathol 2005; 206: 291–304.

  30. 30.

    , , , , , et al. Gene expression profiling reveals the profound upregulation of hypoxia-responsive genes in primary human astrocytes. Physiol Genomics 2006; 25: 435–449.

  31. 31.

    , . Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell 2006; 126: 663–676.

  32. 32.

    . The SoxD transcription factors—Sox5, Sox6, and Sox13—are key cell fate modulators. Int J Biochem Cell Biol 2010; 42: 429–432.

  33. 33.

    , , , , , . Transient expression of doublecortin during adult neurogenesis. J Comp Neurol 2003; 467: 1–10.

  34. 34.

    , . Gene expression in the brain across the sleep-waking cycle. Brain Res 2000; 885: 303–321.

  35. 35.

    , , , , . The role of the vgf gene and VGF-derived peptides in nutrition and metabolism. Genes Nutr 2007; 2: 169–180.

  36. 36.

    , . Role of VGF-derived peptides in the control of food intake, body weight and reproduction. Neuroendocrinology 2008; 88: 80–87.

  37. 37.

    , , , , , et al. The neuropeptide VGF produces antidepressant-like behavioral effects and enhances proliferation in the hippocampus. J Neurosci 2007; 27: 12156–12167.

  38. 38.

    , , , , , et al. Identification of potential CSF biomarkers in ALS. Neurology 2006; 66: 1218–1222.

  39. 39.

    , , , , , et al. Identification of novel biomarker candidates by differential peptidomics analysis of cerebrospinal fluid in Alzheimer's disease. Comb Chem High Throughput Screen 2005; 8: 801–806.

  40. 40.

    , , , , , et al. Identification of CSF biomarkers for frontotemporal dementia using SELDI-TOF. Exp Neurol 2005; 196: 273–281.

  41. 41.

    , , . Target identification for CNS diseases by transcriptional profiling. Neuropsychopharmacology 2009; 34: 18–54.

  42. 42.

    , . VGF, a new player in antidepressant action? Sci Signal 2008; 1: pe19.

  43. 43.

    , , , , , et al. Disease biomarkers in cerebrospinal fluid of patients with first-onset psychosis. PLoS Med 2006; 3: e428.

  44. 44.

    , , , , , et al. CSF metabolic and proteomic profiles in patients prodromal for psychosis. PLoS One 2007; 2: e756.

  45. 45.

    , , . Metabolism and the control of circadian rhythms. Annu Rev Biochem 2002; 71: 307–331.

  46. 46.

    , , , . Regulation of clock and NPAS2 DNA binding by the redox state of NAD cofactors. Science 2001; 293: 510–514.

  47. 47.

    , , , . The role of circadian clock genes in mental disorders. Dialogues Clin Neurosci 2007; 9: 333–342.

  48. 48.

    , , , , , et al. Antipsychotic treatment alters protein expression associated with presynaptic function and nervous system development in rat frontal cortex. J Proteome Res 2009; 8: 3284–3297.

  49. 49.

    , , . A microarray gene expression study of the molecular pharmacology of lithium carbonate on mouse brain mRNA to understand the neurobiology of mood stabilization and treatment of bipolar affective disorder. Pharmacogenet Genomics 2007; 17: 605–617.

  50. 50.

    , , , , , et al. Metabolic profile of antipsychotic-naive individuals with non-affective psychosis. Br J Psychiatry 2009; 194: 434–438.

  51. 51.

    , , , , , et al. Impaired glycolytic response in peripheral blood mononuclear cells of first-onset antipsychotic-naive schizophrenia patients. Mol Psychiatry 2010 (e-pub ahead of print).

  52. 52.

    , , , , , et al. Proteomic analysis of dorsolateral prefrontal cortex indicates the involvement of cytoskeleton, oligodendrocyte, energy metabolism and new potential markers in schizophrenia. J Psychiatr Res 2009; 43: 978–986.

  53. 53.

    , , , , . Redox dysregulation, neurodevelopment, and schizophrenia. Curr Opin Neurobiol 2009; 19: 220–230.

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We acknowledge Royal Society of Physicians in Edinburgh Sim Fellowship to BSP and a China Council Studentship to LS. SJC was supported in part by a NARSAD Young Investigator Award.

Author information

Author notes

    • L Sha
    •  & L MacIntyre

    Equal authorship status.

    • W J Muir



  1. Department of Medical Genetics, Institute for Genetics and Molecular Medicine, University of Edinburgh, Molecular Medicine Centre, Western General Hospital, Edinburgh, UK

    • L Sha
    • , J A Machell
    •  & D J Porteous
  2. Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, UK

    • L MacIntyre
    • , D G Watson
    •  & B S Pickard
  3. Pfizer, Pfizer Global Research and Development, Neuroscience Research Unit, Groton, CT, USA

    • M P Kelly
    •  & N J Brandon
  4. Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK

    • W J Muir
    •  & D H Blackwood
  5. Institute of Membrane and Systems Biology, University of Leeds, Leeds, UK

    • S J Clapcote
  6. CeNsUS—Centre for Neuroscience, University of Strathclyde, Glasgow, UK

    • B S Pickard


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Competing interests

The authors declare no conflict of interest.

Corresponding author

Correspondence to B S Pickard.

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