A common gene-expression profile in BPD and SZ was found in this study. Moderate Q-PCR validation of genes dysregulated in both disorders suggests that this list is a reasonable starting point for evaluating a common gene expression profile in another cohort. Part of this list represents candidate genes that are brain enriched, which might contribute to common pathophysiologic mechanisms and perhaps respond to treatments that are developed in these critical pathways. Notably, some antipsychotics, antidepressants, and mood stabilizers have been shown to affect these pathways (21
). The estimates of lifetime antipsychotic exposure were significantly related to expression for seven of the top candidate genes in a direction consistent with the direction of dysregulation compared with control subjects. This suggests that some dysregulated genes might be targets of antipsychotic treatments. A drug or gene capable of initiating the cascade of changes seen for the 78 transcripts would represent a good candidate gene.
The shared vulnerability gene profile appeared for both SZ and BPD shows a far greater proportion of nonshared to shared genes. The shared genes formed a fraction, 78 genes, compared with 443 genes that were dysregulated in either BPD (198) or SZ (245). Notably only 4 or 5 genes were expected to overlap from combined ANCOVA analyses for BPD and SZ. This 17-fold enrichment of 78 dysregulated core genes indicates a common susceptibility gene-expression profile for both disorders, represents important alterations in response to medications administered to both groups (7
), or downstream events manifest during a chronic psychiatric illness. Although we are not certain about medications last taken near the time of death for each subject, we used lifetime fluphenazine equivalents to interpret additional analyses. Further animal studies to address the effects of medications on these gene transcripts that have importance in both BPD and SZ are required.
On the basis of bioinformatic research, AGXT2L1 likely interacts with SLC7A13 (solute carrier family 7, cationic amino acid transporter, y+ system) and OAT (ornithine aminotransferase). AGXT2L1 has a putative mitochondrial subcellular localization consistent with potential involvement in enzymatic amino acid catabolism of arginine, glutamate, histidine, glutamate, glutamine, and proline. A SAGE study of gene expression also showed the AGXT2L1 gene was expressed in only brain relevant libraries (CGAP libraries) confirming the Novartis SymAtlas query. Further experimental validation is necessary to demonstrate functions for this gene although it is upregulated by lithium treatment. It is interesting that a recent study of lithium treatment in mouse brain produced AGXT2L1 as the top candidate gene related to short-term lithium administration (26
) at a significance level of < 10−12
which passed the experimental FDR criteria.
SLC1A2 (EAAT2 or GLT, high-affinity glutamate transporter, predominantly astroglial) is a brain specific gene highly dysregulated. Alterations to the glutamatergic system in brain have been reported for expression alterations in psychiatric disorders (27
) although not unequivocally demonstrated in all brain regions studied. Caution regarding the specific isoform that is of pathogenetic importance has been raised because both EAAT2a and EAAT2b are alternatively spliced exons for the same gene SLC1A2 (NM_004171) (31
). Our primers were located at the 3′ end in exon 10, and we targeted EAAT2a in Q-PCR validation that is the predominant isoform in human brain (31
). However, SLC1A2 did not validate by Q-PCR perhaps due to targeting the wrong region of the gene and could be a false negative by Q-PCR. The SymAtlas results (20
) showed that the SLC1A2 gene is brain enriched, although SLC1A2 expression was shown in peripheral organs (32
). An SLC1A2 genotype study did show a positive association with schizophrenia in Japanese samples (33
). SLC1A2 merits further study as potential susceptibility factor in BPD and SZ.
Cell death and immune response were found to be significant in both the Ermine J and the Ingenuity Pathways analysis. A potential next step for these studies is in vivo and in vitro screening of compounds that would alter expression of genes (34
). An example of gene alterations found in both functional categories is ERBB2 a transmembrane tyrosine kinase receptor of the ErbB family. The ErbB family includes four members, the epidermal growth factor receptor (EGF-R, ERBB1, ERBB2, ERBB3, and ERBB4). ERBB2, ERBB3, and ERBB4 mRNA appears in both gray and white matter in primate brain (41
). Neuregulin binds to heterodimers composed of ERBB2 with either an ERBB3 or ERBB4 molecule (42
). Receptor-ligand interaction induces the heterodimerization of receptor monomers, which then activates intracellular signaling cascades involved in proliferation, migration, differentiation, and survival or apoptosis (42
). Neuregulin is an important schizophrenia/bipolar disorder susceptibility gene (43
). Additional references for some of the 78 gene relevant genes are contained in Table 7
in Supplement 1.
We have controlled for large obvious effects on gene expression due to gender, age, pH, postmortem interval (PMI), and time to refrigeration. The impact of pH sensitive genes was reduced in stringent analyses after controlling for pH by ANCOVA and removing low pH subjects. Other studies (e.g., 15
) have found that subjects with BPD or SZ have decreased mitochondrial-associated transcripts. Many authors of microarray studies acknowledge that pH will influence mitochondrial gene expression, and when the effect is strongly controlled, such as in our microarray study and others (7
), the magnitude of mitochondrial gene expression differences in SZ or BPD is markedly reduced. This same effect was seen in our study in which we found mitochondrial-related genes before ANCOVA, and after removing outlier chips and samples, there was a reduction in mitochondrial genes that were significant. Microarrays are sensitive to the effect of agonal-pH differences in samples. The SMRI Microarray cases have a significantly reduced pH compared with control subjects, although most cases are rapid deaths (49
). This latter observation might indicate that pH is part of the pathology in BPD and SZ. We find that after careful evaluation with ANCOVA and removal of outlier chips that mitochondrial-associated transcripts were not overrepresented in the SMRI Microarray DLPFC set. Furthermore, immune genes were significantly dysregulated in our study consistent with another recent microarray study (50
) in which pH was well-balanced in case and control subjects. Thus, animal models will certainly play a role in determining whether genes that are altered in pH sensitive pathways also convey behavioral-, immune-, and plasticity-related effects.
The current categories of bipolar disorder and schizophrenia share a common gene expression profile. This makes sense because both disorders often clinically present with prominent mood and psychotic symptoms (5
). A larger number of dysregulated genes are not shared across the disorders, but fold change direction generally followed similar trends in both disorders. Further work to fill in “explanatory gaps” in the common gene expression profiles of these psychiatric disorders is required at the functional level. The shared genes (Table 3
in Supplement 1) merit further consideration in future neurogenomic and cognitive studies of schizophrenia and bipolar disorder candidate genes.