Convergent functional genomics of anxiety disorders: translational identification of genes, biomarkers, pathways and mechanisms

Abstract

Anxiety disorders are prevalent and disabling yet understudied from a genetic standpoint, compared with other major psychiatric disorders such as bipolar disorder and schizophrenia. The fact that they are more common, diverse and perceived as embedded in normal life may explain this relative oversight. In addition, as for other psychiatric disorders, there are technical challenges related to the identification and validation of candidate genes and peripheral biomarkers. Human studies, particularly genetic ones, are susceptible to the issue of being underpowered, because of genetic heterogeneity, the effect of variable environmental exposure on gene expression, and difficulty of accrual of large, well phenotyped cohorts. Animal model gene expression studies, in a genetically homogeneous and experimentally tractable setting, can avoid artifacts and provide sensitivity of detection. Subsequent translational integration of the animal model datasets with human genetic and gene expression datasets can ensure cross-validatory power and specificity for illness. We have used a pharmacogenomic mouse model (involving treatments with an anxiogenic drug—yohimbine, and an anti-anxiety drug—diazepam) as a discovery engine for identification of anxiety candidate genes as well as potential blood biomarkers. Gene expression changes in key brain regions for anxiety (prefrontal cortex, amygdala and hippocampus) and blood were analyzed using a convergent functional genomics (CFG) approach, which integrates our new data with published human and animal model data, as a translational strategy of cross-matching and prioritizing findings. Our work identifies top candidate genes (such as FOS, GABBR1, NR4A2, DRD1, ADORA2A, QKI, RGS2, PTGDS, HSPA1B, DYNLL2, CCKBR and DBP), brain–blood biomarkers (such as FOS, QKI and HSPA1B), pathways (such as cAMP signaling) and mechanisms for anxiety disorders—notably signal transduction and reactivity to environment, with a prominent role for the hippocampus. Overall, this work complements our previous similar work (on bipolar mood disorders and schizophrenia) conducted over the last decade. It concludes our programmatic first pass mapping of the genomic landscape of the triad of major psychiatric disorder domains using CFG, and permitted us to uncover the significant genetic overlap between anxiety and these other major psychiatric disorders, notably the under-appreciated overlap with schizophrenia. PDE10A, TAC1 and other genes uncovered by our work provide a molecular basis for the frequently observed clinical co-morbidity and interdependence between anxiety and other major psychiatric disorders, and suggest schizo-anxiety as a possible new nosological domain.

Adenosinergic Regulation of Striatal Clock Gene Expression and Ethanol Intake During Constant Light

“…Of note, adult ADHD is linked with blunted Per2 expression (Baird et al, 2012). It is also interesting that the other clock genes with altered circadian profiles in ENT1 KO mice, Clock and Dbp, are associated with ADHD (Kissling et al, 2008;Roybal et al, 2007;Xu et al, 2010), bipolar disorder (Le-Niculescu et al, 2008;Lee et al, 2010;Shi et al, 2008;Soria et al, 2010), anxiety (Le-Niculescu et al, 2011a), and AUD (Le-Niculescu et al, 2011b;Le-Niculescu et al, 2008). Interestingly, ENT1 KO mice display mania-like behavior (Ruby et al, 2011) similar to Dbp KO mice (Le-Niculescu et al, 2008).…”

Expression profiling associates blood and brain glucocorticoid receptor signaling with trauma-related individual differences in both sexes

“…Two studies investigated differential gene expression in the amygdala during fear-conditioning based on previous experience of a homotypic (27) or heterotypic stressor (28). Gene expression was also investigated in blood and brain tissue of mice exposed to an anxiogenic vs. an anxiolytic drug using the convergent functional genomics approach (29). Another study examined withinbrain correlations of expression of mitochondrial and mitochondriarelated nuclear genes of rats exposed to inescapable stress (restraint stress with tail-shock) compared with unexposed CONs (30).…”

Blood–brain biomarkers for stress susceptibility

“…Although several showed an overlap with one or both of the other tissues, only nine factors (CREB1, FOXO3, JUN, MYC, MYCN, NFE2L2, NFKBIA, NR3C1, and TP53) were shared by all three, i.e., hippocampus, amygdala, and blood. Data generated by this study will undoubtedly complement other microarraybased studies that have also reported some of these genes (15)(16)(17).…”