Clinical Rounds With Nutrition Support Services

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68406/2/10.1177_011542659400900273.pd

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

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

Best behaviour? Ontologies and the formal description of animal behaviour.

The development of ontologies for describing animal behaviour has proved to be one of the most difficult of all scientific knowledge domains. Ranging from neurological processes to human emotions, the range and scope needed for such ontologies is highly challenging, but if data integration and computational tools such as automated reasoning are to be fully applied in this important area the underlying principles of these ontologies need to be better established and development needs detailed coordination. Whilst the state of scientific knowledge is always paramount in ontology and formal description framework design, this is a particular problem with neurobehavioural ontologies where our understanding of the relationship between behaviour and its underlying biophysical basis is currently in its infancy. In this commentary, we discuss some of the fundamental problems in designing and using behaviour ontologies, and present some of the best developed tools in this domain

Assessing behavioural and cognitive domains of autism spectrum disorders in rodents: current status and future perspectives

Item does not contain fulltextThe establishment of robust and replicable behavioural testing paradigms with translational value for psychiatric diseases is a major step forward in developing and testing etiology-directed treatment for these complex disorders. Based on the existing literature, we have generated an inventory of applied rodent behavioural testing paradigms relevant to autism spectrum disorders (ASD). This inventory focused on previously used paradigms that assess behavioural domains that are affected in ASD, such as social interaction, social communication, repetitive behaviours and behavioural inflexibility, cognition as well as anxiety behaviour. A wide range of behavioural testing paradigms for rodents were identified. However, the level of face and construct validity is highly variable. The predictive validity of these paradigms is unknown, as etiology-directed treatments for ASD are currently not on the market. To optimise these studies, future efforts should address aspects of reproducibility and take into account data about the neurodevelopmental underpinnings and trajectory of ASD. In addition, with the increasing knowledge of processes underlying ASD, such as sensory information processes and synaptic plasticity, phenotyping efforts should include multi-level automated analysis of, for example, representative task-related behavioural and electrophysiological read-outs