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      Candidate genes, pathways and mechanisms for bipolar (manic-depressive) and related disorders: an expanded convergent functional genomics approach.

      Molecular Psychiatry
      Animals, Antimanic Agents, therapeutic use, Bayes Theorem, Bipolar Disorder, chemically induced, drug therapy, genetics, metabolism, Brain, Central Nervous System Stimulants, Disease Models, Animal, Dopamine and cAMP-Regulated Phosphoprotein 32, Enkephalins, drug effects, Gene Expression Profiling, Genetic Linkage, Genetic Predisposition to Disease, Genetic Testing, methods, Genomics, Humans, Male, Methamphetamine, Mice, Mice, Inbred C57BL, Microarray Analysis, Nerve Tissue Proteins, Pharmacogenetics, Phosphoproteins, Protein Precursors, Substance P, Tachykinins, Valproic Acid

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          Abstract

          Identifying genes for bipolar mood disorders through classic genetics has proven difficult. Here, we present a comprehensive convergent approach that translationally integrates brain gene expression data from a relevant pharmacogenomic mouse model (involving treatments with a stimulant--methamphetamine, and a mood stabilizer--valproate), with human data (linkage loci from human genetic studies, changes in postmortem brains from patients), as a bayesian strategy of crossvalidating findings. Topping the list of candidate genes, we have DARPP-32 (dopamine- and cAMP-regulated phosphoprotein of 32 kDa) located at 17q12, PENK (preproenkephalin) located at 8q12.1, and TAC1 (tachykinin 1, substance P) located at 7q21.3. These data suggest that more primitive molecular mechanisms involved in pleasure and pain may have been recruited by evolution to play a role in higher mental functions such as mood. The analysis also revealed other high-probability candidates genes (neurogenesis, neurotrophic, neurotransmitter, signal transduction, circadian, synaptic, and myelin related), pathways and mechanisms of likely importance in pathophysiology.

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          A neuroimaging study examined the neural correlates of social exclusion and tested the hypothesis that the brain bases of social pain are similar to those of physical pain. Participants were scanned while playing a virtual ball-tossing game in which they were ultimately excluded. Paralleling results from physical pain studies, the anterior cingulate cortex (ACC) was more active during exclusion than during inclusion and correlated positively with self-reported distress. Right ventral prefrontal cortex (RVPFC) was active during exclusion and correlated negatively with self-reported distress. ACC changes mediated the RVPFC-distress correlation, suggesting that RVPFC regulates the distress of social exclusion by disrupting ACC activity.
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              Bayesian Theory

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