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The influence of genes on "positive valence systems" constructs: A systematic review
Jonathan L Hess1, Daniel M Kawaguchi1, Kayla E Wagner1,2
1Departmentof Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, New York.
Abstract:
In 2009, the U.S. National Institute of Mental Health (NIMH) proposed an approach toward the deconstruction of psychiatric nosology under the research domain criteria (RDoC) framework. The overarching goal of RDoC is to identify robust, objective measures of behavior, emotion, cognition, and other domains that are more closely related to neurobiology than are diagnoses. A preliminary framework has been constructed, which has connected molecules, genes, brain circuits, behaviors, and other elements to dimensional psychiatric constructs. Although the RDoC framework has salience in emerging studies, foundational literature that pre-dated this framework requires synthesis and translation to the evolving objectives and nomenclature of RDoC. Toward this end, we review the candidate-gene association, linkage, and genome-wide studies that have implicated a variety of loci and genetic polymorphisms in selected Positive Valence Systems (PVS) constructs. Our goal is to review supporting evidence to currently listed genes implicated in this domain and novel candidates. We systematically searched and reviewed literature based on keywords listed under the June, 2011, edition of the PVS matrix on the RDoC website (http://www.nimh.nih.gov/research-priorities/rdoc/positive-valence-systems-workshop-proceedings.shtml), which were supplemented with de novo keywords pertinent to the scope of our review. Several candidate genes linked to the PVS framework were identified from candidate-gene association studies. We also identified novel candidates with loose association to PVS traits from genome-wide studies. There is strong evidence suggesting that PVS constructs, as currently conceptualized under the RDoC initiative, index genetically influenced traits; however, future research, including genetic epidemiological, and psychometric analyses, must be performed.
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