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Accepted (AM)Open Access (License Unspecified), Open
Journal article
Convergent Functional Genomics of bipolar disorder: From animal model pharmacogenomics to human genetics and biomarkers
Neuroscience and biobehavioral reviews, v 31(6), pp 897-903
2007
PMID: 17614132
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Progress in understanding the genetic and neurobiological basis of bipolar disorder(s) has come from both human studies and animal model studies. Until recently, the lack of concerted integration between the two approaches has been hindering the pace of discovery, or more exactly, constituted a missed opportunity to accelerate our understanding of this complex and heterogeneous group of disorders. Our group has helped overcome this “lost in translation” barrier by developing an approach called convergent functional genomics (CFG). The approach integrates animal model gene expression data with human genetic linkage/association data, as well as human tissue (postmortem brain, blood) data. This Bayesian strategy for cross-validating findings extracts meaning from large datasets, and prioritizes candidate genes, pathways and mechanisms for subsequent targeted, hypothesis-driven research. The CFG approach may also be particularly useful for identification of blood biomarkers of the illness.
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Details
- Title
- Convergent Functional Genomics of bipolar disorder: From animal model pharmacogenomics to human genetics and biomarkers
- Creators
- H. Le-Niculescu - Indiana UniversityM.J. McFarland - Indiana UniversityS. Mamidipalli - Indiana UniversityC.A. Ogden - Drexel UniversityR. Kuczenski - University of California, San DiegoS.M. Kurian - Scripps Research InstituteD.R. Salomon - Scripps Research InstituteMing T. Tsuang - University of California, San DiegoJ.I. Nurnberger Jr - Department of Psychiatry, Institute of Psychiatric Research, Indiana University School of Medicine, Indianapolis, IN, USAA.B. Niculescu - Indiana University
- Publication Details
- Neuroscience and biobehavioral reviews, v 31(6), pp 897-903
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Accelerated Career Entry Bachelor of Science in Nursing (BSN)
- Web of Science ID
- WOS:000249879100008
- Scopus ID
- 2-s2.0-34548060706
- Other Identifier
- 991019167463704721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Behavioral Sciences
- Neurosciences