Convergent Functional Genomics
“The increasing volume of information is just more opportunity to build better answers to questions. The more information you have, the better”- Larry Page, Google
Progress in understanding the genetic and neurobiological basis of neuropsychiatric disorders is derived from both human studies and animal-model studies. Until recently, the lack of concerted integration between the two approaches was hindering the pace of research and/or was a missed opportunity to accelerate our understanding of this complex and heterogeneous group of disorders.
Our research group has helped to overcome this "lost in translation" barrier by developing an approach called Convergent Functional Genomics (CFG). The approach integrates data from animal-model gene expression studies with data from human genetic linkage/association studies, as well as data obtained from human tissue (postmortem brain, blood).
CFG extracts actionable results from large, noisy and diverse datasets.
This Bayesian strategy for cross-validating findings extracts meaning from large datasets by prioritizing candidate genes, pathways, and mechanisms; which are then targeted by subsequent hypothesis-driven research. Top candidate genes, for which there are multiple independent lines of evidence, are less likely to be false positives. The network of lines of evidence for each gene is resilient, even if one or another of the nodes (lines of evidence) is less than optimal. In the end, the results speak for themselves in terms of the ability of our Convergent Functional Genomics approach to extract signal and prioritize findings, similar to a Google PageRank algorithm , from large and potentially noisy datasets. The CFG approach has been successfully applied to bipolar disorder, schizophrenia, alcoholism, and blood biomarker discovery.
Biomarkers
Biomarkers: concordant gene expression in brain and peripheral tissues such as blood, due to inherited genetic factors (eg. promoter regions, signal transduction modules) or external factors (medications, stress and other environmental effects).
Convergent Function Genomics in Action
Recently, the CFG approach was used to integrate in a comprehensive fashion genetic and gene expression evidence for bipolar disorder, resulting in the most complete model of bipolar disorder pathophysiology to date (see below).
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Le-Niculescu H, Patel SD, Bhat M, Kuczenski R, Faraone SV, Tsuang MT, McMahon FJ, Schork NJ, Nurnberger Jr JI, and Niculescu AB. Convergent Functional Genomics of Genome-Wide Association Data for Bipolar Disorder: Comprehensive Identification of Candidate Genes, Pathways and Mechanisms. American Journal of Medical Genetics Part B (Neuropsychiatric Genetics). 2009 Mar 5 150B(2):155-181
Clock Genes and Bipolar Disorder
Clock genes mediate the effect of environment on the levels of activity of an organism. They are like the conductor of an orchestra, turning on and off many other genes.
McGrath CL, Glatt SJ, Sklar P, Le-Niculescu H, Kuczenski R, Doyle AE, Biederman J, Mick E, Faraone SV, Niculescu AB, Tsuang MT. Evidence for genetic association of RORB with bipolar disorder. BMC Psychiatry. 2009 Nov 12;9:70.
Le-Niculescu H, McFarland MJ, Ogden CA, Balaraman Y, Patel S , Tan J, Rodd ZA, Paulus M, Geyer M, Edenberg HJ, Glatt SJ, Faraone SV, , Nurnberger JI, Kuczenski R, Tsuang MT and Niculescu AB. Phenomic, convergent functional genomic and biomarker studies in a stress-reactive genetic animal model of bipolar disorder and co-morbid alcoholism. American Journal of Medical Genetics Part B (Neuropsychiatric Genetics). 2008 Mar 5;147(2):134-166.
Convergent Functional Genomics Reveals the Genetic Architecture of Bipolar Disorder
Cumulative Combinatorics of Common Gene Variants and Environment (CC x CG x E) Model for Bipolar and other Complex Disorders(see below).
Patel SD, Le-Niculescu H, Koller DL, Green SD, Lahiri DK, McMahon F, Nurnberger JI, Niculescu AB. Coming to Grips With Complex Disorders: Genetic Risk Prediction in Bipolar Disorder Using Panels of Genes Identified Through Convergent Functional Genomics. American Journal of Medical Genetics Part B (Neuropsychiatric Genetics). 2010. (In Press)