Mood disorders impose a significant burden on public health. It has been estimated that major depressive disorder and bipolar depression are the first and sixth leading causes of disability, accounting for nearly 15% of the total years lived with disability worldwide. Thus, there is considerable motivation to better understand the etiology of these disorders so that more rational and effective strategies for treating and/or preventing them may be developed. Family, twin and adoption studies clearly show that genetic factors play an important role in the etiology. However, because of the apparent complexity of the etiology, success in identifying the relevant susceptibility genes has been limited. Recent advances from the Human Genome Project and in genotyping technology have made it possible to interrogate the genome for disease causing variants in an unprecedented fashion. An increasing number of studies are taking advantage of these advances in order to carry out genetic studies in mood disorders. The challenge is now becoming how to synthesize and make sense of the flood of data that is being generated by these efforts. To help meet this challenge, we propose the following aims: 1) To carry out and integrate systematic meta-analyses of genetic studies of mood disorders that have been published in the peer review literature;the meta-analyses will encompass data from three different classes of genomic experiments including a) association studies of sequence variation, b) association studies of copy number variation, and c) gene expression studies;2) To develop a web-based bioinformatics resource, that we refer to as """"""""Metamoodics,"""""""" for presenting the results of the meta-analyses in the context of salient genomic annotation;and 3) To develop a computational tool within """"""""Metamoodics"""""""" for conducting gene set enrichment analyses of meta-analyzed data from the three classes of genomic experiments to test hypotheses about whether certain molecular genetics pathways are relevant to mood disorders, and to implement this tool to test whether the Wnt signaling pathway relates to susceptibility for bipolar disorder as has been suggested by prior work from our group. We plan to achieve these aims efficiently over a three year period by capitalizing on the intellectual and technical resources at our disposal. We are a multi-disciplinary team of psychiatrists, genetic epidemiologists, bioinformaticists and computer scientists that has been at the forefront of studying the genetics of mood disorders for over two decades. Our goal with this project is to create a central location where the scientific community can gather to explore the current state of knowledge about which genes may contribute to susceptibility to mood disorders in such a way that will help guide future research of the genome in the most fruitful directions. By achieving this goal, we will create a resource that should help to accelerate the pace of discovery for how genetic factors contribute to the etiology of mood disorders.
Mood disorders impose a significant burden on public health;therefore, it is important to understand their causes. This proposal seeks to advance research into the genetic causes by conducting systematic reviews of available gene association and expression studies in mood disorders and developing a web-based bioinformatics resource for integrating the results within the context of other genomic information. The web resource will provide a computational tool for analyzing the synthesized data to test the etiologic contribution of different molecular pathways, such as the Wnt signaling pathway.
|Seifuddin, Fayaz; Pirooznia, Mehdi; Judy, Jennifer T et al. (2013) Systematic review of genome-wide gene expression studies of bipolar disorder. BMC Psychiatry 13:213|
|Rosenberg, P B; Mielke, M M; Han, D et al. (2012) The association of psychotropic medication use with the cognitive, functional, and neuropsychiatric trajectory of Alzheimer's disease. Int J Geriatr Psychiatry 27:1248-57|
|Willour, V L; Seifuddin, F; Mahon, P B et al. (2012) A genome-wide association study of attempted suicide. Mol Psychiatry 17:433-44|
|Badner, J A; Koller, D; Foroud, T et al. (2012) Genome-wide linkage analysis of 972 bipolar pedigrees using single-nucleotide polymorphisms. Mol Psychiatry 17:818-26|
|Pirooznia, Mehdi; Wang, Tao; Avramopoulos, Dimitrios et al. (2012) SynaptomeDB: an ontology-based knowledgebase for synaptic genes. Bioinformatics 28:897-9|
|Belmonte Mahon, Pamela; Pirooznia, Mehdi; Goes, Fernando S et al. (2011) Genome-wide association analysis of age at onset and psychotic symptoms in bipolar disorder. Am J Med Genet B Neuropsychiatr Genet 156B:370-8|
|Psychiatric GWAS Consortium Bipolar Disorder Working Group (2011) Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4. Nat Genet 43:977-83|
|Mielke, M M; Zandi, P P; Shao, H et al. (2010) The 32-year relationship between cholesterol and dementia from midlife to late life. Neurology 75:1888-95|