We have long advocated the use of gene expression datasets for understanding the mechanisms underlying complex human disease, and we believe that the unique nature of data in the Genotype-Tissue Expression (GTEx) program will allow us to enhance our understanding of the functionality for a large class of variants, will lead to great insight into the genetic components of common diseases, and will permit the exploration of several novel scientific hypotheses on both transcriptome biology and the genetic architecture of human disease. The opportunity to analyze the GTEx datasets motivates the development of new statistical methods, software and knowledge databases that will facilitate the use of these results by the larger scientific community for additional investigations. All proposed research is informed by our near-complete immersion in studies relating genotype to phenotype (and in developing methods for relating genotype to phenotype) for many different complex traits. Thus, our specific aims are: 1) to discover cross-tissue and tissue-specific regulatory variation and to use the resulting information for discovery of novel risk pathways, and for partitioning of disease heritability into components corresponding to different classes of functional variants;2) to test hypotheses that are finally feasible to investigate due to the uniqe design of the GTEx program, including the role of gender and other environmental exposures on regulatory variation, and the role of loss of function and missense variants in transcription;and 3) to use systems and network approaches for a better understanding of the organization of gene expression across tissues. All software and the databases developed through this project will be made publicly available immediately.

Public Health Relevance

Understanding the genetic architecture of complex human traits, including that of common diseases, can be greatly enhanced by a better understanding of the role of genetic variation in the inter- and intra-tissue expression variability. The unique structure of the Genotype-Tissue Expression (GTEx) data will allow us to explore novel scientific hypotheses, and motivates development of new statistical methods and knowledge databases. Our project will lead to a partitioning of disease variability into components corresponding to different classes of functional variants, will allow users to query results of transcriptome association studies in all GTEx tissues, and to use this information to discover novel genes and pathways for complex phenotypes.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH101820-02
Application #
8706982
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Addington, Anjene M
Project Start
2013-08-01
Project End
2016-06-30
Budget Start
2014-07-17
Budget End
2015-06-30
Support Year
2
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of Chicago
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
City
Chicago
State
IL
Country
United States
Zip Code
60637
Gamazon, Eric R; Trendowski, Matthew R; Wen, Yujia et al. (2018) Gene and MicroRNA Perturbations of Cellular Response to Pemetrexed Implicate Biological Networks and Enable Imputation of Response in Lung Adenocarcinoma. Sci Rep 8:733
Zhang, Mingfeng; Lykke-Andersen, Soren; Zhu, Bin et al. (2018) Characterising cis-regulatory variation in the transcriptome of histologically normal and tumour-derived pancreatic tissues. Gut 67:521-533
Agrawal, A; Chou, Y-L; Carey, C E et al. (2018) Genome-wide association study identifies a novel locus for cannabis dependence. Mol Psychiatry 23:1293-1302
Gamazon, Eric R; Segrè, Ayellet V; van de Bunt, Martijn et al. (2018) Using an atlas of gene regulation across 44 human tissues to inform complex disease- and trait-associated variation. Nat Genet 50:956-967
Barbeira, Alvaro N; Dickinson, Scott P; Bonazzola, Rodrigo et al. (2018) Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics. Nat Commun 9:1825
Salisbury-Ruf, Christi T; Bertram, Clinton C; Vergeade, Aurelia et al. (2018) Bid maintains mitochondrial cristae structure and function and protects against cardiac disease in an integrative genomics study. Elife 7:
Hohman, Timothy J; Dumitrescu, Logan; Cox, Nancy J et al. (2017) Genetic resilience to amyloid related cognitive decline. Brain Imaging Behav 11:401-409
Dolan, M Eileen; El Charif, Omar; Wheeler, Heather E et al. (2017) Clinical and Genome-Wide Analysis of Cisplatin-Induced Peripheral Neuropathy in Survivors of Adult-Onset Cancer. Clin Cancer Res 23:5757-5768
Parsana, Princy; Amend, Sarah R; Hernandez, James et al. (2017) Identifying global expression patterns and key regulators in epithelial to mesenchymal transition through multi-study integration. BMC Cancer 17:447
Derks, E M; Zwinderman, A H; Gamazon, E R (2017) The Relation Between Inflation in Type-I and Type-II Error Rate and Population Divergence in Genome-Wide Association Analysis of Multi-Ethnic Populations. Behav Genet 47:360-368

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