Genome-wide association studies (GWAS) have analyzed patterns of genomic variation in thousands of subjects and identified a large number of genes and chromosomal regions that are associated with various lung diseases. Since many of these genes remain poorly characterized, a major challenge facing pulmonary research is to systematically investigate their biological functions, the pathways in which they are involved, and the effects of genetic mutations on both. Fortunately, there is a large and growing body of genomic, transcriptomic, and epigenomic data that can be used to help shed light on gene function. Here we propose to leverage these data, using advanced computational methods to systematically characterize the functions of genes identified through GWAS studies for lung diseases with an emphasis on Chronic Obstructive Pulmonary Disease (COPD). Several research groups, including investigators involved in this proposed project, have conducted detailed genetic, genomic, and epigenomic studies on COPD and identified multiple genetic loci that are associated with disease. On the other hand, the multiple data-types generated from these studies have provided a uniquely exciting opportunity to systematically formulate testable hypotheses by using data-integration computational methods. To this end, we have assembled an interdisciplinary team including experts in GWAS, medicine, laboratory biology, and bioinformatics. We will apply recently developed systems biology-based approaches to integrate multiple data-types and construct gene regulatory networks (GRN) centered on GWAS candidates and from these, use the local network to predict functions of the uncharacterized genes. These new functional assignments will then be experimentally validated and, if necessary, further refined through additional rounds of network inference and experimental assessment. Finally, we will create a publicly accessible website to make the functional predictions and network models accessible to the pulmonary community.
Numerous studies have probed the genetics of lung disease, analyzing variation in the genome across thousands of subjects. These studies have identified many variants within genes and other genomic regions that are strongly associated with the disease state, but often these are of unknown functional significance. Here, using COPD as a model, we propose to use """"""""systems biology"""""""" methods to map these genes to pathways and to use these pathway-based associations to assign putative functions to these genes.
|Lao, Taotao; Jiang, Zhiqiang; Yun, Jeong et al. (2016) Hhip haploinsufficiency sensitizes mice to age-related emphysema. Proc Natl Acad Sci U S A 113:E4681-7|
|Jiang, Zhiqiang; Lao, Taotao; Qiu, Weiliang et al. (2016) A Chronic Obstructive Pulmonary Disease Susceptibility Gene, FAM13A, Regulates Protein Stability of Î²-Catenin. Am J Respir Crit Care Med 194:185-97|
|Chang, Yale; Glass, Kimberly; Liu, Yang-Yu et al. (2016) COPD subtypes identified by network-based clustering of blood gene expression. Genomics 107:51-8|
|Vargas, Ashley J; Quackenbush, John; Glass, Kimberly (2016) Diet-induced weight loss leads to a switch in gene regulatory network control in the rectal mucosa. Genomics 108:126-133|
|Silverman, Edwin K (2016) Risk of Lung Disease in PI MZ Heterozygotes. Current Status and Future Research Directions. Ann Am Thorac Soc 13 Suppl 4:S341-5|
|Malleshaiah, Mohan; Padi, Megha; RuÃ©, Pau et al. (2016) Nac1 Coordinates a Sub-network of Pluripotency Factors to Regulate Embryonic Stem Cell Differentiation. Cell Rep 14:1181-94|
|Cloonan, Suzanne M; Glass, Kimberly; Laucho-Contreras, Maria E et al. (2016) Mitochondrial iron chelation ameliorates cigarette smoke-induced bronchitis and emphysema in mice. Nat Med 22:163-74|
|Padi, Megha; Quackenbush, John (2015) Integrating transcriptional and protein interaction networks to prioritize condition-specific master regulators. BMC Syst Biol 9:80|
|Morrow, Jarrett D; Qiu, Weiliang; Chhabra, Divya et al. (2015) Identifying a gene expression signature of frequent COPD exacerbations in peripheral blood using network methods. BMC Med Genomics 8:1|
|Lao, Taotao; Glass, Kimberly; Qiu, Weiliang et al. (2015) Haploinsufficiency of Hedgehog interacting protein causes increased emphysema induced by cigarette smoke through network rewiring. Genome Med 7:12|
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