An integrative approach to construct a regulatory network effected by TDZs

构建受 TDZ 影响的监管网络的综合方法

• 批准号: 8491522
• 负责人: Kyoung Jae Won
• 金额: $ 24万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-04-01 至 2015-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8491522
• 关键词: 2,4-thiazolidinedione; Adipose tissue; Affect; Algorithms; Antidiabetic Drugs; Binding; Binding Sites; Biological; Blood Circulation; Brown Fat; Burn injury; CCAAT-Enhancer-Binding Proteins; Calories; Chemicals; Classification; Clinical; Complex; Data; Data Analyses; Data Set; Development; Diabetes Mellitus; Disease; Distal; Drug Targeting; Enhancers; Environment; Exposure to; Fatty Acids; Fatty acid glycerol esters; Gene Expression; Gene Expression Regulation; Gene Targeting; Genes; Genetic Transcription; Genomics; Heating; Housing; Human; Machine Learning; Measures; Metabolic; Metabolic Diseases; Methodology; Methods; Modeling; Mus; Nature; Non-Insulin-Dependent Diabetes Mellitus; Nucleic Acid Regulatory Sequences; Obesity; Peroxisome Proliferator-Activated Receptors; Positioning Attribute; Prevention approach; Property; RNA; RXR; Regulation; Relative (related person); Risk; Risk Factors; Role; Running; Safety; Therapeutic; Thiazolidinediones; Time; Transcription factor genes; Transcriptional Regulation; Variant; adipokines; base; cardiovascular risk factor; cofactor; design; epigenome; gene interaction; genome-wide; in vivo; innovation; insulin sensitivity; meetings; novel; novel strategies; promoter; public health relevance; response; therapeutic target; time use; transcription factor

DESCRIPTION (provided by applicant): Obesity is a major risk factor for metabolic disorders. Obesit typically leads to accumulation of dysfunctional white adipose tissue (WAT), which further causes metabolic dysregulation with elevated circulation of fatty acids and increased secretion of proinflammatory adipokines. The discovery of fat burning brown adipose tissue (BAT) in humans has raised the exciting possibility of BAT may be targeted as a novel method to treat obesity and metablic diseases. Thiazolidinediones (TZDs) have a function to convert WAT into a "brownlike" state. Beside, TZDs have been used as a remedy for diabetes. But the clinical use of TZDs has been limited because of the safety concerns such as potential cardiovascular risks. Understanding the mechanism will identify efficacious but lower risk drug targets for the metabolic disorders. TZDs act by activatin PPAR? (peroxisome proliferator-activated receptor ?). However, our understanding about the targets f PPAR? and other cofactors is limited. To understand the role of TZDs and further study the browning effect, we propose to develop a novel algorithm to predict long-range promoter-enhancer interaction and construct a transcriptional network. To predict the long-range interactions, we will employ a machine learning algorithm that uses the enhancer RNA (eRNA) levels and gene transcription levels obtained from global run-on sequencing (GROseq) data. GROseq is a useful dataset to predict long-range interactions, as the eRNA levels highly correlate with the gene transcription level. Applyingthe obtained interactions to the known binding sites of TFs including PPAR?, GR, C/EBP, SMRT, and RXR, we will construct a comprehensive TF-gene network. The predicted interaction provides a useful environment to study gene regulation of TZDs. We will study how the distance, relative position, an the combination of multiple TF binding sites affect gene expression. We will also investigate the browning effects by TZDs by including BAT-specific TF binding data in the network. The transcriptioal rule of the BAT-specific binding information, in combination with other TFs, will be analyzed from he TF-gene network. As a whole, these studies use an innovative and creative approach to integrate various types of data to study gene regulation of TZDs. By reprocessing complex genomic datasets ino a comprehensive regulatory network, the proposed algorithm provides a unique view in analyzing the regulatory rules of the browning effect, which will greatly enhance our understanding about the gen regulation of TZDs and identify potential therapeutic targets for diabetes.

描述（由申请人提供）：肥胖是代谢紊乱的主要危险因素。肥胖通常会导致功能失调的白色脂肪组织（WAT）的积累，这进一步导致脂肪酸循环升高和促炎脂肪因子分泌增加的代谢失调。人类脂肪燃烧棕色脂肪组织（BAT）的发现，令人兴奋地提出了BAT作为治疗肥胖和代谢疾病的新方法的可能性。噻唑烷二酮（TZDs）具有将WAT转化为“棕色”状态的功能。此外，TZDs还被用作治疗糖尿病的药物。但tzd的临床应用一直受到限制，因为