组学数据整合识别慢性阻塞性肺病的疾病途径-猫眼课题宝

组学数据整合识别慢性阻塞性肺病的疾病途径

批准号：

9440672

负责人：

RUSSELL Paul BOWLER

金额：

$11.73万

依托单位：

UNIVERSITY OF COLORADO DENVER

依托单位国家：

美国

项目类别：

财政年份：

2017

资助国家：

美国

项目状态：

已结题

起止时间：

2017-09-15 至 2019-08-31

来源：

https://reporter.nih.gov/project-details/9440672

关键词：

Age Animal Model Biological Markers Biology Blood Cause of Death Characteristics Chronic Chronic Obstructive Airway Disease Classification Scheme Clinical Complement Complex Computers Data Data Set Development Diagnostic tests Disease Disease Pathway Disease Progression Disease stratification Distal Early treatment Foundations Funding Gene Expression Genetic Genomics Goals Grant Heart Diseases Hematological Disease Individual Investigation Knowledge Lead Lung diseases Machine Learning Methods Minority Molecular Molecular Profiling Molecular Target National Heart, Lung, and Blood Institute Pathway interactions Phase Phenotype Preparation Prevention Proteins Proteomics Public Health Pulmonary Emphysema Research Personnel Resources Respiratory physiology Risk Risk Factors Sample Size Sampling Scientist Severity of illness Sleep Disorders Smoker Smoking Source Supervision System Time United States United States National Institutes of Health Variant Work base clinical phenotype cohort computerized data processing data integration data mining data space disease phenotype disorder control disorder subtype genome wide association study high dimensionality human disease improved learning strategy metabolomics molecular subtypes multidisciplinary multiple omics new therapeutic target novel novel diagnostics novel therapeutic intervention outcome forecast response secondary analysis treatment strategy

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Project Summary Although chronic obstructive pulmonary disease (COPD) occurs predominantly in smokers, it is unknown why only a minority of smokers (~20-40%) develops chronic airflow limitation and/or destruction of distal airspaces (emphysema). Using several NIH and foundation grants, we have systematically generated genetic, genomics, proteomic, and metabolomics profiles from the NHLBI supported COPDGene cohort, which includes 10,300 current and former smokers age 45-80. This proposal will focus on integrating the omics data generated in the five-year followup (Phase II) of the COPDgene study to identify molecular subtypes of COPD across a broad range of blood profiles (Specific Aim 1). Biomarkers and pathways discriminating the molecular subtypes, in addition to other COPD phenotypes will then be identified (Specific Aim 2). These results will identify markers that are specific to smoking-related lung disease and can be used to develop novel diagnostic tests and therapies for early prevention and treatment of COPD.

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