Clinical significance and genetic determinants of novel imaging measures of emphysema distribution in 9,743 smokers

9,743 名吸烟者肺气肿分布的新型影像学测量的临床意义和遗传决定因素

• 批准号: 10425416
• 负责人: Adel El Boueiz
• 金额: $ 17.06万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-01 至 2023-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10425416
• 关键词: ACVR1B gene; Accounting; Advisory Committees; Affect; Airway Disease; Area; Automobile Driving; Bioinformatics; Biological Process; Chest; Chronic Obstructive Pulmonary Disease; Clinical; Clinical Trials; Clinical/Radiologic; Cohort Studies; Collection; Complex; Computing Methodologies; Critical Care; Data; Detection; Development; Disease; Disease Progression; Dyspnea; Environment; Evaluation; Exhibits; Funding; Generations; Genes; Genetic; Genetic Determinism; Genetic Polymorphism; Genomic approach; Genomics; Goals; Heterogeneity; Hospitals; Image; Investigation; Lobar; Lobe; Lung; Lung Volume Reductions; Machine Learning; Measures; Medical; Medical Genetics; Medical Research; Medicine; Mentors; Mentorship; Methods; Morbidity - disease rate; Nature; Outcome; Pathologic; Patients; Pattern; Persons; Phenotype; Physicians; Physiological; Positioning Attribute; Predictive Analytics; Procedures; Prognosis; Public Health; Pulmonary Emphysema; Pulmonary Function Test/Forced Expiratory Volume 1; Quantitative Trait Loci; Radiology Specialty; Records; Research; Research Personnel; Resources; Respiratory Disease; Science; Scientist; Smoker; Structure of parenchyma of lung; Subgroup; Technology; Testing; Texture; Therapeutic; Therapeutic Intervention; Tissues; Translations; United States; Variant; Visual; Walking; Woman; Work; X-Ray Computed Tomography; attenuation; base; biomedical informatics; career; career development; clinical practice; clinically relevant; clinically significant; cohort; comorbidity; data mining; disease heterogeneity; disease phenotype; disorder risk; disorder subtype; effective therapy; genetic architecture; genetic association; genetic epidemiology; genetic predictors; genetic variant; genome sequencing; genome-wide; genomic predictors; imaging biomarker; imaging genetics; improved; instructor; interest; machine learning method; machine learning model; machine learning prediction; medical schools; mortality; multidisciplinary; novel; personalized care; predicting response; predictive modeling; prognostic; pulmonary function; pulmonary vascular remodeling; quantitative imaging; radiological imaging; rare variant; research and development; respiratory; whole genome

PROJECT SUMMARY/ABSTRACT Candidate: Dr. Adel El Boueiz is a pulmonary and critical care physician-scientist completing a period of T32- funded support at the Channing Division of Network Medicine (CDNM) and Harvard Medical School (HMS). He received a Master's of Medical Science in Biomedical Informatics from HMS in May 2016. He will be promoted to Instructor of Medicine at the CDNM and HMS on July 1, 2017. His principal research interests are the genetic epidemiology of chronic obstructive pulmonary disease (COPD) and the translation of genomic discoveries into clinical practice and public health. His long-term goal is to be an independent investigator with expertise in imaging phenotyping, genomics, and predictive analytics of the regional heterogeneity of the various aspects of COPD (emphysema, airway disease, and pulmonary vascular remodeling). Environment: Dr. El Boueiz will continue to pursue his research and career development in the rich and multidisciplinary environment of the CDNM and the Brigham and Women's Hospital Applied Chest Imaging Lab (ACIL). He will be mentored by Drs. Edwin K. Silverman, Peter J. Castaldi, and Raúl San José Estépar, leaders in the field of COPD quantitative imaging, genetic epidemiology, and predictive analytics with excellent track records of mentoring young investigators towards independent research careers. His career development will also be overseen by an advisory committee with expertise related to key areas of his proposal. Research: COPD is a major cause of morbidity and mortality that is of increasing public health importance. COPD is a heterogeneous disease and this heterogeneity complicates the identification of the predictors of disease progression and consequently, the development of effective therapies. Emphysema distribution is an important COPD-related phenotype that emerged as a strong predictor of the response to lung volume reduction procedures. Despite the availability of advanced texture-based CT quantification methods, global threshold-based quantitative metrics have to date been the cornerstone for the radiological characterization of emphysema distribution with inability to differentiate centrilobular, panlobular, and paraseptal emphysema patterns. In this project, we will apply a texture-based CT quantification method to discover novel imaging biomarkers of the regional heterogeneity of centrilobular, panlobular, and paraseptal emphysema in a large cohort of well-characterized smokers and identify their genetic determinants using whole genome sequencing and integrative genomics analyses. The results will be considered for inclusion along with other rich phenotypic and imaging data in COPD disease progression machine learning predictive models. Relevance: Through improved radiographic phenotyping of emphysema distribution, better understanding of disease pathobiology, and more accurate prediction of disease progression, the proposed work will open new avenues of investigation for the development of personalized and improved COPD therapeutic strategies.

项目总结/摘要 候选人：阿德尔El Boueiz博士是一名肺科和重症监护医生兼科学家，完成了T32- 在网络医学的钱宁分部（CDNM）和哈佛医学院（HMS）的资助支持。他 于2016年5月获得HMS生物医学信息学医学科学硕士学位。合格者给予晋升 2017年7月1日在CDNM和HMS的医学讲师。他的主要研究兴趣是 慢性阻塞性肺疾病（COPD）的遗传流行病学和基因组翻译 临床实践和公共卫生的新发现。他的长期目标是成为一名独立调查员， 在成像表型，基因组学和预测分析的区域异质性的专业知识， COPD的各个方面（肺气肿、气道疾病和肺血管重塑）。 环境：El Boueiz博士将继续在富裕的国家从事研究和职业发展， CDNM和布里格姆妇女医院应用胸部成像实验室的多学科环境 （ACIL）。他将由Edwin K博士指导。Silverman，Peter J. Castaldi，and Raúl San José Estépar， COPD定量成像、遗传流行病学和预测分析领域的领导者， 指导年轻研究人员走向独立研究生涯的记录。他的职业发展 还将由一个咨询委员会监督，该委员会具有与其建议的关键领域相关的专业知识。 研究：COPD是发病率和死亡率的主要原因，其对公共卫生的重要性日益增加。 COPD是一种异质性疾病，这种异质性使COPD的预测因子的识别变得复杂。 疾病进展，从而开发有效的治疗方法。肺气肿分布是一个 重要的COPD相关表型，作为肺容量反应的强预测因子出现 还原程序。尽管有先进的基于纹理的CT量化方法， 迄今为止，基于阈值的定量度量已经成为放射学表征的基石， 肺气肿分布，无法区分小叶中心、全小叶和间隔旁肺气肿 模式.在这个项目中，我们将应用基于纹理的CT量化方法来发现新的成像 在一个大的肺组织中， 一组特征明确的吸烟者，并使用全基因组测序确定其遗传决定因素 和综合基因组学分析。将考虑将结果沿着纳入其他丰富的表型 和成像数据在COPD疾病进展机器学习预测模型中的应用。 相关性：通过改善肺气肿分布的放射学表型， 疾病病理生物学，更准确地预测疾病进展，拟议的工作将开辟新的 研究途径，以开发个性化和改进的COPD治疗策略。

项目成果

Epigenome-wide DNA methylation association study of circulating IgE levels identifies novel targets for asthma.

• DOI: 10.1016/j.ebiom.2023.104758
• 发表时间: 2023-09
• 期刊: EBIOMEDICINE
• 影响因子: 11.1
• 作者: Recto, Kathryn;Kachroo, Priyadarshini;Huan, Tianxiao;Van Den Berg, David;Lee, Gha Young;Bui, Helena;Lee, Dong Heon;Gereige, Jessica;Yao, Chen;Hwang, Shih-Jen;Joehanes, Roby;O'Cornor, George T.;Levy, Daniel;DeMeo, Dawn L.
• 通讯作者: DeMeo, Dawn L.

Deep Learning Integration of Chest Computed Tomography Imaging and Gene Expression Identifies Novel Aspects of COPD.

胸部计算机断层扫描成像和基因表达的深度学习集成确定了慢性阻塞性肺病的新方面。

• DOI: 10.15326/jcopdf.2023.0399
• 发表时间: 2023
• 期刊: Chronic obstructive pulmonary diseases (Miami, Fla.)
• 作者: Chen,Junxiang;Xu,Zhonghui;Sun,Li;Yu,Ke;Hersh,CraigP;Boueiz,Adel;Hokanson,JohnE;Sciurba,FrankC;Silverman,EdwinK;Castaldi,PeterJ;Batmanghelich,Kayhan
• 通讯作者: Batmanghelich,Kayhan

Improved prediction of smoking status via isoform-aware RNA-seq deep learning models.

• DOI: 10.1371/journal.pcbi.1009433
• 发表时间: 2021-10
• 期刊: PLoS computational biology
• 影响因子: 4.3
• 作者: Wang Z;Masoomi A;Xu Z;Boueiz A;Lee S;Zhao T;Bowler R;Cho M;Silverman EK;Hersh C;Dy J;Castaldi PJ
• 通讯作者: Castaldi PJ

Clustering-based COPD subtypes have distinct longitudinal outcomes and multi-omics biomarkers.

• DOI: 10.1136/bmjresp-2021-001182
• 发表时间: 2022-08
• 期刊: BMJ open respiratory research
• 影响因子: 4.1