Defining new asthma phenotypes using high-dimensional data

使用高维数据定义新的哮喘表型

• 批准号: 2901112
• 金额: --
• 依托单位: London School of Hygiene & Tropical Medicine
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2901112
• 关键词: Defining; new; asthma; phenotypes; using

Asthma is a complex respiratory condition that affects millions worldwide and poses significant public health challenges. Traditional models, primarily centred on allergic/atopic mechanisms, have been insufficient in fully explaining the diverse manifestations and treatment responses of asthma. This project seeks to redefine asthma phenotypes (subtypes) by conducting an integrative analysis of high-dimensional data, which includes the sputum microbiome, epigenome, inflammatory markers, and clinical variables.This study will analyse data previously collected from 998 asthmatics and 356 non-asthmatics in Brazil, Ecuador, Uganda, New Zealand, and the UK as part of the WASP study. Investigating these diverse populations across both high-income and low- and middle-income countries is key to understanding the variability in asthma phenotypes, which are influenced by different socioeconomic contexts. The use of advanced statistical methods and multi-omics analysis is crucial to dissect the complex relationships between various biological factors and asthma, providing insights into the disease's heterogeneity.The project's primary components include:a. A systematic review to identify and describe asthma phenotypes using data from multiple sources.b. A scoping review focused on methods for integrating different types of data, emphasizing multidisciplinary research.c. An analysis of sputum epigenome, microbiome, and immunological and clinical data to discern variations related to asthma's presence, severity, and control.d. An exploration of the interrelationships among these variables to develop predictive models of asthma.e. The classification of asthma phenotypes using advanced statistical methods.f. The identification of variations in asthma phenotypes among different clinical subgroups.These objectives are designed to build upon existing knowledge and to assess current health data science techniques for managing complex biological and clinical data. This aligns with the project's commitment to interdisciplinary research and quantitative skills, reflecting key areas of focus for the MRC.A notable aspect of this project is its innovative methodology in classifying asthma phenotypes, blending established definitions with advanced classification systems. This approach, employing advanced statistical methods to integrate clinical and laboratory data, highlights the MRC's emphasis on interdisciplinary skill development and effectively bridges clinical and biomedical research areas. This methodology is vital for delving into the complexities of asthma and providing valuable insights.Expected outcomes of the project include a deeper understanding of asthma's causes, potentially opening new paths for prevention, diagnosis, and treatment strategies. The findings are expected to make a meaningful contribution to the global management of asthma, particularly benefiting LMICs where resources are more limited. Overall, the project represents a robust integration of clinical and biomedical research, enhancing our global understanding of asthma phenotypes.

哮喘是一种复杂的呼吸系统疾病，影响着全世界数百万人，并对公共卫生构成重大挑战。传统的模型，主要集中在过敏/特应性机制，已经不足以充分解释哮喘的各种表现和治疗反应。该项目旨在通过对包括痰微生物组、表观基因组、炎症标记物和临床变量在内的高维数据进行综合分析，重新定义哮喘表型（亚型）。作为WASP研究的一部分，本研究将分析先前从巴西、厄瓜多尔、乌干达、新西兰和英国收集的998名哮喘患者和356名非哮喘患者的数据。调查高收入国家和中低收入国家的这些不同人群是了解哮喘表型变异性的关键，哮喘表型受不同社会经济背景的影响。使用先进的统计方法和多组学分析对于解剖各种生物因素与哮喘之间的复杂关系至关重要，为疾病的异质性提供了见解。项目的主要组成部分包括：a。使用来自多个来源的数据来识别和描述哮喘表型的系统综述。范围审查侧重于整合不同类型数据的方法，强调多学科研究。对痰表观基因组、微生物组、免疫学和临床数据进行分析，以识别与哮喘存在、严重程度和控制相关的变异。探索这些变量之间的相互关系，以建立哮喘的预测模型。使用先进的统计方法对哮喘表型进行分类。不同临床亚群间哮喘表型变异的鉴定。这些目标旨在建立在现有知识的基础上，并评估管理复杂生物和临床数据的当前健康数据科学技术。这与该项目对跨学科研究和定量技能的承诺相一致，反映了MRC关注的关键领域。该项目的一个值得注意的方面是其分类哮喘表型的创新方法，将已建立的定义与先进的分类系统相结合。这种方法采用先进的统计方法来整合临床和实验室数据，突出了MRC对跨学科技能发展的重视，并有效地连接了临床和生物医学研究领域。这种方法对于深入研究哮喘的复杂性和提供有价值的见解至关重要。该项目的预期成果包括更深入地了解哮喘的病因，可能为预防、诊断和治疗策略开辟新的途径。这些发现有望对全球哮喘管理做出有意义的贡献，特别是使资源更有限的低收入国家受益。总体而言，该项目代表了临床和生物医学研究的有力整合，增强了我们对哮喘表型的全球理解。