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Remote Exposome Monitoring for Skin Diseases through Digital Health Devices and Home-Based Multiomics

Remote Exposome Monitoring for Skin Diseases through Digital Health Devices and Home-Based Multiomics
通过数字健康设备和家庭多组学对皮肤病进行远程暴露监测
批准号:
10871108
负责人:
Wilson Liao
金额:
$44.41万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-09-18 至 2025-08-31

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中文摘要
翻译
项目摘要 麻烦,定义为衡量个人的所有暴露以及这些暴露如何与 在许多免疫介导的炎症性皮肤病中起着关键作用。测量 随着时间的推移而烦恼,并使用复杂的读数来了解其对人类健康的影响,例如- 组学分析是未来临床和转化研究的关键优先事项。然而,其中一个主要障碍是, 进行这种纵向的麻烦的研究是他们经常依赖于亲自的临床研究访问。 亲自研究访问,通常需要耗时前往学术医疗中心和缺席 从工作中,可以显着限制研究的地理,种族和社会经济代表性 参与者这些亲自访问通常也每隔几个月发生一次,限制了时间分辨率。 可以测量的麻烦数据。这一建议侧重于创新战略的实施 用于远程、基于家庭的麻烦监测和组学测量。圆满完成这项工作 将为未来研究该问题的合作网络提供宝贵的资源。
英文摘要
Project Summary The exposome, defined as the measure of all exposures for an individual and how those exposures relate to an individual's health, plays a key role in many immune-mediated inflammatory skin diseases. Measuring the exposome over time and understanding its effect on human health using sophisticated readouts such as - omics assays is a key priority for future clinical and translational studies. However, one of the major barriers to conducting such longitudinal exposome studies is their frequent reliance on in-person clinical research visits. In-person research visits, often requiring time-consuming travel to an academic medical center and absence from work, can significantly limit the geographic, racial, and socioeconomic representation of research participants. These in-person visits also typically occur every few months, limiting the temporal resolution of exposome data that can be measured. This proposal focuses on the implementation of innovative strategies for remote, home-based exposome monitoring and -omics measurements. Successful completion of this work will provide valuable resources for a future collaborative network studying the exposome.
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会议论文
Multi-racial genetic analysis of hidradenitis suppurativa
Multi-racial genetic analysis of hidradenitis suppurativa
Multi-racial genetic analysis of hidradenitis suppurativa
Elucidating Systemic Inflammation in Hidradenitis Suppurativa using Single Cell Omics and Machine Learning
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