一个系统科的方法,糖尿病病的研究和实践
William P Martin1, Neil G Docherty1
1Diabetes Complications Research Centre, School of Medicine, Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland.
Nephron
|September 11, 2023
概括
使用多种数据的系统脏学方法,包括OMIC和成像,可以揭示个体糖尿病病 (DKD) 机制. 这种精准医学策略旨在个性化治疗,以获得更好的患者结果.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學專業.
- 系统生物学 系统生物学
- 精准医学是一门精准的医学.
背景情况:
- 糖尿病病 (DKD) 诊断和分期缺乏对异质机制的细粒度.
- 常规的实验室指数不足以对DKD进展进行个性化治疗.
研究的目的:
- 探索一种系统脏学方法,以了解DKD异质性.
- 为了为个别DKD患者的向治疗铺平道路.
主要方法:
- 整合来自临床前模型 (体外,动物) 和人体研究 (KPMP,ENBiBA) 的数据.
- 结合不同的数据领域:临床,成像,组织病理学,超结构和分子奥米克 (转录组学,蛋白质组学).
- 利用机器和深度学习来分析成像和组织病理学数据.
主要成果:
- 临床前模型和多中心队列研究提供了关键的脏组织数据.
- 多维数据的整合为解开个人层面的DKD机制提供了机会.
- 机器学习增强了从复杂数据,包括成像和omics的见解.
结论:
- 通过整合来自多个模型系统和领域的数据,可以创建DKD的精准医学方法.
- 这种方法旨在在正确的时间将正确的治疗方法与正确的DKD患者相匹配.
- 系统脏学和数据集成是推进个性化DKD护理的关键.
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