了解非传染性疾病中的基因环境相互作用的多学科方法:技术,翻译和公平问题
Robel Alemu1,2,3, Nigussie T Sharew4, Yodit Y Arsano5
1Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. robel.alemu@anderson.ucla.edu.
Human genomics
|January 31, 2025
概括
多学科研究通过整合遗传,行为和环境数据,促进对非传染性疾病 (NCD) 的理解. 解决数据缺口和促进公平对于全球健康进步至关重要.
科学领域:
- 基因组学和生物信息学
- 公共卫生 公共卫生
- 翻译医学是一种翻译医学.
背景情况:
- 非传染性疾病 (NCD) 是全球主要的健康负担,导致大量死亡和残疾.
- 非传染性疾病是复杂的基因环境相互作用的结果,需要先进的分析方法来理解.
- 当前的多学科数据集存在异质性,分析性局限性,以及不同祖先的代表性不足,阻碍了概括性并加剧了健康差异.
研究的目的:
- 对2000年至2024年与非传染性疾病相关的全球多学科数据进行范围审查.
- 评估多学科数据集成,翻译应用和NCD研究中的公平考虑方面的进展.
- 确定在精准医学中利用多学科数据的挑战和机会,并改善多种人群的健康结果.
主要方法:
- 覆盖范围审查方法.
- 分析2000-2024年多主题数据集和文献.
- 评估数据整合技术,AI/ML应用以及翻译策略.
主要成果:
- 对非传染性疾病的多学科数据集成取得了显著进展,在翻译研究中越来越多的应用.
- 确定关键挑战,包括数据复杂性,分析局限性和非欧洲祖先的严重不足.
- 利用AI/ML用于基因环境相互作用研究和精准医学的新兴机会.
结论:
- 标准化的协议,协调的数据共享和先进的分析方法对于有效的多领域数据集成至关重要.
- 将多学科的见解转化为精准医学需要解决研究中的公平和公平问题.
- 在代表性不足的地区进行战略投资和能力建设对于公平的全球NCD研究和改善患者结果至关重要.
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