多种病的整合为健康个体的早期预防策略铺平了道路
Dimitrios Kioroglou1, Rubén Gil-Redondo2, Nieves Embade2
1Integrative Genomics Lab, Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, Derio, Basque Country, Spain.
NPJ genomic medicine
|May 3, 2025
概括
健康个体的多原子分析显示了四个不同的子组. 整合基因组学,尿液和血清数据可以提高早期疾病预防策略的分层.
科学领域:
- 发现生物标志物的发现.
- 精准医学是一门精准的医学.
- 多个omics的多个omics.
背景情况:
- 精准医学依赖生物标志物来实现患者分层和改善结果.
- 纵向的多原子分析可告知病理状态,但它们在健康个体中的应用较少被探索.
研究的目的:
- 探索多原子分析对健康个体分层的有用性.
- 评估整合基因组学,尿液代谢学和血清代谢学/脂蛋白组学的分层能力.
- 为了评估分子配置文件的时间稳定性,用于子组识别.
主要方法:
- 在162名健康个体中进行基因组学,尿液代谢学和血清代谢学/脂质蛋白学的横截面整合性研究.
- 欧米层的单独和综合分析.
- 在三个时间点的61个个体的子集中对分子概况的纵向评估.
- 用于风险因素识别的功能注释.
主要成果:
- 与单个的欧米层相比,多欧米集成显示出更高的分层能力.
- 在健康的队列中,确定了四个不同的子组.
- 一个子组显示出失脂蛋白病的风险因素累积,表明未来心血管风险的潜力.
- 分子形状的时间稳定性支持已识别的子组.
结论:
- 多种性质的分析提供了一个强大的框架,用于对健康个体进行分层.
- 这种方法有助于制定用于疾病早期预防的精准医学策略.
- 识别具有特定风险因素的子组可以实现有针对性的监测和干预,从而有可能减少未来的心血管风险.
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