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针对系统医学应用的代谢先天性错误的个性化基因组规模建模
Almut Heinken1, Sandra El Kouche1, Rosa-Maria Guéant-Rodriguez2
1Inserm UMRS 1256 NGERE - Nutrition, Genetics, and Environmental Risk Exposure, University of Lorraine, Nancy F-54000, France.
Metabolism: clinical and experimental
|November 19, 2023
概括
代谢的先天性错误 (IEMs) 是一种罕见的遗传疾病. 欧米克驱动的方法和个性化代谢模型为了解和治疗这些疾病提供了新的方法,为罕见疾病推进了个性化医学.
科学领域:
- 生物化学 生物化学
- 遗传学 遗传学 是一个
- 系统生物学 系统生物学
背景情况:
- 代谢的先天性错误 (IEMs) 涵盖了1000多种罕见的遗传性疾病,具有显著的全球流行率.
- 在IEM中,患者表现和疾病严重程度表现出相当大的变化,类似于常见疾病.
研究的目的:
- 审查omics驱动的策略,以全面了解IEM患者的代谢表型.
- 探索基于约束的重建和分析 (COBRA) 的应用,以建模遗传性疾病.
- 突出肠道微生物群在罕见疾病中的作用,并为IEM管理提出个性化的方法.
主要方法:
- 对代谢表型化的omics驱动方法的审查.
- 基于约束的重建和分析 (COBRA) 应用于机械系统生物学建模.
- 在罕见疾病中对肠道微生物组变化的分析.
主要成果:
- 欧米克斯数据为IEM中的代谢表型提供了一个综合的视图.
- 科巴模型有效地模拟了遗传代谢障碍的影响.
- 在患有罕见疾病的患者中观察到肠道微生物组失调.
结论:
- 个性化代谢模型可以预测生物标志物,并指导针对IEM的量身定制疗法.
- 这种方法有可能在罕见疾病中推进个性化医疗.
- 整合omics,建模和微生物组数据为IEM患者护理提供了一个整体策略.
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