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Chinese Medicine：多组学与机器学习揭示缺血性心力衰竭气虚血瘀证的“基因-蛋白-代谢物”网络

8小时前 吾乃喵大人 MedSci原创 发表于上海

缺血性心力衰竭气虚血瘀证
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研究深刻揭示了气虚血瘀证在现代医学分子水平上的体现，推动了传统中医理论与现代精准医学的有效融合。

亮点总结 首次通过多组学整合多维度分析，揭示了缺血性心力衰竭（IHF）中气虚血瘀（QXXY）证的分子特征，构建了基因-蛋白质-代谢物网络。 明确气虚血瘀证患者存在能量代谢紊乱、慢性炎症激活及凝血功能异常，并发现与中医气血理论高度契合的核心生物标志物。 结合机器学习筛选出多组学联合诊断生物标志物，验证其对气虚血瘀证的高效鉴别能力，奠定精准诊断和靶向治疗基础。 心力衰竭（Heart Failure, HF）作为全球范围内死亡率和致残率居高不下的心血管疾病，其发病率随着人口老龄化持续上升。特别是缺血性心力衰竭（IHF）作为HF的主要病因，约占70%，其病理机制复杂，预后仍极差。目前尽管西医在防治心衰方面取得一定进展，但依然难以满足个体化诊疗需求。 中医临床中“气虚血瘀”证被认为是IHF的主要病因病机，体现为气机不足、血行不畅，表现为疲劳、气短、心悸等症状。传统中医诊断依赖主观临床指标，缺乏现代分子生物学解释，限制其广泛应用与科学化发展。近年来，多组学技术为解析疾病复杂性提供了新工具，结合机器学习可从海量数据中筛选关键分子标志物，为阐明中医证候的分子机制提供了契机。此前相关研究多聚焦单一组学层

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    37分钟前 135672_1610 来自山东省


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    7小时前 ms4000001513304915 来自广东省


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    7小时前 1209e435m98(暂无昵称) 来自浙江省


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    8小时前 梅斯管理员 来自上海


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