发生性肺高血压的风险预测和治疗目标:一个大规模的蛋白质基因分析和门德尔随机化研究
Yuanyuan Zhang1, Yan Zhang2, Sisi Yang1
1Division of Nephrology, Nanfang Hospital, Southern Medical University; National Clinical Research Center for Kidney Disease; State Key Laboratory of Multi-Organ Injury Prevention and Treatment; Guangdong Provincial Institute of Nephrology, Guangdong Provincial Key Laboratory of Renal Failure Research, Guangzhou, 510515, China.
一个新的30蛋白风险评分准确地预测了肺高血压 (PH) 风险,确定了RGMA和NPC2作为这种疾病的潜在治疗点.
科学领域:
- 生物化学 生物化学
- 基因组学就是基因组学.
- 临床医学 临床医学
背景情况:
- 肺高血压 (PH) 构成了严重的健康挑战,治疗选择有限.
- 准确的风险预测和新型治疗点的识别对于管理PH至关重要.
研究的目的:
- 为了识别与肺高血压 (PH) 风险相关的血蛋白.
- 发现PH的潜在治疗点.
- 开发和验证基于蛋白质的PH风险预测模型.
主要方法:
- 在英国大型生物库队列 (n=38,499) 上利用LASSO回归进行培训和测试.
- 使用Harrell的C指数,净重新分类改进 (NRI) 和综合歧视改进 (IDI) 评估模型性能.
- 在来自苏格兰和威尔士的独立队列 (n=5021) 中验证了该模型.
主要成果:
- 与基本和临床模型相比,30蛋白风险得分显示了PH风险的优异预测性能 (C指数=0.873).
- 确定了RGMA和NPC2作为PH的因果因素和潜在的治疗点.
- 鉴定出Endothelin-1是蛋白质与蛋白质相互作用网络中的一个中心枢纽.
结论:
- 开发的蛋白质风险评分为评估PH风险提供了重要的临床实用性.
- RGMA和NPC2代表了肺高血压的有希望的治疗点.
- 蛋白质生物标志物可以提高PH风险预测模型的准确性.
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