通过使用二维树结构结构的亚表型化来阐明糖尿病前期的异质性
Hong Lin1, Yilan Ding1, Xiaojing Jia1
1Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Digital Medicine Innovation Center, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China.
糖尿病前期有不同的形式. 识别这些表型有助于预测2型糖尿病 (T2DM),慢性病 (CKD) 和心血管疾病 (CVD) 的风险,改善个性化护理.
科学领域:
- 代谢健康和内分泌学
- 在医疗保健中的数据科学.
- 公共卫生和流行病学
背景情况:
- 糖尿病前期代表了2型糖尿病 (T2DM) 之前的关键阶段,其临床表现的特点是显著的变化.
- 了解这种异质性对于开发有针对性的干预和个性化的管理策略至关重要.
研究的目的:
- 通过使用大型队列,探索糖尿病前期的现象异质性.
- 根据临床变量识别出不同的糖尿病前期亚型.
- 评估与这些表型相关的T2DM,慢性病 (CKD) 和心血管疾病 (CVD) 的差异风险.
主要方法:
- 区分维度减小树 (DDRTree) 算法的应用.
- 分析了来自中国心脏代谢疾病和癌症队列 (4C) 研究的55,777名参与者.
- 使用了12个临床可用的变量来表型化.
主要成果:
- 确定了四种不同的糖尿病前期表型.
- 现型4显示T2DM风险最高 (高血糖症,胰岛素耐药性,肥胖,高甘油,肝酶).
- 现型3表现出最高的CKD风险 (肥胖,胰岛素耐药性,高血糖症,脂质失调症),并与现型4共享增加的CVD风险,具有各种CVD亚型.
结论:
- 糖尿病前期表现出显著的表型异质性,具有差异性的疾病风险.
- 鉴定的表型为个性化风险分层和糖尿病前期管理提供了基础.
- 结果在外部队列中得到验证,并开发了一个在线风险预测工具.
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