实用医学杂志 ›› 2024, Vol. 40 ›› Issue (16): 2199-2205.doi: 10.3969/j.issn.1006-5725.2024.16.001

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糖尿病分型新视野——基于临床表现向基于病因分子机制转变

杨舒婷,罗说明,周智广()   

  1. 中南大学湘雅二医院代谢内分泌科,糖尿病免疫学教育部重点实验室,国家代谢性疾病临床医学研究中心 (长沙 410011 )
  • 收稿日期:2024-03-28 出版日期:2024-08-25 发布日期:2024-08-26
  • 通讯作者: 周智广 E-mail:zhouzg@hotmail.com
  • 作者简介:周智广,教授、一级主任医师、博士研究生导师、湘雅名医。国家代谢性疾病临床医学研究中心主任、糖尿病免疫学教育部重点实验室主任、中国医师协会内分泌代谢科医师分会名誉会长。38年来坚持扎根临床和科研一线,围绕糖尿病精准诊疗,建立了糖尿病免疫诊断新方法、开辟了免疫治疗新途径、创立了糖尿病“防-管-治”结合的管理新模式,牵头制定中国指南共识10部;在《BMJ》等国际期刊发表论文380余篇,授权国家发明专利25项,获国家科技进步奖3项及湖南省科技进步一等奖2项。荣获全国优秀科技工作者、卫生部有突出贡献中青年专家、中国青年科技奖等荣誉。1993年起享受国务院政府津贴。
  • 基金资助:
    湖南省自然科学基金重大项目(揭榜制)(2021JC0003);湖南省临床医疗技术创新引导项目(2021SK53508);湖南省卫生健康高层次人才重大科研专项(R202344)

A new vision of diabetes classification: A shift from clinical manifestation to etiological molecular mechanism

Shuting YANG,Shuoming LUO,Zhiguang. ZHOU()   

  1. Department of Metabolism Endocrinology,the Second Xiangya Hospital of Central South University,Key Laboratory of Diabetes Immunology,Ministry of Education,National Clinical Medical Research Center for Metabolic Diseases,Changsha 410011,China
  • Received:2024-03-28 Online:2024-08-25 Published:2024-08-26
  • Contact: Zhiguang. ZHOU E-mail:zhouzg@hotmail.com

摘要:

随着医学科技进步和对疾病本质理解的深入,糖尿病的分型正经历着变革,传统基于临床特征和胰岛素依赖性的分类方法逐渐显示出其局限性。近年来,基因组、表观遗传、代谢组学等生物信息技术的应用,以及大数据和机器学习技术在疾病分类中的运用,推动了糖尿病分型向更加精细化和个性化的方向发展。这些新技术揭示了糖尿病复杂的病理生理机制和广泛的异质性,为早期诊断、个性化治疗和预后评估提供了新思路。这一进展不仅对糖尿病的复杂性理解具有重要意义,而且将为患者提供更加精准和有效的治疗方案,标志着糖尿病分型从简单的基于临床表现向基于病因分子机制转变的历史性时刻。

关键词: 糖尿病分型, 病因分子机制, 早期诊断, 个性化治疗

Abstract:

The classification of diabetes is undergoing a significant transformation. As advancements in medical technology and a deeper understanding of its etiology, traditional classification methods based on clinical characteristics and insulin dependency are increasingly revealing their limitations. In recent years, the integration of genomic, epigenetic, and metabolomic technologies, combined with the application of big data analytics and machine learning in disease classification, has propelled diabetes classification towards enhanced precision and personalization. These cutting-edge technologies elucidate the intricate pathophysiological mechanisms and extensive heterogeneity inherent in diabetes, offering novel methodologies for early diagnosis, individualized treatment, and prognostic evaluation. This paradigm shift not only deepens the comprehension of diabetes complexity but also holds the potential to provide more precise and efficacious therapeutic interventions for patients. Consequently, this marks a historic transition from simplistic, clinically-based classification systems to sophisticated, molecular mechanism-based paradigms in diabetes classification.

Key words: diabetes classification, etiological molecular mechanism, early diagnosis, precision medicine

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