亚洲单基因糖尿病登记:患病率,长期肾脏轨迹和发展的诊断算法选择候选基因检测。

Clara Si Hua Tan, Kai Xiang Kee, Huili Zheng, Lovynn Wan Ting Chan, Yuzhen Song, Winston Yin Chian Kon, Ying Jie Chee, Joyce Xia Lian, Rashida Farhad Vasanwala, Fabian Kok Peng Yap, Wann Jia Loh, Tavintharan Subramaniam, Chee Fang Sum, Su Chi Lim
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引用次数: 0

摘要

通过国家医疗保健集团- khoo Teck Puat医院单基因糖尿病登记,我们旨在确定年轻人成熟型糖尿病(MODY)的患病率和频谱,描述主要MODY亚型的长期肾脏轨迹,并基于临床参数和生物标志物的组合开发诊断算法,以优化基因检测候选人的选择。方法:共有373名参加新加坡糖尿病二级护理中心的研究参与者被转介进行基因检测。基因检测的主要纳入标准包括发病年龄≤35岁、体重指数。结果:对49名参与者的16个基因和1个线粒体变异的分析导致了分子诊断,致病变异主要存在于HNF1A(29%)、HNF4A(23%)和GCK(15%)中。在这些主要MODY亚型之间观察到的长期肾脏轨迹数据没有显著差异,但每个亚组的一些关键观察结果是典型的。例如,患有HNF4A-MODY的患者易患微血管并发症(即糖尿病肾病),而患有GCK-MODY的患者患有轻度且非进行性高血糖。结构化诊断算法,包括易于获得的生物标志物,如高敏c反应蛋白(hs-CRP)和高密度脂蛋白-胆固醇(HDL-c),提供了71%的诊断准确率,实现了0.94的阴性预测值和0.68的敏感性。结论:根据提示MODY的临床分类进行基因检测的年轻发病糖尿病患者中MODY的患病率(13%)不容小视。目前的临床评估工具可能包括hs-CRP和HDL-c,以完善基因检测候选人的选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Asian monogenic diabetes registry: prevalence, long-term renal trajectory and development of a diagnostic algorithm for selection of candidates for genetic testing.

Introduction: Through the National Healthcare Group-Khoo Teck Puat Hospital Monogenic Diabetes Registry, we aimed to determine the prevalence and spectrum of maturity-onset diabetes of the young (MODY), describe the long-term renal trajectory of major MODY subtypes, and develop a diagnostic algorithm based on a combination of clinical parameters and biomarkers to refine selection of candidates for genetic testing.

Methods: A total of 373 study participants attending secondary care diabetes centres in Singapore were referred for genetic testing. Key inclusion criteria for genetic testing included onset age ≤35 years, body mass index <32.5 kg/m2 and absence of glutamic acid decarboxylase autoantibody.

Results: Analysis of 16 genes and one mitochondrial variant led to a molecular diagnosis in 49 participants, with pathogenic variants present mostly in HNF1A (29%), HNF4A (23%) and GCK (15%). Long-term renal trajectory data observed between these major MODY subtypes were not significantly different, but some key observations were typical for each subgroup. For instance, patients with HNF4A-MODY were predisposed to the risk of microvascular complications (i.e., diabetic kidney disease), while patients with GCK-MODY had mild and non-progressive hyperglycaemia. A structured diagnostic algorithm, including readily available biomarkers such as high-sensitive C-reactive protein (hs-CRP) and high-density lipoprotein-cholesterol (HDL-c), provided 71% diagnostic accuracy, achieving a negative predictive value of 0.94 and a sensitivity of 0.68.

Conclusion: The prevalence of MODY (13%) is non-trivial among young-onset diabetes referred for genetic testing based on clinical classifiers suggestive of MODY. Current clinical assessment tools may include hs-CRP and HDL-c to refine selection of candidates for genetic testing.

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