A New Tool to Identify Pediatric Patients with Atypical Diabetes Associated with Gene Polymorphisms.

IF 6.8 2区 医学 Q1 ENDOCRINOLOGY & METABOLISM Diabetes & Metabolism Journal Pub Date : 2024-09-01 Epub Date: 2024-03-22 DOI:10.4093/dmj.2023.0166
Sophie Welsch, Antoine Harvengt, Paola Gallo, Manon Martin, Dominique Beckers, Thierry Mouraux, Nicole Seret, Marie-Christine Lebrethon, Raphaël Helaers, Pascal Brouillard, Miikka Vikkula, Philippe A Lysy
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Abstract

Backgruound: Recent diabetes subclassifications have improved the differentiation between patients with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus despite several overlapping features, yet without considering genetic forms of diabetes. We sought to facilitate the identification of monogenic diabetes by creating a new tool that we validated in a pediatric maturity-onset diabetes of the young (MODY) cohort.

Methods: We first created the DIAgnose MOnogenic DIAbetes (DIAMODIA) criteria based on the pre-existing, but incomplete, MODY calculator. This new score is composed of four strong and five weak criteria, with patients having to display at least one weak and one strong criterion.

Results: The effectiveness of the DIAMODIA criteria was evaluated in two patient cohorts, the first consisting of patients with confirmed MODY diabetes (n=34) and the second of patients with T1DM (n=390). These DIAMODIA criteria successfully detected 100% of MODY patients. Multiple correspondence analysis performed on the MODY and T1DM cohorts enabled us to differentiate MODY patients from T1DM. The three most relevant variables to distinguish a MODY from T1DM profile were: lower insulin-dose adjusted A1c score ≤9, glycemic target-adjusted A1c score ≤4.5, and absence of three anti-islet cell autoantibodies.

Conclusion: We validated the DIAMODIA criteria, as it effectively identified all monogenic diabetes patients (MODY cohort) and succeeded to differentiate T1DM from MODY patients. The creation of this new and effective tool is likely to facilitate the characterization and therapeutic management of patients with atypical diabetes, and promptly referring them for genetic testing which would markedly improve clinical care and counseling, as well.

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识别与基因多态性有关的非典型糖尿病小儿患者的新工具。
背景:尽管1型糖尿病(T1DM)和2型糖尿病有一些重叠的特征,但最近的糖尿病亚分类改进了1型糖尿病(T1DM)和2型糖尿病患者之间的区分,但没有考虑糖尿病的遗传形式。我们试图通过创建一种新工具来促进单基因糖尿病的识别,并在小儿成熟-发病型糖尿病(MODY)队列中进行了验证:方法:我们首先在已有但不完整的 MODY 计算器的基础上创建了 DIAgnose MOnogenic DIAbetes(DIAMODIA)标准。这个新的评分标准由四项强标准和五项弱标准组成,患者必须至少符合一项弱标准和一项强标准:结果:在两组患者中对 DIAMODIA 标准的有效性进行了评估,第一组是确诊的 MODY 糖尿病患者(34 人),第二组是 T1DM 患者(390 人)。这些 DIAMODIA 标准成功检测出了 100% 的 MODY 患者。对 MODY 和 T1DM 群体进行的多重对应分析使我们能够区分 MODY 患者和 T1DM 患者。区分 MODY 和 T1DM 的三个最相关变量是:较低的胰岛素剂量调整 A1c 得分≤9,血糖目标调整 A1c 得分≤4.5,以及不存在三种抗小细胞自身抗体:我们验证了 DIAMODIA 标准,因为它能有效识别所有单基因糖尿病患者(MODY 队列),并成功区分 T1DM 和 MODY 患者。这一新的有效工具的建立可能有助于非典型糖尿病患者的特征描述和治疗管理,并能及时将他们转诊至基因检测机构,从而显著改善临床护理和咨询服务。
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来源期刊
Diabetes & Metabolism Journal
Diabetes & Metabolism Journal Medicine-Endocrinology, Diabetes and Metabolism
CiteScore
10.40
自引率
6.80%
发文量
92
审稿时长
52 weeks
期刊介绍: The aims of the Diabetes & Metabolism Journal are to contribute to the cure of and education about diabetes mellitus, and the advancement of diabetology through the sharing of scientific information on the latest developments in diabetology among members of the Korean Diabetes Association and other international societies. The Journal publishes articles on basic and clinical studies, focusing on areas such as metabolism, epidemiology, pathogenesis, complications, and treatments relevant to diabetes mellitus. It also publishes articles covering obesity and cardiovascular disease. Articles on translational research and timely issues including ubiquitous care or new technology in the management of diabetes and metabolic disorders are welcome. In addition, genome research, meta-analysis, and randomized controlled studies are welcome for publication. The editorial board invites articles from international research or clinical study groups. Publication is determined by the editors and peer reviewers, who are experts in their specific fields of diabetology.
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