Polygenic subtype identified in ACCORD trial displays a favorable type 2 diabetes phenotype in the UKBiobank population.

IF 3.8 3区医学 Q2 GENETICS & HEREDITY Human Genomics Pub Date : 2024-06-22 DOI:10.1186/s40246-024-00639-z

Courtney Hershberger, Arshiya Mariam, Kevin M Pantalone, John B Buse, Alison A Motsinger-Reif, Daniel M Rotroff

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Abstract

Introduction: We previously identified a genetic subtype (C4) of type 2 diabetes (T2D), benefitting from intensive glycemia treatment in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. Here, we characterized the population of patients that met the C4 criteria in the UKBiobank cohort.

Research design and methods: Using our polygenic score (PS), we identified C4 individuals in the UKBiobank and tested C4 status with risk of developing T2D, cardiovascular disease (CVD) outcomes, and differences in T2D medications.

Results: C4 individuals were less likely to develop T2D, were slightly older at T2D diagnosis, had lower HbA1c values, and were less likely to be prescribed T2D medications (P < .05). Genetic variants in MAS1 and IGF2R, major components of the C4 PS, were associated with fewer overall T2D prescriptions.

Conclusion: We have confirmed C4 individuals are a lower risk subpopulation of patients with T2D.

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ACCORD 试验确定的多基因亚型在英国生物银行人群中显示出有利的 2 型糖尿病表型。

简介：我们曾在控制糖尿病心血管风险行动（ACCORD）试验中发现了一种2型糖尿病（T2D）遗传亚型（C4），该亚型可从强化血糖治疗中获益。在此，我们对英国生物库队列中符合 C4 标准的患者群体进行了特征描述：利用多基因评分（PS），我们确定了英国生物库中的 C4 患者，并测试了 C4 状态与 T2D 发病风险、心血管疾病（CVD）结局以及 T2D 药物治疗差异的关系：结果：C4人群罹患T2D的几率较低、确诊T2D时年龄稍大、HbA1c值较低，且较少被处方T2D药物（P我们已经证实，C4人群是T2D患者中风险较低的亚人群。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Human Genomics GENETICS & HEREDITY-

CiteScore

6.00

自引率

2.20%

发文量

审稿时长

11 weeks

期刊介绍： Human Genomics is a peer-reviewed, open access, online journal that focuses on the application of genomic analysis in all aspects of human health and disease, as well as genomic analysis of drug efficacy and safety, and comparative genomics. Topics covered by the journal include, but are not limited to: pharmacogenomics, genome-wide association studies, genome-wide sequencing, exome sequencing, next-generation deep-sequencing, functional genomics, epigenomics, translational genomics, expression profiling, proteomics, bioinformatics, animal models, statistical genetics, genetic epidemiology, human population genetics and comparative genomics.