Diabetic Ketoacidosis From New SGLT2i: Can Genomics Estimate Risk (DaNGER)
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 63
- 试验地点
- 2
- 主要终点
- Identification of genomic variants associated with an increased risk of SGLT2 inhibitor-associated DKA
研究概览
简要总结
Sodium glucose co-transporter 2 (SGLT2) inhibitors have revolutionized care for people living with type 2 diabetes mellitus (T2DM). They reduce a person's risk of heart failure, renal failure, myocardial infarction, stroke, cardiovascular mortality, and potentially all-cause mortality. Remarkably, some of these benefits also extend to people who do not have T2DM. While the benefits of SGLT2 inhibitors are impressive, there is one life-threatening side effect associated with their use: diabetic ketoacidosis (DKA). The ability to predict which patients are at highest risk of DKA is needed to sufficiently mitigate this risk. Moreover, considering the impressive benefits of SGLT2 inhibitors, identifying patients at the lowest risk of SGLT2 inhibitor-associated DKA is also important so that providers do not overestimate risk in those who stand to benefit most.
Advances in genomic technologies and related analyses have provided unprecedented opportunities to bring genomics-driven precision medicine initiatives to the forefront of clinical research. Leading these developments has been the progress made by genome-wide association studies (GWAS) due to decreasing genotyping costs, and consequently, the ability to routinely study large numbers of patients. These approaches allow for systematic screening of the genome in an unbiased manner and have accelerated the discovery of genetic variants and novel biological processes that contribute to the development of adverse treatment outcomes.
By using innovative approaches, which harness large cohorts of population controls, sample size limitations that are associated with rare adverse drug reactions such as SGLT2 inhibitor-associated DKA can be overcome. The DANGER study represents a highly innovative new direction wherein partnership among basic science researchers and computational biologists will lead to the application of genomic techniques to identify genetic variants that may be associated with SGLT2 inhibitor-associated DKA.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Control
- 时间视角
- Other
入排标准
- 年龄范围
- 18 Years 至 100 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •To be considered eligible for participation in this study, a participant must meet each of the following criteria:
- •Be 18 years or older and have a diagnosis of type 2 diabetes mellitus.
- •Have been admitted to hospital with SGLT2 inhibitor-associated DKA (cases) or admitted to hospital on an SGLT2 inhibitor and not have DKA (controls).
- •Be able to provide written consent (or, if patient is unable, have a substitute decision maker [SDM] available).
排除标准
- •A participant will be ineligible for participation in this study if he or she satisfies any one or more of the following criteria:
- •Diagnosis of type 1 diabetes mellitus.
- •Unable to spit 10mL into a vial.
- •A first degree relative has already been recruited into the study.
- •Had an alcohol binge before admission
- •Had prolonged fasting (>48 hours) prior to hospital admission
- •Recently stopped their insulin (within the past 7 days prior to hospital admission)
- •Our study will not include children or pregnant women because SGLT2 inhibitors are not approved for use in either patient population.
结局指标
主要结局
Identification of genomic variants associated with an increased risk of SGLT2 inhibitor-associated DKA
时间窗: One year
Genetic ancestry will be calculated using principal component analyses and outliers will be removed. GWAS will be performed with SAIGE, including genetic ancestry and the relevant clinical/demographic variables as covariates, to identify genetic variants associated with SGLT2 inhibitor-associated DKA.
次要结局
未报告次要终点