Diabetic Ketoacidosis From New SGLT2i: Can Genomics Estimate Risk (DaNGER)

Mount Sinai Hospital, Canada

Status: Enrolling

Conditions: Diabetic Ketoacidosis; Diabetes Type 2; DKA

Treatments: Genetic: Genomic analysis

Study type: Observational

Funder types: Other

Identifiers

NCT05402579

CTO 3737

Details and patient eligibility

About

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.

Enrollment: 60 estimated patients

Sex: All

Ages: 18 to 100 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

To be considered eligible for participation in this study, a participant must meet each of the following criteria:

1. Be 18 years or older and have a diagnosis of type 2 diabetes mellitus.
2. Have been admitted to hospital with SGLT2 inhibitor-associated DKA (cases) or admitted to hospital on an SGLT2 inhibitor and not have DKA (controls).
3. Be able to provide written consent (or, if patient is unable, have a substitute decision maker [SDM] available).

Exclusion criteria

A participant will be ineligible for participation in this study if he or she satisfies any one or more of the following criteria:

1. Diagnosis of type 1 diabetes mellitus.
2. Unable to spit 10mL into a vial.
3. A first degree relative has already been recruited into the study.
4. Had an alcohol binge before admission
5. Had prolonged fasting (>48 hours) prior to hospital admission
6. 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.

Trial design

60 participants in 2 patient groups

Cases

Description:

Patients with type 2 diabetes mellitus who were hospitalized with SGLT2 inhibitor-associated DKA (60 cases).

Treatment:

Genetic: Genomic analysis

Controls

Description:

There are two sources for controls. \[1\] Patients hospitalized at one of the participating hospitals who were on an SGLT2i and do not have DKA. \[2\] Population controls using publicly available data from the Canadian Longitudinal Study on Aging (CLSA) database (1000 controls via CLSA).

Treatment:

Genetic: Genomic analysis