Genetic Test for Cardiorenal Complications in Type 2 Diabetes

(GENOCORDIA Trial)

Recruiting at 1 trial location

Overseen By Johanne Tremblay, PhD

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Optithera

Disqualifiers: High frailty index, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 8

Duration: 18 months

2714 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial aims to determine if knowing genetic risks can help people with type 2 diabetes better manage potential heart and kidney issues. Participants will provide a saliva sample for a genetic test to predict their risk; some will receive their results, while others will not. Researchers seek to discover if being informed helps patients and their doctors achieve health targets, such as improved blood sugar levels or blood pressure. Individuals with type 2 diabetes who can visit the clinic regularly are well-suited for this trial. As an unphased trial, this study offers participants the chance to contribute to groundbreaking research that could enhance diabetes management for many.

Do I need to stop my current medications for this trial?

The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the trial coordinators or your doctor.

What prior data suggests that this genetic test is safe?

Research has shown that polygenic risk scores can help predict complications related to type 2 diabetes, such as heart and kidney problems. Studies have found that these scores enable doctors to better identify and manage these risks, potentially improving patient outcomes.

For safety, this genetic testing requires only a saliva sample, making it non-invasive and generally safe. Available research reports no negative effects from the test itself. However, learning about one's risk might cause emotional stress for some individuals. Discussing these concerns with a healthcare provider is advisable.

Overall, participating in this type of study appears safe, with minimal risk from the testing process itself. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about this trial because it uses a Polygenic Risk Score to assess the likelihood of developing cardiorenal complications in people with Type 2 Diabetes. Unlike standard treatments that primarily focus on managing blood sugar levels and symptoms with medication, this approach aims to predict complications before they occur by analyzing genetic data. This innovative method offers a personalized insight, potentially allowing for earlier interventions and tailored treatment plans. The excitement lies in its potential to change the way doctors approach prevention and management, leading to better long-term outcomes for patients.

What evidence suggests that this genetic test is effective for predicting cardiorenal complications in Type 2 Diabetes?

Research has shown that a polygenic risk score (PRS) can help predict the risk of heart and kidney problems in people with type 2 diabetes. One study found that a PRS was linked to a slightly higher risk of serious kidney damage in these patients. In this trial, participants in the "Informed" arm will receive their PRS test results at the start. By predicting risks early, doctors can intervene sooner, potentially leading to better health outcomes. Knowing their genetic risk could motivate patients to achieve important health goals, such as better blood sugar control and normal blood pressure. Overall, a PRS could be a valuable tool in managing the long-term effects of type 2 diabetes. ^{1 2 3 6 7}

Who Is on the Research Team?

Pavel Hamet, MD, PhD

Principal Investigator

CHUM

Are You a Good Fit for This Trial?

This trial is for individuals with Type 2 Diabetes who may also have cardiovascular disease or diabetic kidney disease. Participants will provide a saliva sample, attend clinic visits every three months, and complete quality of life questionnaires.

Inclusion Criteria

Able and willing to provide informed consent to the clinical and PRS parts of the study

I can visit the study site 7 times.

I am an adult with type 2 diabetes.

Exclusion Criteria

I am considered frail and have diabetes.

Any condition that may impact participation in a real-world study according to the treating physician

I refuse to know my heart and kidney risk score.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Genomic Testing

Participants undergo saliva sampling to determine genetic risk using a polygenic risk score test

1 week

1 visit (in-person)

Treatment

Participants receive personalized treatment based on their genomic risk score, with regular checkups every 3 months

18 months

7 visits (in-person)

Follow-up

Participants are monitored for safety and effectiveness after treatment, focusing on achieving therapeutic targets

4 weeks

What Are the Treatments Tested in This Trial?

Interventions

• Polygenic Risk Score

Trial Overview The study tests if knowing one's genetic risk for cardiorenal complications (heart and kidney problems) from Type 2 Diabetes helps achieve better health targets over 18 months. This includes blood sugar levels, blood pressure, urine albumin levels, and kidney function.

How Is the Trial Designed?

Group I: Informed Active Control 1 Intervention

Intervention group tested and informed of the Polygenic risk score test result at the start of the study

Group II: Not initially informed Active Control 1 Intervention

Control group: tested but not informed of the Polygenic Risk Score test result at the start of the study.

Who Is Running the Clinical Trial?

Optithera

Lead Sponsor

Trials

1

Recruited

2,700+

ELNA Medical

Collaborator

Trials

1

Recruited

2,700+

Genome Canada

Collaborator

Trials

17

Recruited

34,400+

Genome Quebec

Collaborator

Trials

8

Recruited

19,800+

Published Research Related to This Trial

A multi-polygenic risk score (multiPRS) developed from 598 SNPs effectively predicts cardiovascular and renal complications in individuals with type 2 diabetes, identifying a high-risk group with a 3.1-fold increased risk of major events and a 4.4-fold increased risk of cardiovascular death.

The model allows for targeted interventions, showing that intensive blood pressure and glucose control reduced cardiovascular death by 47% in high-risk individuals, highlighting its potential for improving outcomes through personalized treatment strategies.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Polygenic risk scores predict diabetes complications and their response to intensive blood pressure and glucose control. Tremblay, J., Haloui, M., Attaoua, R., et al.[2022]

Genetic risk scores (GRSs) have shown potential in identifying individuals with type 1 or type 2 diabetes who are at high risk for developing diabetic kidney disease (DKD), based on a systematic review of 15 studies.

Among the studies with strong methodological quality, 9 reported significant associations between GRSs and DKD outcomes, suggesting that implementing GRSs in clinical settings could help stratify risk for diabetes-related complications.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Genetic risk scores identify people at high risk of developing diabetic kidney disease: A systematic review. Ali, AS., Pham, C., Morahan, G., et al.[2023]

In a study of the UK Biobank population, certain single nucleotide polymorphisms (SNPs) associated with albuminuria were found to correlate with urine albumin-to-creatinine ratio (UACR) traits, but they did not enhance the diagnostic accuracy for kidney damage beyond existing clinical measures.

The research highlighted that while some SNPs showed different effects in diabetic versus non-diabetic individuals, they did not significantly improve the prediction of albuminuria or renal injury, indicating that current clinical variables remain more effective for diagnosis.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Albuminuria-Related Genetic Biomarkers: Replication and Predictive Evaluation in Individuals with and without Diabetes from the UK Biobank. Cañadas-Garre, M., Kunzmann, AT., Anderson, K., et al.[2023]

In a study of 56 Maltese Caucasian patients with type 2 diabetes and nephropathy, those with the DD genotype of the ACE gene experienced a significantly faster decline in kidney function, with a GFR decrease of -7.76 ml/min/year compared to -1.17 ml/min/year in those with ID or II genotypes.

The 3-year mortality rate was notably higher in patients with the DD genotype at 45.2%, compared to 20.0% in those with ID/II genotypes, indicating that the DD genotype is a strong predictor of both renal decline and mortality in this population.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

ACE gene polymorphism as a prognostic indicator in patients with type 2 diabetes and established renal disease. Fava, S., Azzopardi, J., Ellard, S., et al.[2022]

The study found that genetic factors significantly contribute to the heritability of diabetes-related complications, with estimates showing 29% heritability for diabetic kidney disease and varying heritability for microalbuminuria and diabetic retinopathy, indicating a strong genetic influence on these conditions.

Rare genetic variants were identified as major contributors to the heritability of diabetic retinopathy, highlighting that much of the genetic risk for diabetes complications remains to be uncovered, which calls for further genetic research in this area.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Systematic Heritability and Heritability Enrichment Analysis for Diabetes Complications in UK Biobank and ACCORD Studies. Kim, J., Jensen, A., Ko, S., et al.[2023]

In a study involving 995 type 2 diabetes patients, the addition of a genetic risk score (GRS) to conventional risk factors improved the prediction of diabetic nephropathy (DN) risk, with an AUROC of 0.78 compared to 0.75 for clinical factors alone.

The model combining GRS and clinical factors also showed a significant net reclassification improvement of 9.98%, indicating that genetic information can enhance the identification of high-risk individuals for better management of DN.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Genetic risk score for risk prediction of diabetic nephropathy in Han Chinese type 2 diabetes patients. Liao, LN., Li, TC., Li, CI., et al.[2022]

Individuals with Type 2 Diabetes (T2D) face a higher risk of severe complications like heart disease and stroke, highlighting the need for effective risk assessment to identify those who would benefit most from preventive measures.

Integrating genetic information with traditional and new biomarkers could enhance the predictive accuracy for vascular complications in T2D, potentially leading to better-targeted interventions and improved patient outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Biomarkers of vascular complications in type 2 diabetes. Tremblay, J., Hamet, P.[2015]

Diabetic nephropathy affects 35 to 45% of Type 1 diabetes patients after 15-20 years, with glycaemic control and diabetes duration being the main risk factors.

Genetic susceptibility may play a role in the development of diabetic nephropathy, as not all diabetic patients experience this condition, suggesting the need for further research into specific gene polymorphisms that could influence risk.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

[Genetics of diabetic complications: nephropathy]. Jeunemaitre, X.[2019]

This study found no link between the angiotensin-converting enzyme (ACE) gene polymorphisms and increased albumin excretion rates in patients with type II diabetes, suggesting that genetic factors may not play a significant role in diabetic kidney disease for this group.

In contrast, previous research indicated a relationship between ACE gene variations and nephropathy in type I diabetic patients, highlighting potential differences in genetic influences on kidney disease between type I and type II diabetes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Angiotensin-converting enzyme (ACE) gene polymorphism in type II diabetic patients with increased albumin excretion rate. Panagiotopoulos, S., Smith, TJ., Aldred, GP., et al.[2019]

Citations

1. nature.com nature.com/articles/s41467-025-63546-4

Polygenic risk score for type 2 diabetes shows context- ... For kidney diseases, the PRS was associated with a 1.08-fold increased risk (95% CI: 1.03, 1.13) of end stage renal disease (ESRD) in T2D cases ...

2. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC8382653/

Polygenic risk scores predict diabetes complications and ... Type 2 diabetes increases the risk of cardiovascular and renal complications, but early risk prediction could lead to timely intervention and better outcomes.

3. academic.oup.com academic.oup.com/eurjpc/article/31/10/1277/7612622

Interaction between type 2 diabetes polygenic risk and ... The beneficial effect of physical activity on cardiovascular outcomes disappeared among those with high genetic risk for type 2 diabetes.

4. diabetesjournals.org diabetesjournals.org/care/article/47/12/2223/157360/Incremental-Prognostic-Value-of-a-Coronary-Heart

Incremental Prognostic Value of a Coronary Heart Disease ... Incremental Prognostic Value of a Coronary Heart Disease Polygenic Risk Score in Type 2 Diabetes Available. Ify R. Mordi Corresponding Author.

5. link.springer.com link.springer.com/article/10.1007/s00125-025-06419-1

Clinical use of polygenic scores in type 2 diabetes We explore the potential applicability of type 2 diabetes polygenic scores to quantify genetic liability for prediction, screening and risk stratification.

6. medrxiv.org medrxiv.org/content/10.1101/19010785v1.full-text

Polygenic risk scores predict diabetic complications and ... This novel polygenic prediction model identified people with diabetes at low and high risk of complications and improved targeting those at ...

7. ahajournals.org ahajournals.org/doi/10.1161/CIR.0000000000001077

Polygenic Risk Scores for Cardiovascular Disease The clinical tool for type 2 diabetes was the American Diabetes Association risk score, which had a 33% risk threshold over 10 years and ...