Enrolling by invitation

SIGNALUrine Proteomic Signatures for Personalized Diabetes Treatment

0 criteria met from your profileSee at a glance how your profile meets each eligibility criteria.
What is being tested

Semaglutide, 1.34 mg/mL

+ Finerenone Oral Tablet

+ Dapagliflozin (DAPA)

Drug
Who is being recruted

Urogenital Diseases+8

+ Albuminuria

+ Female Urogenital Diseases and Pregnancy Complications

Over 18 Years
See all eligibility criteria
How is the trial designed

Other Study

Phase 4
Interventional
Study Start: November 2025
See protocol details

Summary

Principal SponsorSteno Diabetes Center Copenhagen
Last updated: January 28, 2026
Sourced from a government-validated database.Claim as a partner

Study start date: November 20, 2025

Actual date on which the first participant was enrolled.

This study aims to improve the treatment for people with Type 2 diabetes who do not have severe heart failure or advanced kidney disease. Despite existing treatments for diabetes, many patients still face risks of heart and kidney complications. This research explores how analyzing proteins in urine samples can predict which treatments will best prevent these complications. By understanding different protein patterns, the study seeks to personalize treatment plans using specific medications like dapagliflozin, finerenone, and semaglutide, which have shown potential benefits for heart and kidney health. Participants will provide urine samples, which are analyzed to identify certain protein patterns linked to disease risks. These patterns help predict how well a person might respond to different medications. The study involves taking one of three medications—dapagliflozin, finerenone, or semaglutide—over six months, with doses adjusted based on urine test results. The main goal is to see if this approach of using urine protein analysis to guide treatment decisions is practical. The study also evaluates changes in specific urine markers and protein patterns after treatment to measure effectiveness.

Official TitleSIGNAL - Body Fluid Proteome SIGnatures for persoNALised Intervention to Prevent Cardiovascular and Renal Complications in Diabetes
NCT06954090
Principal SponsorSteno Diabetes Center Copenhagen
Last updated: January 28, 2026
Sourced from a government-validated database.Claim as a partner

Protocol

This section provides details of the study plan, including how the study is designed and what the study is measuring.
Design Details

50 patients to be enrolled

Total number of participants that the clinical trial aims to recruit.

Other Study

Some studies explore topics that don't fall into a specific category. These might include innovative research, new technologies, or emerging healthcare areas.


Eligibility

Researchers look for people who fit a certain description, called eligibility criteria: person's general health condition or prior treatments.
Conditions
Criteria

Any sex

Biological sex of participants that are eligible to enroll.

Over 18 Years

Range of ages for which participants are eligible to join.

Healthy volunteers not allowed

If individuals who are healthy and do not have the condition being studied can participate.

Conditions

Pathology

Urogenital DiseasesAlbuminuriaFemale Urogenital Diseases and Pregnancy ComplicationsProteinuriaSigns and SymptomsPathological Conditions, Signs and SymptomsUrination DisordersUrologic DiseasesUrological ManifestationsFemale Urogenital DiseasesMale Urogenital Diseases

Criteria

Inclusion Criteria: 1. Men and women over 18 years of age. 2. Type 2 diabetes with no clinical signs of HF NYHA Class IV 3. Able to understand the written participant information and give informed consent. Exclusion Criteria: 1. Heart failure NYHA class IV at screening 2. Moderately - or severely increased albuminuria with a UACR ≥ 200 mg/g or CKD with an eGFR \< 30 ml/min/1.73m2 at the screening visit. 3. A female who is pregnant, breastfeeding, or intends to become pregnant, or women of childbearing potential (WOCBP) who are not using highly effective contraceptive methods. 4. Receiving therapy with all three of the study medication prior to enrolment. 5. Myocardial infarction, unstable angina, stroke, or transient ischemic attack within 12 weeks prior to enrolment 6. Known or suspected hypersensitivity to the study medications or related products 7. History of pancreatitis at the screening visit 8. Body mass index \< 18.5 kg/m2 at the screening visit 9. Type 1 diabetes 10. Serum potassium \> 5.0 mmol/L at the screening visit 11. Addison's Disease 12. Concomitant treatment with strong CYP3A4 inhibitors (e.g., itraconazole, ketoconazole, ritonavir, nelfinavir, cobicistat, clarithromycin, telithromycin, nefazodone) 13. Treatment with a potassium-sparing diuretic (amiloride, triamterene) 14. Treatment with other mineralocorticoid receptor antagonist than finerenone (e.g., spironolactone, eplerenone, esaxerenone, canrenone) 15. Elevated Alanine Aminotransferase (ALT) \> 3x upper normal limit, autoimmune hepatitis, and/or severe hepatic impairment (including but not limited to a history of hepatic encephalopathy, a history of oesophageal varices or a history of portocaval shunt.) 16. Autosomal dominant or autosomal recessive polycystic kidney disease 17. Lupus nephritis or ANCA-associated vasculitis, or any other primary or secondary kidney disease requiring immunosuppressive therapy within 6 months prior to screening 18. Kidney transplant or dialysis 19. Presence or history of malignant neoplasms (except basal cell skin cancer or squamous cell skin cancer) within five years before screening. 20. Any other history, condition, therapy, or uncontrolled intercurrent illness that could, as judged by the investigator, affect participant safety or compliance with study requirements. 21. Known or suspected abuse of narcotics. 22. Participant in another intervention study, 23. Vulnerable (i.e., under guardianship) or mentally incapacitated subjects (i.e., not able to understand and sign the informed consent)

Study Plan

Find out more about all the medication administered in this study, their detailed description and what they involve.
Treatment Groups
Study Objectives

3 intervention groups are designated in this study

This study does not include a placebo group 

Treatment Groups

Group I

Active Comparator
3 urine proteomic risk scores will be measured in the study. The CKD273 urine proteomic risk score, a well-established tool used to predict the risk of chronic kidney disease (CKD) progression, CAD160 urine proteomic risk score to predict the risk of coronary artery disease (CAD) and HF2 urine proteomic classifier to predict the risk of heart failure (HF). In addition a Support Vector Machine (SVM), a supervised machine learning algorithm will perform in silico treatment simulations and calculate the change in classification scores for 3 different potential interventions: GLP1-RA semaglutide, SGT2-i dapagliflozin and GLP1-RA finerenone. Based on these changes (with the largest beneficial change indicating the most effective treatment), the most suitable intervention can be selected and the participent will be allocated.

Group II

Active Comparator
3 urine proteomic risk scores will be measured in the study. The CKD273 urine proteomic risk score, a well-established tool used to predict the risk of chronic kidney disease (CKD) progression, CAD160 urine proteomic risk score to predict the risk of coronary artery disease (CAD) and HF2 urine proteomic classifier to predict the risk of heart failure (HF). In addition a Support Vector Machine (SVM), a supervised machine learning algorithm will perform in silico treatment simulations and calculate the change in classification scores for 3 different potential interventions: GLP1-RA semaglutide, SGT2-i dapagliflozin and GLP1-RA finerenone. Based on these changes (with the largest beneficial change indicating the most effective treatment), the most suitable intervention can be selected and the participent will be allocated.

Group III

Active Comparator
3 urine proteomic risk scores will be measured in the study. The CKD273 urine proteomic risk score, a well-established tool used to predict the risk of chronic kidney disease (CKD) progression, CAD160 urine proteomic risk score to predict the risk of coronary artery disease (CAD) and HF2 urine proteomic classifier to predict the risk of heart failure (HF). In addition a Support Vector Machine (SVM), a supervised machine learning algorithm will perform in silico treatment simulations and calculate the change in classification scores for 3 different potential interventions: GLP1-RA semaglutide, SGT2-i dapagliflozin and GLP1-RA finerenone. Based on these changes (with the largest beneficial change indicating the most effective treatment), the most suitable intervention can be selected and the participent will be allocated.

Study Objectives

Primary Objectives

Secondary Objectives

Study Centers

These are the hospitals, clinics, or research facilities where the trial is being conducted. You can find the location closest to you and its status.

This study has 1 location

Suspended

Steno Diabetes Center Copenhagen

Herlev, DenmarkOpen Steno Diabetes Center Copenhagen in Google Maps
Enrolling by invitationOne Study Center