Diabetes Complications, Diabetes Mellitus, Type 1, Diabetic Nephropathies
Conditions
Brief summary
Background: Today diabetic nephropathy is a frequent, and the most lethal and costly complication of diabetes. Although treating blood pressure with agents blocking renin angiotensin system has improved outcome, the prognosis is still poor and no new interventions have been successful during the past decade. There is an urgent need for discovery of new pathways behind the development and progression of diabetic nephropathy as well as of biomarkers which can identify subjects at risk of developing adverse events. Objective: By using a multidimensional 'omics' approach, we aim to search for novel proteins, metabolites and pathways that will point to the putative new mechanisms which underlie the early renal decline. Design: Cross-sectional study, with long-term register-based follow-up. Study population: 160 patients with type 1 diabetes recruited from Steno Diabetes Center Copenhagen stratified based on stage of diabetic kidney disease, and 50 healthy non-diabetic controls. Endpoints: Primary endpoint: Glycocalyx thickness, assessed as perfused boundary region. Secondary endpoints: Gut microbiome characterisation and markers of gastrointestinal inflammation, autonomic and periphery neuropathy, urine and plasma Flow Cytometry Analysis (FACS), metabolomics and proteomics in plasma and urine, and other potential biomarkers.
Detailed description
Design: Cross-sectional study, with long-term register-based follow-up. Study population: 160 patients with type 1 diabetes recruited from Steno Diabetes Center Copenhagen stratified based on stage of diabetic kidney disease, and 50 healthy non-diabetic controls. Endpoints: Primary endpoint: Glycocalyx thickness, assessed as perfused boundary region. Secondary endpoints: Gut microbiome characterisation and markers of gastrointestinal inflammation, autonomic and periphery neuropathy, urine and plasma Flow Cytometry Analysis (FACS), metabolomics and proteomics in plasma and urine, and other potential biomarkers.
Interventions
None listed
Sponsors
Peter Rossing
Study design
Observational model
COHORT
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* Patients with type 1 diabetes * Written informed consent must be provided before participation * Male or female patients \>18 years of age with a diagnosis of type 1 diabetes (WHO criteria) * Persistent urinary albumin creatinine ratio (UACR) assessed from EPJ (Electronic Patient Journal): * \< 30 mg/g in 2 out of 3 consecutive samples (normoalbuminuria) * 30 - 299 mg/g in 2 out of 3 consecutive samples (microalbuminuria) * ≥ 300 mg/g in 2 out of 3 consecutive samples (macroalbuminuria) - at least 30 with concurrent eGFR \< 60 ml/min/1.73m2 2\. Control subjects without diabetes * Written informed consent must be provided before participation. * Male or female patients \>18 years of age without a diagnosis of diabetes (assessed by Hb1Ac, haemoglobin and creatinine)
Exclusion criteria
(Both subjects with and without diabetes) * Non-diabetic kidney disease as indicated by medical history and/or laboratory findings * Renal failure (eGFR\<15 ml/min/1.73m2), dialysis or kidney transplantation * Change in RAAS blocking treatment during the last month * Treatment with antibiotics during the last 2 month * Pregnancy or breastfeeding (urine HCG is performed on all fertile women) * Patients who, in the judgement of the investigator, is incapable to participate * For controls: Other diseases or intake of medicine which in the judgement of the investigator could affect the results, specifically renal, cardiovascular or inflammatory/infectious diseases should be considered for exclusion
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| The microvascular function by estimating the glycocalyx thickness | 2019 | Glycocalyx thickness assessed as perfused boundary region by a hand-hold camera (GlycoCheck) |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Urine and plasma Flow Cytometry Analysis (FACS) | 2019 | cell types related to inflammation |
| Metabolomics in plasma | 2019 | metabolite risk score in plasma |
| Metabolomics in urine | 2019 | metabolite risk score in urine |
| Gut microbiome | 2019 | Characterisation of the gut microbiota and markers of gastrointestinal inflammation |
| proteomics in plasma | 2019 | proteomic risk score in plasma |
| Autonomic neuropathy | 2019 | beat to beat variation (R-R test) upon Deep breathing |
| peripheral neuropathy | 2019 | vibration perception threshold |
| proteomics in urine | 2019 | proteomic risk score in urine |
Countries
Denmark
Outcome results
None listed