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| ID | Type | Description | Link |
|---|---|---|---|
| H-25045491 | Other Identifier | Health Ethics Committee of Copenhagen |
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| Name | Class |
|---|---|
| Steno Diabetes Center Copenhagen | OTHER |
| University of Ulm | OTHER |
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People with diabetes are at increased risk of developing dementia, including Alzheimer's disease and vascular dementia. In addition, persons with diabetes have more pronounced age-related brain atrophy and cognitive difficulties compared to people without diabetes. The mechanisms behind the effects on the brain of diabetes are still unclear. New research suggests that the brains of some people with diabetes do not respond normally to insulin signals, a condition known as brain insulin resistance (BIR). To date, there have been no large clinical studies investigating BIR and its impact on brain health, but several smaller studies suggest that BIR may be a cause of cognitive decline and impaired brain health in people with diabetes. Another mechanism that may contribute to impaired brain health in people with diabetes is damage to the blood vessels in the brain. Damage to blood vessels is a well-known complication of diabetes, but how it affects the brain is not fully described. In this project, we will investigate the relationship between BIR and brain blood vessel dysfunction and its relationship to cognition and brain function. This is done by examining patients with type 1 diabetes (T1D), type 2 diabetes (T2D) and healthy controls. The participants will undergo MRI brain scans to assess the impact of BIR on the brain physiology and to evaluate brain blood vessel health. Participants will undergo comprehensive assessments of their cognitive abilities and thorough health examination.
The BIR-BrainHealth project investigates the role of brain insulin resistance (BIR) as a key mechanism linking diabetes to cognitive decline and dementia risk. By combining cognitive testing with advanced neuroimaging (MRI and PET), metabolic profiling, and multi-omics analyses, the study aims to uncover how BIR affects brain physiology, energy metabolism, and neurovascular function. The present trial registration specifically covers the MRI components of the project and does not include PET imaging.
Diabetes significantly increases the risk of mild cognitive impairment and dementia. The exact link between diabetes and cognitive decline is yet to be fully understood. Early cognitive decline in diabetes suggests a unique pathogenetic trajectory. One hypothesized mechanism involves impaired insulin signaling/transport in the brain, referred to as brain insulin resistance (BIR). Evidence indicates that in some individuals with diabetes, neuronal insulin signaling is abnormal, resulting in dysregulated cerebral metabolism and function. Another possible pathway is cerebrovascular pathology, which may compromise cerebral perfusion and energy metabolism. The present project will investigate the relationship between BIR and cerebrovascular dysfunction, and their impact on cognition and brain function.
We will set up a multicenter study in Denmark and Germany. Initially the study will include 50 participants with type 1 diabetes, 50 participants with type 2 diabetes, and 50 control participants without diabetes. All participants will undergo a comprehensive clinical evaluation to characterize diabetes duration, severity, and systemic comorbidities. The cognitive performance of the participants will be assessed using a neuropsychological test battery of following standardized tests:
Tests will be grouped by cognitive domains, and each domain score is calculated as the mean of the individual component z-scores. A cognitive composite (global score) will be derived from the mean of the domains: learning and memory, executive function and working memory, processing speed, and attention.
Magnetic resonance imaging (MRI) will be performed to assess BIR and structural brain changes, including atrophy. All MRI-scans will be performed on a research-optimized 3 Tesla MRI scanner. BIR will be evaluated by measuring changes in cerebral perfusion from administration of intranasal insulin delivered via nasal spray.
Blood, urine and stool will be collected for biomarker development and characterization of patients with BIR. A multi-omics approach will be applied to identify reliable biomarkers of BIR, incorporating lipidomics, metabolomics, proteomics, and transcriptomics. Lipidomic analysis will quantify approximately 650 lipid species, including phospholipids, lysophos-pholipids, ceramides, sphingolipids, diacylglycerols, and triacylglycerols, using liquid chromatography-mass spectrometry. Metabolomic profiling will measure approximately 300 metabolites, including citric acid cycle intermediates, short-chain fatty acids, ketones, and amino acids, using gas chromatography-mass spectrometry. Proteomic analysis will be conducted using a validated, clinically applicable mass spectrometry method, and transcriptomic profiling will be performed using RNA-based methods. The participants will be genotyped using the Illumina Infinium Global Screening Array (GSA v2.4), with exclusion of rare variants and clinically relevant mutations listed by the American College of Medical Genetics, in accordance with the guidelines of the National Science Ethics Committee on genomic research.
A subset of participants will undergo additional advanced MRI-scanning for assessments of cerebro-vascular function. Brain perfusion, blood-brain barrier integrity, and capillary perfusion distribution will be measured using dynamic contrast-enhanced MRI. Cerebrovascular reactivity will be measured by perfusion-weighted MRI during inhalation of air enriched with 5% CO2, a potent cerebral vasodilator. Cerebral blood flow responses to neuronal activation induced by visual stimulation will be assessed using perfusion-weighted MRI. Lastly, in a subset of participants the brain glucose sensing will be assessed using functional MRI (fMRI). fMRI will be measured prior to, during and following oral ingestion of water containing 75 grams of glucose. The glucose drink is given through a straw while the participants are lying in the scanner and will be consumed over a period of 5 minutes. Blood samples will be collected throughout the scan for measurements of blood glucose.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Type 1 Diabetes | Individuals who have a type 1 diabetes diagnose and meet the inclusion and exclusion criteria. | ||
| Type 2 Diabetes | Individuals who have a type 2 diabetes diagnose and meet the inclusion and exclusion criteria. | ||
| Controls | Individuals who do not have a diabetes diagnose and meet the inclusion and exclusion criteria. |
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| Measure | Description | Time Frame |
|---|---|---|
| Correlation between brain insulin response and cognitive measures | Brain insulin response is assessed by measuring changes in cerebral blood flow following intranasal insulin administration, using arterial spin labelling (ASL) MRI. The neuropsychological test battery includes the following:
Motor function (Grooved Pegboard) Montreal Cognitive Assessment (MoCA) | Baseline (only measured once) |
| Correlation between cerebrovascular reactivity and cognitive measures | Cerebrovascular reactivity is assessed by measuring changes in cerebral blood flow responses to inhalation of hypercapnic air (air enriched with 5% CO2). Cerebral blood flow is measured using combined blood-oxygen-level-dependent (BOLD) MRI, ASL MRI, and phase contrast mapping (PCM) MRI. The neuropsychological test battery includes the following:
Motor function (Grooved Pegboard) Montreal Cognitive Assessment (MoCA) | Baseline (only measured once) |
| Measure | Description | Time Frame |
|---|---|---|
| Blood-brain-barrier permability | Differences in blood-brain-barrier permeability between groups, measured by dynamic contrast enhanced MRI. | Baseline (only measured once) |
| Neurovascular coupling |
| Measure | Description | Time Frame |
|---|---|---|
| Brain insulin response | Differences in brain insulin response between groups, assessed by measuring changes in cerebral blood flow following intranasal insulin administration using ASL MRI. | Baseline (only measured once) |
| Cerebrovascular reactivity |
Inclusion Criteria (all):
Inclusion Criteria (diabetes only):
Exclusion Criteria:
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It is planned to recruit participants in the Greater Copenhagen area in Denmark and the Ulm area in Germany. The participants will be recruited from the outpatient clinic at Steno Diabetes Center Copenhagen and Ulm University Hospital and primary care settings in Denmark and Germany.
In addition to this, participants will be sought by physical advertisements in the local area, through recruitment platforms (join.trialtree.com) and social media.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Henrik BW Larsson, Professor | Contact | +45 24824294 | henrik.bo.wiberg.larsson@regionh.dk |
| Name | Affiliation | Role |
|---|---|---|
| Henrik BW Larsson, Professor | Rigshospitalet, Denmark | Principal Investigator |
| Jørgen Rungby, Professor | Steno Diabetes Center Copenhagen | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Rigshospitalet | Recruiting | Glostrup Municipality | 2600 | Denmark | ||
| Steno Diabetes Center Copenhagen |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 42394131 | Derived | Wangler S, Sorensen P, Kass K, Jensen NJ, Vestergaard MB, Hummel J, Volk R, Antvorskov JC, Pociot F, Rungby J, Heni M, Larsson HBW. Disentangling the effect of brain insulin resistance on brain health (BIR-BrainHealth): Rationale and study protocol. Diabet Med. 2026 Jul 2:e70415. doi: 10.1111/dme.70415. Online ahead of print. |
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| ID | Term |
|---|---|
| D003924 | Diabetes Mellitus, Type 2 |
| D003922 | Diabetes Mellitus, Type 1 |
| D003920 | Diabetes Mellitus |
| D060825 | Cognitive Dysfunction |
| ID | Term |
|---|---|
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
| D004700 | Endocrine System Diseases |
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Blood samples (serum, plasma, buffy coat), urine, and faecal samples are collected and processed by trained personnel and stored at the research biobank at Steno Diabetes Center Copenhagen and at University of Ulm.
Differences in cerebral blood flow responses to visual stimulation between groups, assessed with ASL MRI.
| Baseline (only measured once) |
| Hypothalamic glucose sensing | Differences in cerebral blood flow response in the hypothalamus to glucose ingestion between groups, assessed by combined BOLD and ASL MRI. | Baseline (only measured once) |
Differences in cerebrovascular reactivity between groups, assessed by measuring changes in cerebral blood flow in response to inhalation of hypercapnic air (air enriched with 5% CO2). Cerebral blood flow is measured using combined blood-oxygen-level-dependent (BOLD) MRI, ASL MRI, and phase contrast mapping (PCM) MRI.
| Baseline (only measured once) |
| Brain atrophy and white matter lesion | Differences in brain atrophy and white matter lesion load between groups, assessed by T1- weighted structural MRI and Fluid-Attenuated Inversion Recovery (FLAIR) MRI. | Baseline (only measured once) |
| Correlation between brain atrophy and white matter lesions load and cognitive measures | Brain atrophy and white matter lesion load is assessed by T1- weighted structural MRI and FLAIR MRI. The neuropsychological test battery includes the following:
Motor function (Grooved Pegboard) Montreal Cognitive Assessment (MoCA) | Baseline (only measured once) |
| Cerebral microbleeds | Differences in the amount of cerebral microbleeds between groups, assessed by susceptibility-weighted MRI. | Baseline (only measured once) |
| Correlation between cerebral microbleeds and cognitive measures | Cerebral microbleeds is assessed by susceptibility-weighted MRI. The neuropsychological test battery includes the following:
Motor function (Grooved Pegboard) Montreal Cognitive Assessment (MoCA) | Baseline (only measured once) |
| Structural connectivity | Differences in structural connectivity between groups, assessed by diffusion tensor imaging (DTI) MRI. | Baseline (only measured once) |
| Correlation between structural connectivity and cognitive measures | Structural connectivity is assessed by DTI MRI. The neuropsychological test battery includes the following:
Motor function (Grooved Pegboard) Montreal Cognitive Assessment (MoCA) | Baseline (only measured once) |
| White matter diffusion integrity | Differences in white matter diffusion parameters between groups, assessed by DTI MRI. | Baseline (only measured once) |
| Correlation between white matter diffusion integrity and cognitive measures | White matter diffusion is assessed by DTI MRI. The neuropsychological test battery includes the following:
Motor function (Grooved Pegboard) Montreal Cognitive Assessment (MoCA) | Baseline (only measured once |
| Cerebral blood flow | Differences in resting cerebral blood flow between groups, assessed by ASL and PCM MRI. | Baseline (only measured once) |
| Correlation between resting cerebral blood flow and cognitive measures | Resting cerebral blood flow is assessed by ASL and PCM MRI. The neuropsychological test battery includes the following:
Motor function (Grooved Pegboard) Montreal Cognitive Assessment (MoCA) | Baseline (only measured once) |
| Cerebral metabolic rate of oxygen | Differences in resting cerebral metabolic rate of oxygen between groups, assessed by combined PCM MRI and susceptibility-based oximetry (SBO) MRI. | Baseline (only measured once) |
| Correlation between cerebral metabolic rate of oxygen and cognitive measures | Cerebral metabolic rate of oxygen is assessed by combined PCM MRI and SBO MRI. The neuropsychological test battery includes the following:
Motor function (Grooved Pegboard) Montreal Cognitive Assessment (MoCA) | Baseline (only measured once) |
| Regional brain glucose sensing | Differences in regional cerebral blood flow in response to glucose ingestion between groups, assessed by combined BOLD and ASL MRI. | Baseline (only measured once) |
| Correlation between hypothalamic glucose sensing and biomarkers | Cerebral blood flow response in the hypothalamus to glucose ingestion is assessed by combined BOLD and ASL MRI. A multiomics approach integrating lipidomics, metabolomics, proteomics, transcriptomics, and genotyping will be used to identify reliable biomarkers of brain insulin sensing. | Baseline (only measured once) |
| Correlation between brain insulin response and hypothalamic glucose sensing | Brain insulin response is assessed by measuring changes in cerebral blood flow following administration of intranasal insulin using arterial spin labelling ASL MRI. Cerebral blood flow response in the hypothalamus to glucose ingestion is measured by combined BOLD and ASL MRI. | Baseline (only measured once) |
| Biomarkers of neuronal damage, neuroinflammation, and brain insulin response | Brain insulin response is assessed by measuring changes in cerebral blood flow following administration of intranasal insulin using ASL MRI. A multiomics approach integrating lipidomics, metabolomics, proteomics, transcriptomics, and genotyping will be used to identify biomarkers of neuronal damage, neuroinflammation and brain insulin resistance. | Baseline (only measured once) |
| Biomarkers of blood-brain-barrier integrity and cerebrovascular function | Blood-brain-barrier permeability is assessed by dynamic contrast enhanced MRI A multiomics approach integrating lipidomics, metabolomics, proteomics, transcriptomics, and genotyping will be used to identify biomarkers of vascular function and blood brain barrier integrity. | Baseline (only measured once) |
| Correlation between biomarkers and cognitive measures | A multiomics approach integrating lipidomics, metabolomics, proteomics, transcriptomics, and genotyping will be used to identify biomarkers of cognition. The neuropsychological test battery includes the following:
Motor function (Grooved Pegboard) Montreal Cognitive Assessment (MoCA) | Baseline (only measured once) |
| Flemming Pociot, Professor |
| Steno Diabetes Center Copenhagen |
| Principal Investigator |
| Martin Heni, Professor | University of Ulm | Principal Investigator |
| Recruiting |
| Herlev |
| 2730 |
| Denmark |
| University of Ulm | Recruiting | Ulm | 89081 | Germany |
| D001327 | Autoimmune Diseases |
| D007154 | Immune System Diseases |
| D003072 | Cognition Disorders |
| D019965 | Neurocognitive Disorders |
| D001523 | Mental Disorders |