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| ID | Type | Description | Link |
|---|---|---|---|
| 10001315 | Other Identifier | Swissmedic | |
| CIV-23-12-045014 | Other Identifier | EUDAMED |
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| Name | Class |
|---|---|
| Schweizerische Multiple Sklerose Gesellschaft | OTHER |
| University of Bern | OTHER |
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The purpose of this study is to investigate new quantitative MRI-sequences for assessment of age-specific data for the prediction of brain aging.
After being informed about the study, healthy controls and patients with multiple sclerosis giving written informed consent will undergo blood examination (for determination of the biological age using the publicly available R-package algorithm BioAge), clinical examination (for motor, cognitive and psychological parameters) as well as an MRI-investigation with chemical exchange saturation transfer (CEST) and T1-relaxometry on a 7 Tesla MRI. Data from the healthy controls will be used to set up a normative brain age data set, that could be used for example to train a model for brain age prediction.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Group 1: Healthy Controls | Healthy individuals with a predefined healthy lifestyle (s. inclusion/exclusion criteria), without any progressive disease or any neurological disorder (aside from primary headaches) | ||
| Group 2: Patients with Multiple Sclerosis | Patients with MS with a similar healthy lifestyle (s. inclusion/exclusion criteria), who are able to walk without more than one-sided walking aid (max. EDSS of 6 points), no relapse activity in the last 6 months, without any other progressive disease or other neurological disorder (aside from primary headaches) |
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| Measure | Description | Time Frame |
|---|---|---|
| Brain Age Gap in patients with MS | Difference between estimated brain age and (A) biological as well as (B) chronological age. | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. |
| Measure | Description | Time Frame |
|---|---|---|
| Relationship of brain age gaps with disease severity | Relationship of brain age gaps with disease severity as measured by the expanded disability and severity scale (EDSS; min.-max. according to eligibility criteria: 0-6 points, with a higher score meaning a higher degree of disease severity) | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. |
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Inclusion Criteria:
Informed Consent signed by the subject
Exclusion Criteria:
Group 1 and 2: Any other neurological disease except primary headaches: insufficient language skills in German or French; pregnancy, lactation, any contraindication for MRI (active implants, passive ferromagnetic implants, passive non-ferromagnetic metallic implants >4cm in the region covered by the active RF coils, large tattoos inside a region covered by the active radiofrequency (RF) coils, claustrophobia or suspected/known non-compliance), smoking within the last 10 years prior recruitment, any other drug consumption except moderate alcohol intake (less than a standard drink containing 10 grams of alcohol per day) or use of medical cannabis, any previous head trauma (with known/suspected intracranial consequences), Body Mass Index (BMI) >30, and any other chronic progressive disease.
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Group 1: recruitment from the general population through advertisement Group 2: recruitment primarily from the outpatient MS consultation in Inselspital
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Alejandro X. León Betancourt, Dr.med. | Contact | +41316326093 | alejandro.betancourt@insel.ch | |
| Piotr Radojewski, Dr.med. | Contact | +41316326093 | piotr.radojewski@insel.ch |
| Name | Affiliation | Role |
|---|---|---|
| Robert Hoepner, PD Dr.med. | Head of the MS outpatient clinic | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Inselspital Bern | Recruiting | Bern | Canton of Bern | 3010 | Switzerland |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 36478417 | Background | Piredda GF, Caneschi S, Hilbert T, Bonanno G, Joseph A, Egger K, Peter J, Kloppel S, Jehli E, Grieder M, Slotboom J, Seiffge D, Goeldlin M, Hoepner R, Willems T, Vulliemoz S, Seeck M, Venkategowda PB, Corredor Jerez RA, Marechal B, Thiran JP, Wiest R, Kober T, Radojewski P. Submillimeter T1 atlas for subject-specific abnormality detection at 7T. Magn Reson Med. 2023 Apr;89(4):1601-1616. doi: 10.1002/mrm.29540. Epub 2022 Dec 7. | |
| 35194865 |
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Individual participants data that underlie results in a publication, after deidentification
Starting 9 months and ending 48 months after publication
Encoded data will be provided only to investigators who provide a methodologically sound proposal to achieve the aims in the approved proposal.
Proposals should be directed to brainage@ikmail.com. To gain access, data requestors will need to sign a data access agreement.
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| ID | Term |
|---|---|
| D009103 | Multiple Sclerosis |
| D009410 | Nerve Degeneration |
| ID | Term |
|---|---|
| D020278 | Demyelinating Autoimmune Diseases, CNS |
| D020274 | Autoimmune Diseases of the Nervous System |
| D009422 | Nervous System Diseases |
| D003711 | Demyelinating Diseases |
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Plasma
| Relationship of brain age gaps with gait speed | Relationship of brain age gaps with gait speed as measured by the 25-foot walking test | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. |
| Relationship of brain age gaps with upper extremity function | Relationship of brain age gaps with upper extremity function as measured by the 9-hole Peg Test | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. |
| Relationship of brain age gaps with sitting-to-raise time | Relationship of brain age gaps with a raising test using the sitting-to-raise time | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. |
| Relationship of brain age gaps with cognitive symptoms | Relationship of brain age gaps with cognitive (brief international cognitive assessment in multiple sclerosis (BICAMS)) | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. |
| Relationship of brain age gaps with depression symptoms | Relationship of brain age gaps with depression symptoms as assessed with the brief depression inventory (BDI) | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. |
| Relationship of brain age gaps with fatigue | Relationship of brain age gaps with fatigue as assessed with the fatigue severity score (FSS) | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. |
| Relationship of brain age gaps with quality of life | Relationship of brain age gaps with experienced quality of life as assessed with the Multiple Sclerosis Impact Scale (MSIS)-29 | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. |
| Background |
| Mennecke A, Khakzar KM, German A, Herz K, Fabian MS, Liebert A, Blumcke I, Kasper BS, Nagel AM, Laun FB, Schmidt M, Winkler J, Dorfler A, Zaiss M. 7 tricks for 7 T CEST: Improving the reproducibility of multipool evaluation provides insights into the effects of age and the early stages of Parkinson's disease. NMR Biomed. 2023 Jun;36(6):e4717. doi: 10.1002/nbm.4717. Epub 2022 Mar 17. |
| 34725754 | Background | Kwon D, Belsky DW. A toolkit for quantification of biological age from blood chemistry and organ function test data: BioAge. Geroscience. 2021 Dec;43(6):2795-2808. doi: 10.1007/s11357-021-00480-5. Epub 2021 Nov 2. |
| D001327 | Autoimmune Diseases |
| D007154 | Immune System Diseases |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |