Multiple Sclerosis
Conditions
Keywords
Brain Aging, Multiple Sclerosis, Neurodegeneration, Quantitative MRI
Brief summary
The purpose of this study is to investigate new quantitative MRI-sequences for assessment of age-specific data for the prediction of brain aging.
Detailed description
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.
Interventions
None listed
Sponsors
Insel Gruppe AG, University Hospital Bern
Schweizerische Multiple Sklerose Gesellschaft
University of Bern
Study design
Observational model
CASE_CONTROL
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
ALL
Age
18 Years to 65 Years
Healthy volunteers
Yes
Inclusion criteria
Informed Consent signed by the subject * Group 1: Any healthy individual between 18 and 65 years of age * Group 2: Any individuals with any diagnosis of Multiple Sclerosis between 18 and 65 years of age and EDSS ≤6.0.
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. * Specific Criteria for group 1: The calculated biological age (BioAge R Package algorithm) differs by \> -8/+1 years from the chronological age. These patients will not be further invited for a study visit with clinical examination and MRI. * Specific Criteria for group 2: EDSS \> 6.0 as this impacts physical testing; clinical relapse within the last 6 months
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Brain Age Gap in patients with MS | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. | Difference between estimated brain age and (A) biological as well as (B) chronological age. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Relationship of brain age gaps with disease severity | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. | 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) |
| Relationship of brain age gaps with gait speed | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. | Relationship of brain age gaps with gait speed as measured by the 25-foot walking test |
| Relationship of brain age gaps with upper extremity function | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. | Relationship of brain age gaps with upper extremity function as measured by the 9-hole Peg Test |
| Relationship of brain age gaps with sitting-to-raise time | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. | Relationship of brain age gaps with a raising test using the sitting-to-raise time |
| Relationship of brain age gaps with cognitive symptoms | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. | Relationship of brain age gaps with cognitive (brief international cognitive assessment in multiple sclerosis (BICAMS)) |
| Relationship of brain age gaps with depression symptoms | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. | Relationship of brain age gaps with depression symptoms as assessed with the brief depression inventory (BDI) |
| Relationship of brain age gaps with fatigue | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. | Relationship of brain age gaps with fatigue as assessed with the fatigue severity score (FSS) |
| Relationship of brain age gaps with quality of life | Up to 2 months after recruitment or finalization of MRI-visit, whichever came first. | Relationship of brain age gaps with experienced quality of life as assessed with the Multiple Sclerosis Impact Scale (MSIS)-29 |
Countries
Switzerland
Contacts
CONTACTAlejandro X. León Betancourt, Dr.med.
CONTACTPiotr Radojewski, Dr.med.
PRINCIPAL_INVESTIGATORRobert Hoepner, PD Dr.med.
Head of the MS outpatient clinic
Outcome results
None listed