BrainAgeMS is a prospective, single-center, cross-sectional comparative study protocol designed to determine whether multipool Chemical Exchange Saturation Transfer (CEST) and T1 relaxometry at 7T can serve as biologically grounded imaging markers of brain age in healthy adults and people with multiple sclerosis.
Key Findings
Background
Biological brain aging can diverge substantially from chronological aging, particularly in chronic neurological conditions like multiple sclerosis, where neuroinflammatory and neurodegenerative processes may accelerate age-related brain changes.
The study rationale is based on the premise that MS involves both neuroinflammatory and neurodegenerative processes that may accelerate age-related brain changes.
Brain age gap is defined as the difference between estimated brain age and chronological age.
The study also introduces a second brain age gap: the difference between estimated brain age and biological age as measured by PhenoAge.
Methods
The BrainAgeMS study (NCT06221631) is a prospective, single-center, cross-sectional comparative study recruiting 200 participants aged 18-65 years.
The study recruits 100 healthy controls (HC) and 100 people with multiple sclerosis (pwMS).
All participants are aged 18-65 years.
The study is registered at ClinicalTrials.gov with identifier NCT06221631.
The design is described as prospective, single-center, and cross-sectional.
Methods
All participants undergo 7T MRI featuring multipool Chemical Exchange Saturation Transfer (CEST) and T1 relaxometry as the primary imaging modalities.
7T MRI is used to acquire multipool CEST and T1 relaxometry data.
These modalities are proposed as 'biologically grounded imaging markers of brain age.'
A brain age prediction model will be trained on healthy control data and then applied to pwMS to derive brain age gaps.
Methods
Biological age is determined using the PhenoAge algorithm applied to blood samples collected from all participants.
Blood sampling is performed on all 200 participants.
The PhenoAge algorithm is used to calculate biological age from blood-based biomarkers.
PhenoAge serves as the basis for the second primary outcome: the brain age gap between estimated brain age and biological age.
Methods
The primary outcomes of BrainAgeMS are two brain age gaps in pwMS: the differences between estimated brain age and (i) chronological age and (ii) PhenoAge.
Both gaps are calculated by subtracting the respective reference age (chronological or PhenoAge) from the MRI-estimated brain age.
Secondary outcomes include associations of these brain age gaps with disability, cognition, fatigue, and quality of life in pwMS.
Motor, cognitive, and psychological assessments are conducted on all participants as part of the multimodal evaluation.
Conclusions
If validated, the quantitative MRI markers are proposed to complement existing tools for MS disease monitoring and serve as outcome measures for future brain health interventions.
The authors state these markers 'could complement existing tools for MS disease monitoring.'
The markers are also proposed to 'serve as outcome measures for future brain health interventions.'
This study is a protocol paper and does not yet report clinical or imaging results.
What This Means
This paper describes the design and protocol for a study called BrainAgeMS, which aims to find out whether a specialized type of brain MRI scan can reveal how fast the brain is aging in people with multiple sclerosis (MS). The idea is that the brain's biological age — how old it actually seems based on its tissue properties — may be older than a person's actual calendar age, especially in MS, where inflammation and nerve damage could speed up aging. The study plans to recruit 100 people with MS and 100 healthy adults, all aged 18 to 65, and scan them using a powerful 7-Tesla MRI machine with advanced imaging techniques called CEST and T1 relaxometry. Participants will also have blood drawn to calculate their biological age using a method called PhenoAge, and they will complete tests of movement, thinking, and psychological wellbeing.
The researchers will use the healthy participants' brain scans to build a model that predicts brain age from the MRI data, then apply that model to the MS group to see how much their estimated brain age differs from both their calendar age and their blood-based biological age. These differences — called 'brain age gaps' — are the main outcomes the study is looking for. The researchers will also examine whether larger brain age gaps are linked to worse disability, cognitive problems, fatigue, or reduced quality of life in people with MS.
This research suggests that combining advanced MRI techniques with biological age measurements could provide a more complete picture of how MS affects the brain over time. If the approach is validated, it could offer doctors a new tool for tracking MS progression and evaluating whether treatments or lifestyle interventions help slow brain aging. As of this publication, the study protocol has been registered but results have not yet been reported.
Navarrete S, Capiglioni M, Marti S, Pirpamer L, McKinley R, Hoepner R, et al.. (2026). BrainAgeMS: protocol for a prospective comparative study of brain aging in healthy adults and people with multiple sclerosis.. Frontiers in neurology. https://doi.org/10.3389/fneur.2026.1899641