- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04593082
Obesity and Pediatric Multiple Sclerosis
April 27, 2026 updated by: J. Nicholas Brenton, MD, University of Virginia
Obesity as a Driver of Inflammation and Brain Volume Loss in Pediatric Multiple Sclerosis.
Obesity is one possible contributor to severity of multiple sclerosis and progression of the disease.
We already know that obesity is a risk determinant for acquiring MS, yet the impact of obesity on pediatric MS disease expression and course is unknown.
This study will evaluate the relationship between obesity, obesity-derived inflammatory mediators, and imaging metrics of MS severity in children.
Understanding how childhood obesity contributes to MS severity/progression may yield fundamental insights into disease pathobiology - which may thereby lead to effective strategies for halting its progression in its earliest stages.
Study Overview
Status
Active, not recruiting
Conditions
Study Type
Observational
Enrollment (Estimated)
116
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Locations
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Pennsylvania
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Philadelphia, Pennsylvania, United States, 19104
- Children's Hospital of Philadelphia
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Virginia
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Charlottesville, Virginia, United States, 22903
- University of Virginia
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Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
10 years to 20 years (Child, Adult)
Accepts Healthy Volunteers
Yes
Sampling Method
Non-Probability Sample
Study Population
The study population will be draw from outpatient clinics at UVA and CHOP as well as the surrounding communities for each institution.
Subjects will be screened for eligibility to include BMI measurements at time of study discussion if they are interested.
Description
Pediatric MS subjects will meet below inclusion and exclusion criteria:
Inclusion Criteria:
- Ability to provide informed consent (or assent for minors)
- Relapsing-remitting MS diagnosis per 2017 McDonald criteria
- Ages ≥ 10 years to ≤ 20 years
- Diagnosis of MS or first clinical symptom of MS (whichever comes first) within ≤ 36 months from the time of enrollment.
Exclusion Criteria:
- Progressive form of MS
- Patients with an active, chronic disease of the immune system other than MS
- Conditions affecting the central nervous system (CNS) white matter (e.g. leukodystrophy) or for whom another condition may better explain imaging abnormalities (e.g. lupus)
- Myelin oligodendrocyte glycoprotein (MOG) antibodies on serologic testing
- Corticosteroid exposure within 30 days of study enrollment
Control subjects (Aim 2) will meet the below inclusion and exclusion criteria:
Inclusion Criteria:
- Ability to provide informed consent (or assent for minors)
- Age-, sex-, & BMI-matched to pediatric MS subjects (1:1 allocation)
- Healthy children and young adults from the local communities
Exclusion Criteria:
- History of past imaging or neurologic event raising concern for any inflammatory CNS process
- Medical history or previous/current diagnosis consistent with an autoimmune disorder pertaining to any system of the body (e.g. diabetes mellitus type 1, Crohn's disease, lupus)
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
- Observational Models: Case-Control
- Time Perspectives: Cross-Sectional
Cohorts and Interventions
Group / Cohort |
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Pediatric MS Subjects
Subjects with pediatric MS will undergo fasting lab work, non-contrasted MRI, DEXA scan, and surveys.
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Healthy controls
Non-MS pediatric control subjects who will undergo fasting lab work, DEXA scan, and surveys for comparison to control group.
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Whole brain volumes and focal demyelinating lesion volumes
Time Frame: 3 years
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58 patients with a recent MS diagnosis, stratified by weight category (29 normal weight and 29 overweight/obese).
Subjects will undergo MRI to quantify total brain and lesion volume.
Z-scores for volumetrics will be determined using age- and sex-matched normative data from the NIH-sponsored ABCD dataset.
We will compare mean Z-scores of whole brain volume and focal demyelinating lesion volumes between the two groups.
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3 years
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Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Adipo-cytokine profiles
Time Frame: 3 years
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Fasting adipo-cytokines from MS cohort will be compared to age-, sex-, and BMI-matched controls.
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3 years
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Adipo-cytokines correlation with brain volume loss and neuroaxonal injury
Time Frame: 3 years
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We will measure serum NfL in MS subjects and controls.
We will determine if leptin (a pro-inflammatory adipo-cytokine) predicts degree of brain volume loss and/or neuroaxonal injury in subjects with MS.
This exploratory, mechanistic aim has potential to provide the first link between obesity-derived inflammation and neuronal cell injury/loss.
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3 years
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Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Collaborators
Investigators
- Principal Investigator: J Nicholas Brenton, MD, University of Virginia
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology. 1983 Nov;33(11):1444-52. doi: 10.1212/wnl.33.11.1444.
- Brenton JN, Koenig S, Goldman MD. Vitamin D status and age of onset of demyelinating disease. Mult Scler Relat Disord. 2014 Nov;3(6):684-8. doi: 10.1016/j.msard.2014.07.004. Epub 2014 Jul 28.
- Woolbright EB, Brenton JN. Attitudes toward obestity and diet modification in pediatric MS patients. Americas Committee for Treatment and Research in Multiple Sclerosis (ACTRIMS); February, 28 2020, 2019; West Palm Beach, FL.
- Brenton JN, Woolbright E, Briscoe-Abath C, Qureshi A, Conaway M, Goldman MD. Body mass index trajectories in pediatric multiple sclerosis. Dev Med Child Neurol. 2019 Nov;61(11):1289-1294. doi: 10.1111/dmcn.14233. Epub 2019 Apr 5.
- Centers for Disease Control. Healthy Weight. In. Vol 20162015
- Disanto G, Barro C, Benkert P, Naegelin Y, Schadelin S, Giardiello A, Zecca C, Blennow K, Zetterberg H, Leppert D, Kappos L, Gobbi C, Kuhle J; Swiss Multiple Sclerosis Cohort Study Group. Serum Neurofilament light: A biomarker of neuronal damage in multiple sclerosis. Ann Neurol. 2017 Jun;81(6):857-870. doi: 10.1002/ana.24954.
- Chitnis T, Gonzalez C, Healy BC, Saxena S, Rosso M, Barro C, Michalak Z, Paul A, Kivisakk P, Diaz-Cruz C, Sattarnezhad N, Pierre IV, Glanz BI, Tomic D, Kropshofer H, Haring D, Leppert D, Kappos L, Bakshi R, Weiner HL, Kuhle J. Neurofilament light chain serum levels correlate with 10-year MRI outcomes in multiple sclerosis. Ann Clin Transl Neurol. 2018 Oct 16;5(12):1478-1491. doi: 10.1002/acn3.638. eCollection 2018 Dec.
- Barro C, Benkert P, Disanto G, Tsagkas C, Amann M, Naegelin Y, Leppert D, Gobbi C, Granziera C, Yaldizli O, Michalak Z, Wuerfel J, Kappos L, Parmar K, Kuhle J. Serum neurofilament as a predictor of disease worsening and brain and spinal cord atrophy in multiple sclerosis. Brain. 2018 Aug 1;141(8):2382-2391. doi: 10.1093/brain/awy154.
- Siller N, Kuhle J, Muthuraman M, Barro C, Uphaus T, Groppa S, Kappos L, Zipp F, Bittner S. Serum neurofilament light chain is a biomarker of acute and chronic neuronal damage in early multiple sclerosis. Mult Scler. 2019 Apr;25(5):678-686. doi: 10.1177/1352458518765666. Epub 2018 Mar 15.
- Kuhle J, Nourbakhsh B, Grant D, Morant S, Barro C, Yaldizli O, Pelletier D, Giovannoni G, Waubant E, Gnanapavan S. Serum neurofilament is associated with progression of brain atrophy and disability in early MS. Neurology. 2017 Feb 28;88(9):826-831. doi: 10.1212/WNL.0000000000003653. Epub 2017 Feb 1.
- Valcarcel AM, Linn KA, Vandekar SN, Satterthwaite TD, Muschelli J, Calabresi PA, Pham DL, Martin ML, Shinohara RT. MIMoSA: An Automated Method for Intermodal Segmentation Analysis of Multiple Sclerosis Brain Lesions. J Neuroimaging. 2018 Jul;28(4):389-398. doi: 10.1111/jon.12506. Epub 2018 Mar 8.
- Hagler DJ Jr, Hatton S, Cornejo MD, Makowski C, Fair DA, Dick AS, Sutherland MT, Casey BJ, Barch DM, Harms MP, Watts R, Bjork JM, Garavan HP, Hilmer L, Pung CJ, Sicat CS, Kuperman J, Bartsch H, Xue F, Heitzeg MM, Laird AR, Trinh TT, Gonzalez R, Tapert SF, Riedel MC, Squeglia LM, Hyde LW, Rosenberg MD, Earl EA, Howlett KD, Baker FC, Soules M, Diaz J, de Leon OR, Thompson WK, Neale MC, Herting M, Sowell ER, Alvarez RP, Hawes SW, Sanchez M, Bodurka J, Breslin FJ, Morris AS, Paulus MP, Simmons WK, Polimeni JR, van der Kouwe A, Nencka AS, Gray KM, Pierpaoli C, Matochik JA, Noronha A, Aklin WM, Conway K, Glantz M, Hoffman E, Little R, Lopez M, Pariyadath V, Weiss SR, Wolff-Hughes DL, DelCarmen-Wiggins R, Feldstein Ewing SW, Miranda-Dominguez O, Nagel BJ, Perrone AJ, Sturgeon DT, Goldstone A, Pfefferbaum A, Pohl KM, Prouty D, Uban K, Bookheimer SY, Dapretto M, Galvan A, Bagot K, Giedd J, Infante MA, Jacobus J, Patrick K, Shilling PD, Desikan R, Li Y, Sugrue L, Banich MT, Friedman N, Hewitt JK, Hopfer C, Sakai J, Tanabe J, Cottler LB, Nixon SJ, Chang L, Cloak C, Ernst T, Reeves G, Kennedy DN, Heeringa S, Peltier S, Schulenberg J, Sripada C, Zucker RA, Iacono WG, Luciana M, Calabro FJ, Clark DB, Lewis DA, Luna B, Schirda C, Brima T, Foxe JJ, Freedman EG, Mruzek DW, Mason MJ, Huber R, McGlade E, Prescot A, Renshaw PF, Yurgelun-Todd DA, Allgaier NA, Dumas JA, Ivanova M, Potter A, Florsheim P, Larson C, Lisdahl K, Charness ME, Fuemmeler B, Hettema JM, Maes HH, Steinberg J, Anokhin AP, Glaser P, Heath AC, Madden PA, Baskin-Sommers A, Constable RT, Grant SJ, Dowling GJ, Brown SA, Jernigan TL, Dale AM. Image processing and analysis methods for the Adolescent Brain Cognitive Development Study. Neuroimage. 2019 Nov 15;202:116091. doi: 10.1016/j.neuroimage.2019.116091. Epub 2019 Aug 12.
- Kerbrat A, Aubert-Broche B, Fonov V, Narayanan S, Sled JG, Arnold DA, Banwell B, Collins DL. Reduced head and brain size for age and disproportionately smaller thalami in child-onset MS. Neurology. 2012 Jan 17;78(3):194-201. doi: 10.1212/WNL.0b013e318240799a. Epub 2012 Jan 4.
- Brenton JN, Koshiya H, Engel CE, Herrod S, Engelhard M, Goldman MD. Utility of Physical Disability Outcome Measures in Pediatric-Onset Multiples Sclerosis. American Academy of Neurology. 2017.
- Brenton JN, Koshiya H, Woolbright E, Goldman MD. The Multiple Sclerosis Functional Composite and Symbol Digit Modalities Test as outcome measures in pediatric multiple sclerosis. Mult Scler J Exp Transl Clin. 2019 Apr 29;5(2):2055217319846141. doi: 10.1177/2055217319846141. eCollection 2019 Apr-Jun.
- Brenton JN, Woolbright E, Koshiya H, Engelhard M, Goldman MD. Continuous accelerometry as a measure of physical activity impairment in paediatric-onset multiple sclerosis subjects versus healthy controls. ECTRIMS Online Library. 2017
- Keyhanian K, Saxena S, Gombolay G, Healy BC, Misra M, Chitnis T. Adipokines are associated with pediatric multiple sclerosis risk and course. Mult Scler Relat Disord. 2019 Nov;36:101384. doi: 10.1016/j.msard.2019.101384. Epub 2019 Sep 5.
- Castro K, Ntranos A, Amatruda M, Petracca M, Kosa P, Chen EY, Morstein J, Trauner D, Watson CT, Kiebish MA, Bielekova B, Inglese M, Katz Sand I, Casaccia P. Body Mass Index in Multiple Sclerosis modulates ceramide-induced DNA methylation and disease course. EBioMedicine. 2019 May;43:392-410. doi: 10.1016/j.ebiom.2019.03.087. Epub 2019 Apr 10.
- Stampanoni Bassi M, Iezzi E, Buttari F, Gilio L, Simonelli I, Carbone F, Micillo T, De Rosa V, Sica F, Furlan R, Finardi A, Fantozzi R, Storto M, Bellantonio P, Pirollo P, Di Lemme S, Musella A, Mandolesi G, Centonze D, Matarese G. Obesity worsens central inflammation and disability in multiple sclerosis. Mult Scler. 2020 Sep;26(10):1237-1246. doi: 10.1177/1352458519853473. Epub 2019 Jun 4.
- Shinohara RT, Sweeney EM, Goldsmith J, Shiee N, Mateen FJ, Calabresi PA, Jarso S, Pham DL, Reich DS, Crainiceanu CM; Australian Imaging Biomarkers Lifestyle Flagship Study of Ageing; Alzheimer's Disease Neuroimaging Initiative. Statistical normalization techniques for magnetic resonance imaging. Neuroimage Clin. 2014 Aug 15;6:9-19. doi: 10.1016/j.nicl.2014.08.008. eCollection 2014.
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Actual)
June 3, 2021
Primary Completion (Estimated)
May 21, 2026
Study Completion (Estimated)
June 1, 2027
Study Registration Dates
First Submitted
October 16, 2020
First Submitted That Met QC Criteria
October 16, 2020
First Posted (Actual)
October 19, 2020
Study Record Updates
Last Update Posted (Actual)
April 29, 2026
Last Update Submitted That Met QC Criteria
April 27, 2026
Last Verified
April 1, 2026
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
- Nervous System Diseases
- Pathologic Processes
- Nutrition Disorders
- Overnutrition
- Body Weight
- Autoimmune Diseases
- Immune System Diseases
- Demyelinating Autoimmune Diseases, CNS
- Autoimmune Diseases of the Nervous System
- Demyelinating Diseases
- Overweight
- Pathological Conditions, Signs and Symptoms
- Nutritional and Metabolic Diseases
- Signs and Symptoms
- Obesity
- Multiple Sclerosis
- Inflammation
- Nerve Degeneration
Other Study ID Numbers
- HSR200257
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
UNDECIDED
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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