Associations Between Paramagnetic Rim Lesion Evolution and Clinical and Radiologic Disease Progression in Persons With Multiple Sclerosis.


Journal

Neurology
ISSN: 1526-632X
Titre abrégé: Neurology
Pays: United States
ID NLM: 0401060

Informations de publication

Date de publication:
26 Nov 2024
Historique:
medline: 25 10 2024
pubmed: 25 10 2024
entrez: 24 10 2024
Statut: ppublish

Résumé

Recent technological advances have enabled visualizing in vivo a subset of chronic active brain lesions in persons with multiple sclerosis (pwMS), referred to as "paramagnetic rim lesions" (PRLs), with iron-sensitive MRI. PRLs predict future clinical disease progression, making them a promising clinical and translational imaging marker. However, it is unknown how disease progression is modified by PRL evolution (PRL disappearance, new PRL appearance). This is key to understanding MS pathophysiology and may help inform selection of sensitive endpoints for clinical trials targeting chronic active inflammation. To this end, we assessed the longitudinal associations between PRL disappearance and new PRL appearance and clinical disability progression and brain atrophy. PwMS and healthy controls (HCs) were included from a larger prospective, longitudinal cohort study at the University at Buffalo if they had available 3T MRI and clinical visits at baseline and follow-up timepoints. PwMS with sufficient clinical data for confirmed disability progression (CDP) analysis were included in a Disability Progression Cohort, and pwMS and HCs with brain volumetry data at baseline and follow-up were included in MS and HC Brain Atrophy cohorts. PRLs were assessed at baseline and follow-up and assigned as disappearing, newly appearing, or persisting at follow-up. Linear models were fit to compare annualized PRL disappearance rates or new PRL appearance (yes/no) with annualized rates of CDP and progression independent of relapse activity (PIRA) or with annualized rates of brain atrophy, adjusting for covariates including baseline PRL number and follow-up time. Statistical analyses were corrected for false discovery rate (FDR; i.e., In total, 160 pwMS (73.8% female; mean baseline age 46.6 ± 11.4 years; mean baseline disease duration 13.8 ± 10.6 years; median follow-up time 5.6 [interquartile range 5.2-7.8] years; 26.9% progressive MS) and 27 HCs (74.1% female; mean baseline age 43.9 ± 13.6 years; median follow-up time 5.4 [5.2-5.6] years) were enrolled. Greater PRL disappearance rates were associated with reduced rates of CDP (β mean = -0.262, 95% CI -0.475 to -0.049, Our results show that resolution of existing PRLs and lack of new PRLs are associated with improved clinical outcomes. These findings further motivate the need for novel therapies targeting microglia-mediated brain inflammation and adoption of clinical strategies to prevent appearance of new PRL.

Sections du résumé

BACKGROUND AND OBJECTIVES OBJECTIVE
Recent technological advances have enabled visualizing in vivo a subset of chronic active brain lesions in persons with multiple sclerosis (pwMS), referred to as "paramagnetic rim lesions" (PRLs), with iron-sensitive MRI. PRLs predict future clinical disease progression, making them a promising clinical and translational imaging marker. However, it is unknown how disease progression is modified by PRL evolution (PRL disappearance, new PRL appearance). This is key to understanding MS pathophysiology and may help inform selection of sensitive endpoints for clinical trials targeting chronic active inflammation. To this end, we assessed the longitudinal associations between PRL disappearance and new PRL appearance and clinical disability progression and brain atrophy.
METHODS METHODS
PwMS and healthy controls (HCs) were included from a larger prospective, longitudinal cohort study at the University at Buffalo if they had available 3T MRI and clinical visits at baseline and follow-up timepoints. PwMS with sufficient clinical data for confirmed disability progression (CDP) analysis were included in a Disability Progression Cohort, and pwMS and HCs with brain volumetry data at baseline and follow-up were included in MS and HC Brain Atrophy cohorts. PRLs were assessed at baseline and follow-up and assigned as disappearing, newly appearing, or persisting at follow-up. Linear models were fit to compare annualized PRL disappearance rates or new PRL appearance (yes/no) with annualized rates of CDP and progression independent of relapse activity (PIRA) or with annualized rates of brain atrophy, adjusting for covariates including baseline PRL number and follow-up time. Statistical analyses were corrected for false discovery rate (FDR; i.e.,
RESULTS RESULTS
In total, 160 pwMS (73.8% female; mean baseline age 46.6 ± 11.4 years; mean baseline disease duration 13.8 ± 10.6 years; median follow-up time 5.6 [interquartile range 5.2-7.8] years; 26.9% progressive MS) and 27 HCs (74.1% female; mean baseline age 43.9 ± 13.6 years; median follow-up time 5.4 [5.2-5.6] years) were enrolled. Greater PRL disappearance rates were associated with reduced rates of CDP (β mean = -0.262, 95% CI -0.475 to -0.049,
DISCUSSION CONCLUSIONS
Our results show that resolution of existing PRLs and lack of new PRLs are associated with improved clinical outcomes. These findings further motivate the need for novel therapies targeting microglia-mediated brain inflammation and adoption of clinical strategies to prevent appearance of new PRL.

Identifiants

pubmed: 39447104
doi: 10.1212/WNL.0000000000210004
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e210004

Auteurs

Jack A Reeves (JA)

From the Buffalo Neuroimaging Analysis Center (J.A.R., A.B., D.J., M.M., N.B., F. Salman, F. Schweser, M.G.D., R.Z.), Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo; Department of Biostatistics (G.W.), School of Public Health and Health Professions, State University of New York at Buffalo; and Center for Biomedical Imaging at the Clinical Translational Science Institute (B.W.-G.), University at Buffalo, State University of New York.

Alexander Bartnik (A)

From the Buffalo Neuroimaging Analysis Center (J.A.R., A.B., D.J., M.M., N.B., F. Salman, F. Schweser, M.G.D., R.Z.), Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo; Department of Biostatistics (G.W.), School of Public Health and Health Professions, State University of New York at Buffalo; and Center for Biomedical Imaging at the Clinical Translational Science Institute (B.W.-G.), University at Buffalo, State University of New York.

Dejan Jakimovski (D)

From the Buffalo Neuroimaging Analysis Center (J.A.R., A.B., D.J., M.M., N.B., F. Salman, F. Schweser, M.G.D., R.Z.), Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo; Department of Biostatistics (G.W.), School of Public Health and Health Professions, State University of New York at Buffalo; and Center for Biomedical Imaging at the Clinical Translational Science Institute (B.W.-G.), University at Buffalo, State University of New York.

Maryam Mohebbi (M)

From the Buffalo Neuroimaging Analysis Center (J.A.R., A.B., D.J., M.M., N.B., F. Salman, F. Schweser, M.G.D., R.Z.), Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo; Department of Biostatistics (G.W.), School of Public Health and Health Professions, State University of New York at Buffalo; and Center for Biomedical Imaging at the Clinical Translational Science Institute (B.W.-G.), University at Buffalo, State University of New York.

Niels Bergsland (N)

From the Buffalo Neuroimaging Analysis Center (J.A.R., A.B., D.J., M.M., N.B., F. Salman, F. Schweser, M.G.D., R.Z.), Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo; Department of Biostatistics (G.W.), School of Public Health and Health Professions, State University of New York at Buffalo; and Center for Biomedical Imaging at the Clinical Translational Science Institute (B.W.-G.), University at Buffalo, State University of New York.

Fahad Salman (F)

From the Buffalo Neuroimaging Analysis Center (J.A.R., A.B., D.J., M.M., N.B., F. Salman, F. Schweser, M.G.D., R.Z.), Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo; Department of Biostatistics (G.W.), School of Public Health and Health Professions, State University of New York at Buffalo; and Center for Biomedical Imaging at the Clinical Translational Science Institute (B.W.-G.), University at Buffalo, State University of New York.

Ferdinand Schweser (F)

From the Buffalo Neuroimaging Analysis Center (J.A.R., A.B., D.J., M.M., N.B., F. Salman, F. Schweser, M.G.D., R.Z.), Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo; Department of Biostatistics (G.W.), School of Public Health and Health Professions, State University of New York at Buffalo; and Center for Biomedical Imaging at the Clinical Translational Science Institute (B.W.-G.), University at Buffalo, State University of New York.

Gregory Wilding (G)

From the Buffalo Neuroimaging Analysis Center (J.A.R., A.B., D.J., M.M., N.B., F. Salman, F. Schweser, M.G.D., R.Z.), Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo; Department of Biostatistics (G.W.), School of Public Health and Health Professions, State University of New York at Buffalo; and Center for Biomedical Imaging at the Clinical Translational Science Institute (B.W.-G.), University at Buffalo, State University of New York.

Bianca Weinstock-Guttman (B)

From the Buffalo Neuroimaging Analysis Center (J.A.R., A.B., D.J., M.M., N.B., F. Salman, F. Schweser, M.G.D., R.Z.), Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo; Department of Biostatistics (G.W.), School of Public Health and Health Professions, State University of New York at Buffalo; and Center for Biomedical Imaging at the Clinical Translational Science Institute (B.W.-G.), University at Buffalo, State University of New York.

Michael G Dwyer (MG)

From the Buffalo Neuroimaging Analysis Center (J.A.R., A.B., D.J., M.M., N.B., F. Salman, F. Schweser, M.G.D., R.Z.), Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo; Department of Biostatistics (G.W.), School of Public Health and Health Professions, State University of New York at Buffalo; and Center for Biomedical Imaging at the Clinical Translational Science Institute (B.W.-G.), University at Buffalo, State University of New York.

Robert Zivadinov (R)

From the Buffalo Neuroimaging Analysis Center (J.A.R., A.B., D.J., M.M., N.B., F. Salman, F. Schweser, M.G.D., R.Z.), Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo; Department of Biostatistics (G.W.), School of Public Health and Health Professions, State University of New York at Buffalo; and Center for Biomedical Imaging at the Clinical Translational Science Institute (B.W.-G.), University at Buffalo, State University of New York.

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