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1.
Neuroimage Clin ; 42: 103609, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38718640

RESUMO

BACKGROUND: Prior research has established a link between thalamic pathology and cognitive impairment (CI) in people with multiple sclerosis (pwMS). However, the translation of these findings to pwMS in everyday clinical settings has been insufficient. OBJECTIVE: To assess which global and/or thalamic imaging biomarkers can be used to identify pwMS at risk for CI and cognitive worsening (CW) in a real-world setting. METHODS: This was an international, multi-center (11 centers), longitudinal, retrospective, real-word study of people with relapsing-remitting MS (pwRRMS). Brain MRI exams acquired at baseline and follow-up were collected. Cognitive status was evaluated using the Symbol Digit Modalities Test (SDMT). Thalamic volume (TV) measurement was performed on T2-FLAIR, as well as on T1-WI, when available. Thalamic dysconnectivity, T2-lesion volume (T2-LV), and volumes of gray matter (GM), whole brain (WB) and lateral ventricles (LVV) were also assessed. RESULTS: 332 pwMS were followed for an average of 2.8 years. At baseline, T2-LV, LVV, TV and thalamic dysconnectivity on T2-FLAIR (p < 0.016), and WB, GM and TV volumes on T1-WI (p < 0.039) were significantly worse in 90 (27.1 %) CI vs. 242 (62.9 %) non-CI pwRRMS. Greater SDMT decline over the follow-up was associated with lower baseline TV on T2-FLAIR (standardized ß = 0.203, p = 0.002) and greater thalamic dysconnectivity (standardized ß = -0.14, p = 0.028) in a linear regression model. CONCLUSIONS: PwRRMS with thalamic atrophy and worse thalamic dysconnectivity present more frequently with CI and experience greater CW over mid-term follow-up in a real-world setting.


Assuntos
Atrofia , Disfunção Cognitiva , Imageamento por Ressonância Magnética , Esclerose Múltipla Recidivante-Remitente , Tálamo , Humanos , Esclerose Múltipla Recidivante-Remitente/patologia , Esclerose Múltipla Recidivante-Remitente/diagnóstico por imagem , Esclerose Múltipla Recidivante-Remitente/fisiopatologia , Esclerose Múltipla Recidivante-Remitente/complicações , Feminino , Masculino , Adulto , Tálamo/patologia , Tálamo/diagnóstico por imagem , Disfunção Cognitiva/patologia , Disfunção Cognitiva/fisiopatologia , Disfunção Cognitiva/etiologia , Disfunção Cognitiva/diagnóstico por imagem , Atrofia/patologia , Pessoa de Meia-Idade , Imageamento por Ressonância Magnética/métodos , Estudos Retrospectivos , Estudos Longitudinais
2.
Mult Scler Relat Disord ; 2(4): 340-8, 2013 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-25877844

RESUMO

OBJECTIVE: Clinical response to immunomodulatory therapies in multiple sclerosis (MS) is variable among patients. Currently, there are no validated biomarkers of clinical response to any of the approved treatments for MS. The objective of this study was to determine if HLA-class II alleles predict the clinical response to glatiramer acetate (GA). METHODS: This was a prospective study of 64 MS patients with relapsing-remitting disease. Patients were HLA-typed and classified as GA-responders or non-responders after 2 years of treatment based on a clinical criterion. Statistical models were used to determine whether HLA-DR and DQ alleles and haplotypes predict the clinical response to GA. RESULTS: Tests of association of response singled out four alleles and two haplotypes with nominal p<0.01. The presence of alleles DR15 or DQ6 or the absence of DR17 and DQ2 alleles was associated with favorable clinical response. The presence of the DR15-DQ6 haplotype and the absence of the DR17-DQ2 haplotype were also associated with favorable treatment response. A best fitting two-haplotype model resulted in the identification of three prognostic categories (good, neutral, and poor). A DR15-DQ6 positive but DR17-DQ2 negative combination was strongly predictive of a favorable clinical response (71%). Conversely, a DR15-DQ6 negative but DR17-DQ2 positive combination was strongly predictive of poor clinical response to GA (17%). CONCLUSION: HLA-DR and DQ typing may prove to be useful biomarkers of predicting response to GA in MS and may help select patients appropriate for this treatment.

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