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Sökning: WFRF:(Romero Pinel L.)

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1.
  • Alonso Magdalena, Lucia, et al. (författare)
  • Anticipation of age at onset in multiple sclerosis: methodologic pitfalls
  • 2010
  • Ingår i: Acta Neurologica Scandinavica. - : Hindawi Limited. - 1600-0404 .- 0001-6314. ; 121:6, s. 426-428
  • Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
    • Background/aim - There are several reports that claim anticipation in complex or polygenic diseases such as multiple sclerosis (MS), Crohn disease or schizophrenia. The aim of the present study was to assess age at onset of MS during the last 60 years in the region of Costa de Ponent (Barcelona, Spain) showing how apparent changes in age at onset between generations can be an artefact of analysis based on cohorts that have not been followed enough time. Methods - The study comprised 1100 patients diagnosed of MS. The method used to correct for follow-up time bias involves constructing comparison cohorts that had been observed for the same amount of time. To ensure equal follow-up times, we restricted our analysis to patients whose onset was by 37 years of age (percentile 75) and were at least 37 years old. We analysed differences in age at onset using log-rank test to compare survival curves estimated by Kaplan-Meier method. Results - Age at onset decreases progressively from older to younger generations. However, when adjustment to equal follow-up time was done, anticipation in age at onset was not found. Conclusion - Anticipation of age at onset is undetectable when adjusted for follow-up time.
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2.
  • Mañé-Martínez, M. A., et al. (författare)
  • Glial and neuronal markers in cerebrospinal fluid in different types of multiple sclerosis
  • 2016
  • Ingår i: Journal of Neuroimmunology. - : Elsevier BV. - 0165-5728. ; 299, s. 112-117
  • Tidskriftsartikel (refereegranskat)abstract
    • In the present study, CSF concentrations of NFL, t-tau, p-tau, GFAP, S-100B, YKL-40, MCP-1, α-sAPP, β-sAPP, and Aβ38, Aβ40, Aβ42 were measured in 324 MS patients to test whether a correlation among the biomarkers exists and whether the profile of CSF biomarkers varies among the different types of MS. The CSF concentrations of NFL were significantly higher in RRMS while CSF concentrations of GFAP were higher in PPMS. CSF concentrations of NFL correlated with YKL-40 in CIS patients while CSF concentrations of GFAP correlated with YKL-40 in RRMS patients. © 2016 Elsevier B.V.
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3.
  • Lopez-Soley, E, et al. (författare)
  • Dynamics and Predictors of Cognitive Impairment along the Disease Course in Multiple Sclerosis
  • 2021
  • Ingår i: Journal of personalized medicine. - : MDPI AG. - 2075-4426. ; 11:11
  • Tidskriftsartikel (refereegranskat)abstract
    • (1) Background: The evolution and predictors of cognitive impairment (CI) in multiple sclerosis (MS) are poorly understood. We aimed to define the temporal dynamics of cognition throughout the disease course and identify clinical and neuroimaging measures that predict CI. (2) Methods: This paper features a longitudinal study with 212 patients who underwent several cognitive examinations at different time points. Dynamics of cognition were assessed using mixed-effects linear spline models. Machine learning techniques were used to identify which baseline demographic, clinical, and neuroimaging measures best predicted CI. (3) Results: In the first 5 years of MS, we detected an increase in the z-scores of global cognition, verbal memory, and information processing speed, which was followed by a decline in global cognition and memory (p < 0.05) between years 5 and 15. From 15 to 30 years of disease onset, cognitive decline continued, affecting global cognition and verbal memory. The baseline measures that best predicted CI were education, disease severity, lesion burden, and hippocampus and anterior cingulate cortex volume. (4) Conclusions: In MS, cognition deteriorates 5 years after disease onset, declining steadily over the next 25 years and more markedly affecting verbal memory. Education, disease severity, lesion burden, and volume of limbic structures predict future CI and may be helpful when identifying at-risk patients.
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