Martinez-Lage, P. (Pablo)

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    The impact of silent vascular brain burden in cognitive impairment in Parkinson's disease
    (Wiley-Blackwell, 2012) Toledo, J. (Jon); Lamet, I. (Isabel); Garcia-de-Eulate, R. (Reyes); Gonzalez-Redondo, R. (R.); Rodriguez-Oroz, M.C. (María Cruz); Clavero, P. (P.); Garcia-Garcia, D. (David); Martinez-Lage, P. (Pablo)
    White matter hyperintensities (WMHs) detected by magnetic resonance imaging (MRI) of the brain are associated with dementia and cognitive impairment in the general population and in Alzheimer's disease. Their effect in cognitive decline and dementia associated with Parkinson's disease (PD) is still unclear. METHODS: We studied the relationship between WMHs and cognitive state in 111 patients with PD classified as cognitively normal (n = 39), with a mild cognitive impairment (MCI) (n = 46) or dementia (n = 26), in a cross-sectional and follow-up study. Cognitive state was evaluated with a comprehensive neuropsychological battery, and WMHs were identified in FLAIR and T2-weighted MRI. The burden of WMHs was rated using the Scheltens scale. RESULTS: No differences in WMHs were found between the three groups in the cross-sectional study. A negative correlation was observed between semantic fluency and the subscore for WMHs in the frontal lobe. Of the 36 non-demented patients re-evaluated after a mean follow-up of 30 months, three patients converted into MCI and 5 into dementia. Progression of periventricular WMHs was associated with an increased conversion to dementia. A marginal association between the increase in total WMHs burden and worsening in the Mini Mental State Examination was encountered. CONCLUSIONS: White matter hyperintensities do not influence the cognitive status of patients with PD. Frontal WMHs have a negative impact on semantic fluency. Brain vascular burden may have an effect on cognitive impairment in patients with PD as WMHs increase overtime might increase the risk of conversion to dementia. This finding needs further confirmation in larger prospective studies.
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    Plasma Aβ42/40 ratio alone or combined with FDG-PET can accurately predict amyloid-PET positivity: a cross-sectional analysis from the AB255 Study
    (Springer Science and Business Media LLC, 2019) Prieto, E. (Elena); Pesini, P. (Pedro); Alegret, M. (Montserrat); Hernandez, I. (I.); Pérez-Grijalba, V. (Virginia); Guillen, F. (Fernando); San-José, I. (Itziar); Buendía, M. (Mar); Sarasa, M. (Manuel); Sarasa, L. (Leticia); The AB255 Study Group; Ruiz, A. (Agustín); Sotolongo-Grau, O. (Oscar); Monleón, I. (Inmaculada); Tárraga, L. (Lluis); Arbizu, J. (Javier); Martinez-Lage, P. (Pablo); Boada, M. (Mercè); Munuera, J. (Josep); Romero, J. (Judith)
    Background: To facilitate population screening and clinical trials of disease-modifying therapies for Alzheimer’s disease, supportive biomarker information is necessary. This study was aimed to investigate the association of plasma amyloid-beta (Aβ) levels with the presence of pathological accumulation of Aβ in the brain measured by amyloid-PET. Both plasma Aβ42/40 ratio alone or combined with an FDG-PET-based biomarker of neurodegeneration were assessed as potential AD biomarkers. Methods: We included 39 cognitively normal subjects and 20 patients with mild cognitive impairment from the AB255 Study who had undergone PiB-PET scans. Total Aβ40 and Aβ42 levels in plasma (TP42/40) were quantified using ABtest kits. Subjects were dichotomized as Aβ-PET positive or negative, and the ability of TP42/40 to detect Aβ-PET positivity was assessed by logistic regression and receiver operating characteristic analyses. Combination of plasma Aβ biomarkers and FDG-PET was further assessed as an improvement for brain amyloidosis detection and diagnosis classification. Results: Eighteen (30.5%) subjects were Aβ-PET positive. TP42/40 ratio alone identified Aβ-PET status with an area under the curve (AUC) of 0.881 (95% confidence interval [CI] = 0.779–0.982). Discriminating performance of TP42/40 to detect Aβ-PET-positive subjects yielded sensitivity and specificity values at Youden’s cutoff of 77.8% and 87.5%, respectively, with a positive predictive value of 0.732 and negative predictive value of 0.900. All these parameters improved after adjusting the model for significant covariates. Applying TP42/40 as the first screening tool in a sequential diagnostic work-up would reduce the number of Aβ-PET scans by 64%. Combination of both FDG-PET scores and plasma Aβ biomarkers was found to be the most accurate Aβ-PET predictor, with an AUC of 0.965 (95% CI = 0.913–0.100). Conclusions: Plasma TP42/40 ratio showed a relevant and significant potential as a screening tool to identify brain Aβ positivity in preclinical and prodromal stages of Alzheimer’s disease.