3 research outputs found

    Cortical microstructure in primary progressive aphasia: a multicenter study.

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    BackgroundCortical mean diffusivity is a novel imaging metric sensitive to early changes in neurodegenerative syndromes. Higher cortical mean diffusivity values reflect microstructural disorganization and have been proposed as a sensitive biomarker that might antedate macroscopic cortical changes. We aimed to test the hypothesis that cortical mean diffusivity is more sensitive than cortical thickness to detect cortical changes in primary progressive aphasia (PPA).MethodsIn this multicenter, case-control study, we recruited 120 patients with PPA (52 non-fluent, 31 semantic, and 32 logopenic variants; and 5 GRN-related PPA) as well as 89 controls from three centers. The 3-Tesla MRI protocol included structural and diffusion-weighted sequences. Disease severity was assessed with the Clinical Dementia Rating scale. Cortical thickness and cortical mean diffusivity were computed using a surface-based approach.ResultsThe comparison between each PPA variant and controls revealed cortical mean diffusivity increases and cortical thinning in overlapping regions, reflecting the canonical loci of neurodegeneration of each variant. Importantly, cortical mean diffusivity increases also expanded to other PPA-related areas and correlated with disease severity in all PPA groups. Cortical mean diffusivity was also increased in patients with very mild PPA when only minimal cortical thinning was observed and showed a good correlation with measures of disease severity.ConclusionsCortical mean diffusivity shows promise as a sensitive biomarker for the study of the neurodegeneration-related microstructural changes in PPA

    Use of plasma biomarkers for AT(N) classification of neurodegenerative dementias

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    International audienceObjectives All categories included in the AT(N) classification can now be measured in plasma. However, their agreement with cerebrospinal fluid (CSF) markers is not fully established. A blood signature to generate the AT(N) classification would facilitate early diagnosis of patients with Alzheimer’s disease (AD) through an easy and minimally invasive approach. Methods We measured Aβ, pTau181 and neurofilament light (NfL) in 150 plasma samples of the Sant Pau Initiative on Neurodegeneration cohort including patients with mild cognitive impairment, AD dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal participants. We classified participants in the AT(N) categories according to CSF biomarkers and studied the diagnostic value of plasma biomarkers within each category individually and in combination. Results The plasma Aβ composite, pTau181 and NfL yielded areas under the curve (AUC) of 0.75, 0.78 and 0.88 to discriminate positive and negative participants in their respective A, T and N categories. The combination of all three markers did not outperform pTau181 alone (AUC=0.81) to discriminate A+T+ from A–T– participants. There was a moderate correlation between plasma Aβ composite and CSF Aβ1–42/Aβ1–40 (Rho=−0.5, p<0.001) and between plasma pTau181 and CSF pTau181 in the entire cohort (Rho=0.51, p<0.001). NfL levels in plasma showed high correlation with those in CSF (Rho=0.78, p<0.001). Conclusions Plasma biomarkers are useful to detect the AT(N) categories, and their use can differentiate patients with pathophysiological evidence of AD. A blood AT(N) signature may facilitate early diagnosis and follow-up of patients with AD through an easy and minimally invasive approach
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