Grey matter volume and CSF biomarkers predict neuropsychological subtypes of MCI.
Autor: | Lefort-Besnard J; Normandie Univ, UNICAEN, INSERM, COMETE, Caen, France., Naveau M; Normandie Univ, UNICAEN, CNRS, CEA, INSERM, GIP Cyceron, Caen, France., Delcroix N; Normandie Univ, UNICAEN, CNRS, CEA, INSERM, GIP Cyceron, Caen, France., Decker LM; Normandie Univ, UNICAEN, INSERM, COMETE, Caen, France; Normandie Univ, UNICAEN, CIREVE, Caen, France. Electronic address: leslie.decker@unicaen.fr., Cignetti F; Univ. Grenoble Alpes, CNRS, VetAgro Sup, Grenoble INP, TIMC, Grenoble, France. Electronic address: fabien.cignetti@univ-grenoble-alpes.fr. |
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Jazyk: | angličtina |
Zdroj: | Neurobiology of aging [Neurobiol Aging] 2023 Nov; Vol. 131, pp. 196-208. Date of Electronic Publication: 2023 Jul 12. |
DOI: | 10.1016/j.neurobiolaging.2023.07.006 |
Abstrakt: | There is increasing evidence of different subtypes of individuals with mild cognitive impairment (MCI). An important line of research is whether neuropsychologically-defined subtypes have distinct patterns of neurodegeneration and cerebrospinal fluid (CSF) biomarker composition. In our study, we demonstrated that MCI participants of the ADNI database (N = 640) can be discriminated into 3 coherent neuropsychological subgroups. Our clustering approach revealed amnestic MCI, mixed MCI, and cluster-derived normal subgroups. Furthermore, classification modeling revealed that specific predictive features can be used to differentiate amnestic and mixed MCI from cognitively normal (CN) controls: CSF Aβ Competing Interests: Disclosure statement The authors have no actual or potential conflicts of interest. (Copyright © 2023 Elsevier Inc. All rights reserved.) |
Databáze: | MEDLINE |
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