Cargando…

Soluble amyloid-beta isoforms predict downstream Alzheimer’s disease pathology

BACKGROUND: Changes in soluble amyloid-beta (Aβ) levels in cerebrospinal fluid (CSF) are detectable at early preclinical stages of Alzheimer’s disease (AD). However, whether Aβ levels can predict downstream AD pathological features in cognitively unimpaired (CU) individuals remains unclear. With thi...

Descripción completa

Detalles Bibliográficos
Autores principales: Povala, Guilherme, Bellaver, Bruna, De Bastiani, Marco Antônio, Brum, Wagner S., Ferreira, Pamela C. L., Bieger, Andrei, Pascoal, Tharick A., Benedet, Andrea L., Souza, Diogo O., Araujo, Ricardo M., Zatt, Bruno, Rosa-Neto, Pedro, Zimmer, Eduardo R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8665586/
https://www.ncbi.nlm.nih.gov/pubmed/34895338
http://dx.doi.org/10.1186/s13578-021-00712-3
Descripción
Sumario:BACKGROUND: Changes in soluble amyloid-beta (Aβ) levels in cerebrospinal fluid (CSF) are detectable at early preclinical stages of Alzheimer’s disease (AD). However, whether Aβ levels can predict downstream AD pathological features in cognitively unimpaired (CU) individuals remains unclear. With this in mind, we aimed at investigating whether a combination of soluble Aβ isoforms can predict tau pathology (T+) and neurodegeneration (N+) positivity. METHODS: We used CSF measurements of three soluble Aβ peptides (Aβ(1–38), Aβ(1–40) and Aβ(1–42)) in CU individuals (n = 318) as input features in machine learning (ML) models aiming at predicting T+ and N+. Input data was used for building 2046 tuned predictive ML models with a nested cross-validation technique. Additionally, proteomics data was employed to investigate the functional enrichment of biological processes altered in T+ and N+ individuals. RESULTS: Our findings indicate that Aβ isoforms can predict T+ and N+ with an area under the curve (AUC) of 0.929 and 0.936, respectively. Additionally, proteomics analysis identified 17 differentially expressed proteins (DEPs) in individuals wrongly classified by our ML model. More specifically, enrichment analysis of gene ontology biological processes revealed an upregulation in myelinization and glucose metabolism-related processes in CU individuals wrongly predicted as T+. A significant enrichment of DEPs in pathways including biosynthesis of amino acids, glycolysis/gluconeogenesis, carbon metabolism, cell adhesion molecules and prion disease was also observed. CONCLUSIONS: Our results demonstrate that, by applying a refined ML analysis, a combination of Aβ isoforms can predict T+ and N+ with a high AUC. CSF proteomics analysis highlighted a promising group of proteins that can be further explored for improving T+ and N+ prediction. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13578-021-00712-3.