Multiomics and artificial intelligence enabled peripheral blood-based prediction of amnestic mild cognitive impairment.
Curr Res Transl Med
; 71(1): 103367, 2023.
Article
em En
| MEDLINE
| ID: mdl-36446162
ABSTRACT
BACKGROUND:
Since dementia is preventable with early interventions, biomarkers that assist in diagnosing early stages of dementia, such as mild cognitive impairment (MCI), are urgently needed.METHODS:
Multiomics analysis of amnestic MCI (aMCI) peripheral blood (n = 25) was performed covering the transcriptome, microRNA, proteome, and metabolome. Validation analysis for microRNAs was conducted in an independent cohort (n = 12). Artificial intelligence was used to identify the most important features for predicting aMCI.FINDINGS:
We found that hsa-miR-4455 is the best biomarker in all omics analyses. The diagnostic index taking a ratio of hsa-miR-4455 to hsa-let-7b-3p predicted aMCI patients against healthy subjects with 97% overall accuracy. An integrated review of multiomics data suggested that a subset of T cells and the GCN (general control nonderepressible) pathway are associated with aMCI.INTERPRETATION:
The multiomics approach has enabled aMCI biomarkers with high specificity and illuminated the accompanying changes in peripheral blood. Future large-scale studies are necessary to validate candidate biomarkers for clinical use.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Demência
/
MicroRNAs
/
Disfunção Cognitiva
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Curr Res Transl Med
Ano de publicação:
2023
Tipo de documento:
Article