Multi-Omic Blood Biomarkers as Dynamic Risk Predictors in Late-Onset Alzheimer's Disease
- Author(s)
- Bhalala, OG; Watson, R; Yassi, N;
- Details
- Publication Year 2024-01-19,Volume 25,Issue #2,Page 1231
- Journal Title
- International Journal of Molecular Sciences
- Abstract
- Late-onset Alzheimer's disease is the leading cause of dementia worldwide, accounting for a growing burden of morbidity and mortality. Diagnosing Alzheimer's disease before symptoms are established is clinically challenging, but would provide therapeutic windows for disease-modifying interventions. Blood biomarkers, including genetics, proteins and metabolites, are emerging as powerful predictors of Alzheimer's disease at various timepoints within the disease course, including at the preclinical stage. In this review, we discuss recent advances in such blood biomarkers for determining disease risk. We highlight how leveraging polygenic risk scores, based on genome-wide association studies, can help stratify individuals along their risk profile. We summarize studies analyzing protein biomarkers, as well as report on recent proteomic- and metabolomic-based prediction models. Finally, we discuss how a combination of multi-omic blood biomarkers can potentially be used in memory clinics for diagnosis and to assess the dynamic risk an individual has for developing Alzheimer's disease dementia.
- Publisher
- MDPI
- Keywords
- Humans; *Alzheimer Disease/diagnosis/genetics; Genome-Wide Association Study; Multiomics; Proteomics; Biomarkers; Alzheimer’s disease; genomics; metabolomics; risk prediction
- Research Division(s)
- Population Health And Immunity
- PubMed ID
- 38279230
- Publisher's Version
- https://doi.org/10.3390/ijms25021231
- Open Access at Publisher's Site
https://doi.org/0.3390/ijms2502123- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2024-02-29 09:01:48
Last Modified: 2024-02-29 09:09:32