Multi-Omic Blood Biomarkers as Dynamic Risk Predictors in Late-Onset Alzheimer's Disease

被引：5

作者：

Bhalala, Oneil G. ^{[1
,2
]}

Watson, Rosie ^{[1
,3
]}

Yassi, Nawaf ^{[1
,2
,3
]}

机构：

[1] Walter & Eliza Hall Inst Med Res, Populat Hlth & Immun Div, Parkville 3052, Australia

[2] Univ Melbourne, Royal Melbourne Hosp, Melbourne Brain Ctr, Dept Neurol, Parkville 3050, Australia

[3] Univ Melbourne, Royal Melbourne Hosp, Dept Med, Parkville 3050, Australia

来源：

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES | 2024年 / 25卷 / 02期

关键词：

Alzheimer's disease; genomics; proteomics; metabolomics; risk prediction; PLASMA NEUROFILAMENT LIGHT; PHOSPHORYLATED TAU 181; CHAIN AMINO-ACIDS; AMYLOID-BETA; POLYGENIC RISK; DIAGNOSTIC PERFORMANCE; HAZARD SCORES; SOLUBLE TREM2; ASSOCIATION; DEMENTIA;

D O I：

10.3390/ijms25021231

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

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.

引用

页数：27

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