4.6 Article

Multiomics integrative analysis identifies APOE allele-specific blood biomarkers associated to Alzheimer's disease etiopathogenesis

Journal

AGING-US
Volume 13, Issue 7, Pages 9277-9329

Publisher

IMPACT JOURNALS LLC

Keywords

Alzheimer's disease; APOE; integrative analysis; biomarkers

Funding

  1. Medical Research Council [MR/L501517/1, MC_PC_17112, MR/K013041/1, G0300429, G0902227] Funding Source: Medline
  2. NHLBI NIH HHS [R01 HL105756] Funding Source: Medline

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The study analyzed publicly available data of multiple OMICS technologies from both plasma and brain stratified by APOE haplotype and identified genes and pathways contributing to AD. They also identified a set of biomarkers that could serve as screening tools for a disease lacking specific blood biomarkers.
Alzheimer's disease (AD) is the most common form of dementia, currently affecting 35 million people worldwide. Apolipoprotein E (APOE) epsilon 4 allele is the major risk factor for sporadic, late-onset AD (LOAD), which comprises over 95% of AD cases, increasing the risk of AD 4-12 fold. Despite this, the role of APOE in AD pathogenesis is still a mystery. Aiming for a better understanding of APOE-specific effects, the ADAPTED consortium analyzed and integrated publicly available data of multiple OMICS technologies from both plasma and brain stratified by APOE haplotype (APOE2, APOE3 and APOE4). Combining genome-wide association studies (GWAS) with differential mRNA and protein expression analyses and single-nuclei transcriptomics, we identified genes and pathways contributing to AD in both APOE dependent and independent fashion. Interestingly, we characterized a set of biomarkers showing plasma and brain consistent protein profiles and opposite trends in APOE2 and APOE4 AD cases that could constitute screening tools for a disease that lacks specific blood biomarkers. Beside the identification of APOE-specific signatures, our findings advocate that this novel approach, based on the concordance across OMIC layers and tissues, is an effective strategy for overcoming the limitations of often underpowered single-OMICS studies.

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