Journal
DIAGNOSTICS
Volume 11, Issue 12, Pages -Publisher
MDPI
DOI: 10.3390/diagnostics11122303
Keywords
eQTLs; differential expression; integrative analysis; Alzheimer's disease
Categories
Funding
- ADAPTED consortium from the Innovative Medicines Initiative 2 Joint Undertaking [115975]
- European Union's Horizon 2020 research and innovation program
- European Federation of Pharmaceutical Industries and Associations
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The identification of reliable blood-based biomarkers for Alzheimer's disease has proven to be more difficult than expected, but utilizing high-throughput multi-omics data has opened up new possibilities. By analyzing candidate SNPs and gene expression quantitative trait loci, potential susceptibility factors and biomarkers for AD have been identified for further experimental validation.
There is an urgent need to identify biomarkers for Alzheimer's disease (AD), but the identification of reliable blood-based biomarkers has proven to be much more difficult than initially expected. The current availability of high-throughput multi-omics data opens new possibilities in this titanic task. Candidate Single Nucleotide Polymorphisms (SNPs) from large, genome-wide association studies (GWAS), meta-analyses exploring AD (case-control design), and quantitative measures for cortical structure and general cognitive performance were selected. The Genotype-Tissue Expression (GTEx) database was used for identifying expression quantitative trait loci (eQTls) among candidate SNPs. Genes significantly regulated by candidate SNPs were investigated for differential expression in AD cases versus controls in the brain and plasma, both at the mRNA and protein level. This approach allowed us to identify candidate susceptibility factors and biomarkers of AD, facing experimental validation with more evidence than with genetics alone.
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