Integrated Genomic, Transcriptomic and Proteomic Analysis for Identifying Markers of Alzheimer's Disease.
Laura MadridSandra C LabradorAntonio Gonzalez PerezMaría Eugenia Sáeznull The Alzheimer's Disease Neuroimaging Initiative AdniPublished in: Diagnostics (Basel, Switzerland) (2021)
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.
Keyphrases
- genome wide association
- genome wide
- case control
- high throughput
- poor prognosis
- binding protein
- single cell
- meta analyses
- dna methylation
- copy number
- systematic review
- high resolution
- cognitive decline
- bioinformatics analysis
- randomized controlled trial
- rna seq
- gene expression
- multiple sclerosis
- mass spectrometry
- big data
- deep learning
- artificial intelligence