Prognosis prediction model for conversion from mild cognitive impairment to Alzheimer's disease created by integrative analysis of multi-omics data.
Daichi ShigemizuShintaro AkiyamaSayuri HigakiTaiki SugimotoTakashi SakuraiKeith A BoroevichAlok SharmaTatsuhiko TsunodaTakahiro OchiyaShumpei NiidaKouichi OzakiPublished in: Alzheimer's research & therapy (2020)
Our proposed model was demonstrated to be effective in MCI-to-AD conversion prediction. A network-based meta-analysis of miR-eQTL target genes identified important hub genes associated with AD pathogenesis. Accurate prediction of MCI-to-AD conversion would enable earlier intervention for MCI patients at high risk, potentially reducing conversion to AD.
Keyphrases
- mild cognitive impairment
- cognitive decline
- end stage renal disease
- ejection fraction
- newly diagnosed
- randomized controlled trial
- long non coding rna
- cell proliferation
- chronic kidney disease
- network analysis
- prognostic factors
- peritoneal dialysis
- gene expression
- single cell
- electronic health record
- long noncoding rna
- patient reported outcomes
- big data
- mass spectrometry
- data analysis
- patient reported