GSE167559 Dementia subtype prediction models constructed by penalized regression methods for multiclass classification using serum microRNA expression data

Contributors : Yuya Asanomi ; Daichi Shigemizu ; Shintaro Akiyama ; Takashi Sakurai ; Kouichi Ozaki ; Takahiro Ochiya ; Shumpei NiidaSeries Type : Expression profiling by arrayOrganism : Homo sapiensThere are many subtypes of dementia, and identification of diagnostic biomarkers that are minimally-invasive, low-cost, and efficient is desired. Circulating microRNAs (miRNAs) have recently gained attention as easily accessible and non-invasive biomarkers. We conducted a comprehensive miRNA expression analysis of serum samples from 1348 Japanese dementia patients, composed of four subtypes —Alzheimer’s disease (AD), vascular dementia, dementia with Lewy bodies (DLB), and normal pressure hydrocephalus—and 246 control subjects. We used this data to construct dementia subtype prediction models based on penalized regression models with the multiclass classification. We constructed a final prediction model using 46 miRNAs, which classified dementia patients from an independent validation set into four subtypes of dementia. Network analysis of miRNA target genes revealed important hub genes, SRC and CHD3, associated with the AD pathogenesis. Moreover, MCU and CASP3, which are kn own to be associated with DLB pathogenesis, were identified from our DLB-specific target genes. Our study demonstrates the potential of blood-based biomarkers for use in dementia-subtype prediction models. We believe that further investigation using larger sample sizes will contribute to the accur...
Source: GEO: Gene Expression Omnibus - Category: Genetics & Stem Cells Tags: Expression profiling by array Homo sapiens Source Type: research