Entry Detail



General Information

Database ID:exR0198631
RNA Name:hsa-miR-875-5p
RNA Type:miRNA
Chromosome:chr8
Starnd:-
Coordinate:
Start Site(bp):99536830End Site(bp):99536851
External Links:hsa-miR-875-5p



Disease Information

Disease Name:
Disease Category:
MeSH ID:
Type:
Alias:



Expression Detail

GEO ID:GSE120584
Description:Risk prediction models for dementia constructed by supervised principal component analysis using miRNA expression data
Experimental Design:Disease vs Control
Case Disease Type:Alzheimer's Disease
Case Disease SubType:NA
Case Sample:Alzheimer's Disease
Control Sample:Normal
Number of Case:1021
Number of Control:288
Number of Samples:1309





Regulatory Relationship

mRNA targets:
Gene SymbolChromosomeStart Site(bp)End Site(bp)Strand
MAGT1
chrX
77826364
77895593
-
UBXN4
chr2
135741734
135785056
+
miRNA targets:NA
circRNA targets:NA
lncRNA targets:
lncRNA SymbolChromosomeStart Site(bp)End Site(bp)Strand
AC021078.1
chr5
149494314
149504670
-
AC245033.4
chr15
82533175
82540008
-
NORAD
chr20
36045618
36051018
-
STAG3L5P-PVRIG2P-PILRB
chr7
100336104
100367831
+
Display:



Experiment Detail

GEO ID:GSE120584
Sample Source:Blood
Source Fraction:Serum
Platform:GPL21263
Method:Microarray
Num of detected RNA Type:1
Num of detected RNAs of this Type:2532
Sample treatment protocol:NA
RNA Extract protocol:Total RNA was extracted each from 300uL serum samples using 3D-Gene® RNA extraction reagent from liquid sample kit (Toray Industries, Inc.).
RNA library preparation protocol:miRNA was labeled using 3D-Gene® miRNA Labeling kit in accordance with the manufacturer's instructions.



Reference

PMID:30820472
Title:Risk prediction models for dementia constructed by supervised principal component analysis using miRNA expression data
Author:Shigemizu D, Akiyama S, Asanomi Y, Boroevich KA, Sharma A, Tsunoda T, Matsukuma K, Ichikawa M, Sudo H, Takizawa S, Sakurai T, Ozaki K, Ochiya T, Niida S
Journal:Commun Biol. 2019 Feb 25;2:77.
Description:we investigated potential miRNA biomarkers and constructed risk prediction models, based on a supervised principal component analysis (PCA) logistic regression method, according to the subtype of dementia