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Series GSE44639 Query DataSets for GSE44639
Status Public on Dec 31, 2015
Title Altered microRNA expression in individuals at high risk of type 1 diabetes
Organism Homo sapiens
Experiment type Non-coding RNA profiling by high throughput sequencing
Summary Type 1 diabetes (T1D) is an autoimmune disease characterized by the destruction of pancreatic insulin-producing β cells. CD4+ T cells are integral to the pathogenesis of T1D, but biomarkers that define their pathogenic status in T1D are lacking. miRNAs have essential functions in a wide range of tissues/organs, including the immune system. We reasoned that CD4+ T cells from individuals at high risk for T1D (pre-T1D) might be distinguished by an miRNA signature. We sorted CD4+ T cells from 9 healthy and 7 pre-T1D individuals into 6 subsets, namely naïve, resting regulatory (rTreg), activated regulatory (aTreg), transitional memory (Ttm), central memory (Tcm) and effector memory (Tem) cells, and then compared miRNA profiles between these subsets and between pre-T1D and healthy individuals by deep sequencing. Differential expression of miRNAs was detected in each of the CD4+ T cell subsets. For example, expression of miRNAs that induce apoptosis (miR-15a) or FOXP3 instability (miR-31) was increased in rTreg and aTreg cells, respectively, in pre-T1D individuals, whereas miR-150 was increased in Tem cells of pre-T1D individuals. Importantly, increased miR-150 expression could be detected by qRT-PCR in total CD4+ T and PBMCs of pre-T1D individuals. Consistent with it being a marker of pathogenic CD4+ T cells, we showed that miR-150 regulates IFN-γ production in mouse CD4+ T cells. Thus, comprehensive profiling identifies miRNA profiles that not only distinguish CD4+ T cell subsets but also discriminate individuals with preclinical T1D. The ability to detect differentially expressed miRNAs in total CD4+ T cells or PBMCs should facilitate clinical application of miRNAs as biomarkers.
 
Overall design CD4+T cells from healthy and individuals at high risk for autoimmune type 1 diabetes were sorted into 6 subsets, which resulted in 80 samples, 38 for healthy and 42 for high risk individuals. Each sample was barcoded and miRNA libraries were constructed and subsequently subjected to deep-sequencing on the Illumina GAII or HiSeq platform. The Fastq files are have deconvoluted and stripped of the barcode adaptor sequences.
 
Contributor(s) Chong MW
Citation(s) 26786119
Submission date Feb 25, 2013
Last update date May 15, 2019
Contact name Mark Chong
E-mail(s) mchong@svi.edu.au
Phone 61-3-92313444
Organization name St Vincent's Institute of Medical Research
Street address 9 Princes Street
City Fitzroy
State/province Victoria
ZIP/Postal code 3065
Country Australia
 
Platforms (2)
GPL10999 Illumina Genome Analyzer IIx (Homo sapiens)
GPL11154 Illumina HiSeq 2000 (Homo sapiens)
Samples (80)
GSM1088200 M7_naive
GSM1088201 M8_naive
GSM1088202 M9_naive
Relations
BioProject PRJNA190702
SRA SRP018853

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE44639_RAW.tar 1.0 Mb (http)(custom) TAR (of TXT)
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

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