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A blood based 12-miRNA signature of Alzheimer patients

GSE46579 Homo sapiens (human) Non-coding RNA profiling 70 samples Submitted 2013/06/17 Platform GPL11154
At a glance

Non-coding RNA profiling · human · 70 samples

What it is
Non-coding RNA profilingLevels of RNAs that do not code for proteins, such as miRNA or lncRNA.
Organism
Homo sapiens (human)
Samples
70 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
We applied Next-Generation Sequencing (NGS) to miRNAs from blood samples of 48 AD (Alzheimer's Disease) patients and 22 unaffected controls, yielding a total of 140 unique mature miRNAs with significantly changed expression level. Of these, 82 were higher and 58 lower abundant in samples from AD patients.
Read the full summary ↓
We selected a panel of 12 miRNAs for a qRT-PCR analysis on a larger cohort of 202 samples including not only AD patients and healthy controls but also patients with other CNS illnesses: Multiple Sclerosis, Parkinson's Disease, Major Depression, Bipolar Disorder, Schizophrenia, and Mild Cognitive Impairment, which is assumed to represent a transitional period before the development of AD. MiRNA target enrichment analysis of the selected 12 miRNAs indicated an involvement of miRNAs in nervous system development, neuron projection, neuron projection development, and neuron projection morphogenesis, respectively. Using this 12-miRNA signature we were able to differentiate between AD and controls with an accuracy of 93.3%, a specificity of 95.1%, and a sensitivity of 91.5%. The differentiation of AD from other neurological diseases was possible with accuracies between 73.8% and 77.8%. The differentiation of the other CNS disorders from controls yielded even higher accuracies.
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE46579_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Also filed as BioProject PRJNA201039 and SRA study SRP022043. Searching any of these in the dataset finder brings you back here.

Samples in this study

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