Dataset Information

Alzheimer, Mild Cognitive impairment and control samples from AddneuroMed Cohort (batch 2)

ABSTRACT: Alzheimer case-control samples originate from the EU funded AddNeuroMed Cohort, which is a large cross-European AD biomarker study relying on human blood as the source of RNA. The design is case-control. Cases are either Alzheimer's disease patients, subjects with mild cognitive impairment or age and gender matched controls.

ORGANISM(S): Homo sapiens

SUBMITTER: Jamie Timmons Angela Hodges Robert Howard

PROVIDER: E-GEOD-63061 | ArrayExpress | 2015-08-19

SECONDARY ACCESSION(S): GSE63061PRJNA266530

REPOSITORIES: GEO, ArrayExpress

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Project description:Background: Mild cognitive impairment (MCI) is an intermediate state between normal aging, and Alzheimer’s disease, and other dementias. Early detection of dementia, and MCI, is a crucial issue in terms of secondary prevention. Blood biomarker detection is a possible way for early detection of MCI. Although disease biomarkers are detected by, in general, using single molecular analysis such as t-test, another possible approach is based on interaction between molecules. Results: Differential correlation analysis, which detects difference on correlation of two variables in case/control study, was carried out to the dataset with 745 microRNAs (miRNAs) from plasma samples of 30 age-matched controls and 23 MCI patients in Japan. The 20 pairs of miRNAs, which consist of 20 miRNAs, were selected as MCI markers. Two pairs of miRNAs (hsa-miR-191 and hsa-miR-101, and hsa-miR-103 and hsa-miR-222) out of 20 attained the highest area under the curve (AUC) value of 0.962 for MCI detection. Other two miRNA pairs that include hsa-miR-191 and hsa-miR-125b also attained high AUC value of ≥ 0.95. Pathway analysis was performed to the MCI markers for further understanding of biological implications. As a result, collapsed correlation on hsa-miR-191 and emerged correlation on hsa-miR-125b may have key role in MCI, and dementia progression. Conclusion: Differential correlation analysis, a bioinformatics tool to elucidate complicated and interdependent biological systems behind diseases, detects effective MCI markers that cannot be found by single molecule analysis such as t-test. Overall design: To detect plasma miRNA biomarker for MCI, the blood samples were collected from 30 age-matched controls (Normal, 12 males and 18 females, mean age of 70.4) and 23 MCI patients (11 males and 12 females, mean age of 72.8).Total RNA was extracted from plasma using the miRNeasy Mini Kit (Qiagen). Then, the miRCURY LNA™ Universal RT microRNA PCR System, Ready-to-Use Human panel I and panel II, V2. were performed to profile miRNAs differential expression in these plasma samples. Processed data were compared between control and MCI groups.