Plasma microRNA biomarker detection for mild cognitive impairment using differential correlation analysis
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ABSTRACT: 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.
ORGANISM(S): Homo sapiens
PROVIDER: GSE90828 | GEO | 2016/12/10
SECONDARY ACCESSION(S): PRJNA356063
REPOSITORIES: GEO
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