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Plasma microRNA biomarker detection for mild cognitive impairment using differential correlation analysis

机译:使用差异相关分析的血浆microRNA生物标记物检测轻度认知障碍

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Background Mild cognitive impairment (MCI) is an intermediate state between normal aging and dementia including Alzheimer’s disease. 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 plasma microRNA (miRNA) expression profiles of 30 age- and race-matched controls and 23 Japanese MCI patients. 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 might 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.
机译:背景轻度认知障碍(MCI)是正常衰老和痴呆症(包括阿尔茨海默氏病)之间的一种中间状态。就二级预防而言,早期发现痴呆症和MCI是至关重要的问题。血液生物标志物检测是早期检测MCI的一种可能方法。尽管通常通过使用单分子分析(例如t检验)来检测疾病生物标记,但另一种可能的方法是基于分子之间的相互作用。结果对30名年龄和种族匹配的对照以及23名日本MCI患者的血浆microRNA(miRNA)表达谱进行了差异相关分析,该分析检测了病例/对照研究中两个变量之间的相关性差异。选择由20个miRNA组成的20对miRNA作为MCI标记。 20对中的两对miRNA(hsa-miR-191和hsa-miR-101,以及hsa-miR-103和hsa-miR-222)在MCI检测的曲线(AUC)值为0.962时达到了最高面积。包括hsa-miR-191和hsa-miR-125b在内的其他两个miRNA对也获得了≥0.95的高AUC值。对MCI标记物进行了通路分析,以进一步了解生物学意义。结果,hsa-miR-191的相关性崩溃,hsa-miR-125b的相关性可能在MCI和痴呆症进展中起关键作用。结论差异相关分析是一种阐明疾病背后复杂而相互依赖的生物系统的生物信息学工具,可以检测出有效的MCI标记,而t检验等单分子分析无法发现这些标记。

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