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Fig. 1 | Acta Neuropathologica Communications

Fig. 1

From: Serum microRNA miR-501-3p as a potential biomarker related to the progression of Alzheimer’s disease

Fig. 1

A novel serum miRNA biomarker hsa-miR-501-3p that differentiates patients with Alzheimer’s disease (AD) from controls (CT). a Serum miRNA levels of the three candidates significantly deregulated between AD and controls in the ROW discovery set. Normalized read counts from next-generation sequencing data were converted to a log2 scale and plotted against the disease status. The lower hinge, the line in the middle, and the upper hinge of the box plot show the 25th percentile, 50th percentile (median), and 75th percentile, respectively. The lower whisker extends from the lower hinge to the lowest value that is within 1.5 times the interquartile range (IQR) of the hinge. The upper whisker extends from the upper hinge to the highest value that is within 1.5 times the IQR. LFC: log2 fold change; P: p-value adjusted by the Benjamini–Hochberg procedure for multiple testing correction. b Three candidates’ serum miRNA levels quantified by quantitative reverse transcription PCR (qRT-PCR) in the NIG validation set. Relative expression levels of the miRNAs were calculated using the 2–ΔΔC T method with cel-miR-39-3p (spike-in) and hsa-miR-451a (endogenous control) for normalization and were plotted against the disease status. P-values were computed using the Mann–Whitney U-test between AD and controls. Box plots display the distributions of data in the same way as in Fig. 1a. LFC: log2 fold change. c Significant positive correlation between Mini-Mental State Examination (MMSE) scores and serum hsa-miR-501-3p levels in the NIG validation set. Relative expression levels from the qRT-PCR data were plotted against MMSE. r shows the Spearman rank correlation coefficient. The blue line shows a linear regression line, and a shaded gray area around the line represents 95% confidence intervals. d The receiver-operating characteristic (ROC) curve of serum hsa-miR-501-3p in the NIG validation set. The ROC curve analysis showed 53% sensitivity and 100% specificity. The area under the ROC curve (AUC) was 0.82

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