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. 2010 Feb 1;5(2):e8898.
doi: 10.1371/journal.pone.0008898.

Joint genome-wide profiling of miRNA and mRNA expression in Alzheimer's disease cortex reveals altered miRNA regulation

Juan Nunez-Iglesias  1 , Chun-Chi Liu, Todd E Morgan, Caleb E Finch, Xianghong Jasmine Zhou
Affiliations

Joint genome-wide profiling of miRNA and mRNA expression in Alzheimer's disease cortex reveals altered miRNA regulation

Juan Nunez-Iglesias et al. PLoS One. .

Abstract

Although microRNAs are being extensively studied for their involvement in cancer and development, little is known about their roles in Alzheimer's disease (AD). In this study, we used microarrays for the first joint profiling and analysis of miRNAs and mRNAs expression in brain cortex from AD and age-matched control subjects. These data provided the unique opportunity to study the relationship between miRNA and mRNA expression in normal and AD brains. Using a non-parametric analysis, we showed that the levels of many miRNAs can be either positively or negatively correlated with those of their target mRNAs. Comparative analysis with independent cancer datasets showed that such miRNA-mRNA expression correlations are not static, but rather context-dependent. Subsequently, we identified a large set of miRNA-mRNA associations that are changed in AD versus control, highlighting AD-specific changes in the miRNA regulatory system. Our results demonstrate a robust relationship between the levels of miRNAs and those of their targets in the brain. This has implications in the study of the molecular pathology of AD, as well as miRNA biology in general.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Permutation of miRNA-mRNA target relationships reveals a positive correlation between miRNAs and their targets, or negative for some high-prevalence mRNAs.
(A) Histogram of permuted values of mean correlation between levels of miRNAs and those of their target mRNAs. Red arrowhead indicates true value. (2-sided p-value: 0.002) (B), (C) Weighted correlation shift (formula image) and formula image for a range of cutoffs of log (base 2) mRNA mean expression. (D), (E) Histogram of permuted values for mRNA log-expression cutoffs 4 and 11. (All plots were generated using a ddG cutoff of formula image kcal/mol.)
Figure 2
Figure 2. Histograms of miRNA- and mRNA-level p-values.
mRNA (RefSeq) (A) and miRNA (B) p-value histograms using mRNA log-expression cutoff 4. The p-values are from 1,000 permutations. Here, formula image is the observed mean correlation for that RNA, and formula image is the corresponding permuted correlation.
Figure 3
Figure 3. NCI-60 overall weighted correlation shift, significance, and p-value distributions.
(A) Weighted correlation shift (formula image) vs minimum log (base 2) mRNA expression value. (B) Significance (sign(formula image)formula image(1-formula image)) vs minimum log (base 2) mRNA expression value for the NCI-60 cancer cell line dataset. (C), (D) Distribution of p-values of mRNA and miRNA
Figure 4
Figure 4. Primary breast tumor p-value distributions for mRNA (A) and miRNA (B) correlations.
See this image and copyright information in PMC

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