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

Nunez-Iglesias J, Liu CC, Morgan TE, Finch CE, Zhou XJ - PLoS ONE (2010)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Molecular and Computational Biology, University of Southern California, Los Angeles, California, United States of America.

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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Related in: MedlinePlus

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,  is the observed mean correlation for that RNA, and  is the corresponding permuted correlation.
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pone-0008898-g002: 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, is the observed mean correlation for that RNA, and is the corresponding permuted correlation.

Mentions: The observed distributions of empirical p-values for both miRNAs and mRNAs are shown in Figure 2. (An equivalent figure using the TargetScan miRNA target prediction method is shown in Figure S3, which shows that this result is robust with respect to the prediction method used.) These histograms reveal that most miRNA-mRNA pairs are actually uncorrelated, with only about 60 miRNAs and 400 mRNAs contributing to the positive correlation bias detected among all pairs. Interestingly, despite a positive correlation on average among all miRNA-target pairs, we also found strong peak of about 20 negatively correlated miRNAs and 300 negatively correlated mRNAs. Therefore, the positive correlation average masks distinct populations of positively and negatively correlated miRNA-target pairs, and it is the relative abundance of positive and negative correlations that drives the average.


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

Nunez-Iglesias J, Liu CC, Morgan TE, Finch CE, Zhou XJ - PLoS ONE (2010)

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,  is the observed mean correlation for that RNA, and  is the corresponding permuted correlation.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2813862&req=5

pone-0008898-g002: 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, is the observed mean correlation for that RNA, and is the corresponding permuted correlation.
Mentions: The observed distributions of empirical p-values for both miRNAs and mRNAs are shown in Figure 2. (An equivalent figure using the TargetScan miRNA target prediction method is shown in Figure S3, which shows that this result is robust with respect to the prediction method used.) These histograms reveal that most miRNA-mRNA pairs are actually uncorrelated, with only about 60 miRNAs and 400 mRNAs contributing to the positive correlation bias detected among all pairs. Interestingly, despite a positive correlation on average among all miRNA-target pairs, we also found strong peak of about 20 negatively correlated miRNAs and 300 negatively correlated mRNAs. Therefore, the positive correlation average masks distinct populations of positively and negatively correlated miRNA-target pairs, and it is the relative abundance of positive and negative correlations that drives the average.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Molecular and Computational Biology, University of Southern California, Los Angeles, California, United States of America.

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.

Show MeSH
Related in: MedlinePlus