Dataset Information

Large scale aggregate microarray analysis reveals three distinct molecular subclasses of human preeclampsia.

ABSTRACT:

Background

Preeclampsia (PE) is a life-threatening hypertensive pathology of pregnancy affecting 3-5% of all pregnancies. To date, PE has no cure, early detection markers, or effective treatments short of the removal of what is thought to be the causative organ, the placenta, which may necessitate a preterm delivery. Additionally, numerous small placental microarray studies attempting to identify "PE-specific" genes have yielded inconsistent results. We therefore hypothesize that preeclampsia is a multifactorial disease encompassing several pathology subclasses, and that large cohort placental gene expression analysis will reveal these groups.

Results

To address our hypothesis, we utilized known bioinformatic methods to aggregate 7 microarray data sets across multiple platforms in order to generate a large data set of 173 patient samples, including 77 with preeclampsia. Unsupervised clustering of these patient samples revealed three distinct molecular subclasses of PE. This included a "canonical" PE subclass demonstrating elevated expression of known PE markers and genes associated with poor oxygenation and increased secretion, as well as two other subclasses potentially representing a poor maternal response to pregnancy and an immunological presentation of preeclampsia.

Conclusion

Our analysis sheds new light on the heterogeneity of PE patients, and offers up additional avenues for future investigation. Hopefully, our subclassification of preeclampsia based on molecular diversity will finally lead to the development of robust diagnostics and patient-based treatments for this disorder.

SUBMITTER: Leavey K

PROVIDER: S-EPMC4332506 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

Large scale aggregate microarray analysis reveals three distinct molecular subclasses of human preeclampsia.

Leavey Katherine K Bainbridge Shannon A SA Cox Brian J BJ

PloS one 20150213 2

<h4>Background</h4>Preeclampsia (PE) is a life-threatening hypertensive pathology of pregnancy affecting 3-5% of all pregnancies. To date, PE has no cure, early detection markers, or effective treatments short of the removal of what is thought to be the causative organ, the placenta, which may necessitate a preterm delivery. Additionally, numerous small placental microarray studies attempting to identify "PE-specific" genes have yielded inconsistent results. We therefore hypothesize that preecla ...[more]

PMID: 25679511

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Project description:BackgroundTranscriptional cis-regulatory modules (for example, enhancers) play a critical role in regulating gene expression. While many individual regulatory elements have been characterized, they have never been analyzed as a class.ResultsWe have performed the first such large-scale study of cis-regulatory modules in order to determine whether they have common properties that might aid in their identification and contribute to our understanding of the mechanisms by which they function. A total of 280 individual, experimentally verified cis-regulatory modules from Drosophila were analyzed for a range of sequence-level and functional properties. We report here that regulatory modules do indeed share common properties, among them an elevated GC content, an increased level of interspecific sequence conservation, and a tendency to be transcribed into RNA. However, we find that dense clustering of transcription factor binding sites, especially homotypic clustering, which is commonly believed to be a general characteristic of regulatory modules, is rather a feature that belongs chiefly to a specific subclass. This has important implications for current computational approaches, many of which are biased toward this subset. We explore two new strategies to assess binding site clustering and gauge their performances with respect to their ability to detect all 280 modules and various functionally coherent subsets.ConclusionOur findings demonstrate that cis-regulatory modules share common features that help to define them as a class and that may lead to new insights into mechanisms of gene regulation. However, these properties alone may not be sufficient to reliably distinguish regulatory from non-regulatory sequences. We also demonstrate that there are distinct subclasses of cis-regulatory modules that are more amenable to in silico detection than others and that these differences must be taken into account when attempting genome-wide regulatory element discovery.

Project description:Background: MicroRNAs (miRNAs) are short non-coding RNAs predicted to regulate one third of protein-coding genes via mRNA targeting. In conjunction with key transcription factors, such as the repressor REST (RE1 silencing transcription factor), miRNAs play crucial roles in neurogenesis, which requires a highly orchestrated program of gene expression to ensure the appropriate development and function of diverse neural cell types. Whilst previous studies have highlighted select groups of miRNAs during neural development, there remains a need for amenable models in which miRNA expression and function can be analyzed over the duration of neurogenesis. Principal Findings: We performed large-scale expression profiling of miRNAs in human NTera2/D1 (NT2) cells during retinoic acid (RA)-induced transition from progenitors to fully differentiated neural phenotypes. Our results revealed dynamic changes of miRNA patterns, resulting in distinct miRNA subsets that could be linked to specific neurodevelopmental stages. Moreover, the cell-type specific miRNA subsets were very similar in NT2-derived differentiated cells and human primary neurons and astrocytes. Further analysis identified miRNAs as putative regulators of REST, as well as candidate miRNAs targeted by REST. Finally, we confirmed the existence of two predicted miRNAs; pred-MIR191 and pred-MIR222 associated with SLAIN1 and FOXP2, respectively, and provided some evidence of their potential co-regulation. Conclusions: In the present study, we demonstrate that regulation of miRNAs occurs in precise patterns indicative of their roles in cell fate commitment, progenitor expansion and differentiation into neurons and glia. Furthermore, the similarity between our NT2 system and primary human cells suggests their roles in molecular pathways critical for human in vivo neurogenesis. The experiment consists of a total of 51 arrays: 29 retinoic acid time series arrays (0,2,4,6,8,12,14,21 and 28 days), 2 each of NT2-derived neurons and astrocytes, 12 primary human fetal astrocytes, 3 primary human embryonic astrocytes and 3 primary human neurons. Each condition has a minimum of 2 biological replicates. The samples were compared as single channel experiments. NOTE: The raw data files were submitted as generated in Quantarray with 2 channels, but due to issues with the control sample dye (Cy5 on Channel 1), only the Channel 2 (Cy3) data was analysed.

Dataset Information

Large scale aggregate microarray analysis reveals three distinct molecular subclasses of human preeclampsia.

Background

Results

Conclusion

Publications

Large scale aggregate microarray analysis reveals three distinct molecular subclasses of human preeclampsia.

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