Elsevier

NeuroToxicology

Volume 33, Issue 6, December 2012, Pages 1450-1453
NeuroToxicology

27th Int Neurotox Conf
Integration of genome-wide expression and methylation data: Relevance to aging and Alzheimer's disease

https://doi.org/10.1016/j.neuro.2012.06.008Get rights and content

Abstract

The progressive and latent nature of neurodegenerative diseases, such as Alzheimer's disease (AD) indicates the role of epigenetic modification in disease susceptibility. Previous studies from our lab show that developmental exposure to lead (Pb) perturbs the expression of AD-associated proteins. In order to better understand the role of DNA methylation as an epigenetic modifications mechanism in gene expression regulation, an integrative study of global gene expression and methylation profiles is essential. Given the different formats of gene expression and methylation data, combining these data for integrative analysis can be challenging. In this paper we describe a method to integrate and analyze gene expression and methylation arrays. Methylation array raw data contain the signal intensities of each probe of CpG sites, whereas gene expression data measure the signal intensity values of genes. In order to combine these data, methylation data of CpG sites have to be associated with genes.

Introduction

There are various studies indicating that global epigenetic modification, such as DNA methylation and chromatin modification, are directly influenced by the environment, and play an important role in the developmental origin of adult disease susceptibility (Aguilera et al., 2010, Dolinoy et al., 2007, Jirtle and Skinner, 2007). This is due to the fact that epigenetic alterations have an important effect on gene expression regulation (Movassagh et al., 2010). The relationship between genetics, gene expression and DNA methylation has been mostly limited to studies focusing on specific genes and transcripts in individual cells or tissues (Li et al., 2009, Movassagh et al., 2010). However, the recent development of genome-wide technologies provides unprecedented opportunities to expand our view of the relationship between the genome, transcriptome and methylome. Hence, the integration of genetic and epigenetic data promises to provide insight into the mechanisms affecting epigenetic alteration, and consequently gene expression and disease susceptibility. Studies from our lab on Alzheimer's disease (AD), which is a progressive neurodegenerative disorder, appearing at old age, show that AD may have a developmental origin (Wu et al., 2008, Zawia and Basha, 2005). Lead (Pb) exposure at an early age influences the expression and regulation of AD-related genes later in life. These studies focused on AD-related genes; however a genome-wide analysis of gene expression and DNA methylation is essential to assess the impact of time and environmental exposure of Pb on the genome and epigenome maps. In this paper we describe a method to integrate and analyze gene expression and methylation arrays. Given the different formats of gene expression and methylation data, combining these data for integrative analysis can be challenging. Methylation array raw data contain the signal intensities of each probe of CpG sites, whereas gene expression data measure the signal intensity values of genes. In order to combine these data, methylation data of CpG sites have to be associated with genes.

Section snippets

Animal exposure

C57BL/6 mice were bred in-house at the University of Rhode Island. The experiment was designed as in previous studies (Basha et al., 2003, Basha et al., 2005). Twenty-four hours after the birth of a new mouse dam is Post-natal day 1 (PND1). Male pups from different dams were randomized, pooled and divided into the two following groups: (1) Control-no exposure to Pb and (2) Pb/E – in utero exposure to Pb beginning on gestational day 13 until PND20. All the pups born from control dams are pooled

Results and discussion

The results of two groups: control PND20 (C20) and Pb-exposed PND700 (E700), with three animals averaged for each group are presented. C20 was not compared to E20 because our analysis showed little differences occurring at this early stage (Dosunmu et al., 2012). We determined the relationship between differential gene expression and the differential methylation of (E700  C20) groups by creating a scatter plot, as shown in Fig. 1. Hypermethylated genes that were down-regulated clustered in the

Conclusion

Our data show that the gene expression changes are latent. However, the integration of genomic and epigenomic data reveals that the effects of early Pb exposure on the methylation of genes may be persistent. DNA hypermethylation is shown to have a strong correlation with the down-regulation of gene expression suggesting that early life exposure to Pb interferes with the methylation pattern of genes, which is then sustained throughout life, and has an impact on an animal's ability to respond to

Conflict of interest statement

The authors declare that there is no conflict of interest.

Acknowledgements

This research was supported by the Intramural Research Program of the National Institutes of Health (NIH), National Institute of Environmental Health Sciences (NIEHS) and by grants (ES013022 and AG027246) from the NIH awarded to NHZ. The research core facility was funded (P20RR016457) by the National Center for Research Resources (NCRR), a component of NIH.

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