Quantitative studies of DNA methylation and gene expression in neuropsychiatric traits

K.R. van Eijk

Research output: ThesisDoctoral thesis 1 (Research UU / Graduation UU)

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Abstract

Research has shown that besides genes and environment, epigenetic factors are also playing a role in the development of traits and diseases. Epigenetic changes do not affect the underlying DNA sequence, but affect its structure and is thought to play a major role in regulation of gene expression. DNA methylation, one of the most-characterized epigenetic mechanisms, involves the attachment of a methyl group to the cytosine of a cytosine-phosphate-guanine (CpG) pair. CpG sites often cluster in promoter regions of genes, which are important for control of gene expression. We hypothesize that differences in DNA methylation is involved in disease susceptibility including that of schizophrenia. Schizophrenia is a neuropsychiatric disorder affecting ~1% of the population. The disorder is characterized by positive symptoms (e.g. hallucinations, delusions), and negative symptoms (e.g. social withdrawal and poverty of speech). Despite its high heritability estimate of roughly 80%, only a small proportion can be explained by currently known susceptibility loci. In this thesis, we aimed to study different layers of genomic data (genetic variation, DNA methylation and gene expression) simultaneously in order to get more insight into the biological mechanisms underlying schizophrenia. First, we studied the association between DNA methylation, gene expression, and genetic variation in whole blood of healthy controls. We observed complex and variable patterns of genetic regulation of DNA methylation and gene expression. Secondly, we used the results from a large schizophrenia genome-wide association study to select loci for study of differential gene expression in cases versus controls. We identified three genes of which its expression is under genetic control of disease-associated alleles and for which we also observe different levels of expression between cases and controls. In our third study, we combined the differential gene expression data with DNA methylation profiles. We confirmed that single nucleotide polymorphisms (SNPs), that regulate differentially methylated CpG sites in schizophrenia, are enriched with disease-associated alleles. We were able to provide a specific molecular epigenetic mechanism for at least one known disease locus. In a different study we examined the association between genetic variation and CpG methylation using 22 nuclear schizophrenia families. We observed extensive interaction between the genetic variation and DNA methylation levels, which includes the identification of ‘variation SNPs’ that not so much affect the median level but rather the variance of CpG methylation levels. Since schizophrenia is a brain disorder, we also examined methylation levels from brain samples of patients and control subjects. One of the most significant loci linked to schizophrenia includes micro-RNA137 (miRNA-137). miRNAs are small non-coding RNA molecules and key players in regulation of gene expression. Using these brain samples, we examined the relation between miRNA-137 and DNA methylation. Our findings suggest a possible link between this miRNA and serotonergic and glutamatergic pathways. To conclude, we described genome-wide methods to combine and analyse different types of genomic information. Integrating methylation data with gene expression and genotype data led to the identification of loci that possibly contribute to the susceptibility to schizophrenia.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Utrecht University
Supervisors/Advisors
  • Ophoff, RA, Primary supervisor
  • Boks, Marco, Co-supervisor
Award date25 Jun 2014
Publisher
Print ISBNs978-90-8891-887-2
Publication statusPublished - 25 Jun 2014

Keywords

  • Econometric and Statistical Methods: General
  • Geneeskunde(GENK)
  • Medical sciences
  • Bescherming en bevordering van de menselijke gezondheid

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