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The interplay between genetics, the microbiome, DNA‐methylation & gene‐expression

Bonder, M. J. 2017 [Groningen]: University of Groningen. 172 p.

Research output: ScientificDoctoral Thesis

Documents

  • Title and contents

    Final publisher's version, 359 KB, PDF-document

  • Chapter 1

    Final publisher's version, 294 KB, PDF-document

  • Chapter 2

    Final publisher's version, 2 MB, PDF-document

  • Chapter 3

    Final publisher's version, 846 KB, PDF-document

  • Chapter 4

    Final publisher's version, 615 KB, PDF-document

  • Chapter 5

    Final publisher's version, 1 MB, PDF-document

  • Chapter 6

    Final publisher's version, 1 MB, PDF-document

  • Chapter 7

    Final publisher's version, 2 MB, PDF-document

  • Chapter 8

    Final publisher's version, 1 MB, PDF-document

  • Chapter 9

    Final publisher's version, 3 MB, PDF-document

    Embargo ends: 05/05/2017

  • Chapter 10

    Final publisher's version, 346 KB, PDF-document

  • Appendices

    Final publisher's version, 983 KB, PDF-document

  • Complete thesis

    Final publisher's version, 10 MB, PDF-document

    Embargo ends: 05/05/2017

  • Propositions

    Final publisher's version, 85 KB, PDF-document

There are many factors involved in the development of human diseases and traits. In recent years the field of human genetics has been very successful in linking genetic variation to diseases and traits. By conducting large-scale studies comparing the genetic make-up of affected versus non-affected participants, we have identified thousands of variants in the human genome that are more or less commonly found in cases compared to controls. These genome-wide association studies (GWAS) have been instrumental in the identification of genes linked to a multitude of diseases and traits. Variants in the functional parts of a gene can be relatively straightforward to interpret. However, not all the variants linked to disease can be directly interpreted. By using intermediate molecular data layers, such as gene expression, DNA-methylation or protein levels, we can gain more insight into the genetic variants identified by GWAS.
However, we only get a limited picture of disease by focusing on genetic variation. Another important factor related to disease is the environment. But it is much harder to quantify environmental factors than to determine the genetic differences between two individuals. Using the intermediate molecular data, or biological omics, we can gain insights into the environment of individuals. The environment surrounding individuals can, for instance, influence the composition of their microbiome, but also their gene expression, DNA-methylation and protein levels. By studying the differences in these biological omics in relation to phenotypes and disease, we can learn more about the environmental factors that lead to disease. However, as with GWAS studies, we do not always know what the differences in these biological data layers mean.
In this thesis we have focused on two biological omics, the gut microbiome composition and the DNA-methylome. The gut microbiome is the collection of micro-organisms that live together in the human gut; DNA-methylation is the occurrence of a methyl group bound to the DNA and this mainly occurs at cysteine-guanine pairs. In the first part of the thesis we have focused on inter-individual differences influencing, or influenced by, differences in the microbiome composition, while in the second part, we have focused on changes in DNA-methylation associated to tissue differences and on the influence of genetic variation on DNA-methylation.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
Supervisors/Advisors
Award date22-Mar-2017
Place of Publication[Groningen]
Publisher
Print ISBNs978-90-367-9602-6
Electronic ISBNs978-90-367-9601-9
StatePublished - 2017

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