Publication

Advancing systems medicine based methods to predict drug response in diabetic kidney disease

Mulder, S., 2020, [Groningen]: University of Groningen. 198 p.

Research output: ThesisThesis fully internal (DIV)

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Documents

  • Title and contents

    Final publisher's version, 755 KB, PDF document

  • Chapter 1

    Final publisher's version, 8.17 MB, PDF document

  • Chapter 2

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  • Chapter 3

    Final publisher's version, 8.06 MB, PDF document

  • Chapter 4

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  • Chapter 5

    Final publisher's version, 10.3 MB, PDF document

  • Chapter 6

    Final publisher's version, 9.17 MB, PDF document

  • Chapter 7

    Final publisher's version, 7.6 MB, PDF document

  • Complete thesis

    Final publisher's version, 59.5 MB, PDF document

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  • Propositions

    Final publisher's version, 12.3 KB, PDF document

DOI

  • Skander Mulder
In this thesis we identified several biomarkers that can predict diabetic kidney disease (DKD) progression and drug response. The identified biomarkers belong to multiple molecular pathways such as: inflammation, ECM degradation, fibrosis, energy metabolism and vascular function. The multiple pathways identified in this thesis indicate that DKD is a heterogeneous disease with a complex underlying pathophysiology. In addition, they provide insights in the underlying molecular mechanisms for how the drugs examined in this thesis may confer long-term kidney protection and they may even aid in identifying new drug targets for patients with DKD. Furthermore, the discovered and validated biomarkers and biomarker panels may pave the way for a personalized treatment approach and inform best (drug) treatment choices for individual patients.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
Supervisors/Advisors
Award date3-Nov-2020
Place of Publication[Groningen]
Publisher
Publication statusPublished - 2020

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