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University of Groningen

Chronic kidney disease

Thio, C. H. L.

DOI:

10.33612/diss.133648108

IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from

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Document Version

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Publication date:

2020

Link to publication in University of Groningen/UMCG research database

Citation for published version (APA):

Thio, C. H. L. (2020). Chronic kidney disease: Insights from social and genetic epidemiology. University of

Groningen. https://doi.org/10.33612/diss.133648108

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Stellingen behorende bij het proefschrift

Chronic kidney disease

insights from social and genetic epidemiology

Chris Thio, 27 mei 2020

1. Educational level is inversely associated with chronic kidney disease, but this relation may not be causal (this thesis)

2. Low heart rate variability, an indicator of autonomic dysfunction, does not precede chronic kidney disease (this thesis)

3. A high educational level may be conducive to an environment that offsets genetic risk of chronic kidney disease (this thesis)

4. Chronic kidney disease aggregates in families, and up to 50% of variation in kidney traits can be attributed to genetic factors (this thesis)

5. A genetic risk score based on the combined effects of single nucleotide polymorphisms for creatinine-estimated glomerular filtration rate can be used as a genetic proxy for kidney function

(this thesis)

6. Genetic variants near POU2AF1 and in ADAMTS9-AS2 associate with serum urea in Europeans (this

thesis)

7. Genetic studies on markers of kidney function other than creatinine are needed to advance our understanding of kidney pathophysiology

8. The careful application of concepts from genetics to traditional epidemiology holds promise to revolutionize our understanding of the mechanisms underlying health and disease

9. Given the many stochastic processes that underlie one’s health and social standing, some humility is warranted from those who are healthy and educated

10. “I love deadlines. I love the whooshing sound they make as they fly by” – Douglas Adams, The

Salmon of Doubt

11. “You are smarter than your data. Data do not understand causes and effects; humans do” – Judea Pearl, The Book of Why: The New Science of Cause and Effect

12. “The book can also be a hat” – Stanley Kubrick 13. Epidemiology is (not) dead

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