Diabetologie und Stoffwechsel 2018; 13(S 01): S22
DOI: 10.1055/s-0038-1641819
Poster
Typ-2-Diabetes – Pathophysiologie II
Georg Thieme Verlag KG Stuttgart · New York

Critical evaluation of DNA methylation markers for type-2-diabetes risk prediction

C Krause
1   University of Lübeck, Medical Department I, Lübeck, Germany
,
H Sievert
1   University of Lübeck, Medical Department I, Lübeck, Germany
,
M Grohs
1   University of Lübeck, Medical Department I, Lübeck, Germany
,
C Geißler
1   University of Lübeck, Medical Department I, Lübeck, Germany
,
AT El Gammal
2   University Medical Center Hamburg-Eppendorf, Department of General, Visceral and Thoracic Surgery, Hamburg, Germany
,
S Wolter
2   University Medical Center Hamburg-Eppendorf, Department of General, Visceral and Thoracic Surgery, Hamburg, Germany
,
CM Lill
3   University of Lübeck, Institute of Neurogenetics, Lübeck, Germany
,
UM Krämer
4   University of Lübeck, Department of Neurology, Lübeck, Germany
5   University of Lübeck, Institute of Psychology II, Lübeck, Germany
,
M Kasten
3   University of Lübeck, Institute of Neurogenetics, Lübeck, Germany
6   University of Lübeck, Dept. of Psychiatry and Psychotherapy, Lübeck, Germany
,
C Klein
3   University of Lübeck, Institute of Neurogenetics, Lübeck, Germany
,
G Brabant
1   University of Lübeck, Medical Department I, Lübeck, Germany
,
O Mann
2   University Medical Center Hamburg-Eppendorf, Department of General, Visceral and Thoracic Surgery, Hamburg, Germany
,
H Lehnert
1   University of Lübeck, Medical Department I, Lübeck, Germany
,
H Kirchner
1   University of Lübeck, Medical Department I, Lübeck, Germany
› Author Affiliations
Further Information

Publication History

Publication Date:
26 April 2018 (online)

Also available at
 
 

    Recent epigenome wide association studies (EWAS) indicate a benefit for type-2-diabetes (T2D) risk prediction when leucocyte DNA methylation information is known. Especially methylation at two CpG loci, cg06500161 (ABCG1) and cg11024682 (SREBF1), are promising EWAS-markers to improve risk scoring. Therefore, we evaluated these beyond population-based approaches in the context of personalized medicine.

    By bisulfite pyrosequencing, methylation of both CpG sites was measured in blood of obese and lean subjects without T2D (n = 177), and in liver and visceral adipose tissue (VAT) of obese subjects with or without T2D (n = 99). Linear regression analysis was included to access a relationship between DNA methylation and other metabolic parameters. A methylation risk score (MRS) was calculated as model of additive effects based on both positions. For optimal risk modelling, we included analysis of single nucleotide polymorphisms (SNPs) in both genes.

    Our results show a tissue specific correlation between methylation at cg11024682 and body mass index (BMI) in blood and liver. Leucocyte methylation of both loci is significantly increased in subjects with high HOMA-IR (> 2.5) and correlates with fasting glucose. The neighboring SNP rs9982016 influences methylation at cg06500161 without being associated with T2D itself. Calculation of an MRS using DNA methylation information from blood or VAT enabled a stratification of insulin resistant and sensitive subjects.

    Our results highlight the tissue specificity of DNA methylation. Nevertheless, methylation at both loci in blood proved to be a promising approach for risk assessment and could be valuable for personalized T2D risk prediction in the future.


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