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Abstract: SA-PO322

Sex-Specific Methylation Indices Improve Risk Detection for Kidney Disease in the PROFIL Diabetes Study

Session Information

Category: Diabetic Kidney Disease

  • 702 Diabetic Kidney Disease: Clinical

Authors

  • El-Osta, Sam, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
  • Khurana, Ishant, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
  • Maxwell, Scott S., Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
  • Hansen, Tine, Steno Diabetes Center Copenhagen, Herlev, Capital Region of Denmark, Denmark
  • Ahluwalia, Tarunveer S., Steno Diabetes Center Copenhagen, Herlev, Capital Region of Denmark, Denmark
  • Persson, Frederik, Steno Diabetes Center Copenhagen, Herlev, Capital Region of Denmark, Denmark
  • Rossing, Peter, Steno Diabetes Center Copenhagen, Herlev, Capital Region of Denmark, Denmark
Background

While sex-related differences in type 1 diabetic (T1D) are known to disproportionately affect the development and progression of diabetic kidney disease (DKD), genome wide association studies have failed to discern a genetic influence that stratify disease. This study assessed sex differences in the epigenetic architecture to define novel circulating biomarkers of DKD.

Methods

Despite recent improvements in BeadChip arrays we have used sequencing for broader genomic coverage to define methylation architecture of circulating leukocytes. Constructed on the Kidney Diseases, Improving Global Outcomes (KDIGO) classification of chronic kidney disease we characterised leukocyte methylation profiles by sequencing (methyl-seq) from the Steno Diabetes Centre Copenhagen PROFIL cohort (n=124). The case and control registry comprised of people living without diabetes (n=20) and a low-risk group without DKD (LR, n=36) as well as a moderate risk (MR, n=27), high risk (HR, n=21) and very high risk (VHR, n=20) groups living with DKD. To understand sex-related differences in methylation three-way analyses were performed to distinguish male and female profiles compared to combined sex analyses. Functional methylation analyses assessed pathways and regulatory elements associated with DKD. Differential methylation indices were used to characterise sex-specific biomarkers for DKD risk using eGFR for the prediction of disease progression.

Results

Methylation analyses identified exceptional gene body and promoter methylation in the PROFIL registry emphasizing the importance of sequencing methodologies to improve quantitative epigenetic classification by KDIGO. Methylation was disproportionally associated between sexes for the DKD groups (MR, HR and VHR) when compared to the LR group. Methylation was significantly reduced in females when compared with increased quantitative methylation observed in males. Combinatorial ROC analysis for DKD risk and eGFR decline identified sex-specific methylation scores predictive of DKD progression.

Conclusion

PROFIL provides a T1D framework into the pathogenesis of kidney disease and define sex-specific methylation indices that improve diagnostic performance above clinical modelling alone.

Funding

  • Government Support – Non-U.S.