Abstract: TH-PO1002
Differential DNA Methylation in CKD with Particular Reference to APOL1
Session Information
- CKD: Epidemiology, Risk Factors, and Prevention - 1
October 24, 2024 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: CKD (Non-Dialysis)
- 2301 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention
Authors
- Guga, Suri, King's College London, London, London, United Kingdom
- Kular, Dalvir, King's College London, London, London, United Kingdom
- Hayward, Samantha JL, University of Bristol, Bristol, Bristol, United Kingdom
- Saleem, Moin A., University of Bristol, Bristol, Bristol, United Kingdom
- Bramham, Kate, King's College London, London, London, United Kingdom
- Koziell, Ania B., King's College London, London, London, United Kingdom
Background
Individuals of African descent are generally at increased risk of CKD and specific variants of the APOL1 gene play a significant role. However, not all high risk cases progress to CKD suggesting other factors such as co-variants and environmental/ epigenetic modifiers may contribute. The study examined the role of whole genome DNA methylation (DNAm) on CKD, including its impact on both baseline glomerular filtration rate (eGFR) and rate of change in eGFR. Additionally, the study explored whether differntial DNAm might also explain the differing phenotypes associated with high-risk APOL1 genotypes with no protective allele detected.
Methods
Genome-wide DNAm data from the Genetic Epidemiology Network of Arteriopathy (GENOA) was analysed. Phenotypic evaluation including CKD status together with APOL1 risk variant genotype identified 1,394 cases suitable for study. CKD was defined as estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73 m2 and urine albumin-creatinine ratio (uACR) > 30 ug/mg. Bioinformatics tools were used for DNA methylation (DNAm) analysis controlling for age, cell type, BMI, gender and smoking. EWAS and linear regression analysis was performed on CKD and non-CKD cases. The relationship between APOL1 DNAm on baseline eGFR was analysed used linear regression and a mixed-effects model used to analyse the association between DNAm with change in eGFR.
Results
Analysis DNAm in CKD vs non-CKD showed significant differences at 3 CpG islands (p < 0.05). Whole genome DNAm analysis of high risk APOL1 CKD vs. high risk non-CKD cases identified a unique CpG signal as significantly differentially methylated (p < 0.05). . Mixed-effect model analysis detected an association between DNAm and longitudinal eGFR change (p < 0.05). Lastly, linear regression analyses, adjusted for age and the interval between examinations, identified differential DNAm at another unique CpG. No difference in DNAm was detected in high risk genotype vs. low risk APOL1 genotype cases with or without CKD.
Conclusion
The findings suggest that differential DNAm may contribute to CKD. Additionally, APOL1 DNAm appears associated with CKD development. It might also in part explain why some high risk APOL1 genotype cases develop CKD and others do not. Epigenetic markers could aid in understanding the pathogenesis of CKD and suggest novel avenues for targeted interventions.