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Kidney Week

Abstract: TH-OR085

Genetic and Epigenetic Analysis in Genes Affecting Mitochondrial Function Are Associated with CKD in an Older Population

Session Information

Category: CKD (Non-Dialysis)

  • 1901 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention


  • Mcknight, A.J., Queen's University Belfast, Belfast, United Kingdom
  • Cappa, Ruaidhri Conall, Queen's University Belfast, Belfast, United Kingdom
  • Smyth, Laura Jane, Queen's University Belfast, Belfast, United Kingdom
  • Canadas Garre, Marisa, Queen's University Belfast, Belfast, United Kingdom
  • De campos, Cassio P., Utrecht University, Utrecht, Netherlands
  • Skelly, Ryan, Queen's University Belfast, Belfast, United Kingdom
  • Cruise, Sharon, Queen's University Belfast, Belfast, United Kingdom
  • Kee, Frank, Queen's University Belfast, Belfast, United Kingdom
  • Mcguinness, Bernadette, Queen's University Belfast, Belfast, United Kingdom
  • Godson, Catherine, The Conway Institute of Biomolecular and Biomedical, Belfield, Dublin, Ireland
  • Maxwell, Alexander P., Queen's University Belfast, Belfast, United Kingdom

The Northern Ireland COhort for the Longitudinal study of Ageing (NICOLA) is a ten-year project exploring health and lifestyle information in 8,504 people ≥ 50 years of age via a computer assisted personal interview with an associated bioresource. Chronic kidney disease (CKD) affects ~10% of the World’s population and is more prevalent in older individuals. Optimal renal function is critically dependent upon efficient mitochondria, therefore genetic and epigenetic features that lead to mitochondrial dysfunction may influence CKD.


The discovery cohort comprised 2,567 white European individuals with body mass index ranging from 18.5 - 40 kg/m2. Genotyping was performed using Illumina’s Infinium CoreExome array (n=551,839 SNPs directly typed), with data imputed to the Haplotype Reference Consortium. Methylation data was generated using Illumina’s Infinium MethylationEPIC array (866,554 features with single site resolution). PLINK and Partek Genomics Suite were employed to investigate association with eGFR, serum albumin, urea and creatinine. Replication was conducted in an independent cohort of 402 individuals.


SNPs that demonstrated the most evidence for association include an exonic SNP in the mitochondrial genome MT-TL2 gene (rs2853498; A12308G; a key SNP defining mitochondrial Haplogroup U) with increased creatinine levels (P=0.000153, OR=1.185, 95% CI=1.0929-1.2812). SNPs in nuclear genes that influence mitochondrial function include rs77790196 within SLC39A1 (P= 4.4 x10-07, OR=0.0055, 95% CI=0.0007-0.0412) and rs12564199 within JTB (P=6.6 x10-07, OR=0.006, 95% CI=0.0008-0.0449) associated with decreased eGFR.
Analysis of epigenetic data identified eight genes demonstrating differential methylation with p<10-08 and Δβ ±0.2, including ZBED3, ZNF672, and AHCTF1 for participants with early stage CKD compared to individuals with CKD stages 3-5.


These analyses have identified novel associations linking CKD with SNPs and CpG sites. This may serve as a future basis for the development of predictive multi-omic biomarkers and/or increased understanding of CKD pathogenesis.


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