Abstract: TH-PO996
Genome-Wide DNA Methylation Association Study Identifies DNA Methylation Associated with ESKD
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
Author
- Zhou, Xiaohong, Guangdong Provincial People's Hospital, Guangzhou, Guangdong, China
Background
End stage renal disease (ESRD) is a leading cause of morbidity and mortality worldwide. It has been increasingly appreciated that epigenetic changes, such as DNA methylation, play an important role in kidney disease.
Methods
Here, using Illumina Infinium EPIC arrays, we performed an epigenome-wide association study (EWAS) of DNA methylation in two ESRD cohorts from China (460 ESRD cases and 196 controls with CKD) and Singapore (229 ESRD cases and 508 controls with T2D).
Results
Through a meta-analysis of the association evidences from the two cohorts, we discovered 2400 differentially methylated probes or CpG sites (DMP) whose DNA methylation levels were associated with ESRD at genome wide significance (P < 1.29e-8), with 39% ~ 72% of which were found to be associated with estimated glomerular filtration rate (eGFR) by several EWAS analyses of eGFR. The 2400 DMPs were mostly located in transcriptionally active enhancers, and 42.7% of them were found to be associated with transcriptomic changes according to published eQTM datasets. By interrogating these 2400 DMPs with the genomic functional information for blood, kidney and muscle tissue, we identified 3788 target genes whose transcriptions may be influenced by these DMPs. The enrichment analysis of these target genes revealed the pathways and GO terms related to immunity and inflammation, endocrinology and metabolism, particularly autophagy process, B cell receptor signaling and insulin resistance.
Conclusion
Our findings have not only discovered ESRD associated DNA methylation variations that can be used as biomarkers for ESRD, but also highlighted certain biological processes that are involved in kidney disease progression to ESRD.
Clinical characteristics of the subjects in the GDPH and the KTPH cohort.
| GDPH cohort | AHPL cohort | |||||
| ESRD | CKD | P value | ESRD | CKD | P value | |
| Characteristics | ||||||
| Subjects number | 457 | 196 | - | 229 | 508 | - |
| Age | 48.33(±14.29) | 42.77(±15.57) | < 0.0001 | 61.23 ± 9.94 | 57.68 ± 10.36 | <0.0001 |
| Male cases | 246 (53.83%) | 82(41.83%) | 0.11 | 154 (67.2%) | 286 (56.3%) | 0.005 |
| Complications | ||||||
| Diabetes | 36(11.25%) | 16(8.98%) | 0.5743 | - | - | |
| Hypertension | 226(70.63%) | 45(24.86%) | <0.0001 | 158 (71.2%) | 330 (65.7%) | 0.15 |
| Cardiovascular disease | 108(33.43%) | 5(2.82%) | <0.0001 | 3 (18.8%) | 31 (13.0%) | 0.515 |
| Blood biochemistry | ||||||
| CRP(mg/L) | 6.72(2.75,22.64) | 3.20(2.07,6.20) | <0.0001 | - | - | - |
| Hb A1c% | 5.45(4.90,6.13) | 5.60(5.20,5.90) | 0.475 | 7.05 (6.23,8.20) | 7.80 (6.90,9.00) | <0.0001 |
| Uric acid (umol/L) | 432(361,520) | 367(305,445) | <0.0001 | 445 (377,523) | 454 (386,534) | 0.304 |
| LDL-C (mmol/L) | 2.18(1.50,2.83) | 2.92(1.95,4.00) | <0.0001 | 2.63 (1.97,3.32) | 2.52 (2.11,2.97) | 0.223 |
Funding
- Government Support – Non-U.S.