The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Genome-wide DNA methylation analysis for diabetic nephropathy in type 1 diabetes mellitus
Open accessAbstract
BACKGROUND: Diabetic nephropathy is a serious complication of diabetes mellitus and is associated with considerable morbidity and high mortality. There is increasing evidence to suggest that dysregulation of the epigenome is involved in diabetic nephropathy. We assessed whether epigenetic modification of DNA methylation is associated with diabetic nephropathy in a case-control study of 192 Irish patients with type 1 diabetes mellitus (T1D). Cases had T1D and nephropathy whereas controls had T1D but no evidence of renal disease. METHODS: We performed DNA methylation profiling in bisulphite converted DNA from cases and controls using the recently developed Illumina Infinium HumanMethylation27 BeadChip, that enables the direct investigation of 27,578 individual cytosines at CpG loci throughout the genome, which are focused on the promoter regions of 14,495 genes. RESULTS: Singular Value Decomposition (SVD) analysis indicated that significant components of DNA methylation variation correlated with patient age, time to onset of diabetic nephropathy, and sex. Adjusting for confounding factors using multivariate Cox-regression analyses, and with a false discovery rate (FDR) of 0.05, we observed 19 CpG sites that demonstrated correlations with time to development of diabetic nephropathy. Of note, this included one CpG site located 18 bp upstream of the transcription start site of UNC13B, a gene in which the first intronic SNP rs13293564 has recently been reported to be associated with diabetic nephropathy. CONCLUSION: This high throughput platform was able to successfully interrogate the methylation state of individual cytosines and identified 19 prospective CpG sites associated with risk of diabetic nephropathy. These differences in DNA methylation are worthy of further follow-up in replication studies using larger cohorts of diabetic patients with and without nephropathy.
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Cited by
Du, P., Zhang, X., Huang, C.-C., Jafari, N., Kibbe, W. A., Hou, L., & Lin, S. M. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-587 · Cited by 2,136
Epigenetics and epigenomics in diabetic kidney disease and metabolic memory
Kato, M., & Natarajan, R. (2019) · Nature Reviews Nephrology · doi:10.1038/s41581-019-0135-6 · Cited by 600
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“…in T2D islets is in the same range as reported for other non-malignant conditions analysed with the same technology platform (19 in T1D-related nephropathy; Bell et al , 2010); 84 and 360, respectively, in analyses of ageing in cells and tissue specimens (Bork et al , 2009; Rakyan et al , 2010).”
Diabetic nephropathy—emerging epigenetic mechanisms
Kato, M., & Natarajan, R. (2014) · Nature Reviews Nephrology · doi:10.1038/nrneph.2014.116 · Cited by 318
Metadata
- Authors
- Bell, C. G., Teschendorff, A. E., Rakyan, V. K., Maxwell, A. P., Beck, S., & Savage, D. A.
- Venue
- BMC Medical Genomics
- Published
- 2010-08-05
- Volume
- 3
- Issue
- 1
- Pages
- 33-33
- ISSN
- 1755-8794 (ISSN-L)
- OpenAlex
- W2150250444
- Cited by
- 305
- References
- 39
- FWCI
- 8.98
- Type
- journal article
- Language
- en
- Open access
- gold
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