Differential Methylation of Telomere-Related Genes Is Associated with Kidney Disease in Individuals with Type 1 Diabetes.
Claire HillSeamus DuffyLaura M KettyleLiane McGlynnErkka ValoRany M SalemAlexander ThompsonElizabeth J SwanJill KilnerPeter RossingPaul G ShielsMaria LajerPer-Henrik GroopAlexander Peter MaxwellAmy Jayne McKnightnull On Behalf Of The Genie ConsortiumPublished in: Genes (2023)
Diabetic kidney disease (DKD) represents a major global health problem. Accelerated ageing is a key feature of DKD and, therefore, characteristics of accelerated ageing may provide useful biomarkers or therapeutic targets. Harnessing multi-omics, features affecting telomere biology and any associated methylome dysregulation in DKD were explored. Genotype data for nuclear genome polymorphisms in telomere-related genes were extracted from genome-wide case-control association data (n = 823 DKD/903 controls; n = 247 end-stage kidney disease (ESKD)/1479 controls). Telomere length was established using quantitative polymerase chain reaction. Quantitative methylation values for 1091 CpG sites in telomere-related genes were extracted from epigenome-wide case-control association data (n = 150 DKD/100 controls). Telomere length was significantly shorter in older age groups ( p = 7.6 × 10 -6 ). Telomere length was also significantly reduced ( p = 6.6 × 10 -5 ) in DKD versus control individuals, with significance remaining after covariate adjustment ( p = 0.028). DKD and ESKD were nominally associated with telomere-related genetic variation, with Mendelian randomisation highlighting no significant association between genetically predicted telomere length and kidney disease. A total of 496 CpG sites in 212 genes reached epigenome-wide significance ( p ≤ 10 -8 ) for DKD association, and 412 CpG sites in 193 genes for ESKD. Functional prediction revealed differentially methylated genes were enriched for Wnt signalling involvement. Harnessing previously published RNA-sequencing datasets, potential targets where epigenetic dysregulation may result in altered gene expression were revealed, useful as potential diagnostic and therapeutic targets for intervention.
Keyphrases
- dna methylation
- genome wide
- gene expression
- case control
- big data
- single cell
- copy number
- global health
- electronic health record
- stem cells
- public health
- machine learning
- type diabetes
- rna seq
- high resolution
- deep learning
- cell proliferation
- artificial intelligence
- systematic review
- genome wide identification
- human health