Epigenetic landscapes in human pancreatic islets reveal distinct drivers for adaptation to age and type 2 diabetes

This repository contains the analysis scripts used in the study “Distinct epigenetic landscapes of aging and type 2 diabetes in human pancreatic islets”.

The code implements the full analytical workflow applied to human pancreatic islet multi-omic data, including DNA methylation (Illumina EPIC), RNA-sequencing, and genotyping data. Scripts are written primarily in R.

Scripts are numbered to reflect the logical order of the analysis pipeline:

01-qc_methylation.R – DNA methylation quality control and preprocessing

02-PCA.R – Principal component analysis (PCA) and covariate assessment

03-EWAS.R – Epigenome-wide association studies (EWAS)

04-Volcano_plots.R – Visualization of EWAS results

05-mQTL.R – cis-mQTL analysis to identify CpG sites under genetic control

06-eQTM.R – eQTM model specification 

07-eQTM_target.R – eQTM target gene identification 

08-WGCNA.R – Weighted gene co-expression network analysis (WGCNA) of eQTM-identified genes

09-eQTL.R – Cis-eQTL analysis 

10-MR_file_prep.R – Preparation and harmonisation of mQTL and eQTL inputs for Mendelian randomization

11-MR.R – Mendelian randomization (MR) analyses testing causal effects of DNA methylation on gene expression

12-Methylation_score.R – Construction of a methylation risk score (MRS)

13-Polygenic_score.sh – Polygenic risk score (PRS) calculation

14-Score_plots.R – Visualisation and performance assessment of MRS/PRS models