Table 2.

Examples of epigenetic biomarker applications in diabetes

Epigenetic biomarker	Study subjects	Sample types	Detection Methods	Findings	References
miRNA	Human individual	Pancreatic islet	RNA-sequencing, small-RNA sequencing and genotyping	14 T2D-related miRNAs	[82]
miRNA	Individuals with or without diabetes	Serum	Next-generation sequencing and qPCR technologies (ViiA 7, OpenArray, Dynamic Array)	High-throughput qPCR can be applied for quantitative assessment of miRNA signature	[83]
miRNA	T2D patients from HKDR cohort	Serum	Microarray and qPCR	miR-122-5p and miR-455-3p are potential biomarkers for development of liver cancer in T2D	[84]
miRNA	Women with GDM	Postpartum plasma	OpenArray and qPCR	miR-369-3p is a potential biomarker to predict T2D in women with GDM	[86]
DNA methylation	Incident T2D patients in LOLIPOP study	Peripheral blood	Methylation arrays, next-generation sequencing and pyrosequencing	5 methylation markers including a site in TXNIP gene are associated with incident T2D	[88]
DNA methylation	Individuals with or without diabetes complications	Genomic DNA of whole blood and blood monocytes	Methylation arrays and pyrosequencing	Differential methylation at a number of loci	[91]
DNA methylation	Individuals with T2D and with chronic kidney disease	Peripheral blood	Methylation arrays	Methylation loci associated with baseline and decline in renal function	[92]
DNA methylation	T2D patients from HKDR cohort	Genomic DNA of whole blood	Methylation arrays	CpG sites associated with baseline eGFR and eGFR slope respectively	[93]
Histone modification	DCCT/EDIC participants	Peripheral blood	Chromatin immunoprecipitation (ChIP)—qPCR	Association between HbA1c and H3K9ac, and potential role of epigenetics in metabolic memory	[94]
Relative leukocyte telomere length (rLTL)	T2D patients from HKDR cohort	DNA from whole blood	qPCR for rLTL measurements	rLTL is inversely associated with incident diabetic cardiovascular and renal complications	[96, 97]