DNA methylation age calculators reveal association with diabetic neuropathy in type 1 diabetes

• Published in: Clinical epigenetics Vol. 12; no. 1; p. 52
• Main Authors: Roshandel, Delnaz, Chen, Zhuo, Canty, Angelo J, Bull, Shelley B, Natarajan, Rama, Paterson, Andrew D
• Format: Journal Article
• Language: English
• Published: Germany BioMed Central 05-04-2020
• Subjects: Adolescent; Adult; Age; Aging; Albumins - metabolism; Autonomic nervous system; Blood pressure; Cardiovascular diseases; CpG Islands; Deoxyribonucleic acid; Diabetes; Diabetes mellitus (insulin dependent); Diabetes Mellitus, Type 1 - complications; Diabetes Mellitus, Type 1 - genetics; Diabetes Mellitus, Type 1 - metabolism; Diabetic Neuropathies - genetics; Diabetic Neuropathies - metabolism; Diabetic neuropathy; DNA; DNA Methylation; Epidemiology; Epigenesis, Genetic; Epigenetics; Exercise; Female; Gene expression; Genome-Wide Association Study - methods; Humans; Insulin; Male; Mortality; Nephropathy; Oligonucleotide Array Sequence Analysis; Peripheral neuropathy; Physical activity; Physical fitness; Proteins; Retinopathy; Risk factors; Skin; Young Adult; DNA methylation age; Type 1 diabetes; Diabetic complications
• ISSN: 1868-7075; 1868-7083; 1868-7083; 1868-7075
• DOI: 10.1186/s13148-020-00840-6

Many CpGs become hyper or hypo-methylated with age. Multiple methods have been developed by Horvath et al. to estimate DNA methylation (DNAm) age including Pan-tissue, Skin & Blood, PhenoAge, and GrimAge. Pan-tissue and Skin & Blood try to estimate chronological age in the normal population whereas PhenoAge and GrimAge use surrogate markers associated with mortality to estimate biological age and its departure from chronological age. Here, we applied Horvath's four methods to calculate and compare DNAm age in 499 subjects with type 1 diabetes (T1D) from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study using DNAm data measured by Illumina EPIC array in the whole blood. Association of the four DNAm ages with development of diabetic complications including cardiovascular diseases (CVD), nephropathy, retinopathy, and neuropathy, and their risk factors were investigated.
Pan-tissue and GrimAge were higher whereas Skin & Blood and PhenoAge were lower than chronological age (p < 0.0001). DNAm age was not associated with the risk of CVD or retinopathy over 18-20 years after DNAm measurement. However, higher PhenoAge (β = 0.023, p = 0.007) and GrimAge (β = 0.029, p = 0.002) were associated with higher albumin excretion rate (AER), an indicator of diabetic renal disease, measured over time. GrimAge was also associated with development of both diabetic peripheral neuropathy (OR = 1.07, p = 9.24E-3) and cardiovascular autonomic neuropathy (OR = 1.06, p = 0.011). Both HbA1c (β = 0.38, p = 0.026) and T1D duration (β = 0.01, p = 0.043) were associated with higher PhenoAge. Employment (β = - 1.99, p = 0.045) and leisure time (β = - 0.81, p = 0.022) physical activity were associated with lower Pan-tissue and Skin & Blood, respectively. BMI (β = 0.09, p = 0.048) and current smoking (β = 7.13, p = 9.03E-50) were positively associated with Skin & Blood and GrimAge, respectively. Blood pressure, lipid levels, pulse rate, and alcohol consumption were not associated with DNAm age regardless of the method used.
Various methods of measuring DNAm age are sub-optimal in detecting people at higher risk of developing diabetic complications although some work better than the others.