DNA Methylation mediation of Adverse Outcomes in Type 2 Diabetes

1 Background

DCCT-EDIC Trial

1.1 (Chen et al. 2016) DCCT-EDIC

  • Examined DNA methylation data collected in the DCCT-EDIC study (\(n=1,441\)) using two sets of samples:
Samples Case Control Time of Sample Collection
Whole Blood DNA 32 31 EDIC Study baseline (1991-1993)
Monocytes 31 30 EDIC Study years 16-17 (2009-2010)

where cases and controls were defined by:

  • Cases: DCCT conventional therapy group subjects with mean DCCT HbA1c > 9.1% and showing retinopathy or albuminuria progression by EDIC Study year 10.

  • Controls: DCCT intensive therapy group subjects with mean DCCT HbA1c < 7.3% and without complication progression by EDIC year 10.

  • Objective:

    1. identify the differentially methylated loci between the cases and controls
    2. whether or not the differential methylation levels persisted from baseline to year 16-17.

  • Finding:

    1. after adjustment, they identified 135 hypo-methylated CpG sites and 225 hyper-methylated CpG sites in cases vs controls.
    2. partly due to the differing cell-types in baseline and year 16-17 samples, they only identified 4 hypo-methylated and 8 hyper-methylated sites that were persistent.

1.2 (Chen et al. 2020) DCCT-EDIC

  • A larger cohort of 499 randomly selected participants: 125 each of the DCCT groups (Primary Intensive, Primary Conventional, Secondary Intensive, Secondary Conventional). One subject was excluded due to large differences in estimated white blood cell composition.

  • 815,432 CpG sites, and identified 43 CpG sites associated with mean-DCCT HbA1c (how long and far back?) at a false discovery rate of \(<5\%\), which was further reduced to 11 CpG sites after Bonferroni adjustment (\(\alpha = 0.05\)).

  • Findings:

    • “best combinations of multiple CpGs” selected from the top-ten HbA1c-associated CpG sites could explain the association between mean-DCCT HbA1c and the risk of developing diabetic complications, including
      1. \(71\%\) for proliferative diabetic retinopathy (PDR)
      2. \(73\%\) for severe nonproliferative diabetic retinopathy (SNPDR)
      3. \(68\%\) for clinically significant macular edema (CSME)
      4. \(97\%\) for albumin excretion rate \(>300\) per 24h (AER300),
      5. \(92\%\) for eGFR \(<60\) mL min–1 per 1.73 m2 (GFR60)
      6. \(84\%\) for eGFR slope.
    • 4 HbA1c associated CpG sites as having methylation quantitative trait loci (meQTLs), from which one CpG site (cg08309687) had an identified causal effect on GFR60 development.

  • Pre-processing of methylation data was done using R package minfi and association of historical HbA1c and CpG site methylation was estimated by multiple linear regression.

1.3 (Chen et al. 2024) Chen 2024

1.4 Joslin Kidney Study

1.5 Data

  • Subsample of 277 non-Hispanic white subjects with T1D AND had DKD at baseline

1.6 Others

  • A more recent work by (Kim et al. 2021) identified 8 differentially methylated CpG sites associated with type 2 diabetes in a case-control setting (232 cases, 197 controls), using subjects of East Asian ancestry.

  • Recent work (Yan et al. 2024) analyzed a cross-sectional cohort (\(n=399\)) seeking to identify differentially methylated sites among controls, and diabetes and hypertension attributed chronic kidney disease (CKD) patients, of which 136 were diabetic (unspecified type 1 or 2).

  • (Elliott et al. 2017; Juvinao-Quintero et al. 2023) sought to identify causal relationships between DNA methylation and type 2 diabetes ALSPAC-ARIES subjects (867 mothers and 385 fathers) with genetic and DNA methylation data to conduct analyses.

  • The same authors also authored a review (Juvinao-Quintero et al. 2019) of recent advances in causal effect estimation of DNA methylation on type 2 diabetes.

Glossary

  • DM: Diabetes Mellitus

  • EWAS: Epigenome-wide Association Study

  • DCCT: Diabetes Control and Complications Trial (1983-1993)

    • EDIC: Epidemiology of Diabetes Interventions and Complications (1994-present), longitudinal monitoring of patients enrolled in DCCT

  • CpG site: cytosine/guanine

  • PDR: Proliferative Diabetic Retinopathy

  • SNPDR: Severe Nonproliferative Diabetic Retinopathy

  • CSME: Clinically Significant Macular Edema

  • AER: Albumin Excretion Rate

  • meQTL: Methylation Quantitative Trait Loci

References

Chen, Zhuo, Feng Miao, Barbara H Braffett, John M Lachin, Lingxiao Zhang, Xiwei Wu, Delnaz Roshandel, et al. 2020. “DNA Methylation Mediates Development of HbA1c-Associated Complications in Type 1 Diabetes.” Nature Metabolism 2 (8): 744–62.
Chen, Zhuo, Feng Miao, Andrew D Paterson, John M Lachin, Lingxiao Zhang, Dustin E Schones, Xiwei Wu, et al. 2016. “Epigenomic Profiling Reveals an Association Between Persistence of DNA Methylation and Metabolic Memory in the DCCT/EDIC Type 1 Diabetes Cohort.” Proceedings of the National Academy of Sciences 113 (21): E3002–11.
Chen, Zhuo, Eiichiro Satake, Marcus G Pezzolesi, Zaipul I Md Dom, Devorah Stucki, Hiroki Kobayashi, Anna Syreeni, et al. 2024. “Integrated Analysis of Blood DNA Methylation, Genetic Variants, Circulating Proteins, microRNAs, and Kidney Failure in Type 1 Diabetes.” Science Translational Medicine 16 (748): eadj3385.
Elliott, Hannah R, Hashem A Shihab, Gabrielle A Lockett, John W Holloway, Allan F McRae, George Davey Smith, Susan M Ring, Tom R Gaunt, and Caroline L Relton. 2017. “Role of DNA Methylation in Type 2 Diabetes Etiology: Using Genotype as a Causal Anchor.” Diabetes 66 (6): 1713–22.
Juvinao-Quintero, Diana L, Marie-France Hivert, Gemma C Sharp, Caroline L Relton, and Hannah R Elliott. 2019. “DNA Methylation and Type 2 Diabetes: The Use of Mendelian Randomization to Assess Causality.” Current Genetic Medicine Reports 7: 191–207.
Juvinao-Quintero, Diana L, Gemma C Sharp, Eleanor CM Sanderson, Caroline L Relton, and Hannah R Elliott. 2023. “Investigating Causality in the Association Between DNA Methylation and Type 2 Diabetes Using Bidirectional Two-Sample Mendelian Randomisation.” Diabetologia 66 (7): 1247–59.
Kim, Hakyung, Jae Hyun Bae, Kyong Soo Park, Joohon Sung, and Soo Heon Kwak. 2021. “DNA Methylation Changes Associated with Type 2 Diabetes and Diabetic Kidney Disease in an East Asian Population.” The Journal of Clinical Endocrinology & Metabolism 106 (10): e3837–51.
Yan, Yu, Hongbo Liu, Amin Abedini, Xin Sheng, Matthew Palmer, Hongzhe Li, and Katalin Susztak. 2024. “Unraveling the Epigenetic Code: Human Kidney DNA Methylation and Chromatin Dynamics in Renal Disease Development.” Nature Communications 15 (1): 1–17.