Risk Factors for Retinopathy in Type 1 Diabetes: The DCCT/EDIC Study

Hainsworth, Dean P.; Bebu, Ionut; Aiello, Lloyd Paul; Sivitz, William I.; Gubitosi-Klug, Rose; Malone, John I.; White, Neil H.; Danis, Ronald P.; Wallia, Amisha; Gao, Xiaoyu; Barkmeier, Andrew J.; Das, Arup; Patel, Shriji; Gardner, Thomas W.; Lachin, John M.

doi:10.2337/dc18-2308

Cited by 134 publications

(94 citation statements)

References 22 publications

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“…DCCT-EDIC studies have shown that institution of early intensive therapy lowers the incidence of further progression of retinopathy, and even 30 years after the start of DCCT, former intensive therapy participants still report better Visual Function than the former conventional group 33 . Animal models have also demonstrated that institution of good glycemic control, soon after establishment of diabetes, prevents impairments in mitochondrial biogenesis, and the development of retinopathy 15,17 .…”

Section: Discussionmentioning

confidence: 98%

Epigenetics and Mitochondrial Stability in the Metabolic Memory Phenomenon Associated with Continued Progression of Diabetic Retinopathy

Kowluru

Mohammad

2020

Sci Rep

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Retinopathy continues to progress even when diabetic patients try to control their blood sugar, but the molecular mechanism of this 'metabolic memory' phenomenon remains elusive. Retinal mitochondria remain damaged and vicious cycle of free radicals continues to self-propagate. DnA methylation suppresses gene expression, and diabetes activates DnA methylation machinery. our aim was to investigate the role of DnA methylation in continued compromised mitochondrial dynamics and genomic stability in diabetic retinopathy. Using retinal endothelial cells, incubated in 20 mM glucose for four days, followed by 5 mM glucose for four days, and retinal microvessels from streptozotocininduced diabetic rats in poor glycemia for four months, followed by normal glycemia for four additional months, DnA methylation of mitochondrial fusion and mismatch repair proteins, Mfn2 and Mlh1 respectively, was determined. Retinopathy was detected in trypsin-digested microvasculature. Reinstitution of good glycemia had no beneficial effect on hypermethylation of Mfn2 and Mlh1 and retinal function (electroretinogram), and the retinopathy continued to progress. However, intervention of good glycemia directly with DNA methylation inhibitors (Azacytidine or Dnmt1-siRNA), prevented Mfn2 and Mlh1 hypermethylation, and ameliorated retinal dysfunction and diabetic retinopathy. thus, direct regulation of DnA methylation can prevent/reverse diabetic retinopathy by maintaining mitochondrial dynamics and DnA stability, and prevent retinal functional damage. Diabetic retinopathy is the fifth most common cause of preventable blindness, and hyperglycemia and the duration of diabetes are clinically important risk factors for its development and progression. Pivotal Diabetes Control and Complications Trial (DCCT), and the follow-up Epidemiology of Diabetes Interventions and Complications (EDIC), studies have shown that the clinical features of retinopathy continue to develop long after intensive glucose control is maintained in patients treated with the standard treatment regimen during the DCCT. These studies have further demonstrated that intensive control in the early stages of diabetes is critical as its benefits persist beyond the period of its institution, suggesting a 'metabolic memory' phenomenon 1,2. Both in vitro and in vivo experimental models of diabetic retinopathy also have duplicated this memory phenomenon; retinal histopathology initiated during prior poor glycemic control in dogs and rats does not benefit from the good glycemic control which follows it 3,4. However, the molecular mechanism of the metabolic memory phenomenon still remains elusive. Mitochondrial integrity is critical for cell survival, and in diabetes, damaged mitochondria leak cytochrome C, accelerating retinal capillary cell apoptosis, a phenomenon which precedes the formation of acellular capillaries and pericyte ghosts 5-7. Mitochondria are also highly dynamic, and undergo continuous fusion and fission 8,9. Fission helps remove damaged mitochondria, and fusion unites two m...

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Section: Discussionmentioning

confidence: 98%

Epigenetics and Mitochondrial Stability in the Metabolic Memory Phenomenon Associated with Continued Progression of Diabetic Retinopathy

Kowluru

Mohammad

2020

Sci Rep

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“…The regressions’ R 2 values were used to describe the proportion of the variance of a body composition measure that is explained by an anthropometric measure. The relevance ranking of each variable was based on the z statistics allowing comparisons across risk factors independently of their measurement units 38 . WHR and WHtR were scaled by a factor of 10.…”

Section: Methodsmentioning

confidence: 99%

Waist-height ratio and waist are the best estimators of visceral fat in type 1 diabetes

Parente

Mutter

Harjutsalo

et al. 2020

Sci Rep

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Visceral fat is associated with cardiovascular and kidney disease. However, the relationship between body composition and anthropometric measures in type 1 diabetes is unknown. Using z-statistics, we ranked the ability of body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), waist-height ratio (WHtR) and a body shape index (ABSI) to capture measures of body composition from 603 Dual-energy-X-Ray-Absorptiometry scans of adults with type 1 diabetes. Albuminuria was defined as urinary albumin excretion rate of at least 30 mg/24 h. Women with albuminuria had higher visceral fat mass % (VFM%) (0.9 vs. 0.5%, p = 0.0017) and lower appendicular lean mass % (AppLM%) (25.4 vs 26.4%, p = 0.03) than those without. Men with albuminuria had higher VFM% (1.5 vs. 1.0%, p = 0.0013) and lower AppLM% (30.0 vs 32.3, p < 0.0001) than those without. In men, WHtR estimated VFM% best (z-statistics = 21.1), followed by WC (z = 19.6), BMI (z = 15.1), WHR (z = 14.6) and ABSI (z = 10.1). In women, the ranking was WC (z = 28.9), WHtR (z = 27.3), BMI (z = 20.5), WHR (z = 12.7) and ABSI (z = 10.5). Overall, the ranking was independent of albuminuria. Adults with type 1 diabetes and albuminuria have greater VFM% and lower AppLM% than those without. WHtR and WC best estimate the VFM% in this population, independently of albuminuria and sex.

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“…Here, we investigated DNAm age calculated by all four methods in 499 subjects with T1D from the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study and its association with diabetic complications (CVD, nephropathy, retinopathy, and neuropathy) and their risk factors [14][15][16]. We also examined DNAm age in a smaller subset at two time points, 16-17 years apart, to investigate changes in DNAm age over time.…”

Section: Introductionmentioning

confidence: 99%

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

Roshandel¹,

Chen²,

Canty³

et al. 2020

Clin Epigenet

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Background: 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. Results: 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. Conclusions: 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.

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Risk Factors for Retinopathy in Type 1 Diabetes: The DCCT/EDIC Study

Cited by 134 publications

References 22 publications

Epigenetics and Mitochondrial Stability in the Metabolic Memory Phenomenon Associated with Continued Progression of Diabetic Retinopathy

Epigenetics and Mitochondrial Stability in the Metabolic Memory Phenomenon Associated with Continued Progression of Diabetic Retinopathy

Waist-height ratio and waist are the best estimators of visceral fat in type 1 diabetes

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

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