Aims/hypothesis. Mild cognitive dysfunction is not uncommon in adults with Type 1 diabetes, but its pathogenesis remains unclear. Previous cross-sectional studies had suggested that microangiopathy might affect brain integrity and lead to 'central neuropathy.' To assess the relationship between changes in cognitive performance and the incidence of new micro-and macrovascular complications, 103 young and middle-aged adults (mean age: 40 yrs) with childhood-onset Type 1 diabetes were followed over a 7-year period, and were compared to 57 demographically-similar adults without diabetes. Methods. All subjects completed a comprehensive battery of neurocognitive tests on two occasions. Diabetic subjects also received repeated medical assessments to diagnose the onset of clinically significant complications.Results. Relative to control subjects, diabetic adults showed significant declines on measures of psychomotor efficiency; no between-group differences were evident on learning, memory, or problem-solving tasks. The development of proliferative retinopathy and autonomic neuropathy during the follow-up period predicted decline in psychomotor speed (p<0.01), as did incident macrovascular complications (p<0.05), systolic blood pressure at follow-up (p<0.01), and duration of diabetes (p<0.01). Conclusion/interpretation. This study shows that cognitive efficiency may decline over time in diabetic adults, and that this neurocognitive change may be linked, at least in part, to the occurrence of complications like proliferative retinopathy and elevated blood pressure. Therapeutic interventions that reduce the risk of vascular complications may have a similarly beneficial effect on the brain and reduce the risk of neurocognitive dysfunction in diabetic patients. [Diabetologia (2003)

Review of the literature on the cognitive correlates and consequences of Type 2 diabetes reveals two very intriguing findings. Not only are verbal learning and memory skills most likely to be disrupted as compared to other cognitive skills (e.g. attention, executive function; psychomotor efficiency), but these mnestic deficits appear to be restricted to individuals with diabetes who are older than 60-65 years of age. Middle-aged adults with either Type 2 or Type 1 diabetes are apparently protected insofar as researchers have only infrequently reported learning and memory impairments in that age group. Why do older adults have such an increased risk of diabetes-associated memory dysfunction? In our view, this phenomenon is a consequence of a synergistic interaction between diabetes-related metabolic derangements and the structural and functional changes occurring in the central nervous system (CNS) that are part of the normal ageing process. To critically evaluate that possibility, we summarise what is known about learning and memory dysfunction in the adult with diabetes, examine the extent to which chronic hyperglycaemia may adversely affect the integrity of the CNS, and selectively review the literature on age-associated changes in brain morphology and cognitive function, paying special attention to the threshold theory of cognitive impairment.

OBJECTIVE -To examine the extent to which type 2 diabetes is associated with poorer performance on measures of learning, memory, psychomotor speed, and problem-solving in middle-aged adults. RESEARCH DESIGN AND METHODS-This cross-sectional study evaluated 50 adults (age range 34-65 years, mean 50.8) with type 2 diabetes and 50 demographically similar community control subjects without diabetes. Each subject received a thorough physical examination and a detailed neuropsychological assessment. Factor analysis was used to assign specific tests to 1 of 4 cognitive domains (learning, memory for stories, problem-solving, and psychomotor speed). Hierarchical regression analysis was used to identify demographic and biomedical variables associated with cognitive dysfunction.RESULTS -Learning, memory, and problem-solving skills were unaffected by type 2 diabetes. In contrast, psychomotor slowing was predicted by a diagnosis of diabetes (r 2 change = 0.075, P Ͻ 0.002) with additional variance in psychomotor efficiency explained independently by HbA 1 (r 2 = 0.064, P Ͻ 0.003) and vibratory threshold (r 2 = 0.112, P Ͻ 0.0001). The magnitude of psychomotor slowing on specific tests ranged from 12% (Digit Vigilance) to 23% (Grooved Pegboard).CONCLUSIONS -Middle-aged adults with type 2 diabetes manifest psychomotor slowing that is associated with poorer metabolic control, whereas learning, memory, and problemsolving skills appear to be largely intact. The development of psychomotor slowing may be a manifestation of a "central neuropathy" induced by chronic hyperglycemia.

Objective: To examine the persistence of the original treatment effects 10 years after the Diabetes Control and Complications Trial (DCCT) in the follow-up Epidemiology of Diabetes Interventions and Complications (EDIC) study. In the DCCT, intensive therapy aimed at nearnormal glycemia reduced the risk of microvascular complications of type 1 diabetes mellitus compared with conventional therapy.Methods: Retinopathy was evaluated by fundus photography in 1211 subjects at EDIC year 10. Further 3-step progression on the Early Treatment Diabetic Retinopathy Study scale from DCCT closeout was the primary outcome.Results: After 10 years of EDIC follow-up, there was no significant difference in mean glycated hemoglobin levels (8.07% vs 7.98%) between the original treatment groups. Nevertheless, compared with the former conven-tional treatment group, the former intensive group had significantly lower incidences from DCCT close of further retinopathy progression and proliferative retinopathy or worse (hazard reductions, 53%-56%; PϽ.001). The risk (hazard) reductions at 10 years of EDIC were attenuated compared with the 70% to 71% over the first 4 years of EDIC (PϽ.001). The persistent beneficial effects of former intensive therapy were largely explained by the difference in glycated hemoglobin levels during DCCT. Conclusion:The persistent difference in diabetic retinopathy between former intensive and conventional therapy ("metabolic memory") continues for at least 10 years but may be waning.

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.