Human cerebral neuropathology of Type 2 diabetes mellitus

Nelson, Peter T.; Smith, Charles D.; Abner, Erin L.; Schmitt, Frederick A.; Scheff, Stephen W.; Davis, Gregory J.; Keller, Jeffrey N.; Jicha, Gregory A.; Davis, Daron G.; Wang, Wang‐Xia; Hartman, Adria; Katz, Douglas; Markesbery, William R.

doi:10.1016/j.bbadis.2008.08.005

Cited by 164 publications

(178 citation statements)

References 214 publications

(188 reference statements)

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“…Meanwhile, the decreases in both gE and lE, reflecting remote connection and neighbor connection respectively, implied disrupted topological organizations of the WMNs in patients with diabetes. These abnormal phenomena maybe attributed to reduced WM integrity and increased disconnection; some microvascular lesions and enlarged perivascular spaces would induce possible neuropathology changes in T2DM [30]. Previous studies provide direct evidence for disrupted structural integrity in various WM tracts in diabetic patients, such as the corpus callosum [7,31].…”

Section: Discussionmentioning

confidence: 97%

Disrupted White Matter Network and Cognitive Decline in Type 2 Diabetes Patients

Zhang

Liu

et al. 2016

JAD

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Abstract. Type 2 diabetes mellitus is accompanied by cognitive impairment and is associated with an increased risk of dementia. Damage to brain structures such as white matter network disruption may underlie this cognitive disturbance. In the present study, 886 non-diabetic and 163 type 2 diabetic participants completed a battery of neuropsychological tests. Among them, 38 diabetic patients and 34 non-diabetic participants that matched the patients for age/sex/education received a magnetic resonance imaging-based diffusion tensor imaging. Then we calculated the topological properties of the white matter network using a graph theoretical method to investigate network efficiency differences between groups. We found that type 2 diabetic patients had inferior performances compared to the non-diabetic controls, in several cognitive domains involving executive function, spatial processing, memory, and attention. We also found that diabetic patients exhibited a disrupted topological organization of the white matter network (including the global network properties, i.e., network strength, global efficiency, local efficiency and shortest path length, and the nodal efficiency of the right rolandic operculum) in the brain. Moreover, those global network properties and the nodal efficiency of the right rolandic operculum both had positive correlations with executive function in the patient group. The results suggest that type 2 diabetes mellitus leads to an alteration in the topological organization of the cortical white matter network and this alteration may account for the observed cognitive decline.

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Section: Discussionmentioning

confidence: 97%

Disrupted White Matter Network and Cognitive Decline in Type 2 Diabetes Patients

Zhang

Liu

et al. 2016

JAD

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“…When it comes to diabetes, an increasing number of autopsy studies on possible pathological dementia correlates is becoming available. Thus far the picture that emerges from these studies is that diabetes is not associated with AD-type pathology, whereas vascular pathology in the brain is more common [49][50][51][52].…”

Section: T2dm and Dementiamentioning

confidence: 99%

Caffeine, Diabetes, Cognition, and Dementia

Biessels

2010

JAD

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Abstract. People with diabetes mellitus are at increased risk of cognitive dysfunction. This review explores the relation between caffeine intake, diabetes, cognition and dementia, focusing on type 2 diabetes (T2DM). Epidemiological studies on caffeine/coffee intake and T2DM risk are reviewed. Next, the impact of T2DM on cognition is addressed. Finally, the potential for caffeine to modulate the risk of cognitive decline in the context of diabetes is explored. The conclusion is that, although epidemiological studies indicate that coffee/caffeine consumption is associated with a decreased risk of T2DM and possibly also with a decreased dementia risk, we can at present not be certain that these associations are causal. For now, recommendations for coffee consumption in individuals with T2DM or pre-diabetic stages are therefore difficult to establish, but it should be acknowledged that caffeine does appear to have several properties that warrant further investigations in this field.

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“…Possible mechanisms include inflammation, microvascular lesions, enlarged perivascular spaces, and blood-brain barrier disruption (43). In summary, DTI has low specificity but high sensitivity to white matter pathology.…”

Section: Type 2 Diabetesmentioning

confidence: 99%

Brain Changes Underlying Cognitive Dysfunction in Diabetes: What Can We Learn From MRI?

2014

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Diabetes is associated with cognitive dysfunction and an increased risk of dementia. This article addresses findings with brain MRI that may underlie cognitive dysfunction in diabetes. Studies in adults with type 1 diabetes show regional reductions in brain volume. In those with a diabetes onset in childhood, these volume reductions are likely to reflect the sum of changes that occur during brain development and changes that occur later in life due to exposure to diabetes-related factors. Type 2 diabetes is associated with global brain atrophy and an increased burden of small-vessel disease. These brain changes occur in the context of aging and often also in relation to an adverse vascular risk factor profile. Advanced imaging techniques detect microstructural lesions in the cerebral gray and white matter of patients with diabetes that affect structural and functional connectivity. Challenges are to further unravel the etiology of these cerebral complications by integrating findings from different imaging modalities and detailed clinical phenotyping and by linking structural MRI abnormalities to histology. A better understanding of the underlying mechanisms is necessary to establish interventions that will improve long-term cognitive outcomes for patients with type 1 and type 2 diabetes.Interest in the effect of diabetes on the brain is growing. It is now clear that type 1 diabetes is associated with modest decrements in cognitive functioning, which are most marked in patients with an early childhood diabetes onset (1). These decrements in adults with type 1 diabetes are most evident in the domains of general intelligence, psychomotor speed, and mental flexibility (2). On these domains, the magnitude of the decrements is ;0.3 to 0.7 SD units relative to people without diabetes (2). This implies that, on average, the performance of people with diabetes on these domains is at the 30th to the 40th percentile of control values. The progression of cognitive decrements in adults with type 1 diabetes, relative to people without diabetes, is generally slow, except in subgroups of patients with marked microvascular complications, who may show more marked decline (1).Modest decrements in cognitive functioning, evident on the domains of verbal and visual memory, information processing speed, and executive functioning, have also been noted in people with type 2 diabetes across all age groups (3). Similar to type 1 diabetes, effect sizes are small to moderate (0.3 to 0.4 SD units) (4) and follow a slow progression over time, only modestly exceeding the rate of normal aging-related cognitive decline (3). In older people, however, particularly older than the age of 65, type 2 diabetes is also associated with more severe forms of cognitive impairment. Data from large epidemiological surveys link diabetes to an increased dementia risk. A meta-analysis estimated that people with type 2 diabetes have a relative risk of vascular dementia of 2.5 (95% CI 2.1-3.0) and that of Alzheimer disease is 1.5 (95% CI 1.2-1.8) relative to indiv...

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Human cerebral neuropathology of Type 2 diabetes mellitus

Cited by 164 publications

References 214 publications

Disrupted White Matter Network and Cognitive Decline in Type 2 Diabetes Patients

Disrupted White Matter Network and Cognitive Decline in Type 2 Diabetes Patients

Caffeine, Diabetes, Cognition, and Dementia

Brain Changes Underlying Cognitive Dysfunction in Diabetes: What Can We Learn From MRI?

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