Analysis of the relationships between type 2 diabetes status, glycemic control, and neuroimaging measures in the Diabetes Heart Study Mind

Abstract

Aims To examine the relationships between type 2 diabetes (T2D) status, glycemic control, and T2D duration with magnetic resonance imaging (MRI)-derived neuroimaging measures in European Americans from the Diabetes Heart Study (DHS) Mind cohort. Methods Relationships were examined using marginal models with generalized estimating equations in 784 participants from 514 DHS Mind families. Fasting plasma glucose, glycated hemoglobin, and diabetes duration were analyzed in 682 participants with T2D. Models were adjusted for potential confounders, including age, sex, history of cardiovascular disease, smoking, educational attainment, and use of statins or blood pressure medications. Association was tested with gray and white matter volume, white matter lesion volume, gray matter cerebral blood flow, and white and gray matter fractional anisotropy and mean diffusivity. Results Adjusting for multiple comparisons, T2D status was associated with reduced white matter volume (p=2.48 × 10−6) and reduced gray and white matter fractional anisotropy (p≤0.001) in fully adjusted models, with a trend towards increased white matter lesion volume (p=0.008) and increased gray and white matter mean diffusivity (p≤0.031). Among T2D affected participants, neither fasting glucose, glycated hemoglobin, nor diabetes duration were associated with the neuroimaging measures assessed (p>0.05). Conclusions While T2D was significantly associated with MRI-derived neuroimaging measures, differences in glycemic control in T2D affected individuals in the DHS Mind study do not appear to significantly contribute to variation in these measures. This supports the idea that presence or absence of T2D, not fine gradations of glycemic control, may be more significantly associated with age-related changes in the brain.

The Mechanisms of Type 2 Diabetes-Related White Matter Intensities: A Review

“…Currently, age and hypertension are considered to be consistent risk factors for WMHs. Studies have shown that diabetic subjects are more prone to having more and larger WMHs than non-diabetic subjects (2)(3)(4)(5). A recent review by Del Bene et al more firmly emphasized the relationship between type 2 diabetes and both the presence and severity of WMHs, although the underlying mechanism is still not fully understood (6).…”

Postprandial Hyperglycemia Is Associated With White Matter Hyperintensity and Brain Atrophy in Older Patients With Type 2 Diabetes Mellitus

“…Several studies have obtained conflicting results regarding the associations between glucose indices and WMH. One study found that higher HbA1c levels were associated with WMH ( Schneider et al, 2017 ), while other studies did not find such an association ( Exalto et al, 2014 ; Raffield et al, 2016 ). These controversies may result from a failure to capture daily glucose variability.…”

“…Accumulating evidence indicates that diabetes is associated with global and regional brain atrophy ( Falvey et al, 2013 ; Moran et al, 2013 ; Hirabayashi et al, 2016 ; Raffield et al, 2016 ; Schneider et al, 2017 ). The results of our study extend current observations and clearly demonstrate that postprandial hyperglycemia is independently associated with global brain atrophy.…”

“…Several studies have reported that WMH volume is increased in patients with diabetes compared with non-diabetic subjects ( Novak et al, 2006 ; Raffield et al, 2016 ); however, other studies did not observe this finding ( Falvey et al, 2013 ; Moran et al, 2013 ). Some studies have focused on the association between HbA1c or fasting plasma glucose levels and WMH; however, the results of these studies were inconsistent ( Bryan et al, 2014 ; Exalto et al, 2014 ; Geijselaers et al, 2015 ; Raffield et al, 2016 ; Schneider et al, 2017 ). More recently, an association between fluctuations in HbA1c levels and WMH was reported in diabetes patients who carry the apolipoprotein E4 allele ( Livny et al, 2016 ), which is a strong genetic risk factor for AD.…”

Quantifying the Impact of Type 2 Diabetes on Brain Perfusion Using Deep Neural Networks

“…Initial studies on T2D patients have found that diabetes [3,11] and renal [9,14] disease measures are associated with volumes of certain neuroanatomical structures, however the relationship between diabetes and the perfusion of the brain parenchyma has remained largely unknown. Additionally, according to the U.S. Center for Disease Control, African American adults are about twice as likely to be diagnosed with diabetes as European Americans [2].…”