Subclinical Atherosclerosis Is Inversely Associated With Gray Matter Volume in African Americans With Type 2 Diabetes

The Contribution of Kidney Disease to Cognitive Impairment in Patients with Type 2 Diabetes

PURPOSE OF REVIEW

This review focuses on the relationships between diabetes, cognitive impairment, and the contribution of kidney disease.

RECENT FINDINGS

We review the independent contributions of parameters of kidney disease, including albuminuria, glomerular filtration, bone/mineral metabolism, and vitamin D synthesis, on cognitive performance in patients with diabetes. Potential pathophysiologic mechanisms underlying these associations are discussed highlighting gaps in existing knowledge. Finally, effects of the dialysis procedure on the brain and cognitive performance are considered. Emphasis is placed on novel non-invasive screening tools with the potential to preserve cerebral perfusion during hemodialysis and limit cognitive decline in patients with diabetic ESKD. Patients with type 2 diabetes and advanced chronic kidney disease suffer a higher prevalence of cognitive impairment. This is particularly true in patients with diabetes and end-stage kidney disease (ESKD).

Altered brain volume and its relationship to characteristics of carotid plaques in asymptomatic patients

Carotid plaque is an aggregate marker of exposure to vascular risk factors, which are linked to structural brain changes. We investigated prestroke global and regional changes in brain volume in a carotid plaque population of cognitively healthy individuals and the association between carotid plaque characteristics and these changes.A total of 76 participants were divided into healthy control (HC, n = 28), vulnerable plaque (n = 27) and stable plaque groups (n = 21). All subjects underwent carotid ultrasound and brain magnetic resonance imaging (MRI). Voxel-based morphometry (VBM) was used to examine differences in regional gray matter volumes (rGMVs) among the different groups.The plaque group had a significantly lower mean total cerebral brain volume (TCBV) than the HC group (P = .03). Carotid intima-media thickness (CIMT) was negatively correlated with TCBV (r = -0.311, P = .006) and rGMV in the right thalamus (r = -0.589, P = .001). The rGMVs of the right middle occipital gyrus and bilateral lingual gyrus were significantly different between the unstable and stable groups. The gray-scale median (GSM) of the plaque and the total plaque risk score (TPRS) were correlated with the volume of the right middle occipital gyrus (r=-0.478, P = .001; r = 0.541, P = .001) and bilateral lingual gyrus (r = -0.419, P = .003; r = 0.288, P = .04).Carotid plaque is related to the volume of the brain parenchyma and right thalamus. The rGMVs of the right middle occipital gyrus and bilateral lingual gyrus differed between the vulnerable plaque and stable plaque groups, and the characteristics of carotid plaques may serve as indexes that reflect these changes.

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

The effect of Type 2 Diabetes (T2D) on brain health is poorly understood. This study aims to quantify the association between T2D and perfusion in the brain. T2D is a very common metabolic disorder that can cause long term damage to the renal and cardiovascular systems. Previous research has discovered the shape, volume and white matter microstructures in the brain to be significantly impacted by T2D. We propose a fully-connected deep neural network to classify the regional Cerebral Blood Flow into low or high levels, given 16 clinical measures as predictors. The clinical measures include diabetes, renal, cardiovascular and demographics measures. Our model enables us to discover any nonlinear association which might exist between the input features and target. Moreover, our end-to-end architecture automatically learns the most relevant features and combines them without the need for applying a feature selection method. We achieved promising classification performance. Furthermore, in comparison with six (6) classical machine learning algorithms and six (6) alternative deep neural networks similarly tuned for the task, our proposed model outperformed all of them.

Prefrontal-Parietal White Matter Volumes in Healthy Elderlies Are Decreased in Proportion to the Degree of Cardiovascular Risk and Related to Inhibitory Control Deficits

Cardiovascular risk (CVR) factors may be associated with poor cognitive functioning in elderlies and impairments in brain structure. Using MRI and voxel-based morphometry (VBM), we assessed regional white matter (WM) volumes in a population-based sample of individuals aged 65–75 years (n = 156), subdivided in three CVR subgroups using the Framingham Risk Score. Cognition was assessed using the Short Cognitive Performance Test. In high-risk subjects, we detected significantly reduced WM volume in the right juxtacortical dorsolateral prefrontal region compared to both low and intermediate CVR subgroups. Findings remained significant after accounting for the presence of the APOEε4 allele. Inhibitory control performance was negatively related to right prefrontal WM volume, proportionally to the degree of CVR. Significantly reduced deep parietal WM was also detected bilaterally in the high CVR subgroup. This is the first large study documenting the topography of CVR-related WM brain volume deficits. The significant association regarding poor response inhibition indicates that prefrontal WM deficits related to CVR are clinically meaningful, since inhibitory control is known to rely on prefrontal integrity.

Adiposity is inversely associated with hippocampal volume in African Americans and European Americans with diabetes

AIMS

To assess associations between body mass index (BMI), waist circumference (WC), and computed tomography-determined volumes of pericardial, visceral, and subcutaneous adipose tissue with magnetic resonance imaging-(MRI) based cerebral structure and cognitive performance in individuals with type 2 diabetes (T2D).

METHODS

This study was performed in 348 African Americans (AAs) and 256 European Americans (EAs) with T2D. Associations between adiposity measures with cerebral volumes of white matter (WMV), gray matter (GMV), white matter lesions, hippocampal GMV, and hippocampal WMV, cognitive performance and depression were examined using marginal models incorporating generalized estimating equations. All models were adjusted for age, sex, education, smoking, HbA1c, hypertension, statins, cardiovascular disease, MRI scanner (MRI outcomes only), and time between scans; some neuroimaging measures were additionally adjusted for intracranial volume.

RESULTS

Participants were 59.9% female with mean (SD) age 57.7(9.3)years, diabetes duration 9.6(6.8)years, and HbA1c 7.8(1.9)%. In AAs, inverse associations were detected between hippocampal GMV and both BMI (β [95% CI]-0.18 [-0.30, -0.07], P=0.0018) and WC (-0.23 [-0.35, -0.12], P=0.0001). In the full bi-ethnic sample, inverse associations were detected between hippocampal WMV and WC (P≤0.0001). Positive relationships were observed between BMI (P=0.0007) and WC (P<0.0001) with depression in EAs.

CONCLUSIONS

In patients with T2D, adiposity is inversely associated with hippocampal gray and white matter volumes.

APOL1 renal-risk variants associate with reduced cerebral white matter lesion volume and increased gray matter volume

To assess apolipoprotein L1 gene (APOL1) renal-risk-variant effects on the brain, magnetic resonance imaging (MRI)-based cerebral volumes and cognitive function were assessed in 517 African American-Diabetes Heart Study (AA-DHS) Memory IN Diabetes (MIND) and 2568 hypertensive African American Systolic Blood Pressure Intervention Trial (SPRINT) participants without diabetes. Within these cohorts, 483 and 197 had cerebral MRI, respectively. AA-DHS participants were characterized as follows: 60.9% female, mean age of 58.6 years, diabetes duration 13.1 years, estimated glomerular filtration rate of 88.2 ml/min/1.73 m(2), and a median spot urine albumin to creatinine ratio of 10.0 mg/g. In additive genetic models adjusting for age, sex, ancestry, scanner, intracranial volume, body mass index, hemoglobin A1c, statins, nephropathy, smoking, hypertension, and cardiovascular disease, APOL1 renal-risk-variants were positively associated with gray matter volume (β = 3.4 × 10(-3)) and negatively associated with white matter lesion volume (β = -0.303) (an indicator of cerebral small vessel disease) and cerebrospinal fluid volume (β= -30707) (all significant), but not with white matter volume or cognitive function. Significant associations corresponding to adjusted effect sizes (β/SE) were observed with gray matter volume (0.16) and white matter lesion volume (-0.208), but not with cerebrospinal fluid volume (-0.251). Meta-analysis results with SPRINT Memory and Cognition in Decreased Hypertension (MIND) participants who had cerebral MRI were confirmatory. Thus, APOL1 renal-risk-variants are associated with larger gray matter volume and lower white matter lesion volume suggesting lower intracranial small vessel disease.