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

Hyperglycemia is associated with poorer cognitive performance in a cohort of middle-aged people in Qatar: a cross-sectional study

BACKGROUND

Diabetes mellitus (DM) prevalence in Qatar is among the highest worldwide. DM has been shown to be associated with reduced performance on numerous domains of cognitive function in elderly population. Here, we sought to determine whether such association also exists in a middle-aged cohort.

RESEARCH DESIGN AND METHODS

A cross-sectional study was conducted using data from 981 participants aged 40-65 years from the Qatar Biobank. We analyzed glycemic indices: HbA1c, serum glucose, insulin levels, waist circumference, and waist-hip ratio. Cognitive function was assessed using two domains of CANTAB: the paired episodic memory (visual memory) and reaction time (motor and mental speed).

RESULTS

We found significant associations between DM and cognitive impairment. Poor reaction speed was linked to DM (beta 36.80, P < 0.01), higher HbA1c levels (beta 10.73, P < 0.05), larger waist circumference (beta 1.70, P < 0.001), and higher waist-to-hip ratio (beta 252.56, P ≤ 0.01). Poor memory performance was also associated with increased waist circumference and waist-to-hip ratio.

CONCLUSION

The negative association between DM, its biomarkers, and cognitive impairment reported previously in elderly populations also exists in middle-aged individuals. Further research is needed to explore the causality and impact of dysglycemia on other cognitive domains.

Food Functional Factors in Alzheimer's Disease Intervention: Current Research Progress

Alzheimer's disease (AD) is a complex multifactorial neurodegenerative disease. With the escalating aging of the global population, the societal burden of this disease is increasing. Although drugs are available for the treatment of AD, their efficacy is limited and there remains no effective cure. Therefore, the identification of safe and effective prevention and treatment strategies is urgently needed. Functional factors in foods encompass a variety of natural and safe bioactive substances that show potential in the prevention and treatment of AD. However, current research focused on the use of these functional factors for the prevention and treatment of AD is in its initial stages, and a complete theoretical and application system remains to be determined. An increasing number of recent studies have found that functional factors such as polyphenols, polysaccharides, unsaturated fatty acids, melatonin, and caffeine have positive effects in delaying the progression of AD and improving cognitive function. For example, polyphenols exhibit antioxidant, anti-inflammatory, and neuroprotective effects, and polysaccharides promote neuronal growth and inhibit inflammation and oxidative stress. Additionally, unsaturated fatty acids inhibit Aβ production and Tau protein phosphorylation and reduce neuroinflammation, and melatonin has been shown to protect nerve cells and improve cognitive function by regulating mitochondrial homeostasis and autophagy. Caffeine has also been shown to inhibit inflammation and reduce neuronal damage. Future research should further explore the mechanisms of action of these functional factors and develop relevant functional foods or nutritional supplements to provide new strategies and support for the prevention and treatment of AD.

The "vegetables first" dietary habit correlates with higher-level functional capacity in older adults with diabetes

BACKGROUND

Some studies suggest that the habit of eating vegetables may initially be correlated with maintenance of a higher-level functional capacity; however, such a correlation has not been demonstrated. This study aimed to correlate the habit of eating vegetables first and higher-level functional capacity in older adults with diabetes.

METHODS

Patients aged ≥ 60 years who were treated at Japanese Red Cross Ise Hospital on an ambulatory basis were included in this study. A self-administered questionnaire using the Tokyo Metropolitan Institute of Gerontology Index of Competence (TMIG-IC) was used to evaluate higher-level functional capacity. Participants were instructed to answer the questionnaire regarding the order in which they consumed the mentioned food types, and based on their answers, they were classified into "no order of eating," "carbohydrates first," "protein first," and "vegetables first" groups. Multiple regression analyses with the TMIG-IC score as a dependent variable and the order of eating as explanatory variables were used to determine the partial regression coefficients of the "vegetables first" dietary habit with higher-level functional capacity.

RESULTS

This study included 346 patients. The adjusted partial regression coefficients of the "carbohydrates first," "protein first," and "vegetables first" dietary habits with the TMIG-IC score were 0.27 (95% confidence interval [CI], - 0.29 to 0.84), 0.17 (95% CI, - 0.54 to 0.90), and 0.77 (95% CI, 0.23 to 1.31), respectively.

CONCLUSIONS

The habit of eating vegetables first was correlated with higher-level functional capacity in older adults with diabetes.

Cross-sectional association of continuous glucose monitoring-derived metrics with cerebral small vessel disease in older adults with type 2 diabetes

AIM

To examine cross-sectional associations between continuous glucose monitoring (CGM)-derived metrics and cerebral small vessel disease (SVD) in older adults with type 2 diabetes.

MATERIALS AND METHODS

In total, 80 patients with type 2 diabetes aged ≥70 years were analysed. Participants underwent CGM for 14 days. From the CGM data, we derived mean sensor glucose, percentage glucose coefficient of variation, mean amplitude of glucose excursion, time in range (TIR, 70-180 mg/dl), time above range (TAR) and time below range metrics, glycaemia risk index and high/low blood glucose index. The presence of cerebral SVD, including lacunes, microbleeds, enlarged perivascular spaces and white matter hyperintensities, was assessed, and the total number of these findings comprised the total cerebral SVD score (0-4). Ordinal logistic regression analyses were performed to examine the association of CGM-derived metrics with the total SVD score.

RESULTS

The median SVD score was 1 (interquartile range 0-2). Higher hyperglycaemic metrics, including mean sensor glucose, TAR >180 mg/dl, TAR >250 mg/dl, and high blood glucose index and glycaemia risk index, were associated with a higher total SVD score. In contrast, a higher TIR (per 10% increase) was associated with a lower total SVD score (odds ratio 0.73, 95% confidence interval 0.56-0.95). Glycated haemoglobin, percentage glucose coefficient of variation, mean amplitude of glucose excursions, time below range and low blood glucose index were not associated with total cerebral SVD scores.

CONCLUSIONS

The hyperglycaemia metrics and TIR, derived from CGM, were associated with cerebral SVD in older adults with type 2 diabetes.

The interaction between insulin resistance and Alzheimer's disease: a review article

Insulin serves multiple functions as a growth-promoting hormone in peripheral tissues. It manages glucose metabolism by promoting glucose uptake into cells and curbing the production of glucose in the liver. Beyond this, insulin fosters cell growth, drives differentiation, aids protein synthesis, and deters degradative processes like glycolysis, lipolysis, and proteolysis. Receptors for insulin and insulin-like growth factor-1 are widely expressed in the central nervous system. Their widespread presence in the brain underscores the varied and critical functions of insulin signaling there. Insulin aids in bolstering cognition, promoting neuron extension, adjusting the release and absorption of catecholamines, and controlling the expression and positioning of gamma-aminobutyric acid (GABA). Importantly, insulin can effortlessly traverse the blood-brain barrier. Furthermore, insulin resistance (IR)-induced alterations in insulin signaling might hasten brain aging, impacting its plasticity and potentially leading to neurodegeneration. Two primary pathways are responsible for insulin signal transmission: the phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) pathway, which oversees metabolic responses, and the mitogen-activated protein kinase (MAPK) pathway, which guides cell growth, survival, and gene transcription. This review aimed to explore the potential shared metabolic traits between Alzheimer's disease (AD) and IR disorders. It delves into the relationship between AD and IR disorders, their overlapping genetic markers, and shared metabolic indicators. Additionally, it addresses existing therapeutic interventions targeting these intersecting pathways.

Irreversible atrophy in memory brain regions over 7 years is predicted by glycemic control in type 2 diabetes without mild cognitive impairment

Memory-related impairments in type 2 diabetes may be mediated by insulin resistance and hyperglycemia. Previous cross-sectional studies have controversially suggested a relationship between metabolic control and a decrease in hippocampal volumes, but only longitudinal studies can test this hypothesis directly. We performed a longitudinal morphometric study to provide a direct test of a possible role of higher levels of glycated hemoglobin with long term brain structural integrity in key regions of the memory system - hippocampus, parahippocampal gyrus and fusiform gyrus. Grey matter volume was measured at two different times - baseline and after ~7 years. We found an association between higher initial levels of HbA1C and grey matter volume loss in all three core memory regions, even in the absence of mild cognitive impairment. Importantly, these neural effects persisted in spite of the fact that patients had significantly improved their glycemic control. This suggests that early high levels of HbA1c might be irreversibly associated with subsequent long-term atrophy in the medial temporal cortex and that early intensive management is critical.

Metabolic Profile of Alzheimer's Disease: Is 10-Hydroxy-2-decenoic Acid a Pertinent Metabolic Adjuster?

Alzheimer's disease (AD) represents a significant public health concern in modern society. Metabolic syndrome (MetS), which includes diabetes mellitus (DM) and obesity, represents a modifiable risk factor for AD. MetS and AD are interconnected through various mechanisms, such as mitochondrial dysfunction, oxidative stress, insulin resistance (IR), vascular impairment, inflammation, and endoplasmic reticulum (ER) stress. Therefore, it is necessary to seek a multi-targeted and safer approach to intervention. Thus, 10-hydroxy-2-decenoic acid (10-HDA), a unique hydroxy fatty acid in royal jelly, has shown promising anti-neuroinflammatory, blood-brain barrier (BBB)-preserving, and neurogenesis-promoting properties. In this paper, we provide a summary of the relationship between MetS and AD, together with an introduction to 10-HDA as a potential intervention nutrient. In addition, molecular docking is performed to explore the metabolic tuning properties of 10-HDA with associated macromolecules such as GLP-1R, PPARs, GSK-3, and TREM2. In conclusion, there is a close relationship between AD and MetS, and 10-HDA shows potential as a beneficial nutritional intervention for both AD and MetS.

Metabolic Syndrome as a Risk Factor for Alzheimer's Disease: A Focus on Insulin Resistance

Alzheimer's disease (AD) is the main type of dementia and is a disease with a profound socioeconomic burden due to the lack of effective treatment. In addition to genetics and environmental factors, AD is highly associated with metabolic syndrome, defined as the combination of hypertension, hyperlipidemia, obesity and type 2 diabetes mellitus (T2DM). Among these risk factors, the connection between AD and T2DM has been deeply studied. It has been suggested that the mechanism linking both conditions is insulin resistance. Insulin is an important hormone that regulates not only peripheral energy homeostasis but also brain functions, such as cognition. Insulin desensitization, therefore, could impact normal brain function increasing the risk of developing neurodegenerative disorders in later life. Paradoxically, it has been demonstrated that decreased neuronal insulin signalling can also have a protective role in aging and protein-aggregation-associated diseases, as is the case in AD. This controversy is fed by studies focused on neuronal insulin signalling. However, the role of insulin action on other brain cell types, such as astrocytes, is still unexplored. Therefore, it is worthwhile exploring the involvement of the astrocytic insulin receptor in cognition, as well as in the onset and/or development of AD.

Insulin resistance in Alzheimer's disease: The genetics and metabolomics links

Alzheimer's disease (AD) is a neurodegenerative disease with significant socioeconomic burden worldwide. Although genetics and environmental factors play a role, AD is highly associated with insulin resistance (IR) disorders such as metabolic syndrome (MS), obesity, and type two diabetes mellitus (T2DM). These findings highlight a shared pathogenesis. The use of metabolomics as a downstream systems' biology (omics) approach can help to identify these shared metabolic traits and assist in the early identification of at-risk groups and potentially guide therapy. Targeting the shared AD-IR metabolic trait with lifestyle interventions and pharmacological treatments may offer promising AD therapeutic approach. In this narrative review, we reviewed the literature on the AD-IR pathogenic link, the shared genetics and metabolomics biomarkers between AD and IR disorders, as well as the lifestyle interventions and pharmacological treatments which target this pathogenic link.

Cross-sectional association of metrics derived from continuous glucose monitoring with cognitive performance in older adults with type 2 diabetes

AIM

To examine the association between continuous glucose monitoring (CGM)-derived metrics and cognitive performance in older adults with type 2 diabetes (T2D).

MATERIALS AND METHODS

A total of 100 outpatients with T2D aged 70 years or older were analysed. Participants underwent CGM for 14 days. As CGM-derived metrics, mean sensor glucose (SG), glucose coefficient of variation (CV), time in range (TIR; 70-180 mg/dl), time above range (TAR; > 180 mg/dl) and time below range (TBR; < 70 mg/dl), were calculated. Participants underwent cognitive tests, including the Japanese version of the Montreal Cognitive Assessment (MoCA-J), a delayed word-recall test from the Alzheimer's Disease Assessment Scale-cognitive subscale, a digit symbol substitution test, a letter word fluency test, a trail-making test (TMT) and digit span test (DSP).

RESULTS

In multiple regression analyses adjusted for confounders, a higher mean SG was associated with a lower performance in MoCA-J and TMT part B (TMT-B) (P < .05). A higher TAR was associated with a lower performance in TMT-B and DSP-backward (P < .05). By contrast, a higher TIR was associated with better function in TMT-B and DSP-backward (P < .05). Furthermore, CV and TBR were not associated with any cognitive function.

CONCLUSION

Hyperglycaemia metrics and TIR derived from CGM are associated with cognitive functions, especially with executive function and working memory, in older adults with T2D.

MRI-based machine learning model: A potential modality for predicting cognitive dysfunction in patients with type 2 diabetes mellitus

Background: Type 2 diabetes mellitus (T2DM) is a crucial risk factor for cognitive impairment. Accurate assessment of patients' cognitive function and early intervention is helpful to improve patient's quality of life. At present, neuropsychiatric screening tests is often used to perform this task in clinical practice. However, it may have poor repeatability. Moreover, several studies revealed that machine learning (ML) models can effectively assess cognitive impairment in Alzheimer's disease (AD) patients. We investigated whether we could develop an MRI-based ML model to evaluate the cognitive state of patients with T2DM. Objective: To propose MRI-based ML models and assess their performance to predict cognitive dysfunction in patients with type 2 diabetes mellitus (T2DM). Methods: Fluid Attenuated Inversion Recovery (FLAIR) of magnetic resonance images (MRI) were derived from 122 patients with T2DM. Cognitive function was assessed using the Chinese version of the Montréal Cognitive Assessment Scale-B (MoCA-B). Patients with T2DM were separated into the Dementia (DM) group (n = 40), MCI group (n = 52), and normal cognitive state (N) group (n = 30), according to the MoCA scores. Radiomics features were extracted from MR images with the Radcloud platform. The variance threshold, SelectKBest, and least absolute shrinkage and selection operator (LASSO) were used for the feature selection. Based on the selected features, the ML models were constructed with three classifiers, k-NearestNeighbor (KNN), Support Vector Machine (SVM), and Logistic Regression (LR), and the validation method was used to improve the effectiveness of the model. The area under the receiver operating characteristic curve (ROC) determined the appearance of the classification. The optimal classifier was determined by the principle of maximizing the Youden index. Results: 1,409 features were extracted and reduced to 13 features as the optimal discriminators to build the radiomics model. In the validation set, ROC curves revealed that the LR classifier had the best predictive performance, with an area under the curve (AUC) of 0.831 in DM, 0.883 in MIC, and 0.904 in the N group, compared with the SVM and KNN classifiers. Conclusion: MRI-based ML models have the potential to predict cognitive dysfunction in patients with T2DM. Compared with the SVM and KNN, the LR algorithm showed the best performance.

Relationship between the Responsiveness of Amyloid β Protein to Platelet Activation by TRAP Stimulation and Brain Atrophy in Patients with Diabetes Mellitus

Type 2 DM is a risk factor for dementia, including Alzheimer's disease (AD), and is associated with brain atrophy. Amyloid β protein (Aβ) deposition in the brain parenchyma is implicated in the neurodegeneration that occurs in AD. Platelets, known as abundant storage of Aβ, are recognized to play important roles in the onset and progression of AD. We recently showed that Aβ negatively regulates platelet activation induced by thrombin receptor-activating protein (TRAP) in healthy people. In the present study, we investigated the effects of Aβ on the TRAP-stimulated platelet activation in DM patients, and the relationship between the individual responsiveness to Aβ and quantitative findings of MRI, the volume of white matter hyperintensity (WMH)/intracranial volume (IC) and the volume of parenchyma (PAR)/IC. In some DM patients, Aβ reduced platelet aggregation induced by TRAP, while in others it was unchanged or rather enhanced. The TRAP-induced levels of phosphorylated-Akt and phosphorylated-HSP27, the levels of PDGF-AB and the released phosphorylated-HSP27 correlated with the degree of platelet aggregability. The individual levels of not WMH/IC but PAR/IC was correlated with those of TRAP-stimulated PDGF-AB release. Collectively, our results suggest that the reactivity of TRAP-stimulated platelet activation to Aβ differs in DM patients from healthy people. The anti-suppressive feature of platelet activation to Aβ might be protective for brain atrophy in DM patients.

Medical Certification of Pilots Through the Insulin-Treated Diabetes Mellitus Protocol at the FAA

INTRODUCTION: In 2019, the Federal Aviation Administration (FAA) announced a protocol to evaluate pilots with insulin treated diabetes mellitus (ITDM) for special issuance (SI) medical certification for first-/second-class pilots. The protocol’s aim is improved assessment of ITDM control/hypoglycemia risk and relies on continuous glucose monitoring (CGM) data. This study compares the characteristics of first-/second-class pilots with ITDM and certification outcome.METHODS: Data was collected retrospectively from the FAA Document Imaging Workflow System (DIWS) for pilots considered for a first-/second-class SI under the ITDM program between November 2019 and October 2021. Inclusion criteria required submission of information required for certification decision (SI vs. denial). We extracted data on demographics and CGM parameters including mean glucose, standard deviation, coefficient of variance, time in range (%), time > 250 mg · dl−1 (%), and time < 70–80 mg · dl−1 (%). We compared these parameters between pilots issued an SI vs. denial with Mann-Whitney U-tests and Fisher exact tests using R.RESULTS: Of 200 pilots with ITDM identified, 77 met inclusion criteria. Of those, 55 received SIs and 22 were denied. Pilots issued SI were statistically significantly older (46 vs. 27 yr), had a lower hemoglobin A1c (6.50% vs. 7.10%), lower average glucose (139 mg · dl−1 vs. 156 mg · dl−1), and spent less time with low glucose levels (0.95% vs. 2.0%).DISCUSSION: The FAA program has successfully medically certificated pilots with ITDM for first-/second-class. Pilots granted an ITDM SI reflect significantly better diabetes control, including less potential for hypoglycemia. As this program continues, it will potentially allow previously disqualified pilots to fly safely.Stanwyck LK, DeVoll JR, Pastore J, Gamble Z, Poe A, Gui GV. Medical certification of pilots through the insulin-treated diabetes mellitus protocol at the FAA. Aerosp Med Hum Perform. 2022; 93(8):627–632.

Quantitative analysis of white matter hyperintensity: Comparison of magnetic resonance imaging image analysis software

OBJECTIVE

White matter hyperintensity (WMH), defined as abnormal signals on magnetic resonance imaging (MRI), is an important clinical indicator of aging and dementia. Although MRI image analysis software can automatically detect WMH, the quantitative accuracy of periventricular hyperintensity (PVH) and deep white matter hyperintensity (DWMH) is unknown.

MATERIALS AND METHODS

This study was a sub-analysis of MRI data from an ongoing hospital-based prospective cohort study (the Gimlet study). Between March 2016 and March 2017, we enrolled patients who visited our memory clinic and agreed to undergo medical assessments of cognitive function and fecal examination to study the gut microbiome. Participants with a history of stroke were excluded. WMH was independently quantitatively analyzed using two MRI imaging analysis software modalities: SNIPER and FUSION. Intraclass correlation coefficients and the mean difference in volume were calculated and compared between modalities.

RESULTS

The data of 87 patients (49 women, mean age 74.8 ± 7.9 years) were analyzed. Both total WMH and DWMH volumes obtained using FUSION were greater (p < 0.001), and PVH volume was smaller (p < 0.001) than those obtained using SNIPER. Intraclass correlation coefficients for the lesion measurements of WMH, PVH, and DWMH between the different software were 0.726 (p < 0.001), 0.673 (p < 0.001), and 0.048 (p = 0.231), respectively.

CONCLUSIONS

There were significant differences in the quantitative data of WMH between the two MRI imaging analysis software modalities. Thus, care should be taken for quantitative assessments of WMH.

Altered Structural and Functional MRI Connectivity in Type 2 Diabetes Mellitus Related Cognitive Impairment: A Review

Type 2 diabetes mellitus (T2DM) is associated with cognitive impairment in many domains. There are several pieces of evidence that changes in neuronal neuropathies and metabolism have been observed in T2DM. Structural and functional MRI shows that abnormal connections and synchronization occur in T2DM brain circuits and related networks. Neuroplasticity and energy metabolism appear to be principal effector systems, which may be related to amyloid beta (Aβ) deposition, although there is no unified explanation that includes the complex etiology of T2DM with cognitive impairment. Herein, we assume that cognitive impairment in diabetes may lead to abnormalities in neuroplasticity and energy metabolism in the brain, and those reflected to MRI structural connectivity and functional connectivity, respectively.

Impact of regional white matter hyperintensities on specific gait function in Alzheimer's disease and mild cognitive impairment

BACKGROUND

Gait disturbance and musculoskeletal changes are evident in persons living with Alzheimer's disease (AD). Because complex gait control requires the integration of neural networks, cerebral small vessel disease (SVD), which is highly prevalent in persons with AD, might have an additional impact on gait disturbance. This study investigated whether white matter hyperintensities (WMH) are more predominantly associated with gait disturbance in persons with AD than in individuals with mild cognitive impairment (MCI) and normal cognition (NC) and further identified the regional impact of WMH on specific gait changes.

METHODS

This study included 396 subjects (aged 65 to 86 years, 63.9% female) diagnosed with AD (n = 187), MCI (n = 118), or NC (n = 91). WMH, lacunes, perivascular spaces, and cerebral microbleeds were assessed as markers of SVD. The volume of WMH was quantified in each brain lobe (frontal, temporal, occipital, and parietal) and sublobar regions in the basal ganglia and thalamus. Gait function was assessed using an electronic walkway. We investigated the association between regional WMH and gait disturbance in individuals with AD, MCI, and NC, adjusted for classical and musculoskeletal confounders.

RESULTS

Among markers of SVD, WMH were most associated with gait disturbance. In AD subjects, periventricular WMH in the frontal and parietal lobes were associated with slow gait speed (r_s  = -0.21, P = 0.007 and r_s  = -0.18, P = 0.019, respectively). These lesions were also associated with changes in stride time, double-leg support time, and walking angle (all r_s  > 0.20, P < 0.01). Lesions in the basal ganglia and thalamus were associated with slow gait speed (r_s  = -0.16, P = 0.034 and r_s  = -0.18, P = 0.023, respectively) and greater gait speed variability (r_s  = 0.16, P = 0.034 and r_s  = 0.20, P = 0.010, respectively). MCI subjects showed only associations between sublobar lesions and shorter stride length (r_s  = -0.24, P = 0.016) and increased walking angle (r_s  = 0.32, P = 0.002). NC subjects did not show associations between WMH and gait parameters. MCI and NC subjects were more affected by muscle weakness than WMH for global gait function (r_s  = 0.42, P < 0.001 and r_s  = 0.23, P = 0.046, respectively).

CONCLUSIONS

Persons with AD showed a predominant association between WMH and gait disturbance compared with MCI and NC subjects, and regional WMH had a detrimental effect on specific gait changes.

A review of the mechanisms underlying selected comorbidities in Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder of the central nervous system (CNS) leading to mental deterioration and devastation, and eventually a fatal outcome. AD affects mostly the elderly. AD is frequently accompanied by hypercholesterolemia, hypertension, atherosclerosis, and diabetes mellitus, and these are significant risk factors of AD. Other conditions triggered by the progression of AD include psychosis, sleep disorders, epilepsy, and depression. One important comorbidity is Down’s syndrome, which directly contributes to the severity and rapid progression of AD. The development of new therapeutic strategies for AD includes the repurposing of drugs currently used for the treatment of comorbidities. A better understanding of the influence of comorbidities on the pathogenesis of AD, and the medications used in its treatment, might allow better control of disease progression, and more effective pharmacotherapy.

The association between intraoperative hyperglycemia and cerebrovascular markers

BACKGROUND AND PURPOSE: Hyperglycemia can lead to an increased rate of apoptosis of microglial cells and to damaged neurons. The relation between hyperglycemia and cerebrovascular markers on MRI is unknown. Our aim was to study the association between intraoperative hyperglycemia and cerebrovascular markers. METHODS: In this further analysis of a subgroup investigation of the BIOCOG study, 65 older non-demented patients (median 72 years) were studied who underwent elective surgery of ≥ 60 minutes. Intraoperative blood glucose maximum was determined retrospectively in each patient. In these patients, preoperatively and at 3 months follow-up a MRI scan was performed and white matter hyperintensity (WMH) volume and shape, infarcts, and perfusion parameters were determined. Multivariable logistic regression analyses were performed to determine associations between preoperative cerebrovascular markers and occurrence of intraoperative hyperglycemia. Linear regression analyses were performed to assess the relation between intraoperative hyperglycemia and pre- to postoperative changes in WMH volume. Associations between intraoperative hyperglycemia and postoperative WMH volume at 3 months follow-up were also assessed by linear regression analyses. RESULTS: Eighteen patients showed intraoperative hyperglycemia (glucose maximum ≥ 150 mg/dL). A preoperative more smooth shape of periventricular and confluent WMH was related to the occurrence of intraoperative hyperglycemia [convexity: OR 33.318 (95 % CI (1.002 - 1107.950); p = 0.050]. Other preoperative cerebrovascular markers were not related to the occurrence of intraoperative hyperglycemia. Intraoperative hyperglycemia showed no relation with pre- to postoperative changes in WMH volume nor with postoperative WMH volume at 3 months follow-up. CONCLUSIONS: We found that a preoperative more smooth shape of periventricular and confluent WMH was related to the occurrence of intraoperative hyperglycemia. These findings may suggest that a similar underlying mechanism leads to a certain pattern of vascular brain abnormalities and an increased risk of hyperglycemia.

Elucidating the Relationship Between Diabetes Mellitus and Parkinson's Disease Using 18F-FP-(+)-DTBZ, a Positron-Emission Tomography Probe for Vesicular Monoamine Transporter 2

Diabetes mellitus (DM) and Parkinson’s disease (PD) have been and will continue to be two common chronic diseases globally that are difficult to diagnose during the prodromal phase. Current molecular genetics, cell biological, and epidemiological evidences have shown the correlation between PD and DM. PD shares the same pathogenesis pathways and pathological factors with DM. In addition, β-cell reduction, which can cause hyperglycemia, is a striking feature of DM. Recent studies indicated that hyperglycemia is highly relevant to the pathologic changes in PD. However, further correlation between DM and PD remains to be investigated. Intriguingly, polycystic monoamine transporter 2 (VMAT2), which is co-expressed in dopaminergic neurons and β cells, is responsible for taking up dopamine into the presynaptic vesicles and can specifically bind to the β cells. Furthermore, we have summarized the specific molecular and diagnostic functions of VMAT2 for the two diseases reported in this review. Therefore, VMAT2 can be applied as a target probe for positron emission tomography (PET) imaging to detect β-cell and dopamine level changes, which can contribute to the diagnosis of DM and PD during the prodromal phase. Targeting VMAT2 with the molecular probe ¹⁸F-FP-(+)-DTBZ can be an entry point for the β cell mass (BCM) changes in DM at the molecular level, to clarify the potential relationship between DM and PD. VMAT2 has promising clinical significance in investigating the pathogenesis, early diagnosis, and treatment evaluation of the two diseases.

Brain microstructural abnormalities in type 2 diabetes mellitus: A systematic review of diffusion tensor imaging studies

Type 2 diabetes mellitus (T2DM) is associated with deficits in the structure and function of the brain. Diffusion tensor imaging (DTI) is a highly sensitive method for characterizing cerebral tissue microstructure. Using PRISMA guidelines, we identified 29 studies which have demonstrated widespread brain microstructural impairment and topological network disorganization in patients with T2DM. Most consistently reported structures with microstructural abnormalities were frontal, temporal, and parietal lobes in the lobar cluster; corpus callosum, cingulum, uncinate fasciculus, corona radiata, and internal and external capsules in the white matter cluster; thalamus in the subcortical cluster; and cerebellum. Microstructural abnormalities were correlated with pathological derangements in the endocrine profile as well as deficits in cognitive performance in the domains of memory, information-processing speed, executive function, and attention. Altogether, the findings suggest that the detrimental effects of T2DM on cognitive functions might be due to microstructural disruptions in the central neural structures.

Adult Goat Retinal Neuronal Culture: Applications in Modeling Hyperglycemia

Culture of adult neurons of the central nervous system (CNS) can provide a unique model system to explore neurodegenerative diseases. The CNS includes neurons and glia of the brain, spinal cord and retina. Neurons in the retina have the advantage of being the most accessible cells of the CNS, and can serve as a reliable mirror to the brain. Typically, primary cultures utilize fetal rodent neurons, but very rarely adult neurons from larger mammals. Here, we cultured primary retinal neurons isolated from adult goat up to 10 days, and established an in vitro model of hyperglycemia for performing morphological and molecular characterization studies. Immunofluorescence staining revealed that approximately 30–40% of cultured cells expressed neuronal markers. Next, we examined the relative expression of cell adhesion molecules (CAMs) in adult goat brain and retina. We also studied the effect of different glucose concentrations and media composition on the growth and expression of CAMs in cultured retinal neurons. Hyperglycemia significantly enhances neurite outgrowth in adult retinal neurons in culture. Expression of CAMs such as Caspr1, Contactin1 and Prion is downregulated in the presence of high glucose. Hyperglycemia downregulates the expression of the transcription factor CCAAT/enhancer binding protein (C/EBP α), predicted to bind CAM gene promoters. Collectively, our study demonstrates that metabolic environment markedly affects transcriptional regulation of CAMs in adult retinal neurons in culture. The effect of hyperglycemia on CAM interactions, as well as related changes in intracellular signaling pathways in adult retinal neurons warrants further investigation.

Association of Glucose Fluctuations with Sarcopenia in Older Adults with Type 2 Diabetes Mellitus

Type 2 diabetes mellitus accelerates loss of muscle mass and strength. Patients with Alzheimer’s disease (AD) also show these conditions, even in the early stages of AD. The mechanism linking glucose management with these muscle changes has not been elucidated but has implications for clarifying these associations and developing preventive strategies to maintain functional capacity. This study included 69 type 2 diabetes patients with a diagnosis of cognitive impairment (n = 32) and patients with normal cognition (n = 37). We investigated the prevalence of sarcopenia in diabetes patients with and without cognitive impairment and examined the association of glucose alterations with sarcopenia. Daily glucose levels were evaluated using self-monitoring of blood glucose, and we focused on the effects of glucose fluctuations, postprandial hyperglycemia, and the frequency of hypoglycemia on sarcopenia. Diabetes patients with cognitive impairment displayed a high prevalence of sarcopenia, and glucose fluctuations were independently associated with sarcopenia, even after adjusting for glycated hemoglobin A1c (HbA1c) levels and associated factors. In particular, glucose fluctuations were significantly associated with a low muscle mass, low grip strength, and slow walking speed. Our observation suggests the importance of glucose management by considering glucose fluctuations to prevent the development of disability.