Multi-scale glycemic variability: a link to gray matter atrophy and cognitive decline in type 2 diabetes

Association between cerebral lesions and the severity of diabetic cardiovascular disease, retinopathy, and nephropathy-new lessons to learn from neuroimaging

Diabetes is associated with cerebrovascular lesions detectable through neuroimaging. Neuroimaging is traditionally valued for its insights into the structure of the central nervous system. However, the brain is connected with other organs. The vascular system, hormones, and peripheral nerve system connect the brain to other sections of the body bidirectionaly. This interaction between the brain and other parts encourages us to look at the total body, not just its different parts separately. Growing evidence has shown the link between brain injuries and cardiac, retinal, and kidney disorders, suggesting that neuroimaging has the potential to provide valuable information about peripheral organs This is particularly crucial for a systemic disease like diabetes, which affects the entire body. In this review, we aim to first discuss the data that neuroimaging can reveal about the severity of diabetic retinopathy, nephropathy, and cardiovascular disease in diabetic patients. This interdisciplinary approach could guide the design of new randomized controlled trials, screening programs, and an integrated clinical practice. This study explores the mechanisms underlying the association between the brain and other organs in the context of diabetes. Then we will consider their implications for future research and clinical practice.

Continuous Glucose Monitoring in Comorbid Dementia and Diabetes: The Evidence So Far

BACKGROUND

Type 2 diabetes mellitus (T2DM) and dementia are two of the leading chronic diseases in aging and are known to influence each other's disease progression. There is well-established evidence that T2DM increases the risk for cognitive decline and dementia. At the same time, people with cognitive changes or dementia can find it difficult to manage their diabetes, resulting in hyper- or hypoglycemic events which can exacerbate the dementia disease progression further. Monitoring of glucose variability is, therefore, of critical importance during aging and when people with T2DM develop dementia. The advent of continuous glucose monitoring (CGM) has allowed the monitoring of glucose variability in T2DM more closely. The CGM seems to be highly feasible and acceptable to use in older people with T2DM and has been shown to significantly reduce their hypoglycemic events, often resulting in falls. Less is known as to whether CGM can have a similar beneficial effect on people with T2DM who have cognitive impairment or dementia in community or hospital settings.

AIMS

The current perspective will explore how CGM has made an impact on T2DM management in older people and those with comorbid cognitive impairment or dementia. We will further explore opportunities and challenges of using CGM in comorbid T2DM and dementia in community and hospital settings.

Association of time in range with cognitive impairment in middle-aged type 2 diabetic patients

OBJECTIVE

This study investigated the association of Time In Range (TIR) obtained from Blood Glucose Monitoring (BGM) with Cognitive Impairment (CI) inpatients with middle-aged Type 2 Diabetes Mellitus (T2DM) and further explored whether a TIR goal for T2DM in adults with > 70% possess a protective effect on cognitive function.

RESEARCH DESIGN AND METHODS

A total of 274 inpatients with T2DM aged 40-64 years, who underwent seven-point BGM ( pre meals and 120 min post meals and at bedtime) were recruited in this cross-sectional study. TIR was defined as the percentage of blood glucose within the target range of 3.9-10.0mmol/L. Subjects were divided into Normal Cognitive Function (NCF) (n = 160) and CI (n = 114) groups according to the results of the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE). The association of TIR and other glycemic metrics, calculated from seven-point BGM data, with cognitive dysfunction was analyzed.

RESULTS

The prevalence of CI was 41.6% in patients with middle-aged T2DM (median age 58 years). TIR was lower in CI group than in NCF group (28.6% vs. 42.9%, P = 0.004). The prevalence of CI decreased with ascending tertiles of TIR (p for trend < 0.05). Binary logistic regression analysis showed a significant association between TIR and CI (odds ratio [OR] = 0.84, p < 0.001) after adjusting for confounders (age, education, marital status, age at Diabetes Mellitus (DM) onset, cerebrovascular disease). Further adjustment of Standard Deviation (SD)(OR = 0.84, p = 0.001) or Coefficient of Variation (CV)(OR = 0.83, p < 0.001), TIR was still associated with CI. While a TIR goal of > 70% probably possessed independent protective effect on cognitive function (OR = 0.25, p = 0.001) after controlling for confounders above.

CONCLUSIONS

TIR obtained from BGM was related to CI in middle-aged T2DM individuals and a TIR goal of > 70% probably possessed a protective effect on cognitive function for middle-aged T2DM .

Impact of blood glucose on cognitive function in insulin resistance: novel insights from ambulatory assessment

BACKGROUND/OBJECTIVES

Insulin resistance (IR)-related disorders and cognitive impairment lead to reduced quality of life and cause a significant strain on individuals and the public health system. Thus, we investigated the effects of insulin resistance (IR), and blood glucose fluctuations on cognitive function under laboratory and free-living conditions, using ecological momentary assessment (EMA).

SUBJECTS/METHODS

Baseline assessments included neuropsychological tests and blood analysis. Individuals were classified as either insulin-sensitive (<2) or insulin-resistant (≥2), based on their Homeostatic Model Assessment (HOMA-IR) values. Continuous glucose monitoring (CGM) using a percutaneous sensor was performed for 1 week. Using multiple linear regression, we examined the effects of HOMA-IR and CGM metrics on cognitive domains. Working memory (WM) performance, which was assessed using EMA, 4 times a day for 3 consecutive days, was matched to short-term pre-task CGM metrics. Multilevel analysis was used to map the within-day associations of HOMA-IR, short-term CGM metrics, and WM.

RESULTS

Analyses included 110 individuals (mean age 48.7 ± 14.3 years, 59% female, n = 53 insulin-resistant). IR was associated with lower global cognitive function (b = -0.267, P = 0.027), and WM (b = -0.316; P = 0.029), but not with executive function (b = -0.216; P = 0.154) during baseline. EMA showed that higher HOMA-IR was associated with lower within-day WM performance (β = -0.20, 95% CI -0.40 to -0.00). CGM metrics were not associated with cognitive performance.

CONCLUSIONS

The results confirm the association between IR and decrements in global cognitive functioning and WM, while no effects of CGM metrics were observed, making IR a crucial time point for intervention. Targeting underlying mechanisms (e.g., inflammation) in addition to glycemia could be promising to minimize adverse cognitive effects. Registered under https://drks.de/register/de identifier no. DRKS00022774.

Integrative molecular and structural neuroimaging analyses of the interaction between depression and age of onset: A multimodal magnetic resonance imaging study

Depression is a neurodevelopmental disorder that exhibits progressive gray matter volume (GMV) atrophy. Research indicates that brain development is influential in depression-induced GMV alterations. However, the interaction between depression and age of onset is not well understood by the underlying molecular and neuropathological mechanisms. Thus, 152 first-episode depression individuals and matched 130 healthy controls (HCs) were recruited to undergo T1-weighted high-resolution magnetic resonance imaging for this study. By two-way ANOVA, age and diagnosis were used as factors when analyzing the interaction of GMV in the participants. Then, spatial correlations between neurotransmitter maps and factor-related volume maps are established. Results illustrate a pronounced antagonistic interaction between depression and age of onset in the right insula, superior temporal gyrus, anterior cingulate gyrus, and orbitofrontal gyrus. Depression-caused reductions in GMV are mainly distributed in thalamic-limbic-cortical regions, regardless of age. For the main effect of age, adults exhibit brain atrophy in frontal, cerebellum, parietal, and temporal lobe structures. Cross-modal correlations showed that GMV changes in the interactive regions were linked with the serotonergic system and dopaminergic systems. Summarily, our results reveal the interaction between depression and age of onset in neurobiological mechanisms, which provide hints for future treatment of different ages of depression.

A systematic review of the impact of type 2 diabetes on brain cortical thickness

Introduction

Type 2 diabetes (T2D) has been linked to cognitive impairment and dementia, but its impact on brain cortical structures in individuals prior to or without cognitive impairment remains unclear.

Methods

We conducted a systematic review of 2,331 entries investigating cerebral cortical thickness changes in T2D individuals without cognitive impairment, 55 of which met our inclusion criteria.

Results

Most studies (45/55) reported cortical brain atrophy and reduced thickness in the anterior cingulate, temporal, and frontal lobes between T2D and otherwise cognitively healthy controls. However, the balance of studies (10/55) reported no significant differences in either cortical or total brain volumes. A few reports also noticed changes in the occipital cortex and its gyri. As part of the reports, less than half of studies (18/55) described a correlation between T2D and hippocampal atrophy. Variability in sample characteristics, imaging methods, and software could affect findings on T2D and cortical atrophy.

Discussion

In conclusion, T2D appears linked to reduced cortical thickness, possibly impacting cognition and dementia risk. Microvascular disease and inflammation in T2D may also contribute to this risk. Further research is needed to understand the underlying mechanisms and brain health implications.

The volume of gray matter mediates the relationship between glucolipid metabolism and neurocognition in first-episode, drug-naïve patients with schizophrenia

We aimed to examine the hypotheses that glucolipid metabolism is linked to neurocognition and gray matter volume (GMV) and that GMV mediates the association of glucolipid metabolism with neurocognition in first-episode, drug-naïve (FEDN) patients with schizophrenia. Parameters of glucolipid metabolism, neurocognition, and magnetic resonance imaging were assessed in 63 patients and 31 controls. Compared to controls, patients exhibited higher levels of fasting glucose, triglyceride, and insulin resistance index, lower levels of cholesterol and high-density lipoprotein cholesterol, poorer neurocognitive functions, and decreased GMV in the bilateral insula, left middle occipital gyrus, and left postcentral gyrus. In the patient group, triglyceride levels and the insulin resistance index exhibited a negative correlation with Rapid Visual Information Processing (RVP) mean latency, a measure of attention within the Cambridge Neurocognitive Test Automated Battery (CANTAB), while showing a positive association with GMV in the right insula. The mediation model revealed that triglyceride and insulin resistance index had a significant positive indirect (mediated) influence on RVP mean latency through GMV in the right insula. Glucolipid metabolism was linked to both neurocognitive functions and GMV in FEDN patients with schizophrenia, with the effect pattern differing from that observed in chronic schizophrenia or schizophrenia comorbid with metabolic syndrome. Moreover, glucolipid metabolism might indirectly contribute to neurocognitive deficits through the mediating role of GMV in these patients.

Association of Glycemic Variability With Imaging Markers of Vascular Burden, β-Amyloid, Brain Atrophy, and Cognitive Impairment

BACKGROUND AND OBJECTIVE

We aimed to investigate the association between glycemic variability (GV) and neuroimaging markers of white matter hyperintensities (WMH), beta-amyloid (Aβ), brain atrophy, and cognitive impairment.

METHODS

This was a retrospective cohort study that included participants without dementia from a memory clinic. They all had Aβ PET, brain MRI, and standardized neuropsychological tests and had fasting glucose (FG) levels tested more than twice during the study period. We defined GV as the intraindividual visit-to-visit variability in FG levels. Multivariable linear regression and logistic regression were used to identify whether GV was associated with the presence of severe WMH and Aβ uptake with DM, mean FG levels, age, sex, hypertension, and presence of APOE4 allele as covariates. Mediation analyses were used to investigate the mediating effect of WMH and Aβ uptake on the relationship between GV and brain atrophy and cognition.

RESULTS

Among the 688 participants, the mean age was 72.2 years, and the proportion of female participants was 51.9%. Increase in GV was predictive of the presence of severe WMH (coefficient [95% CI] 1.032 [1.012-1.054]; p = 0.002) and increased Aβ uptake (1.005 [1.001-1.008]; p = 0.007). Both WMH and increased Aβ uptake partially mediated the relationship between GV and frontal-executive dysfunction (GV → WMH → frontal-executive; direct effect, -0.319 [-0.557 to -0.080]; indirect effect, -0.050 [-0.091 to -0.008]) and memory dysfunction (GV → Aβ → memory; direct effect, -0.182 [-0.338 to -0.026]; indirect effect, -0.067 [-0.119 to -0.015]), respectively. In addition, increased Aβ uptake completely mediated the relationship between GV and hippocampal volume (indirect effect, -1.091 [-2.078 to -0.103]) and partially mediated the relationship between GV and parietal thickness (direct effect, -0.00101 [-0.00185 to -0.00016]; indirect effect, -0.00016 [-0.00032 to -0.000002]).

DISCUSSION

Our findings suggest that increased GV is related to vascular and Alzheimer risk factors and neurodegenerative markers, which in turn leads to subsequent cognitive impairment. Furthermore, GV can be considered a potentially modifiable risk factor for dementia prevention.

New Insights into the Relationship between Nutrition and Neuroinflammation in Alzheimer's Disease: Preventive and Therapeutic Perspectives

Neurodegenerative diseases are progressive brain disorders characterized by inexorable synaptic dysfunction and neuronal loss. Since the most consistent risk factor for developing neurodegenerative diseases is aging, the prevalence of these disorders is intended to increase with increasing life expectancy. Alzheimer's disease is the most common cause of neurodegenerative dementia, representing a significant medical, social, and economic burden worldwide. Despite growing research to reach an early diagnosis and optimal patient management, no disease-modifying therapies are currently available. Chronic neuroinflammation has been recognized as a crucial player in sustaining neurodegenerative processes, along with pathological deposition of misfolded proteins, including amyloid-β and tau protein. Modulating neuroinflammatory responses may be a promising therapeutic strategy in future clinical trials. Among factors that are able to regulate neuroinflammatory mechanisms, diet, and nutrients represent easily accessible and modifiable lifestyle components. Mediterranean diet and several nutrients, including polyphenols, vitamins, and omega-3 polyunsaturated fatty acids, can exert antioxidant and anti-inflammatory properties, impacting clinical manifestations, cognitive decline, and dementia. This review aims to provide an updated overview of the relationship between neuroinflammation, nutrition, gut microbiota, and neurodegeneration. We summarize the major studies exploring the effects of diet regimes on cognitive decline, primarily focusing on Alzheimer's disease dementia and the impact of these results on the design of ongoing clinical trials.

[Wearable devices: Perspectives on assessing and monitoring human physiological status]

This review article aims to explore the major challenges that the healthcare system is currently facing and propose a new paradigm shift that harnesses the potential of wearable devices and novel theoretical frameworks on health and disease. Lifestyle-induced diseases currently account for a significant portion of all healthcare spending, with this proportion projected to increase with population aging. Wearable devices have emerged as a key technology for implementing large-scale healthcare systems focused on disease prevention and management. Advancements in miniaturized sensors, system integration, the Internet of Things, artificial intelligence, 5G, and other technologies have enabled wearable devices to perform high-quality measurements comparable to medical devices. Through various physical, chemical, and biological sensors, wearable devices can continuously monitor physiological status information in a non-invasive or minimally invasive way, including electrocardiography, electroencephalography, respiration, blood oxygen, blood pressure, blood glucose, activity, and more. Furthermore, by combining concepts and methods from complex systems and nonlinear dynamics, we developed a novel theory of continuous dynamic physiological signal analysis-dynamical complexity. The results of dynamic signal analyses can provide crucial information for disease prevention, diagnosis, treatment, and management. Wearable devices can also serve as an important bridge connecting doctors and patients by tracking, storing, and sharing patient data with medical institutions, enabling remote or real-time health assessments of patients, and providing a basis for precision medicine and personalized treatment. Wearable devices have a promising future in the healthcare field and will be an important driving force for the transformation of the healthcare system, while also improving the health experience for individuals.

Correlation between long-term glycemic variability and cognitive function in middle-aged and elderly patients with type 2 diabetes mellitus: a retrospective study

Objective

To investigate the correlation between long-term glycemic variability and cognitive function in middle-aged and elderly patients with type 2 diabetes mellitus (T2DM).

Methods

This retrospective analysis includes 222 patients hospitalized at Second Affiliated Hospital of Anhui Medical University from June 2021 to June 2023. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE). All patients were categorized into the MCI group and the non-MCI group based on their MoCA score. Long-term blood glucose fluctuations were measured using glycated hemoglobin A1c standard deviation (HbA1c-SD) and fasting plasma glucose standard deviation (FPG-SD). The study compared general clinical data, blood biochemical indicators, and glycemic variability indicators between the two groups. The differences between the groups were compared using t-test, Chi-Square Test, or Mann-Whitney U test. Kendall's correlation analysis, multivariate logistic regression analysis and ROC curve correlation analysis were further used to analyze the correlation and diagnostic power.

Results

The differences in age, MoCA scores, MMSE scores, HOMA-β, HbA1c-M, HbA1c-SD, FPG-M, FPG-SD, eGFR, Smoking, GLP-1RA and SGLT-2i usage were statistically significant between the two groups (P < 0.05). Kendall's correlation analysis showed that age, HbA1c-M, HbA1c-SD, FPG-M, and FPG-SD was negatively correlated with MoCA scores; meanwhile, the HOMA-β, and eGFR was positively correlated with MoCA scores. Multiple logistic regression analysis revealed that HbA1c-SD, FPG-SD and Smoking were risk factors for cognitive dysfunction, while eGFR, GLP-1RA and SGLT-2i usage was a protective effect. The area under the curve (AUC) values for predicting MCI prevalence were 0.830 (95% CI [0.774-0.877], P < 0.001) for HbA1c-SD, 0.791 (95% CI [0.655-0.808], P < 0.001) for FPG-SD, and 0.698 (95% CI [0.633-0.757], P < 0.001) for eGFR. The optimal diagnostic values were 0.91, 1.32, and 74.81 ml/min/1.73 m2 for HbA1c-SD, FPG-SD, and eGFR, respectively.

Conclusions

Cognitive function in middle-aged and elderly T2DM patients is influenced by long-term blood glucose variability, with poorer cognitive function observed in individuals with higher blood glucose variability. The impact of HbA1c-SD on MCI exhibited a greater magnitude compared to that of PFG-SD and smoking. Additionally, renal function, GLP-1RA and SGLT-2i usage exert positive effects on cognitive function.

Glycaemic variability, assessed with continuous glucose monitors, is associated with diet, lifestyle and health in people without diabetes

Background

Continuous glucose monitors (CGMs) provide high-frequency information regarding daily glucose variation and are recognised as effective for improving glycaemic control in individuals living with diabetes. Despite increased use in individuals with non-diabetic blood glucose concentrations (euglycemia), their utility as a health tool in this population remains unclear.

Objectives

To characterise variation in time in range (TIR) and glycaemic variability in large populations without diabetes or impaired glucose tolerance; describe associations between CGM-derived glycaemic metrics and metabolic and cardiometabolic health traits; identify key diet and lifestyle factors associated with TIR and glycaemic variability.

Design

Glycaemic variability (coefficient of variation) and time spent in both the ADA secondary target range (TIRADA; 3.9-7.8 mmol/L) and a more stringent range (TIR3.9-5.6; 3.9-5.6 mmol/L) were calculated during free-living in PREDICT 1, PREDICT 2, and PREDICT 3 euglycaemic community-based volunteer cohorts. Associations between CGM derived glycaemic metrics, markers of cardiometabolic health, diet (food frequency questionnaire and logged diet records), diet-habits, and lifestyle were explored.

Results

Data from N=4135 participants (Mean SD; Age: 47 12 y; Sex: 83% Female, BMI: 27 6 kg/m2). Median glycaemic variability was 14.8% (IQR 12.6-17.6%), median TIRADA was 95.8% (IQR 89.6-98.6%) and TIR3.9-5.6 was 75.0% (IQR 64.6-82.8%). Greater TIR3.9-5.6 was associated with lower HbA1c, ASCVD 10y risk and HOMA-IR (all p < 0.05). Lower glycaemic variability was associated with lower % energy derived from carbohydrate (rs: 0.17, p < 0.01), ultra-processed foods (NOVA 4, % EI; rs: 0.12, p = 0.01) and a longer overnight fasting duration (rs: -0.10, p = 0.01).

Conclusions

A stringent TIR target provides sensitivity to detect changes in HOMA-IR, ASCVD 10 y risk and HbA1c that were not detected using ADA secondary targets. Associations among TIR, glycaemic variability, dietary intake (e.g. carbohydrate and protein) and habits (e.g. nocturnal fasting duration) highlight potential strategic targets to improve glycaemic metrics derived from continuous glucose monitors.

Near-Infrared Spectroscopy: A Free-Living Neuroscience Tool to Better Understand Diabetes and Obesity

The human brain is the least accessible of all organs and attempts to study it in vivo rely predominantly on neuroimaging. Functional near-infrared spectroscopy (fNIRS) allows for the study of cortical neural activity in a non-invasive manner that may resemble free-living conditions. Moreover, compared to other neuroimaging tools, fNIRS is less expensive, it does not require the use of ionizing radiation, and can be applied to all study populations (patients suffering from claustrophobia, or neonates). In this narrative review, we provide an overview of the available research performed using fNIRS in patients with diabetes and obesity. The few studies conducted to date have presented controversial results regarding patients with diabetes, some reporting a greater hemodynamic response and others reporting a reduced hemodynamic response compared to the controls, with an unclear distinction between types 1 and 2. Subjects with obesity or a binge eating disorder have reduced prefrontal activation in response to inhibitory food or non-food stimuli; however, following an intervention, such as cognitive treatment, prefrontal activation is restored. Moreover, we discuss the potential of future applications of fNIRS for a better understanding of cortical neural activity in the context of metabolic disorders.

Visit-to-visit HbA1c variability, dementia, and hippocampal atrophy among adults without diabetes

OBJECTIVES

Adults without diabetes are not completely healthy; they are probably heterogeneous with several potential health problems. The management of hemoglobin A1c (HbA1c) is crucial among patients with diabetes; but whether similar management strategy is needed for adults without diabetes is unclear. Thus, this study aimed to investigate the associations of visit-to-visit HbA1c variability with incident dementia and hippocampal volume among middle-aged and older adults without diabetes, providing potential insights into this question.

METHODS

We conducted a prospective analysis for incident dementia in 10,792 participants (mean age 58.9 years, 47.8 % men) from the UK Biobank. A subgroup of 3793 participants (mean age 57.8 years, 48.6 % men) was included in the analysis for hippocampal volume. We defined HbA1c variability as the difference in HbA1c divided by the mean HbA1c over the 2 sequential visits ([latter - former]/mean). Dementia was identified using hospital inpatient records with ICD-9 codes. T1-structural brain magnetic resonance imaging was conducted to derive hippocampal volume (normalized for head size). The nonlinear and linear associations were examined using restricted cubic spline (RCS) models, Cox regression models, and multiple linear regression models.

RESULTS

During a mean follow-up (since the second round) of 8.4 years, 90 (0.8 %) participants developed dementia. The RCS models suggested no significant nonlinear associations of HbA1c variability with incident dementia and hippocampal volume, respectively (All P > 0.05). Above an optimal cutoff of HbA1c variability at 0.08, high HbA1c variability (increment in HbA1c) was associated with an increased risk of dementia (Hazard Ratio, 1.88; 95 % Confidence Interval, 1.13 to 3.14, P = 0.015), and lower hippocampal volume (coefficient, -96.84 mm3, P = 0.037), respectively, in models with adjustment of covariates including age, sex, etc. Similar results were found for a different cut-off of 0. A series of sensitivity analyses verified the robustness of the findings.

CONCLUSIONS

Among middle-aged and older adults without diabetes, increasing visit-to-visit HbA1c variability was associated with an increased dementia risk and lower hippocampal volume. The findings highlight the importance of monitoring and controlling HbA1c fluctuation in apparently healthy adults without diabetes.

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.

Glucose variability: A physiological correlate of eating disorder behaviors among individuals with binge-spectrum eating disorders

OBJECTIVES

Elevated glucose variability may be one mechanism that increases risk for significant psychological and physiological health conditions among individuals with binge-spectrum eating disorders (B-EDs), given the impact of eating disorder (ED) behaviors on blood glucose levels. This study aimed to characterize glucose variability among individuals with B-EDs compared with age-matched, sex-matched, and body mass index-matched controls, and investigate the association between frequency of ED behaviors and glucose variability.

METHODS

Participants were 52 individuals with B-EDs and 22 controls who wore continuous glucose monitors to measure blood glucose levels and completed ecological momentary assessment surveys to measure ED behaviors for 1 week. Independent samples t-tests compared individuals with B-EDs and controls and multiple linear regression models examined the association between ED behaviors and glucose variability.

RESULTS

Individuals with B-EDs demonstrated numerically higher glucose variability than controls (t = 1.42, p = .08, d = 0.43), although this difference was not statistically significant. When controlling for covariates, frequency of ED behaviors was significantly, positively associated with glucose variability (t = 3.17, p = .003) with medium effect size (f2  = 0.25). Post hoc analyses indicated that binge eating frequency was significantly associated with glucose variability, while episodes of 5+ hours without eating were not.

DISCUSSION

Glucose variability among individuals with B-EDs appears to be positively associated with engagement in ED behaviors, particularly binge eating. Glucose variability may be an important mechanism by which adverse health outcomes occur at elevated rates in B-EDs and warrants future study.

PUBLIC SIGNIFICANCE

This study suggests that some individuals with binge ED and bulimia nervosa may experience elevated glucose variability, a physiological symptom that is linked to a number of adverse health consequences. The degree of elevation in glucose variability is positive associated with frequency of eating disorder behaviors, especially binge eating.

Association between Type 2 Diabetes Mellitus and Brain Atrophy: A Meta-Analysis

BACKGROUND

Type 2 diabetes mellitus (T2DM) is known to be associated with cognitive decline and brain structural changes. This study systematically reviews and estimates human brain volumetric differences and atrophy associated with T2DM.

METHODS

PubMed, PsycInfo and Cochrane Library were searched for brain imaging studies reporting on brain volume differences between individuals with T2DM and healthy controls. Data were examined using meta-analysis, and association between age, sex, diabetes characteristics and brain volumes were tested using meta-regression.

RESULTS

A total of 14,605 entries were identified; after title, abstract and full-text screening applying inclusion and exclusion criteria, 64 studies were included and 42 studies with compatible data contributed to the meta-analysis (n=31,630; mean age 71.0 years; 44.4% male; 26,942 control; 4,688 diabetes). Individuals with T2DM had significantly smaller total brain volume, total grey matter volume, total white matter volume and hippocampal volume (approximately 1% to 4%); meta-analyses of smaller samples focusing on other brain regions and brain atrophy rate in longitudinal investigations also indicated smaller brain volumes and greater brain atrophy associated with T2DM. Meta-regression suggests that diabetes-related brain volume differences start occurring in early adulthood, decreases with age and increases with diabetes duration.

CONCLUSION

T2DM is associated with smaller total and regional brain volume and greater atrophy over time. These effects are substantial and highlight an urgent need to develop interventions to reduce the risk of T2DM for brain health.

Compensatory thalamocortical functional hyperconnectivity in type 2 Diabetes Mellitus

Type 2 diabetes mellitus (T2DM) is associated with brain damage and cognitive decline. Despite the fact that the thalamus involves aspects of cognition and is typically affected in T2DM, existing knowledge of subregion-level thalamic damage and its associations with cognitive performance in T2DM patients is limited. The thalamus was subdivided into 8 subregions in each hemisphere. Resting-state functional and structural MRI data were collected to calculate resting-state functional connectivity (rsFC) and gray matter volume (GMV) of each thalamic subregion in 62 T2DM patients and 50 healthy controls. Compared with controls, T2DM patients showed increased rsFC of the medial pre-frontal thalamus, posterior parietal thalamus, and occipital thalamus with multiple cortical regions. Moreover, these thalamic functional hyperconnectivity were associated with better cognitive performance and lower glucose variability in T2DM patients. However, there were no group differences in GMV for any thalamic subregions. These findings suggest a possible neural compensation mechanism whereby selective thalamocortical functional hyperconnectivity facilitated by better glycemic control help to preserve cognitive ability in T2DM patients, which may ultimately inform intervention and prevention of T2DM-related cognitive decline in real-world clinical settings.

Impairments in intrinsic functional networks in type 2 diabetes: A meta-analysis of resting-state functional connectivity

Type 2 diabetes mellitus (T2DM) is associated with abnormal communication among large-scale brain networks, revealed by resting-state functional connectivity (rsFC), with inconsistent results between studies. We performed a meta-analysis of seed-based rsFC studies to identify consistent network connectivity alterations. Thirty-three datasets from 30 studies (1014 T2DM patients and 902 healthy controls [HC]) were included. Seed coordinates and between-group effects were extracted, and the seeds were divided into networks based on their location. Compared to HC, T2DM patients showed hyperconnectivity and hypoconnectivity within the DMN, DMN hypoconnectivity with the affective network (AN), ventral attention network (VAN) and frontal parietal network, and DMN hyperconnectivity with the VAN and visual network. T2DM patients also showed AN hypoconnectivity with the somatomotor network and hyperconnectivity with the VAN. T2DM illness durations negatively correlated with within-DMN rsFC. These DMN-centered impairments in large-scale brain networks in T2DM patients may help to explain the cognitive deficits associated with T2DM.

Safety of Intranasal Insulin in Type 2 Diabetes on Systemic Insulin: A Double-Blinded Placebo-Controlled Sub-Study of Memaid Trial

AIMS

To determine safety of intranasal insulin (INI) in MemAID trial participants with diabetes treated with systemic insulins.

MATERIALS AND METHODS

This randomized, double-blinded trial consisted of 24-week INI or placebo treatment once daily and 24-week follow-up. Safety outcomes were: 1) Short-term effects on glycemic variability, hypoglycemic episodes on continuous glucose monitoring (CGM) at baseline and on-treatment. 2) Long-term effects on glucose metabolism and weight on INI/placebo treatment and post-treatment follow-up. Of 86 screened subjects, 14 were randomized, 9 (5 INI, 4 Placebo) completed CGM at baseline and on-treatment, and 5 (2 INI, 3 Placebo) completed treatment and follow-up.

RESULTS

INI was safe and was not associated with serious adverse events, hypoglycemic episodes or weight gain. INI administration did not acutely affect capillary glucose. Glycemic variability on CGM decreased with INI, compared to baseline. On INI treatment, there was a long-term trend toward lower HbA1c, plasma glucose and insulin. No interactions with subcutaneous insulins were observed.

CONCLUSIONS

INI is safe in older people with diabetes treated with systemic insulins, and it is not associated with adverse events, hypoglycemia or weight gain. Future studies are needed to determine whether INI administration can reduce glycemic variability, improve insulin sensitivity and thus potentially lessen diabetes burden in this population.

Large-scale functional connectivity predicts cognitive impairment related to type 2 diabetes mellitus

BACKGROUND

Large-scale functional connectivity (LSFC) patterns in the brain have unique intrinsic characteristics. Abnormal LSFC patterns have been found in patients with dementia, as well as in those with mild cognitive impairment (MCI), and these patterns predicted their cognitive performance. It has been reported that patients with type 2 diabetes mellitus (T2DM) may develop MCI that could progress to dementia. We investigated whether we could adopt LSFC patterns as discriminative features to predict the cognitive function of patients with T2DM, using connectome-based predictive modeling (CPM) and a support vector machine.

AIM

To investigate the utility of LSFC for predicting cognitive impairment related to T2DM more accurately and reliably.

METHODS

Resting-state functional magnetic resonance images were derived from 42 patients with T2DM and 24 healthy controls. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). Patients with T2DM were divided into two groups, according to the presence (T2DM-C; n = 16) or absence (T2DM-NC; n = 26) of MCI. Brain regions were marked using Harvard Oxford (HOA-112), automated anatomical labeling (AAL-116), and 264-region functional (Power-264) atlases. LSFC biomarkers for predicting MoCA scores were identified using a new CPM technique. Subsequently, we used a support vector machine based on LSFC patterns for among-group differentiation. The area under the receiver operating characteristic curve determined the appearance of the classification.

RESULTS

CPM could predict the MoCA scores in patients with T2DM (Pearson’s correlation coefficient between predicted and actual MoCA scores, r = 0.32, P=0.0066 [HOA-112 atlas]; r = 0.32, P=0.0078 [AAL-116 atlas]; r = 0.42, P=0.0038 [Power-264 atlas]), indicating that LSFC patterns represent cognition-level measures in these patients. Positive (anti-correlated) LSFC networks based on the Power-264 atlas showed the best predictive performance; moreover, we observed new brain regions of interest associated with T2DM-related cognition. The area under the receiver operating characteristic curve values (T2DM-NC group vs. T2DM-C group) were 0.65-0.70, with LSFC matrices based on HOA-112 and Power-264 atlases having the highest value (0.70). Most discriminative and attractive LSFCs were related to the default mode network, limbic system, and basal ganglia.

CONCLUSION

LSFC provides neuroimaging-based information that may be useful in detecting MCI early and accurately in patients with T2DM.

Long-term glycemic variability and risk of stroke in patients with diabetes: a meta-analysis

OBJECTIVES

Long-term glycemic variability has been related to increased risk of vascular complication in patients with diabetes. However, the association between parameters of long-term glycemic variability and risk of stroke remains not fully determined. We performed a meta-analysis to systematically evaluate the above association.

METHODS

Medline, Embase, and Web of Science databases were searched for longitudinal follow-up studies comparing the incidence of stroke in diabetic patients with higher or lower long-term glycemic variability. A random-effect model incorporating the potential heterogeneity among the included studies were used to pool the results.

RESULTS

Seven follow-up studies with 725,784 diabetic patients were included, and 98% of them were with type 2 diabetes mellitus (T2DM). The mean follow-up duration was 7.7 years. Pooled results showed that compared to those with lowest category of glycemic variability, diabetic patients with the highest patients had significantly increased risk of stroke, as evidenced by glycemic variability analyzed by fasting plasma glucose coefficient of variation (FPG-CV: risk ratio [RR] = 1.24, 95% confidence interval [CI] 1.11 to 1.39, P < 0.001; I² = 53%), standard deviation of FPG (FPG-SD: RR = 1.16, 95% CI 1.02 to 1.31, P = 0.02; I² = 74%), HbA1c coefficient of variation (HbA1c-CV: RR = 1.88, 95% CI 1.61 to 2.19 P < 0.001; I² = 0%), and standard deviation of HbA1c (HbA1c-SD: RR = 1.73, 95% CI 1.49 to 2.00, P < 0.001; I² = 0%).

CONCLUSIONS

Long-term glycemic variability is associated with higher risk of stroke in T2DM patients.

Abnormal vibration perception threshold alters the gait features in type 2 diabetes mellitus patients

OBJECTIVE

It is generally believed that gait characteristics of diabetic neuropathic patients differ from those of non-diabetic ones. However, it is still unclear how the abnormal foot sensation influences the gait during walking in type 2 diabetes mellitus (T2DM). For the purpose of gaining a better insight into the alterations of detailed gait parameters and figuring out important aspects in the gait indexes by peripheral neuropathy in elder T2DM patients, we compared the gait features in participants with normal glucose tolerance (NGT) controls and diabetic individuals complicated by peripheral neuropathy or not.

SUBJECTS AND METHODS

Gait parameters were observed during the 10-m walk on flat land among different conditions of diabetes in 1,741 participants from three clinical centers. Subjects were divided into four groups: persons with NGT were taken as the control group; patients with T2DM included three subgroups: DM control (no chronic complications), DM-DPN (DM complicated by only peripheral neuropathy), and DM-DPN+LEAD (DM complicated by both neuropathy and artery disease). The clinical characteristics and gait parameters were assessed and compared among these four groups. Analyses of variance were employed to verify possible differences of gait parameters between groups and conditions. Stepwise multivariate regression analysis was performed to reveal possible predictors of gait deficits. Receiver operating characteristic (ROC) curve analysis was employed to find any discriminatory power of diabetic peripheral neuropathy (DPN) for the step time.

RESULTS

In participants burdened with DPN, whether complicated by lower extremity arterial disease (LEAD) or not, step time increased sharply (p < 0.05). Stepwise multivariate regression models showed that independent variables of gait abnormality were sex, age, leg length, vibration perception threshold (VPT), and ankle-brachial index (ABI) (p < 0.01). Meanwhile, VPT was a significant independent predictor of step time, spatiotemporal variability (SD_A), and temporal variability (SD_B) (p < 0.05). ROC curve analysis was explored to find the discriminatory power of DPN for the occurrence of increased step time. The area under the curve (AUC) value was 0.608 (95% CI: 0.562-0.654, p < 0.01), and the cutoff point was 538.41 ms accompanied by a higher VPT. A significant positive association was observed between increased step time and the highest VPT group [odds ratio (OR) = 1.83, 95% CI: 1.32-2.55, p< 0.01]. In female patients, this OR value elevated to 2.16 (95% CI: 1.25-3.73, p< 0.01).

CONCLUSIONS

In addition to sex, age, and leg length, VPT was a distinct factor that associated with altered gait parameters. DPN is associated with increased step time, and the step time increases with worsening VPT in type 2 diabetes.

HbA1c Variability and the Risk of Dementia in Patients with Diabetes: A Meta-Analysis

BACKGROUND

Variability of HbA1c has been related to the incidence micro and macrovascular complications in patients with diabetes. However, the association between of visit-to-visit variability of HbA1c and risk of dementia has not been fully determined. A meta-analysis was performed to comprehensively evaluate the above association.

METHODS

Medline, Embase, and Web of Science databases were searched for longitudinal follow-up studies comparing the incidence of dementia in diabetic patients with higher or lower variability of HbA1c. A random-effect model incorporating the potential heterogeneity among the included studies were used to pool the results.

RESULTS

Five retrospective studies with 577592 diabetic patients were included, and 99% of them were with type 2 diabetes mellitus (T2DM). With a mean follow-up duration of 6.3 years, 31963 patients had newly diagnosed dementia. Pooled results showed that diabetic patients with higher HbA1c variability was associated with higher risk of dementia, as evidenced by studies with coefficient of variation (CV: hazard ratio (HR): 1.06; 95% confidence interval (CI): 1.003-1.120; p=0.04; I ² = 47%) and standard deviation (SD : HR: 1.19; 95% CI: 1.06-1.32; p=0.002; I ² = 0%) of HbA1c in continuous variables, and CV of HbA1c (HR: 1.18; 95% CI: 1.08-1.28; p < 0.001; I ² = 31%) in categorized variables.

CONCLUSIONS

Higher variability of HbA1c is associated with a higher incidence of dementia in patients with diabetes.

Perspectives of glycemic variability in diabetic neuropathy: a comprehensive review

Diabetic neuropathy is one of the most prevalent chronic complications of diabetes, and up to half of diabetic patients will develop diabetic neuropathy during their disease course. Notably, emerging evidence suggests that glycemic variability is associated with the pathogenesis of diabetic complications and has emerged as a possible independent risk factor for diabetic neuropathy. In this review, we describe the commonly used metrics for evaluating glycemic variability in clinical practice and summarize the role and related mechanisms of glycemic variability in diabetic neuropathy, including cardiovascular autonomic neuropathy, diabetic peripheral neuropathy and cognitive impairment. In addition, we also address the potential pharmacological and non-pharmacological treatment methods for diabetic neuropathy, aiming to provide ideas for the treatment of diabetic neuropathy.

Zhang et al. describe metrics for evaluating glycaemic variability (GV) in clinical practice and summarize the role and related mechanisms of GV in diabetic neuropathy, including cardiovascular autonomic neuropathy, diabetic peripheral neuropathy and cognitive impairment. They aim to stimulate ideas for the treatment of diabetic neuropathy.

The Rate of Decrease in Brain Perfusion in Progressive Supranuclear Palsy and Corticobasal Syndrome May Be Impacted by Glycemic Variability-A Pilot Study

Progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS) are tauopathic parkinsonian syndromes, presently lacking disease-modifying treatments. Patients affected by these diseases suffer due to multidimensional deteriorations resulting in motor and cognitive impairment. Previously published research has confirmed risk factors that may impact the course of PSP and CBS, among them hypertension and diabetes. Less data is available regarding prediabetes and glycemic variability. In this study, 26 patients with clinical diagnoses of PSP and CBS were examined using glycated hemoglobin and perfusion single-photon emission tomography (SPECT). Patients were divided into two groups-PSP/CBS patients with glycated hemoglobin (HbA1c) below and above 5.7%. The results of the perfusion evaluation were compared with the values from healthy volunteers from the software's database. A decrease in perfusion in certain regions of interest was observed among patients affected by increased glycemic variability. A more pronounced decrement in perfusion was observed only in some regions of interest-the hippocampus, pons, left thalamus, right insula. The results indicated that, among PSP/CBS patients, individuals with more pronounced glycemic variability had more severe hypoperfusion in certain brain regions in comparison with PSP/CBS patients without carbohydrate metabolism disorders. Due to the fact that PSP and CBS are associated with cognitive impairment, an additional decrease in perfusion in the hippocampal area may impact the rate of cognitive deterioration.

A multimodal meta-analysis of regional structural and functional brain alterations in type 2 diabetes

Neuroimaging studies have identified brain structural and functional alterations of type 2 diabetes mellitus (T2DM) patients; however, there is no systematic information on the relations between abnormalities in these two domains. We conducted a multimodal meta-analysis of voxel-based morphometry and regional resting-state functional MRI studies in T2DM, including fifteen structural datasets (693 patients and 684 controls) and sixteen functional datasets (378 patients and 358 controls). We found, in patients with T2DM compared to controls, conjoint decreased regional gray matter volume (GMV) and altered intrinsic activity mainly in the default mode network including bilateral superior temporal gyrus/Rolandic operculum, left middle and inferior temporal gyrus, and left supramarginal gyrus; decreased GMV alone in the limbic system; and functional abnormalities alone in the cerebellum, insula, and visual cortex. This meta-analysis identified complicated patterns of conjoint and dissociated brain alterations in T2DM patients, which may help provide new insight into the neuropathology of T2DM.

Increased resting state functional irregularity of T2DM brains with high HbA1c: sign for impaired verbal memory function?

Glycosylated hemoglobin A1c (HbA1c) has been considered as a key contributor to impaired cognition in type 2 diabetes mellitus (T2DM) brains. However, how does it affect the brain and whether the glucose controlling can slow down the process are still unknown. In the current study, T2DM patients with high glycosylated hemoglobin level (HGL) and controls with normal glycosylated hemoglobin level (NGL) were enrolled to investigate the relationships between HbA1c, brain imaging characteristics and cognitive function. First, a series of cognitive tests including California Verbal Learning Test (CVLT) were conducted. Then, the functional irregularity based on resting state functional magnetic resonance imaging data was evaluated via a new data-driven brain entropy (BEN) mapping analysis method. We found that the HGLs exhibited significantly increased BEN in the right precentral gyrus (PreCG.R), the right middle frontal gyrus (MFG.R), the triangular and opercular parts of the right inferior frontal gyrus (IFGtriang.R and IFGoperc.R). The strengths of the functional connections of PreCG.R with the brainstem/cerebellum were decreased. Partial correlation analysis showed that HbA1c had a strong positive correlation to regional BEN and negatively correlated with some CVLT scores. Negative correlations also existed between the BEN of PreCG.R/IFGoperc.R and some CVLT scores, suggesting the correspondence between higher HbA1c, increased BEN and decreased verbal memory function. This study demonstrated the potential of BEN in exploring the functional alterations affected by HbA1c and interpreting the verbal memory function decline. It will help understanding the neurophysiological mechanism of T2DM-induced cognitive decline and taking effective prevention or treatment measures.

Diabetes-Alzheimer's Disease Link: Targeting Mitochondrial Dysfunction and Redox Imbalance

Significance: It is of common sense that the world population is aging and life expectancy is increasing. However, as the population ages, there is also an exponential risk to live into the ages where the brain-related frailties and neurodegenerative diseases develop. Hand in hand with those events, the world is witnessing a major upsurge in diabetes diagnostics. Remarkably, all of this seems to be narrowly related, and clinical and research communities highlight for the upcoming threat that it will represent for the present and future generations. Recent Advances: It is of utmost importance to clarify the influence of diabetes-related metabolic features on brain health and the mechanisms underlying the increased likelihood of developing neurodegenerative diseases, in particular Alzheimer's disease. Thereupon, a wealth of evidence suggests that mitochondria and associated oxidative stress are at the root of the link between diabetes and co-occurring disorders in the brain. Critical Issues: The scientific community has been challenged with constant failures of clinical trials raising major issues in the advance of the therapeutic field to fight chronic diseases epidemics. Thus, a change of paradigms is urgently needed. Future Directions: It has become urgent to identify new and solid candidates able to clinically reproduce the positive outcomes obtained in preclinical studies. On this basis, strategies settled to counteract diabetes-induced neurodegeneration encompassing mitochondrial dysfunction, redox status imbalance, and/or insulin dysregulation seem worth to follow. Hopefully, ongoing innovative research based on reliable experimental tools will soon bring the desired answers allowing pharmaceutical industry to apply such knowledge to human medicine.

Improved time in range and postprandial hyperglycemia with canagliflozin in combination with teneligliptin: Secondary analyses of the CALMER study

Aims/Introduction

We recently reported the beneficial effect of the combination of sodium–glucose cotransporter 2 inhibitor and dipeptidyl peptidase‐4 inhibitor on daily glycemic variability in patients with type 2 diabetes mellitus. Additional favorable effects of combination therapy were explored in this secondary analysis.

Materials and Methods

The CALMER study was a multicenter, open‐label, prospective, randomized, parallel‐group comparison trial for type 2 diabetes mellitus involving continuous glucose monitoring under meal tolerance tests. Patients were randomly assigned to switch from teneligliptin to canagliflozin (SWITCH group) or to add canagliflozin to teneligliptin (COMB group). The continuous glucose monitoring metrics, including time in target range, were investigated.

Results

All 99 participants (mean age 62.3 years; mean glycated hemoglobin 7.4%) completed the trial. The time in target range was increased in the COMB group (71.2–82.7%, P < 0.001). The extent of the reduction in time above target range was significantly larger in the COMB group compared with the SWITCH group (−14.8% vs −7.5%, P < 0.01). Area under the curve values for glucose at 120 min after all meal tolerance tests were significantly decreased in the COMB group compared with the SWITCH group (P < 0.05).

Conclusions

Sodium–glucose cotransporter 2 inhibitor combined with dipeptidyl peptidase‐4 inhibitor improved the quality of glycemic variability and reduced postprandial hyperglycemia compared with each monotherapy.

Sodium-glucose cotransporter 2 inhibitors reduce day-to-day glucose variability in patients with type 1 diabetes

AIMS/INTRODUCTION

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) are used worldwide because of their multiple benefits for patients with type 2 diabetes. The purpose of this study was to determine the efficacy and safety of SGLT2i in patients with type 1 diabetes.

MATERIALS AND METHODS

Patients with type 1 diabetes who had been treated with SGLT2i for >12 weeks were included in this retrospective observation study. We recorded the changes in body mass, insulin dose, blood and urine test data, and adverse events. The changes in day-to-day glucose variability, as the primary end-point, was evaluated using the interquartile range (P25/P75) of the ambulatory glucose data obtained using continuous glucose monitoring.

RESULTS

A total of 51 patients (37 women; mean age 52.7 years) were included. Glycated hemoglobin and body mass significantly decreased by 0.4% and 1.6 kg, respectively. The total required insulin dose decreased by 9.4% (42.7 ± 26.6-38.7 ± 24.3 units/day). Continuous glucose monitoring data were obtained from 30 patients. P25/P75 decreased by 17.6 ± 20.7% during SGLT2i treatment (P < 0.001). The percentage of time per day within the target glucose range of 70-180 mg/dL significantly increased (from 42.2 to 55.5%, P < 0.001), without an increase in the percentage of time spent in the hypoglycemic range (<70 mg/dL). Urinary ketone bodies were detected in four patients (7.8%), but none developed ketoacidosis.

CONCLUSIONS

SGLT2i improved day-to-day glucose variability and time in the target glucose range, without increasing frequency of hypoglycemia, in patients with type 1 diabetes, and reduced glycated hemoglobin, body mass and the required insulin dose.

Reduced Brain Gray Matter Volume in Patients With First-Episode Major Depressive Disorder: A Quantitative Meta-Analysis

Background: The findings of many neuroimaging studies in patients with first-episode major depressive disorder (MDD), and even those of previous meta-analysis, are divergent. To quantitatively integrate these studies, we performed a meta-analysis of gray matter volumes using voxel-based morphometry (VBM). Methods: We performed a comprehensive literature search for relevant studies and traced the references up to May 1, 2021 to select the VBM studies between first-episode MDD and healthy controls (HC). A quantitative meta-analysis of VBM studies on first-episode MDD was performed using the Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) method, which allows a familywise error rate (FWE) correction for multiple comparisons of the results. Meta-regression was used to explore the effects of demographics and clinical characteristics. Results: Nineteen studies, with 22 datasets comprising 619 first-episode MDD and 707 HC, were included. The pooled and subgroup meta-analysis showed robust gray matter reductions in the left insula, the bilateral parahippocampal gyrus extending into the bilateral hippocampus, the right gyrus rectus extending into the right striatum, the right superior frontal gyrus (dorsolateral part), the left superior frontal gyrus (medial part) and the left superior parietal gyrus. Meta-regression analyses showed that higher HDRS scores were significantly more likely to present reduced gray matter volumes in the right amygdala, and the mean age of MDD patients in each study was negatively correlated with reduced gray matter in the left insula. Conclusions: The present meta-analysis revealed that structural abnormalities in the fronto-striatal-limbic and fronto-parietal networks are essential characteristics in first-episode MDD patients, which may become a potential target for clinical intervention.

Glycemic Variability and CNS Inflammation: Reviewing the Connection

Glucose is the primary energy source for the brain, and exposure to both high and low levels of glucose has been associated with numerous adverse central nervous system (CNS) outcomes. While a large body of work has highlighted the impact of hyperglycemia on peripheral and central measures of oxidative stress, cognitive deficits, and vascular complications in Type 1 and Type 2 diabetes, there is growing evidence that glycemic variability significantly drives increased oxidative stress, leading to neuroinflammation and cognitive dysfunction. In this review, the latest data on the impact of glycemic variability on brain function and neuroinflammation will be presented. Because high levels of oxidative stress have been linked to dysfunction of the blood-brain barrier (BBB), special emphasis will be placed on studies investigating the impact of glycemic variability on endothelial and vascular inflammation. The latest clinical and preclinical/in vitro data will be reviewed, and clinical/therapeutic implications will be discussed.

A Prospective Longitudinal Study on the Relationship Between Glucose Fluctuation and Cognitive Function in Type 2 Diabetes: PROPOSAL Study Protocol

INTRODUCTION

Although the risk of dementia among patients with type 2 diabetes mellitus (T2DM) is double that of those without T2DM, the mechanism remains to be elucidated and the glycemic goal to prevent progression of cognitive impairment is unclear. Results from cross-sectional studies suggest that glucose fluctuations are associated with impairment of cognitive function among T2DM patients. Therefore, the aim of the longitudinal study described here is to evaluate the relationships between glucose fluctuation indexes assessed by continuous glucose monitoring (CGM) and cognitive function among elderly patients with T2DM.

METHODS

This will be a prospective, single-center, 2-year longitudinal study in which a total of 100 elderly patients with T2DM showing mild cognitive impairment (MCI) will be enrolled. Glucose fluctuations, assessed using the FreeStyle Libre Pro continuous glucose monitoring system (Abbott Laboratories), and results of cognitive tests, namely the Montreal Cognitive Assessment (MoCA) and Alzheimer's Disease Assessment Scale (ADAS), will be evaluated at baseline, 1-year visit and 2-year visit. The primary endpoint is the relationships between indexes of glucose fluctuation and change in MoCA and ADAS scores. Secondary endpoints are the relationships between the indexes of glucose fluctuation or cognitive scores and the following: indexes representing intracranial lesions obtained by magnetic resonance imaging and angiography of the head; Geriatric Depression Scale score; Apathy Scale score; carotid intima-media thickness assessed by echography; inflammatory markers; fasting glucose; glycated hemoglobin; blood pressure; and the development of cardiovascular and renal events.

PLANNED OUTCOMES

The current study is scheduled for completion in June 2022. The results could lead to the elucidation of novel glycemic goals to prevent the progression of cognitive impairment and/or of relationships between glucose fluctuations and cognitive function among T2DM patients. The findings of the study will be reported in publications and conference presentations.

TRIAL REGISTRATION

University Hospital Medical Information Network Clinical Trial Registry (UMIN000038546).

Common Brain Structural Alterations Associated with Cardiovascular Disease Risk Factors and Alzheimer's Dementia: Future Directions and Implications

Recent reports suggest declines in the age-specific risk of Alzheimer's dementia in higher income Western countries. At the same time, investigators believe that worldwide trends of increasing mid-life modifiable risk factors [e.g., cardiovascular disease (CVD) risk factors] coupled with the growth of the world's oldest age groups may nonetheless lead to an increase in Alzheimer's dementia. Thus, understanding the overlap in neuroanatomical profiles associated with CVD risk factors and AD may offer more relevant targets for investigating ways to reduce the growing dementia epidemic than current targets specific to isolated AD-related neuropathology. We hypothesized that a core group of common brain structural alterations exist between CVD risk factors and Alzheimer's dementia. Two co-authors conducted independent literature reviews in PubMed using search terms for CVD risk factor burden (separate searches for 'cardiovascular disease risk factors', 'hypertension', and 'Type 2 diabetes') and 'aging' or 'Alzheimer's dementia' with either 'grey matter volumes' or 'white matter'. Of studies that reported regionally localized results, we found support for our hypothesis, determining 23 regions commonly associated with both CVD risk factors and Alzheimer's dementia. Within this context, we outline future directions for research as well as larger cerebrovascular implications for these commonalities. Overall, this review supports previous as well as more recent calls for the consideration that both vascular and neurodegenerative factors contribute to the pathogenesis of dementia.

Cardiovascular Risk Factors: It's Time to Focus on Variability!

Atherosclerotic heart disease remains a leading cause of morbidity and mortality worldwide. While extensive research supports cardiovascular risk factor reduction in the form of achieving evidence-based blood pressure, lipid, glucose, and body weight targets as a means to improve cardiovascular outcomes, residual risk remains. Emerging data have demonstrated that the intraindividual variability of these risk factor targets potentially contribute to this residual risk. It may therefore be time to define risk factor by not only its magnitude and duration as done traditionally, but perhaps also by the variability of that particular risk factor over time.

Frontostriatal Brain Activation Is Associated With the Longitudinal Progression of Cardiometabolic Risk

OBJECTIVE

Cardiometabolic risk refers to a set of interconnected factors of vascular and metabolic origin associated with both cardiovascular disease and various brain disorders. Although midlife cardiometabolic risk is associated with future brain dysfunction, emerging evidence suggests that alterations in autonomic and central nervous system function may precede increases in cardiometabolic risk.

METHODS

The present study tested whether patterns of cerebral blood flow in brain areas associated with autonomic regulation were associated with increases in overall cardiometabolic risk. A community sample of 109 adults with resting systolic blood pressure between 120 and 139 mm Hg, diastolic blood pressure between 80 and 89 mm Hg, or both underwent pseudocontinuous arterial spin labeling to quantify cerebral blood flow responses to cognitively challenging tasks. Cardiometabolic risk and cerebral blood flow measurements were collected at baseline and at a 2-year follow-up.

RESULTS

Regression analyses showed that greater frontostriatal cerebral blood flow responses to cognitive challenge were associated with higher cardiometabolic risk at follow-up (β = 0.26 [95% confidence interval = 0.07 to 0.44], t = 2.81, p = .006, ΔR = 0.04). These findings were specific to frontostriatal brain regions, as frontoparietal, insular-subcortical, and total cerebral blood flow were not associated with progression of cardiometabolic risk. Moreover, cardiometabolic risk was not associated with frontostriatal cerebral blood flow responses 2 years later.

CONCLUSIONS

Frontostriatal brain function may precede and possibly forecast the progression of cardiometabolic risk.

Memory advancement by intranasal insulin in type 2 diabetes (MemAID) randomized controlled clinical trial: Design, methods and rationale

BACKGROUND

Type 2 diabetes mellitus (T2DM) accelerates brain aging and increases the risk for dementia. Insulin is a key neurotrophic factor in the brain, where it modulates energy metabolism, neurovascular coupling, and regeneration. Impaired insulin-mediated brain signaling and central insulin resistance may contribute to cognitive and functional decline in T2DM. Intranasal insulin (INI) has emerged as a potential therapy for treating T2DM-related cognitive impairment.

METHODS/DESIGN

Ongoing from 2015, a prospective, two-center, randomized, double-blind, placebo-controlled trial of 210 subjects (120 T2DM and 90 non-diabetic older adults) randomized into four treatment arms (60 T2DM-INI, 60 T2DM-Placebo, 45 Control-INI, and 45 Control-Placebo) evaluating the long-term effects of daily intranasal administration of 40 International Units (IU) of human insulin, as compared to placebo (sterile saline) over 24 weeks and 24 weeks of post-treatment follow-up. Study outcomes are: 1) long-term INI effects on cognition, daily functionality, and gait speed; 2) identifying a clinically relevant phenotype that predicts response to INI therapy; 3) long-term safety.

CONCLUSION

This study addresses an important knowledge gap about the long-term effects of intranasal insulin on memory and cognition in older people with T2DM and non-diabetic controls, and may provide a novel therapeutic target for prevention and treatment of cognitive and functional decline and dementia. Trial Registration NCT02415556.

Association between visit-to-visit variability of HbA1c and cognitive decline: a pooled analysis of two prospective population-based cohorts

AIMS/HYPOTHESIS

The aim of this study was to investigate the association between visit-to-visit variability in HbA1c and cognitive function decline in the elderly population.

METHODS

We performed a pooled analysis of two prospective population-based cohorts (the Health Retirement Study [HRS] and the English Longitudinal Study of Ageing [ELSA]). Cognitive function, including memory and executive function, were assessed at baseline and every 2 years, while HbA1c levels were assessed at baseline and every 4 years. Visit-to-visit variability (VVV) in HbA1c was calculated using the CV, SD and variation independent of the mean (VIM) during the follow-up period. Linear mixed models were used to evaluate the association between HbA1c variability and cognitive function decline with adjustment for demographics, mean HbA1c, education, smoking, alcohol consumption, BMI, baseline hypertension, baseline diabetes status and HDL-cholesterol.

RESULTS

The study enrolled 6237 participants (58.23% women, mean age 63.38 ± 8.62 years) with at least three measurements of HbA1c. The median follow-up duration was 10.56 ± 1.86 years. In the overall sample, compared with the lowest quartile of HbA1c variability, participants in the highest quartile of HbA1c variability had a significantly worse memory decline rate (-0.094 SD/year, 95% CI -0.185, -0.003) and executive function decline rate (-0.083 SD/year, 95% CI -0.125, -0.041), irrespective of mean HbA1c values over time. Among individuals without diabetes, each 1-SD increment in HbA1c CV was associated with a significantly higher rate of memory z score decline (-0.029, 95% CI -0.052, -0.005) and executive function z score decline (-0.049, 95% CI -0.079, -0.018) in the fully adjusted model.

CONCLUSIONS/INTERPRETATION

We observed a significant association between long-term HbA1c variability and cognitive decline among the non-diabetic population in this study. The effect of maintaining steady glucose control on the rate of cognitive decline merits further investigation.

Glucose Fluctuations Are Linked to Disrupted Brain Functional Architecture and Cognitive Impairment

BACKGROUND

Type 2 diabetes mellitus (T2DM) accelerates cognitive decline, which is believed to be triggered by aberrant neural activity.

OBJECTIVE

To explore how glucose fluctuations impact brain functional architecture and cognition in T2DM patients.

METHODS

T2DM patients were divided according to glycemic variability, forming two categories: patients with fluctuating glucose levels and patients with stable glucose levels. Degree centrality (DC) was calculated within the cerebral gray matter of each participant and was compared among the two patient groups and a healthy control group. The relationships between glucose fluctuations and aberrant DC and cognitive performance, as well as the relationship between aberrant DC and cognitive performance, were further explored.

RESULTS

Compared with T2DM patients with stable glucose levels, T2DM patients with fluctuating glucose levels exhibited significantly worse performance on the Montreal Cognitive Assessment, Trail Making Test-B (TMT-B), and verbal fluency test (VFT), as well as significant decreases in DC in certain regions, most of which were within the default mode network. In the combined T2DM group, the mean amplitude of glycemic excursions (MAGE) was positively correlated with TMT-B scores and negatively correlated with VFT scores. Moreover, the MAGE was negatively correlated with DC in the left medial prefrontal cortex (mPFC). In addition, TMT-B scores were negatively correlated with reduced DC in the left mPFC.

CONCLUSION

These findings further contribute to the mounting evidence of the effects of glycemic variability on the diabetic brain. Tightened control of glucose fluctuations might prevent cognitive decline and changes in brain functional architecture in T2DM individuals.

Molecular Mechanisms of Glucose Fluctuations on Diabetic Complications

Accumulating evidence indicates the occurrence and development of diabetic complications relates to not only constant high plasma glucose, but also glucose fluctuations which affect various kinds of molecular mechanisms in various target cells and tissues. In this review, we detail reactive oxygen species and their potentially damaging effects upon glucose fluctuations and resultant downstream regulation of protein signaling pathways, including protein kinase C, protein kinase B, nuclear factor-κB, and the mitogen-activated protein kinase signaling pathway. A deeper understanding of glucose-fluctuation-related molecular mechanisms in the development of diabetic complications may enable more potential target therapies in future.

Diabetes and the link between neuroplasticity and glutamate in the aging human motor cortex

OBJECTIVES

In older adults, type-2 diabetes mellitus (T2DM) impacts cognition and increases dementia risk. Prior studies suggest that impaired neuroplasticity may contribute to the cognitive decline in T2DM, but the underlying mechanisms of altered neuroplasticity are unclear. We investigated the relationship of the concentration of glutamatergic metabolites with measures of cortical plasticity in older adults across the spectrum of glucose intolerance/insulin resistance.

METHODS

Forty adults (50-87 years: 17-T2DM, 14-pre-diabetes, 9-controls) underwent magnetic resonance spectroscopy to quantify glutamate and other key metabolites within a 2 cm3 region around the hand knob of the left primary motor cortex. Thirty-six also underwent a separate transcranial magnetic stimulation (TMS) assessment of cortical excitability and plasticity using single-pulse TMS and intermittent theta-burst stimulation targeting the same brain region.

RESULTS

Group differences were observed in relative concentrations of glutamine (p = .028), glucose (p = .008), total cholines (p = .048), and the glutamine/glutamate ratio (p = .024). Cortical plasticity was reduced in both T2DM and pre-diabetes groups relative to controls (p-values < .05). Only the T2DM group showed a significant positive association between glutamate concentration and plasticity (r = .56, p = .030).

CONCLUSIONS

Neuroplastic mechanisms are already impaired in pre-diabetes. In T2DM, reduced cortico-motor plasticity is associated with lower cortical glutamate concentration.

SIGNIFICANCE

Impaired plasticity in T2DM is associated with low glutamatergic metabolite levels. The glutamatergic neurotransmission system constitutes a potential therapeutic target for cognitive problems linked to plasticity-related deficiencies in T2DM.

Cognitive Frailty in Older People with Type 2 Diabetes Mellitus: the Central Role of Hypoglycaemia and the Need for Prevention

PURPOSE OF REVIEW

To highlight the central role of hypoglycaemia in the causation of cognitive frailty and explore ways of recognition and prevention of hypoglycaemia.

RECENT FINDINGS

Cognitive frailty is an emerging new concept defined as the concomitant presence of physical frailty and cognitive impairment. In older people with diabetes, cognitive frailty is associated with an increased risk of mortality greater than from either physical frailty or cognitive impairment alone. Hypoglycaemia is directly associated with increased risk of cognitive impairment and physical frailty which are the two components of cognitive frailty. The incidence of hypoglycaemia in older people with diabetes is rising and hypoglycaemia-related hospitalisation has overtaken that of hyperglycaemia. Recognition of hypoglycaemic episodes in old age remains challenging which leads to misdiagnoses and under-reporting. Therefore, hypoglycaemia prevention strategies are needed. Research is still required to investigate whether prevention of hypoglycaemia would lead to a reduction in the incidence of cognitive frailty.

Acute glucose fluctuation impacts microglial activity, leading to inflammatory activation or self-degradation

Diabetes mellitus is associated with an increased risk of Alzheimer’s dementia and cognitive decline. The cause of neurodegeneration in chronic diabetic patients remains unclear. Changes in brain microglial activity due to glycemic fluctuations may be an etiological factor. Here, we examined the impact of acute ambient glucose fluctuations on BV-2 microglial activity. Biochemical parameters were assayed and showed that the shift from normal glucose (NG; 5.5 mM) to high glucose (HG; 25 mM) promoted cell growth and induced oxidative/inflammatory stress and microglial activation, as evidenced by increased MTT reduction, elevated pro-inflammatory factor secretion (i.e., TNF-α and oxygen free radicals), and upregulated expression of stress/inflammatory proteins (i.e., HSP70, HO-1, iNOS, and COX-2). Also, LPS-induced inflammation was enlarged by an NG-to-HG shift. In contrast, the HG-to-NG shift trapped microglia in a state of metabolic stress, which led to apoptosis and autophagy, as evidenced by decreased Bcl-2 and increased cleaved caspase-3, TUNEL staining, and LC3B-II expression. These stress episodes were primarily mediated through MAPKs, PI3K/Akt, and NF-κB cascades. Our study demonstrates that acute glucose fluctuation forms the stress that alters microglial activity (e.g., inflammatory activation or self-degradation), representing a novel pathogenic mechanism for the continued deterioration of neurological function in diabetic patients.

Glycemic Variability and Brain Glucose Levels in Type 1 Diabetes

The impact of glycemic variability on brain glucose transport kinetics among individuals with type 1 diabetes mellitus (T1DM) remains unclear. Fourteen individuals with T1DM (age 35 ± 4 years; BMI 26.0 ± 1.4 kg/m²; HbA_1c 7.6 ± 0.3) and nine healthy control participants (age 32 ± 4; BMI 23.1 ± 0.8; HbA_1c 5.0 ± 0.1) wore a continuous glucose monitor (Dexcom) to measure hypoglycemia, hyperglycemia, and glycemic variability for 5 days followed by ¹H MRS scanning in the occipital lobe to measure the change in intracerebral glucose levels during a 2-h glucose clamp (target glucose concentration 220 mg/dL). Hyperglycemic clamps were also performed in a rat model of T1DM to assess regional differences in brain glucose transport and metabolism. Despite a similar change in plasma glucose levels during the hyperglycemic clamp, individuals with T1DM had significantly smaller increments in intracerebral glucose levels (P = 0.0002). Moreover, among individuals with T1DM, the change in brain glucose correlated positively with the lability index (r = 0.67, P = 0.006). Consistent with findings in humans, streptozotocin-treated rats had lower brain glucose levels in the cortex, hippocampus, and striatum compared with control rats. These findings that glycemic variability is associated with brain glucose levels highlight the need for future studies to investigate the impact of glycemic variability on brain glucose kinetics.

What magnetic resonance imaging reveals - A systematic review of the relationship between type II diabetes and associated brain distortions of structure and cognitive functioning

Due to its increasing prevalence, Type 2 diabetes mellitus (T2DM) represents a major health challenge for modern society. Despite it being of fundamental interest, only a few MRI studies have conducted statistical analyses to draw scientifically valid conclusions about the complex interplay of T2DM and its associated clinical, structural, functional, metabolite, as well as cognitive distortions. Therefore, a systematic review of 68 manuscripts, following the PRISMA guidelines, was conducted. Notably, although the associations between imaging, clinical, and cognitive variables are not fully homogeneous, findings show a clear trend towards a link between altered brain structure and a decline in cognitive processing ability. The results of the review highlight the heterogeneity of the methods used across manuscripts in terms of assessed clinical variables, imaging, and data analysis methods. This is particularly significant as, if the subjects' criteria are not carefully considered, results are easily prone to confounding factors.

Lower cerebral vasoreactivity as a predictor of gait speed decline in type 2 diabetes mellitus

Gait speed is an indicator of overall functional health and is correlated with survival in older adults. We prospectively evaluated the long-term association between cerebral vasoreactivity and gait speed during normal walking (NW) and dual-task walking (DTW) in older adults with and without type 2 diabetes mellitus (T2DM). 40 participants (aged 67.3 ± 8.8 years, 20 with T2DM) completed a 2-year prospective study consisting of MRI, blood sampling, and gait assessments. The whole brain vasoreactivity was quantified using continuous arterial spin labeling MRI. Gait speed during DTW was assessed by subtracting serial sevens. Dual-task cost was calculated as the percent change in gait speed from NW to DTW. In the entire cohort, higher glycemic profiles were associated with a slower gait speed. In the diabetic group, lower vasoreactivity was associated with a slower gait speed during NW ([Formula: see text] = 0.30, p = 0.019) and DTW ([Formula: see text] = 0.35, p = 0.01) and a higher dual-task cost ([Formula: see text] = 0.69, p = 0.009) at 2-year follow-up. The participants with T2DM and lower cerebral vasoreactivity had a greater decrease in gait speed during NW and DTW after the 2-year follow-up ([Formula: see text] = 0.17, p = 0.04 and [Formula: see text] = 0.28, p = 0.03, respectively). Longer diabetes duration was associated with a higher dual-task cost ([Formula: see text] = 0.19, p = 0.04) and a greater decrease in gait speed during NW ([Formula: see text] = 0.17, p = 0.02). These findings indicate that in older adults with type 2 diabetes, gait performance is highly dependent on the integrity of cerebrovascular regulation.

Effects of glycemic variability and hyperglycemia in acute ischemic stroke on post-stroke cognitive impairments

AIMS

We aimed to investigate the effect of glycemic variability in the acute stage of stroke on the development of post-stroke cognitive impairment (PSCI).

METHODS

Patients who underwent blood glucose tests at least five times within 7 days after acute ischemic stroke were included. Factors related to glycemic variability (standard deviation (SD), coefficient of variance (CV), and mean absolute glucose (MAG)) were calculated; neuropsychological assessments were administered 3 months after stroke. PSCI was defined as a score of less than -2 SDs for age-, sex-, and education-adjusted means in at least one cognitive domain.

RESULTS

A total of 354 patients were enrolled. PSCI was identified in 74 (20.9%) subjects. In the diabetic group (n = 87), MAG was a significant predictor for PSCI (adjusted OR, 1.94; 95% CI, 1.11-3.42); however, it was not significant in the non-diabetic group, although PSCI exhibited an increasing tendency within higher SD and MAG tertiles. Moreover, hyperglycemia demonstrated a detrimental effect on PSCI, regardless of diabetes status; this effect did not appear in poorly-controlled diabetic patients with HbA1c ≥ 8.0%.

CONCLUSIONS

Glycemic variability and hyperglycemia during acute ischemic stroke were identified as novel predictors for PSCI. Although this result is not evidence of a causal relationship, our study suggests that monitoring glycemic index and controlling its variability during the acute phase of ischemic stroke may help to prevent poor cognitive outcomes.

Cortical thickness contributes to cognitive heterogeneity in patients with type 2 diabetes mellitus

The aim of this study was to investigate cerebral cortical thickness alterations in patients with type 2 diabetes mellitus (T2DM) and their association with mild cognitive impairment (MCI).Thirty T2DM patients without MCI, 30 T2DM patients with MCI, and 30 healthy controls were recruited. All subjects underwent high-resolution sagittal T1-weighted structural imaging using a 3-dimensional magnetization prepared rapid acquisition gradient echo (MPRAGE) sequence. The cortical thicknesses of the whole brain of the 3 groups were analyzed and compared using analysis of variance (ANOVA) test. Partial correlations between the cortical thicknesses of each brain region and standard laboratory testing data were analyzed for the T2DM without MCI group. The associations between cortical thicknesses and neuropsychological scale scores were also analyzed in the T2DM with MCI group.Compared with the healthy controls, the T2DM without MCI group showed statistically significant reduction in the cortical thickness of the left posterior cingulate gyrus, right isthmus cingulate gyrus, middle temporal gyrus, paracentral lobule, and transverse temporal gyrus. No significant correlation was found between the standard laboratory testing data and the cortical thicknesses of these cerebral regions. Compared with the T2DM without MCI group, the cortical thickness alterations in the T2DM with MCI group were bidirectional. Increased cortical thickness was found in the left parahippocampal gyrus and the right isthmus cingulate gyrus. Decreased cortical thickness was observed in the left pars triangularis and the right pars opercularis. Significant correlations were found between the cortical thickness of the right pars opercularis and the Complex Figure Test-delayed recall scores (r = 0.464, ρ = 0.015), Trail Making Test A consuming time (r = -0.454, ρ = 0.017), and Montreal Cognitive Assessment scores (r = 0.51, ρ = 0.007).T2DM could influence the gray matter of several brain regions. The cortical thickness reduction of the right pars opercularis may be a biomarker of cognitive impairment and play an important role in its pathophysiological mechanism.