Type 2 diabetes and cognitive dysfunction-towards effective management of both comorbidities

High expression of CNOT6L contributes to the negative development of type 2 diabetes

OBJECTIVE

Type 2 diabetes (T2D) is a chronic metabolic disorder characterized by reduced responsiveness of body cells to insulin, leading to elevated blood sugar levels. CNOT6L is involved in glucose metabolism, insulin secretion regulation, pancreatic beta-cell proliferation, and apoptosis. These functions may be closely related to the pathogenesis of T2D. However, the exact molecular mechanisms linking CNOT6L to T2D remain unclear. Therefore, this study aims to elucidate the role of CNOT6L in T2D.

METHODS

The T2D datasets GSE163980 and GSE26168 profiles were downloaded from the Gene Expression Omnibusdatabase generated by GPL20115 and GPL6883.The R package limma was used to screen differentially expressed genes (DEGs). A weighted gene co-expression network analysis was performed. Construction and analysis of the protein-protein interaction (PPI) network, functional enrichment analysis, gene set enrichment analysis, and comparative toxicogenomics database (CTD) analysis were performed. Target Scan was used to screen miRNAs that regulate central DEGs. The results were verified by reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR), western blotting (WB), and blood glucose measurements in mice.

RESULTS

A total of 1951 DEGs were identified. GO and KEGG enrichment analysis revealed that differentially expressed genes were mainly enriched in the insulin signaling pathway, ECM-receptor interaction, and PPAR signaling pathway. Metascape analysis indicated enrichment primarily in the cAMP signaling pathway and enzyme-linked receptor protein signaling pathway. WGCNA analysis yielded 50 intersecting genes. PPI network construction and algorithm identification identified two core genes (CNOT6L and GRIN2B), among which CNOT6L gene was associated with multiple miRNAs. CTD analysis revealed associations of core genes with type 2 diabetes, diabetic complications, dyslipidemia, hyperglycemia, and inflammation. WB and RT-qPCR results showed that in different pathways, CNOT6L protein and mRNA levels were upregulated in type 2 diabetes.

CONCLUSION

CNOT6L is highly expressed in type 2 diabetes mellitus, and can cause diabetes complications, inflammation and other physiological processes by regulating miRNA, PPAR and other related signaling pathways, with poor prognosis. CNOT6L can be used as a potential therapeutic target for type 2 diabetes.

Bioinformatics analysis of effective biomarkers and immune infiltration in type 2 diabetes with cognitive impairment and aging

With the increasing prevalence of diabetes mellitus worldwide, type 2 diabetes mellitus (T2D) combined with cognitive impairment and aging has become one of the common and important complications of diabetes mellitus, which seriously affects the quality of life of the patients, and imposes a heavy burden on the patients' families and the society. Currently, there are no special measures for the treatment of cognitive impairment and aging in type 2 diabetes mellitus. Therefore, the search for potential biological markers of type 2 diabetes mellitus combined with cognitive impairment and aging is of great significance for future precisive treatment. We downloaded three gene expression datasets from the GEO database: GSE161355 (related to T2D with cognitive impairment and aging), GSE122063, and GSE5281 (related to Alzheimer's disease). Differentially expressed genes (DEGs) were identified, followed by gene set enrichment analysis (GSEA). A protein-protein interaction (PPI) network was constructed using the STRING database, and the top 15 hub genes were identified using the CytoHubba plugin in Cytoscape. Core genes were ultimately determined using three machine learning methods: LASSO regression, Support Vector Machine Recursive Feature Elimination (SVM-RFE), and Linear Discriminant Analysis (LDA). The diagnostic performance of these genes was assessed using ROC curve analysis and validated in an independent dataset (GSE5281). Regulatory genes related to ferroptosis were screened from the FerrDb database, and their biological functions were further explored through GO and KEGG enrichment analyses. Finally, the CIBERSORT algorithm was used to analyze immune cell infiltration, and the correlation between core genes and immune cell infiltration levels was calculated, leading to the construction of an mRNA-miRNA regulatory network. In the GSE161355 and GSE122063 datasets, 217 common DEGs were identified. GSEA analysis revealed their enrichment in the PI3K-PLC-TRK signaling pathway, TP53 regulation of metabolic genes pathway, Notch signaling pathway, among others. PPI network analysis identified 15 candidate core genes, and further selection using LASSO, LDA, and SVM-RFE machine learning algorithms resulted in 6 core genes: BCL6, TP53, HSP90AA1, CRYAB, IL1B, and DNAJB1. ROC curve analysis indicated that these genes had good diagnostic performance in the GSE161355 dataset, with TP53 and IL1B achieving an AUC of 0.9, indicating the highest predictive accuracy. BCL6, HSP90AA1, CRYAB, and DNAJB1 also had AUCs greater than 0.8, demonstrating moderate predictive accuracy. Validation in the independent dataset GSE5281 showed that these core genes also had good diagnostic performance in Alzheimer's disease samples (AUC > 0.6). Ferroptosis-related analysis revealed that IL1B and TP53 play significant roles in apoptosis and immune response. Immune cell infiltration analysis showed that IL1B is significantly positively correlated with infiltration levels of monocytes and NK cells, while TP53 is significantly negatively correlated with infiltration levels of follicular helper T cells. The construction of the miRNA-mRNA regulatory network suggested that miR-150a-5p might play a key role in the regulation of T2D-associated cognitive impairment and aging by TP53. This study, by integrating bioinformatics and machine learning methods, identified BCL6, TP53, HSP90AA1, CRYAB, IL1B, and DNAJB1 as potential diagnostic biomarkers for T2D with cognitive impairment and aging, with a particular emphasis on the significance of TP53 and IL1B in immune cell infiltration. These findings not only enhance our understanding of the molecular mechanisms linking type 2 diabetes to cognitive impairment and aging, providing new targets for early diagnosis and treatment, but also offer new directions and targets for basic research.

Diabetes, Prediabetes, and Brain Aging: The Role of Healthy Lifestyle

OBJECTIVE

Diabetes is a well-known risk factor for dementia. We investigated the association between (pre)diabetes and older brain age and whether this can be attenuated by modifiable lifestyle behaviors.

RESEARCH DESIGN AND METHODS

The study included 31,229 dementia-free adults from the UK Biobank between the ages of 40 and 70 years. Glycemic status (normoglycemia, prediabetes, or diabetes) was ascertained based on medical history, medication use, and HbA1c measured at baseline. Information on cardiometabolic risk factors (obesity, hypertension, low HDL, and high triglycerides) and lifestyle behaviors (smoking, drinking, and physical activity) was also collected at baseline. Participants underwent up to two brain MRI scans over 11 years of follow-up. Brain age was estimated using a machine learning model based on 1,079 brain MRI phenotypes and used to calculate brain age gap (BAG; i.e., brain age minus chronological age).

RESULTS

At baseline, 13,518 participants (43.3%) had prediabetes and 1,149 (3.7%) had diabetes. Prediabetes (β = 0.22 [95% CI 0.10, 0.34]) and diabetes (2.01 [1.70, 2.32]) were both associated with significantly higher BAG, and diabetes was further associated with significant increase in BAG over time (0.27 [0.01, 0.53]). The association between (pre)diabetes and higher BAG was more pronounced in men and in people with two or more cardiometabolic risk factors. In joint exposure analysis, having a healthy lifestyle (i.e., no smoking, no heavy drinking, and high physical activity) significantly attenuated the diabetes-BAG association.

CONCLUSIONS

Diabetes and even prediabetes are associated with accelerated brain aging, especially among men and people with poor cardiometabolic health. However, a healthy lifestyle may counteract this.

Mechanistic Insights and Potential Therapeutic Implications of NRF2 in Diabetic Encephalopathy

Diabetic encephalopathy (DE) is a complication of diabetes, especially type 2 diabetes (T2D), characterized by damage in the central nervous system and cognitive impairment, which has gained global attention. Despite the extensive research aimed at enhancing our understanding of DE, the underlying mechanism of occurrence and development of DE has not been established. Mounting evidence has demonstrated a close correlation between DE and various factors, such as Alzheimer's disease-like pathological changes, insulin resistance, inflammation, and oxidative stress. Of interest, nuclear factor erythroid 2-related factor 2 (NRF2) is a transcription factor with antioxidant properties that is crucial in maintaining redox homeostasis and regulating inflammatory responses. The activation and regulatory mechanisms of NRF2 are a relatively complex process. NRF2 is involved in the regulation of multiple metabolic pathways and confers neuroprotective functions. Multiple studies have provided evidence demonstrating the significant involvement of NRF2 as a critical transcription factor in the progression of DE. Additionally, various molecules capable of activating NRF2 expression have shown potential in ameliorating DE. Therefore, it is intriguing to consider NRF2 as a potential target for the treatment of DE. In this review, we aim to shed light on the role and the possible underlying mechanism of NRF2 in DE. Furthermore, we provide an overview of the current research landscape and address the challenges associated with using NRF2 activators as potential treatment options for DE.

The use of technology in type 2 diabetes and prediabetes: a narrative review

The increasing incidence of type 2 diabetes, which represents 90% of diabetes cases globally, is a major public health concern. Improved glucose management reduces the risk of vascular complications and mortality; however, only a small proportion of the type 2 diabetes population have blood glucose levels within the recommended treatment targets. In recent years, diabetes technologies have revolutionised the care of people with type 1 diabetes, and it is becoming increasingly evident that people with type 2 diabetes can also benefit from these advances. In this review, we describe the current knowledge regarding the role of technologies for people living with type 2 diabetes and the evidence supporting their use in clinical practice. We conclude that continuous glucose monitoring systems deliver glycaemic benefits for individuals with type 2 diabetes, whether treated with insulin or non-insulin therapy; further data are required to evaluate the role of these systems in those with prediabetes (defined as impaired glucose tolerance and/or impaired fasting glucose and/or HbA1c levels between 39 mmol/mol [5.7%] and 47 mmol/mol [6.4%]). The use of insulin pumps seems to be safe and effective in people with type 2 diabetes, especially in those with an HbA1c significantly above target. Initial results from studies exploring the impact of closed-loop systems in type 2 diabetes are promising. We discuss directions for future research to fully understand the potential benefits of integrating evidence-based technology into care for people living with type 2 diabetes and prediabetes.

Alterations in Neuronal Nicotinic Acetylcholine Receptors in the Pathogenesis of Various Cognitive Impairments

Cognitive impairment is a typical symptom of both neurodegenerative and certain other diseases. In connection with these different pathologies, the etiology and neurological and metabolic changes associated with cognitive impairment must differ. Until these characteristics and differences are understood in greater detail, pharmacological treatment of the different forms of cognitive impairment remains suboptimal. Neurotransmitter receptors, including neuronal nicotinic acetylcholine receptors (nAChRs), dopamine receptors, and glutamine receptors, play key roles in the functions and metabolisms of the brain. Among these, the role of nAChRs in the development of cognitive impairment has attracted more and more attention. The present review summarizes what is presently known concerning the structure, distribution, metabolism, and function of nAChRs, as well as their involvement in major cognitive disorders such as Alzheimer's disease, Parkinson's disease, vascular dementia, schizophrenia, and diabetes mellitus. As will be discussed, the relevant scientific literature reveals clearly that the α4β2 and α7 nAChR subtypes and/or subunits of the receptors play major roles in maintaining cognitive function and in neuroprotection of the brain. Accordingly, focusing on these as targets of drug therapy can be expected to lead to breakthroughs in the treatment of cognitive disorders such as AD and schizophrenia.

Associations of Cognitive Impairment with All-Cause and Cardiovascular Mortality Among Individuals with Diabetes: A Prospective Cohort Study

This study explored the association between diabetes, cognitive imFpairment (CI), and mortality in a cohort of 2931 individuals aged 60 and above from the 2011 to 2014 NHANES. Mortality data was gathered through 2019, and multivariable Cox proportional hazards models were used to determine the association between diabetes, CI, and mortality adjusting for sociodemographic characteristics, lifestyle factors, and comorbidity conditions. The study spanned up to 9.17 years, observing 579 deaths, with individuals having both diabetes and CI showing the highest all-cause mortality (23.6 events per 100 patient-years). Adjusted analysis revealed a 2.34-fold higher risk of all-cause mortality for this group, surpassing those with diabetes or CI alone. These results held after a series of stratified and sensitivity analyses. In conclusion, CI was linked to higher all-cause mortality in individuals with diabetes, emphasizing the need to address cognitive dysfunction in diabetic patients.

Microglial activation and polarization in type 2 diabetes-related cognitive impairment: A focused review of pathogenesis

Microglia, as immune cells in the central nervous system, are closely related to cognitive impairment associated with type 2 diabetes (T2D). Preliminary explorations have investigated the relationship between T2D-related cognitive impairment and the activation and polarization of microglia. This review summarizes the potential mechanisms of microglial activation and polarization in the context of T2D. It discusses central inflammatory responses, neuronal apoptosis, amyloid-β deposition, and abnormal phosphorylation of Tau protein mediated by microglial activation and polarization, exploring the connections between microglial activation and polarization and T2D-related cognitive impairment from multiple perspectives. Additionally, this review provides references for future treatment targeting microglia in T2D-related cognitive impairment and for clinical translation.

Identification of common biomarkers in diabetic kidney disease and cognitive dysfunction using machine learning algorithms

Cognitive dysfunction caused by diabetes has become a serious global medical issue. Diabetic kidney disease (DKD) exacerbates cognitive dysfunction in patients, although the precise mechanism behind this remains unclear. Here, we conducted an investigation using RNA sequencing data from the Gene Expression Omnibus (GEO) database. We analyzed the differentially expressed genes in DKD and three types of neurons in the temporal cortex (TC) of diabetic patients with cognitive dysfunction. Through our analysis, we identified a total of 133 differentially expressed genes (DEGs) shared between DKD and TC neurons (62 up-regulated and 71 down-regulated). To identify potential common biomarkers, we employed machine learning algorithms (LASSO and SVM-RFE) and Venn diagram analysis. Ultimately, we identified 8 overlapping marker genes (ZNF564, VPS11, YPEL4, VWA5B1, A2ML1, KRT6A, SEC14L1P1, SH3RF1) as potential biomarkers, which exhibited high sensitivity and specificity in ROC curve analysis. Functional analysis using Gene Ontology (GO) revealed that these genes were primarily enriched in autophagy, ubiquitin/ubiquitin-like protein ligase activity, MAP-kinase scaffold activity, and syntaxin binding. Further enrichment analysis using Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) indicates that these biomarkers may play a crucial role in the development of cognitive dysfunction and diabetic nephropathy. Building upon these biomarkers, we developed a diagnostic model with a reliable predictive ability for DKD complicated by cognitive dysfunction. To validate the 8 biomarkers, we conducted RT-PCR analysis in the cortex, hippocampus and kidney of animal models. The results demonstrated the up-regulation of SH3RF1 in the cortex, hippocampus and kidney of mice, which was further confirmed by immunofluorescence and Western blot validation. Notably, SH3RF1 is a scaffold protein involved in cell survival in the JNK signaling pathway. Based on these findings, we support that SH3RF1 may be a common gene expression feature that influences DKD and cognitive dysfunction through the apoptotic pathway.

The application and clinical translation of the self-evolving machine learning methods in predicting diabetic retinopathy and visualizing clinical transformation

Objective

This study aims to analyze the application and clinical translation value of the self-evolving machine learning methods in predicting diabetic retinopathy and visualizing clinical outcomes.

Methods

A retrospective study was conducted on 300 diabetic patients admitted to our hospital between January 2022 and October 2023. The patients were divided into a diabetic retinopathy group (n=150) and a non-diabetic retinopathy group (n=150). The improved Beetle Antennae Search (IBAS) was used for hyperparameter optimization in machine learning, and a self-evolving machine learning model based on XGBoost was developed. Value analysis was performed on the predictive features for diabetic retinopathy selected through multifactor logistic regression analysis, followed by the construction of a visualization system to calculate the risk of diabetic retinopathy occurrence.

Results

Multifactor logistic regression analysis revealed that being male, having a longer disease duration, higher systolic blood pressure, fasting blood glucose, glycosylated hemoglobin, low-density lipoprotein cholesterol, and urine albumin-to-creatinine ratio were risk factors for the development of diabetic retinopathy, while non-pharmacological treatment was a protective factor. The self-evolving machine learning model demonstrated significant performance advantages in early diagnosis and prediction of diabetic retinopathy occurrence.

Conclusion

The application of the self-evolving machine learning models can assist in identifying features associated with diabetic retinopathy in clinical settings, enabling early prediction of disease occurrence and aiding in the formulation of treatment plans to improve patient prognosis.

The association of the comorbidity status of metabolic syndrome and cognitive dysfunction with health-related quality of life

PURPOSE

Both metabolic syndrome (MetS) and cognitive dysfunction impair health-related quality of life (HRQOL). This study aims to determine whether individuals experiencing both MetS and cognitive dysfunction have lower HRQOL.

METHODS

This cross-sectional study enrolled 567 participants who attended outpatient clinics at a medical center in northern Taiwan. MetS was diagnosed according to the modified criteria for the Asian population. Cognitive function was categorized as normal, mild cognitive dysfunction, and advanced cognitive dysfunction according to the score of the Montreal Cognitive Assessment, Taiwanese version. HRQOL was assessed using the SF-36v2® Health Survey (SF-36v2). The associations of the comorbidity status of MetS and cognitive dysfunction with HRQOL were analyzed using linear regression models, adjusting for age, sex, marital status, education level, income groups, and activities of daily living.

RESULTS

Out of 567 participants, 33 (5.8%) had MetS with mild cognitive dysfunction, and 34 (6.0%) had MetS with advanced cognitive dysfunction. Participants with both MetS and advanced cognitive dysfunction exhibited the lowest scores in the physical component summary and almost all scales of HRQOL. MetS exacerbated the inverse association between mild cognitive dysfunction and the mental component summary. For those with MetS, the scores on scales of role physical, bodily pain, vitality, and social functioning worsened as cognitive function deteriorated (all Ptrend<0.05).

CONCLUSION

As the severity of comorbidity between MetS and cognitive dysfunction varies, patients exhibited poorer performance in different aspects of HRQOL. Future research is needed to find solutions to improve HRQOL for patients with both MetS and cognitive dysfunction.

Phlorizin ameliorates cognitive and behavioral impairments via the microbiota-gut-brain axis in high-fat and high-fructose diet-induced obese male mice

The long-term high-fat, high-sugar diet exacerbates type 2 diabetes mellitus (T2DM)-related cognitive impairments. Phlorizin, a well-studied natural compound found in apples and other plants, is recognized for its bioactive properties, including modulation of glucose and lipid metabolism. Despite its established role in mitigating metabolic disorders, the neuroprotective effects of phlorizin, particularly against diabetes-related cognitive dysfunction, have not been fully elucidated. Therefore, the present study aimed to investigate the effect of dietary supplementation of phlorizin on high-fat and high-fructose diet (HFFD)-induced cognitive dysfunction and evaluate the crucial role of the microbiota-gut-brain axis. We found that dietary supplementation of phlorizin for 14 weeks effectively prevented glucolipid metabolism disorder, spatial learning impairment, and memory impairment in HFFD mice. In addition, phlorizin improved the HFFD-induced decrease in synaptic plasticity, neuroinflammation, and excessive activation of microglia in the hippocampus. Transcriptomics analysis shows that the protective effect of phlorizin on cognitive impairment was associated with increased expression of neurotransmitters and synapse-related genes in the hippocampus. Phlorizin treatment alleviated colon microbiota disturbance, mainly manifested by an increase in gut microbiota diversity and the abundance of short-chain fatty acid (SCFA)-producing bacteria. The level of microbial metabolites, including SCFA, inosine 5'-monophosphate (IMP), and D (-)-beta-hydroxybutyric acid (BHB) were also significantly increased after phlorizin treatment. Integrating multiomics analysis observed tight connections between phlorizin-regulated genes, microbiota, and metabolites. Furthermore, removal of the gut microbiota via antibiotics treatment diminished the protective effect of phlorizin against HFFD-induced cognitive impairment, underscoring the critical role of the gut microbiota in mediating cognitive behavior. Importantly, supplementation with SCFA and BHB alone mimicked the regulatory effects of phlorizin on cognitive function. Therefore, phlorizin shows promise as a potential nutritional therapy for addressing cognitive impairment associated with metabolic disorders. Further research is needed to explore its effectiveness in preventing and alleviating neurodegenerative diseases.

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.

Navigating the intersection: Diabetes and Alzheimer's intertwined relationship

Alzheimer's disease (AD) and Diabetes mellitus (DM) exhibit comparable pathophysiological pathways. Genetic abnormalities in APP, PS-1, and PS-2 are linked to AD, with diagnostic aid from CSF and blood biomarkers. Insulin dysfunction, termed "type 3 diabetes mellitus" in AD, involves altered insulin signalling and neuronal shrinkage. Insulin influences beta-amyloid metabolism, exacerbating neurotoxicity in AD and amyloid production in DM. Both disorders display impaired glucose transporter expression, hastening cognitive decline. Mitochondrial dysfunction and Toll-like receptor 4-mediated inflammation worsen neurodegeneration in both diseases. ApoE4 raises disease risk, especially when coupled with dyslipidemia common in DM. Targeting shared pathways like insulin-degrading enzyme activation and HSP60 holds promise for therapeutic intervention. Recognizing these interconnected mechanisms underscores the imperative for developing tailored treatments addressing the overlapping pathophysiology of AD and DM, offering potential avenues for more effective management of both conditions.

Prevalence of mild cognitive impairment and modifiable risk factors: A cross-sectional study in rural older adults with diabetes

To determine the prevalence and modifiable risk factors for MCI in older adults with T2DM in rural China. This cross-sectional study encompassed 96 villages, employing a cluster sampling approach to recruit eligible older adults with T2DM as study participants. Logistic regression analysis was utilized to identify modifiable risk factors associated with MCI. Average marginal effects were calculated. The discriminatory performance of these risk factors in identifying MCI was evaluated by plotting the receiver operating curve and calculating the value of the area under the curve. A total of 898 older adults with T2DM in our study. The overall prevalence of MCI was 50.22 %. Independent associations with MCI were found in poor self-management ability of diabetes (OR = 0.808, 95 % CI: 0.808, 0.766), depressive symptoms (OR = 3.500, 95 % CI: 1.933, 6.337), moderate (OR = 0.936, 95 % CI: 0.017, 0.075) and high (OR = 0.939, 95 % CI: 0.016, 0.100) levels of physical activity, poorer oral health (OR = 2.660, 95 % CI: 2.226, 3.179), and lower grip strength (OR = 0.913, 95 % CI: 0.870, 0.958). The AUC was 0.967 (95 % CI 0.508-0.470). The prevalence of MCI was high among older adults with T2DM in rural areas of China. The self-management ability of diabetes, depressive symptoms, physical activity, oral health and grip strength were modifiable risk factors of MCI. Targeted interventions should be developed and implemented to address these modifiable risk factors, aiming to enhance cognitive function and mitigate the incidence of MCI in older adults with T2DM.

Daphnetin modulates GLP-1R to alleviate cognitive dysfunction in diabetes: implications for inflammation and oxidative stress

Daphnetin exerts certain pharmacological function on a variety of diseases, but its role in diabetic cognitive dysfunction has not been elucidated. In this study, we carried a series of pharmacological studies of GLP-1R with daphnetin. In rats and PC12 cells, we found that daphnetin could alleviate diabetic cognitive dysfunction and increase the expression level of GLP-1R. Additionally, the anti-diabetic cognitive dysfunction effect of DAP was accompanied by the inhibition of inflammation and oxidative stress. Further in-depth studies demonstrated that the inhibition GLP-1R enhanced the protective effect of daphnetin, whilst, the overexpression of GLP-1R weakened the protective effect of daphnetin. These results indicated that daphnetin protects diabetes cognitive dysfunction by regulating GLP-1R-mediated inflammation and oxidative stress, act as a GLP-1R agonist. The study further demonstrated that daphnetin has great value in preventing cognitive dysfunction in type 2 diabetes, and GLP-1R is a key potential target for the treatment of related diseases.

Analysis of current situation and influencing factors of cognitive dysfunction associated with type 2 diabetes and follow-up study on treatment effectiveness

Background

Many studies have explored the risk factors associated with cognitive impairment in patients with Type 2 diabetes mellitus (T2DM). However, research on determining the optimal threshold for these risk factors and comparative studies on the therapeutic effects of insulin and metformin is limited. This study aims to establish the optimal threshold for cognitive impairment risk factors in T2DM patients and compare the efficacy of insulin and metformin in treating mild cognitive impairment (MCI).

Methods

A total of 308 patients with T2DM were included. The optimal threshold for cognitive impairment risk factors was determined using receiver operating characteristic curve and binary logistic regression models. MCI patients were divided into three groups: insulin, metformin, and insulin with metformin. The treatment effect was evaluated after a 6-month follow-up.

Results

The study identified several factors that influenced cognitive function in T2DM patients, including female gender, duration of diabetes >13.50 years, years of education >7.50 years, and serum sodium level > 141.90 mmol/L. Metformin and insulin with metformin showed superior therapeutic effects compared to insulin alone, but no difference was observed between metformin and combination therapy.

Conclusion

Special attention should be given to female and those with diabetes duration >13.50 years, as well as to individuals with educational level ≤ 7.50 years and serum sodium concentration ≤ 141.90 mmol/L. Metformin and insulin with metformin effectively improve MCI in patients with T2DM and outperform insulin monotherapy. The efficacy of metformin and combination therapy was found to be comparable.

Should dietary restrictions be imposed on Alzheimer's Disease patients affected by type 2 diabetes?

INTRODUCTION

Antidiabetic drugs, reduction of carbohydrates intake, maintaining normal weight and physical activity are the cornerstone of diabetes 2 treatment.

METHODS

This opinion article is not intended to challenge hundreds of studies unequivocally demonstrating the benefits of a healthy lifestyle including appropriate diet in controlling the consequences of T2DM. The article questions whether the benefits of dietary restrictions for the management of T2D in older adults who are already demented, are worth the potential detrimental effects on quality of life for the patients and their caregivers, as well as the effects of dietary restrictions on frailty, sarcopenia.

DISCUSSION

However, the benefit of dietary restrictions including carbohydrates restrictions, might not manifest in elderly Alzheimer and vascular dementia patients with type 2 diabetes. On the contrary, such restrictions might hinder the patients' and caregiver's quality of life and encumber attempts to maintain normal weight in a population which tends to be underweight. Therefore, the benefit/risk ratio of dietary restriction should be weighed in this population on an individual basis.

Irisin alleviates the pyroptosis of β cells in T2DM by inhibiting NLRP3 inflammasome through regulating miR-19b-3p/SOCS3/STAT3 axis mediated autophagy

The purpose of this study was to analyze the mechanism by which irisin affects β-cell pyroptosis in type 2 diabetes mellitus (T2DM). The in vivo T2DM model was established by raised with high-fat diet and intraperitoneally injection of streptozocin. Min6 cells were divided into four groups: negative control (NC), high glucose (HG), HG + irisin, and HG + irisin+3-MA. The cell viability was determined by CCK-8 assay. Dual-luciferase gene reporter assay was conducted to confirm the binding between miR-19b-3p and SOCS3. The expression level of FNDC5 and GSDMD was visualized using the immunofluorescence assay. The protein level of FNDC5, Beclin1, LC3II/I, NLRP3, cleaved-caspase-1, GSDMD-N, STAT3, p-STAT3, and SOCS3 was determined by Western blotting. The secretion of irisin, lactate dehydrogenase (LDH), and insulin was checked by ELISA. In vivo results showed that pathological changes in islet tissues with declined number of β cells, elevated FBG value, decreased FIN and HOMA-β value, elevated autophagy-associated proteins expressions, and activated NLRP3 signaling in T2DM mice, which were dramatically reversed by FNDC5 overexpression. Furthermore, the declined level of miR-19b-3p and p-STAT3, as well as the upregulation of SOCS3, was greatly rescued by FNDC5 overexpression. The in vitro data confirmed the binding site between SOCS3 and miR-19b-3p. SOCS3 was downregulated and p-STAT3 was upregulated in miR-19b-3p mimic-treated Min6 cells. In HG-stimulated Min6 cells, the elevated cell viability, increased production of insulin, decreased release of LDH, and inactivated NLRP3 signaling induced by irisin were abolished by miR-19b-3p inhibitor and STAT3 inhibitor. The increased level of autophagy-related proteins and activated SOCS3/STAT3 axis induced by irisin in HG-stimulated Min6 cells were abolished by miR-19b-3p inhibitor. The inhibitory effect of irisin against NLRP3 signaling in HG-stimulated Min6 cells was abrogated by 3-MA. In conclusion, irisin alleviated the pyroptosis of β cells in T2DM by inhibiting NLRP3 signaling through miR-19b-3p/SOCS3/STAT3 axis mediated autophagy.

Beneficial Effects of Echinacoside on Cognitive Impairment and Diabetes in Type 2 Diabetic db/db Mice

INTRODUCTION

Cognitive dysfunction is an important comorbidity of diabetes. Insulin resistance may play a critical role in diabetes-related cognitive impairment. Echinacoside (ECH), a natural phenylethanoid glycoside, is the active component of anti-diabetes prescriptions in traditional Chinese medicine. Its effect on modulating insulin resistance has been confirmed but modulating neurodegenerative disease remains unclear.

METHODS

Db/db mice, a spontaneous type 2 diabetes mode, were intragastrically administered ECH by 300 mg/kg or an equivalent volume of saline. Weight, blood glucose, and insulin resistance index were measured. Morris water maze test was performed to observe the compound effects on cognition. Hippocampal lesions were observed by histochemical analysis.

RESULTS

In db/db mice, ECH alleviated diabetes symptoms, memory loss, and hippocampal neuronal damage. Next, the expression of CD44 and phosphorylated tau was upregulated in diabetic mice. In addition, the insulin receptor substrate-1/phosphatidylinositol 3-kinase /protein kinase B signaling pathway was dysregulated in diabetic mice. All these dysregulations could be reversed by ECH.

DISCUSSION

This study provides theoretical support and experimental evidence for the future application of ECH in diabetic cognition dysfunction treatment, promoting the development of traditional medicines.

Anti-Inflammatory Diet and Dementia in Older Adults With Cardiometabolic Diseases

Importance

Inflammation has been proposed as a mechanism linking cardiometabolic diseases (CMDs) to increased risk of dementia. However, whether an anti-inflammatory diet can support brain and cognitive health among people with CMDs is unclear.

Objective

To examine CMD status and dietary inflammatory potential in association with dementia risk and brain magnetic resonance imaging (MRI) measures using joint effect analysis.

Design, Setting, and Participants

The UK Biobank is an ongoing community-based cohort study with baseline assessments conducted between March 13, 2006, and October 1, 2010. The present study included 84 342 dementia-free older adults (≥60 years), who were followed up until January 20, 2022 (maximum, 15 years). A subsample (n = 8917) underwent brain MRI scans between May 2, 2014, and March 13, 2020.

Exposures

Baseline CMDs (including type 2 diabetes, heart disease, and stroke) were ascertained from medical records. Dietary Inflammatory Index scores (anti-inflammatory [≤-1.5 points], neutral [>-1.5 to <0.5 points], or proinflammatory [≥0.5 points]) were calculated from participants' average intake of 31 nutrients, assessed up to 5 times using the Oxford WebQ, a web-based, 24-hour dietary assessment.

Main Outcomes and Measures

Incident dementia was identified through linkage to medical records. Regional brain volumes were collected from brain MRI scans.

Results

The study included 84 342 participants (mean [SD] age, 64.1 [2.9] years; 43 220 [51.2%] female). At baseline, 14 079 (16.7%) had at least 1 CMD. Over a median follow-up of 12.4 (IQR, 11.8-13.1) years, 1559 individuals (1.9%) developed dementia. With the use of joint effect analysis, the hazard ratio of dementia was 2.38 (95% CI, 1.93-2.93) for people with CMDs and a proinflammatory diet and 1.65 (95% CI, 1.36-2.00) for those with CMDs and an anti-inflammatory diet (reference: CMD-free, anti-inflammatory diet). Dementia risk was 31% lower (hazard ratio, 0.69; 95% CI, 0.55-0.88; P = .003) among people with CMDs and an anti-inflammatory diet. On brain MRI, participants with CMDs and an anti-inflammatory diet compared with a proinflammatory diet additionally had significantly larger gray matter volume (β = -0.15; 95% CI, -0.24 to -0.06 vs β = -0.27; 95% CI, -0.38 to -0.16) and smaller white matter hyperintensity volume (β = 0.05; 95% CI, -0.04 to 0.14 vs β = 0.16; 95% CI, 0.05-0.27).

Conclusions and Relevance

In this cohort study, people with CMDs and an anti-inflammatory compared with proinflammatory diet had a significantly lower hazard ratio of dementia, larger gray matter volume, and smaller white matter hyperintensity volume.

HbA1c variability associated with dementia risk in people with type 2 diabetes

INTRODUCTION

Although poor glycemic control is associated with dementia, it is unknown if variability in glycemic control, even in those with optimal glycosylated hemoglobin A1c (HbA1c) levels, increases dementia risk.

METHODS

Among 171,964 people with type 2 diabetes, we evaluated the hazard of dementia association with long-term HbA1c variability using five operationalizations, including standard deviation (SD), adjusting for demographics and comorbidities.

RESULTS

The mean baseline age was 61 years (48% women). Greater HbA1c SD was associated with greater dementia hazard (adjusted hazard ratio = 1.15 [95% confidence interval: 1.12, 1.17]). In stratified analyses, higher HbA1c SD quintiles were associated with greater dementia hazard among those with a mean HbA1c < 6% (P = 0.0004) or 6% to 8% (P < 0.0001) but not among those with mean HbA1c ≥ 8% (P = 0.42).

DISCUSSION

Greater HbA1c variability is associated with greater dementia risk, even among those with HbA1c concentrations at ideal clinical targets. These findings add to the importance and clinical impact of recommendations to minimize glycemic variability.

HIGHLIGHTS

We observed a cohort of 171,964 people with type 2 diabetes (mean age 61 years). This cohort was based in Northern California between 1996 and 2018. We examined the association between glycosylated hemoglobin A1c (HbA1c) variability and dementia risk. Greater HbA1c variability was associated with greater dementia hazard. This was most evident among those with normal-low mean HbA1c concentrations.

Leptin receptor reactivation restores brain function in early-life Lepr-deficient mice

Obesity is a chronic disease caused by excessive fat accumulation that impacts the body and brain health. Insufficient leptin or leptin receptor (LepR) is involved in the disease pathogenesis. Leptin is involved with several neurological processes, and it has crucial developmental roles. We have previously demonstrated that leptin deficiency in early life leads to permanent developmental problems in young adult mice, including an imbalance in energy homeostasis, alterations in melanocortin and the reproductive system and a reduction in brain mass. Given that in humans, obesity has been associated with brain atrophy and cognitive impairment, it is important to determine the long-term consequences of early-life leptin deficiency on brain structure and memory function. Here, we demonstrate that leptin-deficient (LepOb) mice exhibit altered brain volume, decreased neurogenesis and memory impairment. Similar effects were observed in animals that do not express the LepR (LepRNull). Interestingly, restoring the expression of LepR in 10-week-old mice reverses brain atrophy, in addition to neurogenesis and memory impairments in older animals. Our findings indicate that leptin deficiency impairs brain development and memory, which are reversible by restoring leptin signalling in adulthood.

AdipoRon Ameliorates Synaptic Dysfunction and Inhibits tau Hyperphosphorylation through the AdipoR/AMPK/mTOR Pathway in T2DM Mice

There is growing evidence showing that adiponectin (APN) can improve Alzheimer's disease(AD)-like pathological changes by improving insulin resistance. However, the role of AdipoRon (an Adiponectin receptor agonist) on synaptic plasticity and cognitive dysfunction in the early stages of type 2 diabetes mellitus(T2DM) remains unknown. In this study, we investigated the neuroprotective effect and the molecular mechanism underlying the effect of AdipoRon in T2DM mice. We found that AdipoRon significantly restored the cognitive deficits in T2DM mice, including shorter escape latency, more crossing times, increased distances, and percentage of time in the target quadrant. In addition, AdipoRon treatment up-regulated synaptic proteins (PSD95, SYN, GAP43, and SYP), increased the number of hippocampal synapses and attenuated synaptic damage, including the length, the number and the density of dendritic spines in CA1 and DG regions. Furthermore, AdipoRon attenuated Tau phosphorylation at multiple AD-related sites (p-tau 205, p-tau 396, p-tau 404) by promoting AdipoR expression and activating the AMPK/mTOR pathway. Our data suggests that AdipoRon exerts neuroprotective effects on the T2DM mice, which may be mediated by the activation of the AdipoR/AMPK/mTOR signaling pathway.

A High-Carbohydrate Diet Induces Cognitive Impairment and Promotes Amyloid Burden and Tau Phosphorylation via PI3K/Akt/GSK-3β Pathway in db/db Mice

BACKGROUND

Cognitive impairment is a prevalent complication of type 2 diabetes, influenced significantly by various dietary patterns. High-carbohydrate diets (HCDs) are commonly consumed nowadays; however, the specific impact of HCDs on cognitive function in diabetes remains unclear.

METHODS

The objective of this study was to investigate whether an HCD has effects on cognition in diabetes. Eight-week-old diabetic (db/db) mice and wild-type (WT) mice underwent a twelve-week dietary intervention, including a normal diet (ND), an HCD, or a high-fat diet (HFD). Following this, behavioral tests were conducted, and related hippocampal pathology was evaluated.

RESULTS

Our results demonstrated that an HCD exacerbated cognitive decline in db/db mice compared to an ND. Additionally, an HCD increased amyloid-β burden and expression of β-site APP cleaving enzyme-1. An HCD was also found to promote the phosphorylation of tau protein via the PI3K/Akt/GSK-3β pathway. Furthermore, an HCD markedly induced neuroinflammation and increased the quantity of microglia and astrocytes. However, these damages induced by an HCD were less severe than those caused by an HFD.

CONCLUSIONS

Collectively, our findings indicate that a high intake of carbohydrates can have an adverse impact on cognitive function in diabetes.

Microglial AKAP8L: a key mediator in diabetes-associated cognitive impairment via autophagy inhibition and neuroinflammation triggering

BACKGROUND

Diabetes-associated cognitive impairment (DACI) poses a significant challenge to the self-management of diabetes, markedly elevating the risk of adverse complications. A burgeoning body of evidence implicates microglia as a central player in the pathogenesis of DACI.

METHODS

We utilized proteomics to identify potential biomarkers in high glucose (HG)-treated microglia, followed by gene knockdown techniques for mechanistic validation in vitro and in vivo.

RESULTS

Our proteomic analysis identified a significant upregulation of AKAP8L in HG-treated microglia, with concurrent dysregulation of autophagy and inflammation markers, making AKAP8L a novel biomarker of interest. Notably, the accumulation of AKAP8L was specific to HG-treated microglia, with no observed changes in co-cultured astrocytes or neurons, a pattern that was mirrored in streptozotocin (STZ)-induced diabetic mice. Further studies through co-immunoprecipitation and proximity ligation assay indicated that the elevated AKAP8L in HG-treated microglial cells interacts with the mTORC1. In the STZ mouse model, we demonstrated that both AKAP8L knockdown and rapamycin treatment significantly enhanced cognitive function, as evidenced by improved performance in the Morris water maze, and reduced microglial activation. Moreover, these interventions effectively suppressed mTORC1 signaling, normalized autophagic flux, mitigated neuroinflammation, and decreased pyroptosis.

CONCLUSIONS

Our findings highlight the critical role of AKAP8L in the development of DACI. By interacting with mTORC1, AKAP8L appears to obstruct autophagic processes and initiate a cascade of neuroinflammatory responses. The identification of AKAP8L as a key mediator in DACI opens up new avenues for potential therapeutic interventions.

Dilemmas in Elderly Diabetes and Clinical Practice Involving Traditional Chinese Medicine

Diabetes is a widespread chronic disease that occurs mainly in the elderly population. Due to the difference in pathophysiology between elderly and young patients, the current clinical practice to treat elderly patients with anti-diabetes medications still faces some challenges and dilemmas, such as the urgent need for early diagnosis and prevention, and an imbalance between restricted dietary intake and the risk of undernutrition. Traditional Chinese medicine (TCM) offers various treatment regimens that are actively utilized in the field of diabetes management. Through multiple targets and multiple pathways, TCM formulas, medicinal herbs, and active natural products enhance the efficacy of diabetes prevention and diabetes control measures, simplify complex medication management, and improve common symptoms and common diabetic complications in elderly people. Historically, natural products have played a key role in material composition analysis of TCM and mechanism interpretation to enable drug discovery. However, there have been few conclusions on this topic. This review summarizes the development of TCM for the prevention and management of diabetes in elderly people, existing evidence-based clinical practices, and prospects for future development.

Liraglutide combined with routine therapy improves renal function, renal fibrosis, immune status, and prognosis of type 2 diabetes patients

OBJECTIVE

To investigate the effect of Liraglutide in conjunction with routine therapy on renal function, renal fibrosis, immune status, and prognosis in patients with diabetes mellitus.

METHODS

The clinical data of patients with Type 2 diabetes mellitus (T2DM) treated at the First Affiliated Hospital of Jishou University from March 2021 to March 2022 were retrospectively analyzed. Patients were assigned into a control group (n=42) and a study group (n=42) according to their treatment regimen. The control group received routine treatment, and the study group received Liraglutide in addition to routine treatment. The therapeutic effects, blood glucose levels, renal function, renal fibrosis, and Immunoglobulin (Ig) levels as well as the incidence of adverse reactions, were compared between the two groups.

RESULTS

The effective rate was higher in study group (97.62%) than that of the control group (78.57%) (P<0.05). After treatment, the fasting blood-glucose (FBG), 2-hour postprandial plasma glucose (2hPG), and glycosylated hemoglobin (HbA1c) levels were decreased; and the study group displayed a significantly lower blood glucose level than the control group (all P<0.05). Also, the serum creatinine (Scr), blood urea nitrogen (BUN), and 24-hour urinary protein quantification (24h-UPor) were decreased after treatment; and the study group showed more pronounced improvement in renal function index than did the control group (all P<0.05). The levels of IgA, IgM, and IgG were increased after treatment compared to pre-treatment; and the study group exhibited significantly better improvement than the control group (all P<0.05). However, the study group reported a notably higher incidence of adverse reactions than the control group (19.05% vs 2.38%; P<0.05).

CONCLUSION

Liraglutide combined with routine therapy is effective in treating patients with diabetes, which can effectively reduce the levels of blood glucose andurinary protein, and the degree of renal fibrosis, while improving renal and immune functions and the clinical prognosis of diabetic patients.

Development and validation of a risk prediction model for mild cognitive impairment in elderly patients with type 2 diabetes mellitus

BACKGROUND

The prevalence of mild cognitive impairment (MCI) is steadily increasing among elderly people with type 2 diabetes (T2DM). This study aimed to create and validate a predictive model based on a nomogram.

METHODS

This cross-sectional study collected sociodemographic characteristics, T2DM-related factors, depression, and levels of social support from 530 older adults with T2DM. We used LASSO regression and multifactorial logistic regression to determine the predictors of the model. The performance of the nomogram was evaluated using calibration curves, receiver operating characteristics (ROC), and decision curve analysis (DCA).

RESULTS

The nomogram comprised age, smoking, physical activity, social support, depression, living alone, and glycosylated hemoglobin. The AUC for the training and validation sets were 0.914 and 0.859. The DCA showed good clinical applicability.

CONCLUSIONS

This predictive nomogram has satisfactory accuracy and discrimination. Therefore, the nomogram can be intuitively and easily used to detect MCI in elderly adults with T2DM.

Age of type 2 diabetes onset as a risk factor for dementia: A 13-year retrospective cohort study

AIMS

To examine whether age at type 2 diabetes onset is an independent predictor of dementia risk.

METHODS

Retrospective cohort drawn from healthcare administrative records of all inhabitants within Romagna's catchment area, Italy, with an estimated onset of type 2 diabetes in 2008-2017 and aged ≥ 55, with follow-up until 2020. Time to dementia or censoring was estimated with the Kaplan-Meier method, using diabetes onset as the time origin. Age groups were compared with the log-rank test. Multivariable competing-risks analysis was used to assess predictors of dementia.

RESULTS

In patients aged ≥ 75 years, dementia-free survival (DFS) declined to below 90 % within five years and linearly decreased to 68.8 % until the end of follow-up. In contrast, DFS for those aged 55-64 years showed a marginal decrease, reaching 97.4 % after 13 years. Competing-risks regression showed that individuals aged ≥ 75 and 65-74 had a significantly higher risk of dementia compared to those aged 55-64 years. Having more comorbidities at diabetes onset and initial treatment with ≥ 2 antidiabetics were clinical predictors.

CONCLUSIONS

Later age at onset of diabetes is strongly associated with dementia. A better understanding of the diabetes-dementia relationship is needed to inform strategies for promoting specific healthcare pathways.

Cerebral Microbleeds Associate with Brain Endothelial Cell Activation-Dysfunction and Blood-Brain Barrier Dysfunction/Disruption with Increased Risk of Hemorrhagic and Ischemic Stroke

Globally, cerebral microbleeds (CMBs) are increasingly being viewed not only as a marker for cerebral small vessel disease (SVD) but also as having an increased risk for the development of stroke (hemorrhagic/ischemic) and aging-related dementia. Recently, brain endothelial cell activation and dysfunction and blood-brain barrier dysfunction and/or disruption have been shown to be associated with SVD, enlarged perivascular spaces, and the development and evolution of CMBs. CMBs are a known disorder of cerebral microvessels that are visualized as 3-5 mm, smooth, round, or oval, and hypointense (black) lesions seen only on T2*-weighted gradient recall echo or susceptibility-weighted sequences MRI images. CMBs are known to occur with high prevalence in community-dwelling older individuals. Since our current global population is the oldest recorded in history and is only expected to continue to grow, we can expect the healthcare burdens associated with CMBs to also grow. Increased numbers (≥10) of CMBs should raise a red flag regarding the increased risk of large symptomatic neurologic intracerebral hemorrhages. Importantly, CMBs are also currently regarded as markers of diffuse vascular and neurodegenerative brain damage. Herein author highlights that it is essential to learn as much as we can about CMB development, evolution, and their relation to impaired cognition, dementia, and the exacerbation of neurodegeneration.

Bitter yet beneficial: The dual role of dietary alkaloids in managing diabetes and enhancing cognitive function

With the rising prevalence of diabetes and its association with cognitive impairment, interest in the use of dietary alkaloids and other natural products has grown significantly. Understanding how these compounds manage diabetic cognitive dysfunction (DCD) is crucial. This comprehensive review explores the etiology of DCD and the effects of alkaloids in foods and dietary supplements that have been investigated as DCD therapies. Data on how dietary alkaloids like berberine, trigonelline, caffeine, capsaicin, 1-deoxynojirimycin, nuciferine, neferine, aegeline, tetramethylpyrazine, piperine, and others regulate cognition in diabetic disorders were collected from PubMed, Research Gate, Web of Science, Science Direct, and other relevant databases. Dietary alkaloids could improve memory in behavioral models and modulate the mechanisms underlying the cognitive benefits of these compounds, including their effects on glucose metabolism, gut microbiota, vasculopathy, neuroinflammation, and oxidative stress. Evidence suggests that dietary alkaloids hold promise for improving cognition in diabetic patients and could open exciting avenues for future research in diabetes management.

Microvascular burden and long-term risk of stroke and dementia in type 2 diabetes mellitus

OBJECTIVE

To examine the associations between microvascular disease (MVD) and risk of stroke, dementia, and their major subtypes among individuals with type 2 diabetes mellitus (T2DM).

METHODS

We included 26,173 participants with T2DM from the UK Biobank who had no known stroke or dementia at baseline. MVD burden was reflected by the presence of retinopathy, peripheral neuropathy, and chronic kidney disease. Cox regression models were used to estimate hazard ratios (HRs) and 95 % confidential intervals (CIs) of stroke and dementia associated with overall MVD burden and individual MVD.

RESULTS

During a median follow-up of 11.5 years, 1103 incident stroke (964 ischemic and 269 hemorrhagic stroke) and 813 incident dementia (312 Alzheimer's disease and 304 vascular dementia) cases were identified. The risk of stroke, dementia, and their major subtypes all increased with an increasing number of MVD (all P-trend <0.001). The adjusted HRs (95 % CIs) comparing three with no MVD were 5.03 (3.16, 8.02) for all stroke, 4.57 (2.75, 7.59) for ischemic stroke, and 6.60 (2.65, 16.43) for hemorrhagic stroke. The corresponding estimates were 4.28 (2.33, 7.86) for all-cause dementia, 6.96 (3.02, 16.01) for Alzheimer's disease, and 3.81 (1.40, 10.42) for vascular dementia. Among the three MVD, chronic kidney disease showed the strongest associations with both stroke subtypes, while peripheral neuropathy was most strongly associated with both dementia subtypes.

CONCLUSIONS

Risk of stroke, dementia, and their major subtypes increased with an increasing number of MVD. The associations of individual MVD with stroke and dementia varied substantially by types of MVD.

Comparing major and mild cognitive impairment risks in older type-2 diabetic patients: a Danish register-based study on dipeptidyl peptidase-4 inhibitors vs. glucagon-like peptide-1 analogues

INTRODUCTION

The prevalence of major and mild cognitive impairment (CI) in type-2 diabetes older patients is 15-25% and 30-60%, respectively, thus affecting quality of life and health outcomes. There is, therefore, the need of head-to-head studies aiming at identifying the optimal treatment for individuals with type-2 diabetes at increased risk of mild and major CI. This study focuses on the risk of developing mild and major CI in Danish patients treated with dipeptidyl peptidase-4 inhibitors (DPP-4i) and glucagon-like peptide-1 analogues (GLP-1a) using administrative and healthcare registers.

METHODS

An active comparator design with a 3-year follow-up period was used. The main outcome was the hospital admission with a diagnosis of mild CI or major CI. Multivariate Cox Regression analysis was performed using the high-dimensional propensity score to obtain adjusted Hazard Ratio (HR) estimates. Inverse probability of treatment weighting (IPTW) and marginal structured model were used to calculate risk differences while accounting for the variations of confounders throughout the follow-up period.

RESULTS

Our results show a significant higher risk of major CI between DPP-4i and GLP-1a in unadjusted [HR (95% CI) = 3.13 (2.45-4.00), p < 0.001] and adjusted analyses [HR (95% CI) = 1.58 (1.22-2.06), p = 0.001]. No statistically significant differences were observed for mild CI. IPTW resulted stable throughout the follow-up period. Marginal structure modeling (β (95% CI) = 0.022 (0.020-0.024), p < 0.001) resulted in a higher risk of major CI for DPP-4i when compared to GLP-1a.

DISCUSSION

DPP-4i was associated with an increased risk of developing major CI when compared to GLP-1a among older individuals with type-2 diabetes.

Berberine improves cognitive impairment by alleviating brain atrophy and promoting white matter reorganization in diabetic db/db mice: a magnetic resonance imaging-based study

Diabetic cognitive impairment is a common complication in type 2 diabetes. Berberine (BBR) is an isoquinoline alkaloid that has been shown to have neuroprotective effects against diabetes. This study aimed to investigate the effect of BBR on the gray and white matter of the brain by using magnetic resonance imaging (MRI) and to explore the underlying mechanisms. The study used diabetic db/db mice and administered BBR (50 and 100 mg/kg) intragastrically for twelve weeks. Morris water maze was applied to examine cognitive function. T2-weighted imaging (T2WI) was performed to assess brain atrophy, and diffusion tensor imaging (DTI) combined with fiber tracking was conducted to monitor the structural integrity of the white matter, followed by histological immunostaining. Furthermore, the protein expressions of the phosphatidylinositol 3-kinase (PI3K)/ protein kinase B (AKT)/ glycogen synthase kinase-3β (GSK-3β) were detected. The results revealed that BBR significantly improved the spatial learning and memory of the db/db mice. T2WI exhibited ameliorated brain atrophy in the BBR-treated db/db mice, as evidenced by reduced ventricular volume accompanied by increased hippocampal volumes. DTI combined with fiber tracking revealed that BBR increased FA, fiber density and length in the corpus callosum/external capsule of the db/db mice. These imaging findings were confirmed by histological immunostaining. Notably, BBR significantly enhanced the protein levels of phosphorylated AKT at Ser473 and GSK-3β at Ser9. Collectively, this study demonstrated that BBR significantly improved the cognitive function of the diabetic db/db mice through ameliorating brain atrophy and promoting white matter reorganization via AKT/GSK-3β pathway.

Longitudinal Change in Serum Neurofilament Light Chain in Type 2 Diabetes and Early Diabetic Polyneuropathy: ADDITION-Denmark

OBJECTIVE

To investigate the longitudinal development of neurofilament light chain (NfL) levels in type 2 diabetes with and without diabetic polyneuropathy (+/-DPN) and to explore the predictive potential of NfL as a biomarker for DPN.

RESEARCH DESIGN AND METHODS

We performed retrospective longitudinal case-control analysis of data from 178 participants of the Anglo-Danish-Dutch Study of Intensive Treatment in People with Screen-Detected Diabetes in Primary Care-Denmark (ADDITION-Denmark) cohort of people with screen-detected type 2 diabetes. Biobank samples acquired at the ADDITION-Denmark 5- and 10-year follow-ups were analyzed for serum NfL (s-NfL) using single-molecule array, and the results were compared with established reference material to obtain NfL z-scores. DPN was diagnosed according to Toronto criteria for confirmed DPN at the 10-year follow-up.

RESULTS

s-NfL increased over time in +DPN (N = 39) and -DPN participants (N = 139) at levels above normal age-induced s-NfL increase. Longitudinal s-NfL change was greater in +DPN than in -DPN participants (17.4% [95% CI 4.3; 32.2] or 0.31 SD [95% CI 0.03; 0.60] higher s-NfL or NfL z-score increase in +DPN compared with -DPN). s-NfL at the 5-year follow-up was positively associated with nerve conduction studies at the 10-year follow-up (P = 0.02 to <0.001), but not with DPN risk. Areas under the curve (AUCs) for s-NfL were not inferior to AUCs for the Michigan Neuropathy Screening Instrument questionnaire score or vibration detection thresholds. Higher yearly s-NfL increase was associated with higher DPN risk (odds ratio 1.36 [95% CI 1.08; 1.71] per 1 ng/L/year).

CONCLUSIONS

Our findings suggest that preceding s-NfL trajectories differ slightly between those with and without DPN and imply a possible biomarker value of s-NfL trajectories in DPN.

Trajectories of cognitive function among people aged 45 years and older living with diabetes in China: Results from a nationally representative longitudinal study (2011~2018)

OBJECTIVES

Diabetes is associated with decline of cognitive function. Exploring different trajectories of cognitive function occurring in people with diabetes is important to improved prognosis. This study aimed to investigate differential patterns of trajectories of cognitive function and baseline determinants of trajectory group membership utilizing data from middle-aged and older Chinese adults with diabetes.

METHODS

Participants of the Chinese Health And Retirement Longitudinal Study (CHARLS) aged 45 years and above received biennial assessments between 2011 and 2018. The primary outcome was overall cognitive function score operationalized as sum of mental intactness and episodic memory scores derived from the Telephone Interview of Cognitive Status (TICS). A weighted growth mixture model was used to estimate cognitive function trajectories of CHARLS participants with diabetes, and baseline factors associated with trajectory group membership were investigated with weighted multinomial logistic regression.

RESULTS

Data from 1,463 participants with diabetes aged 45 years and above were analyzed, a three-group trajectory model showed the best fit for overall cognitive scores: low baseline, linear declining (22.1%); moderate baseline, linear declining (37.5%) and high-stable (40.3%). Older participants, females, participants with low education, with nighttime sleep <6 h, without daytime napping habits, and with depressive symptoms were at a higher risk of unfavorable cognitive function trajectories.

CONCLUSIONS

We identified heterogeneous trajectories of cognitive function among middle-aged and older people living with diabetes in China. Socially vulnerable groups including females, rural residents, and those with low education were at a higher risk for unfavorable trajectories. In health programs aimed at preventing and mitigating cognitive decline in individuals with diabetes more attention should be given to vulnerable groups. Reduced nighttime sleep, lack of daytime napping, and depressive symptoms appear to be modifiable risk factors.

Deciphering the dual role of N-methyl-D-Aspartate receptor in postoperative cognitive dysfunction: A comprehensive review

Postoperative cognitive dysfunction (POCD) is a common complication following surgery, adversely impacting patients' recovery, increasing the risk of negative outcomes, prolonged hospitalization, and higher mortality rates. The N-methyl-D-aspartate (NMDA) receptor, crucial for learning, memory, and synaptic plasticity, plays a significant role in the development of POCD. Various perioperative factors, including age and anesthetic use, can reduce NMDA receptor function, while surgical stress, inflammation, and pain may lead to its excessive activation. This review consolidates preclinical and clinical research to explore the intricate relationship between perioperative factors affecting NMDA receptor functionality and the onset of POCD. It discusses the influence of aging, anesthetic administration, perioperative injury, pain, and inflammation on the NMDA receptor-related pathophysiology of POCD. The comprehensive analysis presented aims to identify effective treatment targets for POCD, contributing to the improvement of patient outcomes post-surgery.

Diabetes mellitus in older persons with neurocognitive disorder: overtreatment prevalence and associated structural brain MRI findings

BACKGROUND

Tight diabetes control is often applied in older persons with neurocognitive disorder resulting in increased hypoglycemic episodes but little is known about the pattern of brain injury in these overtreated patients. This study aims to: (a) quantify the prevalence of diabetes overtreatment in cognitively impaired older adults in a clinical population followed in an academic memory clinic (b) identify risk factors contributing to overtreatment; and (c) explore the association between diabetes overtreatment and specific brain region volume changes.

METHODS

Retrospective study of older patients with type 2 diabetes and cognitive impairment who were diagnosed in a memory clinic from 2013 to 2020. Patients were classified into vulnerable and dependent according to their health profile. Overtreatment was defined when glycated hemoglobin was under 7% for vulnerable and 7.6% for dependent patients. Characteristics associated to overtreatment were examined in multivariable analysis. Grey matter volume in defined brain regions was measured from MRI using voxel-based morphometry and compared in patients over- vs. adequately treated.

RESULTS

Among 161 patients included (median age 76.8 years, range 60.8-93.3 years, 32.9% women), 29.8% were considered as adequately treated, 54.0% as overtreated, and 16.2% as undertreated. In multivariable analyses, no association was observed between diabetes overtreatment and age or the severity of cognitive impairment. Among patients with neuroimaging data (N = 71), associations between overtreatment and grey matter loss were observed in several brain regions. Specifically, significant reductions in grey matter were found in the caudate (adj β coeff: -0.217, 95%CI: [-0.416 to -0.018], p = .033), the precentral gyri (adj βcoeff:-0.277, 95%CI: [-0.482 to -0.073], p = .009), the superior frontal gyri (adj βcoeff: -0.244, 95%CI: [-0.458 to -0.030], p = .026), the calcarine cortex (adj βcoeff:-0.193, 95%CI: [-0.386 to -0.001], p = .049), the superior occipital gyri (adj βcoeff: -0.291, 95%CI: [-0.521 to -0.061], p = .014) and the inferior occipital gyri (adj βcoeff: -0.236, 95%CI: [-0.456 to - 0.015], p = .036).

CONCLUSION

A significant proportion of older patients with diabetes and neurocognitive disorder were subjected to excessively intensive treatment. The association identified with volume loss in several specific brain regions highlights the need to further investigate the potential cerebral damages associated with overtreatment and related hypoglycemia in larger sample.

Alterations in Brain Morphometric Networks and Their Relationship with Memory Dysfunction in Patients with Type 2 Diabetes Mellitus

Cognitive dysfunction, a significant complication of type 2 diabetes mellitus (T2DM), can potentially manifest even from the early stages of the disease. Despite evidence of global brain atrophy and related cognitive dysfunction in early-stage T2DM patients, specific regions vulnerable to these changes have not yet been identified. The study enrolled patients with T2DM of less than five years' duration and without chronic complications (T2DM group, n=100) and demographically similar healthy controls (control group, n=50). High-resolution T1-weighted magnetic resonance imaging data were subjected to independent component analysis to identify structurally significant components indicative of morphometric networks. Within these networks, the groups' gray matter volumes were compared, and distinctions in memory performance were assessed. In the T2DM group, the relationship between changes in gray matter volume within these networks and declines in memory performance was examined. Among the identified morphometric networks, the T2DM group exhibited reduced gray matter volumes in both the precuneus (Bonferroni-corrected p=0.003) and insular-opercular (Bonferroni-corrected p=0.024) networks relative to the control group. Patients with T2DM demonstrated significantly lower memory performance than the control group (p=0.001). In the T2DM group, reductions in gray matter volume in both the precuneus (r=0.316, p=0.001) and insular-opercular (r=0.199, p=0.047) networks were correlated with diminished memory performance. Our findings indicate that structural alterations in the precuneus and insular-opercular networks, along with memory dysfunction, can manifest within the first 5 years following a diagnosis of T2DM.

Risk factors and metabolomics of mild cognitive impairment in type 2 diabetes mellitus

Objective: This study aimed to explore the risk factors, metabolic characteristics, and potential biomarkers of mild cognitive impairment in type 2 diabetes mellitus (T2DM-MCI) and to provide potential evidence for the diagnosis, prevention, and treatment of mild cognitive impairment (MCI) in patients with type 2 diabetes mellitus (T2DM). Methods: A total of 103 patients with T2DM were recruited from the Endocrinology Department of The Second Affiliated Hospital of Dalian Medical University for inclusion in the study. The Montreal Cognitive Assessment (MoCA) was utilized to evaluate the cognitive functioning of all patients. Among them, 50 patients were categorized into the T2DM-MCI group (MoCA score < 26 points), while 53 subjects were classified into the T2DM without cognitive impairment (T2DM-NCI) group (MoCA score ≥ 26 points). Serum samples were collected from the subjects, and metabolomics profiling data were generated by Ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS). These groups were analyzed to investigate the differences in expression of small molecule metabolites, metabolic pathways, and potential specific biomarkers. Results: Comparison between the T2DM-MCI group and T2DM-NCI group revealed significant differences in years of education, history of insulin application, insulin resistance index, insulin-like growth factor-binding protein-3 (IGFBP-3), and creatinine levels. Further binary logistic regression analysis of the variables indicated that low educational level and low serum IGFBP-3 were independent risk factor for T2DM-MCI. Metabolomics analysis revealed that differential expression of 10 metabolites between the T2DM-MCI group and T2DM-NCI group (p < 0.05 and FDR<0.05, VIP>1.5). Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analysis revealed that fatty acid degradation was the most significant pathway. Receiver operating characteristic (ROC) analysis shows that lysophosphatidylcholine (LPC) 18:0 exhibited greater diagnostic efficiency. Conclusion: This study revealed that a shorter duration of education and lower serum IGFBP-3 levels are independent risk factors for T2DM-MCI. Serum metabolites were found to be altered in both T2DM-MCI and T2DM-NCI groups. T2DM patients with or without MCI can be distinguished by LPC 18:0. Abnormal lipid metabolism plays a significant role in the development of MCI in T2DM patients.

Novel insights into immune-related genes associated with type 2 diabetes mellitus-related cognitive impairment

BACKGROUND

The cognitive impairment in type 2 diabetes mellitus (T2DM) is a multifaceted and advancing state that requires further exploration to fully comprehend. Neuroinflammation is considered to be one of the main mechanisms and the immune system has played a vital role in the progression of the disease.

AIM

To identify and validate the immune-related genes in the hippocampus associated with T2DM-related cognitive impairment.

METHODS

To identify differentially expressed genes (DEGs) between T2DM and controls, we used data from the Gene Expression Omnibus database GSE125387. To identify T2DM module genes, we used Weighted Gene Co-Expression Network Analysis. All the genes were subject to Gene Set Enrichment Analysis. Protein-protein interaction network construction and machine learning were utilized to identify three hub genes. Immune cell infiltration analysis was performed. The three hub genes were validated in GSE152539 via receiver operating characteristic curve analysis. Validation experiments including reverse transcription quantitative real-time PCR, Western blotting and immunohistochemistry were conducted both in vivo and in vitro. To identify potential drugs associated with hub genes, we used the Comparative Toxicogenomics Database (CTD).

RESULTS

A total of 576 DEGs were identified using GSE125387. By taking the intersection of DEGs, T2DM module genes, and immune-related genes, a total of 59 genes associated with the immune system were identified. Afterward, machine learning was utilized to identify three hub genes (H2-T24, Rac3, and Tfrc). The hub genes were associated with a variety of immune cells. The three hub genes were validated in GSE152539. Validation experiments were conducted at the mRNA and protein levels both in vivo and in vitro, consistent with the bioinformatics analysis. Additionally, 11 potential drugs associated with RAC3 and TFRC were identified based on the CTD.

CONCLUSION

Immune-related genes that differ in expression in the hippocampus are closely linked to microglia. We validated the expression of three hub genes both in vivo and in vitro, consistent with our bioinformatics results. We discovered 11 compounds associated with RAC3 and TFRC. These findings suggest that they are co-regulatory molecules of immunometabolism in diabetic cognitive impairment.

Trends in Cognitive Function Before and After Diabetes Onset: The China Health and Retirement Longitudinal Study

BACKGROUND AND OBJECTIVES

Individuals with prevalent diabetes were known to have a higher risk of dementia and lower cognitive function. However, trends of cognitive function before diabetes and in the short term after new-onset diabetes remain unclear.

METHODS

This study included participants without baseline diabetes from the China Health and Retirement Longitudinal Study. Cognitive tests were conducted at baseline (wave 1) and at least one time from wave 2 (2013) to wave 4 (2018). Cognitive function was assessed using a global cognition score which was the summary measure of 4 cognitive tests. A linear mixed model was constructed to fit the trends in cognitive function before and after diabetes onset and the trends among nondiabetes. The threshold of statistical significance was p < 0.05.

RESULTS

During the 7-year follow-up, 1,207 (9.7% of 12,422, 59.1 ± 8.6 years, 39.9% male participants) participants developed new-onset diabetes. The cognitive function of both the without diabetes group and the diabetes group declined annually during the follow-up. The annual decline rate of the diabetes group before diabetes onset was similar to that of the without diabetes group during the whole follow-up period. After diabetes onset, participants experienced statistically significant faster cognitive declines in global cognition (-0.023 SD/year; 95% CI -0.043 to -0.004; p = 0.019) and visuospatial abilities test (-0.036 SD/year; -0.061 to -0.011; p = 0.004), but not in tests of episodic memory (-0.018 SD/year; -0.041 to 0.004; p = 0.116), attention and calculation (-0.017 SD/year; -0.037 to 0.003; p = 0.090), or orientation (0.001 SD/year; -0.018 to 0.020; p = 0.894), compared with the cognitive slope before diabetes. In subgroup analysis, compared with those who developed diabetes between 45-54 years, those developing diabetes older (55-64 years, p for interaction = 0.701; 65-74 years, p for interaction = 0.996) did not demonstrate different rates of global cognitive decline after diabetes.

DISCUSSION

Individuals experienced faster rate of cognitive decline in a few years after diabetes onset, but not during the prediabetes period. Age did not modify the effect of diabetes on postdiabetes cognitive decline. Efforts in eliminating the adverse impacts on cognition should be started on diagnosis of diabetes.

A new nomogram model for the individualized prediction of mild cognitive impairment in elderly patients with type 2 diabetes mellitus

Background

A high risk of developing mild cognitive impairment (MCI) is faced by elderly patients with type 2 diabetes mellitus (T2DM). In this study, independent risk factors for MCI in elderly patients with T2DM were investigated, and an individualized nomogram model was developed.

Methods

In this study, clinical data of elderly patients with T2DM admitted to the endocrine ward of the hospital from November 2021 to March 2023 were collected to evaluate cognitive function using the Montreal Cognitive Assessment scale. To screen the independent risk factors for MCI in elderly patients with T2DM, a logistic multifactorial regression model was employed. In addition, a nomogram to detect MCI was developed based on the findings of logistic multifactorial regression analysis. Furthermore, the accuracy of the prediction model was evaluated using calibration and receiver operating characteristic curves. Finally, decision curve analysis was used to evaluate the clinical utility of the nomogram.

Results

In this study, 306 patients were included. Among them, 186 patients were identified as having MCI. The results of multivariate logistic regression analysis demonstrated that educational level, duration of diabetes, depression, glycated hemoglobin, walking speed, and sedentary duration were independently correlated with MCI, and correlation analyses showed which influencing factors were significantly correlated with cognitive function (p <0.05). The nomogram based on these factors had an area under the curve of 0.893 (95%CI:0.856-0.930)(p <0.05), and the sensitivity and specificity were 0.785 and 0.850, respectively. An adequate fit of the nomogram in the predictive value was demonstrated by the calibration plot.

Conclusions

The nomogram developed in this study exhibits high accuracy in predicting the occurrence of cognitive dysfunction in elderly patients with T2DM, thereby offering a clinical basis for detecting MCI in patients with T2DM.

A Nomogram Including Total Cerebral Small Vessel Disease Burden Score for Predicting Mild Vascular Cognitive Impairment in Patients with Type 2 Diabetes Mellitus

Background

Total cerebral small vessel disease (CSVD) burden score is an important predictor of vascular cognitive impairment (VCI). However, few predictive models of VCI in type 2 diabetes mellitus (T2DM) patients have included the total CSVD burden score, especially in the early stage of VCI.

Objective

To develop and validate a nomogram that includes the total CSVD burden score to predict mild VCI in patients with T2DM.

Methods

A total of 322 eligible participants with T2DM who were divided into mild and normal cognitive groups were enrolled in this retrospective study. Demographic data, laboratory data and imaging markers of CSVD were collected. The total CSVD burden score was calculated by combining the different CSVD markers. Step-backward multivariable logistic regression analysis with the Akaike information criterion was applied to select significant predictors and develop a best-fit predictive nomogram. The performance of the nomogram was assessed in terms of discriminative ability, calibrated ability, and clinical usefulness.

Results

The nomogram model consisted of five variables: age, education, hemoglobin A1c level, serum homocysteine level, and total CSVD burden score. A nomogram with these variables showed good discriminative ability (area under the receiver operating characteristic curve was 0.801 in internal verification). In addition, the Hosmer-Lemeshow test (χ2 =9.226, P=0.417) and bootstrap-corrected calibration plot indicated that the nomogram had good calibration. The Brier score of the predictive model was 0.178. Decision curve analysis demonstrated that when the threshold probability ranged between 16% and 98%, the use of the nomogram to predict mild VCI in patients with T2DM provide a greater net benefit.

Conclusions

The nomogram, composed of age, education, stroke, HbA1c level, Hcy level, and total CSVD burden score, had good predictive accuracy and may provide clinicians with a practical tool for predicting the risk of mild VCI in T2DM patients.

Understanding the relationship between type-2 diabetes, MRI markers of neurodegeneration and small vessel disease, and dementia risk: a mediation analysis

To explore to which extent neurodegeneration and cerebral small vessel disease (SVD) could mediate the association between type-2 diabetes and higher dementia risk. The analytical sample consisted in 2228 participants, out of the Three-City study, aged 65 and older, free of dementia at baseline who underwent brain MRI. Diabetes was defined by medication intake or fasting or non-fasting elevated glucose levels. Dementia status was assessed every 2 to 3 years, during up to 12 years of follow-up. Brain parenchymal fraction (BPF) and white matter hyperintensities volume (WMHV) were selected as markers of neurodegeneration and cerebral SVD respectively. We performed a mediation analysis of the effect of baseline BPF and WMHV (mediators) on the association between diabetes and dementia risk using linear and Cox models adjusted for age, sex, education level, hypertension, hypercholesterolemia, BMI, smoking and alcohol drinking status, APOE-ε4 status, and study site. At baseline, 8.8% of the participants had diabetes. Diabetes (yes vs. no) was associated with higher WMHV (βdiab = 0.193, 95% CI 0.040; 0.346) and lower BPF (βdiab = -0.342, 95% CI -0.474; -0.210), as well as with an increased risk of dementia over 12 years of follow-up (HRdiab = 1.65, 95% CI 1.04; 2.60). The association between diabetes status and dementia risk was statistically mediated by higher WMHV (HRdiab=1.05, 95% CI 1.01; 1.11, mediated part = 10.8%) and lower BPF (HRdiab = 1.12, 95% CI 1.05; 1.20, mediated part = 22.9%). This study showed that both neurodegeneration and cerebral SVD statistically explained almost 30% of the association between diabetes and dementia.

Development and Validation of a Risk Score for Mild Cognitive Impairment in Individuals with Type 2 Diabetes in China: A Practical Cognitive Prescreening Tool

Aim

Numerous evidence suggests that diabetes increases the risk of cognitive impairment. This study aimed to develop and validate a multivariable risk score model to identify mild cognitive impairment (MCI) in patients with type 2 diabetes mellitus (T2DM).

Methods

This cross-sectional study included 1256 inpatients (age: 57.5 ± 11.2 years) with T2DM in a tertiary care hospital in China. MCI was diagnosed according to the criteria recommended by the National Institute on Aging-Alzheimer's Association Workgroup, and a MoCA score of 19-25 indicated MCI. Participants were randomly allocated into the derivation and validation sets at 7:3 ratio. Logistic regression models were used to identify predictors for MCI in the derivation set. A scoring system based on the predictors' beta coefficient was developed. Predictive ability of the risk score was tested by discrimination and calibration methods.

Results

Totally 880 (285 with MCI, 32.4%) and 376 (167 with MCI, 33.8%) patients were allocated in the derivation and validation set, respectively. Age, education, HbA1c, self-reported history of severe hypoglycemia, and microvascular disease were identified as predictors for MCI and constituted the risk score. The AUCs (95% CI) of the risk score were 0.751 (0.717, 0.784) in derivation set and 0.776 (0.727, 0.824) in validation set. The risk score showed good apparent calibration of observed and predicted MCI probabilities and was capable of stratifying individuals into 3 risk categories by two cut-off points (low risk: ≤ 3, medium risk: 4-13, and high risk ≥ 14).

Conclusion

The risk score based on age, education, HbA1c, self-reported history of severe hypoglycemia, and microvascular disease can effectively assess MCI risk in adults with T2DM at different age. It can serve as a practical prescreening tool for early detection of MCI in daily diabetes care.

Large-scale functional network connectivity mediates the associations between lipids metabolism and cognition in type 2 diabetes

Type 2 diabetes (T2D) is associated with dyslipidemia and mild cognitive impairment. This study investigated the relationships between serum lipids metabolism, cognition, and functional connectivity (FC) within and between brain networks in T2D patients. The study included 102 T2D patients and 45 healthy controls who underwent functional magnetic resonance imaging, lipid profile tests, and cognitive assessments. Thirteen functional networks were identified using independent component analysis. The statistical analyses included multivariate analysis of covariance, partial correlation, canonical correlation, and mediation analyses. We found widely reduced between-network FCs in T2D, especially between the ventral sensorimotor network (SMN) and dorsal attention network (DAN) (p = 0.001) and between the ventral SMN and lateral visual network (VN) (p < 0.001). Moreover, lower between-network FCs were correlated with worse serum lipids metabolism and poorer cognitive performance (all p < 0.05). Importantly, between-network FCs mediated the relationship between lipid metabolism and cognition (β = -0.3136, 95% CI: -0.7660, -0.0186). Within-network analyses revealed altered FCs within the anterior default mode network, DAN, and lateral VN, each positively correlated with global cognition (all p < 0.01). Our results suggest the potential of improving cognitive function by regulating serum lipids in individuals with T2D.