Type 2 diabetes mellitus-associated transcriptome alterations in cortical neurones and associated neurovascular unit cells in the ageing brain

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.

Prospecting Specific Protein Patterns for High Body Mass Index (BMI), Metabolic Syndrome and Type 2 Diabetes in Saliva and Blood Plasma From a Brazilian Population

PURPOSE

Obesity and its associated metabolic disorders, such as T2DM and MeS, are a growing public health problem worldwide. Our goal was the identification of protein patterns that are uniquely characteristic of higher BMI, MeS, and T2DM in a Brazilian population.

EXPERIMENTAL DESIGN

Saliva and plasma proteomes, clinical parameters were analyzed in a population from the state of Rio de Janeiro, Brazil, a mixed-race population. Volunteers were sorted by their BMI into normal (n = 29), overweight (n = 25), and obese (n = 15) and were compared with individuals with MeS (n = 23) and T2DM (n = 11).

RESULTS

The Random Forest (RF) predictive model revealed that three clinical variables, BMI, HOMA-IR, and fasting blood glucose, are most important for predicting MeS and T2DM. A total of six plasmatic proteins (ABCD4, LDB1, PDZ, podoplanin, lipirin-alpha-3, and WRS) and six salivary proteins (hemoglobin subunit beta, POTEE, T cell receptor alpha variable 9-2, lactotransferrin, cystatin-S, carbonic anhydrase 6), are enhanced in T2DM and in MeS.

CONCLUSIONS AND CLINICAL RELEVANCE

Our data revealed similar alterations in protein composition across individuals with abnormal weight gain, T2DM, and MeS. This finding confirms the close link between these conditions at the molecular level in the studied population, potentially enhancing our understanding of these diseases and paving the way for the development of novel diagnostic tools.

Identifying transcriptomic profiles of iron-quercetin complex treated peripheral blood mononuclear cells from healthy volunteers and diabetic patients

Peripheral blood is an alternative source of stem/progenitor cells for regenerative medicine owing to its ease of retrieval and blood bank storage. Previous in vitro studies indicated that the conditioned medium derived from peripheral blood mononuclear cells (PBMCs) treated with the iron-quercetin complex (IronQ) contains potent angiogenesis and wound-healing properties. This study aims to unveil the intricate regulatory mechanisms governing the effects of IronQ on the transcriptome profiles of human PBMCs from healthy volunteers and those with diabetes mellitus (DM) using RNA sequencing analysis. Our findings revealed 3741 and 2204 differentially expressed genes (DEGs) when treating healthy and DM PBMCs with IronQ, respectively. Functional enrichment analyses underscored the biological processes shared by the DEGs in both conditions, including inflammatory responses, cell migration, cellular stress responses, and angiogenesis. A comprehensive exploration of these molecular alterations exposed a network of 20 hub genes essential in response to stimuli, cell migration, immune processes, and the mitogen-activated protein kinase (MAPK) pathway. The activation of these pathways enabled PBMCs to potentiate angiogenesis and tissue repair. Corroborating this, quantitative real-time polymerase chain reaction (qRT-PCR) and cell phenotyping confirmed the upregulation of candidate genes associated with anti-inflammatory, pro-angiogenesis, and tissue repair processes in IronQ-treated PBMCs. In summary, combining IronQ and PBMCs brings about substantial shifts in gene expression profiles and activates pathways that are crucial for tissue repair and immune response, which is promising for the enhancement of the therapeutic potential of PBMCs, especially in diabetic wound healing.

An Artificial Intelligence Prediction Model of Insulin Sensitivity, Insulin Resistance, and Diabetes Using Genes Obtained through Differential Expression

Insulin is a powerful pleiotropic hormone that affects processes such as cell growth, energy expenditure, and carbohydrate, lipid, and protein metabolism. The molecular mechanisms by which insulin regulates muscle metabolism and the underlying defects that cause insulin resistance have not been fully elucidated. This study aimed to perform a microarray data analysis to find differentially expressed genes. The analysis has been based on the data of a study deposited in Gene Expression Omnibus (GEO) with the identifier "GSE22309". The selected data contain samples from three types of patients after taking insulin treatment: patients with diabetes (DB), patients with insulin sensitivity (IS), and patients with insulin resistance (IR). Through an analysis of omics data, 20 genes were found to be differentially expressed (DEG) between the three possible comparisons obtained (DB vs. IS, DB vs. IR, and IS vs. IR); these data sets have been used to develop predictive models through machine learning (ML) techniques to classify patients with respect to the three categories mentioned previously. All the ML techniques present an accuracy superior to 80%, reaching almost 90% when unifying IR and DB categories.

Exploring the molecular targets for Type 2 diabetes-induced Alzheimer's disease through bioinformatics analysis

Aim: The purpose of this study was to elucidate the potential mechanisms of Alzheimer's disease (AD) induced by Type 2 diabetes mellitus (T2DM) through bioinformatics analysis, to provide new treatment targets for this disease. Methods: We used weighted gene coexpression network analysis and differentially expressed genes analysis to identify significantly differentially expressed genes shared by T2DM and AD. Molecular docking was used to predict possible protein targets for T2DM-induced AD. Results: The direct interaction of CD44 and STAT3 may play a significant role in the development of T2DM-induced AD. Conclusion: A new approach to treating T2DM-associated AD may be provided by these hub genes and their predicted molecular targets.

Type 2 Diabetes and Parkinson's Disease: A Focused Review of Current Concepts

Highly reproducible epidemiological evidence shows that type 2 diabetes (T2D) increases the risk and rate of progression of Parkinson's disease (PD), and crucially, the repurposing of certain antidiabetic medications for the treatment of PD has shown early promise in clinical trials, suggesting that the effects of T2D on PD pathogenesis may be modifiable. The high prevalence of T2D means that a significant proportion of patients with PD may benefit from personalized antidiabetic treatment approaches that also confer neuroprotective benefits. Therefore, there is an immediate need to better understand the mechanistic relation between these conditions and the specific molecular pathways affected by T2D in the brain. Although there is considerable evidence that processes such as insulin signaling, mitochondrial function, autophagy, and inflammation are involved in the pathogenesis of both PD and T2D, the primary aim of this review is to highlight the evidence showing that T2D-associated dysregulation of these pathways occurs not only in the periphery but also in the brain and how this may facilitate neurodegeneration in PD. We also discuss the challenges involved in disentangling the complex relationship between T2D, insulin resistance, and PD, as well as important questions for further research. © 2022 International Parkinson and Movement Disorder Society.

The landscape of expression and alternative splicing variation across human traits

Understanding the consequences of individual transcriptome variation is fundamental to deciphering human biology and disease. We implement a statistical framework to quantify the contributions of 21 individual traits as drivers of gene expression and alternative splicing variation across 46 human tissues and 781 individuals from the Genotype-Tissue Expression project. We demonstrate that ancestry, sex, age, and BMI make additive and tissue-specific contributions to expression variability, whereas interactions are rare. Variation in splicing is dominated by ancestry and is under genetic control in most tissues, with ribosomal proteins showing a strong enrichment of tissue-shared splicing events. Our analyses reveal a systemic contribution of types 1 and 2 diabetes to tissue transcriptome variation with the strongest signal in the nerve, where histopathology image analysis identifies novel genes related to diabetic neuropathy. Our multi-tissue and multi-trait approach provides an extensive characterization of the main drivers of human transcriptome variation in health and disease.

Revealing genetic links of Type 2 diabetes that lead to the development of Alzheimer's disease

Background

A factor leading to Alzheimer's Disease (AD), portrayed by peripheral insulin resistance, is Type 2 diabetes mellitus (T2D). The likelihood of T2D cases would be at boosted danger in alternating AD cases has severe social consequences. Several genes have been detected via gene expression profiling or different techniques; despite the consideration of the utility of numerous of these genes stays insufficient.

Methods

This project is designed to uncover the mutual genomics motifs between AD and T2D via non-negative matrix factorization (NMF) of differentially expressed genes (DEGs) of T2D Mellitus of human cortical neurons of the neurovascular unit gene expression data. A rank factorization value is calculated by employing the combination of the NMF model with the unit invariant knee (UIK) point method. The metagenes are further determined by remarking the enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and gene ontology (GO) enrichment tools. In this study, the most highly expressed genes of metagenes are subjected to protein-protein interaction (PPI) network study to discover the most significant biomarkers of T2D Mellitus in the ageing brain.

Results

We screened the most important shared genes (CDKN1A, COL22A1, EIF4A, GFAP, SLC1A1, and VIM) and essential human molecular pathways that motivate these diseases. The study aimed to validate the most significant hub genes using network-based methods which detected the corresponding relationship between AD and T2D.

Conclusions

Using in silico tools, the computational pipeline has broadly examined transformed pathways and discovered promising biomarkers and drug targets. We validated the most significant hub genes using network-based methods which detected the corresponding relationship between AD and T2D. These consequences on brain cells hypothetically reserve to diabetic Alzheimer's so-called type 3 diabetes (T3D) and may offer promising methodologies for curative intrusion.

Role of mitochondrial DNA in diabetes Mellitus Type I and Type II

Morbidity and mortality from diabetes mellitus and associated illnesses is a major problem across the globe. Anti-diabetic medicines must be improved despite existing breakthroughs in treatment approaches. Diabetes has been linked to mitochondrial dysfunction. As a result, particular mitochondrial diabetes kinds like MIDD (maternally inherited diabetes & deafness) and DAD (diabetic autonomic dysfunction) have been identified and studied (diabetes and Deafness). Some mutations as in mitochondrial DNA (mtDNA), that encodes for a significant portion of mitochondrial proteins as well as mitochondrial tRNA essential for mitochondrial protein biosynthesis, are responsible for hereditary mitochondrial diseases. Tissue-specificity and heteroplasmy have a role in the harmful phenotype of mtDNA mutations, making it difficult to generalise findings from one study to another. There are a huge increase in the number for mtDNA mutations related with human illnesses that have been identified using current sequencing technologies. In this study, we make a list on mtDNA mutations linked with diseases and diabetic illnesses and explore the methods by which they contribute to the pathology's emergence.

Diabetes and dementia: Clinical perspective, innovation, knowledge gaps

The world faces a pandemic-level prevalence of type 2 diabetes. In parallel with this massive burden of metabolic disease is the growing prevalence of dementia as the population ages. The two health issues are intertwined. The Lancet Commission on dementia prevention, intervention, and care was convened to tackle the growing global concern of dementia by identifying risk factors. It concluded, along with other studies, that diabetes as well as obesity and the metabolic syndrome more broadly, which are frequently comorbid, raise the risk of developing dementia. Type 2 diabetes is a modifiable risk factor; however, it is uncertain whether anti-diabetic drugs mitigate risk of developing dementia. Reasons are manifold but constitute a critical knowledge gap in the field. This review outlines studies of type 2 diabetes on risk of dementia, illustrating key concepts. Moreover, it identifies knowledge gaps, reviews strategies to help fill these gaps, and concludes with a series of recommendations to mitigate risk and advance understanding of type 2 diabetes and dementia.

Vascular contributions to cognitive impairment/dementia in diabetes: role of endothelial cells and pericytes

Vascular contributions to cognitive impairment/dementia (VCID) are a leading cause of dementia, a known neurodegenerative disorder characterized by progressive cognitive decline. Although diabetes increases the risks of stroke and the development of cerebrovascular disease, the cellular and vascular mechanisms that lead to VCID in diabetes are yet to be determined. A growing body of research has identified that cerebrovascular cells within the neurovascular complex display an array of cellular responses that impact their survival and reparative properties, which plays a significant role in VCID development. Specifically, endothelial cells and pericytes are the primary cell types that have gained much attention in dementia-related studies due to their molecular and phenotypic heterogeneity. In this review, we will discuss the various morphological subclasses of endothelial cells and pericytes as well as their relative distribution throughout the cerebrovasculature. Furthermore, the use of diabetic and stroke animal models in preclinical studies has provided more insight into the impact of sex differences on cerebral vascularization in progressive VCID. Understanding how cellular responses and sex differences contribute to endothelial cell and pericyte survival and function will set the stage for the development of potential preventive therapies for dementia-related disorders in diabetes.

Profiling cell-type specific gene expression in post-mortem human brain samples through laser capture microdissection

The transcriptome of a cell constitutes an essential piece of cellular identity and contributes to the multifaceted complexity and heterogeneity of cell-types within the mammalian brain. Thus, while a wealth of studies have investigated transcriptomic alterations underlying the pathophysiology of diseases of the brain, their use of bulk-tissue homogenates makes it difficult to tease apart whether observed differences are explained by disease state or cellular composition. Cell-type-specific enrichment strategies are, therefore, crucial in the context of gene expression profiling. Laser capture microdissection (LCM) is one such strategy that allows for the capture of specific cell-types, or regions of interest, under microscopic visualization. In this review, we focus on using LCM for cell-type specific gene expression profiling in post-mortem human brain samples. We begin with a discussion of various LCM systems, followed by a walk-through of each step in the LCM to gene expression profiling workflow and a description of some of the limitations associated with LCM. Throughout the review, we highlight important considerations when using LCM with post-mortem human brain samples. Whenever applicable, commercially available kits that have proven successful in the context of LCM with post-mortem human brain samples are described.

Identification and Experimental Validation of Marker Genes between Diabetes and Alzheimer’s Disease

Currently, Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) are widely prevalent in the elderly population, and accumulating evidence implies a strong link between them. For example, patients with T2DM have a higher risk of developing neurocognitive disorders, including AD, but the exact mechanisms are still unclear. This time, by combining bioinformatics analysis and in vivo experimental validation, we attempted to find a common biological link between AD and T2DM. We firstly downloaded the gene expression profiling (AD: GSE122063; T2DM: GSE161355) derived from the temporal cortex. To find the associations, differentially expressed genes (DEGs) of the two datasets were filtered and intersected. Based on them, enrichment analysis was carried out, and the least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination (SVM-RFE) algorithms were used to identify the specific genes. After verifying in the external dataset and in the samples from the AD and type 2 diabetes animals, the shared targets of the two diseases were finally determined. Based on them, the ceRNA networks were constructed. Besides, the logistic regression and single-sample gene set enrichment analysis (ssGSEA) were performed. As a result, 62 DEGs were totally identified between AD and T2DM, and the enrichment analysis indicated that they were much related to the function of synaptic vesicle and MAPK signaling pathway. Based on the evidence from external dataset and RT-qPCR, CARTPT, EPHA5, and SERPINA3 were identified as the marker genes in both diseases, and their clinical significance and biological functions were further analyzed. In conclusion, discovering and exploring the marker genes that are dysregulated in both 2 diseases could help us better comprehend the intrinsic relationship between T2DM and AD, which may inspire us to develop new strategies for facing the dilemmas of clinical or basic research in cognitive dysfunction.

High glucose and palmitic acid induces neuronal senescence by NRSF/REST elevation and the subsequent mTOR-related autophagy suppression

Cell senescence is a basic aging mechanism. Previous studies have found that the cellular senescence in adipose tissue and other tissues, such as the pancreas, muscle and liver, is associated with the pathogenesis and progression of type 2 diabetes; however, strong evidence of whether diabetes directly causes neuronal senescence in the brain is still lacking. In this study, we constructed a high glucose and palmitic acid (HGP) environment on PC12 neuronal cells and primary mouse cortical neurons to simulate diabetes. Our results showed that after HGP exposure, neurons exhibited obvious senescence-like phenotypes, including increased NRSF/REST level, mTOR activation and cell autophagy suppression. Downregulation of NRSF/REST could remarkably alleviate p16, p21 and γH2A.X upregulations induced by HGP treatment, and enhance mTOR-autophagy of neurons. Our results suggested that the diabetic condition could directly induce neuronal senescence, which is mediated by the upregulation of NRSF/REST and subsequent reduction of mTOR-autophagy.

Overview of Transcriptomic Research on Type 2 Diabetes: Challenges and Perspectives

Type 2 diabetes (T2D) is a common chronic disease whose etiology is known to have a strong genetic component. Standard genetic approaches, although allowing for the detection of a number of gene variants associated with the disease as well as differentially expressed genes, cannot fully explain the hereditary factor in T2D. The explosive growth in the genomic sequencing technologies over the last decades provided an exceptional impetus for transcriptomic studies and new approaches to gene expression measurement, such as RNA-sequencing (RNA-seq) and single-cell technologies. The transcriptomic analysis has the potential to find new biomarkers to identify risk groups for developing T2D and its microvascular and macrovascular complications, which will significantly affect the strategies for early diagnosis, treatment, and preventing the development of complications. In this article, we focused on transcriptomic studies conducted using expression arrays, RNA-seq, and single-cell sequencing to highlight recent findings related to T2D and challenges associated with transcriptome experiments.

Cerebral Microvascular Senescence and Inflammation in Diabetes

Stress-induced premature senescence can contribute to the accelerated metabolic aging process in diabetes. Progressive accumulation of senescent cells in the brain, especially those displaying the harmful inflammatory senescence-associated secretory phenotype (SASP), may lead to cognitive impairment linked with metabolic disturbances. In this context, the senescence within the neurovascular unit (NVU) should be studied as much as in the neurons as emerging evidence shows that neurogliovascular communication is critical for brain health. It is also known that cerebrovascular dysfunction and decreased cerebral blood flow (CBF) precede the occurrence of neuronal pathologies and overt cognitive impairment. Various studies have shown that endothelial cells, the major component of the NVU, acquire a senescent phenotype via various molecular mediators and pathways upon exposure to high glucose and other conditions mimicking metabolic disturbances. In addition, senescence in the other cells that are part of the NVU, like pericytes and vascular smooth cells, was also triggered upon exposure to diabetic conditions. The senescence within the NVU may compromise functional and trophic coupling among glial, vascular, and neuronal cells and the resulting SASP may contribute to the chronic neurovascular inflammation observed in Alzheimer's Disease and Related Dementias (ADRD). The link between diabetes-mediated cerebral microvascular dysfunction, NVU senescence, inflammation, and cognitive impairment must be widely studied to design therapeutic strategies.

Detection of molecular signatures and pathways shared by Alzheimer's disease and type 2 diabetes

Alzheimer's disease (AD) and type 2 diabetes (T2D) are common in the general elderly population, conferring heavy individual, social, and economic stresses on families and society. Accumulating evidence indicates T2D to be a risk factor for AD. However, the underlying mechanisms for this association are largely unknown. This study aimed to identify the shared molecular signatures between AD and T2D through integrated analysis of temporal cortex gene expression data. Gene Ontology (GO) and pathway enrichment analysis, protein over-representation analysis, protein-protein interaction, DEG-transcription factor interactions, DEG-microRNA interactions, protein-drug interactions, gene-disease association analysis, and protein subcellular localization analysis of the common DEGs were performed. We identified 16 common DEGs between the two datasets, which were mainly enriched in the biological processes of apoptosis, autophagy, inflammation, and hemostasis. We also identified five hub proteins encoded by the DEGs, five central regulatory transcription factors, and six microRNAs. Protein-drug interaction analysis showed C1QB to be associated with different drugs. Gene-disease association analysis revealed that hub genes, SFN and ITGB2, were actively engaged in other diseases. Collectively, these findings provide new insights into shared molecular mechanisms between AD and T2D and provide novel candidate targets for therapeutic intervention.

A Comprehensive Review of Neuronal Changes in Diabetics

There has been an exponential rise in diabetes mellitus (DM) cases on a global scale. Diabetes affects almost every system of the body, and the nervous system is no exception. Although the brain is dependent on glucose, providing it with the energy required for optimal functionality, glucose also plays a key role in the regulation of oxidative stress, cell death, among others, which furthermore contribute to the pathophysiology of neurological disorders. The variety of biochemical processes engaged in this process is only matched by the multitude of clinical consequences resulting from it. The wide-ranging effects on the central and peripheral nervous system include, but are not limited to axonopathies, neurodegenerative diseases, neurovascular diseases, and general cognitive impairment. All language search was conducted on MEDLINE, COCHRANE, EMBASE, and GOOGLE SCHOLAR till September 2021. The following search strings and Medical Subject Headings (MeSH terms) were used: "Diabetes Mellitus," "CNS," "Diabetic Neuropathy," and "Insulin." We explored the literature on diabetic neuropathy, covering its epidemiology, pathophysiology with the respective molecular pathways, clinical consequences with a special focus on the central nervous system and finally, measures to prevent and treat neuronal changes. Diabetes is slowly becoming an epidemic, rapidly increasing the clinical burden on account of its wide-ranging complications. This review focuses on the neuronal changes occurring in diabetes such as the impact of hyperglycemia on brain function and structure, its association with various neurological disorders, and a few diabetes-induced peripheral neuropathic changes. It is an attempt to summarize the relevant literature about neuronal consequences of DM as treatment options available today are mostly focused on achieving better glycemic control; further research on novel treatment options to prevent or delay the progression of neuronal changes is still needed.

The Role of Mitochondrial Mutations and Chronic Inflammation in Diabetes

Diabetes mellitus and related disorders significantly contribute to morbidity and mortality worldwide. Despite the advances in the current therapeutic methods, further development of anti-diabetic therapies is necessary. Mitochondrial dysfunction is known to be implicated in diabetes development. Moreover, specific types of mitochondrial diabetes have been discovered, such as MIDD (maternally inherited diabetes and deafness) and DAD (diabetes and Deafness). Hereditary mitochondrial disorders are caused by certain mutations in the mitochondrial DNA (mtDNA), which encodes for a substantial part of mitochondrial proteins and mitochondrial tRNA necessary for mitochondrial protein synthesis. Study of mtDNA mutations is challenging because the pathogenic phenotype associated with such mutations depends on the level of its heteroplasmy (proportion of mtDNA copies carrying the mutation) and can be tissue-specific. Nevertheless, modern sequencing methods have allowed describing and characterizing a number of mtDNA mutations associated with human disorders, and the list is constantly growing. In this review, we provide a list of mtDNA mutations associated with diabetes and related disorders and discuss the mechanisms of their involvement in the pathology development.