Gene Expression Profiling Identifies Downregulation of the Neurotrophin-MAPK Signaling Pathway in Female Diabetic Peripheral Neuropathy Patients

Exploring the Potential Role of Oligodendrocyte-Associated PIP4K2A in Alzheimer's Disease Complicated with Type 2 Diabetes Mellitus via Multi-Omic Analysis

Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) are two common diseases that affect the elderly population worldwide. The identification of common genes associated with AD and T2DM holds promise for potential biomarkers and intriguing pathogenesis of these two complicated diseases. This study utilized a comprehensive approach by integrating transcriptome data from multiple cohorts, encompassing both AD and T2DM. The analysis incorporated various data types, including blood and tissue samples as well as single-cell datasets, allowing for a detailed assessment of gene expression patterns. From the brain region-specific single-cell analysis, PIP4K2A, which encodes phosphatidylinositol-5-phosphate 4-kinase type 2 alpha, was found to be expressed mainly in oligodendrocytes compared to other cell types. Elevated levels of PIP4K2A in AD and T2DM patients' blood were found to be associated with key cellular processes such as vesicle-mediated transport, negative regulation of autophagosome assembly, and cytosolic transport. The identification of PIP4K2A's potential roles in the cellular processes of AD and T2DM offers valuable insights into the development of biomarkers for diagnosis and therapy, especially in the complication of these two diseases.

Identification of Differentially Expressed Genes and Protein-Protein Interaction in Patients With COVID-19 and Diabetes Peripheral Neuropathy: A Bioinformatics and System Biology Approach

The coronavirus disease 2019 (COVID-19) pandemic has had a significant impact globally, resulting in a higher death toll and persistent health issues for survivors, particularly those with pre-existing medical conditions. Numerous studies have demonstrated a strong correlation between catastrophic COVID-19 results and diabetes. To gain deeper insights, we analysed the transcriptome dataset from COVID-19 and diabetic peripheral neuropathic patients. Using the R programming language, differentially expressed genes (DEGs) were identified and classified based on up and down regulations. The overlaps of DEGs were then explored between these groups. Functional annotation of those common DEGs was performed using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Bio-Planet, Reactome, and Wiki pathways. A protein-protein interaction (PPI) network was created with bioinformatics tools to understand molecular interactions. Through topological analysis of the PPI network, we determined hub gene modules and explored gene regulatory networks (GRN). Furthermore, the study extended to suggesting potential drug molecules for the identified mutual DEG based on the comprehensive analysis. These approaches may contribute to understanding the molecular intricacies of COVID-19 in diabetic peripheral neuropathy patients through insights into potential therapeutic interventions.

Diagnostic biomarker for type 2 diabetic peripheral neuropathy via comprehensive bioinformatics analysis

BACKGROUND

Diabetic peripheral neuropathy (DPN) is a common complication of Type 2 diabetes mellitus (T2DM), which frequently results in disabling neuropathic pain and lower-limb amputation. The identification of noninvasive biomarkers for DPN may help early detection and individualized treatment of DPN.

METHODS

In this study, we identified differentially expressed genes (DEGs) between DPN and the control based on blood-source (GSE95849) and tissue-source gene expression profiles (GSE143979) from the Gene Expression Omnibus (GEO) database using limma, edgeR, and DESeq2 approaches. KEGGG and GO functional enrichments were performed. Hub genes and their correlation with infiltrating immune cells were analyzed. Real-time quantitative polymerase chain reaction (RT-qPCR) was used to quantify hub gene expression.

RESULTS

In total, 144 DEGs between DPN and the control were identified. Functional enrichment revealed that the DEGs were mainly enriched in immune-related pathways like the Fc epsilon receptor Ig signaling pathway. By protein-protein interaction (PPI) network analysis, FCER1G, SYK, ITGA4, F13A1, MS4A2, and PTK2B were screened as hub genes with higher expression in DPN patients, among which half were immune genes (FCER1G, PTK2B, and SYK). RT-qPCR demonstrated that mRNA expression of FCER1G, PTK2B, and SYK was significantly increased in patients with DPN compared with both diabetic nonperipheral neuropathy (DNN) and normal subjects. The area under the receiver operating characteristic (ROC) curve of FCER1G, PTK2B, and SYK was 0.84, 0.81, and 0.73, respectively, suggesting their great advantages as diagnostic biomarkers to predict the progression of neuropathy in T2DM. Further analysis indicated that the expression of FCER1G, PTK2B, and SYK was negatively correlated with the cell proportion of significantly altered resting natural killer cells, T follicular helper cells, and activated mast cells, but positively correlated with monocytes.

CONCLUSIONS

Our findings demonstrated FCER1G, PTK2B, and SYK are potential diagnostic biomarkers and therapeutic targets for DPN, which provides new insight into DPN pathogenesis and therapies.

The Relationship Between UA/HDL and Diabetic Peripheral Neuropathy: A Cross-Sectional Analysis

Purpose

This study was designed to analyze correlations between the uric acid to high-density lipoprotein cholesterol ratio (UHR) and peripheral nerve conduction velocity (NCV) among type 2 diabetes mellitus (T2DM) patients.

Patients and Methods

This was a single-center cross-sectional analysis of 324 T2DM patients. All patients were separated into a group with normal NCV (NCVN) and a group with abnormal NCV (NCVA). Patients were also classified into groups with low and high UHR values based on the median UHR in this study cohort. Neurophysiological data including motor and sensory conduction velocity (MCV and SCV, respectively) were measured for all patients.

Results

Relative to patients with low UHR values, those in the high UHR group presented with greater NCVA prevalence (P = 0.002). UHR remained negatively correlated with bilateral superficial peroneal nerve SCV, bilateral common peroneal nerve MCV, bilateral ulnar nerve SCV, and bilateral right median nerve MCV even after adjustment for confounding factors. UHR was identified as an NCVA-related risk factor, with a 1.370-fold increase in NCVA prevalence for every unit rise in UHR (P < 0.001).

Conclusion

These results identify UHR as a risk factor associated with NCVA that was independently negatively associated with NCV among T2DM patients.

Application of multiple machine learning approaches to determine key pyroptosis molecules in type 2 diabetes mellitus

Objective

Pyroptosis, a lytic and inflammatory programmed cell death, has been implicated in type 2 diabetes mellitus (T2DM) and its complications. Nonetheless, it remains elusive exactly which pyroptosis molecule exerts an essential role in T2DM, and this study aims to solve such issue.

Methods

Transcriptional profiling datasets of T2DM, i.e., GSE20966, GSE95849, and GSE26168, were acquired. Four machine learning models, namely, random forest, support vector machine, extreme gradient boosting, and generalized linear modeling, were built based on pyroptosis genes. A nomogram of key pyroptosis genes was also generated, and the clinical value was appraised via calibration curves and decision curve analysis. Immune infiltration was inferred utilizing CIBERSORT. Drug-druggable target relationships were acquired from the Drug Gene Interaction Database. Through WGCNA, key pyroptosis-relevant genes were selected.

Results

Most pyroptosis genes exhibited upregulation in T2DM relative to controls, indicating the activity of pyroptosis in T2DM. The SVM model composed of BAK1, CHMP2B, NLRP6, PLCG1, and TIRAP exhibited the best performance in T2DM diagnosis, with AUC = 1. The nomogram can predict the risk of T2DM for clinical practice. NK cells resting exhibited a lower abundance in T2DM versus normal specimens, with a higher abundance of neutrophils. NLRP6 was positively linked with neutrophils. Drugs (keracyanin, 9,10-phenanthrenequinone, diclofenac, phosphomethylphosphonic acid adenosyl ester, acetaminophen, cefixime, aspirin, ustekinumab) potentially targeted the key pyroptosis genes. Additionally, CHMP2B-relevant genes were determined.

Conclusion

Altogether, this work proposes the key pyroptosis genes in T2DM, which might become possible molecules for the management and treatment of T2DM and its complications.

Exploring the common pathogenesis of Alzheimer's disease and type 2 diabetes mellitus via microarray data analysis

Background

Alzheimer's Disease (AD) and Type 2 Diabetes Mellitus (DM) have an increased incidence in modern society. Although more and more evidence has supported that DM is prone to AD, the interrelational mechanisms remain fully elucidated.

Purpose

The primary purpose of this study is to explore the shared pathophysiological mechanisms of AD and DM.

Methods

Download the expression matrix of AD and DM from the Gene Expression Omnibus (GEO) database with sequence numbers GSE97760 and GSE95849, respectively. The common differentially expressed genes (DEGs) were identified by limma package analysis. Then we analyzed the six kinds of module analysis: gene functional annotation, protein-protein interaction (PPI) network, potential drug screening, immune cell infiltration, hub genes identification and validation, and prediction of transcription factors (TFs).

Results

The subsequent analyses included 339 common DEGs, and the importance of immunity, hormone, cytokines, neurotransmitters, and insulin in these diseases was underscored by functional analysis. In addition, serotonergic synapse, ovarian steroidogenesis, estrogen signaling pathway, and regulation of lipolysis are closely related to both. DEGs were input into the CMap database to screen small molecule compounds with the potential to reverse AD and DM pathological functions. L-690488, exemestane, and BMS-345541 ranked top three among the screened small molecule compounds. Finally, 10 essential hub genes were identified using cytoHubba, including PTGS2, RAB10, LRRK2, SOS1, EEA1, NF1, RAB14, ADCY5, RAPGEF3, and PRKACG. For the characteristic Aβ and Tau pathology of AD, RAPGEF3 was associated significantly positively with AD and NF1 significantly negatively with AD. In addition, we also found ADCY5 and NF1 significant correlations with DM phenotypes. Other datasets verified that NF1, RAB14, ADCY5, and RAPGEF3 could be used as key markers of DM complicated with AD. Meanwhile, the immune cell infiltration score reflects the different cellular immune microenvironments of the two diseases.

Conclusion

The common pathogenesis of AD and DM was revealed in our research. These common pathways and hub genes directions for further exploration of the pathogenesis or treatment of these two diseases.

Shared and specific biological signalling pathways for diabetic retinopathy, peripheral neuropathy and nephropathy by high-throughput sequencing analysis

OBJECTIVES

We aimed to explore the shared and specific signalling pathways involved in diabetic retinopathy (DR), diabetic peripheral neuropathy (DPN) and diabetic nephropathy (DN).

METHODS

Differentially expressed mRNAs and lncRNAs were identified by high-throughput sequencing. Subsequently, functional enrichment analysis, protein-protein interaction (PPI) analysis and lncRNAs-mRNAs networks were conducted to determine the pathogenic mechanisms underlying DR, DPN and DN.

RESULTS

Twenty-six biological pathways were shared among DR, DPN and DN groups compared to the type 2 diabetes mellitus (T2DM) group without complications, and most of the shared pathways and core proteins were involved in immune and inflammatory responses of microvascular damage. Cytokine‒cytokine receptor interactions and chemokine signalling pathway were the most significant and specific pathways for DR, and the lncRNA‒mRNA regulatory networks affected DR by targeting these pathways. Sphingolipid metabolism and neuroactive ligand-receptor pathways were found to be specific for the pathogenesis of DPN. Moreover, multiple amino acid metabolic pathways were involved in the occurrence and progression of DN.

CONCLUSIONS

Diabetic retinopathy, DPN and DN exhibited commonality and heterogeneity simultaneously. The shared pathologic mechanisms underlying these diabetic complications are involved in diabetic microvascular damage via immune and inflammatory pathways. Our findings predict several biomarkers and therapeutic targets for these diabetic complications.

Toll-like receptor 9 (TLR9) gene deletion-mediated fracture healing in type II diabetic osteoporosis associates with inhibition of the nuclear factor-kappa B (NF-κB) signaling pathway

Diabetes is characterized by increased fracture risk. Evidence from in vivo studies is lacking for anti-fracture strategies in diabetes. Our microarray analyses predicted association of Toll-like receptor 9 (TLR9) with both diabetes and osteoporosis, which was the focus of this work in a murine model of type II diabetic osteoporosis (T2DOP). A T2DOP model with fracture was established in TLR9 knockout (TLR9^−/−) mice, which were then treated with the NF-κB signaling pathway inhibitor (PDTC) and activator (TNF-α). The obtained data suggested that TLR9 knockout augmented regeneration of bone tissues and cartilage area in the callus, and diminished fibrous tissues in T2DOP mice. Moreover, TLR9 depletion significantly affected bone mineral density (BMD), bone volume/tissue volume (BV/TV), connectivity density, trabecular number, trabecular separation and trabecular thickness, thus promoting fracture recovery. Bone morphology and structure were also improved in response to TLR9 depletion in T2DOP mice. TLR9 depletion inactivated NF-κB signaling in T2DOP mice. PDTC was found to enhance fracture healing in T2DOP mice, while TNF-α negated this effect. Collectively, these data indicate that TLR9 depletion may hold anti-fracture properties, making it a potential therapeutic target for T2DOP.

Abbreviations: Diabetic osteoporosis (DOP); bone mineral density (BMD); Toll-like receptors (TLRs); type 2 diabetes (T2D); Toll-like receptor 9 (TLR9); nuclear factor-kappaB (NF-κB); streptozotocin (STZ); type 2 diabetic osteoporosis (T2DOP); Gene Expression Omnibus (GEO); Kyoto encyclopedia of genes and genomes (KEGG); pyrrolidine dithiocarbamate (PDTC); computed tomography (CT); Hematoxylin–eosin (HE); bone morphogenetic protein 7 (BMP7); analysis of variance (ANOVA);

Gene expression profiling reveals candidate biomarkers and probable molecular mechanisms in chronic stress

Chronic stress refers to nonspecific systemic reactions under the over-stimulation of different external and internal factors for a long time. Previous studies confirmed that chronic psychological stress had a negative effect on almost all tissues and organs. We intended to further identify potential gene targets related to the pathogenesis of chronic stress-induced consequences involved in different diseases. In our study, mice in the model group lived under the condition of chronic unpredictable mild stress (CUMS) until they expressed behaviors like depression which were supposed to undergo chronic stress. We applied high-throughput RNA sequencing to assess mRNA expression and obtained transcription profiles in lung tissue from CUMS mice and control mice for analysis. In view of the prediction of high-throughput RNA sequences and bioinformatics software, and mRNA regulatory network was constructed. First, we conducted differentially expressed genes (DEGs) and obtained 282 DEGs between CUMS (group A) and the control model (group B). Then, we conducted functional and pathway enrichment analyses. In general, the function of upregulated regulated DEGs is related to immune and inflammatory responses. PPI network identified several essential genes, of which ten hub genes were related to the T cell receptor signaling pathway. qRT-PCR results verified the regulatory network of mRNA. The expressions of CD28, CD3e, and CD247 increased in mice with CUMS compared with that in control. This illustrated immune pathways are related to the pathological molecular mechanism of chronic stress and may provide information for identifying potential biomarkers and early detection of chronic stress.

Identification of Up-Regulated ANXA3 Resulting in Fracture Non-Union in Patients With T2DM

Diabetes mellitus is a metabolic disorder that increases fracture risk and interferes with bone formation and impairs fracture healing. Genomic studies on diabetes and fracture healing are lacking. We used a weighted co-expression network analysis (WGCNA) method to identify susceptibility modules and hub genes associated with T2DM and fracture healing. First, we downloaded the GSE95849, GSE93213, GSE93215, and GSE142786 data from the Gene Expression Omnibus (GEO) website, analyzed differential expression genes and constructed a WGCNA network. Second, we screened out 30 hub genes, which were found to be enriched in neutrophil activation, translational initiation, RAGE receptor binding, propanoate metabolism, and other pathways through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) analyses. Third, we searched for genes related to bone metabolism and fracture healing in the published genome-wide single nucleotide polymorphism (SNP) data, built a protein-protein interaction (PPI) network with hub genes, and found that they were associated with metabolic process, blood vessel development, and extracellular matrix organization. ANXA3 was identified as the biomarker based on gene expression and correlation analysis. And the AUC value of it was 0.947. Fourth, we explored that ANXA3 was associated with neutrophils in fracture healing process by single-cell RNA sequencing analysis. Finally, we collected clinical patient samples and verified the expression of ANXA3 by qRT-PCR in patents with T2DM and fracture non-union. In conclusion, this is the first genomics study on the effect of T2DM on fracture healing. Our study identified some characteristic modules and hub genes in the etiology of T2DM-associated fracture non-union, which may help to further investigate the molecular mechanisms. Up-regulated ANXA3 potentially contributed to fracture non-union in T2DM by mediating neutrophils. It can be a prognostic biomarker and potential therapeutic target.

Transcriptomic studies revealed pathophysiological impact of COVID-19 to predominant health conditions

Despite the association of prevalent health conditions with coronavirus disease 2019 (COVID-19) severity, the disease-modifying biomolecules and their pathogenetic mechanisms remain unclear. This study aimed to understand the influences of COVID-19 on different comorbidities and vice versa through network-based gene expression analyses. Using the shared dysregulated genes, we identified key genetic determinants and signaling pathways that may involve in their shared pathogenesis. The COVID-19 showed significant upregulation of 93 genes and downregulation of 15 genes. Interestingly, it shares 28, 17, 6 and 7 genes with diabetes mellitus (DM), lung cancer (LC), myocardial infarction and hypertension, respectively. Importantly, COVID-19 shared three upregulated genes (i.e. MX2, IRF7 and ADAM8) with DM and LC. Conversely, downregulation of two genes (i.e. PPARGC1A and METTL7A) was found in COVID-19 and LC. Besides, most of the shared pathways were related to inflammatory responses. Furthermore, we identified six potential biomarkers and several important regulatory factors, e.g. transcription factors and microRNAs, while notable drug candidates included captopril, rilonacept and canakinumab. Moreover, prognostic analysis suggests concomitant COVID-19 may result in poor outcome of LC patients. This study provides the molecular basis and routes of the COVID-19 progression due to comorbidities. We believe these findings might be useful to further understand the intricate association of these diseases as well as for the therapeutic development.

Analysis of Communal Molecular Mechanism and Potential Therapeutic Targets in Heart Failure and Type 2 Diabetes Mellitus

Background

Although increasing evidence has suggested an interaction between heart failure (HF) and Type 2 diabetes mellitus (T2DM), the common mechanisms of the two diseases remain unclear. Therefore, this study aimed to obtain the differentially expressed genes (DEGs) and potential biomarkers or therapeutic targets in HF and T2DM.

Methods

The communal DEGs of HF and T2DM were identified by analyzing the two microarray datasets (GSE84796 and GSE95849), and functional annotation was performed for the communal DEGs to uncover the potential molecular mechanisms of HF and T2DM. Subsequently, STRING database and Cytoscape software were used to construct the protein-protein interaction (PPI) network and screen the hub genes. Finally, co-expression and drug-gene interaction prediction analysis and mRNA-miRNA regulatory network analysis were performed for hub genes.

Results

A total of 233 up-regulated genes and 3 down-regulated genes were found between HF and T2DM. The functional enrichment of DEGs and genes in each four modules were mainly involved in immunity. In addition, five hub genes were identified from PPI network, including SYK, SELL, RAC2, TLR8 and ITGAX.

Conclusion

The communal DEGs and hub genes identified in this research contribute to discover the underlying biological mechanisms and presents potential biomarkers or therapeutic targets in HF and T2DM.

LTB4-Driven Inflammation and Increased Expression of ALOX5/ACE2 During Severe COVID-19 in Individuals With Diabetes

Diabetes is a known risk factor for severe coronavirus disease 2019 (COVID-19), the disease caused by the new coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there is a lack of knowledge about the mechanisms involved in the evolution of COVID-19 in individuals with diabetes. We aimed to evaluate whether the chronic low-grade inflammation of diabetes could play a role in the development of severe COVID-19. We collected clinical data and blood samples of patients with and without diabetes hospitalized for COVID-19. Plasma samples were used to measure inflammatory mediators and peripheral blood mononuclear cells, for gene expression analysis of the SARS-CoV-2 main receptor system (ACE2/TMPRSS2), and for the main molecule of the leukotriene B₄ (LTB₄) pathway (ALOX5). We found that diabetes activates the LTB₄ pathway and that during COVID-19 it increases ACE2/TMPRSS2 as well as ALOX5 expression. Diabetes was also associated with COVID-19-related disorders, such as reduced oxygen saturation as measured by pulse oximetry/fraction of inspired oxygen (FiO₂) and arterial partial pressure of oxygen/FiO₂ levels, and increased disease duration. In addition, the expressions of ACE2 and ALOX5 are positively correlated, with increased expression in patients with diabetes and COVID-19 requiring intensive care assistance. We confirmed these molecular results at the protein level, where plasma LTB₄ is significantly increased in individuals with diabetes. In addition, IL-6 serum levels are increased only in individuals with diabetes requiring intensive care assistance. Together, these results indicate that LTB₄ and IL-6 systemic levels, as well as ACE2/ALOX5 blood expression, could be early markers of severe COVID-19 in individuals with diabetes.

Acupuncture Can Play an Antidepressant Role by Regulating the Intestinal Microbes and Neurotransmitters in a Rat Model of Depression

BACKGROUND Acupuncture, which has many good effects and few adverse effects, is widely recognized as an alternative therapy for depression in clinical practice. This study aimed to explore the mechanism of acupuncture in antidepressant treatment. MATERIAL AND METHODS In this experiment, Sprague-Dawley rats were randomly divided into 4 groups: control, chronic unpredictable mild stress (CUMS), acupuncture, and fluoxetine groups. The CUMS, acupuncture, and fluoxetine groups were orphaned and subjected to chronic unpredictable stress for 6 weeks, and the acupuncture and fluoxetine groups were treated with their respective intervention in weeks 4-6. The body weight of rats was monitored weekly. After behavioral tests were completed, serum, feces, and hippocampal tissue of rats were collected. RESULTS The results showed that the acupuncture and fluoxetine treatments could alleviate the behavioral changes caused by CUMS. The treatments increased the total distance of rat crossing in the open-field test, prolonged the activity time of the open cross maze in the open arm, and improved the rate of sucrose consumption in the sucrose preference test. In addition, both the decreased level of dopamine (DA) and 5-hydroxytryptamine (5-HT) in serum and hippocampus caused by CUMS were improved after the treatments with acupuncture and fluoxetine, and the decreased expression of brain-derived neurotrophic factor signaling and the astrocytes in the hippocampus caused by CUMS were increased after the treatments with acupuncture and fluoxetine. Acupuncture and fluoxetine also decreased the ß isoform of calmodulin-dependent protein kinase II in the hippocampus, which was increased by CUMS. Furthermore, acupuncture regulated intestinal microbial disorders caused by CUMS, which reduced the relative abundance ratio of Bacteroidetes/Firmicutes in rats. CONCLUSIONS Our experimental results indicate that acupuncture can alleviate depression-like performance in CUMS rats by regulating intestinal microbes and neurotransmitters.

Upregulation of T Cell Receptor Signaling Pathway Components in Gestational Diabetes Mellitus Patients: Joint Analysis of mRNA and circRNA Expression Profiles

OBJECTIVE

Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy, and its pathogenesis is still unclear. Studies have shown that circular RNAs (circRNAs) can regulate blood glucose levels by targeting mRNAs, but the role of circRNAs in GDM is still unknown. Therefore, a joint microarray analysis of circRNAs and their target mRNAs in GDM patients and healthy pregnant women was carried out.

METHODS

In this study, microarray analyses of mRNA and circRNA in 6 GDM patients and 6 healthy controls were conducted to identify the differentially expressed mRNA and circRNA in GDM patients, and some of the discovered mRNAs and circRNAs were further validated in additional 56 samples by quantitative realtime PCR (qRT-PCR) and droplet digital PCR (ddPCR).

RESULTS

Gene ontology and pathway analyses showed that the differentially expressed genes were significantly enriched in T cell immune-related pathways. Cross matching of the differentially expressed mRNAs and circRNAs in the top 10 KEGG pathways identified 4 genes (CBLB, ITPR3, NFKBIA, and ICAM1) and 4 corresponding circRNAs (circ-CBLB, circ-ITPR3, circ-NFKBIA, and circ-ICAM1), and these candidates were subsequently verified in larger samples. These differentially expressed circRNAs and their linear transcript mRNAs were all related to the T cell receptor signaling pathway, and PCR results confirmed the initial microarray results. Moreover, circRNA/miRNA/mRNA interactions and circRNA-binding proteins were predicted, and circ-CBLB, circ-ITPR3, and circ-ICAM1 may serve as GDM-related miRNA sponges and regulate the expression of CBLB, ITPR3, NFKBIA, and ICAM1 in cellular immune pathways.

CONCLUSION

Upregulation of T cell receptor signaling pathway components may represent the major pathological mechanism underlying GDM, thus providing a potential approach for the prevention and treatment of GDM.

Transcriptome-wide Association Study Identifies Genetically Dysregulated Genes in Diabetic Neuropathy

BACKGROUND

Complications are the main cause of the disease burden of diabetes. Genes determining the development and progression of diabetic complications remain to be identified. Diabetic neuropathy is the most common and debilitating complication and mainly affects the nerves of legs and feet. In this study, we attempted to identify diabetic neuropathy-specific genes from reliable large-scale genome-wide association studies (GWASs) for diabetes perse.

METHODS

Taking advantage of publicly available data, we initially converted the GWAS signals to transcriptomic profiles in the tibial nerve using the functional summary-based imputation (FUSION) algorithm. The FUSION-derived genes were then checked to determine whether they were differentially expressed in the sciatic nerve of mouse models of diabetic neuropathy. The dysregulated genes identified in the sciatic nerve were explored in the blood of patients with diabetes.

RESULTS

We found that eleven out of 452 FUSION-derived genes were regulated by diabetes GWAS loci and were altered in the sciatic nerve of mouse models with early-stage neuropathy. Among the eleven genes, significant (P-value<0.05) expression alterations of HSD17B4, DHX32, MERTK, and SFXN4 could be detected in the blood of human patients.

CONCLUSIONS

Our analyses identified genes with an effect in the sciatic nerve and provided the possibility of noninvasive early detection of diabetic neuropathy.

Identification of Key Genes Involved in Diabetic Peripheral Neuropathy Progression and Associated with Pancreatic Cancer

INTRODUCTION

Diabetes mellitus (DM) patients suffer from high morbidity and premature mortality due to various diabetic complications and even cancers. Therefore, this study aimed to identify key genes involved in the pathogenesis of diabetic peripheral neuropathy (DPN) and pancreatic cancer (PC).

METHODS

We analyzed three gene expression profiles (GSE95849, GSE28735 and GSE59953) to obtain differentially expressed genes (DEGs). Then, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was then used to establish a protein-protein interaction (PPI) network. The MCODE and cytoHubba plug-ins of Cytoscape were used to select hub genes. Finally, survival analysis of the hub genes was performed using the Kaplan-Meier plotter and GEPIA online tool.

RESULTS

We first analyzed GSE95849 to obtain DPN-related genes. DEGs were obtained from three groups in GSE95849. The DEGs were enriched in the Toll-like receptor signaling pathway, hematopoietic cell lineage and chemokine signaling pathway. Importantly, we identified three shared genes as hub genes, including TLR4, CCR2 and MMP9. We then analyzed and integrated GSE95849 and GSE28735 to obtain genes common in DM and PC. A total of 58 mutual DEGs were identified, and these DEGs were enriched in the ECM-receptor interaction, focal adhesion and pathways in cancer. Five hub genes (including PLAU, MET, CLU, APOL1 and MMP9) were associated with the overall survival of PC patients. However, the results from the analysis of GSE59953 showed that hyperglycemia or TGF-β1 treatment did not affect the expression level of these hub genes, but the DEGs based on hyperglycemia or TGF-β1 treatment were mostly enriched in the ECM-receptor interaction, focal adhesion and pathways in cancer. Finally, functional enrichment analysis of MMP9 showed that significant genes correlated with MMP9 were associated with the tumorigenicity of cancers, insulin resistance, development of DM and inflammation.

CONCLUSION

In summary, inflammation and immunity-related pathways may play an important role in DM and DPN, while the ECM-receptor interaction, focal adhesion and pathways in cancer pathways may play significant roles in DM and PC. MMP9 may be used as a prognostic marker for PC and may be helpful for the treatment of DM, DPN and PC.

Association between Circulating B-Type Natriuretic Peptide and Diabetic Peripheral Neuropathy: A Cross-Sectional Study of a Chinese Type 2 Diabetic Population

Cardiovascular disease which is associated with cardiac dysfunction, usually measured with circulating levels of B-type natriuretic peptide (BNP), has been associated with incidence and progression of diabetic peripheral neuropathy (DPN). The potential relationship of circulating physiological levels of BNP with DPN, however, has not been reported. Circulating levels of BNP were measured in 258 patients with type 2 diabetes mellitus (T2DM), and participants were divided into a DPN group (n = 61) and no DPN group (n = 197). The relationship between circulating physiological levels of BNP and DPN and other parameters was analyzed. Circulating levels of BNP were significantly elevated in T2DM patients with DPN compared to those without (P = 0.001). Circulating levels of BNP were significantly and positively associated with systolic blood pressure (P = 0.035), neutrophil-to-lymphocyte ratio (P = 0.007), creatinine (P = 0.030), vibration perception threshold values (P = 0.021), and the prevalence of diabetic foot ulceration (P = 0.039), peripheral arterial disease (P = 0.013), DPN (P = 0.032), and diabetic nephropathy (P = 0.020) and negatively with lymphocyte count (P = 0.003) and ankle-brachial index (P = 0.038), irrespective of age, sex, and body mass index. Moreover, circulating levels of BNP was an independent decisive factor for the presence of DPN after multivariate adjustment (odds ratio, 1.044; 95% confidence interval, 1.006-1.084; P = 0.024). Additionally, the higher quartiles of circulating BNP were related significantly to an increased risk of DPN compared to the lowest quartile (P = 0.003). Last but most importantly, the analysis of receiver operating characteristic curves revealed that the best cutoff value for circulating levels of BNP to predict DPN was 15.18 pg/mL (sensitivity 78.7% and specificity 48.2%). These findings suggest that high circulating physiological levels of BNP may be associated with the development of DPN and may be a potential biomarker for DPN in patients with T2DM.

Gene Expression Profiling of the Sciatic Nerve in Streptozotocin-Induced Diabetic Rats with Peripheral Neuropathy

AIMS

To investigate the candidate biomarkers and molecular mechanisms involved in the early phase of experimental diabetic peripheral neuropathy (DPN).

METHODS

Diabetes in Sprague-Dawley rats was induced with streptozotocin (STZ) treatment, followed with neurological tests and histological examinations to assess the neuropathic symptoms of DPN. Microarray was performed on the sciatic nerve tissues from control rats and DPN rats at then6th week after diabetes induction, and differentially expressed genes (DEGs) between them were identified and applied for further bioinformatic analyses.

RESULTS

Experimental DPN rats were successfully constructed, presenting significantly decreased withdrawal threshold and motor nerve conduction velocity, and typical histological changes in the sciatic nerve. 597 DEGs (186 up- and 411 downregulated) were identified in DPN rats. DEGs from the 3 most highly connected clusters in the protein-protein interaction network were enriched for biological processes or pathways such as "cell division," "cell cycle," "protein phosphorylation," "chemokine signaling pathway," "neuropeptide signaling pathway," "response to drug," "cellular response to insulin stimulus," "PPAR signaling pathway," and "glycerophospholipid metabolism." Thirteen genes were identified as the hub DEGs in the PPI network. Eleven transcriptional factors (TFs) targeting 9 of the 13 hub DEGs were predicted.

CONCLUSIONS

The present study identified a pool of candidate biomarkers such as Cdk1, C3, Mapk12, Agt, Adipoq, Cxcl2, and Mmp9 and molecular mechanisms which may be involved in the early phase of experimental DPN. The findings provide clues for exploring new strategies for the early diagnosis and treatment of DPN.

Transcriptome Analysis of the Human Tibial Nerve Identifies Sexually Dimorphic Expression of Genes Involved in Pain, Inflammation, and Neuro-Immunity

Sex differences in gene expression are important contributors to normal physiology and mechanisms of disease. This is increasingly apparent in understanding and potentially treating chronic pain where molecular mechanisms driving sex differences in neuronal plasticity are giving new insight into why certain chronic pain disorders preferentially affect women vs. men. Large transcriptomic resources are now available and can be used to mine for sex differences to gather insight from molecular profiles using donor cohorts. We performed in-depth analysis of 248 human tibial nerve (hTN) transcriptomes from the GTEx Consortium project to gain insight into sex-dependent gene expression in the peripheral nervous system (PNS). We discover 149 genes with sex differential gene expression. Many of the more abundant genes in men are associated with inflammation and appear to be primarily expressed by glia or immune cells, with some genes downstream of Notch signaling. In women, we find the differentially expressed transcription factor SP4 that is known to drive a regulatory program, and may impact sex differences in PNS physiology. Many of these 149 differentially expressed (DE) genes have some previous association with chronic pain but few of them have been explored thoroughly. Additionally, using clinical data in the GTEx database, we identify a subset of DE, sexually dimorphic genes in diseases associated with chronic pain: arthritis and Type II diabetes. Our work creates a unique resource that identifies sexually dimorphic gene expression in the human PNS with implications for discovery of sex-specific pain mechanisms.

Gene expression profiling reveals candidate biomarkers and probable molecular mechanism in diabetic peripheral neuropathy

PURPOSE

To investigate the molecular mechanism and search for candidate biomarkers in the gene expression profile of patients with diabetic peripheral neuropathy (DPN).

METHODS

Differentially expressed genes (DEGs) of progressive vs non-progressive DPN patients in dataset GSE24290 were screened. Functional enrichment analysis was conducted, and hub genes were extracted from the protein-protein interaction network. The expression level of hub genes in serum samples in another dataset GSE95849 was obtained, followed by the ROC curve analysis.

RESULTS

A total of 352 DEGs were obtained from dataset GSE24290. They were involved in 14 gene ontology terms and 10 Kyoto Encyclopedia of Genes and Genomes pathways, mainly related to lipid metabolism. Eight hub genes (LEP, APOE, ADIPOQ, FABP4, CD36, GPAM, CIDEC, and PNPLA4) were revealed, and their expression level was obtained in dataset GSE95849. The receiver operating characteristic curve analysis indicated that CIDEC (AUC=1), APOE (AUC=0.833), CD36 (AUC=0.803), and PNPLA4 (AUC=0.861) might be candidate serum biomarkers of DPN.

CONCLUSION

Lipid metabolism of Schwann cells might be inhibited in progressive DPN. CIDEC, APOE, CD36, and PNPLA4 might be potential predictive biomarkers in the early DPN diagnosis of patients with DM.

Bioinformatics methodologies for coeliac disease and its comorbidities

Coeliac disease (CD) is a complex, multifactorial pathology caused by different factors, such as nutrition, immunological response and genetic factors. Many autoimmune diseases are comorbidities for CD, and a comprehensive and integrated analysis with bioinformatics approaches can help in evaluating the interconnections among all the selected pathologies. We first performed a detailed survey of gene expression data available in public repositories on CD and less commonly considered comorbidities. Then we developed an innovative pipeline that integrates gene expression, cell-type data and online resources (e.g. a list of comorbidities from the literature), using bioinformatics methods such as gene set enrichment analysis and semantic similarity. Our pipeline is written in R language, available at the following link: http://bioinformatica.isa.cnr.it/COELIAC_DISEASE/SCRIPTS/. We found a list of common differential expressed genes, gene ontology terms and pathways among CD and comorbidities and the closeness among the selected pathologies by means of disease ontology terms. Physicians and other researchers, such as molecular biologists, systems biologists and pharmacologists can use it to analyze pathology in detail, from differential expressed genes to ontologies, performing a comparison with the pathology comorbidities or with other diseases.

lncRNA-based study of epigenetic regulations in diabetic peripheral neuropathy

Diabetes remains one of the most prevalent non-communicable diseases in the world, affecting over 400 million of people worldwide, causing serious complications leading to amputations and even death. Over the years, researchers have found that, in addition to genomic mutations, epigenetic mechanisms also play a role in the development of diabetes-specifically type-2 diabetes. Long noncoding RNAs (lncRNAs) have been linked to mediate epigenetic mechanisms, including those in late-stage diabetes. This study attempts to assess the unexplored topic of how lncRNAs could be used to assess the epigenetic mechanisms present in diabetic peripheral neuropathy (DPN); a serious complication of the disease often leading to amputation. Differential lncRNA expression analysis was done with a dataset containing DPN and healthy patients. Standard and corrected t test, and also LIMMA was applied. Results of this study indicates the usefulness of lncRNAs as an exploratory tool to elucidate the complexity of the epigenetic mechanisms of human DPN.

Identification of Potential Therapeutic Targets in the Liver of Pioglitazone-Treated Type 2 Diabetes Sprague-Dawley Rats via Expression Profile Chip and iTRAQ Assay

The aim of the present study was to identify key antidiabetic nodes in the livers of pioglitazone-treated type 2 diabetes mellitus Sprague-Dawley rats by transcriptomic and proteomic analysis. Rats were randomly divided into the control, the diabetes model, and the pioglitazone-treated groups. After treatment with pioglitazone for 11 weeks, the effects on fasting blood glucose, body weight, and blood biochemistry parameters were evaluated. Microarray and iTRAQ analysis were used to determine the differentially expressed genes/proteins in rat livers. 1.5-fold changes in gene expression and 1.2-fold changes in protein were set as the screening criteria. After treatment with pioglitazone for 11 weeks, fasting blood glucose in pioglitazone-treated rats was significantly lower than that in the model group. There was a tendency for pioglitazone to reduce TC, TG, TP, ALB, BUN, and HDL-c levels. Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) were applied to analyze differentially expressed genes/proteins. Furthermore, Western blotting and RT-qPCR were used to validate the results of microarray and iTRAQ. In conclusion, Cyp7a1, Cp, and RT1-EC2 are differentially expressed genes/proteins since they showed a similar trend in rats in the model group and the pioglitazone-treated group.