Multi-Omics Analysis Revealed the rSNPs Potentially Involved in T2DM Pathogenic Mechanism and Metformin Response.

Background The onset and progression of type 1 diabetes mellitus (T1DM) is closely related to autoimmunity. Effective monitoring of the immune system and developing targeted therapies are frontier fields in T1DM treatment. Currently, the most available tissue that reflects the immune system is peripheral blood mononuclear cells (PBMCs). Thus, the aim of this study was to identify key PBMC biomarkers of T1DM.Methods Common differentially expressed genes (DEGs) were screened from the Gene Expression Omnibus (GEO) datasets GSE9006, GSE72377, and GSE55098, and PBMC mRNA expression in T1DM patients was compared with that in healthy participants by GEO2R. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interaction (PPI) network analyses of DEGs were performed using the Cytoscape, DAVID, and STRING databases. The vital hub genes were validated by reverse transcription-polymerase chain reaction using clinical samples. The disease-gene-drug interaction network was built using the Comparative Toxicogenomics Database (CTD) and Drug Gene Interaction Database (DGIdb).Results We found that various biological functions or pathways related to the immune system and glucose metabolism changed in PBMCs from T1DM patients. In the PPI network, the DEGs of module 1 were significantly enriched in processes including inflammatory and immune responses and in pathways of proteoglycans in cancer. Moreover, we focused on four vital hub genes, namely, chitinase-3-like protein 1 (CHI3L1), C-X-C motif chemokine ligand 1 (CXCL1), matrix metallopeptidase 9 (MMP9), and granzyme B (GZMB), and confirmed them in clinical PBMC samples. Furthermore, the disease-gene-drug interaction network revealed the potential of key genes as reference markers in T1DM.Conclusion These results provide new insight into T1DM pathogenesis and novel biomarkers that could be widely representative reference indicators or potential therapeutic targets for clinical applications.

Identification of KCNJ15 as a Susceptibility Gene in Asian Patients with Type 2 Diabetes Mellitus

Subclinical left ventricular (LV) dysfunction is prevalent in type 2 diabetes (T2DM). As obesity has been proposed as one causal factor in the disease process, this could bias the reported prevalences. We wanted to characterize echocardiographic LV dysfunction in obese T2DM subjects as compared to non-diabetic obese controls. One hundred patients with T2DM without clinical signs of heart failure (29% females, mean ± SD age 58.4 ± 10.5 years, body mass index (BMI) 30.1 ± 5.5 kg/m(2), blood pressure (BP) 141 ± 18/83 ± 9 mmHg) and 100 non-diabetic controls (29% females) matched for age (58.6 ± 10.5 years), BMI (29.8 ± 4.0 kg/m(2) and systolic BP (140 ± 14 mmHg) underwent echocardiography and color tissue Doppler imaging (TDI). Diastolic function was evaluated with conventional Doppler recordings and early (e') and late (a') myocardial velocities. The ratio between early transmitral filling (E) and the corresponding myocardial tissue velocity (e') served as an index of LV filling pressure. T2DM patients had more concentric hypertrophy with a relative wall thickness of 0.42 ± 0.07 vs controls 0.38 ± 0.07, P < 0.001. The T2DM group had signs of diastolic dysfunction with lower E/A ratio (0.91 ± 0.27 vs. 1.12 ± 0.38, P < 0.001), deceleration time (195 ± 49 vs 242 ± 72 ms, P < 0.001), e' (5.7 ± 2.0 vs. 6.6 ± 1.8 cm/s, P = 0.001), and a' (6.5 ± 2.0 vs. 7.6 ± 1.5 cm/s, P < 0.001) compared to the controls, and higher E/e' (13.3 ± 4.7 vs. 11.1 ± 3.5, P < 0.001). Thus, there were indications of pseudo normalization and increased filling pressure in the T2DM group, whereas the controls had evidence for relaxation abnormalities without elevated filling pressure. Compared to a non-diabetic obese group, more advanced subclinical impairment of diastolic function was seen in T2DM.

Introduction: Variability in the effectiveness of metformin treatment among individuals with type 2 diabetes mellitus (T2DM) has been linked to various genetic factors. Understanding the genetic mechanisms underlying the action of metformin can greatly aid the personalized management of T2DM. Our investigation aimed to explore the impact of genetic variations in the organic cation transporters (OCT1 and OCT3) genes on the efficacy of metformin therapy in T2DM individuals from North India. Methods: This observational cross-sectional study assessed the influence of OCT1 (rs628031) and OCT3 (rs2292334) polymorphisms on metformin response in T2DM patients. Metformin response was determined based on HbA1c levels, dividing patients (n = 177) into two categories: responders (HbA1C&lt;7%; n = 127) and non-responders (HbA1C≥7%; n = 50). Responders were further classified as T2DM patients receiving either monotherapy (n = 55) or combination therapy (n = 72). Genotyping was conducted using the PCR-RFLP method. Results: No significant association was observed between OCT1 (rs628031) polymorphism and metformin response in T2DM patients. However, a notable association was found between OCT3 (rs2292334) polymorphism and metformin response. Carriers of the AA genotype exhibited enhanced efficacy of metformin in both monotherapy (OR (CI)= 0.29(0.11-0.72), p=0.007) and combination therapy (OR (CI)= 0.41(0.16-1.0), p=0.047). Additionally, the A allele was more prevalent in responders (OR (CI)= 0.48(0.28-0.84), p=0.010), while the G allele was associated with reduced efficacy of metformin in T2DM patients (OR (CI)= 2.07(1.19-3.61), p=0.010). Conclusion: Genotyping of OCT3 (rs2292334) may serve as a valuable tool in predicting the response to metformin in T2DM patients.

Type 2 diabetes mellitus (T2DM) and cancer are highly prevalent diseases imposing major health burden globally. Several epidemiological studies indicate increased susceptibility to cancer in T2DM patients. However, genetic factors linking T2DM with cancer have been poorly studied. In this study, we followed computational approaches using the raw gene expression data of peripheral blood mononuclear cells of T2DM and cancer patients available in the gene expression omnibus (GEO) database. Our analysis identified shared differentially expressed genes (DEGs) in T2DM and three common cancer types, namely, pancreatic cancer (PC), liver cancer (LC), and breast cancer (BC). The functional and pathway enrichment analysis of identified common DEGs highlighted the involvement of critical biological pathways, including cell cycle events, immune system processes, cell morphogenesis, gene expression, and metabolism. We retrieved the protein–protein interaction network for the top DEGs to deduce molecular-level interactions. The network analysis found 7, 6, and 5 common hub genes in T2DM vs. PC, T2DM vs. LC, and T2DM vs. BC comparisons, respectively. Overall, our analysis identified important genetic markers potentially able to predict the chances of PC, LC, and BC onset in T2DM patients.

BackgroundPolycystic ovary syndrome (PCOS) and type 2 diabetes mellitus (T2DM) are two prevalent and interrelated disorders that pose an increasingly significant global health burden. Cellular senescence may represent a pivotal process driving the progression of both conditions. Senescent cells, through the senescence-associated secretory phenotype (SASP), can induce chronic inflammation, which is highly likely to exacerbate the pathological progression of PCOS and T2DM. However, the molecular pathways linking cellular senescence to PCOS and T2DM have not yet been systematically elucidated.MethodsThe transcriptome datasets of PCOS (GSE54248) and T2DM (GSE23561) were obtained from the GEO database, and differentially expressed genes (DEGs) were screened using the limma package. Age-related DEGs (ARDEGs) were obtained by intersecting DEGs with age-related genes, and the protein-protein interaction (PPI) network was constructed based on the STRING database. Hub genes with diagnostic value were determined via the Wilcoxon rank sum test and receiver operating characteristic (ROC) curve. CIBERSORT was used to analyze the infiltration characteristics of immune cells, and the functions of the hub gene were analyzed by gene set enrichment analysis (GSEA). Single-cell sequencing was used to locate gene expression patterns, and qRT–PCR was used to verify the expression of candidate genes in clinical samples.Results80 DEGs between PCOS and T2DM samples were obtained, and 15 ARDEGs were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that they were related to inflammatory response and immune response, and were involved in specific functions and pathways. Four hub genes were identified: TUBA4A, RTN1, G6PD, and HP. qRT–PCR experimental results showed that HP, G6PD, TUBA4A, and RTN1 were highly expressed in the peripheral blood of PCOS and T2DM patients, compared to healthy people.DiscussionThis study revealed the potential connections between PCOS, T2DM, and aging-related molecular networks and signaling pathways and discovered multiple potential therapeutic targets. It provides new intervention directions for clinicians, especially based on aging mechanisms.

Type 2 diabetes mellitus (T2DM) and cancer are highly prevalent diseases imposing major health burden globally. Several epidemiological studies indicate increased susceptibility to cancer in T2DM patients. However, genetic factors linking T2DM with cancer have been poorly studied. In this study, we followed computational approaches using the raw gene expression data of peripheral blood mononuclear cells of T2DM and cancer patients available in the gene expression omnibus (GEO) database. Our analysis identified shared differentially expressed genes (DEGs) in T2DM and three common cancer types, namely, pancreatic cancer (PC), liver cancer (LC), and breast cancer (BC). The functional and pathway enrichment analysis of identified common DEGs highlighted the involvement of critical biological pathways, including cell cycle events, immune system processes, cell morphogenesis, gene expression, and metabolism. We retrieved the protein–protein interaction network for the top DEGs to deduce molecular-level interactions. The network analysis found 7, 6, and 5 common hub genes in T2DM vs. PC, T2DM vs. LC, and T2DM vs. BC comparisons, respectively. Overall, our analysis identified important genetic markers potentially able to predict the chances of PC, LC, and BC onset in T2DM patients.

To clarify the expression of N6-methyladenosine (m6 A) modulators involved in the pathogenesis of type 2 diabetes mellitus (T2DM). We further explored the association of serum insulin-like growth factor 2 mRNA-binding proteins 3 (IGF2BP3) levels and odds of T2DM in a high-risk population. The gene expression data set GSE25724 was obtained from the Gene Expression Omnibus, and a cluster heatmap was generated by using the R package ComplexHeatmap. Differential expression analysis for 13 m6 A RNA methylation regulators between nondiabetic controls and T2DM subjects was performed using an unpaired t test. A cross-sectional design, including 393 subjects (131 patients with newly diagnosed T2DM, 131 age- and sex-matched subjects with prediabetes, and 131 healthy controls), was carried out. The associations between serum IGF2BP3 concentrations and T2DM were modeled by restricted cubic spline and logistic regression models. Two upregulated (IGF2BP2 and IGF2BP3) and 5 downregulated (methyltransferase-like 3 [METTL3], alkylation repair homolog protein 1 [ALKBH1], YTH domain family 2 [YTHDF2], YTHDF3, and heterogeneous nuclear ribonucleoprotein [HNRNPC]) m6 A-related genes were found in islet samples of T2DM patients. A U-shaped association existed between serum IGF2BP3 levels and odds of T2DM according to cubic natural spline analysis models, after adjustment for body mass index, waist circumference, diastolic blood pressure, total cholesterol, and triglyeride. Multivariate logistic regression showed that progressively higher odds of T2DM were observed when serum IGF2BP3 levels were below 0.62 ng/mL (odds ratio 3.03 [95% confidence interval 1.23-7.47]) in model 4. Seven significantly altered m6 A RNA methylation genes were identified in T2DM. There was a U-shaped association between serum IGF2BP3 levels and odds of T2DM in the general Chinese adult population. This study provides important evidence for further examination of the role of m6 A RNA methylation, especially serum IGF2BP3 in T2DM risk assessment.

BackgroundCoronary artery disease (CAD) confers considerable morbidity and mortality in diabetes. However, the role of CAD in additive effect of left ventricular (LV) function has rarely been explored in type 2 diabetes mellitus (T2DM) patients. This study aimed to investigate how CAD affect LV systolic and diastolic function in T2DM patients.Materials and methodsA total of 282 T2DM patients {104 patients with CAD [T2DM (CAD +)] and 178 without [T2DM (CAD −)]} and 83 sex- and age- matched healthy controls underwent cardiac magnetic resonance scanning. LV structure, function, global strains [including systolic peak strain (PS), peak systolic (PSSR) and diastolic strain rate (PDSR) in radial, circumferential and longitudinal directions] and late gadolinium enhancement (LGE) parameters were measured. T2DM (CAD +) patients were divided into two subgroups based on the median of Gensini score (60) which was calculated to assess the severity of CAD. Multivariable linear regression analyses were constructed to investigate the determinants of reduced LV function.ResultsCompared with normal controls, T2DM (CAD −) patients exhibited increased LV end-diastolic and end-systolic volume index and decreased LV global strains, while T2DM(CAD +) patients showed more marked increase and decrease than T2DM(CAD-) and healthy controls, except for longitudinal PDSR (PDSR-L) (all P < 0.017). All of LV global strains demonstrated a progressive decrease from normal controls, through Gensini score ≤ 60, to Gensini score > 60 group, except for PDSR-L (all P < 0.017). CAD was an independent predictor of reduced LV global circumferential PS (GCPS, β = 0.22, p < 0.001), PSSR (PSSR-C, β = 0.17, p = 0.005), PDSR (PDSR-C, β = 0.22, p < 0.001), global radial PS (GRPS, β = 0.19, p = 0.001), and global longitudinal PS (GLPS, β = 0.18, p = 0.003) in T2DM. The Gensini score was associated with decreased GCPS, PSSR-C, PDSR-C, GRPS, and GLPS in T2DM (CAD +) (all p < 0.05).ConclusionCAD has an additive deleterious effect on LV systolic and diastolic function in T2DM patients. Among T2DM (CAD +) patients, the Gensini score is associated with reduced LV contractile and diastolic function.Trial registration Retrospectively registered

The prevalence of type 2 diabetes mellitus (T2DM) is increasing dramatically worldwide. Dysregulation of microRNA (miRNA) as key regulators of gene expression, has been reported in numerous diseases including diabetes. The aim of this study was to investigate the expression levels of miRNA-122, miRNA-126-3p and miRNA-146a in diabetic and pre-diabetic patients and in healthy individuals, and to determine whether the changes in the level of these miRNAs are reliable biomarkers in diagnosis, prognosis, and pathogenesis of T2DM. Additionally, we examined the relationship between miRNA levels and plasma concentrations of inflammatory factors including tumor necrosis factor alpha (TNF-α) and interleukin 6 (Il-6) as well as insulin resistance. In this case-control study, participants (n = 90) were allocated to three groups (n = 30/group): T2DM, pre-diabetes and healthy individuals as control (males and females, age: 25–65, body mass index: 25–35). Expression of miRNA was determined by real-time polymerase chain reaction (RT-PCR). Furthermore, plasma concentrations of TNF-α, IL-6 and fasting insulin were measured by enzyme-linked immunosorbent assay. Homeostatic model assessment for insulin resistance (HOMA-IR) was calculated as an indicator of insulin resistance. MiRNA-122 levels were higher while miRNA-126-3p and miRNA-146a levels were lower in T2DM and pre-diabetic patients compared to control (p<0.05). Furthermore, a positive correlation was found between miRNA-122 expression and TNF-α (r = 0.82), IL-6 (r = 0.83) and insulin resistance (r = 0.8). Conversely, negative correlations were observed between miRNA-126-3p and miRNA-146a levels and TNF-α (r = -0.7 and r = -0.82 respectively), IL-6 (r = -0.65 and r = -0.78 respectively) as well as insulin resistance (r = -0.67 and r = -0.78 respectively) (all p<0.05). Findings of this study suggest the miRNAs can potentially contribute to the pathogenesis of T2DM. Further studies are required to examine the reproducibility of these findings.

Type 2 diabetes mellitus (T2DM) is a long-term metabolic disorder. It is characterized by hyperglycemia, insulin resistance (IR), and relative impairment in insulin secretion. IR plays a major role in the pathogenesis of T2DM. Many previous studies have investigated the relationship between estrogen, androgen, and obesity, but few focused on the relationship between sex hormones, abnormal lipid metabolism, and IR. The goal for the present study was to identify the association of IR with sex hormone, abnormal lipid metabolism in type 2 diabetes, and impaired glucose tolerance (IGT) patients.In total 13,400 participants were analyzed based on the results of the glucose tolerance test. Using a cross-sectional study, we showed the relationship between IR and the level of sex hormones among 3 different glucose tolerance states: normal control people, IGT, and T2DM patients. We also analyzed the relationship between IR and abnormal lipid metabolism.Significantly, luteinizing, progesterone, estradiol, prolactin, and follicle-stimulating hormone levels decreased in T2DM and IGT patients compared with those in normal control people. The association between IR and lipid metabolism disorders in T2DM and IGT patients was also observed.Our clinical findings may offer new insights into understanding the mechanism of metabolic disorders and in new therapeutic methods for the treatment of the prevalence of type 2 diabetes.

Serum and tissue expression levels of microRNAs-661, -571 and -770-5p among diabetic foot ulcer patients compared to healthy controls

The relationship between type 2 diabetes mellitus (T2DM) and osteoporosis (OP) has been widely recognized in recent years, but the mechanism of interaction remains unknown. The aim of this study was to investigate the genetic features and signaling pathways that are shared between T2DM and OP. We analyzed the GSE76894 and GSE76895 datasets for T2DM and GSE56815 and GSE7429 for OP from the Gene Expression Omnibus (GEO) database to identify shared genes in T2DM and OP, and we constructed coexpression networks based on weighted gene coexpression network analysis (WGCNA). Shared genes were then further analyzed for functional pathway enrichment. We selected the best common biomarkers using the least absolute shrinkage and selection operator (LASSO) algorithm and validated the common biomarkers, followed by RT-PCR, immunofluorescence, Western blotting, and enzyme-linked immunosorbent assay (ELISA) to validate the expression of these hub genes in T2DM and OP mouse models and patients. We found 8,506 and 2,030 DEGs in T2DM and OP, respectively. Four modules were identified as significant for T2DM and OP using WGCNA. A total of 19 genes overlapped with the strongest positive and negative modules of T2DM and OP. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed these genes may be involved in pantothenate and CoA biosynthesis and the glycosaminoglycan biosynthesis-chondroitin sulfate/dermatan sulfate and renin-angiotensin system signaling pathway. The LASSO algorithm calculates the six optimal common biomarkers. RT-PCR results show that LTB, TPBG, and VNN1 were upregulated in T2DM and OP. Immunofluorescence and Western blot show that VNN1 is upregulated in the pancreas and bones of T2DM model mice and osteoporosis model mice. Similarly, the level of VNN1 in the sera of patients with T2DM, OP, and T2DM and OP was higher than that in the healthy group. Based on the WGCNA and LASSO algorithms, we identified genes and pathways that were shared between T2DM and OP. Both pantothenate and CoA biosynthesis and the glycosaminoglycan biosynthesis-chondroitin sulfate/dermatan sulfate and renin-angiotensin systems may be associated with the pathogenesis of T2DM and OP. Moreover, VNN1 may be a potential diagnostic marker for patients with T2DM complicated by OP. This study provides a new perspective for the systematic study of possible mechanisms of combined OP and T2DM.

Circular RNAs (circRNAs) are an abundant class of endogenous non-coding RNAs and are associated with numerous diseases, including cancer, cardiovascular diseases, and type 2 diabetes mellitus (T2DM). However, the association between circRNAs and inflammation or inflammatory cytokines in patients with T2DM remains to be fully elucidated. The purpose of the present study was to investigate the expression profiles of circRNAs in peripheral leucocytes of patients with T2DM and their association with inflammatory cytokines. Peripheral blood from patients with T2DM (n=43) and healthy individuals (n=45) were collected for RNA sequencing and later verification. Reverse transcription-polymerase chain reaction (RT-PCR) and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analyses were used to detect the expression levels of circRNAs. The expression of inflammatory factors, including interleukin (IL)-1, (IL)-6, and tumor necrosis factor (TNF)-α were measured via enzyme-linked immunosorbent assay. Furthermore, the mRNA expression level of ankyrin repeat domain 36 (ANKRD36), a protein located at 2q11.2 that interacts with the GAPDH gene, was measured using RT-qPCR analysis. The circRNA/microRNA (miRNA) interaction was predicted using RegRNA and mirPath software. In total, 220 circRNAs were found to be differentially expressed between patients with T2DM and healthy individuals, of which 107 were upregulated and 113 were downregulated. Among the nine selected circRNAs, circANKRD36 was significantly upregulated in patients with T2DM compared with control subjects (P=0.02). The expression level of circANKRD36 was positively correlated with glucose and glycosylated hemoglobin (r=0.3250, P=0.0047 and r=0.3171, P=0.0056, respectively). The expression level of IL-6 was significantly different between the T2DM group and control group (P=0.028) and was positively correlated with circANKRD36. The difference of circANKRD36 host gene expression between patients with T2DM and healthy controls was significant (P=0.04). Taken together, circANKRD36 may be involved in T2DM and inflammation-associated pathways via interaction with miRNAs, including hsa-miR-3614-3p, hsa-miR-498, and hsa-miR-501-5p. The expression of circANKRD36 was up regulated in peripheral blood leucocytes and was correlated with chronic inflammation in T2DM. Therefore, circANKRD36 can be used as a potential biomarker for screening chronic inflammation in patients with T2DM.

Free fatty acids (FFAs) participate in a variety of physiological functions. FFAs are associated with the development of type 2 diabetes mellitus (T2DM). Uyghurs and Kazaks have a different prevalence of T2DM, which cannot be explained by traditional risk factors. This study aimed to examine FFAs as potential biomarkers to distinguish between healthy and T2DM Uyghurs and Kazaks. This was a prospective study conducted at the Xianjiang Medical University from 01/2007 to 06/2010 in Uyghurs and Kazaks. The subjects were grouped as T2DM patients (Uyghurs: n=39; Kazaks, n=21) and controls (Uyghurs: n=35; Kazaks, n=40). Gas chromatography-mass spectrometry (GC-MS) and partial least squares discriminant analysis (PLS-DA) models were used to study the FFA profiles between Uyghurs and Kazaks with T2DM. PLS-DA analysis showed that among Kazaks, T2DM patients had lower C22:6, C18:3 n-6, and C20:3 n-6, but higher C22:0 levels compared with controls. Among Uyghurs, the most important variables to discriminate T2DM patients from controls were higher C22:6 and C20:4 n-6, and lower C22:0, C14:1, C18:3 n6, and C20:3 n6. Kazaks and Uyghurs displayed different FFA profiles between patients with T2DM and controls. These results suggest different risk factors and pathogenesis of T2DM between Kazaks and Uyghurs.