Proteomics, metabolomics and metagenomics for type 2 diabetes and its complications

Unveiling novel metabolic alterations in postmenopausal osteoporosis and type 2 diabetes mellitus through NMR-based metabolomics: A pioneering approach for identifying early diagnostic markers

BACKGROUND AND AIMS

Postmenopausal osteoporosis (PMO) and type 2 diabetes mellitus (T2DM) frequently coexist in postmenopausal women. The study aimed to explore metabolic variations linked to these circumstances and their simultaneous presence through proton nuclear magnetic resonance metabolomics (1H NMR).

MATERIALS AND METHODS

Serum samples from 80 postmenopausal women, including 20 PMO individuals, 20 T2DM, 20 T2DM + PMO, and 20 healthy postmenopausal women, were analyzed using 1H NMR spectroscopy.

RESULTS

Our study revealed significant metabolic profile differences among the four groups. Notably, the T2DM + PMO group showed elevated levels of alanine, pyruvate, glutamate, lactate, and aspartate, indicating their involvement in lipid metabolism, energy, and amino acids. Importantly, our multivariate statistical analysis identified a metabolite set that accurately distinguished the groups, suggesting its potential as an early diagnostic marker.

CONCLUSION

The 1H NMR metabolomics approach uncovered metabolic biomarkers intricately linked to postmenopausal osteoporosis (PMO), type 2 diabetes mellitus (T2DM), and their concurrent presence. Among these biomarkers, alanine emerged as a pivotal player, showing its significant role in the metabolic landscape associated with PMO and T2DM. These findings shed light on the pathophysiological mechanisms underlying these conditions and underscore alanine's potential as a diagnostic biomarker.

MetaBIDx: a new computational approach to bacteria identification in microbiomes

Objectives: This study introduces MetaBIDx, a computational method designed to enhance species prediction in metagenomic environments. The method addresses the challenge of accurate species identification in complex microbiomes, which is due to the large number of generated reads and the ever-expanding number of bacterial genomes. Bacterial identification is essential for disease diagnosis and tracing outbreaks associated with microbial infections. Methods: MetaBIDx utilizes a modified Bloom filter for efficient indexing of reference genomes and incorporates a novel strategy for reducing false positives by clustering species based on their genomic coverages by identified reads. The approach was evaluated and compared with several well-established tools across various datasets. Precision, recall, and F1-score were used to quantify the accuracy of species prediction. Results: MetaBIDx demonstrated superior performance compared to other tools, especially in terms of precision and F1-score. The application of clustering based on approximate coverages significantly improved precision in species identification, effectively minimizing false positives. We further demonstrated that other methods can also benefit from our approach to removing false positives by clustering species based on approximate coverages. Conclusion: With a novel approach to reducing false positives and the effective use of a modified Bloom filter to index species, MetaBIDx represents an advancement in metagenomic analysis. The findings suggest that the proposed approach could also benefit other metagenomic tools, indicating its potential for broader application in the field. The study lays the groundwork for future improvements in computational efficiency and the expansion of microbial databases.

Predictive model for vitamin C levels in hyperinsulinemic individuals based on age, sex, waist circumference, low-density lipoprotein, and immune-associated serum proteins

Vitamin C (ascorbic acid) is an important water-soluble antioxidant associated with decreased oxidative stress in type 2 diabetes (T2D) patients. A previous targeted plasma proteomic study has indicated that ascorbic acid is associated with markers of the immune system in healthy subjects. However, the association between the levels of ascorbic acid and blood biomarkers in subjects at risk of developing T2D is still unknown. Serum ascorbic acid was measured by ultra-performance liquid chromatography and serum proteins were quantified by untargeted liquid-chromatography mass spectrometry in 25 hyperinsulinemia subjects that were randomly assigned a high dairy intake diet or an adequate dairy intake diet for 6 weeks, then crossed-over after a 6-week washout period. Spearman correlation followed by gene ontology analyses were performed to identify biological pathways associated with ascorbic acid. Finally, machine learning analysis was performed to obtain a specific serum protein signature that could predict ascorbic acid levels. After adjustments for waist circumference, LDL, HDL, fasting insulin, fasting blood glucose, age, gender, and dairy intake; serum ascorbic acid correlated positively with different aspects of the immune system. Machine learning analysis indicated that a signature composed of 21 features that included 17 proteins (mainly from the immune system), age, sex, waist circumference, and LDL could predict serum ascorbic acid levels in hyperinsulinemia subjects. In conclusion, the result reveals a correlation as well as modulation between serum ascorbic acid levels and proteins that play vital roles in regulating different aspects of the immune response in individuals at risk of T2D. The development of a predictive signature for ascorbic acid will further help the assessment of ascorbic acid status in clinical settings.

Validating Fractalkine receptor as a target and identifying candidates for drug discovery against type 2 diabetes

Type 2 diabetes mellitus (T2DM) is one of the most common chronic diseases employing abnormal levels of insulin. Enhancing the insulin production is greatly aided by the regulatory mechanisms of the Fractalkine receptor (CX3CR1) system in islet β-cell function. However, elements including a high-fat diet, obesity, and ageing negatively impact the expression of CX3CR1 in islets. CX3CL1/CX3CR1 receptor-ligand complex is now recognized as a novel therapeutic target. It suggests that T2DM-related β-cell dysfunction may result from lower amount of these proteins. We analyzed the differential expression of CX3CR1 gene samples taken from persons with T2DM using data obtained from the Gene Expression Omnibus database. Homology modeling enabled us to generate the three-dimensional structure of CX3CR1 and a possible binding pocket. The optimized CX3CR1 structure was subjected to rigorous screening against a massive library of 693 million drug-like molecules from the ZINC15 database. This screening process led to the identification of three compounds with strong binding affinity at the identified binding pocket of CX3CR1. To further evaluate the potential of these compounds, molecular dynamics simulations were conducted over a 50 ns time scale to assess the stability of the protein-ligand complexes. These simulations revealed that ZINC000032506419 emerged as the most promising drug-like compound among the three potent molecules. The discovery of ZINC000032506419 holds exciting promise as a potential therapeutic agent for T2D and other related metabolic disorders. These findings pave the way for the development of effective medications to address the complexities of T2DM and its associated metabolic diseases.

Alpinia officinarum Hance extract ameliorates diabetic gastroparesis by regulating SCF/c-kit signaling pathway and rebalancing gut microbiota

Diabetic gastroparesis (DGP) is a common complication of type 2 diabetes mellitus (T2DM). Alpinia officinarum Hance (AOH) is one of the most commonly used both as a food and folk medicines, which is rich in diarylheptanoids and flavonoids. The gastroprotection and hypoglycemic effect make AOH has great potential in developing of anti-DGP complementary medicine. However, the molecular mechanisms of AOH that act against DGP are yet to be elucidated. In this study, we evaluated the therapeutic effects, the potential molecular mechanism, and the changes of gut microbiota of AOH in DGP. The 5 components of the AOH were analyzed, and the potential signaling pathway of AOH improving DGP was predicted by molecular docking. Subsequently, DGP rat model was constructed using high-fat-irregular-diet, AOH intervention significantly reduced blood glucose levels, increased gastrointestinal propulsion rate, and improved gastric histological morphology in DGP rats. Meanwhile, AOH has been shown to regulate the SCF/c-kit signaling pathway and rebalance the gut microbiota, which may be closely related to its role in improving DGP. Taken together, AOH may play a protective role on DGP through multiple mechanisms, which might pave the road for development and utilization of AOH.

Analysis of bone metabolic alterations linked with osteoporosis progression in type 2 diabetic db/db mice

Type 2 diabetes (T2D) is a common chronic disease, characterized by persistent hyperglycemia and insulin resistance. This disorder is associated with decreased bone quality and an elevated risk of bone fractures. However, evidence on the relationship between systemic metabolic change and the development of type 2 diabetic osteoporosis (T2DOP) remains elusive. Herein, we investigate the changes of bone metabolites with bone loss in db/db mice (an animal model of T2DOP exhibited bone loss with age progression), and explore the potential metabolic mechanism underlying type 2 diabetes and osteoporosis. C57BKS male mice were distributed in four groups, consisting six mice in each group: 8w m/m, 24w m/m, 8w db/db and 24w db/db. Bone morphometric and biomechanical parameters of db/db mice were analyzed by micro-CT and materials tester, it was found that 24w db/db mice showed severe bone loss and decreased bone tissue hardness compared with misty/misty littermates. The tibia of misty/misty mice (8 weeks, 24 weeks) and db/db mice (8 weeks, 24 weeks) were screened for differential metabolites by UPLC-Orbitrap MS. Ninety-eight metabolites were identified (35 and 63 metabolites are associated with early staged and late staged, respectively), consisting of amino acids, fatty acyls, and nucleotides. Notably, fatty acyls (such as 18-HEPE, 16(17)-EpDPE, arachidonic acid) and glycerophospholipids (such as phosphocholines (PC) (O-10:1(9E)/0:0), PC (O-16:1(9E)/0:0) [U] and phosphatidylethanolamines (PE) (P-16:0/0:0)) were significantly increased, and metabolites of amino acid pathway (such as l-glutamine, proline, phenylalanine) showed a downregulation trend. Dysregulation of lipid and glutathione pathways is the major contributor to progression of T2DOP in C57BKS mice.

Omics to Unveil Diabetes Mellitus Pathogenesis and Biomarkers: Focus on Proteomics, Lipidomics, and Metabolomics

Diabetes mellitus (DM) is a chronic metabolic disorder characterized by elevated blood sugar levels, resulting from either body's inability to produce or effectively utilize insulin. There are several types of DM, but the most common are type 1 diabetes (T1D), type 2 diabetes (T2D), and gestational diabetes mellitus (GDM). DM is a complex disease and a global health concern, and the current clinical markers, such as fasting glucose, are helpful in the diagnosis of DM, but are not specific and sensitive, especially when measured on the beginning of the pathogenesis. Therefore, there is a pressing need to discover new early biomarkers that can provide an early diagnosis. Omics is an important field for the discovery of potential new biomarkers, especially proteomics, metabolomics, and lipidomics, where techniques such as liquid chromatography, mass spectrometry, and nuclear magnetic resonance are utilized to identify novel DM biomarkers and their pathways. In this review, we report papers that applied omics in the context of DM to identify new markers and their relationship with this disease, with the aim of elucidating new diagnostic techniques for the main types of DM.

Epigenetic changes underlie the association between diabetes mellitus and oral diseases

Patients with diabetes mellitus (DM) suffer from oral complications related to oral infections, periodontal diseases, and endodontic lesions. Emerging evidence has revealed the contribution of the epigenetic process as the underlying mechanism of DM complications. DNA methylation, histone modifications, and non-coding RNAs are epigenetic regulators that directly affect gene expression. The present review elaborated on the role of epigenetic dysregulation in the etiology of diabetes-related periodontal and endodontic diseases. The narrative review study was prepared using databases such as PubMed, Google Scholar, Science Direct, and Scopus. The formation of glycation products as a result of hyperglycemic condition increases oxidative stress, and elevates chronic inflammatory mediators that could in turn adversely change the cellular environment and alter the epigenetic status. This process contributes to the alteration of regulatory genes expression, leading to the development of diabetes-induced bone complications and impaired odontogenic capacity of pulp. Indeed, epigenetic mechanisms mediate the interaction between gene expression and DM cellular environment. Further investigations on epigenetic factors involved in DM oral complications may provide novel therapeutic targets.

Integrating (Nutri-)Metabolomics into the One Health Tendency-The Key for Personalized Medicine Advancement

Metabolomics is an advanced technology, still under development, with multiple research applications, especially in the field of health. Individual metabolic profiles, the functionality of the body, as well as its interaction with the environment, can be established using this technology. The body's response to various external factors, including the food consumed and the nutrients it contains, has increased researchers' interest in nutrimetabolomics. Establishing correlations between diet and the occurrence of various diseases, or even the development of personalized nutrition plans, could contribute to advances in precision medicine. The interdependence between humans, animals, and the environment is of particular importance today, with the dramatic emergence and spread of zoonotic diseases, food, water and soil contamination, and the degradation of resources and habitats. All these events have led to an increase in risk factors for functional diseases, burdening global health. Thus, this study aimed to highlight the importance of metabolomics, and, in particular, nutrimetabolomics, as a technical solution for a holistic, collaborative, and precise approach for the advancement of the One Health strategy.

Hydrogen-Rich Water Ameliorates Metabolic Disorder via Modifying Gut Microbiota in Impaired Fasting Glucose Patients: A Randomized Controlled Study

OBJECTIVE

Molecular hydrogen (H₂) exhibits antioxidant, anti-inflammatory and anti-apoptotic effects, and has shown benefits in glucose and lipid metabolism in certain animal metabolic disorder models. However, the potential benefits of H₂ treatment in individuals with impaired fasting glucose (IFG) has seldom been studied. This randomized controlled study (RCT) aims to investigate the effects of hydrogen-rich water (HRW) on IFG subjects and explore the underlying mechanism involved.

METHODS

Seventy-three patients with IFG were enrolled in a randomized, double-blind, placebo-controlled clinical study. These patients were assigned to receive either 1000 mL per day of HRW or placebo pure water (no H₂ infusion) for a duration of eight weeks. Metabolic parameters and fecal gut microbiota were assessed at baseline (week 0) and at week 8. A combined analysis of metabolomics and intestinal microbiota was conducted to investigate the correlation between the effect of H₂ on the metabolisms and the diversity of intestinal flora in the IGF patients.

RESULTS

Both pure water and HRW demonstrated a significant reduction in fasting blood glucose in IFG patients, with a significant difference between pure water and HRW after eight weeks. Among IFG patients with abnormal pre-experimental fatty liver, 62.5% (10/16) in the HRW group and 31.6% (6/19) in the pure water group achieved remission. Furthermore, 16S RNA analysis revealed HRW-modified gut microbiota dysbiosis in the fecal samples of IGF patients. Through Pearson correlation analysis, the differential gut microbiota obtained by 16S analysis was found to be highly correlated with nine metabolites.

CONCLUSION

H₂ slightly improved metabolic abnormalities and gut microbiota dysbiosis, providing a novel target and theoretical basis for the prevention and treatment of blood glucose regulation in patients with IFG.

Rapid Multivariate Analysis Approach to Explore Differential Spatial Protein Profiles in Tissue

Spatially targeted proteomics analyzes the proteome of specific cell types and functional regions within tissue. While spatial context is often essential to understanding biological processes, interpreting sub-region-specific protein profiles can pose a challenge due to the high-dimensional nature of the data. Here, we develop a multivariate approach for rapid exploration of differential protein profiles acquired from distinct tissue regions and apply it to analyze a published spatially targeted proteomics data set collected from Staphylococcus aureus-infected murine kidney, 4 and 10 days postinfection. The data analysis process rapidly filters high-dimensional proteomic data to reveal relevant differentiating species among hundreds to thousands of measured molecules. We employ principal component analysis (PCA) for dimensionality reduction of protein profiles measured by microliquid extraction surface analysis mass spectrometry. Subsequently, k-means clustering of the PCA-processed data groups samples by chemical similarity. Cluster center interpretation revealed a subset of proteins that differentiate between spatial regions of infection over two time points. These proteins appear involved in tricarboxylic acid metabolomic pathways, calcium-dependent processes, and cytoskeletal organization. Gene ontology analysis further uncovered relationships to tissue damage/repair and calcium-related defense mechanisms. Applying our analysis in infectious disease highlighted differential proteomic changes across abscess regions over time, reflecting the dynamic nature of host-pathogen interactions.

A Strategic Research Framework for Defeating Diabetes in India: A 21st-Century Agenda

Indian people are at high risk for type 2 diabetes (T2DM) even at younger ages and lower body weights. Already 74 million people in India have the disease, and the proportion of those with T2DM is increasing across all strata of society. Unique aspects, related to lower insulin secretion or function, and higher hepatic fat deposition, accompanied by the rise in overweight (related to lifestyle changes) may all be responsible for this unrelenting epidemic of T2DM. Yet, research to understand the causes, pathophysiology, phenotypes, prevention, treatment, and healthcare delivery of T2DM in India seriously lags behind. There are major opportunities for scientific discovery and technological innovation, which if tapped can generate solutions for T2DM relevant to the country's context and make leading contributions to global science. We analyze the situation of T2DM in India, and present a four-pillar (etiology, precision medicine, implementation research, and health policy) strategic research framework to tackle the challenge. We offer key research questions for each pillar, and identify infrastructure needs. India offers a fertile environment for shifting the paradigm from imprecise late-stage diabetes treatment toward early-stage precision prevention and care. Investing in and leveraging academic and technological infrastructures, across the disciplines of science, engineering, and medicine, can accelerate progress toward a diabetes-free nation.

The association of dietary approaches to stop hypertension (DASH) with the odds of diabetic nephropathy and metabolic markers in women: a case-control study

OBJECTIVES

Epidemiologic studies have reported that diet is associated with diabetes and its complications through different pathways. We sought to examine the associations between the Dietary Approaches to Stop Hypertension (DASH) diet and the odds of diabetic nephropathy (DN) developing in Iranian women with existing type 2 diabetes.

METHODS

In this case-control study, 105 women with DN and 105 controls, matched for age and diabetes duration, were selected from the Kowsar Diabetes Clinic in Semnan, Iran. DASH, estimated using dietary intake, was assessed using a validated and reliable food frequency questionnaire with 147 items. Anthropometric measurements were assessed for all subjects. Logistic regression was performed to examine the association between DASH and the odds of developing DN.

RESULTS

After controlling for potential confounders, subjects in the highest intake of DASH diet adherence have 84% lower odds of DN, compared to those with the lowest intake (OR = 0.16, 95% CI = 0.07-0.34, P < 0.001). Among DASH diet subcategories, intakes of vegetables (80%), fruits (88%), nuts and legumes (87%), and low-fat dairy (73%) decreased the risk of DN after adjustment for confounders (P < 0.001).

CONCLUSIONS

This study showed that the DASH diet is associated with lower odds of DN development in women with type 2 diabetes.

The biomarkers discovery of hyperuricemia and gout: proteomics and metabolomics

Background

Hyperuricemia and gout are a group of disorders of purine metabolism. In recent years, the incidence of hyperuricemia and gout has been increasing, which is a severe threat to people's health. Several studies on hyperuricemia and gout in proteomics and metabolomics have been conducted recently. Some literature has identified biomarkers that distinguish asymptomatic hyperuricemia from acute gout or remission of gout. We summarize the physiological processes in which these biomarkers may be involved and their role in disease progression.

Methodology

We used professional databases including PubMed, Web of Science to conduct the literature review. This review addresses the current landscape of hyperuricemia and gout biomarkers with a focus on proteomics and metabolomics.

Results

Proteomic methods are used to identify differentially expressed proteins to find specific biomarkers. These findings may be suggestive for the diagnosis and treatment of hyperuricemia and gout to explore the disease pathogenesis. The identified biomarkers may be mediators of the link between hyperuricemia, gout and kidney disease, metabolic syndrome, diabetes and hypertriglyceridemia. Metabolomics reveals the main influential pathways through small molecule metabolites, such as amino acid metabolism, lipid metabolism, or other characteristic metabolic pathways. These studies have contributed to the discovery of Chinese medicine. Some traditional Chinese medicine compounds can improve the metabolic disorders of the disease.

Conclusions

We suggest some possible relationships of potential biomarkers with inflammatory episodes, complement activation, and metabolic pathways. These biomarkers are able to distinguish between different stages of disease development. However, there are relatively few proteomic as well as metabolomic studies on hyperuricemia and gout, and some experiments are only primary screening tests, which need further in-depth study.

Hypoglycemic Effect of the N-Butanol Fraction of Torreya grandis Leaves on Type 2 Diabetes Mellitus in Rats through the Amelioration of Oxidative Stress and Enhancement of β-Cell Function

Materials and Methods

Sprague-Dawley rats were randomly divided into six groups: control, T2DM, metformin, high-dose BFTL (800 mg/kg), middle-dose BFTL (400 mg/kg), and low-dose BFTL (200 mg/kg). After 4 weeks of BFTL treatment, the correlations of serum indicators with protein expression in tissue were determined, and pathological changes in the liver, kidneys, and pancreas were analyzed.

Results

Compared with the results in the T2DM group, serum fasting blood glucose, triglyceride, total cholesterol, malondialdehyde, alanine aminotransferase, and aspartate aminotransferase levels were significantly decreased (p < 0.05), whereas superoxide dismutase and glutathione peroxidase levels were significantly increased (p < 0.05) in the high-, middle-, and low-dose BFTL groups. The treatment also improved oral glucose tolerance. In addition, the pathological changes of the liver, kidney, and pancreas were improved by BFTL treatment. Cytochrome and caspase-3 expression in pancreatic was significantly decreased (p < 0.05) by BFTL treatment, whereas the Bcl-2/Bax ratio was significantly increased (p < 0.05). Discussion and Conclusion. BFTL exerted significant hypoglycemic effect on T2DM model rats, and its mechanism involved the suppression of blood glucose levels and oxidative stress by improving the metabolism of blood lipids and antioxidant capacity, boosting β-cell function, and inhibiting β-cell apoptosis.

Does the Mediterranean diet reduce the odds of diabetic nephropathy in women? A case–control study

Background

In recent decades, the prevalence of chronic diseases such as diabetes is increasing. One of the major complications of diabetes is diabetic nephropathy (DN), so it is important to find a way that can delay or control the onset of DN. Therefore, in this study, we investigated the relationship between the Mediterranean diet (MED) and the odds of DN.

Methods

This case–control study was performed among 210 women (30–65 years) who were referred to the Kowsar Diabetes Clinic in Semnan, Iran. Biochemical variables and anthropometric measurements were assessed. The food frequency questionnaire (FFQ) was used to calculate dietary intakes. Data from dietary intakes based on the FFQ were used to evaluate the MED score. Logistic regression was used to examine the associations.

Results

Our results showed that in the crude model with higher adherence to the MED (OR: 0.272; 95% CI: 0.154, 0.481; P = 0.001), the odds of DN has reduced by 73%, and in model 1, after controlling for potential confounders, with higher adherence to the MED (OR: 0.239; 95% CI: 0.128, 0.447; P = 0.001), the odds of DN has reduced by 76% compared to low adherence. Also, in model 1, significant associations were observed between high consumption of grains (OR: 0.360; 95% CI: 0.191, 0.676; P = 0.001), legumes (OR: 0.156; 95% CI: 0.083, 0.292; P = 0.001), vegetables (OR: 0.273; 95% CI: 0.149, 0.501; P = 0.001), fruits (OR: 0.179; 95% CI: 0.093, 0.347; P = 0.001), fish (OR: 0.459; 95% CI: 0.254, 0.827; P = 0.01), and reduced odds of DN (P &lt; 0.05).

Conclusion

We observed that with higher adherence to the MED, the odds of DN had reduced through mechanisms. However, additional studies are needed to confirm these findings.

Therapeutic mechanisms of mulberry leaves in type 2 diabetes based on metabolomics

Background: Type 2 diabetes (T2D) is considered as one of the most significant metabolic syndromes worldwide, and the long-term use of the drugs already on the market for T2D often gives rise to some side effects. The mulberry leaf (ML), Morus alba L., has advantages in terms of its comprehensive therapeutic efficacy, which are characterized as multicomponent, multitarget, multipathway, and matching with the complex pathological mechanisms of diabetes.

Methods: T2D rats were established by a high-fat diet combined with an intraperitoneal injection of streptozotocin; an evaluation of the hypoglycemic effects of the ML in combination with fasting blood glucose and other indicators, in addition to the utilization of metabolomics technology, was performed to analysis the metabolite changes in serum of rats.

Results: MLs significantly reduced the fasting blood glucose of T2D rats, while improving the symptoms of polyphagia and polyuria. ML treatment altered the levels of various metabolites in the serum of T2D rats, which are involved in multiple metabolic pathways (amino acid metabolism, carbohydrate metabolism, and lipid metabolism), played a role in antioxidative stress and anti-inflammation, modulated immune and gluconeogenesis processes, and improved obesity as well as insulin resistance (IR).

Conclusion: The ML contains a variety of chemical components, and metabolomic results have shown that MLs regulate multiple metabolic pathways to exert hypoglycemic effects, suggesting that MLs may have great promise in the development of new hypoglycemic drugs.

Integrated Analyses of Microbiomics and Metabolomics Explore the Effect of Gut Microbiota Transplantation on Diabetes-Associated Cognitive Decline in Zucker Diabetic Fatty Rats

Diabetes-associated cognitive decline (DACD), one of the complications of type 2 diabetes (T2DM), correlates significantly with the disorder in glycolipid metabolism, insulin/leptin resistance, and accumulation of β-amyloid (Aβ). Although gut microbiota transplantation (GMT), a novel non-invasive physiotherapy strategy, has been a promising intervention to alleviate the symptoms of T2DM, its protective effect on progressive cognitive decline remains elusive. Here, we transplanted the gut microbiota of healthy or cognitive decline donor rats into ZDF or LZ rats, and integrated microbiomics and metabolomics to evaluate the directional effect of the gut microbiota on the recipient rats. The basal metabolism phenotype changed in ZDF rats instead of in LZ rats. One possible mechanism is that the microbiota and metabolites alter the structure of the intestinal tract, stimulate the brain insulin and leptin signaling pathways, and regulate the deposition of Aβ in the brain. It is worth noting that 10 species of genera, such as Parabacteroides, Blautia, and Lactobacillus, can regulate 20 kinds of metabolites, such as propanoic acid, acetic acid, and citramalic acid, and having a significant improvement on the cognitive behavior of ZDF rats. In addition, the correlation analysis indicated the gut microbiota and metabolites are highly associated with host phenotypes affected by GMT. In summary, our study indicates that altering the microbiota-gut-brain axis by reshaping the composition of gut microbiota is a viable strategy that has great potential for improving cognitive function and combatting DACD.

A Novel Integrated Biomarker for Evaluation of Risk and Severity of Coronary Atherosclerosis, and Its Validation

Objective: To assess the feasibility of a combination of biochemical and imaging parameters for estimation of risk and severity of coronary atherosclerosis (CA), and to verify the created integrated biomarker (i-BIO) on independent cohort. Methods: Two cohorts of patients admitted to the hospital for coronary angiography and ultrasound carotid dopplerography were enrolled into the study (n = 205 and n = 216, respectively). The extent of CA was assessed by Gensini Score (GS). Results: According to GS, participants were distributed as follows: atherosclerosis-free (GS = 0), CA of any stage (GS > 0), subclinical CA (GS < 35), severe CA (GS ≥ 35). Based on the analysis of mathematical models, including biochemical and imaging parameters, we selected and combined the most significant variables as i-BIO. The ability of i-BIO to detect the presence and severity of CA was estimated using ROC-analysis with cut-off points determination. Risk of any CA (GS > 0) at i-BIO > 4 was 7.3 times higher than in those with i-BIO ≤ 4; risk of severe CA (GS ≥ 35) at i-BIO ≥ 9 was 3.1 times higher than at i-BIO < 9. Results on the tested cohort confirmed these findings. Conclusions: The i-BIO > 4 detected CA (GS > 0) with sensitivity of 87.9%, i-BIO ≥ 9 excluded patients without severe CA (GS < 35), specificity 79.8%. Validation of i-BIO confirmed the feasibility of i-BIO > 4 to separate patients with any CA with sensitivity 76.2%, and of i-BIO ≥ 9 to exclude atherosclerosis-free subjects with specificity of 84.0%.

The role of interleukin-1β in type 2 diabetes mellitus: A systematic review and meta-analysis

Type 2 diabetes mellitus (T2DM) is a multifactorial non-communicable disease that is characterized by insulin resistance and chronic sub-clinical inflammation. Among the emerging inflammatory markers observed to be associated with β-cell damage is interleukin 1β (IL1β), a proinflammatory cytokine that modulates important metabolic processes including insulin secretion and β-cell apoptosis. The present systematic review and meta-analysis gathers available evidence on the emerging role of IL1β in T2DM. PubMed and Embase were searched for human studies that assessed 1L1β in T2DM individuals from 2016-2021. Thirteen studies (N=2680; T2DM=1182, controls=1498) out of 523 were included in the systematic review and only 3 studies in the meta-analysis. Assays were the most commonly used quantification method and lipopolysaccharides as the most common stimulator for IL1β upregulation. Random and fixed effects meta-analysis showed non-significant mean differences of IL1β concentrations between the T2DM and controls. Given the high heterogeneity and small subset of studies included, caution is advised in the interpretation of results. The present systematic review and meta-analysis highlights the limited evidence available that could implicate 1L1β as a potent biomarker for T2DM. Standardization of 1L1β assays with larger sample sizes are encouraged in future observational and prospective studies.

Gut microbial indicators of metabolic health underlie age-related differences in obesity and diabetes risk among Native Hawaiians and Pacific Islanders

Native Hawaiians and Pacific Islanders (NHPIs) suffer from higher prevalence of and mortality to type 2 diabetes mellitus (T2DM) than any other major race/ethnic group in Hawaii. Health inequities in this indigenous population was further exacerbated by the SARS-CoV-2 pandemic. T2DM progression and medical complications exacerbated by COVID-19 are partially regulated by the gut microbiome. However, there is limited understanding of the role of gut bacteria in the context of inflammation-related diseases of health disparities including T2DM and obesity. To address these gaps, we used a community-based research approach from a cohort enriched with NHPI residents on the island of Oahu, Hawaii (N=138). Gut microbiome profiling was achieved via 16s rDNA metagenomic sequencing analysis from stool DNA. Gut bacterial capacity for butyrate-kinase (BUK)-mediated fiber metabolism was assessed using quantitative PCR to measure the abundance of BUK DNA and RNA relative to total bacterial load per stool sample. In our cohort, age positively correlated with hemoglobin A1c (%; R=0.39; P<0.001) and body mass index (BMI; R=0.28; P<0.001). The relative abundance of major gut bacterial phyla significantly varied across age groups, including Bacteroidetes (P<0.001), Actinobacteria (P=0.007), and Proteobacteria (P=0.008). A1c was negatively correlated with the relative levels of BUK DNA copy number (R=-0.17; P=0.071) and gene expression (R=-0.33; P=0.003). Interestingly, we identified specific genera of gut bacteria potentially mediating the effects of diet on metabolic health in this cohort. Additionally, α-diversity among gut bacterial genera significantly varied across T2DM and BMI categories. Together, these results provide insight into age-related differences in gut bacteria that may influence T2DM and obesity in NHPIs. Furthermore, we observed overlapping patterns between gut bacteria and T2DM risk factors, indicating more nuanced, interdependent interactions among these factors as partial determinants of health outcomes. This study adds to the paucity of NHPI-specific data to further elucidate the biological characteristics associated with pre-existing health inequities in this racial/ethnic group that is significantly underrepresented in biomedical research.

Omics era in type 2 diabetes: From childhood to adulthood

Parallel to the dramatic rise of pediatric obesity, estimates reported an increased prevalence of type 2 diabetes (T2D) already in childhood. The close relationship between obesity and T2D in children is mainly sustained by insulin resistance (IR). In addition, the cardiometabolic burden of T2D including nonalcoholic fatty liver disease, cardiovascular disease and metabolic syndrome is also strictly related to IR. Although T2D pathophysiology has been largely studied in an attempt to improve therapeutic options, molecular mechanisms are still not fully elucidated. In this perspective, omics approaches (including lipidomics, metabolomics, proteomics and metagenomics) are providing the most attractive therapeutic options for T2D. In particular, distinct both lipids and metabolites are emerging as potential therapeutic tools. Of note, among lipid classes, the pathogenic role of ceramides in T2D context has been supported by several data. Thus, selective changes of ceramides expression might represent innovative therapeutic strategies for T2D treatment. More, distinct metabolomics pathways have been also found to be associated with higher T2D risk, by providing novel potential T2D biomarkers. Taken together, omics data are responsible for the expanding knowledge of T2D pathophysiology, by providing novel insights to improve therapeutic strategies for this tangled disease. We aimed to summarize the most recent evidence in the intriguing field of the omics approaches in T2D both in adults and children.

MicroRNA-506 modulates insulin resistance in human adipocytes by targeting S6K1 and altering the IRS1/PI3K/AKT insulin signaling pathway

The incidence of obesity has increased rapidly, becoming a worldwide public health issue that involves insulin resistance. A growing number of recent studies have demonstrated that microRNAs play a significant role in controlling the insulin signaling network. For example, miR-506-3p expression has been demonstrated to correlate with insulin sensitivity; however, the underlying mechanism remains unknown. In this study, we found that miR-506-3p enhanced glucose uptake by 2-deoxy-D-glucose uptake assays and regulated the protein expression of key genes involved in the PI3K/AKT insulin signaling pathway including IRS1, PI3K, AKT, and GlUT4. We next predicted ribosomal protein S6 kinase B1 (S6K1) to be a candidate target of miR-506-3p by bioinformatics analysis and confirmed using dual-luciferase assays that miR-506-3p regulated S6K1 expression by binding to its 3'-UTR. Moreover, modulating S6K1 expression counteracted the effects of miR-506-3p on glucose uptake and PI3K/AKT pathway activation. In conclusion, miR-506-3p altered IR in adipocytes by regulating S6K1-mediated PI3K/AKT pathway activation. Taken together, these findings provide novel insights and potential targets for IR therapy.

Bacterial Extracellular Vesicles in Gastrointestinal Tract Cancer: An Unexplored Territory

Bacterial extracellular vesicles are membrane-enclosed, lipid bi-layer nanostructures that carry different classes of biomolecules, such as nucleic acids, lipids, proteins, and diverse types of small molecular metabolites, as their cargo. Almost all of the bacteria in the gut secrete extracellular vesicles to assist them in competition, survival, material exchange, host immune modulation, infection, and invasion. The role of gut microbiota in the development, progression, and pathogenesis of gastrointestinal tract (GIT) cancer has been well documented. However, the possible involvement of bacterial extracellular vesicles (bEVs) in GIT cancer pathophysiology has not been given due attention. Studies have illustrated the ability of bEVs to cross physiological barriers, selectively accumulate near tumor cells, and possibly alter the tumor microenvironment (TME). A systematic search of original published works related to bacterial extracellular vesicles on gastrointestinal cancer was performed for this review. The current systemic review outlines the possible impact of gut microbiota derived bEVs in GIT cancer in light of present-day understanding. The necessity of using advanced sequencing technologies, such as genetic, proteomic, and metabolomic investigation methodologies, to facilitate an understanding of the interrelationship between cancer-associated bacterial vesicles and gastrointestinal cancer is also emphasized. We further discuss the clinical and pharmaceutical potential of bEVs, along with future efforts needed to understand the mechanism of interaction of bEVs in GIT cancer pathogenesis.

Proteomics changes after negative pressure wound therapy in diabetic foot ulcers

Label-free quantitative mass spectrometry was used to analyze the differences in the granulation tissue protein expression profiles of patients with diabetic foot ulcers (DFUs) before and after negative-pressure wound therapy (NPWT) to understand how NPWT promotes the healing of diabetic foot wounds. A total of three patients with DFUs hospitalized for Wagner grade 3 were enrolled. The patients received NPWT for one week. The granulation tissue samples of the patients prior to and following NPWT for one week were collected. The protein expression profiles were analyzed with label-free quantitative mass spectrometry and the differentially expressed proteins (DEPs) in the DFU patients prior to and following NPWT for one week were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were conducted to annotate the DEPs and DEP-associated signaling pathways. Western blotting and ELISA were performed to validate the results. By comparing the differences in the protein profiles of granulation tissue samples prior to and following NPWT for one week, 36 proteins with significant differences were identified (P<0.05); 33 of these proteins were upregulated and three proteins were downregulated. NPWT altered proteins mainly associated with antioxidation and detoxification, the cytoskeleton, regulation of the inflammatory response, complement and coagulation cascades and lipid metabolism. The functional validation of the DEPs demonstrated that the levels of cathepsin S in peripheral blood and granulation tissue were significantly lower than those prior to NPWT (P<0.05), while the levels of protein S isoform 1, inter α-trypsin inhibitor heavy chain H4 and peroxiredoxin-2 in peripheral blood and granulation tissue were significantly higher than those prior to NPWT (P<0.05). The present study identified multiple novel proteins altered by NPWT and laid a foundation for further studies investigating the mechanism of action of NPWT.

Multi-omics: Opportunities for research on mechanism of type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is a burdensome global disease. In-depth understanding of its mechanism will help to optimize diagnosis and treatment, which reduces the burden. Multi-omics research has unparalleled advantages in contributing to the overall understanding of the mechanism of this chronic metabolic disease. In the past two decades, the study of multi-omics on T2DM-related intestinal flora perturbation and plasma dyslipidemia has shown tremendous potential and is expected to achieve major breakthroughs. The regulation of intestinal flora in diabetic patients has been confirmed by multiple studies. The use of metagenomics, 16S RNA sequencing, and metabolomics has comprehensively identified the overall changes in the intestinal flora and the metabolic disturbances that could directly or indirectly participate in the intestinal flora-host interactions. Lipidomics combined with other “omics” has characterized lipid metabolism disorders in T2DM. The combined application and cross-validation of multi-omics can screen for dysregulation in T2DM, which will provide immense opportunities to understand the mechanisms behind T2DM.

Characterization of glucose-binding proteins isolated from health volunteers and human type 2 diabetes mellitus patients

Glucose is one of the most important monosaccharides. Although hyperglycemia in type 2 diabetes mellitus (T2DM) lead to a series of changes; however, little is known about the alterations of serum proteins in T2DM, especially those proteins with glucose affinity. In this study, the glucose-binding proteins (GlcBPs) of serum were isolated from 30 health volunteer (HV) and 30 T2DM patients by glucose-magnetic particle conjugates (GMPC) and identified by mass spectrum analysis. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) indicated the main gene annotations and pathways of this GlcBPs, while Motif-X webtool provided the potential glucose-binding domains. Further docking analysis and glycan microarray were used to understand the interaction between the glucose and glucose-binding domains. A total of 149 and 119 GlcBPs were identified from HV and T2DM cases. Four hundred and sixty-eight GO annotations in 165 identified GlcBPs were available, while the majority involved in cellular processes and binding function. A short peptide, EGDEEITCLNGFWLE, which was derived from the Motif-X analysis, presented a high-binding ability to the glucose from both docking analysis and glycan analysis. GMPC provides a powerful tool for GlcBPs isolation and indicates the alteration of GlcBPs in T2DM.

Identification of Key Biomarkers and Immune Infiltration in Sciatic Nerve of Diabetic Neuropathy BKS-db/db Mice by Bioinformatics Analysis

Diabetic neuropathy (DN) is one of the chronic complications of diabetes which can cause severe harm to patients. In order to determine the key genes and pathways related to the pathogenesis of DN, we downloaded the microarray data set GSE27382 from Gene Expression Omnibus (GEO) and adopted bioinformatics methods for comprehensive analysis, including functional enrichment, construction of PPI networks, central genes screening, TFs-target interaction analysis, and evaluation of immune infiltration characteristics. Finally, we examined quantitative real- time PCR (qPCR) to validate the expression of hub genes. A total of 318 differentially expressed genes (DEGs) were identified, among which 125 upregulated DEGs were enriched in the mitotic nuclear division, extracellular region, immunoglobulin receptor binding, and p53 signaling pathway, while 193 downregulated DEGs were enriched in ion transport, membrane, synapse, sodium channel activity, and retrograde endocannabinoid signaling. GSEA plots showed that condensed nuclear chromosome kinetochore were the most significant enriched gene set positively correlated with the DN group. Importantly, we identified five central genes (Birc5, Bub1, Cdk1, Ccnb2, and Ccnb1), and KEGG pathway analysis showed that the five hub genes were focused on progesterone-mediated oocyte maturation, cell cycle, and p53 signaling pathway. The proportion of immune cells from DN tissue and normal group showed significant individual differences. In DN samples, T cells CD4 memory resting and dendritic cells resting accounted for a higher proportion, and macrophage M2 accounted for a lower proportion. In addition, all five central genes showed consistent correlation with immune cell infiltration levels. qPCR showed the same expression trend of five central genes as in our analysis. Our research identified key genes related to differential genes and immune infiltration related to the pathogenesis of DN and provided new diagnostic and potential therapeutic targets for DN.

A Prediction Model Based on Noninvasive Indicators to Predict the 8-Year Incidence of Type 2 Diabetes in Patients with Nonalcoholic Fatty Liver Disease: A Population-Based Retrospective Cohort Study

Background

The prevention of type 2 diabetes (T2D) and its associated complications has become a major priority of global public health. In addition, there is growing evidence that nonalcoholic fatty liver disease (NAFLD) is associated with an increased risk of diabetes. Therefore, the purpose of this study was to develop and validate a nomogram based on independent predictors to better assess the 8-year risk of T2D in Japanese patients with NAFLD.

Methods

This is a historical cohort study from a collection of databases that included 2741 Japanese participants with NAFLD without T2D at baseline. All participants were randomized to a training cohort (n = 2058) and a validation cohort (n = 683). The data of the training cohort were analyzed using the least absolute shrinkage and selection operator method to screen the suitable and effective risk factors for Japanese patients with NAFLD. A cox regression analysis was applied to build a nomogram incorporating the selected features. The C-index, receiver operating characteristic curve (ROC), calibration plot, decision curve analysis, and Kaplan-Meier analysis were used to validate the discrimination, calibration, and clinical usefulness of the model. The results were reevaluated by internal validation in the validation cohort.

Results

We developed a simple nomogram that predicts the risk of T2D for Japanese patients with NAFLD by using the parameters of smoking status, waist circumference, hemoglobin A1c, and fasting blood glucose. For the prediction model, the C-index of training cohort and validation cohort was 0.839 (95% confidence interval (CI), 0.804-0.874) and 0.822 (95% CI, 0.777-0.868), respectively. The pooled area under the ROC of 8-year T2D risk in the training cohort and validation cohort was 0.811 and 0.805, respectively. The calibration curve indicated a good agreement between the probability predicted by the nomogram and the actual probability. The decision curve analysis demonstrated that the nomogram was clinically useful.

Conclusions

We developed and validated a nomogram for the 8-year risk of incident T2D among Japanese patients with NAFLD. Our nomogram can effectively predict the 8-year incidence of T2D in Japanese patients with NAFLD and helps to identify people at high risk of T2D early, thus contributing to effective prevention programs for T2D.

The Multiomics Analyses of Fecal Matrix and Its Significance to Coeliac Disease Gut Profiling

Gastrointestinal (GIT) diseases have risen globally in recent years, and early detection of the host’s gut microbiota, typically through fecal material, has become a crucial component for rapid diagnosis of such diseases. Human fecal material is a complex substance composed of undigested macromolecules and particles, and the processing of such matter is a challenge due to the unstable nature of its products and the complexity of the matrix. The identification of these products can be used as an indication for present and future diseases; however, many researchers focus on one variable or marker looking for specific biomarkers of disease. Therefore, the combination of genomics, transcriptomics, proteomics and metabonomics can give a detailed and complete insight into the gut environment. The proper sample collection, sample preparation and accurate analytical methods play a crucial role in generating precise microbial data and hypotheses in gut microbiome research, as well as multivariate data analysis in determining the gut microbiome functionality in regard to diseases. This review summarizes fecal sample protocols involved in profiling coeliac disease.

Correlation Analysis between GDM and Gut Microbial Composition in Late Pregnancy

The prevalence of GDM is very high worldwide. The specific pathogenesis of GDM is currently not very clear. Recent research suggests that changes in the intestinal flora during pregnancy play a key role in it. Therefore, this study is aimed at exploring the characteristics of the intestinal flora of patients with gestational diabetes in the third trimester of pregnancy and at finding the intestinal flora with significant differences in healthy pregnant women to provide a basis for future clinical attempts of using intestinal microecological agents to treat gestational diabetes mellitus (GDM). We sequenced the V3-V4 regions of the 16S ribosomal ribonucleic acid (rRNA) gene from stool samples of 52 singleton pregnant women at >28 weeks of gestation. Our results showed that there were significant differences between the NOR group vs. GDM group and the G group vs. LG group among Bacteroides, Firmicutes, and Firmicutes/Bacteroides. At the species level, there were significant differences in the abundance of eight species in the NOR and GDM groups. Among them, the relative abundance of Clostridium_spiroforme, Eubacterium_dolichum, and Ruminococcus_gnavus was positively correlated with FBG, and Pyramidobacter_piscolens was negatively correlated with FBG, whereas there were significant differences in the abundance of five species in the G and LG groups. Functional analysis showed that there were differences in the biosynthesis and metabolism of polysaccharides, digestive system, classification, and degradation of the intestinal microbes between the NOR and GDM groups and between the G and LG groups. These results indicated that the gut microbes between GDM patients in the third trimester of pregnancy and healthy controls had essential characteristic changes and might be involved in the regulation of patients' blood glucose levels.

Cancer Signaling Transcriptome Is Upregulated in Type 2 Diabetes Mellitus

We aimed to explore the differences in the whole transcriptome of peripheral blood mononuclear cells between elderly individuals with and without type 2 diabetes (T2D). We conducted a microarray-based transcriptome analysis of 19 individuals with T2D and 15 without. Differentially expressed genes according to linear models were submitted to the Ingenuity Pathway Analysis system to conduct a functional enrichment analysis. We established that diseases, biological functions, and canonical signaling pathways were significantly associated with T2D patients when their logarithms of Benjamini–Hochberg-adjusted p-value were >1.30 and their absolute z-scores were >2.0 (≥2.0 meant “upregulation” and ≤ −2.0 “downregulation”). Cancer signaling pathways were the most upregulated ones in T2D (z-score = 2.63, −log(p-value) = 32.3; 88.5% (n = 906) of the total differentially expressed genes located in these pathways). In particular, integrin (z-score = 2.52, −log(p-value) = 2.03) and paxillin (z-score = 2.33, −log(p-value) = 1.46) signaling pathways were predicted to be upregulated, whereas the Rho guanosine diphosphate (Rho-GDP) dissociation inhibitor signaling pathway was predicted to be downregulated in T2D individuals (z-score = −2.14, −log(p-value) = 2.41). Our results suggest that, at transcriptional expression level, elderly individuals with T2D present an increased activation of signaling pathways related to neoplastic processes, T-cell activation and migration, and inflammation.

Exploring efficacy of natural-derived acetylphenol scaffold inhibitors for α-glucosidase: Synthesis, in vitro and in vivo biochemical studies

The discovery of novel α-glucosidase inhibitors and anti-diabetic candidates from natural or natural-derived products represents an attractive therapeutic option. Here, a collection of acetylphenol analogues derived from paeonol and acetophenone were synthesized and evaluated for their α-glucosidase inhibitory activity. Most of derivatives, such as 9a-9e, 9i, 9m-9n and 11d-1e, (IC₅₀ = 0.57 ± 0.01 μM to 8.45 ± 0.57 μM), exhibited higher inhibitory activity than the parent natural products and were by far more potent than the antidiabetic drug acarbose (IC₅₀ = 57.01 ± 0.03 μM). Among these, 9e and 11d showed the most potent activity in a non-competitive manner. The binding processes between the two most potent compounds and α-glucosidase were spontaneous. Hydrophobic interactions were the main forces for the formation and stabilization of the enzyme - acetylphenol scaffold inhibitor complex, and induced the topography image changes and aggregation of α-glucosidase. In addition, everted intestinal sleeves in vitro and the maltose loading test in vivo further demonstrated the α-glucosidase inhibition of the two compounds, and our findings proved that they have significant postprandial hypoglycemic effects.

Integration of transcriptomic, proteomic and metabolomic data to reveal the biological mechanisms of AAI injury in renal epithelial cells

Overexposure to aristolochic acid I (AAI) can induce aristolochic acid nephropathy (AAN). However, the comprehensive mechanisms of AAI-induced nephrotoxicity have not been entirely explicated. To investigate the toxicological mechanisms by which AAI induces renal injury, human kidney cells (HK-2 cells) were subjected to comprehensive transcriptomic, proteomic and metabolomic analyses. The transcriptomic analysis identified a total of 7749 differentially expressed genes (DEGs) after AAI treatment, while the proteomic analysis found 598 differentially expressed proteins (DEPs) after AAI treatment. The metabolomic analysis revealed 49 and 42 differentially expressed metabolites (DEMs) in the positive and negative ion modes, respectively. Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on these DEGs, DEPs and DEMs. The results of the comprehensive analyses of transcripts, proteins, and metabolites indicated that the DEGs, DEPs, and DEMs were jointly regulated in three ways. These genes, proteins and metabolites and their related dysregulated pathways may be promising targets for research on the mechanisms of AAI injury in human renal epithelial cells. This study provides large-scale omics data that can be used to formulate new strategies for the prevention, rapid diagnosis, and treatment of AAI injury.

Prevalence of nephropathy in patients with type 2 diabetes in Iran: A systematic review and meta-analysis based on geographic information system (GIS)

BACKGROUND AND AIMS

Diabetic nephropathy are one of the most important causes of renal failure and dysfunction in diabetic patients and imposes high costs for the healthcare system. Studies conducted in Iran show different prevalence. This study aims to determine the overall prevalence of nephropathy in patients with type 2 diabetes in Iran with a systematic review and meta-analysis.

METHODS

The present study was carried out by meta-analysis from January 2000 to May 2020. Related articles were obtained through searching in Scopus, Cochrane, Library, ScienceDirect, Embase, SID, Magiran, Barakatkns, Medline (PubMed), and Google Scholar. Heterogeneity of studies was studied using I² index and data were analyzed using Comprehensive Meta-Analysis and Arc map (ArcGIS 10.6) software.

RESULTS

In a review of 18 articles and 6190 subjects aged 20-83 years, the overall prevalence of nephropathy in patients with type 2 diabetes in Iran was 30.6% (95%CI: 24.3-37.7) based on a meta-analysis. The highest prevalence of nephropathy in patients with type 2 diabetes was obtained in Tehran province with 57.3% (95%CI: 51.5-62.9) in 2008 and the lowest prevalence of nephropathy in patients with type 2 diabetes was obtained in Hamedan province with 14.4% (95%CI: 11.3-18.8) in 2016. An increase in sample size and research year reduces the prevalence of nephropathy in patients with type 2 diabetes in Iran, and differences were statistically significant (P < 0.05).

CONCLUSION

Considering the high prevalence of nephropathy in patients with type 2 diabetes in Iran, it is essential that health policymakers take effective measures to reduce this disease in diabetic patients.

Progress in the Treatment of Diabetes Mellitus Based on Intestinal Flora Homeostasis and the Advancement of Holistic Analysis Methods

Diabetes mellitus (DM) is a complex metabolic disorder characterized by abnormal glucose metabolism, which is accompanied by alterations in energy metabolism, intestinal bacterial metabolism, amino acid metabolism, lipid metabolism, nucleotide metabolism, and others. However, intestinal flora metabolism plays a fundamental role in host metabolism; they are complementary to each other and help maintain homeostasis, thus ensuring the normal operation of the host metabolic system. This suggests that a holistic analysis method would be of great use in the study of the overall metabolism in patients with DM. With this in mind, this review summarizes the mechanism of intestinal flora metabolism regarding the occurrence of DM and assesses the effects of drug treatments on the intestinal flora of patients with diabetes. Based on these results, we combined intestinal flora metabolism with host metabolism to evaluate the necessity and the advantages of holistic metabonomics analyses in the treatment of DM and its complications.

Identification of Hub Genes in Type 2 Diabetes Mellitus Using Bioinformatics Analysis

BACKGROUND

Type 2 diabetes mellitus (T2DM) is one of the most common chronic diseases in the world with complicated pathogenesis. This study aimed to identify differentially expressed genes (DEGs) and molecular pathways in T2DM using bioinformatics analysis.

MATERIALS AND METHODS

To explore potential therapeutic targets for T2DM, we analyzed three microarray datasets (GSE50397, GSE38642, and GSE44035) acquired from the Gene Expression Omnibus (GEO) database. DEGs between T2DM islet and normal islet were picked out by the GEO2R tool and Venn diagram software. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) to identify the pathways and functional annotation of DEGs. Then, protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes/Proteins (STRING).

RESULTS

In total, we identified 36 DEGs in the three datasets, including 32 up-regulated genes and four down-regulated genes. The improved functions and pathways of the DEGs enriched in cytokine-cytokine receptor interaction, pathways in cancer, PI3K-Akt signaling pathway, and Rheumatoid arthritis. Among them, ten hub genes with a high degree of connectivity were selected. Furthermore, via the re-analysis of DAVID, four genes (IL6, MMP3, MMP1, and IL11) were significantly enriched in the Rheumatoid arthritis pathway.

CONCLUSION

Our study, based on the GEO database, identified four significant up-regulated DEGs and provided novel targets for diagnosis and treatment of T2DM.

Optimization Techniques to Deeply Mine the Transcriptomic Profile of the Sub-Genomes in Hybrid Fish Lineage

It has been shown that reciprocal cross allodiploid lineage with sub-genomes derived from the cross of Megalobrama amblycephala (BSB) × Culter alburnus (TC) generates the variations in phenotypes and genotypes, but it is still a challenge to deeply mine biological information in the transcriptomic profile of this lineage owing to its genomic complexity and lack of efficient data mining methods. In this paper, we establish an optimization model by non-negative matrix factorization approach for deeply mining the transcriptomic profile of the sub-genomes in hybrid fish lineage. A new so-called spectral conjugate gradient algorithm is developed to solve a sequence of large-scale subproblems such that the original complicated model can be efficiently solved. It is shown that the proposed method can provide a satisfactory result of taxonomy for the hybrid fish lineage such that their genetic characteristics are revealed, even for the samples with larger detection errors. Particularly, highly expressed shared genes are found for each class of the fish. The hybrid progeny of TC and BSB displays significant hybrid characteristics. The third generation of TC-BSB hybrid progeny (BTF3 and TBF3) shows larger trait separation.

Inhibition of cyclin-dependent kinase 5 activity alleviates diabetes-related cognitive deficits

Cognitive deficit is a prevalent and underestimated complication of diabetes, and the underlying cellular and molecular mechanisms are not well understood. Aberrant activity of cyclin-dependent kinase (Cdk)5 is implicated in a number of neurodegenerative diseases. The present study examined the role of Cdk5 in the progression of diabetes-related cognitive deficits. We showed that the Cdk5 protein expression and kinase activity were significantly increased in diabetic mice at 16 wk. In primary cultured hippocampal neurons exposed to 30 mM glucose, Cdk5 protein and kinase activity were also elevated in a time-dependent manner. Moreover, the high glucose exposure led to an aberrant Cdk5 activation due to its activator p25 that was cleaved from p35 by calpain. Both in diabetic mice and in cultured hippocampal neurons exposed to high glucose, inhibition of Cdk5 activity with roscovitine (Ros) or short hairpin RNA (shRNA) decreased the protein levels of cleaved caspase-3 and the ratio of Bax and Bcl-2. The apoptotic rate detected by TUNEL in vivo or Annexin V and propidium iodide staining for flow cytometry in vitro also had obvious reduction. In addition, high glucose exposure resulted in the increase of phosphorylated (phospho)-MAPK kinase (MKK)6, phospho-p38, and c-Jun, which were rescued by Ros or Cdk5 shRNA. It is more important that the cognitive deficits of diabetic mice were also effectively alleviated by Ros. These results indicate that aberrant Cdk5 activity triggered hippocampal neuron apoptosis by activating MKK6/p38 MAPK cascade in hyperglycemia. Inhibition of Cdk5 overactivation attenuates neuronal apoptosis and cognitive deficits and contributes to the relief of diabetic neurotoxicity in the brain.-Liu, W., Zhou, Y., Liang, R., Zhang, Y. Inhibition of cyclin-dependent kinase 5 activity alleviates diabetes-related cognitive deficits.

Relevance of Multi-Omics Studies in Cardiovascular Diseases

Cardiovascular diseases are the leading cause of death around the world. Despite the larger number of genes and loci identified, the precise mechanisms by which these genes influence risk of cardiovascular disease is not well understood. Recent advances in the development and optimization of high-throughput technologies for the generation of “omics data” have provided a deeper understanding of the processes and dynamic interactions involved in human diseases. However, the integrative analysis of “omics” data is not straightforward and represents several logistic and computational challenges. In spite of these difficulties, several studies have successfully applied integrative genomics approaches for the investigation of novel mechanisms and plasma biomarkers involved in cardiovascular diseases. In this review, we summarized recent studies aimed to understand the molecular framework of these diseases using multi-omics data from mice and humans. We discuss examples of omics studies for cardiovascular diseases focused on the integration of genomics, epigenomics, transcriptomics, and proteomics. This review also describes current gaps in the study of complex diseases using systems genetics approaches as well as potential limitations and future directions of this emerging field.

An integrative investigation on the efficacy of Plantaginis semen based on UPLC-QTOF-MS metabolomics approach in hyperlipidemic mice

Plantaginis semen, the dried mature seed of Plantago asiatica L. or Plantago deprdssa Willd., has a prominent effect on the treatment of obesity, type 2 diabetes and lipid disorders, however, its clinical application is limited due to inadequate in-depth mechanism exploration and incomplete discussion of action targets of its in vivo. Therefore, an untargeted metabolomics approach was firstly applied to study the serum metabolic differences in mice. Metabolomics analysis was performed using ultra performance liquid chromatography quadrupole time of flight mass spectrometry (UPLC-QTOF-MS) together with multivariate statistical data analysis. The results showed that Plantaginis semen can mainly improve blood lipids, some degree in blood glucose and insulin levels in high-fat mice, in addition, the phenotype of liver and fat stained sections demonstrated remarkable results. A total of 22 metabolites involved in arachidonic acid, glycerophospholipid, glycosphingolipid, linoleate, Omega-3 fatty acid, phosphatidylinositol phosphate and tyrosine metabolisms were identified. In further, it was found that the possible mechanisms of Plantaginis semen on hyperlipidemic mice lied in the biosynthesis of thyroxine, biological effects of enzymes of phospholipase A2 activity, glucosylceramide synthase and inositol essential enzyme 1α, genes expressions of fatty acid metabolism and inflammation. Serum metabolomics revealed that Plantaginis semen could cure the organism disease via regulating multiple metabolic pathways which will be helpful for understanding the mechanism of this herb and providing references for better applications of it in clinic, even researches on other TCMs.