Metabolomics window into diabetic complications

High Glucose-Induced Senescent Fibroblasts-Derived Exosomal miR-497 Inhibits Wound Healing by Regulating Endothelial Cellular Autophagy via ATG13

Background: Fibroblasts play a crucial role in diabetic wound healing, and their senescence is the cause of delayed wound repair. It was reported that fibroblasts can secrete exosomes that can mediate a vital role in diabetic complications. Our purpose is to examine the biological function of high glucose (HG)-induced senescent fibroblasts from the perspective of exosomes and reveal the mechanism at cellular and animal levels. Methods: HG-induced senescent fibroblasts were measured by senescence-associated β-galactosidase staining and immunofluorescence. Flow cytometry, 5-ethynyl-2'-deoxyuridine (edu), and cell counting kit 8 (CCK-8) assay were applied to detect apoptosis and cell viability. Fibroblasts and endothelial cells were cocultured, and the migration and angiogenesis abilities were detected by scratch, transwell, and tube formation assays. Exosomes were isolated and identified from fibroblasts that were treated differently. Then, the function of exosomes was investigated in cells and mice, including examining the cellular phenotype changes, detecting the autophagy levels, and evaluating the wound healing rate. Furthermore, the potential mechanism by which senescent fibroblast-derived exosomes inhibit wound healing was examined via bioinformatics, real-time quantitive polymerase chain reaction (qPCR), transfection, and dual-luciferase assays. Results: It illustrated that HG-induced senescent fibroblasts exhibited adverse impacts on cellular proliferation, migration, and angiogenesis of endothelial cells via secreting exosomes, and senescent fibroblast-derived exosomes (S-Exos) can delay skin wound defects in mice. Subsequent differential analysis of the GSE153214 and GSE48417 datasets elucidated that miR-497 was the biomarker in the senescent fibroblasts. Interestingly, the miR-497 levels were also elevated in S-Exos. Its overexpression can regulate human umbilical vein endothelial cell function by regulating autophagy via targeting ATG13. Furthermore, in vivo experiments also illustrated that miR-497 can delay wound healing and reduce autophagy. Conclusions: Our study demonstrated that exosomes from senescent fibroblasts can impair endothelial cell function and impede diabetic wound healing. The underlying mechanism was that fibroblast-derived exosomal miR-497 can target ATG13 to reduce autophagy, offering insight into new therapy for diabetic complications and other diseases.

Advancements, Challenges, and clinical implications of integration of metabolomics technologies in diabetic nephropathy

BACKGROUND

Diabetic nephropathy (DN), a severe complication of diabetes, involves a range of renal abnormalities driven by metabolic derangements. Metabolomics, revealing dynamic metabolic shifts in diseases like DN and offering insights into personalized treatment strategies, emerges as a promising tool for improved diagnostics and therapies.

METHODS

We conducted an extensive literature review to examine how metabolomics contributes to the study of DN and the challenges associated with its implementation in clinical practice. We identified and assessed relevant studies that utilized metabolomics methods, including nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) to assess their efficacy in diagnosing DN.

RESULTS

Metabolomics unveils key pathways in DN progression, highlighting glucose metabolism, dyslipidemia, and mitochondrial dysfunction. Biomarkers like glycated albumin and free fatty acids offer insights into DN nuances, guiding potential treatments. Metabolomics detects small-molecule metabolites, revealing disease-specific patterns for personalized care.

CONCLUSION

Metabolomics offers valuable insights into the molecular mechanisms underlying DN progression and holds promise for personalized medicine approaches. Further research in this field is warranted to elucidate additional metabolic pathways and identify novel biomarkers for early detection and targeted therapeutic interventions in DN.

Sarcopenia: A dive into metabolism to promote a multimodal, preventive, and regenerative approach

Sarcopenia, the age-related loss of skeletal muscle mass and function, poses a significant challenge in the field of geriatrics and gerontology, impacting the health and independence of older adults. Understanding and addressing sarcopenia is crucial for optimizing clinical outcomes and enhancing the quality of life along with aging. By synthesizing current research findings and theoretical frameworks, this review elucidates the multifaceted mechanisms underlying sarcopenia, mainly focusing on energy balance and metabolic processes. Furthermore, the manuscript explores the implications of sarcopenia on overall health outcomes, functional decline, and quality of life in older individuals. The study concludes with a perspective on the role of preventive and regenerative medicine in sarcopenia, where the two main lifestyle pillars (exercise and diet) represent key factors.

Therapeutic implications of dapagliflozin on the metabolomics profile of diabetic rats: A GC-MS investigation coupled with multivariate analysis

BACKGROUND

Diabetes mellitus is a complex metabolic disorder with systemic implications, necessitating the search for reliable biomarkers and therapeutic strategies. This study investigates the metabolomics profile alterations in diabetic rats, with a focus on the therapeutic effects of Dapagliflozin, a drug known to inhibit renal glucose reabsorption, using Gas Chromatography-Mass Spectrometry analysis.

METHODS

A GC-MS based metabolomics approach combined with multivariate and univariate statistical analyses was utilized to study serum samples from a diabetic model of Wistar rats, treated with dapagliflozin. Metabolomics pathways analysis was also performed to identify the altered metabolic pathways associated with the disease and the intervention.

RESULTS

Dapagliflozin treatment in diabetic rats resulted in normalized levels of metabolites associated with insulin resistance, notably branched-chain and aromatic amino acids. Improvements in glycine metabolism were observed, suggesting a modulatory role of the drug. Additionally, reduced palmitic acid levels indicated an alleviation of lipotoxic effects. The metabolic changes indicate a restorative effect of dapagliflozin on diabetes-induced metabolic perturbations.

CONCLUSIONS

The comprehensive metabolomics analysis demonstrated the potential of GC-MS in revealing significant metabolic pathway alterations due to dapagliflozin treatment in diabetic model rats. The therapy induced normalization of key metabolic disturbances, providing insights that could advance personalized diabetes mellitus management and therapeutic monitoring, highlighting the utility of metabolomics in understanding drug mechanisms and effects.

Precision Cardio-oncology: Update on Omics-Based Diagnostic Methods

OPINION STATEMENT

Cardio-oncology is an emerging interdisciplinary field dedicated to the early detection and treatment of adverse cardiovascular events associated with anticancer treatment, and current clinical management of anticancer-treatment-related cardiovascular toxicity (CTR-CVT) remains limited by a lack of detailed phenotypic data. However, the promise of diagnosing CTR-CVT using deep phenotyping has emerged with the development of precision medicine, particularly the use of omics-based methodologies to discover sensitive biomarkers of the disease. In the future, combining information produced by a variety of omics methodologies could expand the clinical practice of cardio-oncology. In this review, we demonstrate how omics approaches can improve our comprehension of CTR-CVT deep phenotyping, discuss the positive and negative aspects of available omics approaches for CTR-CVT diagnosis, and outline how to integrate multiple sets of omics data into individualized monitoring and treatment. This will offer a reliable technical route for lowering cardiovascular morbidity and mortality in cancer patients and survivors.

Development and External Validation of Machine Learning Models for Diabetic Microvascular Complications: Cross-Sectional Study With Metabolites

BACKGROUND

Diabetic kidney disease (DKD) and diabetic retinopathy (DR) are major diabetic microvascular complications, contributing significantly to morbidity, disability, and mortality worldwide. The kidney and the eye, having similar microvascular structures and physiological and pathogenic features, may experience similar metabolic changes in diabetes.

OBJECTIVE

This study aimed to use machine learning (ML) methods integrated with metabolic data to identify biomarkers associated with DKD and DR in a multiethnic Asian population with diabetes, as well as to improve the performance of DKD and DR detection models beyond traditional risk factors.

METHODS

We used ML algorithms (logistic regression [LR] with Least Absolute Shrinkage and Selection Operator and gradient-boosting decision tree) to analyze 2772 adults with diabetes from the Singapore Epidemiology of Eye Diseases study, a population-based cross-sectional study conducted in Singapore (2004-2011). From 220 circulating metabolites and 19 risk factors, we selected the most important variables associated with DKD (defined as an estimated glomerular filtration rate <60 mL/min/1.73 m2) and DR (defined as an Early Treatment Diabetic Retinopathy Study severity level ≥20). DKD and DR detection models were developed based on the variable selection results and externally validated on a sample of 5843 participants with diabetes from the UK biobank (2007-2010). Machine-learned model performance (area under the receiver operating characteristic curve [AUC] with 95% CI, sensitivity, and specificity) was compared to that of traditional LR adjusted for age, sex, diabetes duration, hemoglobin A1c, systolic blood pressure, and BMI.

RESULTS

Singapore Epidemiology of Eye Diseases participants had a median age of 61.7 (IQR 53.5-69.4) years, with 49.1% (1361/2772) being women, 20.2% (555/2753) having DKD, and 25.4% (685/2693) having DR. UK biobank participants had a median age of 61.0 (IQR 55.0-65.0) years, with 35.8% (2090/5843) being women, 6.7% (374/5570) having DKD, and 6.1% (355/5843) having DR. The ML algorithms identified diabetes duration, insulin usage, age, and tyrosine as the most important factors of both DKD and DR. DKD was additionally associated with cardiovascular disease history, antihypertensive medication use, and 3 metabolites (lactate, citrate, and cholesterol esters to total lipids ratio in intermediate-density lipoprotein), while DR was additionally associated with hemoglobin A1c, blood glucose, pulse pressure, and alanine. Machine-learned models for DKD and DR detection outperformed traditional LR models in both internal (AUC 0.838 vs 0.743 for DKD and 0.790 vs 0.764 for DR) and external validation (AUC 0.791 vs 0.691 for DKD and 0.778 vs 0.760 for DR).

CONCLUSIONS

This study highlighted diabetes duration, insulin usage, age, and circulating tyrosine as important factors in detecting DKD and DR. The integration of ML with biomedical big data enables biomarker discovery and improves disease detection beyond traditional risk factors.

Untargeted metabolomics analysis reveals spatial metabolic heterogeneity in different intestinal segments of type 1 diabetic mice

Type 1 diabetes (T1D) has been reported to cause systematic metabolic disorders, but metabolic changes in different intestinal segments of T1D remain unclear. In this study, we analyzed metabolic profiles in the jejunum, ileum, cecum and colon of streptozocin-induced T1D and age-matched control (CON) mice by an LC-MS-based metabolomics method. The results show that segment-specific metabolic disorders occurred in the gut of T1D mice. In the jejunum, we found that T1D mainly led to disordered amino acid metabolism and most amino acids were significantly lower relative to CON mice. Moreover, fatty acid metabolism was disrupted mainly in the ileum, cecum and colon of T1D mice, such as arachidonic acid, alpha-linolenic acid and linoleic acid metabolism. Thus, our study reveals spatial metabolic heterogeneity in the gut of T1D mice and provides a metabolic view on diabetes-associated intestinal diseases.

Salvianolic acid B and tanshinone IIA synergistically improve early diabetic nephropathy through regulating PI3K/Akt/NF-κB signaling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Diabetic nephropathy (DN) is one of the most common and serious complications of diabetes, which lacks effective treatment. Salviae Miltiorrhizae Radix Et Rhizoma is one of the key compatible traditional Chinese medicine in the prescription for the treatment of DN. Salvianolic acid B and tanshinone IIA are two monomer active components with high content and clear structure in Salvia miltiorrhiza, which can effectively improve early (DN), respectively.

AIM OF THE STUDY

To evaluate the compatible effect of salvianolic acid B and tanshinone IIA on early DN rats and elucidate the mechanism.

METHODS

Early DN rats were induced by streptozotocin combined with high glucose and high fat diet, and intervened by salvianolic acid B, tanshinone IIA and their combinations. The pathological sections of kidney, liver and biochemical indexes were analyzed. Network pharmacology method was used to predict the possible mechanism. The mechanisms were elucidated by metabolomics, Elisa, and Western blot.

RESULTS

Given our analysis, salvianolic acid B and tanshinone IIA can synergistically regulate 24 h UTP, Urea and Scr and improve kidney damage in early DN rats. The metabolic abnormalities of early DN rats were improved by regulating the biosynthesis of saturated fatty acids, glycerol phospholipid metabolism, steroid biosynthesis, alanine, and arachidonic acid. Salvianolic acid B combined with tanshinone IIA at a mass ratio of 13.4:1 can significantly reduce kidney inflammation, up-regulate p-PI3K/PI3K and p-Akt/Akt and down-regulate p-NF-κB/NF-κB, which better than the single-used group and can be reversed by PI3K inhibitor LY294002.

CONCLUSION

Salvianolic acid B and tanshinone IIA can synergistically improve glucose and lipid disorders, liver and kidney damage, and resist kidney inflammation in early DN rats, and the mechanism may be related to regulating PI3K/Akt/NF-κB signaling pathway.

Characterizing the metabolic divide: distinctive metabolites differentiating CAD-T2DM from CAD patients

OBJECTIVE

To delineate the metabolomic differences in plasma samples between patients with coronary artery disease (CAD) and those with concomitant CAD and type 2 diabetes mellitus (T2DM), and to pinpoint distinctive metabolites indicative of T2DM risk.

METHOD

Plasma samples from CAD and CAD-T2DM patients across three centers underwent comprehensive metabolomic and lipidomic analyses. Multivariate logistic regression was employed to discern the relationship between the identified metabolites and T2DM risk. Characteristic metabolites' metabolic impacts were further probed through hepatocyte cellular experiments. Subsequent transcriptomic analyses elucidated the potential target sites explaining the metabolic actions of these metabolites.

RESULTS

Metabolomic analysis revealed 192 and 95 significantly altered profiles in the discovery (FDR < 0.05) and validation (P < 0.05) cohorts, respectively, that were associated with T2DM risk in univariate logistic regression. Further multivariate regression analyses identified 22 characteristic metabolites consistently associated with T2DM risk in both cohorts. Notably, pipecolinic acid and L-pipecolic acid, lysine derivatives, exhibited negative association with CAD-T2DM and influenced cellular glucose metabolism in hepatocytes. Transcriptomic insights shed light on potential metabolic action sites of these metabolites.

CONCLUSIONS

This research underscores the metabolic disparities between CAD and CAD-T2DM patients, spotlighting the protective attributes of pipecolinic acid and L-pipecolic acid. The comprehensive metabolomic and transcriptomic findings provide novel insights into the mechanism research, prophylaxis and treatment of comorbidity of CAD and T2DM.

Oxidative Stress Mediates Epigenetic Modifications and the Expression of miRNAs and Genes Related to Apoptosis in Diabetic Retinopathy Patients

Knowledge on the underlying mechanisms and molecular targets for managing the ocular complications of type 2 diabetes mellitus (T2DM) remains incomplete. Diabetic retinopathy (DR) is a major cause of irreversible visual disability worldwide. By using ophthalmological and molecular-genetic approaches, we gathered specific information to build a data network for deciphering the crosslink of oxidative stress (OS) and apoptosis (AP) processes, as well as to identify potential epigenetic modifications related to noncoding RNAs in the eyes of patients with T2DM. A total of 120 participants were recruited, being classified into two groups: individuals with T2MD (T2MDG, n = 67), divided into a group of individuals with (+DR, n = 49) and without (-DR, n = 18) DR, and a control group (CG, n = 53). Analyses of compiled data reflected significantly higher plasma levels of malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GPx) and significantly lower total antioxidant capacity (TAC) in the +DR patients compared with the -DR and the CG groups. Furthermore, the plasma caspase-3 (CAS3), highly involved in apoptosis (AP), showed significantly higher values in the +DR group than in the -DR patients. The microRNAs (miR) hsa-miR 10a-5p and hsa-miR 15b-5p, as well as the genes BCL2L2 and TP53 involved in these pathways, were identified in relation to DR clinical changes. Our data suggest an interaction between OS and the above players in DR pathogenesis. Furthermore, potential miRNA-regulated target genes were identified in relation to DR. In this concern, we may raise new diagnostic and therapeutic challenges that hold the potential to significantly improve managing the diabetic eye.

Identification of blood metabolic biomarkers associated with diabetic distal symmetric sensorimotor polyneuropathy in patients with type 2 diabetes mellitus

BACKGROUND

Distal symmetric sensorimotor polyneuropathy (DSPN) is a common neurologic complication of type 2 diabetes mellitus (T2DM), but the underlying mechanisms and changes in serum metabolites remain largely undefined. This study aimed to characterize the plasma metabolite profiles of participants with T2DM using targeted metabolomics analysis and identify potential biomarkers for DSPN.

METHODS

A combined liquid chromatography MS/MS and direct flow injection were used to quantify plasma metabolite obtained from 63 participants with T2DM, 81 with DSPN, and 33 nondiabetic control participants. A total of 130 metabolites, including amino acids, biogenic amines, sphingomyelins (SM), phosphatidylcholines, carnitines, and hexose, were analyzed.

RESULTS

A total of 16 plasma metabolites and 3 cholesterol-related laboratory parameters were found to have variable importance in the projection score >1.0 and false discovery rate <5.0% between control, T2DM, and DSPN. Among these variables, five serum metabolites, including phenylalanine (AUC = 0.653), alanine (AUC = 0.630), lysine (AUC = 0.622) tryptophan (AUC = 0.620), and SM C16:0 (AUC = 0.630), are potential biomarkers (all p < .05) in distinguishing T2DM with DSPN from those without (AUC = 0.720).

CONCLUSIONS

In this cross-sectional study, derangement of several metabolites in the plasma was observed in T2DM with and without DSPN, and these metabolites may be potential biomarkers for predicting DSPN. Longitudinal studies are warranted.

Advantages of omics approaches for elucidating metabolic changes in diabetic peripheral neuropathy

Various animal and cell culture models of diabetes mellitus (DM) have been established and utilized to study diabetic peripheral neuropathy (DPN). The divergence of metabolic abnormalities among these models makes their etiology complicated despite some similarities regarding the pathological and neurological features of DPN. Thus, this study aimed to review the omics approaches toward DPN, especially on the metabolic states in diabetic rats and mice induced by chemicals (streptozotocin and alloxan) as type 1 DM models and by genetic mutations (MKR, db/db and ob/ob) and high-fat diet as type 2 DM models. Omics approaches revealed that the pathways associated with lipid metabolism and inflammation in dorsal root ganglia and sciatic nerves were enriched and controlled in the levels of gene expression among these animal models. Additionally, these pathways were conserved in human DPN, indicating the pivotal pathogeneses of DPN. Omics approaches are beneficial tools to better understand the association of metabolic changes with morphological and functional abnormalities in DPN.

RIPK1 and RIPK3 inhibitors: potential weapons against inflammation to treat diabetic complications

Diabetes mellitus is a metabolic disease that is characterized by chronic hyperglycemia due to a variety of etiological factors. Long-term metabolic stress induces harmful inflammation leading to chronic complications, mainly diabetic ophthalmopathy, diabetic cardiovascular complications and diabetic nephropathy. With diabetes complications being one of the leading causes of disability and death, the use of anti-inflammatories in combination therapy for diabetes is increasing. There has been increasing interest in targeting significant regulators of the inflammatory pathway, notably receptor-interacting serine/threonine-kinase-1 (RIPK1) and receptor-interacting serine/threonine-kinase-3 (RIPK3), as drug targets for managing inflammation in treating diabetes complications. In this review, we aim to provide an up-to-date summary of current research on the mechanism of action and drug development of RIPK1 and RIPK3, which are pivotal in chronic inflammation and immunity, in relation to diabetic complications which may be benefit for explicating the potential of selective RIPK1 and RIPK3 inhibitors as anti-inflammatory therapeutic agents for diabetic complications.

Potential Benefits of Antioxidant Phytochemicals in Type 2 Diabetes

The clinical relationship between diabetes and inflammation is well established. Evidence clearly indicates that disrupting oxidant-antioxidant equilibrium and elevated lipid peroxidation could be a potential mechanism for chronic kidney disease associated with type 2 diabetes mellitus (T2DM). Under diabetic conditions, hyperglycemia, especially inflammation, and increased reactive oxygen species generation are bidirectionally associated. Inflammation, oxidative stress, and tissue damage are believed to play a role in the development of diabetes. Although the exact mechanism underlying oxidative stress and its impact on diabetes progression remains uncertain, the hyperglycemia-inflammation-oxidative stress interaction clearly plays a significant role in the onset and progression of vascular disease, kidney disease, hepatic injury, and pancreas damage and, therefore, holds promise as a therapeutic target. Evidence strongly indicates that the use of multiple antidiabetic medications fails to achieve the normal range for glycated hemoglobin targets, signifying treatment-resistant diabetes. Antioxidants with polyphenols are considered useful as adjuvant therapy for their potential anti-inflammatory effect and antioxidant activity. We aimed to analyze the current major points reported in preclinical, in vivo, and clinical studies of antioxidants in the prevention or treatment of inflammation in T2DM. Then, we will share our speculative vision for future diabetes clinical trials.

Diabetic Retinopathy: A Pharmacological Consideration

Diabetes mellitus (DM) has become a worldwide problem, endangering the well-being of people. This issue is further aggravated by the increased fatty content in the diet of most of the Indian population. It is a preeminent source of the genesis of morbidity in the citizens of any given continent, including both new-world countries and old ones too. A major stumbling block that diabetes creates in the healthy living of any of its sufferers is a complication called diabetic retinopathy (DR), which, in its most elementary and perspicuous form, refers to damage to the blood vessels in the retina of the human eye that occurs as a result of high serum glucose levels. DR can have many symptoms, including obscure and blurred vision, trouble observing and distinguishing various colors, and eye floaters. One of the most significant reasons for the manifestation of new cases of complete blindness may be attributed to DR. The appearance of lesions in the body's small blood vessels forms the basis of retinopathic detection. The currently accepted approach for the prevention and cure of this ailment targets deterring the microvascular complexities through medicinal agents that are placed directly into the vitreous space, photocoagulation through laser medium (visual perceptivity is balanced), and some other surgeries related to the vitreous chamber. Anti-vascular endothelial growth factor (anti-VEGF) therapy provided to the patient by intravitreal route is, at present, the most crucial process for curing the sufferer of the given illness, as it can result in optical advancement with decreased unfavorable effects.

Metabolomic Investigation of Blood and Urinary Amino Acids and Derivatives in Patients with Type 2 Diabetes Mellitus and Early Diabetic Kidney Disease

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease; however, few biomarkers of its early identification are available. The aim of the study was to assess new biomarkers in the early stages of DKD in type 2 diabetes mellitus (DM) patients. This cross-sectional pilot study performed an integrated metabolomic profiling of blood and urine in 90 patients with type 2 DM, classified into three subgroups according to albuminuria stage from P1 to P3 (30 normo-, 30 micro-, and 30 macroalbuminuric) and 20 healthy controls using high-performance liquid chromatography and mass spectrometry (UPLC-QTOF-ESI* MS). From a large cohort of separated and identified molecules, 33 and 39 amino acids and derivatives from serum and urine, respectively, were selected for statistical analysis using Metaboanalyst 5.0. online software. The multivariate and univariate algorithms confirmed the relevance of some amino acids and derivatives as biomarkers that are responsible for the discrimination between healthy controls and DKD patients. Serum molecules such as tiglylglycine, methoxytryptophan, serotonin sulfate, 5-hydroxy lysine, taurine, kynurenic acid, and tyrosine were found to be more significant in the discrimination between group C and subgroups P1-P2-P3. In urine, o-phosphothreonine, aspartic acid, 5-hydroxy lysine, uric acid, methoxytryptophan, were among the most relevant metabolites in the discrimination between group C and DKD group, as well between subgroups P1-P2-P3. The identification of these potential biomarkers may indicate their involvement in the early DKD and 2DM progression, reflecting kidney injury at specific sites along the nephron, even in the early stages of DKD.

Amino acid analysis as a method of discovering biomarkers for diagnosis of diabetes and its complications

Diabetes mellitus (DM) is a severe chronic diseases with a global prevalence of 9%, leading to poor health and high health care costs, and is a direct cause of millions of deaths each year. The rising epidemic of diabetes and its complications, such as retinal and peripheral nerve disease, is a huge burden globally. A better understanding of the molecular pathways involved in the development and progression of diabetes and its complications can facilitate individualized prevention and treatment. High diabetes mellitus incidence rate is caused mainly by lack of non-invasive and reliable methods for early diagnosis, such as plasma biomarkers. The incidence of diabetes and its complications in the world still grows so it is crucial to develop a new, faster, high specificity and more sensitive diagnostic technologies. With the advancement of analytical techniques, metabolomics can identify and quantify multiple biomarkers simultaneously in a high-throughput manner, and effective biomarkers can greatly improve the efficiency of diabetes and its complications. By providing information on potential metabolic pathways, metabolomics can further define the mechanisms underlying the progression of diabetes and its complications, help identify potential therapeutic targets, and improve the prevention and management of T2D and its complications. The application of amino acid metabolomics in epidemiological studies has identified new biomarkers of diabetes mellitus (DM) and its complications, such as branched-chain amino acids, phenylalanine and arginine metabolites. This study focused on the analysis of metabolic amino acid profiling as a method for identifying biomarkers for the detection and screening of diabetes and its complications. The results presented are all from recent studies, and in all cases analyzed, there were significant changes in the amino acid profile of patients in the experimental group compared to the control group. This study demonstrates the potential of amino acid profiles as a detection method for diabetes and its complications.

Abelmoschus Manihot ameliorates the levels of circulating metabolites in diabetic nephropathy by modulating gut microbiota in non-obese diabetes mice

Huangkui capsule (HKC), a traditional Chinese medicine, has been used for medication of kidney diseases, including diabetic nephropathy (DN). The current study aimed to evaluate the effects of HKC in the modulation of gut microbiota and the amelioration of metabolite levels by using non-obese diabetes (NOD) mice with DN. The microbiota from three parts of intestines (duodenum, ileum and colon) in NOD mice with and without HKC treatment were analysed using 16S rDNA sequencing techniques. Untargeted metabolomics in plasma of NOD mice were analysed with liquid mass spectrometry. Results showed that HKC administration ameliorated DN in NOD mice and the flora in duodenum were more sensitive to HKC intervention, while the flora in colon had more effects on metabolism. The bacterial genera such as Faecalitalea and Muribaculum significantly increased and negatively correlated with most of the altered metabolites after HKC treatment, while Phyllobacterium, Weissella and Akkermansia showed an opposite trend. The plasma metabolites, mainly including amino acids and fatty acids such as methionine sulfoxide, BCAAs and cis-7-Hexadecenoic acid, exhibited a distinct return to normal after HKC treatment. The current study thereby provides experimental evidence suggesting that HKC may modulate gut microbiota and subsequently ameliorate the metabolite levels in DN.

Systematic assessment of streptozotocin-induced diabetic metabolic alterations in rats using metabolomics

PURPOSE

Type 1 diabetes is characterized by elevated blood glucose levels, which negatively impacts multiple organs and tissues throughout the body, and its prevalence is on the rise. Prior reports primarily investigated the serum and urine specimen from diabetic patients. However, only a few studies examined the overall metabolic profile of diabetic animals or patients. The current systemic investigation will benefit the knowledge of STZ-based type 1 diabetes pathogenesis.

METHODS

Male SD rats were arbitrarily separated into control and streptozotocin (STZ)-treated diabetic rats (n = 7). The experimental rats received 50mg/kg STZ intraperitoneal injection daily for 2 consecutive days. Following 6 weeks, metabolites were assessed via gas chromatography-mass spectrometry (GC-MS), and multivariate analysis was employed to screen for differentially expressed (DE) metabolites between the induced diabetic and normal rats.

RESULTS

We identified 18, 30, 6, 24, 34, 27, 27 and 12 DE metabolites in the serum, heart, liver, kidney, cortex, renal lipid, hippocampus, and brown fat tissues of STZ-treated diabetic rats, compared to control rats. Based on our analysis, the largest differences were observed in the amino acids (AAs), B-group vitamin, and purine profiles. Using the metabolic pathway analysis, we screened 13 metabolic pathways related to the STZ-exposed diabetes pathogenesis. These pathways were primarily AA metabolism, followed by organic acids, sugars, and lipid metabolism.

CONCLUSION

Based on our GC-MS analysis, we identified potential metabolic alterations within the STZ-exposed diabetic rats, which may aid in the understanding of diabetes pathogenesis.

Label-free Aptasensor for the Ultrasensitive Detection of Insulin Via a Synergistic Fluorescent Turn-on Strategy Based on G-quadruplex and AIEgens

Insulin, the only hormone regulating blood glucose level, is strongly associated with diabetes and its complications. Specific recognition and ultrasensitive detection of insulin are of clinical significance for the early diagnosis and treatment of diabetes. Inspired by aggregation-induced emission, we presented a turn-on label-free fluorescence aptasensor for insulin detection. Quaternized tetraphenylethene salt was synthesized as the fluorescence probe. Guanine-rich aptamer IGA3 was selected as recognition element. Graphene oxide was chosen as the quencher. Under optimized conditions, the fluorescence aptasensor displayed a wide linear range (1.0 pM-1.0 μM) with a low limit of detection (0.42 pM). Furthermore, the aptasensor was successfully applied to detect insulin in human serum. Spiked recoveries were obtained in the range of 96.06%-104.26%. All these results demonstrated that the proposed approach has potential application in the clinical diagnostics of diabetes.

Metabolomic Signature of Diabetic Kidney Disease in Cerebrospinal Fluid and Plasma of Patients with Type 2 Diabetes Using Liquid Chromatography-Mass Spectrometry

Diabetic kidney disease (DKD) is the major cause of end stage renal disease in patients with type 2 diabetes mellitus (T2DM). The subtle metabolic changes in plasma and cerebrospinal fluid (CSF) might precede the development of DKD by years. In this longitudinal study, CSF and plasma samples were collected from 28 patients with T2DM and 25 controls, during spinal anesthesia for elective surgery in 2017. These samples were analyzed using liquid chromatography-mass spectrometry (LC-MS) in 2017, and the results were correlated with current DKD in 2017, and the development of new-onset DKD, in 2021. Comparing patients with T2DM having new-onset DKD with those without DKD, revealed significantly increased CSF tryptophan and plasma uric acid levels, whereas phosphatidylcholine 36:4 was lower. The altered metabolites in the current DKD cases were uric acid and paraxanthine in the CSF and uric acid, L-acetylcarnitine, bilirubin, and phosphatidylethanolamine 38:4 in the plasma. These metabolic alterations suggest the defective mitochondrial fatty acid oxidation and purine and phospholipid metabolism in patients with DKD. A correlation analysis found CSF uric acid had an independent positive association with the urine albumin-to-creatinine ratio. In conclusion, these identified CSF and plasma biomarkers of DKD in diabetic patients, might be valuable for monitoring the DKD progression.

GC × GC-TOFMS metabolomics analysis identifies elevated levels of plasma sugars and sugar alcohols in diabetic mellitus patients with kidney failure

Two dimensional GC (GC × GC)-time-of-flight mass spectrometry (TOFMS) has been used to improve accurate metabolite identification in the chemical industry, but this method has not been applied as readily in biomedical research. Here, we evaluated and validated the performance of high resolution GC × GC-TOFMS against that of GC-TOFMS for metabolomics analysis of two different plasma matrices, from healthy controls (CON) and diabetes mellitus (DM) patients with kidney failure (DM with KF). We found GC × GC-TOFMS outperformed traditional GC-TOFMS in terms of separation performance and metabolite coverage. Several metabolites from both the CON and DM with KF matrices, such as carbohydrates and carbohydrate-conjugate metabolites, were exclusively detected using GC × GC-TOFMS. Additionally, we applied this method to characterize significant metabolites in the DM with KF group, with focused analysis of four metabolite groups: sugars, sugar alcohols, amino acids, and free fatty acids. Our plasma metabolomics results revealed 35 significant metabolites (12 unique and 23 concentration-dependent metabolites) in the DM with KF group, as compared with those in the CON and DM groups (N = 20 for each group). Interestingly, we determined 17 of the 35 (14/17 verified with reference standards) significant metabolites identified from both the analyses were metabolites from the sugar and sugar alcohol groups, with significantly higher concentrations in the DM with KF group than in the CON and DM groups. Enrichment analysis of these 14 metabolites also revealed that alterations in galactose metabolism and the polyol pathway are related to DM with KF. Overall, our application of GC × GC-TOFMS identified key metabolites in complex plasma matrices.

Review of potential biomarkers of inflammation and kidney injury in diabetic kidney disease

Diabetic kidney disease is expected to increase rapidly over the coming decades with rising prevalence of diabetes worldwide. Current measures of kidney function based on albuminuria and estimated glomerular filtration rate do not accurately stratify and predict individuals at risk of declining kidney function in diabetes. As a result, recent attention has turned towards identifying and assessing the utility of biomarkers in diabetic kidney disease. This review explores the current literature on biomarkers of inflammation and kidney injury focussing on studies of single or multiple biomarkers between January 2014 and February 2020. Multiple serum and urine biomarkers of inflammation and kidney injury have demonstrated significant association with the development and progression of diabetic kidney disease. Of the inflammatory biomarkers, tumour necrosis factor receptor-1 and -2 were frequently studied and appear to hold most promise as markers of diabetic kidney disease. With regards to kidney injury biomarkers, studies have largely targeted markers of tubular injury of which kidney injury molecule-1, beta-2-microglobulin and neutrophil gelatinase-associated lipocalin emerged as potential candidates. Finally, the use of a small panel of selective biomarkers appears to perform just as well as a panel of multiple biomarkers for predicting kidney function decline.

Preliminary serum and fecal metabolomics study of spontaneously diabetic cynomolgus monkeys based on LC-MS/MS

BACKGROUND

Using untargeted metabolomics techniques, the goal of the study is to differentially screen serum and feces metabolite profiles of spontaneously diabetic and healthy cynomolgus monkeys, to explore potential serum and fecal biomarkers and analyze affected metabolic pathways.

METHODS

We adopted the diagnostic criteria for T2DM recommended by ADA for humans: FSG ≥7.0 mmol/L (126 mg/dl) and HbA1c ≥ 6.5%. The serum and feces samples from three diagnosed spontaneously T2DM cynomolgus monkeys and 11 age-matched healthy controls were enrolled in the study. We employed LC-MS/MS-based untargeted metabolomic methods to reveal the differential metabolite profiles of serum and feces samples between the two groups and to analyze the affected metabolic pathways in MetaboAnalyst 5.0 based on KEGG library.

RESULTS

Six and 44 differential metabolites were identified in serum and feces samples, respectively, and the corresponding affected commonly metabolic pathways involved several metabolic ways, such as arginine biosynthesis, pantothenate and CoA biosynthesis, alanine, aspartate and glutamate metabolism, valine, leucine and isoleucine biosynthesis, and histidine metabolism.

CONCLUSION

The differential potential serum and feces biomarkers obtained from the LC-MS/MS based untargeted metabolomic may help to explain the potential pathophysiological mechanisms of T2DM and offer pivotal information for the early diagnosis and treatment of DM.

Integrated Analysis of Crucial Genes and miRNAs Associated with Osteoporotic Fracture of Type 2 Diabetes

Purpose. The aim of this study is to explore pathological mechanisms of bone fragility in type 2 diabetes mellitus (T2DM) patients. Methods. Identifying common genes for T2DM and osteoporosis by taking the intersection is shared by the Comparative Toxicogenomics Database (CTD), DISEASES, and GeneCards databases. The differentially expressed genes (DEGs) and the differentially expressed miRNAs (DEMs) were identified by analyzing the Gene Expression Omnibus (GEO) datasets (GSE35958, GSE43950, and GSE70318). FunRich and miRNet were applied to predict potential upstream transcription factors and downstream target genes of candidate DEMs, respectively. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore potential mechanisms using Metascape. Eventually, a miRNA-gene network was constructed by Cytoscape software. Results. 271 common targets and 35 common DEGs between T2DM and osteoporosis were screened out in the above databases, and a total of ten DEMs were obtained in the GSE70318. SP1 was predicted to potentially regulate most of the DEMs. Enrichment analysis showed the PI3K-Akt signaling pathway and AGE-RAGE signaling pathway in diabetic complications may play an important role in diabetic skeletal fragility. Two genes (NAMPT and IGFBP5) were considered as key genes involving in the development of diabetic osteoporosis. Through the construction of the miRNA-gene network, most of the hub genes were found to be potentially modulated by miR-96-5p and miR-7-5p. Conclusion. The study uncovered several important genes, miRNAs, and pathological mechanisms involved in diabetic skeletal fragility, among which the PI3K-Akt signaling pathway and AGE-RAGE signaling pathway in diabetic complications may play important roles.

Altered Caffeine Metabolism Is Associated With Recurrent Hypoglycemia in Type 2 Diabetes Mellitus: A UPLC-MS-Based Untargeted Metabolomics Study

Background

Recurrent hypoglycemia (RH) is well known to impair awareness of hypoglycemia and increase the risk of severe hypoglycemia; the underlying mechanism requires further understanding. We aimed to investigate the metabolic characteristic profile for RH in type 2 diabetes mellitus (T2DM) patients and explore the potential metabolic mechanism and prevention strategies.

Methods

We screened 553 community-based T2DM patients. T2DM with RH (DH group, n=40) and T2DM without hypoglycemia (DC group, n=40) were assigned in the case-control study, matched by propensity score matching. Non-targeted, global metabolite profiling was conducted using ultra-high performance liquid chromatography-mass spectrometry. Principal component analysis and supervised projections to latent structures-discriminant analysis were constructed to evaluate the potential biomarkers. Metabolites with a fold change of >2.0 or <0.5, a t-test q-value <0.05, and variable importance in projection value of >1 were identified as significantly differential metabolites. MetaboAnalyst was performed to analyze the related metabolic pathways.

Results

We identified 12 significantly distinct metabolites as potential biomarkers of RH, which were enriched in five pathways; the caffeine metabolic pathway was the most dominant related one. Caffeine and its main downstream metabolites (theophylline and paraxanthine, all q <0.05) were significantly lower during RH. The combination of these metabolites can serve as a reliable predictor biomarker for RH (area under the curve = 0.88). Regarding lipid metabolism, triglyceride was upregulated (P=0.003) and the O-Acylcarnitine was downregulated (q < 0.001). Besides, RH was accompanied by lower phenylalanine (q=0.003) and higher cortisone (q=0.005) levels.

Conclusions

RH in T2DM is accompanied by caffeine, lipolysis, phenylalanine, and cortisone metabolism abnormalities. Caffeine might be a reliable candidate biomarker and potential prevention strategy for RH, but further validation studies are needed.

Clinical Trial Registry

Chi CTR 1900026361, 2019-10-3.

A Contemporary Insight of Metabolomics Approach for Type 1 Diabetes: Potential for Novel Diagnostic Targets

High-throughput omics has been widely applied in metabolic disease, type 1 diabetes (T1D) was one of the most typical diseases. Effective prevention and early diagnosis are very important because of infancy and persistent characteristics of T1D. The occurrence and development of T1D is a chronic and continuous process, in which the production of autoantibodies (ie serum transformation) occupies the central position. Metabolomics can evaluate the metabolic characteristics of serum before seroconversion, the changes with age and T1D complications. And the addition of natural drug metabolomics is more conducive to the systematic and comprehensive diagnosis and treatment of T1D. This paper reviewed the metabolic changes and main pathogenesis from pre-diagnosis to treatment in T1D. The metabolic spectrum of significant abnormal energy and glucose-related metabolic pathway, down-regulation of lipid metabolism and up-regulation of some antioxidant pathways has appeared before seroconversion, indicating that the body has been in the dual state of disease progression and disease resistance before T1D onset. Some metabolites (such as methionine) are closely related to age, and the types of autoantibodies produced are age-specific. Some metabolites may jointly predict DN with eGFR, and metabolomics can further contribute to the pathogenesis based on the correlation between DN and DR. Many natural drug components have been proved to act on abnormal metabolic pathways of T1D and have a positive impact on some metabolic levels, which is very important for further finding therapeutic targets and developing new drugs with small side effects. Metabolomics can provide auxiliary value for the diagnosis of T1D and provide a new direction to reveal the pathogenesis of T1D and find new therapeutic targets. The development of T1D metabolomics shows that high-throughput research methods are expected to be introduced into clinical practice.

Evaluation of change in metabolome caused by comprehensive diabetes treatment: A prospective observational study of diabetes inpatients with gas chromatography/mass spectrometry-based non-target metabolomic analysis

AIMS/INTRODUCTION

Diabetes patients develop a variety of metabolic abnormalities in addition to hyperglycemia. However, details regarding change in various metabolites after comprehensive diabetes treatment remain unknown. This study aimed to identify the short-term change in metabolome in inpatients who were subject to comprehensive diabetes treatment, using gas chromatography/mass spectrometry-based non-target metabolomics techniques.

MATERIALS AND METHODS

Participants of the present study were randomly recruited from the patients with type 2 diabetes hospitalized due to problems with glycemic control (n = 31) and volunteers without diabetes (n = 30), both of whom were aged between 20 and 75 years. A metabolomic analysis of fasting plasma samples on the 2nd (pre-treatment) and 16th hospital (post-treatment) day with gas chromatography/mass spectrometry using a multiple reaction monitoring mode was carried out.

RESULTS

A principal component analysis showed that metabolome of fasting plasma was different between individuals with and without diabetes. The metabolome of fasting plasma in diabetes patients after treatment was different from that of pre-treatment, as well as individuals without diabetes. Many amino acids (proline, glycine, serine, threonine, methionine, pyroglutamic acid, glutamine and lysine) were significantly increased by >10% after administering the inpatient diabetes treatment. A hierarchical clustering analysis showed that in the case of patients with markedly decreased monosaccharide levels and increased 1,5-anhydroglucitol, the levels of amino acids increased more significantly.

CONCLUSIONS

After a 2-week comprehensive treatment, the plasma levels of various amino acids increased in conjunction with the reduction in monosaccharide levels in poorly controlled type 2 diabetes patients.

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.

Pathophysiology of Physical Inactivity-Dependent Insulin Resistance: A Theoretical Mechanistic Review Emphasizing Clinical Evidence

The modern lifestyle has a negative impact on health. It is usually accompanied by increased stress levels and lower physical activity, which interferes with body homeostasis. Diabetes mellitus is a relatively common metabolic disorder with increasing prevalence globally, associated with various risk factors, including lower physical activity and a sedentary lifestyle. It has been shown that sedentary behavior increases the risk of insulin resistance, but the intermediate molecular mechanisms are not fully understood. In this mechanistic review, we explore the possible interactions between physical inactivity and insulin resistance to help better understand the pathophysiology of physical inactivity-dependent insulin resistance and finding novel interventions against these deleterious pathways.

Ocular surface complications in diabetes: The interrelationship between insulin and enkephalin

Diabetes is a multi-faceted disorder with increasing prevalence and rising healthcare costs. The burden of diabetes is increased because of associated complications affecting nearly all organs including the eye. The underlying pathophysiology for the onset of these ocular surface disorders is not well known. Enkephalins are endogenous opioids that originate in the brain and have numerous actions in the human body. Opioid growth factor (OGF), chemically termed [Met5]-enkephalin, binds to a novel, nuclear-associated receptor and mediates cellular homeostasis. Serum OGF levels are elevated in diabetic individuals and rodent models of diabetes. Sustained blockade of the OGF receptor (OGFr) with opioid receptor antagonists, such as naltrexone (NTX), reverses many complications of diabetes in the animal model, including delayed cutaneous wound healing, dry eye, altered corneal surface sensitivity, and keratopathy. The increased enkephalin levels observed in diabetes suggest a relationship between endogenous opioid peptides and the pathophysiology of diabetes. It is common for diabetic patients to undergo insulin therapy to restore normal blood glucose levels. However, this restoration does not alter OGF serum levels nor ameliorate ocular surface complications in the animal model of diabetes. Moreover, sex differences in the prevalence of diabetes, response to insulin therapy, and abnormalities in the OGF-OGFr axis have been reported. This review highlights current knowledge on the dysregulation of the OGF-OGFr pathway and possible relationships of insulin and enkephalins to the development of ocular surface defects in diabetes. It proposes that this dysregulation is a fundamental mechanism for the pathobiology of diabetic complications.

Serum metabolic signatures of subclinical atherosclerosis in patients with type 2 diabetes mellitus: a preliminary study

AIMS

Atherosclerotic cardiovascular disease remains the leading cause of death among patients with diabetes. Early identification of subclinical atherosclerosis is essential for the management of diabetic patients. This study aimed to characterize serum metabolic signatures associated with carotid intima-media thickness (C-IMT), a proxy of subclinical atherosclerosis, in patients with type 2 diabetes mellitus (T2DM).

METHODS

After 1:1 matching by sex, age, body mass index, glycated haemoglobin A_1c, and other clinical parameters, a total of 462 T2DM patients were enrolled, consisting of 231 patients with C-IMT of ≥ 1 mm (abnormal C-IMT) and 231 patients with C-IMT of < 1 mm (normal C-IMT). C-IMT was assessed using ultrasonography. The serum metabolic profiling of fasting blood samples was performed using liquid chromatography-tandem triple quadrupole mass spectrometer coupled with the multivariate and univariate statistical analysis.

RESULTS

Patients with abnormal C-IMT had significantly higher deoxycholic acid (DCA) and taurodeoxycholic acid (TDCA) levels, and lower levels of taurocholic acid (TCA) than those with normal C-IMT. Conditional logistic regression analysis revealed that per 1-standard deviation increase of DCA, TDCA and TCA were significantly associated with 64.7% (95% CI: 1.234-2.196) and 38.5% (95% CI: 1.124-1.706) higher, and 26.8% (95% CI: 0.597-0.897) lower risk of abnormal C-IMT, after adjustment of confounders. The addition of DCA, TCA, or DCA × TDCA/TCA ratio significantly improved the discrimination of abnormal C-IMT over traditional risk factors.

CONCLUSIONS

Serum bile acids may be potential biomarkers for subclinical atherosclerosis in T2DM patients, which needs further confirmation.

Importance of Identifying Novel Biomarkers of Microvascular Damage in Type 1 Diabetes

Microvascular complications of type 1 diabetes, which primarily include diabetic kidney disease, retinopathy, and neuropathy, are characterized by damage to the microvasculature of the kidney, retina, and neurons. The pathogenesis of these complications is multifactorial, and several pathways are implicated. These complications are often silent during their early stages, and once symptoms develop, there might be little to be done to cure them. Thus, there is a strong need for novel biomarkers to identify individuals at risk of microvascular complications at an early stage and guide the implementation of new therapeutic options for preventing their development and progression. Recent advancements in proteomics, metabolomics, and other 'omics' have led to the identification of several potential biomarkers of microvascular complications. However, biomarker discovery has met several challenges and, up to now, there are no new biomarkers that have been implemented into clinical practice. This highlights the need for further work in this area to move towards better diagnostic and prognostic approaches.

Update in the epidemiology, risk factors, screening, and treatment of diabetic retinopathy

Despite progress in the treatment of diabetic macular edema and diabetic retinopathy, the rate of lower fundus examination due to limitations of medical resources delays the diagnosis and treatment of diabetic retinopathy. Therefore, implementation of automated diabetic retinopathy screening program and the identification of more specific and sensitive biomarkers are important for facilitating the earlier detection of diabetic macular edema and diabetic retinopathy to decrease the prevalence of poor vision and blindness.

Decreased amino acids in the brain might contribute to the progression of diabetic neuropathic pain

AIMS

The pathophysiological alteration of diabetic neuropathic pain (DNP) in brain is unclear. Here we aimed to explore the metabolomic characteristics of brain in rats over the progression of DNP through metabolomic analysis.

METHODS

Adult rats were randomly divided into control group and DNP group. Body weight, blood glucose and behavioral assessment of neuropathic pain were measured every week after streptozotocin (STZ) injection. Finally, the brains of 2 rats from control group and 6 rats from DNP group were removed every 4 weeks after STZ injection for metabolomics analysis.

RESULTS

After 4 weeks of STZ-injection, the rats with diabetes developed DNP, which was characterized as mechanical allodynia and thermal nociception. As for metabolomic analysis, differentially expressed metabolites (DE metabolites) showed a dynamic alteration over the development of DNP and affected several KEGG pathways associated with amino acid metabolism. Furthermore, the expression of l-Threonine, l-Methionine, d-Proline, l-Lysine and N-Acetyl-l-alanine were significantly decreased at all time points of DNP group. The amino acids which were precursor of analgesic neurotransmitters were downregulated over the progression of DNP, including l-tryptophan, l-histidine and l-tyrosine.

CONCLUSIONS

The impairment of amino acid metabolism in brain might contribute to the progression of DNP through decreasing analgesic neurotransmitters.

Serum Bile Acid Profiles Improve Clinical Prediction of Nonalcoholic Fatty Liver in T2DM patients

Background: The present study aimed to assess the ability of serum bile acid profiles to predict the development of nonalcoholic fatty liver (NAFL) in type 2 diabetes mellitus (T2DM) patients. Methods: Using targeted ultraperformance liquid chromatography (UPLC) coupled with triple quadrupole mass spectrometry (TQ/MS), we compared serum bile acid levels in T2DM patients with NAFL (n = 30) and age- and sex-matched T2DM patients without NAFL (n = 36) at the first time. Second, an independent cohort study of T2DM patients with NAFL (n = 17) and age- and sex-matched T2DM patients without NAFL (n = 20) was used to validate the results. The incremental benefits of serum biomarkers, clinical variables alone, or with biomarkers were then evaluated using receiver operating characteristic (ROC) curves and decision curve analysis. The area under the curve (AUC), integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were used to evaluate the biomarker predictive abilities. Results: The serum bile acid profiles in T2DM patients with NAFL were significantly different from T2DM patients without NAFL, as characterized by the significant elevation of LCA, TLCA, TUDCA, CDCA-24G, and TCDCA, which may be potential biomarkers for the identification of NAFL in T2DM patients. Based on the improvement in AUC, IDI, and NRI, the addition of 5 bile acids to a model with clinical variables statistically improved its predictive value. Similar results were found in the validation cohort. Conclusions: These results highlight that the detected biomarkers may contribute to the progression of NAFL in T2DM patients, and these biomarkers particularly in combination may help in the diagnosis of NAFL and allow earlier intervention in T2DM patients.

Metabolomic profiling to reveal the therapeutic potency of Posidonia oceanica nanoparticles in diabetic rats

Posidonia oceanica is a sea grass belonging to the family Posidoniaceae, which stands out as a substantial reservoir of bioactive compounds. In this study, the secondary metabolites of the P. oceanica rhizome were annotated using UPLC-HRESI-MS/MS, revealing 86 compounds including simple phenolic acids, flavonoids, and their sulphated conjugates. Moreover, the P. oceanica butanol extract exhibited substantial antioxidant and antidiabetic effects in vitro. Thus, a reliable, robust drug delivery system was developed through the encapsulation of P. oceanica extract in gelatin nanoparticles to protect active constituents, control their release and enhance their therapeutic activity. To confirm these achievements, untargeted GC-MS metabolomics analysis together with biochemical evaluation was employed to investigate the in vivo anti-diabetic potential of the P. oceanica nano-extract. The results of this study demonstrated that the P. oceanica gelatin nanoparticle formulation reduced the serum fasting blood glucose level significantly (p < 0.05) in addition to improving the insulin level, together with the elevation of glucose transporter 4 levels. Besides, multivariate/univariate analyses of the GC-MS metabolomic dataset revealed several dysregulated metabolites in diabetic rats, which were restored to normalized levels after treatment with the P. oceanica gelatin nanoparticle formulation. These metabolites mainly originate from the metabolism of amino acids, fatty acids and carbohydrates, indicating that this type of delivery was more effective than the plain extract in regulating these altered metabolic processes. Overall, this study provides novel insight for the potential of P. oceanica butanol extract encapsulated in gelatin nanoparticles as a promising and effective antidiabetic therapy.

The potential of P. oceanica butanol extract encapsulated in gelatin nanoparticles as a promising and effective antidiabetic therapy has been investigated via metabolomics.

The Role of Mesenchymal Stromal Cells-Derived Small Extracellular Vesicles in Diabetes and Its Chronic Complications

Mesenchymal stromal cells (MSCs) are applied in regenerative medicine of several tissues and organs nowadays by virtue of their self-renewal capabilities, multiple differentiation capacity, potent immunomodulatory properties, and their ability to be favourably cultured and manipulated. With the continuous development of "cell-free therapy" research, MSC-derived small extracellular vesicles (MSC-sEVs) have increasingly become a research hotspot in the treatment of various diseases. Small extracellular vesicles (SEVs) are membrane vesicles with diameters of 30 to 150 nm that mediate signal transduction between adjacent or distal cells or organs by delivering non-coding RNA, protein, and DNA. The contents and effects of sEVs vary depending on the properties of the originating cell. In recent years, MSC-sEVs have been found to play an important role in the occurrence and development of diabetes mellitus as a new way of communication between cells. Diabetes mellitus is a common metabolic disease in clinic. Its complications of the heart, brain, kidney, eyes, and peripheral nerves are a serious threat to human health and has been a hot issue for clinicians. MSC-sEVs could be applied to repair or prevent damage from the complications of diabetes mellitus through anti-inflammatory effects, reduction of endoplasmic reticulum-related protein stress, polarization of M2 macrophages, and increasing autophagy. Therefore, we highly recommend that MSC-sEVs-based therapies to treat diabetes mellitus and its chronic complication be further explored. The analysis of the role and molecular mechanisms of MSC-sEVs in diabetes and its related complications will provide new idea and insights for the prevention and treatment of diabetes.

The Potential Roles of Artemisinin and Its Derivatives in the Treatment of Type 2 Diabetes Mellitus

Type 2 diabetes mellitus (T2DM) is a chronic disease that has become a global public health problem. Studies on T2DM prevention and treatment mostly focus on discovering therapeutic drugs. Artemisinin and its derivatives were originally used as antimalarial treatments. In recent years, the roles of artemisinins in T2DM have attracted much attention. Artemisinin treatments not only attenuate insulin resistance and restore islet ß-cell function in T2DM but also have potential therapeutic effects on diabetic complications, including diabetic kidney disease, cognitive impairment, diabetic retinopathy, and diabetic cardiovascular disease. Many in vitro and in vivo experiments have confirmed the therapeutic utility of artemisinin and its derivatives on T2DM, but no article has systematically demonstrated the specific role artemisinin plays in the treatment of T2DM. This review summarizes the potential therapeutic effects and mechanism of artemisinin and its derivatives in T2DM and associated complications, providing a reference for subsequent related research.

Clinical and Molecular-Genetic Insights into the Role of Oxidative Stress in Diabetic Retinopathy: Antioxidant Strategies and Future Avenues

Reactive oxygen species (ROS) overproduction and ROS-signaling pathways activation attack the eyes. We evaluated the oxidative stress (OS) and the effects of a daily, core nutritional supplement regimen containing antioxidants and omega 3 fatty acids (A/ω3) in type 2 diabetics (T2DM). A case-control study was carried out in 480 participants [287 T2DM patients with (+)/without (-) diabetic retinopathy (DR) and 193 healthy controls (CG)], randomly assigned to a daily pill of A/ω3. Periodic evaluation through 38 months allowed to outline patient characteristics, DR features, and classic/OS blood parameters. Statistics were performed by the SPSS 24.0 program. Diabetics displayed significantly higher circulating pro-oxidants (p = 0.001) and lower antioxidants (p = 0.0001) than the controls. Significantly higher plasma malondialdehyde/thiobarbituric acid reactive substances (MDA/TBARS; p = 0.006) and lower plasma total antioxidant capacity (TAC; p = 0.042) and vitamin C (0.020) was found in T2DM + DR versus T2DM-DR. The differential expression profile of solute carrier family 23 member 2 (SLC23A2) gene was seen in diabetics versus the CG (p = 0.001), and in T2DM + DR versus T2DM - DR (p < 0.05). The A/ω3 regime significantly reduced the pro-oxidants (p < 0.05) and augmented the antioxidants (p < 0.05). This follow-up study supports that a regular A/ω3 supplementation reduces the oxidative load and may serve as a dietary prophylaxis/adjunctive intervention for patients at risk of diabetic blindness.

Multiplatform Metabolomics Reveals Novel Serum Metabolite Biomarkers in Diabetic Retinopathy Subjects

Diabetic retinopathy (DR) is the main cause of vision loss or blindness in working age adults worldwide. The lack of effective diagnostic biomarkers for DR leads to unsatisfactory curative treatments. To define potential metabolite biomarkers for DR diagnosis, a multiplatform-based metabolomics study is performed. In this study, a total of 905 subjects with diabetes without DR (NDR) and with DR at different clinical stages are recruited. Multiplatform metabolomics methods are used to characterize the serum metabolic profiles and to screen and validate the DR biomarkers. Based on the criteria p < 0.05 and false-discovery rate < 0.05, 348 and 290 metabolites are significantly associated with the pathogenesis of DR and early-stage DR, respectively. The biomarker panel consisting of 12-hydroxyeicosatetraenoic acid (12-HETE) and 2-piperidone exhibited better diagnostic performance than hemoglobin A1c (HbA1c) in differentiating DR from diabetes, with AUCs of 0.946 versus 0.691 and 0.928 versus 0.648 in the discovery and validation sets, respectively. In addition, this panel showed higher sensitivity in early-stage DR detection than HbA1c. In conclusion, this multiplatform-based metabolomics study comprehensively revealed the metabolic dysregulation associated with DR onset and progression. The defined biomarker panel can be used for detection of DR and early-stage DR.

Pattern recognition receptor-mediated inflammation in diabetic vascular complications

The innate immune system contains multiple classes of pattern recognition receptors (PRRs), which recognize pathogen-associated molecular patterns (PAMPs) and danger-associated molecular patterns (DAMPs) in the intracellular and extracellular space. Although PRRs are indispensable for the detection and clearance of invading pathogens, dysregulated PRR activation by extrinsic and intrinsic factors leads to inflammatory diseases. PRR-mediated inflammation has been shown to play a pivotal role in the pathogenesis of diabetic vascular complications (DVCs), which are the leading causes of morbidity and mortality in diabetic patients. Upon sensing hyperglycemia-generated DAMPs, PRRs activate intracellular signaling pathways leading to the production of proinflammatory cytokines and chemokines in various cells of the kidney, brain, eye, and heart. The resulting chronic, low-grade inflammation contributes to DVCs. In this review, we summarize the role of PRRs in DVCs including diabetic nephropathy, neuropathy, retinopathy, and cardiomyopathy. We propose that targeting PRRs and associated signaling pathways may be beneficial for the management of DVCs.

PPARα Agonist Oral Therapy in Diabetic Retinopathy

Diabetic retinopathy (DR) is an eye condition that develops after chronically poorly-managed diabetes, and is presently the main cause for blindness on a global scale. Current treatments for DR such as laser photocoagulation, topical injection of corticosteroids, intravitreal injection of anti-vascular endothelial growth factor (VEGF) agents and vitreoretinal surgery are only applicable at the late stages of DR and there are possibilities of significant adverse effects. Moreover, the forms of treatment available for DR are highly invasive to the eyes. Safer and more effective pharmacological treatments are required for DR treatment, in particular at an early stage. In this review, we cover recently investigated promising oral pharmacotherapies, the methods of which are safer, easier to use, patient-friendly and pain-free, in clinical studies. We especially focus on peroxisome proliferator-activator receptor alpha (PPARα) agonists in which experimental evidence suggests PPARα activation may be closely related to the attenuation of vascular damages, including lipid-induced toxicity, inflammation, an excess of free radical generation, endothelial dysfunction and angiogenesis. Furthermore, oral administration of selective peroxisome proliferator-activated receptor alpha modulator (SPPARMα) agonists may induce hepatic fibroblast growth factor 21 expression, indirectly resulting in retinal protection in animal studies. Our review will enable more comprehensive approaches for understanding protective roles of PPARα for the prevention of DR development.

The effects of high-fat diet and metformin on urinary metabolites in diabetes and prediabetes rat models

High-fat diet (HFD) interferes with the dietary plan of patients with type 2 diabetes mellitus (T2DM). However, many diabetes patients consume food with higher fat content for a better taste bud experience. In this study, we examined the effect of HFD on rats at the early onset of diabetes and prediabetes by supplementing their feed with palm olein oil to provide a fat content representing 39% of total calorie intake. Urinary profile generated from liquid chromatography-mass spectrometry analysis was used to construct the orthogonal partial least squares discriminant analysis (OPLS-DA) score plots. The data provide insights into the physiological state of an organism. Healthy rats fed with normal chow (NC) and HFD cannot be distinguished by their urinary metabolite profiles, whereas diabetic and prediabetic rats showed a clear separation in OPLS-DA profile between the two diets, indicating a change in their physiological state. Metformin treatment altered the metabolomics profiles of diabetic rats and lowered their blood sugar levels. For prediabetic rats, metformin treatment on both NC- and HFD-fed rats not only reduced their blood sugar levels to normal but also altered the urinary metabolite profile to be more like healthy rats. The use of metformin is therefore beneficial at the prediabetes stage.

UPLC-MS-based serum metabolomics reveals protective effect of Ganoderma lucidum polysaccharide on ionizing radiation injury

ETHNOPHARMACOLOGICAL RELEVANCE

Ganoderma lucidum Polysaccharide (GLP),traditional Chinese medicine (TCM) active ingredient, has a long history and has good curative effects on radiation injury. However, the mechanism of GLP treating radiation injury has not been clearly elucidated.

THE AIM OF THE STUDY

This study was aimed to investigate the preventive effects of GLP on mice with radiation injury and to explore its mechanisms by serum metabolomics.

MATERIALS AND METHODS

Thirty mice were randomly divided into three groups,and namely 10 per group. The normal control group and the radiation model with normal saline and GLP group with GLP treatment (96 mg·kg-1) for 14 days. 2 h after 7th day after the intragastric administration, the model group and GLP group were subjected to whole body irradiation by X-rays except the normal control group. The peripheral blood WBC, RBC, HGB, PLT indicators.UPLC-Q-TOF-MS technique was used to analyze the serum of normal group, model group and GLP group, and to explore its potential key biomarkers and corresponding related metabolic pathways.

RESULTS

The number of peripheral blood leukocytes (WBC) in the radiation model group was lower than that in the GLP group and the number of platelets (PLT) in the GLP group was significantly higher than that in the model group.Combined with the methods of principal component analysis (PCA), projection to latent structure-discrimination analysis (PLS-DA), three group were clearly distinguished from each other and 18 metabolites were identified as the potential biomarkers in the GLP treated mice. The identified biomarkers indicated that there were perturbations of the taurine and hypotaurine metabolism and glycerophospholipid metabolism.

CONCLUSION

GLP can play a role in radiation protection by improving the expression of related potential biomarkers and related metabolic pathways in serum of radiation-induced mice.

Sex-Specific Metabolic Changes in Peripheral Organs of Diabetic Mice

Diabetes mellitus (DM) can cause systemic metabolic disorders, but the impact of gender on DM-related metabolic changes is rarely reported. Herein, we analyzed metabolic alterations in the heart, liver, and kidney of male and female mice from normal to diabetes via a ¹H NMR-based metabolomics method and aimed to investigate sex-specific metabolic mechanisms underlying the onset and development of diabetes and its complications. Our results demonstrate that male mice had more significant metabolic disorders from normal to diabetes than female mice. Moreover, the kidney was found as the major organ of metabolic disorders during the development of diabetes, followed by the liver and heart. These altered metabolites were mainly implicated in energy metabolism as well as amino acid, choline, and nucleotide metabolism. Therefore, this study suggests that the kidney is the primary organ affected by diabetes in a sex-specific manner, which provides a metabolic view on the pathogenesis of diabetic kidney diseases between genders.

Untargeted Metabolomic Approach Shows No Differences in Subcutaneous Adipose Tissue of Diabetic and Non-Diabetic Subjects Undergoing Bariatric Surgery: An Exploratory Study

BACKGROUND

Obesity plays a major role in the development of insulin resistance (IR) and diabetes (T2DM). Increased adipose tissue (AT) is particularly of interest because it activates a chronic inflammatory response in adipocytes and other tissues. AT plays key endocrine and metabolic functions, acting in the regulation of insulin sensitivity and energy homeostasis. Additionally, it can be easily collected during bariatric surgery. The purpose of this pilot study was to explore the potential differences in AT metabolism, through comparing the untargeted metabolomic profiles of diabetic and non-diabetic obese patients undergoing bariatric surgery.

METHODS

For this exploratory study, samples were collected from 17 subjects. Subcutaneous AT (SAT) samples from obese-diabetic (n = 8) and Obese-non-Diabetic (n = 9) subjects were obtained from the Human Metabolic Tissue Bank. Untargeted metabolomic profiling was performed by Metabolon® Inc. Statistical analysis was performed using the MetaboAnalyst 4.0 platform.

RESULTS

Among the 421 metabolites identified and analyzed there were no significant differences between the Obese-Diabetics and the Obese-non-Diabetics. Small changes were observed by fold change analysis mainly in lipid (n = 12; e.g. NEFAs) and amino acid (n = 8; e.g. BCAAs) metabolic pathways. Dysregulation of these metabolites has been associated with IR and other T2DM-related pathophysiological processes.

CONCLUSION

Obesity may influence SAT metabolism masking T2DM-dependent dysregulation. Better understanding the metabolic differences within SAT in diabetic populations may help identify potential biomarkers for diagnosis and monitoring of T2DM in patients undergoing bariatric surgery.

Plasma Metabolites Associate with All-Cause Mortality in Individuals with Type 2 Diabetes

Alterations in the human metabolome occur years before clinical manifestation of type 2 diabetes (T2DM). By contrast, there is little knowledge of how metabolite alterations in individuals with diabetes relate to risk of diabetes complications and premature mortality. Metabolite profiling was performed using liquid chromatography-mass spectrometry in 743 participants with T2DM from the population-based prospective cohorts The Malmö Diet and Cancer-Cardiovascular Cohort (MDC-CC) and The Malmö Preventive Project (MPP). During follow-up, a total of 175 new-onset cases of cardiovascular disease (CVD) and 298 deaths occurred. Cox regressions were used to relate baseline levels of plasma metabolites to incident CVD and all-cause mortality. A total of 11 metabolites were significantly (false discovery rate (fdr) <0.05) associated with all-cause mortality. Acisoga, acylcarnitine C10:3, dimethylguanidino valerate, homocitrulline, N2,N2-dimethylguanosine, 1-methyladenosine and urobilin were associated with an increased risk, while hippurate, lysine, threonine and tryptophan were associated with a decreased risk. Ten out of 11 metabolites remained significantly associated after adjustments for cardiometabolic risk factors. The associations between metabolite levels and incident CVD were not as strong as for all-cause mortality, although 11 metabolites were nominally significant (p < 0.05). Further examination of the mortality-related metabolites may shed more light on the pathophysiology linking diabetes to premature mortality.

A lipidome-wide association study of the lipoprotein insulin resistance index

Background

The lipoprotein insulin resistance (LPIR) score was shown to predict insulin resistance (IR) and type 2 diabetes (T2D) in healthy adults. However, the molecular basis underlying the LPIR utility for classification remains unclear.

Objective

To identify small molecule lipids associated with variation in the LPIR score, a weighted index of lipoproteins measured by nuclear magnetic resonance, in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study (n = 980).

Methods

Linear mixed effects models were used to test the association between the LPIR score and 413 lipid species and their principal component analysis-derived groups. Significant associations were tested for replication with homeostatic model assessment-IR (HOMA-IR), a phenotype correlated with the LPIR score (r = 0.48, p <  0.001), in the Heredity and Phenotype Intervention (HAPI) Heart Study (n = 590).

Results

In GOLDN, 319 lipids were associated with the LPIR score (false discovery rate-adjusted p-values ranging from 4.59 × 10^− 161 to 49.50 × 10^− 3). Factors 1 (triglycerides and diglycerides/storage lipids) and 3 (mixed lipids) were positively (β = 0.025, p = 4.52 × 10^− 71 and β = 0.021, p = 5.84 × 10^− 41, respectively) and factor 2 (phospholipids/non-storage lipids) was inversely (β = − 0.013, p = 2.28 × 10^− 18) associated with the LPIR score. These findings were replicated for HOMA-IR in the HAPI Heart Study (β = 0.10, p = 1.21 × 10^− 02 for storage, β = − 0.13, p = 3.14 × 10^− 04 for non-storage, and β = 0.19, p = 8.40 × 10^− 07 for mixed lipids).

Conclusions

Non-storage lipidomics species show a significant inverse association with the LPIR metabolic dysfunction score and present a promising focus for future therapeutic and prevention studies.