Role of aromatic amino acids in pathogeneses of diabetic nephropathy in Chinese patients with type 2 diabetes

Integrated multiomic analyses: An approach to improve understanding of diabetic kidney disease

AIM

Diabetes is increasing in prevalence worldwide, with a 20% rise in prevalence predicted between 2021 and 2030, bringing an increased burden of complications, such as diabetic kidney disease (DKD). DKD is a leading cause of end-stage kidney disease, with significant impacts on patients, families and healthcare providers. DKD often goes undetected until later stages, due to asymptomatic disease, non-standard presentation or progression, and sub-optimal screening tools and/or provision. Deeper insights are needed to improve DKD diagnosis, facilitating the identification of higher-risk patients. Improved tools to stratify patients based on disease prognosis would facilitate the optimisation of resources and the individualisation of care. This review aimed to identify how multiomic approaches provide an opportunity to understand the complex underlying biology of DKD.

METHODS

This review explores how multiomic analyses of DKD are improving our understanding of DKD pathology, and aiding in the identification of novel biomarkers to detect disease earlier or predict trajectories.

RESULTS

Effective multiomic data integration allows novel interactions to be uncovered and empathises the need for harmonised studies and the incorporation of additional data types, such as co-morbidity, environmental and demographic data to understand DKD complexity. This will facilitate a better understanding of kidney health inequalities, such as social-, ethnicity- and sex-related differences in DKD risk, onset and progression.

CONCLUSION

Multiomics provides opportunities to uncover how lifetime exposures become molecularly embodied to impact kidney health. Such insights would advance DKD diagnosis and treatment, inform preventative strategies and reduce the global impact of this disease.

The Potential Use of Targeted Proteomics and Metabolomics for the Identification and Monitoring of Diabetic Kidney Disease

Diabetic kidney disease (DKD) is a prevalent microvascular complication of diabetes mellitus and is associated with a significantly worse prognosis compared to diabetic patients without kidney involvement, other microvascular complications, or non-diabetic chronic kidney disease, due to its higher risk of cardiovascular events, faster progression to end-stage kidney disease, and increased mortality. In clinical practice, diagnosis is based on estimated glomerular filtration rate (eGFR) and albuminuria. However, given the limitations of these diagnostic markers, novel biomarkers must be identified. Omics is a new field of study involving the comprehensive analysis of various types of biological data at the molecular level. In different fields, they have shown promising results in (early) detection of diseases, personalized medicine, therapeutic monitoring, and understanding pathogenesis. DKD is primarily utilized in scientific research and has not yet been implemented in routine clinical practice. The aim of this review is to provide an overview of currently available data on targeted omics. After an extensive literature search, 25 different (panels of) omics were withheld and analyzed. Both serum/plasma and urine proteomics and metabolomics have been described with varying degrees of evidence. For all omics, there is still a relative paucity of data from large, prospective, longitudinal cohorts, presumably because of the heterogeneity of DKD and the lack of patient selection in studies, the complexity of omics technologies, and various practical and ethical considerations (e.g., limited accessibility, cost, and privacy concerns).

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.

Deliverables from Metabolomics in Kidney Disease: Adenine, New Insights, and Implication for Clinical Decision-Making

BACKGROUND

Chronic kidney disease (CKD) presents a persistent global health challenge, characterized by complex pathophysiology and diverse progression patterns. Metabolomics has emerged as a valuable tool in unraveling the intricate molecular mechanisms driving CKD progression.

SUMMARY

This comprehensive review provides a summary of recent progress in the field of metabolomics in kidney disease with a focus on spatial metabolomics to shed important insights to enhancing our understanding of CKD progression, emphasizing its transformative potential in early disease detection, refined risk assessment, and the development of targeted interventions to improve patient outcomes.

KEY MESSAGE

Through an extensive analysis of metabolic pathways and small-molecule fluctuations, bulk and spatial metabolomics offers unique insights spanning the entire spectrum of CKD, from early stages to advanced disease states. Recent advances in metabolomics technology have enabled spatial identification of biomarkers to provide breakthrough discoveries in predicting CKD trajectory and enabling personalized risk assessment. Furthermore, metabolomics can help decipher the complex molecular intricacies associated with kidney diseases for exciting novel therapeutic approaches. A recent example is the identification of adenine as a key marker of kidney fibrosis for diabetic kidney disease using both untargeted and targeted bulk and spatial metabolomics. The metabolomics studies were critical to identify a new biomarker for kidney failure and to guide new therapeutics for diabetic kidney disease. Similar approaches are being pursued for acute kidney injury and other kidney diseases to enhance precision medicine decision-making.

Interactive Effects of Empagliflozin and Hyperglycemia on Urinary Amino Acids in Individuals With Type 1 Diabetes

Optimizing energy use in the kidney is critical for normal kidney function. Here, we investigate the effect of hyperglycemia and sodium-glucose cotransporter 2 (SGLT2) inhibition on urinary amino acid excretion in individuals with type 1 diabetes (T1D). The open-label ATIRMA trial assessed the impact of 8 weeks of 25 mg empagliflozin orally once per day in 40 normotensive normoalbuminuric young adults with T1D. A consecutive 2-day assessment of clamped euglycemia and hyperglycemia was evaluated at baseline and posttreatment visits. Principal component analysis was performed on urinary amino acids grouped into representative metabolic pathways using MetaboAnalyst. At baseline, acute hyperglycemia was associated with changes in 25 of the 33 urinary amino acids or their metabolites. The most significant amino acid metabolites affected by acute hyperglycemia were 3-hydroxykynurenine, serotonin, glycyl-histidine, and nicotinic acid. The changes in amino acid metabolites were reflected by the induction of four biosynthetic pathways: aminoacyl-tRNA; valine, leucine, and isoleucine; arginine; and phenylalanine, tyrosine, and tryptophan. In acute hyperglycemia, empagliflozin significantly attenuated the increases in aminoacyl-tRNA biosynthesis and valine, leucine, and isoleucine biosynthesis. Our findings using amino acid metabolomics indicate that hyperglycemia stimulates biosynthetic pathways in T1D. SGLT2 inhibition may attenuate the increase in biosynthetic pathways to optimize kidney energy metabolism.

ARTICLE HIGHLIGHTS

Altered metabolic profiles and targets relevant to the protective effect of acteoside on diabetic nephropathy in db/db mice based on metabolomics and network pharmacology studies

ETHNOPHARMACOLOGICAL RELEVANCE

Diabetic nephropathy (DN) was a major cause of end-stage renal failure and a common microvascular complication in patients with diabetes mellitus (DM). Acteoside (ACT) was the main ingredient extracted from the leaves of Rehmannia glutinosa, which had the functions of entering the lung, moisturizing the skin and relieving itching, nourishing yin and tonifying the kidney, cooling blood, and stopping bleeding. ACT had attracted worldwide interest because of its therapeutic effects on DM and its complications.

AIM OF THE STUDY

To clarify the metabolic profiles and targets of ACT in db/db mice based on metabolomics and network pharmacology studies.

MATERIALS AND METHODS

Db/db mice were used to observe the biochemical indices and histopathological changes in the kidney to evaluate the pharmacological effects of ACT on DN. Untargeted metabolomics studies were performed to investigate by UHPLC-LTQ-Orbitrap MS on urine, serum, and kidney samples. The key targets and pathways were analyzed by network pharmacology. For the pathways enriched by untargeted metabolomics, targeted metabolomics by UHPLC-QQQ-MS/MS was performed in kidney samples for validation. Sensitive biomarkers in kidney samples were evaluated. The effect of ACT on the improvement of DN from the perspective of metabolism of small molecules in vivo was described.

RESULTS

ACT could delay the progression of DN and improve the degree of histopathological damage to the kidney. The pathways were focused on amino acid metabolism by untargeted metabolomics. Through network pharmacology analysis, the effect pathways were related to signal transduction, carbohydrate, lipid, amino acid metabolism and mainly affected the endocrine and immune systems. Amino acid metabolism was disturbed in the kidney of db/db mice, which could be callback by ACT, such as tryptophan, glutamine, cysteine, leucine, threonine, proline, phenylalanine, histidine, serine, arginine, asparagine by targeted metabolomics.

CONCLUSIONS

In conclusion, this study provided strong support for ACT on DN treatment in clinics. Meanwhile, the Rehmannia glutinosa was used fully to raise the income level of farmers economically, while achieving the social benefit of empowering rural revitalization.

Network pharmacology and molecular docking of endogenous active metabolites in diabetic kidney disease

OBJECTIVES

Network pharmacology and molecular docking were used to predict endogenous active metabolites with protective effects in diabetic kidney disease (DKD).

METHODS

We utilized metabolomics to screen differentially expressed metabolites in kidney tissues of mice with type 2 DKD and predicted potential targets using relevant databases. The interaction network between endogenous active metabolites and target proteins was established by integrating differentially expressed metabolites and proteins associated with DKD identified through proteomics. Gene ontology (GO) and signaling pathway enrichment analysis were performed. The biological functions of the active candidate metabolites and their effects on downstream pathways were also verified.

RESULTS

Metabolomics revealed 130 differentially expressed metabolites. Through co-expression network analysis coupled with the investigation of differentially expressed proteins in proteomics, 2-hydroxyphenylpropionylglycine (2-HPG) emerged as a key regulator of DKD. 2-HPG was found to modulate the progression of DKD by regulating the conformation and activity of synaptophysin 1 (SYNJ1), with a correlation coefficient of 0.974. In vivo experiments revealed that SYNJ1 expression was significantly downregulated in the Macroalbuminuria Group compared to the Control Group and negatively correlated with proteinuria (r = -0.7137), indicating its important role in DKD progression. Immunofluorescence demonstrated that treatment with 2-HPG restores the expression of the foot process marker protein Wilms tumor-1 (WT-1) in podocytes injured by high glucose levels. Western blot and polymerase chain reaction support the involvement of SYNJ1 in this process.

CONCLUSIONS

This study demonstrated the significance of the 2-HPG/SYNJ1 signaling axis in safeguarding the foot process of podocytes in DKD.

Application of Metabolomics and Traditional Chinese Medicine for Type 2 Diabetes Mellitus Treatment

Diabetes is a major global public health problem with high incidence and case fatality rates. Traditional Chinese medicine (TCM) is used to help manage Type 2 Diabetes Mellitus (T2DM) and has steadily gained international acceptance. Despite being generally accepted in daily practice, the TCM methods and hypotheses for understanding diseases lack applicability in the current scientific characterization systems. To date, there is no systematic evaluation system for TCM in preventing and treating T2DM. Metabonomics is a powerful tool to predict the level of metabolites in vivo, reveal the potential mechanism, and diagnose the physiological state of patients in time to guide the follow-up intervention of T2DM. Notably, metabolomics is also effective in promoting TCM modernization and advancement in personalized medicine. This review provides updated knowledge on applying metabolomics to TCM syndrome differentiation, diagnosis, biomarker discovery, and treatment of T2DM by TCM. Its application in diabetic complications is discussed. The combination of multi-omics and microbiome to fully elucidate the use of TCM to treat T2DM is further envisioned.

Abnormal tryptophan catabolism in diabetes mellitus and its complications: Opportunities and challenges

In recent years, the incidence rate of diabetes mellitus (DM), including type 1 diabetes mellitus(T1DM), type 2 diabetes mellitus(T2DM), and gestational diabetes mellitus (GDM), has increased year by year and has become a major global health problem. DM can lead to serious complications of macrovascular and microvascular. Tryptophan (Trp) is an essential amino acid for the human body. Trp is metabolized in the body through the indole pathway, kynurenine (Kyn) pathway and serotonin (5-HT) pathway, and is regulated by intestinal microorganisms to varying degrees. These three metabolic pathways have extensive regulatory effects on the immune, endocrine, neural, and energy metabolism systems of the body, and are related to the physiological and pathological processes of various diseases. The key enzymes and metabolites in the Trp metabolic pathway are also deeply involved in the pathogenesis of DM, playing an important role in pancreatic function, insulin resistance (IR), intestinal barrier, and angiogenesis. In DM and its complications, there is a disruption of Trp metabolic balance. Several therapy approaches for DM and complications have been proven to modify tryptophan metabolism. The metabolism of Trp is becoming a new area of focus for DM prevention and care. This paper reviews the impact of the three metabolic pathways of Trp on the pathogenesis of DM and the alterations in Trp metabolism in these diseases, expecting to provide entry points for the treatment of DM and its complications.

Urine metabolomics reveals biomarkers and the underlying pathogenesis of diabetic kidney disease

PURPOSE

Diabetic kidney disease (DKD) is the most common complication of type 2 diabetes mellitus (T2DM), and its pathogenesis is not yet fully understood and lacks noninvasive and effective diagnostic biomarkers. In this study, we performed urine metabolomics to identify biomarkers for DKD and to clarify the potential mechanisms associated with disease progression.

METHODS

We applied a liquid chromatography-mass spectrometry-based metabolomics method combined with bioinformatics analysis to investigate the urine metabolism characteristics of 79 participants, including healthy subjects (n = 20), T2DM patients (n = 20), 39 DKD patients that included 19 DKD with microalbuminuria (DKD + micro) and 20 DKD with macroalbuminuria (DKD + macro).

RESULTS

Seventeen metabolites were identified between T2DM and DKD that were involved in amino acid, purine, nucleotide and primarily bile acid metabolism. Ultimately, a combined model consisting of 2 metabolites (tyramine and phenylalanylproline) was established, which had optimal diagnostic performance (area under the curve (AUC) = 0.94). We also identified 19 metabolites that were co-expressed within the DKD groups and 41 metabolites specifically expressed in the DKD + macro group. Ingenuity pathway analysis revealed three interaction networks of these 60 metabolites, involving the sirtuin signaling pathway and ferroptosis signaling pathway, as well as the downregulation of organic anion transporter 1, which may be important mechanisms that mediate the progression of DKD.

CONCLUSIONS

This work reveals the metabolic alterations in T2DM and DKD, constructs a combined model to distinguish them and delivers a novel strategy for studying the underlying mechanism and treatment of DKD.

Plasma Amino Acids in Early Pregnancy and Midpregnancy and Their Interplay With Phospholipid Fatty Acids in Association With the Risk of Gestational Diabetes Mellitus: Results From a Longitudinal Prospective Cohort

OBJECTIVE

We prospectively evaluated plasma amino acids (AAs) in early pregnancy and midpregnancy and their interplay with phospholipid fatty acids (FAs) in association with gestational diabetes mellitus (GDM) risk.

RESEARCH DESIGN AND METHODS

From a longitudinal pregnancy cohort of 2,802 individuals, concentrations of 24 plasma AAs at 10-14 and 15-26 gestational weeks (GW) were assessed among 107 GDM case subjects and 214 non-GDM control subjects. We estimated adjusted odds ratios (OR) and 95% CI for the associations of plasma AAs and the joint associations of plasma AAs and phospholipid FAs with GDM risk, adjusting for risk factors including age, prepregnancy BMI, and family history of diabetes.

RESULTS

Glycine at 10-14 GW was inversely associated with GDM (adjusted OR [95% CI] per SD increment: 0.55 [0.39-0.79]). Alanine, aspartic acid, and glutamic acid at 10-14 GW were positively associated with GDM (1.43 [1.08-1.88], 1.41 [1.11-1.80], and 1.39 [0.98-1.98]). At 15-26 GW, findings for glycine, alanine, aspartic acid, and the glutamine-to-glutamic acid ratio were consistent with the directions observed at 10-14 GW. Isoleucine, phenylalanine, and tyrosine were positively associated with GDM (1.64 [1.19-2.27], 1.15 [0.87-1.53], and 1.56 [1.16-2.09]). All P values for linear trend were <0.05. Several AAs and phospholipid FAs were significantly and jointly associated with GDM. For instance, the lowest risk was observed among women with higher glycine and lower even-chain saturated FAs at 10-14 GW (adjusted OR [95% CI] 0.15 [0.06, 0.37]).

CONCLUSIONS

Plasma AAs may be implicated in GDM development starting in early pregnancy. Associations of AAs with GDM may be enhanced in the copresence of phospholipid FA profile.

Efficacy of Yishen Huashi Granules Combined with Linagliptin Tablets on Blood Glucose and Renal Function in Patients with Type 2 Diabetic Nephropathy

Objective

To probe into the efficacy of Yishen Huashi granules combined with linagliptin tablets in the treatment of type 2 diabetic nephropathy (DN) and its effect on blood glucose and renal function in patients.

Methods

70 patients with type 2 DN at our hospital between May 2020 and May 2022 were chosen as the research objects and separated into the control group and the research group based on their treatments. With 35 cases in each group, the patients treated with initial therapy and linagliptin tablets were enrolled in the control group, and those who received the above treatments and also Yishen Huashi granules were included in the research group. Their clinical indexes such as blood glucose and renal function were compared with both groups after treatment.

Results

After treatment, the research group had remarkably lower fasting blood glucose (FPG), 2 h-postprandial blood glucose (2 h-PBG), and glycosylated hemoglobin A1c (HbA1c) levels than those in the control group (P < 0.05). After treatment, the research group had remarkably lower levels of total cholesterol (TC), triglyceride (TG), and low-density lipoprotein (LDL) (P < 0.05) and higher high-density lipoprotein (HDL) levels (P < 0.05) than those in the control group. After treatment, the urinary microalbumin (u-mALB) level was remarkably lower in both groups (P < 0.05) and was distinctly lower in the research group than in the control group (P < 0.05). After treatment, the research group had remarkably lower renal function indexes such as serum creatinine (SCr), blood urea nitrogen (BUN), urinary protein (UPro), and urinary albumin excretion rate (UAER) (P < 0.05) and a higher estimated glomerular filtration rate (eGFR) level (P < 0.05) than those in the control group. The efficacy was evaluated by the traditional Chinese medicine (TCM) syndrome score after treatment. There were no patients in complete remission between both the groups, where slight differences were found in the proportion of significant remission (P > 0.05), with the total effective rate of the research group remarkably higher than that of the control group (P < 0.05).

Conclusion

The combination of Yishen Huashi granules and linagliptin tablets can reduce the blood glucose and blood lipid levels in patients with type 2 DN and lower UPro and protect renal function at the same time, which provides a new idea and a method for clinical treatment of type 2 DN with integrated traditional Chinese and Western medicine.

Compound dietary fiber and high-grade protein diet improves glycemic control and ameliorates diabetes and its comorbidities through remodeling the gut microbiota in mice

Dietary intervention with a low glycemic index and full nutritional support is emerging as an effective strategy for diabetes management. Here, we found that the treatment of a novel compound dietary fiber and high-grade protein diet (CFP) improved glycemic control and insulin resistance in streptozotocin-induced diabetic mice, with a similar effect to liraglutide. In addition, CFP treatment ameliorated diabetes-related metabolic syndromes, such as hyperlipidemia, hepatic lipid accumulation and adipogenesis, systemic inflammation, and diabetes-related kidney damage. These results were greatly associated with enhanced gut barrier function and altered gut microbiota composition and function, especially those bacteria, microbial functions, and metabolites related to amino acid metabolism. Importantly, no adverse effect of CFP was found in our study, and CFP exerted a wider arrange of protection against diabetes than liraglutide. Thereby, fortification with balanced dietary fiber and high-grade protein, like CFP, might be an effective strategy for the management and treatment of diabetes.

Combination of mulberry leaf active components possessed synergetic effect on SD rats with diabetic nephropathy by mediating metabolism, Wnt/β-catenin and TGF-β/Smads signaling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Mulberry leaf has attracted much attention due to its excellent curative effect on diabetes and its complications, whether the combination of its effective components have protective and synergistic effect on diabetic nephropathy (DN) in vivo remain unclear.

AIM OF THE STUDY

The aim of this study was to investigate the protective and synergistic effect of the combination (MAF_1:1 and MAF_1:5) of mulberry leaf alkaloids (MA) and flavonoids extract (MF) on DN.

MATERIALS AND METHODS

A step by step method consisted of network pharmacological prediction, animal in vivo validation and metabolic mechanism research was used to construct the multi-component-target-pathway network of mulberry leaf against DN. Firstly, the potential components and mechanism of mulberry leaf against DN was explored by network pharmacology analysis. Secondly, DN animal model was established to validate the anti-DN activity of these potential compounds. Thirdly, the metabolomics of serum and urine samples from animal experiments was analyzed to explore the anti-DN mechanism of these potential compounds.

RESULTS

The results of network pharmacology demonstrated that a total of 7 compounds detected in MA and MF exhibited anti-DN activity, their mechanism were strongly in connection with metabolic pathways, arachidonic acid metabolism, sphingolipid signaling pathway, etc. The results of animal experiment indicated that MAF_1:1 and MAF_1:5 significantly relieved metabolic disorders through regulating Wnt/β-catenin and TGF-β/Smads signaling pathway, just like MF or MA alone. Metabolomics suggested they could regulate 16 serum and 7 urine endogenous metabolites through arachidonic acid metabolism, phenylalanine metabolism and sphingolipid metabolism, thus alleviated DN. Significantly, MAF_1:1 and MAF_1:5 might possess synergistic effect considering their therapeutic effects on DN rats were superior to the single use of MA or MF.

CONCLUSIONS

MAF_1:1 and MAF_1:5 possessed protective and synergistic effect on DN rats through multi-target and multi-pathways. These findings were of great scientific significance and application value to reveal the advantage of mulberry leaf in preventing and treating DN.

Analysis of plasma free amino acids in diabetic rat and the intervention of Ginkgo biloba leaves extract using hydrophilic interaction liquid chromatography coupled with tandem mass-spectrometry

Amino acids (AAs) are important metabolites that are related with diabetes. However, their roles in the initiation and development of diabetes mellitus (DM), especially in the treatment of Ginkgo biloba leaves extract (GBE) have not been fully explored. Thus, we investigated the roles that AAs played in the progression and GBE supplementation of DM rat induced by streptozotocin. The rats were randomly divided into a normal control group treated with drug-free solution, a normal control group treated with GBE, a DM group treated with drug-free solution, and DM group treated with GBE; and maintained on this protocol for 9 weeks. Rat plasma was collected from the sixth week to the ninth week and then analyzed with the optimized hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry method. A total of 17 AAs with differential levels were monitored to indicate dysfunction of AAs metabolism to confirm the occurrence and development of DM. Treatment with GBE partially reversed the changes seen in seven AAs including leucine, isoleucine, tyrosine, glutamic acid, asparagines, lysine and alanine in DM rats, indicating that GBE could prevent the occurrence and development of DM by acting on AAs metabolism. The improvement of those AAs metabolism disorders may play a considerable role in the treatment of GBE on the occurrence and development of DM. Those findings potentially promote the understanding of the pathogenic progression of DM and reveal the therapeutic mechanism of GBE against DM.

Metabolomics as a tool for the early diagnosis and prognosis of diabetic kidney disease

Diabetic kidney disease (DKD) is one of the most prevalent comorbidities of diabetes mellitus and the leading cause of the end-stage renal disease (ESRD). DKD results from chronic exposure to hyperglycemia, leading to progressive alterations in kidney structure and function. The early development of DKD is clinically silent and when albuminuria is detected the lesions are often at advanced stages, leading to rapid kidney function decline towards ESRD. DKD progression can be arrested or substantially delayed if detected and addressed at early stages. A major limitation of current methods is the absence of albuminuria in non-albuminuric phenotypes of diabetic nephropathy, which becomes increasingly prevalent and lacks focused therapy. Metabolomics is an ever-evolving omics technology that enables the study of metabolites, downstream products of every biochemical event that occurs in an organism. Metabolomics disclosures complex metabolic networks and provide knowledge of the very foundation of several physiological or pathophysiological processes, ultimately leading to the identification of diseases' unique metabolic signatures. In this sense, metabolomics is a promising tool not only for the diagnosis but also for the identification of pre-disease states which would confer a rapid and personalized clinical practice. Herein, the use of metabolomics as a tool to identify the DKD metabolic signature of tubule interstitial lesions to diagnose or predict the time-course of DKD will be discussed. In addition, the proficiency and limitations of the currently available high-throughput metabolomic techniques will be discussed.

Alterations in the Gut Microbiota and Their Metabolites in Colorectal Cancer: Recent Progress and Future Prospects

Colorectal cancer (CRC) is a leading cause of cancer morbidity and mortality worldwide. The etiology and pathogenesis of CRC remain unclear. A growing body of evidence suggests dysbiosis of gut bacteria can contribute to the occurrence and development of CRC by generating harmful metabolites and changing host physiological processes. Metabolomics, a systems biology method, will systematically study the changes in metabolites in the physiological processes of the body, eventually playing a significant role in the detection of metabolic biomarkers and improving disease diagnosis and treatment. Metabolomics, in particular, has been highly beneficial in tracking microbially derived metabolites, which has substantially advanced our comprehension of host-microbiota metabolic interactions in CRC. This paper has briefly compiled recent research progress of the alterations of intestinal flora and its metabolites associated with CRC and the application of association analysis of metabolomics and gut microbiome in the diagnosis, prevention, and treatment of CRC; furthermore, we discuss the prospects for the problems and development direction of this association analysis in the study of CRC. Gut microbiota and their metabolites influence the progression and causation of CRC, and the association analysis of metabolomics and gut microbiome will provide novel strategies for the prevention, diagnosis, and therapy of CRC.

Acylcarnitines: Can They Be Biomarkers of Diabetic Nephropathy?

Diabetic nephropathy (DN), one of the most serious microvascular complications of diabetes mellitus (DM), may progress to end-stage renal disease (ESRD). Current biochemical biomarkers, such as urinary albumin excretion rate (UAER), have limitations for early screening and monitoring of DN. Recent studies have identified some metabolites as candidate biomarkers for early detection of DN. In this review, we summarize the role of dysregulated acylcarnitines (AcylCNs) in DN pathophysiology. Lower abundance of short- and medium-chain AcylCNs and higher long-chain AcylCNs often occurred in DM with normal albuminuria and microalbuminuria, compared with advanced stages of DN. The increase of long-chain AcylCNs was supposed to be an adaptive compensation in fat acids (FAs) oxidation in the early stage of DN. Conversely, the decrease of long-chain AcylCNs was due to incomplete oxidation of FAs in advanced stage of DN. Thus, AcylCNs may serve as sensitive biomarkers in predicting the risk of DN.

Association Between Plasma Vitamin D2 and Type 2 Diabetes Mellitus

OBJECTIVE

To investigate the relationship between plasma vitamin D2(VD2) and type 2 diabetes(T2DM).

METHOD

Data from electronic medical records of 797 inpatients treated at Sun Yat Sen Memorial Hospital, Sun Yat-sen University between June 24, 2019 and December 24, 2020 were collected, and a total of 596 patients were enrolled after screening based on inclusion and exclusion criteria. Patients were divided into diabetic and non-diabetic groups according to whether they had T2DM. The Wilcoxon rank sum test was finally selected for the analysis of differences between groups according to the distribution of patients' plasma VD2, and logistic regression models were used to find the corresponding influencing factors.

RESULT

Of the 596 hospitalized patients, 138 (23.15%) were diagnosed with T2DM. The Wilcoxon test showed no statistically significant difference in plasma VD2 concentrations between the T2DM and non-T2DM groups (p=0.833). After adjustment for confounders by multivariate logistic regression, there was still no significant difference in plasma VD2 concentrations between the two groups (P=0.316, OR: 1.15 (0.88,1.49)). The uncorrelated relationship between VD2 and T2DM was not found to change after incorporating 12 indicators, including demographic characteristics, laboratory indicators and complications, into the logistic regression model by 3 steps, even the OR (1.08 (0.92,1.26)) did not change in the 3 models. Similarly, the adjusted ORs agreed that there was no statistical association between VD2 and T2DM.

CONCLUSION

VD2 levels are similar in patients with T2DM compared to those without T2DM. Clinical caution should be exercised in giving VD2 supplementation to patients with T2DM unless other diseases requiring VD2 supplementation (e.g., rickets, osteoporosis) are present.

Amino Acid-Induced Impairment of Insulin Signaling and Involvement of G-Protein Coupling Receptor

Amino acids are needed for general bodily function and well-being. Despite their importance, augmentation in their serum concentration is closely related to metabolic disorder, insulin resistance (IR), or worse, diabetes mellitus. Essential amino acids such as the branched-chain amino acids (BCAAs) have been heavily studied as a plausible biomarker or even a cause of IR. Although there is a long list of benefits, in subjects with abnormal amino acids profiles, some amino acids are correlated with a higher risk of IR. Metabolic dysfunction, upregulation of the mammalian target of the rapamycin (mTOR) pathway, the gut microbiome, 3-hydroxyisobutyrate, inflammation, and the collusion of G-protein coupled receptors (GPCRs) are among the indicators and causes of metabolic disorders generating from amino acids that contribute to IR and the onset of type 2 diabetes mellitus (T2DM). This review summarizes the current understanding of the true involvement of amino acids with IR. Additionally, the involvement of GPCRs in IR will be further discussed in this review.

Amino Acid Signature of Oxidative Stress in Patients with Type 2 Diabetes: Targeted Exploratory Metabolomic Research

Oxidative stress plays a key role in the development of chronic diabetes-related complications. Previous metabolomic studies showed a positive association of diabetes and insulin resistance with branched-chain amino acids (AAs) and aromatic AAs. The purpose of this research is to identify distinct metabolic changes associated with increased oxidative stress, as assessed by nitrotyrosine levels, in type 2 diabetes (T2DM). Serum samples of 80 patients with insulin-treated T2DM are analyzed by AA-targeted metabolomics using ultrahigh-performance liquid chromatography/mass spectrometry. Patients are divided into two groups based on their nitrotyrosine levels: the highest level of oxidative stress (Q4 nitrotyrosine) and lower levels (Q1–Q3 nitrotyrosine). The identification of biomarkers is performed in MetaboAnalyst version 5.0 using a t-test corrected for false discovery rate, unsupervised principal component analysis and supervised partial least-squares discriminant analysis (PLS-DA). Four AAs have significantly different levels between the groups for highest and lower oxidative stress. Cysteine, phenylalanine and tyrosine are substantially increased while citrulline is decreased (p-value <0.05 and variable importance in the projection [VIP] >1). Corresponding pathways that might be disrupted in patients with high oxidative stress are phenylalanine, tyrosine and tryptophan biosynthesis, arginine biosynthesis, phenylalanine metabolism, cysteine and methionine metabolism and tyrosine metabolism.