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

Follicular fluid profiling unveils anti-Müllerian hormone alongside glycolytic and mitochondrial dysfunction as markers of polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder affecting women of reproductive age, yet the molecular mechanisms influencing its pathophysiology remain poorly defined. A comprehensive prospective case-control study was conducted to elucidate the follicular fluid (FF) hormone and metabolite profile in women with PCOS and its implications for oocyte maturation and fertilization. The study involved 40 age- and body mass index (BMI)-matched women undergoing in vitro fertilization (IVF), including 20 diagnosed with PCOS and 20 controls with infertility due to tubal or male factors. A distinctive hormone profile in the FF of women with PCOS was identified, characterized by significantly higher anti-Müllerian hormone (AMH) levels (24.90 ± 17.61 vs. 16.68 ± 17.67 pmol/L, p = 0.0039) and lower progesterone (8253 ± 4748 vs. 25362 ± 10862 ng/mL, p < 0.0001) and estradiol levels (388.23 ± 210.58 vs. 651.48 ± 390.79 ng/mL, p = 0.0208) compared to normoovulatory controls. Moreover, a metabolite fingerprint associated with glycolytic and mitochondrial dysfunction was observed, as evidenced by lower lactate (4575.44 ± 1507.76 vs. 5595.34 ± 1073.32 μmol/L, p = 0.0182) and formate (64.51 ± 16.06 vs. 75.81 ± 16.63 μmol/L, p = 0.0351) levels and higher citrate levels (136.93 ± 52.53 vs. 109.15 ± 24.17 μmol/L, p = 0.0409) in the FF of women with PCOS. These findings suggest that the molecular profile of the FF in women with PCOS might be related to granulosa cell glycolytic and mitochondrial dysfunction, which can have a negative impact on oocyte fertilization potential. The study provides an integrative analysis of the FF hormone and metabolite profile in women with PCOS, offering insights into the molecular mechanisms underlying the reproductive dysfunctions associated with this condition.

Shenzhuo formulation ameliorates diabetic nephropathy by regulating cytochrome P450-mediated arachidonic acid metabolism

BACKGROUND

Diabetic nephropathy (DN) is a major complication of diabetes, marked by progressive renal damage and an inflammatory response. Although research has investigated the pathological mechanisms underlying DN, effective treatment options remain limited.

AIM

To evaluate the therapeutic impact of Shenzhuo formulation (SZF) on a DN mouse model and to examine its potential molecular mechanisms using transcriptomic and metabolomic approaches.

METHODS

We established a DN mouse model through a high-fat diet combined with streptozotocin (STZ) injection, followed by SZF treatment. We analyzed SZF’s effects on gene expression and metabolite profiles in renal tissues of DN mice using transcriptomics and metabolomics techniques. Additionally, based on transcriptomic and non-targeted metabolomic findings, we further assessed SZF’s influence on the expression of factors related to the cytochrome P450 (CYP450)-mediated arachidonic acid (AA) metabolism pathway, as well as its effects on inflammation and oxidative stress.

RESULTS

SZF intervention significantly decreased hyperglycemia and mitigated renal function impairment in DN mice. Pathological analysis revealed that SZF treatment improved renal tissue damage, reduced fibrosis, and diminished glycogen deposition. Transcriptomic analysis indicated that SZF influenced mRNA expression of CYP450-related genes, including Cyp2j13, Cyp2b9, Pla2 g2e/Cyp4a12a, Cyp4a32, Cyp2e1, and Cyp4a14. Non-targeted metabolomic results demonstrated that SZF altered the levels of metabolites associated with the AA metabolic pathway, including 5,6-EET, 14,15-EET, phosphatidylcholine, and 20-HETE. Further experiments showed that SZF upregulated the expression of CYP4A and CYP2E proteins in renal tissue, as well as CYP2J and CYP2B proteins. Additionally, SZF significantly reduced the expression of inflammatory factors in renal tissue, enhanced antioxidant enzyme activity, and alleviated oxidative stress.

CONCLUSION

SZF exerts anti-inflammatory and antioxidant effects by regulating CYP450-mediated AA metabolism, leading to improved renal function and improved pathological state in DN mice.

Metabolomics Based Exploration of the Mechanism of Action of Tripterygium Glycosides in Diabetic Kidney Disease

Tripterygium glycosides (TGs), the primary active components of Tripterygium wilfordii, have demonstrated therapeutic efficacy in treating diabetic kidney disease (DKD). However, the precise mechanisms underlying their action remain elusive, limiting the full realization of their medicinal potential. This study employed serum metabolomics based on liquid chromatography-mass spectrometry (LC-MS) analysis to elucidate the mechanisms by which TGs combat DKD. We evaluated the protective effects of TGs on DKD following treatment. Serum samples were collected before and after treatment, and their metabolic profiles were analyzed using LC-MS. Our metabolomics analysis revealed that TGs significantly modulated the hedgehog signaling pathway, a key metabolic pathway implicated in DKD pathogenesis. This study represents the first comprehensive investigation of the metabolic pathways regulated by TGs in the context of DKD using a metabolomics approach. Our findings provide a robust theoretical foundation for the more effective utilization and potential combination therapies involving TGs in the management of DKD. These insights pave the way for further research and development of targeted therapeutic strategies for this challenging condition.

Kidney function-related protection of polysaccharides from red kidney bean and small black soybean via urine metabolomics in type 2 diabetic rats

Diabetic nephropathy is a significant microvascular complication of diabetes mellitus. Crude polysaccharides extracted from red kidney beans and small black soybeans (RK, SB) have demonstrated promising antidiabetic effects in type 2 diabetic rats. This study evaluated the protective effects of RK and SB on kidney function in diabetic rats by examining kidney markers and urine metabolism. It also investigated the impact of pure polysaccharides (RKP, SBP) to pinpoint the active component of RK and SB. Findings indicated that RK and SB influenced kidney function by affecting the kidney index and key urine metabolites, like citric acid and cis-aconitic acid, linked to the TCA cycle and phenylalanine metabolism. Furthermore, a higher dose (400 mg/kg) of RKP and SBP was more effective in treating kidney damage in diabetic models than the optimal 200 mg/kg dose of RK and SB. This was shown by better regulation of urea nitrogen and uric acid levels, improved kidney tissue health seen in HE staining, and fewer red-stained lipid droplets in the kidney, as indicated by Oil Red O staining. Overall, this study provided additional evidence to support RKP and SBP as a functional ingredients production in the food industry.

A paper-based label-free plasmonic nanosensor for portable pre-diagnosis of multiple metabolic diseases

Early diagnosis is crucial for improving the prognosis of patients with metabolic diseases. In this study, we developed an innovative, multiplexed, and user-friendly paper-based plasmonic nanosensor by integrating previously established FeHOAuC (Fe2+-catalyzed H2O2 prevents the aggregation of AuNPs by oxidizing cysteine) label-free plasmonic nanosensor. Initially, we prepared a paper art with designated sampling and colorimetric sections by applying polydimethylsiloxane onto cellulose and nitrocellulose papers. Subsequently, we fabricated and optimized the oxidase-coupled FeHOAuC system on the paper platform. The proposed nanosensor's sensitivity, specificity, and feasibility were evaluated using a quantitative color algorithm. In this sensor, pre-loaded oxidases convert target analytes into H2O2, which subsequently induces a color change in AuNPs by oxidizing cysteine under the catalytic action of Fe2+. This paper-based sensor can quantitatively measure glucose, cholesterol, uric acid, and lactate within 40 min. The limit of detection of 5-10 μM, combined with its demonstrated specificity, makes it highly suitable for the early diagnosis of related metabolic diseases. Importantly, through a straightforward dropping procedure and a smartphone camera, the plasmonic nanosensor can distinguish disease-related small molecules in real serum samples. In conclusion, the proposed paper-based plasmonic nanosensor device exhibited favorable performance with simple operation, presenting significant potential for domiciliary early diagnosis of multiple metabolic diseases.

Predicting diabetic kidney disease with serum metabolomics and gut microbiota

This study aims to identify biomarkers for reliably predicting diabetic kidney disease (DKD), systematically characterize serum metabolites and gut microbiota in DKD patients, and investigate the correlation between differential serum metabolites and gut microbiota. From September 2021 to January 2023, 90 subjects were recruited: 30 with DKD, 30 with type 2 diabetes mellitus (T2DM), and 30 normal controls (NCs). Serum metabolites, including 180 different metabolites, were analyzed using untargeted metabolomics UPLC-MS/MS, and gut microbiota were assessed via 16S rRNA sequencing. Differential metabolites were identified through univariate (t-test or Mann-Whitney U-test, P < 0.05) and multivariate analyses (OPLS-DA model, VIP > 1, P < 0.05), followed by selection using the least absolute shrinkage and selection operator (LASSO). The selected overlapping serum metabolites, along with DKD-associated differential gut microbiota, were used to develop a logistic regression prediction model for DKD based on six markers. In the DKD group compared to the DM and NC groups, 39 and 60 differential serum metabolites were identified, respectively (VIP > 1, P < 0.01). Among these, 36 serum metabolites, including alpha-Hydroxyisobutyric acid, were significantly elevated in DKD patients compared to those with DM. Of these, 28 metabolites showed a negative correlation with estimated glomerular filtration rate (eGFR), while 29 showed a positive correlation with urine albumin creatinine ratio (UACR). Patients with DKD were further categorized into subgroups (DKD middle and DKD early) based on eGFR (eGFR < 90 ml/min/1.73m2, eGFR ≥ 90 ml/min/1.73m2), revealing 23 differential metabolites. Dysbiosis of the gut microbiota was evident in DKD patients, with lower relative abundances of g_Prevotella and g_Faecalibacterium compared to the DM and NC groups. Subgroup analysis indicated decreased relative abundances of g_Prevotella and g_Faecalibacterium in the DKD middle group, along with a decrease in g_Klebsiella compared to the DKD early group, which correlated positively with DKD patients' eGFR. There were 11 common metabolites among the three groups of differential metabolites. Among these, three serum metabolites-imidazolepropionic acid, adipoylcarnitine, and 1-methylhistidine-were identified as predictive serum metabolic markers. Disease prediction models (logistic regression models) were constructed based on these three metabolites combined with three genera of bacteria. These models demonstrated strong discriminatory power for diagnosing patients with DKD compared to patients with DM (area under the receiver operating characteristic curve (AUROC) = 0.939 and precision-recall curve (AUPR) = 0.940). The models also effectively discriminated between patients with DKD and NCs (0.976, 0.973). This study revealed distinctive serum metabolites and gut microbiota in patients with DKD. It demonstrated the potential utility of three specific serum metabolites and three genera of bacteria in diagnosing patients with DKD and assessing their renal dysfunction.

Uncoupling protein 1-mediated protective effects of β3-adrenergic receptor agonist on kidney fibrosis via promoting adipose tissue browning in diabetic mice

BACKGROUND

Diabetes mellitus (DM) is a global health concern. Diabetic kidney disease (DKD) is a prevalent severe complication of DM and therapy is urgently needed. Adipose tissue (AT) plays a crucial role in the energy mediation through glucolipid metabolism. Mirabegron is a specific β3-adrenergic receptor agonist, which can activate thermogenesis in adipocytes, improve energy consumption, and increase insulin sensitivity and glucose tolerance. Therefore, mirabegron may play a role in DKD pathogenesis. However, its effects and precise mechanisms remain unclear.

METHODS

A DKD mouse model based on type 2 DM (T2DM) was constructed and treated with mirabegron. Mice with AT surgically removed and mice with uncoupling protein 1 (Ucp1) knockout were used to confirm whether thermogenesis induced by mirabegron was the key process.

RESULTS

Mirabegron promoted AT browning in DKD mice. Mirabegron increased insulin sensitivity, promoted glucolipid metabolism, reduced inflammatory factor levels in kidney tissue, and improved renal function and fibrosis in DKD mice. Notably, all of these benefits disappeared in AT-removed DKD mice or in Ucp1 knockout DKD mice.

CONCLUSIONS

Mirabegron protects against kidney fibrosis in DM mice by activating AT thermogenesis via the UCP1 pathway. Thus, mirabegron may provide a promising potential option for DKD therapy.

Exploring the interplay between adipokine-mediated celastrol target genes and T cells in diabetic nephropathy: a mendelian randomization-based causal inference

BACKGROUND

Diabetic nephropathy (DN) is influenced by dysregulated adipokines, which play a key role in inflammation, immune responses, and lipid metabolism. However, the precise molecular mechanisms linking adipokine dysregulation, immune cell infiltration, and metabolic reprogramming in DN remain poorly understood. Celastrol, a bioactive lipid regulator, has been shown to mitigate renal immune-inflammatory damage by inhibiting the PI3K/Akt/NF-κB signaling pathway. Yet, its specific impact on adipokine-mediated immune responses and lipid metabolism in DN is unclear. This study aims to elucidate the interplay between adipokine-mediated target genes in DN and investigate how celastrol modulates these interactions.

METHODS

Gene expression profiles of DN patients were obtained from GEO datasets (GSE30122 and GSE30528) and analyzed for differentially expressed genes (DEGs) using the limma package. Gene set variation analysis (GSVA) was conducted to assess lipid metabolism pathways, while Mendelian randomization (MR) and Pearson correlation evaluated the association between DEGs and adipokines. Immune cell infiltration was analyzed using the IOBR R package (MCP-counter and xCell methods), followed by MR analysis of DN-related immune responses. Celastrol target genes were identified using the SEA database.

RESULTS

A total of 70 intersecting DEGs were identified. GSVA revealed that brown and beige adipocyte differentiation pathways were downregulated, while adipocyte-related pathways were upregulated in DN (p < 0.05). MR analysis demonstrated that adiponectin was negatively associated with DN (OR = 0.77, P = 0.005), whereas leptin (OR = 1.92, P = 0.016) and resistin (OR = 1.43, P < 0.001) were positively associated. Three key genes, MAGI2, FGF9, and THBS2 were linked to DN risk and T cell infiltration. THBS2 was positively correlated with T cell infiltration (OR = 0.51, P = 6.7e-06), while FGF9 (OR = -0.8, P = 2.2e-16) and MAGI2 (OR = 0.75, P = 1.3e-13) were negatively correlated. 22 celastrol target genes, including MAGI2, FGF9, and THBS2, were identified.

CONCLUSION

Our findings reveal that celastrol modulates DN progression through adipokine-immune crosstalk, with FGF9, MAGI2, and THBS2 emerging as key regulatory genes. These insights provide new avenues for biomarker discovery and therapeutic implications in the development of DN.

Serum metabolic profiling of patients with diabetic kidney disease based on gas chromatography-mass spectrometry

Introduction

Given the increasing incidence rate of diabetic kidney disease (DKD), there is an urgent need for methods to diagnose and treat DKD in clinics.

Methods

Serum samples were collected from 56 DKD patients and 32 healthy controls (HCs) at the First Affiliated Hospital of Ningbo University, and the metabolic profiles were obtained through untargeted metabolomics using gas chromatography mass spectrometry. The data were then analyzed using principal components analysis, orthogonal partial least-squares discriminant analysis, Pearson correlation analysis, and receiver operating characteristic (ROC) curve.

Results

It was found that the serum metabolic profiles of the DKD patients were significantly different from those of the HCs. A total of 68 potential differential metabolites were identified that were involved in arginine biosynthesis, ascorbate and aldarate metabolism, and galactose metabolism, among others; a total of 31 differential metabolites were also identified between early-stage (EDG) and late-stage (LDG) DKD patients. Additionally, 30 significant metabolic differences were observed among the EDG, LDG, and HC groups. Based on Pearson correlation analysis between the abundances of the differential metabolites and clinical markers (estimated glomerular filtration rate, blood urea nitrogen, serum creatinine, and urinary albumin/creatinine ratio) and area under the ROC curve (AUROC) analysis, the AUROC values of myoinositol and gluconic acid were found to be 0.992 and 0.991, respectively, which can be used to distinguish DKD patients from HCs.

Discussion

These results indicate that myoinositol and gluconic acid could possibly be used as biomarkers of DKD.

Integrated metabolomics and mass spectrometry imaging analysis reveal the efficacy and mechanism of Huangkui capsule on type 2 diabetic nephropathy

BACKGROUND

Huangkui capsule (HKC), a Chinese patent medicine, is clinically used for treating diabetic nephropathy. However, the core disease-specific biomarkers and targets of type 2 diabetic nephropathy (T2DN) and the therapeutic mechanism of HKC are not fully elucidated.

PURPOSE

This study aimed to investigate the therapeutic effects and underlying molecular mechanisms of HKC for T2DN.

STUDY DESIGN

The db/db mouse model was used to evaluate the efficacy of HKC for T2DN, and the core pathways regulated by HKC were studied to determine its kidney protective mechanism.

METHODS

High-throughput UPLC-MS/MS and multivariate analysis were employed to analyze the serum and kidney metabolic profiles of db/db mice, identifying potential core biomarkers of T2DN. Atmospheric pressure matrix-assisted laser desorption/ionization mass spectrometry imaging was used to locate in situ spatial distribution of core biomarkers and drug active ingredients in kidney tissues. Biochemical indicators, histopathology, immunohistochemistry, immunofluorescence, molecular docking, and western blotting were combined to reveal therapeutic effects, pathways, and targets of HKC.

RESULTS

HKC substantially improved pathological characteristics, kidney function, oxidative stress, inflammation, and lipid metabolism indicators of T2DN. Twelve core disease-specific biomarker that significantly influenced clustering were identified and its unique spatial distribution information in the kidneys was revealed. 3-dehydrosphinganine, retinyl ester, and 9-cis-retinoic acid (9cRA) could serve as novel disease-specific biomarkers for T2DN. Based on newly discovered biomarkers, quercetin, myricetin, and isorhamnetin were found to act on key enzymes SPT, ALDH1A1, AOX, LRAT, and DGAT1 in retinol and sphingolipid metabolism pathways. Western blotting showed that HKC ameliorated T2DN by targeting these enzymes, upregulating 9cRA and retinyl ester, downregulating 3-dehydrosphinganine, increasing TGF-β signal transduction, inhibiting the expression of the immune fibrosis proteins OX-8, Col-I and α-SMA, inhibiting Th17 cell development and ceramide synthesis, reducing IL-1β, TNF-α, MDA, TC, LDL-C, and TG levels, and increaseing SOD activity.

CONCLUSIONS

HKC exerts significant therapeutic effects on T2DN. HKC corrects the metabolic disorder of sphingolipids and retinol, and improves T2DN by regulating the activities of SPT, ALDH1A1, AOX, LRAT, and DGAT1. This study provides valuable ideas and new mechanistic insights for the treatment of T2DN with HKC.

Targeting the NF-κB p65-MMP28 axis: Wogonoside as a novel therapeutic agent for attenuating podocyte injury in diabetic nephropathy

BACKGROUND

Although recent progress provides mechanistic insights into diabetic nephropathy (DN), effective treatments remain scarce. DN, characterized by proteinuria and a progressive decline in renal function, primarily arises from podocyte injury, which impairs the glomerular filtration barrier. Wogonoside, a bioactive compound from the traditional Chinese herb Scutellaria baicalensis, has not been explored for its role in DN.

PURPOSE

This study aimed to investigate the therapeutic effects of wogonoside on podocyte injury in DN and its molecular mechanisms.

METHODS

The effects of wogonoside were examined using HFD/STZ-induced DN mouse models and high glucose (HG)-induced MPC-5 cells. Oxidative stress and inflammation markers were analyzed via Western blot and RT-qPCR. Wogonoside targets were identified through DARTS-MS and validated by SPR, molecular docking, alanine scanning, and CETSA. RNA-Seq analysis was employed to identify downstream targets, and the p65-MMP28 axis was explored through p65 knockdown and overexpression studies. The regulatory effect of p65 on Mmp28 was confirmed through dual-luciferase reporter assays and ChIP-qPCR.

RESULTS

Wogonoside treatment significantly reduced oxidative stress and inflammation in vivo and in vitro. Mechanistic studies identified p65 as a direct target of wogonoside, with SPR confirming a strong binding affinity (KD = 25.05 μM). Molecular docking and alanine scanning identified LYS221 as a critical binding site, which was further supported by CETSA using the p65 K221A mutant. RNA-Seq analysis revealed Mmp28 as a downstream effector of p65 involved in HG-induced podocyte injury. Functional studies demonstrated that wogonoside's protective effects on antioxidant and inflammatory pathways are mediated via the p65-MMP28 axis. Dual-luciferase reporter assays revealed that p65 regulates Mmp28 transcription, and ChIP-qPCR confirmed its direct promoter binding.

CONCLUSIONS

This study highlights wogonoside as a promising candidate for the treatment of podocyte injury in DN by targeting the NF-κB p65-MMP28 signaling axis. These findings provide novel insights into wogonoside's therapeutic potential and its molecular mechanisms, paving the way for its further development as a DN intervention.

CircMRP4 orchestrates podocytes injury via the miR-499-5p/RRAGB/mTORC1 axis in diabetic kidney disease

Diabetic kidney disease2 (DKD) is a chronic complication of diabetes characterized by kidney damage due to persistent hyperglycemia. A growing number of evidence indicated that circular RNAs3 (circRNAs) play a crucial role in diabetes and associated complications. However, the function and mechanism of circRNAs in DKD remain unclear. Herein, we investigated the expression profiles of circRNAs in DKD mice compared to non-diabetic mice using RNA-seq analysis. A novel circRNA, circMRP4, derived from the circularization of Multidrug resistance-associated protein 44 (MRP4) was identified. The expression of circMRP4 was significantly increased in both kidney tissues of DKD and mouse podocytes exposed to high glucose5 (HG). In addition, knockdown of circMRP4 alleviated podocytes apoptosis and inflammation induced by HG, while circMRP4 overexpression resulted in the opposite impact. Dual-luciferase reporter, RNA immunoprecipitation and RNA pull-down assay demonstrated that circMRP4 could directly target miR-499-5p which was closely associated with podocytes apoptosis and inflammation. Furthermore, circMRP4 was found to act as a sponge for miR-499-5p, leading to the upregulation of its target RRAGB, thereby activating the mTORC1/P70S6K signaling. In summary, our findings suggested that circMRP4 mediated podocytes apoptosis and inflammation in DKD by modulating the miR-499-5p/RRAGB/mTORC1/P70S6K axis, highlighting circMRP4 as a potential therapeutic target for DKD.

Vinegar-processed Schisandra chinensis polysaccharide ameliorates type 2 diabetes via modulation serum metabolic profiles, gut microbiota, and fecal SCFAs

Numerous studies indicate that Schisandra chinensis (Turcz.) Baill (SC) has anti-type 2 diabetes mellitus (T2DM) effects, and its processed products are commonly used in clinical practice. However, limited reports exist on the mechanisms of polysaccharides from its vinegar products and their role in T2DM. We purified a novel polysaccharide from vinegar-processed Schisandra chinensis (VSC) and used intestinal microbiota 16S rRNA analysis and metabolomics to study changes in T2DM mice after vinegar-processed Schisandra chinensis polysaccharide (VSP) intervention, aiming to elucidate how VSP alleviates T2DM. VSP has shown significant therapeutic effects in T2DM mice, which can regulate the imbalance of glucose and lipid metabolism, alleviate pancreatic and liver damage, restore the integrity of the intestinal barrier, and inhibit the inflammatory response. Serum metabolomics and microbiological analysis showed that VSP could significantly regulate 104 endogenous metabolites and rectify gut microbiota disorders in T2DM mice. Additionally, VSP enhanced the levels of short-chain fatty acids (SCFAs) and the expression of GPR41/43 in the colon of T2DM mice. Correlation analysis revealed significant correlations among specific gut microbiota, serum metabolites, and fecal SCFAs. Overall, these findings will provide a basis for further VSP development.

Proteomic and metabolomic profiling reveals the underlying molecular mechanisms in modified alternate-day fasting-mediated protection against Diabetic kidney disease

BACKGROUND

Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease, and while lifestyle interventions like intermittent fasting have shown promise in treating diabetes, the impact of modified alternate-day fasting (MADF) on DKD is not well understood. This study aimed to explore MADF's effects on DKD in db/db mice, a model for the condition, and to investigate its underlying mechanisms.

METHODS

We implemented an MADF regimen in db/db mice on a high-fat diet, measuring blood glucose, body weight, and renal function at various times. After the intervention, we analyzed the proteome and metabolome of renal tissues.

RESULTS

MADF was found to reduce hyperglycemia and slow the pathological progression of DKD in the mice. Proteomic analysis identified 165 proteins that increased and 196 that decreased in the kidneys of db/db mice compared to controls. MADF intervention led to a decrease in 26 of the increased proteins and an increase in 18 of the decreased ones. Notably, many of these proteins, including cathepsin S (CTSS), were related to lysosomes, suggesting a role in renal protection. Metabolomic profiling revealed changes in metabolites associated with inflammation, such as prostaglandin A1, which was downregulated in db/db mice and upregulated with MADF. Western blotting, immunohistochemistry, and immunofluorescence staining confirmed the expression changes of CTSS observed in the proteomic data. Additionally, CTSS expression was found to increase in renal cells exposed to high glucose and palmitic acid.

CONCLUSION

MADF appears to mitigate the progression of DKD, with proteomic evidence pointing to lysosome-related proteins like CTSS as potential mediators of its renal protective effects. These findings indicate that MADF and the inhibition of CTSS could be considered as novel therapeutic strategies for DKD treatment.

Metabolomics approach reveals key plasma biomarkers in multiple myeloma for diagnosis, staging, and prognosis

BACKGROUND

Multiple myeloma (MM) is the most aggressive and prevalent primary malignant tumor within the blood system, and can be classified into grades RISS-I, II, and III. High-grade tumors are associated with decreased survival rates and increased recurrence rates. To better understand metabolic disorders and expand the potential targets for MM, we conducted large-scale untargeted metabolomics on plasma samples from MM patients and healthy controls (HC).

METHODS

Our study included 33 HC, 38 newly diagnosed MM patients (NDMM) categorized into three RISS grades (grade I: n = 5; grade II: n = 19; grade III: n = 8), and 92 MM patients post-targeted therapy with bortezomib-based regimens. Simultaneously, MM cell lines were employed for validation studies. Metabolites were analyzed and identified using ultra high liquid chromatography coupled with Q Orbitrap mass spectrometry (UPLC-HRMS), followed by verification through a self-built database.

RESULTS

Compared with HC participants, a total of 70 metabolites were identified as undergoing significant changes in NDMM. These metabolites were significantly enriched in citrate cycle, choline metabolism, glycerophospholipid metabolism, and sphingolipid metabolism, etc. Notably, a panel of circulating plasma metabolite biomarkers, including lactic acid and leucine, has emerged not only as diagnostic indicators but also as valuable tools for tumor surveillance, aiding in the assessment of disease stage and prognostic evaluation. Moreover, 14 differential metabolites were identified in both MM cell lines and MM patients. Among these, intracellular levels of lactate and leucine significantly decreased in vitro, aligning with the plasma results.

CONCLUSION

Our findings on key metabolites and metabolic pathways provide novel insights into the exploration of diagnostic and therapeutic targets for MM. A prospective study is essential to validate these discoveries for future MM patient care.

Cardiorenal syndrome: clinical diagnosis, molecular mechanisms and therapeutic strategies

As the heart and kidneys are closely connected by the circulatory system, primary dysfunction of either organ usually leads to secondary dysfunction or damage to the other organ. These interactions play a major role in the pathogenesis of a clinical entity named cardiorenal syndrome (CRS). The pathophysiology of CRS is complicated and involves multiple body systems. In early studies, CRS was classified into five subtypes according to the organs associated with the vicious cycle and the acuteness and chronicity of CRS. Increasing evidence shows that CRS is associated with a variety of pathological mechanisms, such as haemodynamics, neurohormonal changes, hypervolemia, hypertension, hyperuraemia and hyperuricaemia. In this review, we summarize the classification and currently available diagnostic biomarkers of CRS. We highlight the recently revealed molecular pathogenesis of CRS, such as oxidative stress and inflammation, hyperactive renin‒angiotensin‒aldosterone system, maladaptive Wnt/β-catenin signalling pathway and profibrotic TGF‒β1/Smad signalling pathway, as well as other pathogeneses, such as dysbiosis of the gut microbiota and dysregulation of noncoding RNAs. Targeting these CRS-associated signalling pathways has new therapeutic potential for treating CRS. In addition, various chemical drugs, natural products, complementary therapies, blockers, and agonists that protect against CRS are summarized. Since the molecular mechanisms of CRS remain to be elucidated, no single intervention has been shown to be effective in treating CRS. Pharmacologic therapies designed to block CRS are urgently needed. This review presents a critical therapeutic avenue for targeting CRS and concurrently illuminates challenges and opportunities for discovering novel treatment strategies for CRS.

Relationship between metabolomics of T2DM patients and the anti-diabetic effects of Phellodendri Chinensis Cortex-Anemarrhenae Rhizoma herb pair in mice

ETHNOPHARMACOLOGICAL RELEVANCE

Type 2 diabetes mellitus (T2DM) poses significant threats to public health. In Traditional Chinese Medicine (TCM), the Phellodendri Chinensis Cortex-Anemarrhenae Rhizoma (PCC/AR) herb pair has long been used for T2DM treatment, although its specific anti-diabetic mechanisms remain unclear.

AIM OF THE STUDY

This study aimed to elucidate the relationship between metabolomics of T2DM patients and the anti-diabetic effects of PCC/AR herb pair in mice through clinical metabolomics and both in vitro and in vivo experiments.

MATERIALS AND METHODS

In this study, a T2DM mouse model was established via high-fat feeding (HFD) and streptozotocin (STZ) injection. The effects of PCC/AR on blood glucose, lipid metabolism, and inflammatory markers were evaluated. High-performance liquid chromatography-mass spectrometry (HPLC-MS) was performed for metabolomics analysis of T2DM patients.

RESULTS

Serum metabolomics analysis identified significant alterations in metabolites linked to the biosynthesis of unsaturated fatty acids and purine metabolism in T2DM patients, with elevated 2-hydroxyvaleric acid (2HB) levels. In T2DM mice, PCC/AR intervention normalized FBG, GHbA1c, TC, TG, LDL-C, HDL-C, TNF-α and IL-1β levels, while improving insulin sensitivity and pancreatic β-cell function in T2DM mice. Notably, PCC/AR reduced key enzymes in gluconeogenesis and fatty acid synthesis, PEPCK and ACC1.

CONCLUSION

PCC/AR herb pair exerts an anti-diabetes effect in T2DM mice by regulating 2HB through ACC1 inhibition, thereby reducing FFA and TG synthesis. Additionally, PCC/AR may also exert its effects by modulating glucose and lipid metabolism and reducing inflammation. These results support further investigation into the PCC/AR herb pair as a complementary therapy for T2DM.

Microbiota-related metabolites correlated with the severity of COVID-19 patients

BACKGROUND

Coronavirus disease 2019 (COVID-19) is a global pandemic with high mortality, and the treatment options for the severe patients remain limited. Previous studies reported the altered gut microbiota in severe COVID-19. But there are no comprehensive data on the role of microbial metabolites in COVID-19 patients.

METHODS

We identified 153 serum microbial metabolites and assessed the changes in 72 COVID-19 patients upon admission and one-month after their discharge, comparing these changes to those in 133 healthy control individuals from the outpatient department during the same period.

RESULTS

Our study revealed that microbial metabolites varied across different stages and severity of COVID-19 patients. These altered microbial metabolites included tryptophan, bile acids, fatty acids, amino acids, vitamins and those containing benzene. A total of 13 distinct microbial metabolites were identified in COVID-19 patients compared to healthy controls. Notably, correlations were found among these disrupted metabolites and organ injury and inflammatory responses related to COVID-19. Furthermore, these metabolites did not restore to the normal levels one month after discharge. Importantly, two microbial metabolites were the core microbial metabolites related to the severity of COVID-19 patients.

CONCLUSIONS

The microbial metabolites were altered in the acute and recovery stage, correlating with disease severity of COVID-19. These results indicated the important role of gut microbiota in the progression of COVID-19, and facilitated the potential therapeutic microbial target for severe COVID-19 patients.

Decoding Kidney Pathophysiology: Omics-Driven Approaches in Precision Medicine

Chronic kidney disease (CKD) is a major worldwide health concern because of its progressive nature and complex biology. Traditional diagnostic and therapeutic approaches usually fail to account for disease heterogeneity, resulting in low efficacy. Precision medicine offers a novel approach to studying kidney disease by combining omics technologies such as genomics, transcriptomics, proteomics, metabolomics, and epigenomics. By identifying discrete disease subtypes, molecular biomarkers, and therapeutic targets, these technologies pave the way for personalized treatment approaches. Multi-omics integration has enhanced our understanding of CKD by revealing intricate molecular linkages and pathways that contribute to treatment resistance and disease progression. While pharmacogenomics offers insights into expected responses to personalized treatments, single-cell and spatial transcriptomics can be utilized to investigate biological heterogeneity. Despite significant development, challenges persist, including data integration concerns, high costs, and ethical quandaries. Standardized data protocols, collaborative data-sharing frameworks, and advanced computational tools such as machine learning and causal inference models are required to address these challenges. With the advancement of omics technology, nephrology may benefit from improved diagnostic accuracy, risk assessment, and personalized care. By overcoming these barriers, precision medicine has the potential to develop novel techniques for improving patient outcomes in kidney disease treatment.

Research progress of gut microbiome and diabetic nephropathy

Diabetic nephropathy is an important complication of diabetic microvascular injury, and it is also an important cause of end-stage renal disease. Its high prevalence and disability rate significantly impacts patients' quality of life while imposing substantial social and economic burdens. Gut microbiota affects host metabolism, multiple organ functions, and regulates host health throughout the life cycle. With the rapid development of technology, researchers have found that gut microbiota is closely related to the progression of diabetic kidney disease. This review explores the role of gut microbiome in diabetic nephropathy summarizing proposed mechanisms of progression and focusing on microbial metabolites, intestinal barrier disruption, inflammation, filtration barrier damage and renal fibrosis. This review also examines the mechanism and limitations of current treatments, including drugs, fecal microbiota transplantation, and lifestyle changes, offering new perspectives on prevention and treatment.

Multi-Omics Research on Angina Pectoris: A Novel Perspective

Angina pectoris (AP), a clinical syndrome characterized by paroxysmal chest pain, is caused by insufficient blood supply to the coronary arteries and sudden temporary myocardial ischemia and hypoxia. Long-term AP typically induces other cardiovascular events, including myocardial infarction and heart failure, posing a serious threat to patient safety. However, AP's complex pathological mechanisms and developmental processes introduce significant challenges in the rapid diagnosis and accurate treatment of its different subtypes, including stable angina pectoris (SAP), unstable angina pectoris (UAP), and variant angina pectoris (VAP). Omics research has contributed significantly to revealing the pathological mechanisms of various diseases with the rapid development of high-throughput sequencing approaches. The application of multi-omics approaches effectively interprets systematic information on diseases from the perspective of genes, RNAs, proteins, and metabolites. Integrating multi-omics research introduces novel avenues for identifying biomarkers to distinguish different AP subtypes. This study reviewed articles related to multi-omics and AP to elaborate on the research progress in multi-omics approaches (including genomics, transcriptomics, proteomics, and metabolomics), summarized their applications in screening biomarkers employed to discriminate multiple AP subtypes, and delineated integration methods for multi-omics approaches. Finally, we discussed the advantages and disadvantages of applying a single-omics approach in distinguishing diverse AP subtypes. Our review demonstrated that the integration of multi-omics technologies is preferable for quick and precise diagnosis of the three AP types, namely SAP, UAP, and VAP.

Advance in the application of metabolomics technology in poultry

Metabolomics is a science that takes small molecular metabolites in organisms as the research object and determines the dynamic changes of metabolites at the overall level through a variety of modern analytical techniques. At present, metabolomics technology has been widely used in biological significance interpretation, food safety and quality, breeding, disease diagnosis, functional compound identification, and other fields. Its application in poultry science has also become the focus of widespread attention. With the sustainable development of analytical techniques, metabolomics has great potential in the application of poultry science. In this paper, the research progress of metabolomics in poultry growth and development, genetics and breeding, egg quality, meat quality, and disease is reviewed and concluded, which is expected to provide scientific ideas for the research of metabolomics in poultry.

RXRα/MR signaling promotes diabetic kidney disease by facilitating renal tubular epithelial cells senescence and metabolic reprogramming

Cell senescence and metabolic reprogramming are significant features of diabetic kidney disease (DKD). However, the underlying mechanisms between cell senescence and metabolic reprogramming are poorly defined. Here, we report that retinoid X receptor α (RXRα), a key nuclear receptor transcription factor, regulates cell senescence and metabolic reprogramming in DKD. Through high-throughput sequencing, bioinformatic analysis and experimental validation, we confirmed the critical role of RXRα in promoting cell senescence and metabolic dysregulation in renal tubular epithelial cells (RTECs) induced by lipid overload. In vivo, in situ injection of AAV9-shRxra into the kidney reduced proteinuria, RTECs senescence and insulin resistance in DKD mice. In vitro, knockdown of RXRα markedly improved G2/M phase arrest and suppressed the expression of senescence-associated secretory phenotypes (SASPs). Protein-protein interaction (PPI) analysis and unbiased bioinformatics were employed to identify the direct interactions between RXRα and the mineralocorticoid receptor (MR), which were subsequently validated through coimmunoprecipitation. Gene network analysis revealed the collaborative regulatory role of RXRα and MR in RTECs senescence. In an accelerated aging mouse model, treatment with a MR antagonist has been shown to inhibite the RXRα/MR signaling, improve RTECs senescence, and reduce interstitial fibrosis and lipid deposition in the kidneys. These findings indicate that inhibition of RXRα/MR signaling could alleviate cell senescence during metabolic disorders. Thus, our study revealed that RXRα/MR signaling serves as a critical regulatory factor mediating the crosstalk between cell senescence and metabolic reprogramming, shedding light on a novel mechanism for targeting cell senescence and metabolic dysregulation in DKD.

The ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol is associated with diabetic kidney disease: A cross-sectional study

Non-High-Density Lipoprotein Cholesterol to High-Density Lipoprotein Cholesterol Ratio (NHHR) is a significant indicator of atherosclerosis. However, its association with diabetic kidney disease (DKD) remains unclear. This study aims to explore the relationship between NHHR and the prevalence of DKD among the U.S. adults using data from the National Health and Nutrition Examination Survey (NHANES) spanning 1999 to 2020. Participants were selected based on the stringent inclusion and exclusion criteria. We utilized single-factor analysis, multivariate logistic regression, and smooth curve fitting to investigate the relationship between NHHR and DKD. Our study included 8,329 diabetic individuals, who were categorized into DKD and non-DKD groups based on the presence or absence of kidney damage. A significant difference in NHHR was observed between these groups. After adjusting for potential confounders, we found that NHHR was positively associated with the prevalence of DKD. Specifically, each one-unit increase in NHHR corresponded to a 6% rise in the prevalence of DKD, with this association remaining significant across stratified NHHR values. Threshold effect analysis revealed an inflection point at an NHHR of 1.75, beyond this point, each unit increase in NHHR was associated with a 7% increase in the prevalence of DKD. Subgroup analysis confirmed the robustness of these findings. Our study demonstrates a significant correlation between NHHR and DKD prevalence, suggesting that monitoring NHHR could be an effective strategy for reducing DKD prevalence.

Metabolomics analysis of human spermatozoa reveals impaired metabolic pathways in asthenozoospermia

BACKGROUND

Infertility is a major health issue, affecting 15% of reproductive-age couples with male factors contributing to 50% of cases. Asthenozoospermia (AS), or low sperm motility, is a common cause of male infertility with complex aetiology, involving genetic and metabolic alterations, inflammation and oxidative stress. However, the molecular mechanisms behind low motility are unclear. In this study, we used a metabolomics approach to identify metabolic biomarkers and pathways involved in sperm motility.

METHODS

We compared the metabolome and lipidome of spermatozoa of men with normozoospermia (n = 44) and AS (n = 22) using untargeted LC-MS and the metabolome of seminal fluid using 1H-NMR. Additionally, we evaluated the seminal fluid redox status to assess the oxidative stress in the ejaculate.

RESULTS

We identified 112 metabolites and 209 lipids in spermatozoa and 27 metabolites in the seminal fluid of normozoospermic and asthenozoospermic men. PCA analysis of the spermatozoa's metabolomics and lipidomics data showed a clear separation between groups. Spermatozoa of asthenozoospermic men presented lower levels of several amino acids, and increased levels of energetic substrates and lysophospholipids. However, the metabolome and redox status of the seminal fluid was not altered inAS.

CONCLUSIONS

Our results indicate impaired metabolic pathways associated with redox homeostasis and amino acid, energy and lipid metabolism in AS. Taken together, these findings suggest that the metabolome and lipidome of human spermatozoa are key factors influencing their motility and that oxidative stress exposure during spermatogenesis or sperm maturation may be in the aetiology of decreased motility in AS.

Analysis of the global burden of CKD-T2DM in young and middle-aged adults in 204 countries and territories from 2000 to 2019: A systematic study of the global burden of disease in 2019

BACKGROUND

Diabetes stands as a principal risk factor for severe complications including renal and cardiovascular diseases. The gradual rise in type 2 diabetes cases globally, coupled with a trend towards younger demographics, has led to an escalating prevalence of chronic kidney disease. However, its etiology is multifaceted, necessitating individualized treatment and refinement, particularly crucial in screening and managing the burden of CKD-T2DM. A comprehensive analysis of CKD-T2DM burden at global, regional, and national levels from 2000 to 2019, based on the latest data, can inform screening, early diagnostics, and treatment strategies, thereby optimizing healthcare resource allocation.

METHODS

Utilizing data sourced from the Global Burden of Disease (GBD) database, we delineated the incidence, mortality, and DALYs rates of CKD-T2DM from 2000 to 2019 across global, regional, and national scales. We summarized the age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and age-standardized death rate (ASDR) of CKD-T2DM globally, regionally, and nationally, presenting them visually. Moreover, we calculated and visually depicted the estimated annual percentage change (EAPC) of various CKD-T2DM indicators at these levels. Additionally, CKD-T2DM patients were stratified by age to compare the age distribution of patient deaths and the age burden between 2000 and 2019.

FINDINGS

The disease burden of CKD-T2DM among young and middle-aged individuals globally has shown a sustained increase from 2000 to 2019. Incidence, mortality, and DALYs rates have exhibited an overall upward trend, with males showing higher rates compared to females. Significant disparities exist among different countries and regions, with India, China, and Mexico emerging as the countries with the highest number of new cases. Nicaragua, Mexico, and the United Arab Emirates have the highest age-standardized incidence rates, whereas Uganda, Ethiopia, and Burundi have the lowest. At the age level, the burden of CKD-T2DM exhibits varying trends among different age groups but generally shows an upward trajectory, particularly in the 45-49 age bracket. High systolic blood pressure and high BMI stand as the primary contributing factors to mortality and DALYs, with variations in their influence observed across different regions and levels of development.

INTERPRETATION

ver the past 20 years, the burden of CKD-T2DM among young and middle-aged individuals globally has continued to increase, with disparities existing among different countries, regions, and age groups, but overall showing an upward trend. The reasons for this trend are multifaceted, including global lifestyle changes such as dietary shifts, sedentary lifestyles, obesity, as well as population aging and inadequate preventive measures in certain regions. Addressing these challenges necessitates optimizing screening methods, adjusting lifestyles, enhancing management strategies, improving medical care and awareness levels, particularly intensifying awareness and screening efforts among males, reinforcing prevention and control measures for the 45-49 age group, enhancing infrastructure and healthcare resources in developing countries, fostering international collaboration, and implementing context-specific measures.

Metabolomic profiling of human semen in patients with oligospermia using high performance liquid chromatography-tandem mass spectrometry

Male infertility is one of the most common reproductive dysfunctions. Despite oligospermia being a cause of infertility, few studies have been conducted on it. This study aimed to investigate differences in semen metabolic patterns in patients with oligospermia and to identify potential biomarkers associated with oligospermia. Semen samples from oligospermia patients (20 cases) and healthy controls (20 cases) were detected by high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS), and 72 and 89 metabolites were identified as potential markers in positive and negative ion modes, respectively. In addition, the results identified multiple metabolic pathways in patients with oligospermia, such as glycine serine and threonine metabolism, Synthesis and degradation of ketone bodies, Valine, leucine, and isoleucine degradation. These results described unique metabolic characteristics of semen in patients with oligospermia and provided novel insights into the mechanism of the semen disorder.

The Retinal Blood Flow Density Is Related to the Pathological Severity of Diabetic Kidney Disease

INTRODUCTION

This study aimed to investigate the correlation between fundus blood flow parameters and the severity of pathological biopsy in patients with diabetic kidney disease (DKD).

METHODS

Data of patients with type 2 diabetes mellitus who completed renal pathology biopsies and optical coherence tomography angiography (OCTA) examinations, including renal function, 24-h urine protein quantification, and macular flow imaging, were collected. DKD pathology biopsies were graded as stages 1-4, and differences and correlations of the parameters were compared between groups. The grading was transformed into early (stage 1) and late (stages 2-4), and regression analyses were conducted to develop a model, draw a nomogram, and test efficacy.

RESULTS

This study included 157 eyes from 157 individuals in total. Urinary microalbumin and to urinary creatinine ratio (mALB/NCR) increased with pathological grading, whereas while glomerular filtration rate was decreased (p < 0.01). Corresponding retinal blood flow in superficial, deep, and full paracentral rings was decreased, which correlated with pathological grading (p < 0.01), with the highest blood flow density in the whole layer (r2 = -0.707). Meaningfully, in the early DKD model (area under the curve = 0.929 [0.889-0.970], p < 0.01), whole-layer blood flow density, mALB/NCR, and diabetes duration were statistically significant.

CONCLUSIONS

The decrease in macular retinal blood flow density detected by OCTA is closely associated with the increase in pathological grading of DKD and can be used as a noninvasive parameter for monitoring early changes in DKD.

An Overview of Pre-Analytical Factors Impacting Metabolomics Analyses of Blood Samples

Discrepant sample processing remains a significant challenge within blood metabolomics research, introducing non-biological variation into the measured metabolome and biasing downstream results. Inconsistency during the pre-analytical phase can influence experimental processes, producing metabolome measurements that are non-representative of in vivo composition. To minimize variation, there is a need to create and adhere to standardized pre-analytical protocols for blood samples intended for use in metabolomics analyses. This will allow for reliable and reproducible findings within blood metabolomics research. In this review article, we provide an overview of the existing literature pertaining to pre-analytical factors that influence blood metabolite measurements. Pre-analytical factors including blood tube selection, pre- and post-processing time and temperature conditions, centrifugation conditions, freeze-thaw cycles, and long-term storage conditions are specifically discussed, with recommendations provided for best practices at each stage.

Targeting Lactobacillus johnsonii to reverse chronic kidney disease

Accumulated evidence suggested that gut microbial dysbiosis interplayed with progressive chronic kidney disease (CKD). However, no available therapy is effective in suppressing progressive CKD. Here, using microbiomics in 480 participants including healthy controls and patients with stage 1-5 CKD, we identified an elongation taxonomic chain Bacilli-Lactobacillales-Lactobacillaceae-Lactobacillus-Lactobacillus johnsonii correlated with patients with CKD progression, whose abundance strongly correlated with clinical kidney markers. L. johnsonii abundance reduced with progressive CKD in rats with adenine-induced CKD. L. johnsonii supplementation ameliorated kidney lesion. Serum indole-3-aldehyde (IAld), whose level strongly negatively correlated with creatinine level in CKD rats, decreased in serum of rats induced using unilateral ureteral obstruction (UUO) and 5/6 nephrectomy (NX) as well as late CKD patients. Treatment with IAld dampened kidney lesion through suppressing aryl hydrocarbon receptor (AHR) signal in rats with CKD or UUO, and in cultured 1-hydroxypyrene-induced HK-2 cells. Renoprotective effect of IAld was partially diminished in AHR deficiency mice and HK-2 cells. Our further data showed that treatment with L. johnsonii attenuated kidney lesion by suppressing AHR signal via increasing serum IAld level. Taken together, targeting L. johnsonii might reverse patients with CKD. This study provides a deeper understanding of how microbial-produced tryptophan metabolism affects host disease and discovers potential pathways for prophylactic and therapeutic treatments for CKD patients.

Ramulus Mori (Sangzhi) Alkaloids Alleviate Diabetic Nephropathy through Improving Gut Microbiota Disorder

Diabetic nephropathy (DN), one of the leading causes of end-stage kidney failure worldwide, is closely associated with high mortality in diabetic patients. However, therapeutic drugs for DN are still lacking. Ramulus Mori alkaloids (SZ-A), an effective component of alkaloids extracted from Ramulus Mori, have been found to improve glucose and lipid metabolism to mitigate diabetes and obesity; however, few studies have focused on their effects on DN progression. Thus, we investigated the protective role of SZ-A on DN through 16S rRNA sequencing, non-targeted metabolomics, and fecal microbiota transplantation (FMT) experiments. To address our hypothesis, we established the DN mouse model by combining a high-fat diet (HFD) with streptozotocin (STZ) injection. Herein, we demonstrated that SZ-A supplementation was recalcitrant to renal injury in DN mice, improving glomerular morphology, reversing the blood biochemistry parameters, and ameliorating podocyte injury. Importantly, the composition of the gut microbiota altered after SZ-A treatment, especially with the elevated abundance of Dubosiella and the increased level of serum pentadecanoic acid. FMT experiments further revealed that the gut microbiota exerted critical effects in mediating the beneficial roles of SZ-A. In vitro experiments proved that pentadecanoic acid administration improved podocyte apoptosis induced by AGEs. Taken together, SZ-A play a renoprotective role, possibly through regulating the gut microbiota and promoting pentadecanoic acid production. Our current study lends support to more extensive clinical applications of SZ-A.

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.

Easy-Amanida: An R Shiny application for the meta-analysis of aggregate results in clinical metabolomics using Amanida and Webchem

Meta-analysis is a useful tool in clinical research, as it combines the results of multiple clinical studies to improve precision when answering a particular scientific question. While there has been a substantial increase in publications using meta-analysis in various clinical research topics, the number of published meta-analyses in metabolomics is significantly lower compared to other omics disciplines. Metabolomics is the study of small chemical compounds in living organisms, which provides important insights into an organism's phenotype. However, the wide variety of compounds and the different experimental methods used in metabolomics make it challenging to perform a thorough meta-analysis. Additionally, there is a lack of consensus on reporting statistical estimates, and the high number of compound naming synonyms further complicates the process. Easy-Amanida is a new tool that combines two R packages, "amanida" and "webchem", to enable meta-analysis of aggregate statistical data, like p-value and fold-change, while ensuring the compounds naming harmonization. The Easy-Amanida app is implemented in Shiny, an R package add-on for interactive web apps, and provides a workflow to optimize the naming combination. This article describes all the steps to perform the meta-analysis using Easy-Amanida, including an illustrative example for interpreting the results. The use of aggregate statistics metrics extends the use of Easy-Amanida beyond the metabolomics field.

Intermittent protein restriction before but not after the onset of diabetic kidney disease attenuates disease progression in mice

Background

High dietary protein intake exacerbates proteinuria in individuals with diabetic kidney disease (DKD). However, studies on the impacts of low protein diet (LPD) on DKD have yielded conflicting results. Furthermore, patient compliance to continuous protein restriction is challenging.

Objective

The current study aims to investigate the effects of intermittent protein restriction (IPR) on disease progression of DKD.

Methods

Diabetic KK-Ay mice were used in this study. For the IPR treatment, three consecutive days of LPD were followed by four consecutive days of normal protein diet (NPD) within each week. For early intervention, mice received IPR before DKD onset. For late intervention, mice received IPR after DKD onset. In both experiments, age-matched mice fed continuous NPD served as the control group. Kidney morphology, structure and function of mice in different groups were examined.

Results

Intermittent protein restriction before DKD onset ameliorated pathological changes in kidney, including nephromegaly, glomerular hyperfiltration, tubular injuries and proteinuria, without improving glycemic control. Meanwhile, IPR initiated after DKD onset showed no renoprotective effects despite improved glucose homeostasis.

Conclusion

Intermittent protein restriction before rather than after DKD onset protects kidneys, and the impacts of IPR on the kidneys are independent of glycemic control. IPR shows promise as an effective strategy for managing DKD and improving patient compliance.

Metabolomic biomarkers for benign conditions and malignant ovarian cancer: Advancing early diagnosis

BACKGROUND

Ovarian cancer (OC) is a major global cause of death among gynecological cancers, with a high mortality rate. Early diagnosis, distinguishing between benign conditions and early malignant OC forms, is vital for successful treatment. This research investigates serum metabolites to find diagnostic biomarkers for early OC identification.

METHODS

Metabolomic profiles derived from the serum of 60 patients with benign conditions and 60 patients with malignant OC were examined using ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). Comparative analysis revealed differential metabolites linked to OC, aiding biomarker identification for early-diagnosis of OC via machine learning features. The predictive ability of these biomarkers was evaluated against the traditional biomarker, cancer antigen 125 (CA125).

RESULTS

84 differential metabolites were identified, including 2-Thiothiazolidine-4-carboxylic acid (TTCA), Methionyl-Cysteine, and Citrulline that could serve as potential biomarkers to identify benign conditions and malignant OC. In the diagnosis of early-stage OC, the area under the curve (AUC) for Citrulline was 0.847 (95 % Confidence Interval (CI): 0.719-0.974), compared to 0.770 (95 % CI: 0.596-0.944) for TTCA, and 0.754 for Methionine-Cysteine (95 % CI: 0.589-0.919). These metabolites demonstrate a superior diagnostic capability relative to CA125, which has an AUC of 0.689 (95 % CI: 0.448-0.931). Among these biomarkers, Citrulline stands out as the most promising. Additionally, in the diagnosis of benign conditions and malignant OC, using logistic regression to combine potential biomarkers with CA125 has an AUC of 0.987 (95 % CI: 0.9708-1) has been proven to be more effective than relying solely on the traditional biomarker CA125 with an AUC of 0.933 (95 % CI: 0.870-0.996). Furthermore, among all the differential metabolites, lipid metabolites dominate, significantly impacting glycerophospholipid metabolism pathway.

CONCLUSION

The discovered serum metabolite biomarkers demonstrate excellent diagnostic performance for distinguishing between benign conditions and malignant OC and for early diagnosis of malignant OC.

Combined analysis of metabolomics and 16S rRNA sequencing for ankylosing spondylitis patients before and after secukinumab therapy

OBJECTIVE

Alterations in gut microbiota have been implicated in the pathogenesis of ankylosing spondylitis (AS), but the underlying mechanisms remain elusive. This study aims to investigate changes in gut microbiota and metabolites in individuals with AS before and after treatment with secukinumab, to identify the biological characteristics specific to AS patients and investigate the potential biomarkers, for optimizing therapeutic strategies more effectively.

METHODS

Fecal microbiome data were collected from 30 AS patients before and after secukinumab therapy and compared with data from 40 healthy controls (HC). Additionally, we analyzed the metabolic profile of both groups from plasma.

RESULTS

Findings indicated that the treatment-induced changes in the composition of several crucial bacterial groups, including Megamonas, Prevotella_9, Faecalibacterium, Roseburia, Bacteroides, and Agathobacter. Post-treatment, these groups exhibited a distribution more akin to that of the healthy populations compared with their pretreatment status. We identified three gut microbial taxa, namely Prevotellaceae_bacterium_Marseille_P2831, Prevotella_buccae, and Elusimicrobiota, as potential biomarkers for diagnosing individuals at a higher risk of developing AS and assessing disease outcomes. Plasma metabolomics analysis revealed 479 distinct metabolites and highlighted three disrupted metabolic pathways. Integration of microbiome and metabolomics datasets demonstrated a significant degree of correlation, underscoring the impact of the microbiome on metabolic activity.

CONCLUSION

Secukinumab can restore the balance of the gut microbiome and metabolites in AS patients, rendering them more similar to those found in the healthy population. The analysis of microbiome and metabolomics data have unveiled some candidate biomarkers capable of evaluating treatment efficacy.

Polysaccharides from Dendrobium officinale delay diabetic kidney disease interstitial fibrosis through LncRNA XIST/TGF-β1

PURPOSE

Renal interstitial fibrosis is a pathological manifestation of the progression of diabetic kidney disease (DKD). Dendrobium officinale polysaccharides (DOP), one of the major active components of Dendrobium officinale, have hypoglycemic and hypolipidemic effects and are used clinically to treat diabetes. However, the role of DOP in delaying DKD progression remains unclear. This study aimed to explore the potential mechanisms by which DOP delays DKD renal interstitial fibrosis.

METHODS

Using db/db mice as a model of DKD, we administered DOP by gavage and observed its therapeutic effectiveness. Employing ASO technology, we knocked down lncRNA XIST expression in kidney tissues and detected the expression of lncRNA XIST, TGF-β1, and renal interstitial fibrosis-related molecules.

RESULTS

DOP was primarily composed of monosaccharides, with 91.57% glucose and 1.41% mannose, forming a spheroid-like structure. It has a high polydispersity index with an Mw/Mn of 6.146, and the polysaccharides are mainly connected by 4-Man(p) and 4-Glc(p) linkages. In the kidneys of db/db mice, lncRNA XIST and TGF-β1 are highly expressed; however, their expression is significantly reduced after gastric infusion with DOP, and upon knockdown of lncRNA XIST, it might delay the progression of renal interstitial fibrosis in DKD.

CONCLUSION

DOP may delay the progression of DKD renal interstitial fibrosis through the regulation of the LncRNA XIST/TGF-β1 related fibrotic pathway. This provides a new perspective for clinical strategies to delay the progression of DKD renal interstitial fibrosis.

Lipid metabolism disorder in diabetic kidney disease

Diabetic kidney disease (DKD), a significant complication associated with diabetes mellitus, presents limited treatment options. The progression of DKD is marked by substantial lipid disturbances, including alterations in triglycerides, cholesterol, sphingolipids, phospholipids, lipid droplets, and bile acids (BAs). Altered lipid metabolism serves as a crucial pathogenic mechanism in DKD, potentially intertwined with cellular ferroptosis, lipophagy, lipid metabolism reprogramming, and immune modulation of gut microbiota (thus impacting the liver-kidney axis). The elucidation of these mechanisms opens new potential therapeutic pathways for DKD management. This research explores the link between lipid metabolism disruptions and DKD onset.

Tangshen formula protects against podocyte apoptosis via enhancing the TFEB-mediated autophagy-lysosome pathway in diabetic nephropathy

ETHNOPHARMACOLOGICAL RELEVANCE

Diabetic nephropathy (DN) is the leading cause of end-stage kidney disease and currently there are no specific and effective drugs for its treatment. Podocyte injury is a detrimental feature and the major cause of albuminuria in DN. We previously reported Tangshen Formula (TSF), a Chinese herbal medicine, has shown therapeutic effects on DN. However, the underlying mechanisms remain obscure.

AIM OF THE STUDY

This study aimed to explore the protective effect of TSF on podocyte apoptosis in DN and elucidate the potential mechanism.

MATERIALS AND METHODS

The effects of TSF were assessed in a murine model using male KKAy diabetic mice, as well as in advanced glycation end products-stimulated primary mice podocytes. Transcription factor EB (TFEB) knockdown primary podocytes were employed for mechanistic studies. In vivo and in vitro studies were performed and results assessed using transmission electron microscopy, immunofluorescence staining, and western blotting.

RESULTS

TSF treatment alleviated podocyte apoptosis and structural impairment, decreased albuminuria, and mitigated renal dysfunction in KKAy mice. Notably, TSF extracted twice showed a more significant reduction in proteinuria than TSF extracted three times. Accumulation of autophagic biomarkers p62 and LC3, and aberrant autophagic flux in podocytes of DN mice were significantly altered by TSF therapy. Consistent with the in vivo results, TSF prevented the apoptosis of primary podocytes exposed to AGEs and activated autophagy. However, the anti-apoptosis capacity of TSF was countered by the autophagy-lysosome inhibitor chloroquine. We found that TSF increased the nuclear translocation of TFEB in diabetic podocytes, and thus upregulated transcription of its several autophagic target genes. Pharmacological activation of TFEB by TSF accelerated the conversion of autophagosome to autolysosome and lysosomal biogenesis, further augmented autophagic flux. Conversely, TFEB knockdown negated the favorable effects of TSF on autophagy in AGEs-stimulated primary podocytes.

CONCLUSIONS

These findings indicate TSF appears to attenuate podocyte apoptosis and promote autophagy in DN via the TFEB-mediated autophagy-lysosome system. Thus, TSF may be a therapeutic candidate for DN.

Biomarkers of bipolar disorder based on metabolomics: A systematic review

Bipolar disorder (BD) is a severe affective disorder characterized by recurrent episodes of depression or mania/hypomania, which significantly impair cognitive function, life skills, and social abilities of patients. There is little understanding of the neurobiological mechanisms of BD. The diagnosis of BD is primarily based on clinical assessment and psychiatric examination, highlighting the urgent need for objective markers to facilitate the diagnosis of BD. Metabolomics can be used as a diagnostic tool for disease identification and evaluation. This study summarized the altered metabolites in BD and analyzed aberrant metabolic pathways, which might contribute to the diagnosis of BD. Search of PubMed and Web of science for human BD studies related to metabolism to identify articles published up to November 19, 2022 yielded 987 articles. After screening and applying the inclusion and exclusion criteria, 16 untargeted and 11 targeted metabolomics studies were included. Pathway analysis of the potential differential biometabolic markers was performed using the Kyoto encyclopedia of genes and genomes (KEGG). There were 72 upregulated and 134 downregulated biomarkers in the untargeted metabolomics studies using blood samples. Untargeted metabolomics studies utilizing urine specimens revealed the presence of 78 upregulated and 54 downregulated metabolites. The targeted metabolomics studies revealed abnormalities in the metabolism of glutamate and tryptophan. Enrichment analysis revealed that the differential metabolic pathways were mainly involved in the metabolism of glucose, amino acid and fatty acid. These findings suggested that certain metabolic biomarkers or metabolic biomarker panels might serve as a reference for the diagnosis of BD.

Current data processing methods and reporting standards for untargeted analysis of volatile organic compounds using direct mass spectrometry: a systematic review

INTRODUCTION

Untargeted direct mass spectrometric analysis of volatile organic compounds has many potential applications across fields such as healthcare and food safety. However, robust data processing protocols must be employed to ensure that research is replicable and practical applications can be realised. User-friendly data processing and statistical tools are becoming increasingly available; however, the use of these tools have neither been analysed, nor are they necessarily suited for every data type.

OBJECTIVES

This review aims to analyse data processing and analytic workflows currently in use and examine whether methodological reporting is sufficient to enable replication.

METHODS

Studies identified from Web of Science and Scopus databases were systematically examined against the inclusion criteria. The experimental, data processing, and data analysis workflows were reviewed for the relevant studies.

RESULTS

From 459 studies identified from the databases, a total of 110 met the inclusion criteria. Very few papers provided enough detail to allow all aspects of the methodology to be replicated accurately, with only three meeting previous guidelines for reporting experimental methods. A wide range of data processing methods were used, with only eight papers (7.3%) employing a largely similar workflow where direct comparability was achievable.

CONCLUSIONS

Standardised workflows and reporting systems need to be developed to ensure research in this area is replicable, comparable, and held to a high standard. Thus, allowing the wide-ranging potential applications to be realised.

Metabolome evidence of CKDu risks after chronic exposure to simulated Sri Lanka drinking water in zebrafish

It is still a serious public health issue that chronic kidney disease of uncertain etiology (CKDu) in Sri Lanka poses challenges in identification, prevention, and treatment. What environmental factors in drinking water cause kidney damage remains unclear. This study aimed to investigate the risks of various environmental factors that may induce CKDu, including water hardness, fluoride (HF), heavy metals (HM), microcystin-LR (MC-LR), and their combined exposure (HFMM). The research focused on comprehensive metabolome analysis, and correlation with transcriptomic and gut microbiota changes. Results revealed that chronic exposure led to kidney damage and pancreatic toxicity in adult zebrafish. Metabolomics profiling showed significant alterations in biochemical processes, with enriched metabolic pathways of oxidative phosphorylation, folate biosynthesis, arachidonic acid metabolism, FoxO signaling pathway, lysosome, pyruvate metabolism, and purine metabolism. The network analysis revealed significant changes in metabolites associated with renal function and diseases, including 20-Hydroxy-LTE4, PS(18:0/22:2(13Z,16Z)), Neuromedin N, 20-Oxo-Leukotriene E4, and phenol sulfate, which are involved in the fatty acyls and glycerophospholipids class. These metabolites were closely associated with the disrupted gut bacteria of g_ZOR0006, g_Pseudomonas, g_Tsukamurella, g_Cetobacterium, g_Flavobacterium, which belonged to dominant phyla of Firmicutes and Proteobacteria, etc., and differentially expressed genes (DEGs) such as egln3, ca2, jun, slc2a1b, and gls2b in zebrafish. Exploratory omics analyses revealed the shared significantly changed pathways in transcriptome and metabolome like calcium signaling and necroptosis, suggesting potential biomarkers for assessing kidney disease.

Development of Serum Lactate Level-Based Nomograms for Predicting Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients

Purpose

To establish nomograms integrating serum lactate levels and traditional risk factors for predicting diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM) patients.

Patients and methods

A total of 570 T2DM patients and 100 healthy subjects were enrolled. T2DM patients were categorized into normal and high lactate groups. Univariate and multivariate logistic regression analyses were employed to identify independent predictors for DKD. Then, nomograms for predicting DKD were established, and the model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration, and decision curve analysis (DCA).

Results

T2DM patients exhibited higher lactate levels compared to those in healthy subjects. Glucose, platelet, uric acid, creatinine, and hypertension were independent factors for DKD in T2DM patients with normal lactate levels, while diabetes duration, creatinine, total cholesterol, and hypertension were indicators in high lactate levels group (P<0.05). The AUC values were 0.834 (95% CI, 0.776 to 0.891) and 0.741 (95% CI, 0.688 to 0.795) for nomograms in both normal lactate and high lactate groups, respectively. The calibration curve demonstrated excellent agreement of fit. Furthermore, the DCA revealed that the threshold probability and highest Net Yield were 17-99% and 0.36, and 24-99% and 0.24 for the models in normal lactate and high lactate groups, respectively.

Conclusion

The serum lactate level-based nomogram models, combined with traditional risk factors, offer an effective tool for predicting DKD probability in T2DM patients. This approach holds promise for early risk assessment and tailored intervention strategies.

Current updates on metabolites and its interlinked pathways as biomarkers for diabetic kidney disease: A systematic review

Diabetic kidney disease (DKD) is a major microvascular complication of diabetes mellitus (DM) that poses a serious risk as it can lead to end-stage renal disease (ESRD). DKD is linked to changes in the diversity, composition, and functionality of the microbiota present in the gastrointestinal tract. The interplay between the gut microbiota and the host organism is primarily facilitated by metabolites generated by microbial metabolic processes from both dietary substrates and endogenous host compounds. The production of numerous metabolites by the gut microbiota is a crucial factor in the pathogenesis of DKD. However, a comprehensive understanding of the precise mechanisms by which gut microbiota and its metabolites contribute to the onset and progression of DKD remains incomplete. This review will provide a summary of the current scenario of metabolites in DKD and the impact of these metabolites on DKD progression. We will discuss in detail the primary and gut-derived metabolites in DKD, and the mechanisms of the metabolites involved in DKD progression. Further, we will address the importance of metabolomics in helping identify potential DKD markers. Furthermore, the possible therapeutic interventions and research gaps will be highlighted.

Dihydroxyacetone phosphate accumulation leads to podocyte pyroptosis in diabetic kidney disease

Diabetic kidney disease (DKD) can lead to accumulation of glucose upstream metabolites due to dysfunctional glycolysis. But the effects of accumulated glycolysis metabolites on podocytes in DKD remain unknown. The present study examined the effect of dihydroxyacetone phosphate (DHAP) on high glucose induced podocyte pyroptosis. By metabolomics, levels of DHAP, GAP, glucose-6-phosphate and fructose 1, 6-bisphosphate were significantly increased in glomeruli of db/db mice. Furthermore, the expression of LDHA and PKM2 were decreased. mRNA sequencing showed upregulation of pyroptosis-related genes (Nlrp3, Casp1, etc.). Targeted metabolomics demonstrated higher level of DHAP in HG-treated podocytes. In vitro, ALDOB expression in HG-treated podocytes was significantly increased. siALDOB-transfected podocytes showed less DHAP level, mTORC1 activation, reactive oxygen species (ROS) production, and pyroptosis, while overexpression of ALDOB had opposite effects. Furthermore, GAP had no effect on mTORC1 activation, and mTORC1 inhibitor rapamycin alleviated ROS production and pyroptosis in HG-stimulated podocytes. Our findings demonstrate that DHAP represents a critical metabolic product for pyroptosis in HG-stimulated podocytes through regulation of mTORC1 pathway. In addition, the results provide evidence that podocyte injury in DKD may be treated by reducing DHAP.

Associations between dietary patterns and renal impairment in individuals with diabetes: a cross-sectional study

BACKGROUND

A variety of chronic diseases are affected by diet. To our knowledge, few studies have investigated the relationship between dietary patterns and renal impairment in individuals with diabetes within an Asian population. This study aimed to assess the relationship between renal impairment and dietary patterns in individuals with diabetes within a Chinese population.

METHODS

In this cross-sectional survey, we analysed data on 1522 participants with diabetes aged 18 years or older who took part in the China National Diabetic Chronic Complications Study. We utilised the Chinese Diabetes Complications Questionnaire, including the semiquantitative food frequency questionnaire (SQFFQ). We identified three dietary patterns using factor analysis: Chinese traditional, healthy and plant-based dietary patterns, and these dietary patterns were used to classify participants into four groups based on the quartiles of their scores. A decrease in the estimated glomerular filtration rate (eGFR; <60 mL/min/1.73 m2 ) and an increase in the albumin-to-creatinine ratio (ACR; ≥3 mg/mmol) were used as indicators of renal impairment. Binary logistic regression models were used to estimate the odds ratio (OR) of the highest quartile (Q4: high intake levels of each dietary pattern) for renal impairment compared to the lowest quartile (Q1: low intake levels of each dietary pattern).

RESULTS

Among the 1522 participants, there was a 5.5% prevalence of low eGFR, with prevalence rates of 5.2% in men and 5.9% in women, yet the prevalence of albuminuria was as high as 47.9%. After adjusting for confounders, participants in Q4 of the plant-based dietary pattern had a smaller OR for renal impairment than those in Q1.

CONCLUSIONS

Our findings demonstrated that a plant-based dietary pattern is associated with a reduced risk of renal impairment in a population with diabetes.

A simple, rapid and sensitive HILIC LC-MS/MS method for simultaneous determination of 16 purine metabolites in plasma and urine

Purine intermediates play important roles in physiological function and participate in the kidney disorders, while a targeted quantification of the metabolic alterations in the purine metabolism in acute kidney injury (AKI) individuals has not been conducted. In the study, a novel, rapid and sensitive LC-MS method for simultaneous quantification of 16 purine metabolites was developed using hydrophilic interaction separation mode in human plasma and urine. The developed method was validated by using charcoal-stripped plasma and urine as blank matrix. The results showed that the method was good linear (R2 > 0.99) and the lower limit of quantification (LLOQ) ranged from 0.833 ng/mL to 800 ng/mL. The recovery and matrix effect were repeatable and stable. The intraday precision ranged from 0.7% to 12.7%, while the inter-day precision ranged from 1.6% to 18.5%. Most analytes were stable in the autosampler and could subject three freeze-thaw cycles. The method provided a wider coverage of purine metabolites and completed good separation of interfering compounds of nucleosides, deoxynucleosides and their corresponding nucleobases without derivatization, which was time-saving and labor-saving for the large-scale analysis. Furthermore, the method was successfully applied to plasma and urine samples of hospitalized patients without and with AKI. The results showed certain purine intermediates were up-regulated in plasma and down-regulated in urine of AKI inpatients, indicating that AKI stress may associate with inflammatory responses. The novel method can facilitate the quantitative analysis of purine metabolites in biological fluids, and exhibit great prospects in providing more information on the pathogenesis of AKI.

Quantitative profiling of carboxylic compounds by gas chromatography-mass spectrometry for revealing biomarkers of diabetic kidney disease

Diabetic kidney disease (DKD), a common microvascular complication of diabetes, currently lacks specific diagnostic indicators and therapeutic targets, resulting in miss of early intervention. To profile metabolic conditions in complex and precious biological samples and screen potential biomarkers for DKD diagnosis and prognosis, a rapid, convenient and reliable quantification method for carboxyl compounds by gas chromatography-mass spectrometry (GC-MS) was established with isobutyl chloroformate derivatization. The derivatives were extracted with hexane, injected into GC-MS and quantified with selected ion monitoring mode. This method showed excellent linearity(R2 > 0.99), good recoveries (81.1%-115.5%), good repeatability (RSD < 20%) and sensitivity (LODs: 0.20-499.90 pg, LOQs: 2.00-1007.00 pg). Among the 37 carboxyl compounds analyzed, 12 metabolites in short-chain fatty acids (SCFAs) metabolism pathway and amino acid metabolism pathway were linked with DKD development and among them, 6 metabolites were associated with both development and prognosis of DKD in mice. In conclusion, a reliable, convenient and sensitive method based on isobutyl chloroformate derivatization and GC-MS analysis is established and successfully applied to quantify 37 carboxyl compounds in biological samples of mice and 12 potential biomarkers for DKD development and prognosis are screened.

GLP-1 Receptor Agonist Improves Mitochondrial Energy Status and Attenuates Nephrotoxicity In Vivo and In Vitro

High-sugar and high-fat diets cause significant harm to health, especially via metabolic diseases. In this study, the protective effects of the antidiabetic drug exenatide (synthetic exendin-4), a glucagon-like peptide 1 (GLP-1) receptor agonist, on high-fat and high-glucose (HFHG)-induced renal injuries were investigated in vivo and in vitro. In vivo and in vitro renal injury models were established. Metabolomic analysis based on 1H-nuclear magnetic resonance was performed to examine whether exenatide treatment exerts a protective effect against kidney injury in diabetic rats and to explore its potential molecular mechanism. In vivo, 8 weeks of exenatide treatment resulted in the regulation of most metabolites in the diabetes mellitus group. In vitro results showed that exendin-4 restored the mitochondrial functions of mesangial cells, which were perturbed by HFHG. The effects of exendin-4 included the improved antioxidant capacity of mesangial cells, increased the Bcl-2/Bax ratio, and reduced protein expression of cyt-c and caspase-3 activation. In addition, exendin-4 restored mesangial cell energy metabolism by increasing succinate dehydrogenase and phosphofructokinase activities and glucose consumption while inhibiting pyruvate dehydrogenase E1 activity. In conclusion, GLP-1 agonists improve renal injury in diabetic rats by ameliorating metabolic disorders. This mechanism could be partially related to mitochondrial functions and energy metabolism.

Diagnostic challenges of diabetic kidney disease

Diabetic kidney disease (DKD) is one of the most common microvascular complications of both type 1 and type 2 diabetes and the most common cause of the end-stage renal disease (ESRD). It has been evidenced that targeted interventions at an early stage of DKD can efficiently prevent or delay the progression of kidney failure and improve patient outcomes. Therefore, regular screening for DKD has become one of the fundamental principles of diabetes care. Long-established biomarkers such as serum-creatinine-based estimates of glomerular filtration rate and albuminuria are currently the cornerstone of diagnosis and risk stratification in routine clinical practice. However, their immanent biological limitations and analytical variations may influence the clinical interpretation of the results. Recently proposed new predictive equations without the variable of race, together with the evidence on better accuracy of combined serum creatinine and cystatin C equations, and both race- and sex-free cystatin C-based equation, have enabled an improvement in the detection of DKD, but also require the harmonization of the recommended laboratory tests, wider availability of cystatin C testing and specific approach in various populations. Considering the complex pathophysiology of DKD, particularly in type 2 diabetes, a panel of biomarkers is needed to classify patients in terms of the rate of disease progression and/or response to specific interventions. With a personalized approach to diagnosis and treatment, in the future, it will be possible to respond to DKD better and enable improved outcomes for numerous patients worldwide.