Associations between local acidosis induced by renal LDHA and renal fibrosis and mitochondrial abnormalities in patients with diabetic kidney disease

Sulforaphane reverses the enhanced NSCLC metastasis by regulating the miR-7-5p/c-Myc/LDHA axis in the acidic tumor microenvironment

BACKGROUND

The presence of distant metastasis at the time of initial diagnosis is a prevalent issue in non-small cell lung cancer (NSCLC), affecting around 30-40 % of the patients. Acidic tumor microenvironment (TME) provides favorable conditions that increase the invasiveness and aggressiveness of NSCLC. The activity of the glycolytic enzyme lactate dehydrogenase (LDHA) increases intracellular lactate accumulation, which creates an acidic TME. However, it is not yet known whether LDHA is involved in enhancing the metastatic potential of NSCLC and if LDHA is a druggable therapeutic target for NSCLC.

PURPOSE

We aimed to investigate the molecular mechanisms underlying the enhanced NSCLC metastasis in acidic TME, and to explore whether sulforaphane (SFN), an active compound in Raphani Semen, can serve as a LDHA inhibitor to inhibit NSCLC metastasis in the acidic TME.

METHODS

To mimic the acidic TME, NSCLC cells were cultured in acidic medium (pH 6.6), normal medium (pH 7.4) served as control. Western blotting, bioinformatic analysis, luciferase assay and rescue experiments were used to explore the mechanism and investigate the anti-metastatic effect of SFN both in vitro and in vivo.

RESULTS

Acidic environment increases the expression of LDHA which in turn increases the production of lactic acid that contributes to the acidity of TME. Interestingly, elevated LDHA expression results from increased c-Myc expression, which transactivates LDHA. c-Myc expression is directly regulated by miR-7-5p. In vitro study shows that overexpression of miR-7-5p reverses the acidic pH-enhanced c-Myc and LDHA expressions and also abolishes the enhanced NSCLC cell migration. More importantly, SFN significantly inhibits NSCLC growth and metastasis by reducing lactate production via the miR-7-5p/c-Myc/LDHA axis. Besides, it also regulates the expressions of monocarboxylate transporter 1 (MCT1) and MCT4 that transport lactate across cell membrane.

CONCLUSIONS

The miR-7-5p/c-Myc/LDHA axis is involved in the enhanced NSCLC metastasis in the acidic TME. SFN, a novel LDHA inhibitor, reduces lactate production by targeting the miR-7-5p/c-Myc/LDHA axis, and hence inhibits NSCLC metastasis. Our findings not only delineate a novel mechanism, but also support the clinical translation of SFN as a novel therapeutic agent for treating metastatic NSCLC.

The glycolytic enzyme PFKFB3 drives kidney fibrosis through promoting histone lactylation-mediated NF-κB family activation

Persistently elevated glycolysis in kidney has been demonstrated to promote chronic kidney disease (CKD). However, the underlying mechanism remains largely unclear. Here, we observed that 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3), a key glycolytic enzyme, was remarkably induced in kidney proximal tubular cells (PTCs) following ischemia-reperfusion injury (IRI) in mice, as well as in multiple etiologies of patients with CKD. PFKFB3 expression was positively correlated with the severity of kidney fibrosis. Moreover, patients with CKD and mice exhibited increased urinary lactate/creatine levels and kidney lactate, respectively. PTC-specific deletion of PFKFB3 significantly reduced kidney lactate levels, mitigated inflammation and fibrosis, and preserved kidney function in the IRI mouse model. Similar protective effects were observed in mice with heterozygous deficiency of PFKFB3 or those treated with a PFKFB3 inhibitor. Mechanistically, lactate derived from PFKFB3-mediated tubular glycolytic reprogramming markedly enhanced histone lactylation, particularly H4K12la, which was enriched at the promoter of NF-κB signaling genes like Ikbkb, Rela, and Relb, activating their transcription and facilitating the inflammatory response. Further, PTC-specific deletion of PFKFB3 inhibited the activation of IKKβ, I κ B α, and p65 in the IRI kidneys. Moreover, increased H4K12la levels were positively correlated with kidney inflammation and fibrosis in patients with CKD. These findings suggest that tubular PFKFB3 may play a dual role in enhancing NF-κB signaling by promoting both H4K12la-mediated gene transcription and its activation. Thus, targeting the PFKFB3-mediated NF-κB signaling pathway in kidney tubular cells could be a novel strategy for CKD therapy.

Zinc Deficiency Causes Glomerulosclerosis and Renal Interstitial Fibrosis Through Oxidative Stress and Increased Lactate Metabolism in Rats

Chronic kidney disease (CKD) is a highly prevalent condition characterized by renal fibrosis as its ultimate manifestation. Zinc deficiency is closely associated with CKD, evidenced by its link to renal fibrosis. Recently, local lactic acidosis has been demonstrated to promote renal fibrosis. Under zinc-deficient conditions, mitochondrial function is compromised and abnormal lactate metabolism might be induced potentially. However, it remains unclear whether zinc deficiency leads to renal fibrosis through local lactic acidosis. Zinc deficiency rat models were successfully established by feeding zinc-deficient diet. Western blot, qPCR, IHC, and other experiments were employed to investigate the key markers and molecular mechanisms of glomerulosclerosis and renal interstitial fibrosis. Our results indicate that zinc deficiency reduces specific markers of podocytes (podocalyxin, WT1, and nephrin) and activates the Wnt3a/β-catenin pathway, a key pathway in podocyte injury. Concurrently, glomerulosclerosis is indicated by increased urinary microalbumin and serum creatinine levels along with histological alteration observed through PAS and Masson staining in zinc-deficient rats. Furthermore, various degrees of upregulation for several markers of interstitial fibrosis including α-SMA, FN1 and collagen III are also revealed. These findings were further confirmed by Masson staining and IHC. Additionally, alterations in four markers in the EMT process, N-cadherin, E-cadherin, Vimentin, and snail, were consistent with expectations. We then confirmed the activation of the non-canonical TGF-β1 pathway known as the PI3K/AKT/mTOR pathway. An elevation in renal ROS levels accompanied by increased mitochondrial marker cytochrome C expression as well as an elevated NADH/NAD + ratio is also observed within the kidneys. Furthermore, the activity of both MMP/TIMP system and fibrinolytic system was abnormally enhanced under zinc deficiency conditions. Finally, we find zinc supplementation could significantly ameliorate relevant pathological alterations induced by zinc deficiency. These results collectively point that zinc deficiency causes podocyte damage ultimately resulting in glomerulosclerosis via accumulation of ROS and induces interstitial fibrosis via lactic acidosis.

ACSF2 and lysine lactylation contribute to renal tubule injury in diabetes

AIMS

Lactate accumulation is reported to be a biomarker for diabetic nephropathy progression. Lactate drives lysine lactylation, a newly discovered post-translational modification that is involved in the pathogenesis of cancers and metabolic and inflammatory disease. Here, we aimed to determine whether lysine lactylation is involved in the pathogenesis of diabetic nephropathy.

METHODS

Renal biopsy samples from individuals with diabetic nephropathy (n=22) and control samples from individuals without diabetes and kidney disease (n=9) were obtained from the First Affiliated Hospital of Zhengzhou University for immunohistochemical staining. In addition, we carried out global lactylome profiling of kidney tissues from db/m and db/db mice using LC-MS/MS. Furthermore, we assessed the role of lysine lactylation and acyl-CoA synthetase family member 2 (ACSF2) in mitochondrial function in human proximal tubular epithelial cells (HK-2).

RESULTS

The expression level of lysine lactylation was significantly increased in the kidneys of individuals with diabetes as well as in kidneys from db/db mice. Integrative lactylome analysis of the kidneys of db/db and db/m mice identified 165 upregulated proteins and 17 downregulated proteins, with an increase in 356 lysine lactylation sites and a decrease in 22 lysine lactylation sites decreased. Subcellular localisation analysis revealed that most lactylated proteins were found in the mitochondria (115 proteins, 269 sites). We further found that lactylation of the K182 site in ACSF2 contributes to mitochondrial dysfunction. Finally, the expression of ACSF2 was notably increased in the kidneys of db/db mice and individuals with diabetic nephropathy.

CONCLUSIONS

Our study strongly suggests that lysine lactylation and ACSF2 are mediators of mitochondrial dysfunction and may contribute to the progression of diabetic nephropathy.

DATA AVAILABILITY

The LC-MS/MS proteomics data have been deposited in the ProteomeXchange Consortium database ( https://proteomecentral.proteomexchange.org ) via the iProX partner repository with the dataset identifier PXD050070.

Roles of Mitochondrial Dysfunction in Diabetic Kidney Disease: New Perspectives from Mechanism to Therapy

Diabetic kidney disease (DKD) is a common microvascular complication of diabetes and the main cause of end-stage renal disease around the world. Mitochondria are the main organelles responsible for producing energy in cells and are closely involved in maintaining normal organ function. Studies have found that a high-sugar environment can damage glomeruli and tubules and trigger mitochondrial dysfunction. Meanwhile, animal experiments have shown that DKD symptoms are alleviated when mitochondrial damage is targeted, suggesting that mitochondrial dysfunction is inextricably linked to the development of DKD. This article describes the mechanisms of mitochondrial dysfunction and the progression and onset of DKD. The relationship between DKD and mitochondrial dysfunction is discussed. At the same time, the progress of DKD treatment targeting mitochondrial dysfunction is summarized. We hope to provide new insights into the progress and treatment of DKD.

Glycolytic lactate in diabetic kidney disease

Lactate elevation is a well-characterized biomarker of mitochondrial dysfunction, but its role in diabetic kidney disease (DKD) is not well defined. Urine lactate was measured in patients with type 2 diabetes (T2D) in 3 cohorts (HUNT3, SMART2D, CRIC). Urine and plasma lactate were measured during euglycemic and hyperglycemic clamps in participants with type 1 diabetes (T1D). Patients in the HUNT3 cohort with DKD had elevated urine lactate levels compared with age- and sex-matched controls. In patients in the SMART2D and CRIC cohorts, the third tertile of urine lactate/creatinine was associated with more rapid estimated glomerular filtration rate decline, relative to first tertile. Patients with T1D demonstrated a strong association between glucose and lactate in both plasma and urine. Glucose-stimulated lactate likely derives in part from proximal tubular cells, since lactate production was attenuated with sodium-glucose cotransporter-2 (SGLT2) inhibition in kidney sections and in SGLT2-deficient mice. Several glycolytic genes were elevated in human diabetic proximal tubules. Lactate levels above 2.5 mM potently inhibited mitochondrial oxidative phosphorylation in human proximal tubule (HK2) cells. We conclude that increased lactate production under diabetic conditions can contribute to mitochondrial dysfunction and become a feed-forward component to DKD pathogenesis.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Association between lactate dehydrogenase and the risk of diabetic kidney disease in patients with type 2 diabetes

Objective

This study aims to investigate the association between lactate dehydrogenase (LDH) and the risk of diabetic kidney disease (DKD) in patients with type 2 diabetes (T2D).

Methods

The study enrolled patients with diagnosis of T2D between 2009 and 2018 from the National Nutrition and Health Examination Survey (NHANES) database. Demographic information, laboratory test, and diagnostic data were collected. Restricted cubic spline (RCS) plots were used to assess the dose-effect relationship between LDH levels and the risk of DKD in patients with T2D. Based on LDH levels, individuals were divided into higher and lower groups using dichotomy, and multivariate logistic regression analysis was conducted to explore the relationship between different LDH levels and the risk of DKD in T2D patients. Stratified analysis was performed to assess the consistency of the result.

Results

A total of 4888 patients were included in the study, with 2976 (60.9%) patients without DKD and 1912 (39.1%) patients with DKD. RCS plots showed that the risk of DKD increased with increasing LDH levels. Multifactorial logistic regression analysis revealed that T2D patients with higher LDH levels had a 45% increased risk of DKD compared to those with lower LDH levels (OR=1.45; 95% CI: 1.11-1.89). Furthermore, each standard deviation increase in LDH level was associated with a 24% increase in DKD incidence among T2D patients (OR=1.24; 95% CI: 1.07-1.44). Stratified analysis consistently supported these findings.

Conclusions

LDH can serve as a valuable biomarker for screening DKD in patients with T2D.

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.

Identification and analysis of diverse cell death patterns in diabetic kidney disease using microarray-based transcriptome profiling and single-nucleus RNA sequencing

BACKGROUND

Diabetic kidney disease (DKD) is the most lethal complication of diabetes. Diverse programmed cell death (PCD) has emerged as a crucial disease phenotype that has the potential to serve as an indicator of renal function decline and can be used as a target for researching drugs for DKD.

METHODS

Microarray-based transcriptome profiling and single-nucleus transcriptome sequencing (snRNA-seq) related to DKD were retrieved from the Gene Expression Omnibus (GEO) database. 13 PCD-related genes (including alkaliptosis, apoptosis, autophagy-dependent cell death, cuproptosis, disulfidptosis, entotic cell death, ferroptosis, lysosome-dependent cell death, necroptosis, netotic cell death, oxeiptosis, parthanatos, and pyroptosis) were obtained from various public databases and reviews. The gene set variation analysis (GSVA) analysis was used to explore the pathway activity of these 13 PCDs in DKD, and the pathway activity of these PCDs in different renal cells was studied based on DKD-related snRNA-seq data. To identify the core PCDs that play a significant role in DKD, we analyzed the relationships between different types of PCD and immune infiltration, fibrosis-related gene expression levels, glomerular filtration rate (GFR), and diagnostic efficiency in DKD. Using the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm, we screened for core death genes among the core PCDs and constructed a cell death-related signature (CDS) risk score based on the Least Absolute Shrinkage and Selection Operator (LASSO). Finally, we validated the predictive performance of the CDS risk score in an independent validation set.

RESULTS

We identified 4 core PCD pathways, namely entotic cell death, apoptosis, necroptosis, and pyroptosis in DKD, and further applied the WGCNA algorithm to screen 4 core death genes (CASP1, CYBB, PLA2G4A, and CTSS) and constructed a CDS risk score based on these genes. The CDS risk score demonstrated high diagnostic efficiency for DKD patients, and those with higher scores had higher levels of immune cell infiltration and poorer GFR.

CONCLUSION

Our study sheds light on the fact that multiple PCDs contribute to the progression of DKD, highlighting potential therapeutic targets for treating this disease.

Diabetic Nephropathy: Significance of Determining Oxidative Stress and Opportunities for Antioxidant Therapies

Diabetes mellitus (DM) belongs to the category of socially significant diseases with epidemic rates of increases in prevalence. Diabetic nephropathy (DN) is a specific kind of kidney damage that occurs in 40% of patients with DM and is considered a serious complication of DM. Most modern methods for treatments aimed at slowing down the progression of DN have side effects and do not produce unambiguous positive results in the long term. This fact has encouraged researchers to search for additional or alternative treatment methods. Hyperglycemia has a negative effect on renal structures due to a number of factors, including the activation of the polyol and hexosamine glucose metabolism pathways, the activation of the renin-angiotensin-aldosterone and sympathetic nervous systems, the accumulation of advanced glycation end products and increases in the insulin resistance and endothelial dysfunction of tissues. The above mechanisms cause the development of oxidative stress (OS) reactions and mitochondrial dysfunction, which in turn contribute to the development and progression of DN. Modern antioxidant therapies for DN involve various phytochemicals (food antioxidants, resveratrol, curcumin, alpha-lipoic acid preparations, etc.), which are widely used not only for the treatment of diabetes but also other systemic diseases. It has also been suggested that therapeutic approaches that target the source of reactive oxygen species in DN may have certain advantages in terms of nephroprotection from OS. This review describes the significance of studies on OS biomarkers in the pathogenesis of DN and analyzes various approaches to reducing the intensity of OS in the prevention and treatment of DN.

Epigenetic modification in diabetic kidney disease

Diabetic kidney disease (DKD) is a common microangiopathy in diabetic patients and the main cause of death in diabetic patients. The main manifestations of DKD are proteinuria and decreased renal filtration capacity. The glomerular filtration rate and urinary albumin level are two of the most important hallmarks of the progression of DKD. The classical treatment of DKD is controlling blood glucose and blood pressure. However, the commonly used clinical therapeutic strategies and the existing biomarkers only partially slow the progression of DKD and roughly predict disease progression. Therefore, novel therapeutic methods, targets and biomarkers are urgently needed to meet clinical requirements. In recent years, increasing attention has been given to the role of epigenetic modification in the pathogenesis of DKD. Epigenetic variation mainly includes DNA methylation, histone modification and changes in the noncoding RNA expression profile, which are deeply involved in DKD-related inflammation, oxidative stress, hemodynamics, and the activation of abnormal signaling pathways. Since DKD is reversible at certain disease stages, it is valuable to identify abnormal epigenetic modifications as early diagnosis and treatment targets to prevent the progression of end-stage renal disease (ESRD). Because the current understanding of the epigenetic mechanism of DKD is not comprehensive, the purpose of this review is to summarize the role of epigenetic modification in the occurrence and development of DKD and evaluate the value of epigenetic therapies in DKD.

Targeting immunometabolism during cardiorenal injury: roles of conventional and alternative macrophage metabolic fuels

Macrophages play critical roles in mediating and resolving tissue injury as well as tissue remodeling during cardiorenal disease. Altered immunometabolism, particularly macrophage metabolism, is a critical underlying mechanism of immune dysfunction and inflammation, particularly in individuals with underlying metabolic abnormalities. In this review, we discuss the critical roles of macrophages in cardiac and renal injury and disease. We also highlight the roles of macrophage metabolism and discuss metabolic abnormalities, such as obesity and diabetes, which may impair normal macrophage metabolism and thus predispose individuals to cardiorenal inflammation and injury. As the roles of macrophage glucose and fatty acid metabolism have been extensively discussed elsewhere, we focus on the roles of alternative fuels, such as lactate and ketones, which play underappreciated roles during cardiac and renal injury and heavily influence macrophage phenotypes.

Mutual regulation of lactate dehydrogenase and redox robustness

The nature of redox is electron transfer; in this way, energy metabolism brings redox stress. Lactate production is associated with NAD regeneration, which is now recognized to play a role in maintaining redox homeostasis. The cellular lactate/pyruvate ratio could be described as a proxy for the cytosolic NADH/NAD ratio, meaning lactate metabolism is the key to redox regulation. Here, we review the role of lactate dehydrogenases in cellular redox regulation, which play the role of the direct regulator of lactate–pyruvate transforming. Lactate dehydrogenases (LDHs) are found in almost all animal tissues; while LDHA catalyzed pyruvate to lactate, LDHB catalyzed the reverse reaction . LDH enzyme activity affects cell oxidative stress with NAD/NADH regulation, especially LDHA recently is also thought as an ROS sensor. We focus on the mutual regulation of LDHA and redox robustness. ROS accumulation regulates the transcription of LDHA. Conversely, diverse post-translational modifications of LDHA, such as phosphorylation and ubiquitination, play important roles in enzyme activity on ROS elimination, emphasizing the potential role of the ROS sensor and regulator of LDHA.

Advances in energy metabolism in renal fibrosis

Renal fibrosis is a common pathway toward chronic kidney disease (CKD) and is the main pathological predecessor for end-stage renal disease; thus, preventing progressive CKD and renal fibrosis is essential to reducing their consequential morbidity and mortality. Emerging evidence has connected renal fibrosis to metabolic reprogramming; abnormalities in energy metabolism pathways, such as glycolysis, the tricarboxylic acid cycle, and lipid metabolism, are known to cause diseases of diverse etiologies. Cytokine interventions in affected metabolic pathways may significantly reduce the degree of fibrosis, highlighting therapeutic targets for drug development for renal fibrosis. Here, we discuss the relationship between glycolysis, lipid metabolism, mitochondrial and peroxisome dysfunction, and renal fibrosis in detail and propose that targeted therapies for specific metabolic pathways are expected to represent the next generation of treatments for renal fibrosis.