The link between diabetic retinal and renal microvasculopathy is associated with dyslipidemia and upregulated circulating level of cytokines

Serum metabolic profiling in diabetic kidney disease patients using ultra-high performance liquid chromatography-tandem mass spectrometry

Background

Diabetic kidney disease (DKD) remains one of the leading causes of end-stage renal failure. The currently available diagnostic and classification markers, such as the urinary albumin-to-creatinine ratio and estimated glomerular filtration rate, demonstrate inadequate precision in forecasting the onset and progression of DKD. This study aims to investigate the serum metabolic profile of patients with DKD, with the objective of identifying reliable biomarkers that can enhance the prediction of the transition from diabetes mellitus (DM) to DKD and distinguishing DKD from nondiabetic kidney disease (NDKD).

Methods

Untargeted metabolomic analysis was performed on serum samples obtained from 53 DKD patients, 54 NDKD patients, 59 individuals diagnosed with simple diabetes mellitus (SDM), and 56 healthy controls utilizing ultra-high performance liquid chromatography-tandem mass spectrometry. Differential metabolites among the groups were identified, metabolic pathways were investigated, and the diagnostic efficacy of selected metabolites was evaluated.

Results

The metabolic enrichment pathways shared between DKD and NDKD encompassed glycerophospholipid metabolism, glycerolipid metabolism, and tryptophan metabolism. In contrast, pyrimidine metabolism and arginine biosynthesis were uniquely enriched in DKD. Compared to the NDKD group, significantly elevated levels of phosphatidylglycerol (PG, 14:0) and D-Maltose were observed in DKD patients. Additionally, in comparison to the SDM group, the DKD group exhibited significant increases in lysophosphatidic acid (LPA, 16:3), LPA (18:5), LPA (22:5), phosphatidic acid (PA, 18:3), PG (26:4), L-Glutamine, Uridine, Cytidine, Formyl-N-acetyl-5-methoxykynurenamine, 2-Oxoadipate, Thymidine, L-Citrulline, and 5-Hydroxy-L-tryptophan, while PG (28:4) levels were markedly reduced. Among these, Uridine, Cytidine, Thymidine, and L-Citrulline were associated with pyrimidine metabolism, whereas L-Glutamine and L-Citrulline participated in the arginine biosynthesis pathway. Furthermore, the differential metabolites exhibited varying degrees of correlation with renal function indicators in DKD patients.

Conclusions

PG (14:0) and D-Maltose may help distinguish DKD from NDKD, while L-Glutamine, Uridine, Cytidine, Thymidine, and L-Citrulline are linked to the progression from DM to DKD. Larger studies are needed to validate these findings and assess their diagnostic and causal significance.

Systemic immune indicators for predicting renal damage in newly diagnosed type 1 diabetic children

BACKGROUND

Early kidney damage is a significant complication in children with newly diagnosed type 1 diabetes mellitus (T1DM). Systemic inflammation plays a key role in the development of diabetic nephropathy. Several inflammatory markers, including the systemic immune inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR), have been proposed as potential indicators of diabetic complications.

AIM

To investigate the association between SII, NLR, PLR, and early kidney damage in newly diagnosed T1DM children without pre-existing albuminuria, assessing their utility as predictive biomarkers.

METHODS

A longitudinal cohort study was conducted on 102 children aged 3-18 years with newly diagnosed T1DM [baseline urinary albumin-to-creatinine ratio (UACR) < 30 mg/g] recruited between January 2020 and June 2023. Participants were followed biannually for up to three years. Demographic, clinical, and laboratory data, including inflammatory markers (SII, NLR, PLR), were collected at baseline and follow-up. Logistic regression and receiver operating characteristic analyses were used to evaluate the predictive utility of these markers for early kidney damage, defined as UACR ≥ 30 mg/g.

RESULTS

SII emerged as a significant independent predictor of early kidney damage [odds ratio = 1.002, 95% confidence interval (CI): 1.0008-1.0033, P = 0.0016], with an area under the curve of 0.719 (95%CI: 0.612-0.826, P < 0.001). Using an SII threshold of ≥ 624.015 achieved a sensitivity of 59.6% and specificity of 92%. Combining SII with NLR and PLR improved predictive accuracy (area under the curve = 0.787), with sensitivity and specificity of 63.5% and 96%, respectively. Correlation analyses revealed significant associations between SII, metabolic markers (triglycerides, glycated hemoglobin), and UACR.

CONCLUSION

SII is a reliable biomarker for early kidney damage in T1DM children, offering high specificity for identifying at-risk patients. Combining SII with NLR and PLR enhances diagnostic precision, supporting its integration into clinical practice. Longitudinal monitoring of these markers may facilitate early interventions to mitigate renal complications in pediatric T1DM.

Targeting lipid metabolic reprogramming to alleviate diabetic kidney disease: molecular insights and therapeutic strategies

Diabetic kidney disease (DKD) is one of the major complications of diabetes, and its pathological progression is closely associated with lipid metabolic reprogramming. Under diabetic conditions, renal cells undergo significant lipid metabolic abnormalities, including increased lipid uptake, impaired fatty acid oxidation, disrupted cholesterol efflux, and enhanced lipid catabolism, as adaptive responses to metabolic stress. These changes result in the accumulation of lipids such as free fatty acids, diacylglycerol, and ceramides, leading to lipotoxicity that triggers inflammation and fibrosis. Hypoxia in the DKD microenvironment suppresses fatty acid oxidation and promotes lipid synthesis through the HIF-1α pathway, while chronic inflammation exacerbates lipid metabolic disturbances via inflammatory cytokines, inflammasomes, and macrophage polarization. Targeting lipid metabolism represents a promising therapeutic strategy for alleviating DKD; however, further clinical translational studies are warranted to validate the efficacy and safety of these approaches.

Potential Association Between Atherogenic Coefficient, Prognostic Nutritional Index, and Various Obesity Indices in Diabetic Nephropathy

Background/Objectives: Type 2 diabetes mellitus (T2DM), is a rapidly growing global health concern, often accompanied by chronic kidney disease (CKD) and metabolic disturbances. Obesity-related indices, such as the visceral adiposity index (VAI) and body adiposity index (BAI), have been linked to cardiovascular and renal complications in diabetic patients. However, studies integrating both the atherogenic coefficient (AC) and prognostic nutritional index (PNI) for evaluating diabetic nephropathy (DN) remain limited. This study aimed to assess the associations of obesity-related indices with immunological and nutritional factors in patients with T2DM and prediabetes (PreDM). Methods: A retrospective, cross-sectional study was conducted over six months at a university clinical hospital in Dolj County, Romania. The study enrolled 268 newly diagnosed T2DM patients and 150 PreDM patients. Anthropometric parameters, laboratory tests, and demographic data were collected. AC and PNI were calculated using standard formulas, and statistical analyses were performed to determine their associations with metabolic and inflammatory markers. Results: Our study found that T2DM patients had significantly lower PNI values, indicating mild malnutrition, while PreDM patients maintained a normal nutritional status. AC was significantly higher in T2DM patients, correlating with lipid profile alterations and systemic inflammation. Obesity indices, particularly VAI, were significantly elevated in T2DM patients with higher AC values. Statistically significant differences in total cholesterol, low-density lipoprotein cholesterol (LDL-c), and triglycerides were observed between AC subgroups, reinforcing its role in cardiovascular risk assessment. Conclusions: The findings highlight the potential of AC and PNI as biomarkers for assessing nutritional, inflammatory, and lipemic status in diabetic patients. The significant associations between obesity-related indices, lipid profiles, and inflammation markers suggest that early assessment of these parameters may potentially aid in predicting diabetic complications. Further studies are needed to explore the clinical utility of AC and PNI in managing T2DM and CKD progression. Future research should investigate how the lipidic spectrum alters the progression of DN across various patient groups with diabetes and prediabetes.

Untargeted metabolomic and proteomic analysis implicates SIRT2 as a novel therapeutic target for diabetic nephropathy

Diabetic nephropathy (DN) is one of the major causes of end-stage renal disease. This study aimed to explore the internal relationship between metabolic processes and autoimmune responses in patients with DN via untargeted metabolomics and Olink proteomics. The serum of 10 patients who were diagnosed with DN and 10 healthy individuals via untargeted metabolomics and Olink proteomics. Animal models were used to validate the characterized genes. Correlation analysis of major differentially abundant metabolites and differentially expressed proteins revealed that SIRT2 might be a key hub linking energy metabolism and innate immune responses. KEGG enrichment analysis showed that HIF-1 signaling pathway and renal cell carcinoma pathway were co-enriched pathways in energy metabolism and inflammatory response. VEGFA plays a vital role in these two signaling pathways. The ability of SIRT2 to regulate VEGFA expression has been demonstrated. In vivo experiments revealed that SIRT2, VEGFA, and HIF-1α were highly expressed in the kidneys of mice with diabetic nephropathy. In conclusion, our study combines metabolomics and proteomics to provide valuable insights into the synergistic roles of metabolic disorders and inflammatory responses in DN. The data suggest that SIRT2 may be a key target affecting these processes.

Association of Albumin-To-Creatinine Ratio With Diabetic Retinopathy Among US Adults (NHANES 2009-2016)

OBJECTIVE

This study investigates the relationship between the albumin-to-creatinine ratio and diabetic retinopathy (DR) in US adults using NHANES data from 2009 to 2016. This study assesses the predictive efficacy of the urinary serum albumin-to-creatinine ratio (UACR/SACR Ratio) against traditional biomarkers such as the serum albumin-to-creatinine ratio (SACR) and urinary albumin-to-creatinine ratio (UACR) for evaluating DR risk. Additionally, the study explores the potential of these biomarkers, both individually and in combination with HbA1c, for early detection and risk stratification of DR.

METHODS

This cross-sectional study analysed data from 2594 diabetic adults in the National Health and Nutrition Examination Survey (NHANES 2009-2016). Multivariate logistic regression models, adjusted for demographic (sex, age, race and education) and clinical factors (WBC, PLT, RDW, HbA1c, HBP and CHD), examined the associations between biomarkers and DR. Biomarkers were analysed both continuously and in quartiles to assess dose-response relationships. Receiver operating characteristic (ROC) curve analysis evaluated the predictive accuracy of individual biomarkers and combined models.

RESULTS

Elevated SACR levels were inversely related to DR risk, while UACR showed a positive correlation. The UACR/SACR ratio demonstrated superior predictive capability for DR compared to SACR and UACR alone. The most accurate predictive model combined SACR, UACR, UACR/SACR ratio and HbA1c (AUC = 0.614), highlighting DR development complexity. Subgroup analyses revealed stronger associations in participants aged < 60 years and those with hypertension (both p < 0.05), with more pronounced effects observed in males and Mexican Americans, while lifestyle factors showed no significant modifying effect.

CONCLUSION

The UACR/SACR Ratio emerged as a potentially superior DR predictor, particularly in younger patients and those with hypertension, suggesting its utility in enhancing early detection and risk stratification. Comprehensive evaluation of renal function and glycaemic control biomarkers, considering age- and comorbidity-specific patterns, could improve DR risk prediction and management. Future longitudinal studies should validate these findings, particularly in identified high-risk subgroups, and investigate underlying mechanisms, potentially advancing personalised DR prediction and management strategies.

Associations between cardiometabolic indices and the risk of diabetic kidney disease in patients with type 2 diabetes

BACKGROUND

This study was designed to assess the associations between emerging cardiometabolic indices-the atherogenic index of plasma (AIP), the stress hyperglycemia ratio (SHR), the triglyceride-glucose (TyG) index, and the homeostasis model assessment of insulin resistance (HOMA-IR)-and the incidence of diabetic kidney disease (DKD) in type 2 diabetes (T2D) patients.

METHODS

We consecutively enrolled 4351 T2D patients. The AIP, SHR, TyG index, and HOMA-IR were calculated from baseline parameters. DKD was defined as a urine albumin/creatinine ratio > 30 mg/g or an eGFR < 60 mL/min per 1.73 m. All participants were categorized into tertiles based on the cardiometabolic indices. Multivariate logistic regression models, restricted cubic splines, and receiver operating characteristic (ROC) curves were used for analysis.

RESULTS

A total of 1371 (31.5%) patients were diagnosed with DKD. A restricted cubic spline showed a J-shaped association of the AIP and TyG index with DKD, a log-shaped association between HOMA-IR and DKD, and a U-shaped association between the SHR and DKD incidence. Multivariate logistic regression revealed that individuals in the highest tertile of the four cardiometabolic indices had a significantly greater risk of DKD than did those in the lowest tertile (AIP: OR = 1.08, 95% CI = 1.02-1.14, P = 0.005; SHR: OR = 1.42, 95% CI = 1.12-1.81, P = 0.004; TyG index: OR = 1.86, 95% CI = 1.42-2.45, P < 0.001; HOMA-IR: OR = 2.24, 95% CI = 1.52-3.30, P < 0.001). The receiver operating characteristic curves showed that the HOMA-IR score was better than other indices at predicting the risk of DKD, with an optimal cutoff of 3.532.

CONCLUSIONS

Elevated AIP, SHR, TyG index and HOMA-IR are associated with a greater risk of DKD in patients with T2D. Among these indices, the HOMA-IR score demonstrated the strongest association with and predictive value for DKD incidence.

Administration of Bevacizumab and the Risk of Chronic Kidney Disease Development in Taiwan Residents: A Population-Based Retrospective Cohort Study

Vascular endothelial growth factor (VEGF) plays a significant role as a pro-angiogenic and pro-permeability factor within the kidney. Bevacizumab is a pharmaceutical monoclonal anti-VEGF antibody that inhibits the growth of new blood vessels, which blocks blood supply and thereby restricts tumor growth. Thus, we conducted a nationwide study to explore the risk of chronic kidney disease (CKD) development in Taiwan residents after bevacizumab therapy. We drew data from the extensive National Health Insurance Research Database (NHIRD), which encompasses data from >99% of Taiwan's population from 1995 onwards. Individuals who received bevacizumab between 2012-2018 were identified as the bevacizumab cohort, with the index date set at the first usage. We randomly selected dates within the study period for the control group to serve as index dates. We excluded patients with a history of CKD prior to the index date or those <20 years old. In both cohorts, patients' propensity scores matched in a 1:1 ratio based on sex, age, index year, income, urbanization level, comorbidities, and medications. We found patients treated with bevacizumab had a significantly higher risk of contracting CKD than patients without bevacizumab (adjusted hazard ratio = 1.35, 95% confidence interval = 1.35-1.73). The risk of CKD was 1.35-fold higher in participants with bevacizumab treatment than those in the control group. These findings suggest that close monitoring of CKD development after bevacizumab administration is needed.