Risk Of Diabetic Nephropathy Research Articles

Bidirectional two-sample Mendelian randomization analysis unveils causal association between inflammatory cytokines and the risk of diabetic nephropathy

ObjectivePrevious observational studies have indicated associations between various inflammatory cytokines and diabetic nephropathy (DN) caused by type 2 diabetes mellitus (T2DM). However, the causality remains unclear. We aimed to further evaluate the causal association between 91 inflammatory cytokines and DN using bidirectional two-sample Mendelian randomization (MR) analysis.MethodSummary statistics for DN were obtained from a publicly available genome-wide association study (GWAS) analysis. Data pertaining to inflammatory cytokines were derived from a GWAS protein quantitative trait locus (pQTL) study. The primary analytical approach employed the inverse variance weighted (IVW) method, complemented by MR-Egger regression, weighted mode (WM), and weighted median (WME) methods to evaluate the causal association between inflammatory cytokines and DN. Sensitivity analyses were conducted to validate the robustness of the findings.ResultAmong individuals of European ancestry, the IVW method results revealed a positive causal association between the gene expression of tumor necrosis factor ligand superfamily member 14 (TNFSF14), and TNF-related activation-induced cytokine (TRANCE) with DN. Conversely, a negative causal association was observed between the gene expression of interleukin-1-alpha (IL-1α), and transforming growth factor-alpha (TGF-α) with DN. Among individuals of East Asian ancestry, the IVW method results indicated a negative causal association between the gene expression of glial cell line-derived neurotrophic factor (GDNF) and DN. Notably, these findings persisted without evidence of horizontal pleiotropy or heterogeneity, ensuring their robustness and reliability.ConclusionThe MR analysis underscores a causal association between inflammatory cytokines and DN, providing an important reference and evidence for the study of DN.

Partial reduction of interleukin-33 signaling improves senescence and renal injury in diabetic nephropathy.

Diabetic nephropathy (DN) is a frequent and costly complication of diabetes with limited understandings of mechanisms and therapies. Emerging evidence points to the important roles of interleukin-33 (IL-33) in acute kidney injury, yet its contribution to DN is still unclear. We here found a ubiquitous increase of IL-33 and its receptor (ST2) in murine models and patients with DN. Surprisingly, both IL-33 and ST2 knockdown aggravated renal lesions in DN, while overexpression of IL-33 also exacerbated the condition. Further population-based analyses revealed a positive correlation of IL-33 expression with renal dysfunction in DN patients. Individuals with high IL-33expression-related polygenic risk score had a higher DN risk. These findings confirmed the harmful effects of IL-33 on DN. Conversely, endogenous and exogenous partial reduction of IL-33 signaling conferred renoprotective effects in vivo and in vitro. Mechanistically, IL-33 induced senescence by regulating cell cycle factors in HK-2 cells, and accordingly senescence led to renal cell damage through the secretion of senescence-related secretory phenotype (SASP) including IL-33 and prostaglandins. Together, elevated IL-33 accelerates cellular senescence to drive DN possibly by SASP production, while a partial blockage improves renal injury and senescence. Our findings pinpoint a possible and new avenue for DN interventions.

Establishing a Risk Model for Diabetic Nephropathy and Addressing the Therapeutic Effect of Combined Epalrestat- Dapagliflozin Regimen.

To explore the construction of a diagnostic prediction model of diabetic nephropathy (DN) in type 2 diabetic patients for prognostic risk prediction and observe the therapeutic effect of Epalrestat combined with Dapagliflozin on DN. The study consisted of two phases, phase I: A retrospective analysis was conducted on the case information and clinical treatment related data of a total of 460 patients who underwent kidney biopsy from June 2018 to June 2021. They were randomly divided into validation queue and training queue. The predictive factors of the diagnostic prediction model were obtained through multivariate logistic regression. An interventional study of 94 patients with DN admitted between January 2022 and August 2023 was conducted, and they were randomized into a control group (n = 47) receiving Dapagliflozin and a research group (n = 47) receiving Epalrestat combined with Dapagliflozin. The glucose metabolism, renal function, and treatment safety of the two groups before and after treatment were compared. In addition, the adverse reactions during the treatment of the two groups were counted. In the phase I of the study, the DN risk model established showed a good performance in the diagnosis and risk assessment of patients with DN and could provide certain reference opinions for future clinical practice. In the phase II of the study, the research group showed better glucose metabolism and renal function than the control group after treatment (P < .05), but no statistical difference was identified between groups in the incidence of adverse reactions (P > .05). Conclusion. Epalrestat combined with Dapagliflozin is significantly effective in the treatment of DN, which can effectively improve glucose metabolism and renal function in DN patients.

Association between body fat variation rate and risk of diabetic nephropathy - a posthoc analysis based on ACCORD database

BackgroundWeight control has consistently been regarded as a significant preventive measure against diabetic nephropathy. however, the potential impact of substantial fluctuations in body fat during this process on the risk of diabetic nephropathy remains uncertain. This study aimed to investigate the association between body fat variation rate and diabetic nephropathy incident in American patients with type 2 diabetes.MethodsThe study used data from the Action to Control Cardiovascular Risk in diabetes (ACCORD) trial to calculate body fat variation rates over two years and divided participants into Low and High groups. The hazard ratio and 95% confidence interval were estimated using a Cox proportional hazards model, and confounding variables were addressed using propensity score matching.ResultsFour thousand six hundred nine participants with type 2 diabetes were studied, with 1,511 cases of diabetic nephropathy observed over 5 years. High body fat variation rate was linked to a higher risk of diabetic nephropathy compared to low body fat variation rate (HR 1.13, 95% CI 1.01–1.26). Statistically significant interaction was observed between body fat variation rate and BMI (P interaction = 0.008), and high level of body fat variation rate was only associated with increased risk of diabetic nephropathy in participants with BMI > 30 (HR 1.34 and 95% CI 1.08–1.66).ConclusionsAmong participants with Type 2 Diabetes Mellitus, body fat variation rate was associated with increased risk of diabetic nephropathy. Furthermore, the association was modified by BMI, and positive association was demonstrated in obese but not non-obese individuals. Consequently, for obese patients with diabetes, a more gradual weight loss strategy is recommended to prevent drastic fluctuations in body fat.Trial registrationClinical Trials. gov, no. NCT000000620 (Registration Date 199909).Graphical

Causal role of 731 immune cells in diabetic nephropathy: a bi-directional two-sample Mendelian randomization study.

The primary cause of end-stage renal disease (ESRD) is diabetic nephropathy (DN), and a growing body of research indicates that immunology plays a part in how DN develops into ESRD. Our objective is to identify causal relationships between various immune invading cells and DN to identify possible targets for immunotherapy. This study used a complete Mendelian randomization (MR) analysis with two samples to identify the underlying mechanism linking immune cell characteristics with DN. Using publicly available genetic data, we investigated the causal link between 731 immune cell profiles and DN risk. Included were four different types of immune systems: morphological parameters (MP), absolute cell (AC), relative cell (RC), and median fluorescence intensities (MFI). The results' robustness, heterogeneity, and horizontal pleiotropy were confirmed through extensive sensitivity analysis. Following FDR (False Discovery Rate correction method) correction, no statistically significant differences were observed; however, six immunophenotypes were shown to be significantly associated with DN risk at the 0.25 level. Only CD28+ CD4- CD8- T cells were identified as the protective immunophenotype (OR = 0.588, 95% CI 0.437-0.792, P = 4.71 × 10-4). Moreover, DN had no discernible impact on immunophenotyping after FDR correction. Surprisingly, three unadjusted phenotypes with low P values were discovered to be positively correlated with the risk of DN: CD20 on IgD- CD27- B cells (OR = 1.263, 95% CI 1.076-1.482, P = 4.22 × 10-3), CD8 on naive CD8 + T cells with Effector Memory (OR = 1.107, 95% CI 1.013-1.209, P = 2.40 × 10-2), and CD8 on Effector Memory CD8 + T cells (OR = 1.126, 95% CI 1.024-1.239, P = 1.46 × 10-2). Our findings provide a genetic basis for the association between immune cells and DN and should inform future clinical research.

Association of lipid-lowering drugs with the risk of type 2 diabetes and its complications: a mendelian randomized study

BackgroundThe pathogenesis of type 2 diabetes mellitus is somewhat associated with lipid metabolism. We aim to assess the impact of lipid-lowering drugs (HMGCR inhibitors, PCSK9 inhibitors, and NPC1L1 inhibitors) on type 2 diabetes mellitus and its complications through a two-sample Mendelian randomization (MR) study.MethodWe identified suitable genetic instruments from the GWAS database that represent the expression levels of three genes, interpreting reduced genetically proxied gene expression as indicative of lipid-lowering drug use. We evaluated the causal relationships among these variables employing a two-sample Mendelian randomization approach, with the Inverse Variance Weighted (IVW) analysis serving as the primary method. Coronary artery disease was utilized as a positive control to validate the reliability of the selected genetic instruments.ResultIncreased genetically proxied HMGCR expression is significantly associated with a reduced risk of type 2 diabetes mellitus (OR = 0.64, 95%CI = 0.55–0.74), which was replicated in the FinnGen study with consistent results (OR = 0.65, 95%CI = 0.53–0.80). Increased genetically proxied HMGCR expression is associated with a reduced risk of diabetic retinopathy (OR = 0.23, 95%CI = 0.12–0.44) and diabetic nephropathy (OR = 0.35, 95%CI = 0.17–0.71). In contrast, increased genetically proxied PCSK9 expression is associated with a decreased risk of diabetic coma (OR = 0.70, 95%CI = 0.50–0.98), diabetic neuropathy (OR = 0.24, 95%CI = 0.14–0.42), diabetic retinopathy (OR = 0.67, 95%CI = 0.48–0.96), diabetic cardiovascular diseases (OR = 0.62, 95%CI = 0.38–0.99), and diabetic nephropathy (OR = 0.62, 95%CI = 0.41–0.95).ConclusionsThis Mendelian randomization study suggests an association between HMGCR and the pathogenesis of type 2 diabetes mellitus, with increased genetically proxied HMGCR expression reducing the risk of type 2 diabetes mellitus, while PCSK9 and NPC1L1 show no significant association with type 2 diabetes mellitus. These findings may offer more reasonable lipid-lowering drug options for patients with dyslipidemia.

Association of MnSOD, CAT, and GPx1 Gene Polymorphism with Risk of Diabetic Nephropathy in South Indian Patients: A Case-Control Study.

Diabetic nephropathy (DN) is one of the common complications of type 2 diabetes mellitus (T2DM), and oxidative stress plays a key role in the pathogenesis of DN. Studies have demonstrated that antioxidants (MnSOD, CAT, and GPx1) may reduce the complications associated with T2DM. The purpose of the study is to correlate the role of antioxidant gene polymorphisms in the pathogenesis of DN among T2DM individuals in the South Indian population. It clarifies the importance of early manifestation and reliable genetic indicators modulating the oxidative stress mechanism in DN.The study participants were divided and grouped as Group 1: Control, Group 2: T2DM without DN, and Group 3: T2DM with DN (n = 100 in each group). The levels of plasma glucose, HbA1c, renal profile, SOD, CAT, GPx1, MDA, and TAS were assessed. MnSOD (rs4880), CAT (rs1049982), and GPx1 (rs1050450) polymorphisms were genotyped via Tetra-arms PCR.The genotypes of GPx1 depict a significant role in the progression of DN in T2DM patients (co-dominant [OR: 2.134; 95% CI (1.202-3.788), p < 0.01], dominant [OR: 2.015; 95% CI (1.117-3.634), p = 0.02], and recessive model [OR: 2.215; 95% CI (1.235-3.972), p = 0.008]); whereas rs4880 and rs1049982 polymorphisms are not associated with DN progression. As a result, GPx1 (rs1050450) polymorphism could be a diagnostic risk factor for developing DN in T2DM patients. Moreover, the genotypes of rs4880 and rs1049982 polymorphism show significant difference in the antioxidant parameters compared to the genotypes of rs1050450.In contradiction to earlier studies, the current study demonstrates that the genotypes of rs1050450 (GPx1) can be considered as an influential component for higher susceptibility and risk of developing DN in T2DM patients among the South Indian population.

Establishment of a metabolite diagnostic model for the risk of diabetic nephropathy in type 2 diabetic population: Based on a cross-sectional study in China

IntroductionThis study aimed to investigate the correlation between various plasma metabolites and the likelihood of developing diabetic nephropathy (DN) and construct a diagnostic model for DN in Chinese patients with type 2 diabetes mellitus (T2DM). MethodsA cross-sectional investigation was conducted in a hospital setting. Based on medical data, a total of 743 patients from a tertiary hospital were selected and categorized into two groups: the diabetic nephropathy group (DN group) and the non-diabetic nephropathy group (non-DN group). Plasma levels of metabolites, including amino acids and acylcarnitines, were determined using a laser counter measurement system (LC-MS). Subsequently, partial least-squares regression was used to assess the significance of these metabolites. Receiver operating characteristic (ROC) curves were generated for factors that ranked highest in terms of relevance. Model performance was assessed using the curve (AUC). ResultsOf the 743 patients with T2DM admitted to the hospital, 145 had DN. Compared with the non-DN group, the DN group exhibited elevated systolic blood pressure (P ​= ​0.001), high-density lipoprotein cholesterol (P ​= ​0.01), and low-density lipoprotein cholesterol (P ​= ​0.042). Additionally, the DN group had a higher prevalence of stroke patients (P ​< ​0.001) and diabetic retinopathy patients (P ​< ​0.001). Finally, a risk model that included citrulline, leucine, tyrosine, valine, propionylcarnitine (C3), and palmitoylcarnitine (C16) was developed. This model achieved an AUC of 0.709, with a 95% confidence interval (CI) ranging from 0.626 to 0.793. ConclusionsA diagnostic model consisting of six plasma metabolites to assess the risk of DN in Chinese patients with T2DM may provide clues for future research.

Gene Polymorphisms of the antioxidant enzymes NOX, GSTP, and GPX and diabetic nephropathy risk in Saudi patients with type 2 diabetes

Oxidative stress has been hypothesized to play a crucial role in the complications of type 2 diabetes (T2D). Hyperglycaemia-mediated increases in free radicals have a deleterious effect on cellular compartments and nucleic acids, leading to imbalances between free radicals and antioxidant enzymes. This case–control study comprised two groups with 100 participants (50 T2D and 50 DN patients) and aimed to examine the association between single-nucleotide polymorphisms (SNPs) in the genes encoding nicotinamide adenine dinucleotide phosphate oxidase (NOX), glutathione S-transferase P (GSTP1), and glutathione peroxidase 1(GPX1) and diabetic nephropathy (DN) risk in patients with T2D. An SNP genotyping assay was performed using TaqMan assay and real-time PCR to identify the SNPs (NOX rs4673, GSTP rs1695, GPX1 rs1050450). The Sanger method was used to validate our findings. Fisher chi-square analyses revealed no significant differences in these genes when comparing T2D patients with and without DN. Our findings suggest no association between the rs4673, rs1695, and rs1050450 SNPs and DN in Saudi patients with T2D.

Association of Helicobacter pylori infection with complications of diabetes: a single-center retrospective study

BackgroundPrevious studies examined the association of Helicobacter pylori infection (H. pylori) with complications of diabetes, but the results have been inconsistent. The aim of this study of patients with type-2 diabetes (T2D) was to determine the association of H. pylori infection with the major complications of diabetes.MethodsThis single-center retrospective study examined patients with T2D who received H. pylori testing between January 2016 and December 2021. Logistic regression analyses were used to evaluate the association of H. pylori infection with four major complications of diabetes.ResultsWe examined 960 patients with T2D, and 481 of them (50.1%) were positive for H. pylori. H. pylori infection was significantly associated with diabetic nephropathy (odds ratio [OR] = 1.462; 95% confidence interval [CI]: 1.006,2.126; P = 0.046). In addition, the co-occurrence of H. pylori positivity with hypertension (OR = 4.451; 95% CI: 2.351,8.427; P < 0.001), with glycated hemoglobin A1c (HbA1c) of at least 8% (OR = 2.925; 95% CI: 1.544,5.541; P = 0.001), and with diabetes duration of at least 9 years (OR = 3.305; 95% CI:1.823,5.993; P < 0.001) further increased the risk of diabetic nephropathy. There was no evidence of an association of H. pylori infection with retinopathy, neuropathy, or peripheral vascular disease.ConclusionsOur study of T2D patients indicated that those with H. pylori infections had an increased risk of nephropathy, and this risk was greater in patients who also had hypertension, an HbA1c level of 8% or more, and diabetes duration of 9 years or more.

The impact of homocysteine on patients with diabetic nephropathy: a mendelian randomization study.

Homocysteine (Hcy) has been associated with an increased risk of diabetic nephropathy (DN) in patients, but there is still controversy. This study aims to investigate the causal relationship between plasma Hcy and DN. A Mendelian randomization (MR) study using data from 2 samples was employed to infer causal relationships. The aggregated genetic data associated with Hcy was derived from the largest genome-wide association study (GWAS) to date, involving 44,147 individuals of European ancestry.Data on SNP-diabetic nephropathy, creatinine, and urea nitrogen were obtained from the IEU GWAS database. The analysis method employed a fixed-effect or random-effect inverse variance-weighted approach to estimate effects.Additional analysis methods were used to assess stability and sensitivity. The potential for pleiotropy was evaluated using the MR-Egger intercept test. Using 12 SNPs as instrumental variables, two-sample MR analysis revealed no evidence of a causal relationship between genetically predicted plasma Hcy levels and diabetic nephropathy, as well as creatinine and blood urea nitrogen levels. This finding is consistent with the results obtained from other testing methods. Two-sample Mendelian Randomization analysis found no evidence of a causal relationship between plasma homocysteine levels and diabetic nephropathy, creatinine, or urea.

Causal Effects of Oxidative Stress on Diabetes Mellitus and Microvascular Complications: Insights Integrating Genome-Wide Mendelian Randomization, DNA Methylation, and Proteome.

Oxidative stress (OS) is involved in the development of diabetes, but the genetic mechanisms are not completely understood. We integrated multi-omics data in order to explore the genetic relations between OS-related genes, diabetes mellitus, and microvascular complications using Mendelian randomization and colocalization analysis. Summary-level data related to OS were acquired from respective studies of methylation, expression, and protein abundance quantitative trait loci. Genetic associations concerning diabetes, diabetic nephropathy (DN), and diabetic retinopathy (DR) were derived from the FinnGen study. Summary-data-based Mendelian randomization (SMR) analysis was conducted to evaluate the correlations between molecular features concerned with OS-related genes and diabetes mellitus, along with its microvascular complications. Additionally, we performed colocalization analysis to determine if the detected signal pairs shared a causal genetic variant. At the genetic level, we identified ten potential causal associations of oxidative stress genes with diabetes, along with microvascular complications, through SMR and colocalization analysis. After integrating the DNA methylation quantitative trait loci (mQTL) and expression QTL (eQTL) data, our analyses revealed a correlation between the methylation site cg26343298 and reduced expression of TP53INP1, supporting the protective role of cg26343298 methylation on type 2 diabetes (T2D) and diabetic nephropathy. Similarly, an inverse association was observed between gene methylation and expression in CHEK1 (cg07110182), confirming the beneficial effect of modification of CHEK1 by cg07110182 in diabetic retinopathy. In addition, upregulation of SUOX expression by cg22580629 was linked to a reduced risk of diabetic retinopathy. At circulating protein levels, genetically predicted a higher level of ICAM1 (OR 1.05, 95%CI 1.03-1.08) was positively connected with the risk of diabetic retinopathy. This SMR study elucidated that the TP53INP1 gene was putatively associated with T2D and DN risk, while the SUOX and CHEK1 genes were associated with DR risk through oxidative stress mechanisms. Additionally, our study showed a positive correlation between the ICAM-1 protein and DR. These findings may enhance our understanding of their pathogenesis and suggest new therapeutic targets for clinical practice.

The causal role between circulating immune cells and diabetic nephropathy: a bidirectional Mendelian randomization with mediating insights

Diabetic nephropathy (DN) is a critical inflammatory condition linked to diabetes, affecting millions worldwide. This study employs Mendelian randomization (MR) to explore the causal relationship between immune cell signatures and DN, analyzing over 731 immune signatures and incorporating data from 1400 metabolites to investigate potential mediators. Despite no statistically significant influence of DN on immunophenotypes after FDR correction, some phenotypes with unadjusted low P-values warranted mention, including CD34 on Hematopoietic Stem Cell (Myeloid cell Panel), CD45 on CD33− HLA DR− (Myeloid cell Panel). Furthermore, three immunophenotypes were identified to have a significant impact on DN risk: CD16−CD56 on HLA DR+ NK (TBNK Panel), CD45 on HLA DR+ T cell (TBNK Panel), and CD33dim HLA DR+ CD11b+ AC (Myeloid cell Panel). Our findings underscore the critical role of immune cells in DN, highlighting potential mediators and offering new insights into its underlying mechanisms.

431-P: Identification of the Serum Uric Acid Threshold for Predicting Diabetic Nephropathy Risk in Patients with Type 1 Diabetes

431-P: Identification of the Serum Uric Acid Threshold for Predicting Diabetic Nephropathy Risk in Patients with Type 1 Diabetes

Apoptosis and NETotic cell death affect diabetic nephropathy independently: An study integrative study encompassing bioinformatics, machine learning, and experimental validation

ObjectiveAlthough programmed cell death (PCD) and diabetic nephropathy (DN) are intrinsically conneted, the interplay among various PCD forms remains elusive. In this study, We aimed at identifying independently DN-associated PCD pathways and biomarkers relevant to the related pathogenesis. MethodsWe acquired DN-related datasets from the GEO database and identified PCDs independently correlated with DN (DN-PCDs) through single-sample Gene Set Enrichment Analysis (ssGSEA) as well as, univariate and multivariate logistic regression analyses. Subsequently, applying differential expression analysis, weighted gene co-expression network analysis (WGCNA), and Mfuzz cluster analysis, we filtered the DN-PCDs pertinent to DN onset and progression. The convergence of various machine learning techniques ultimately spotlighted hub genes, substantiated through dataset meta-analyses and experimental validations, thereby confirming hub genes and related pathways expression consistencies. ResultsWe harmonized four DN-related datasets (GSE1009, GSE142025, GSE30528, and GSE30529) post-batch-effect removal for subsequent analyses. Our differential expression analysis yielded 709 differentially expressed genes (DEGs), comprising 446 upregulated and 263 downregulated DEGs. Based on our ssGSEA as well as univariate and multivariate logistic regressions, apoptosis and NETotic cell death were appraised as independent risk factors for DN (Odds Ratio > 1, p < 0.05). Next, we further refined 588 apoptosis- and NETotic cell death-associated genes through WGCNA and Mfuzz analysis, resulting in the identification of 17 DN-PCDs. Integrating protein-protein interaction (PPI) network analyses, network topology, and machine learning, we pinpointed hub genes (e.g., IL33, RPL11, and CX3CR1) as significant DN risk factors with expression corroborating in subsequent meta-analyses and experimental validations. Our GSEA enrichment analysis discerned differential enrichments between DN and control samples within pathways such as IL2/STAT5, IL6/JAK/STAT3, TNF-α via NF-κB, apoptosis, and oxidative phosphorylation, with related proteins such as IL2, IL6, and TNFα, which we subsequently submitted to experimental verification. ConclusionInnovatively stemming from from PCD interactions, in this study, we discerned PCDs with an independent impact on DN: apoptosis and NETotic cell death. We further screened DN evolution- and progression-related biomarkers, i.e. IL33, RPL11, and CX3CR1, all of which we empirically validated. This study not only poroposes a PCD-centric perspective for DN studies but also provides evidence for PCD-mediated immune cell infiltration exploration in DN regulation. Our results could motivate further exploration of DN pathogenesis, such as how the inflammatory microenvironment mediates NETotic cell death in DN regulation, representing a promising direction for future research.

Association between hyperuricemia and diabetic nephropathy: insights from the national health and nutrition examination survey 2007–2016 and mendelian randomization analysis

BackgroundThis study aimed to investigate the role of uric acid (UA) in diabetic nephropathy (DN) from epidemiological and genetic perspectives.MethodsWe used data from the 2007–2016 National Health and Nutrition Examination Survey to evaluate the relationship between UA and DN risk using weighted multivariate-adjusted logistic regression. Subsequently, a two-sample Mendelian randomization study was conducted using genome-wide association study summary statistics. The main inverse variance weighting (IVW) method and supplementary MR method were used to verify the causal relationship between UA and DN, and sensitivity analysis was conducted to confirm the credibility of the results.ResultsOur observational study enrolled 4363 participants with diabetes mellitus from NHANES, among them, 2682 (61.4%) participants were identified as DN. The multivariate logistic regression model showed that compared with those without hyperuricemia, the DN risk of the hyperuricemia population was significantly increased (P < 0.05). The MR results suggest a direct causal effect of hyperuricemia on DN (IVW odds ratio (OR): 1.37 (95% confidence interval 1.07–1.76); P = 0.01), which is consistent with findings from other MR methods.ConclusionThe evidence from observational studies indicates a positive correlation between HUA and the onset of DN. And the causal effects of HUA on DN were supported by the MR analysis.

The causal relationship between 5 serum lipid parameters and diabetic nephropathy: a Mendelian randomization study.

Serum lipids were found to be correlated with chronic kidney disease and cardiovascular disease. Here, we aimed to research the potential causal associations between five serum lipid parameters and the risk of diabetic nephropathy using several Mendelian Randomization methods. Genetic data was obtained from the UK Biobank datasets. Causal effects were estimated using multiple MR methods. Heterogeneity and pleiotropy tests were performed. MR analysis revealed that HDL-C and TG exhibited causal associations with diabetic nephropathy (P<0.05). Similar trends were not observed for other lipid parameters. Our research has suggested links between HDL-C, TG and diabetic nephropathy. The findings could contribute to further elucidation of the disease etiology. This article only uses Mendel randomization method to analyze the relationship between blood lipids and diabetes nephropathy, which is more convincing when combined with population data.

Impact of frailty on mortality, hospitalization, cardiovascular events, and complications in patients with diabetes mellitus: a systematic review and meta-analysis.

Several studies have focused on the impact of frailty on the health outcomes of individuals with diabetes mellitus (DM). This meta-analysis aims to systematically synthesize the existing evidence on frailty and its association with mortality, hospitalizations, cardiovascular diseases, and diabetic complications in DM. A comprehensive search in PubMed, Embase, and SCOPUS was carried out to identify relevant studies assessing the impact of frailty on mortality, hospitalizations, complications, and cardiovascular events in individuals with DM. The quality of the included studies was evaluated using the New Castle Ottawa Scale. From the 22 studies included, our meta-analysis revealed significant associations between frailty and adverse outcomes in individuals with DM. The pooled hazard ratios for mortality and frailty showed a substantial effect size of 1.84 (95% CI 1.46-2.31). Similarly, the odds ratio for hospitalization and frailty demonstrated a significant risk with an effect size of 1.63 (95% CI 1.50-1.78). In addition, frailty was associated with an increased risk of developing diabetic nephropathy (HR, 3.17; 95% CI 1.16-8.68) and diabetic retinopathy (HR, 1.94; 95% CI 0.80-4.71). Our results show a consistent link between frailty and increased mortality, heightened hospitalization rates, and higher risks of cardiovascular disease, diabetic nephropathy, and diabetic retinopathy for patients with DM. PROSPERO Registration Number: CRD42023485166.

Mendelian randomization analysis reveals causal relationships between circulating cell traits and renal disorders.

The aim of this study was to investigate the causal relationships between circulating cell traits and risk of renal disorders. We applied a comprehensive two-sample Mendelian randomization (MR) analysis. Single nucleotide polymorphisms (SNPs) from publicly available genome-wide association studies (GWAS) databases were utilized. Genetically predicted instrumental variables of human blood cell traits were extracted from Blood Cell Consortium (BCX) while data on renal diseases was obtained from Finngen consortium. The primary MR analysis was conducted using the inverse variance weighted (IVW) method, with the weighted median (WM) and MR-Egger models used as additional methods. Sensitivity analyses, including MR-PRESSO, radial regression and MR-Egger intercept were conducted to detect outliers and assess horizontal pleiotropy. We further utilized the leave-one-out analysis to assess the robustness of the results. Causal associations were considered significant based on false rate correction (FDR), specifically when the IVW method provided a pFDR < 0.05. Our results demonstrated that both white blood cell (WBC) count (OR = 1.50, 95% CI = 1.10-2.06, pFDR = 0.033, pIVW = 0.011) and lymphocyte count (OR = 1.50, 95% CI = 1.13-1.98, pFDR = 0.027, pIVW = 0.005) were causally associated with a higher risk of IgA nephropathy. Furthermore, WBC count was identified as a significant genetic risk factor for renal malignant neoplasms (OR = 1.23, 95% CI = 1.06-1.43, pFDR = 0.041, pIVW = 0.007). Additionally, an increased level of genetically predicted eosinophils was found to be causally associated with a higher risk of diabetic nephropathy (OR = 1.21, 95% CI = 1.08-1.36, pFDR = 0.007, pIVW = 0.001). No evidence of pleiotropy was determined. Our findings provide evidence of causal associations of circulating WBC count, lymphocyte count and IgA nephropathy, WBC count and renal malignant neoplasms, and eosinophil count and diabetic nephropathy. These results have the potential to contribute to the development of novel diagnostic options and therapeutic strategies for renal disorders.

Significant Association of Candidate Genes (AGTR1 and TGF-Β1) Polymorphism with Diabetic Nephropathy in Diabetes Mellitus Type 2 Patients.

Diabetic nephropathy (DN) is one of the complications of diabetes mellitus (DM). This study aimed to investigate the association between genetic polymorphisms, specifically AGTR1 (rs5186) and TGF-β1 (rs1800470), and the risk of developing Diabetic nephropathy (DN) in type 2 diabetes mellitus patients, compared to those without DN and healthy controls. A case-control study was conducted on 165 diabetic patients (59 with diabetic nephropathy (DN) and 54 without DN (DM)), and 52 healthy controls (HC). The genotyping was done using amplification refractory mutation system method (ARMS-PCR). Age, gender, and duration of diabetes were matched across groups. Clinical parameters including FBS, RBS, HbA1C, creatinine, urea, SBP, DBP, total cholesterol, triglycerides, LDL, and BMI were assessed. Diabetic patients with nephropathy exhibited significantly higher levels of clinical parameters compared to those without nephropathy and healthy controls. The risk allele of AGTR1 , C (p <0.0001), and risk allele containing genotypes AC (p <0.0001) and CC (p - 0.0010) were significantly higher in DN patients compared to DM and HC groups. Similarly, the TGF-β1 risk allele C (p - 0.0001), and corresponding genotypes TC (p - 0.0038) and CC (p - 0.0027) were significantly associated with increased risk of diabetic nephropathy compared to DM and HC groups. The data showed significant association of AGTR1 (rs5186) and TGF-β1 (rs1800470) polymorphism with an increased risk of diabetic nephropathy in type 2 diabetes mellitus patients. More investigation will be required to disseminate the results, while increasing the samples size and using whole genome sequencing.