Identification of common and specific fibrosis-related genes in three common chronic kidney diseases.

BACKGROUND: Kidney fibrosis is the common final pathway of virtually all advanced forms of chronic kidney disease (CKD) including diabetic nephropathy (DN), IgA nephropathy (IgAN) and membranous nephropathy (MN), with complex mechanism. Comparative gene expression analysis among these types of CKD may shed light on its pathogenesis. Therefore, we conducted this study aiming at exploring the common and specific fibrosis-related genes involved in different types of CKD. METHODS: Kidney biopsy specimens from patients with different types of CKD and normal control subjects were analyzed using the NanoString nCounter® Human Fibrosis V2 Panel. Genes differentially expressed in all fibrotic DN, IgAN and MN tissues compared to the normal controls were regarded as the common fibrosis-related genes in CKD, whereas genes exclusively differentially expressed in fibrotic DN, IgAN or MN samples were considered to be the specific genes related to fibrosis in DN, IgAN and MN respectively. Quantitative real-time PCR (qRT-PCR) was performed to validate the expression of the selected genes. RESULTS: Protein tyrosine phosphatase receptor type C (PTPRC), intercellular cell adhesion molecule-1 (ICAM1), vascular cell adhesion molecule-1 (VCAM1), interleukin 10 receptor alpha (IL10RA) and CC chemokine receptor 2 (CCR2) were identified as the potential common genes for kidney fibrosis in different types of CKD, while peroxisome proliferator-activated receptor alpha (PPARA), lactate oxidase (LOX), secreted phosphoprotein 1 (SPP1) were identified as the specific fibrosis-associated genes for DN, IgAN and MN respectively. qRT-PCR demonstrated that the expression levels of these selected genes were consistent with the NanoString analysis. CONCLUSIONS: There were both commonalities and differences in the mechanisms of fibrosis in different types of CKD, the commonalities might be used as the common therapeutic targets for kidney fibrosis in CKD, while the differences might be used as the diagnostic markers for DN, IgAN and MN respectively. Inflammation was highly relevant to the pathogenesis of fibrosis. This study provides further insight into the pathophysiology and treatment of fibrotic kidney disease.

A new perspective on proteinuria and drug therapy for diabetic kidney disease.

Diabetic kidney disease (DKD) is one of the leading causes of end-stage renal disease worldwide and significantly increases the risk of premature death due to cardiovascular diseases. Elevated urinary albumin levels are an important clinical feature of DKD. Effective control of albuminuria not only delays glomerular filtration rate decline but also markedly reduces cardiovascular disease risk and all-cause mortality. New drugs for treating DKD proteinuria, including sodium-glucose cotransporter two inhibitors, mineralocorticoid receptor antagonists, and endothelin receptor antagonists, have shown significant efficacy. Auxiliary treatment with proprietary Chinese medicine has also yielded promising results; however, it also faces a broader scope for development. The mechanisms by which these drugs treat albuminuria in patients with DKD should be described more thoroughly. The positive effects of combination therapy with two or more drugs in reducing albuminuria and protecting the kidneys warrant further investigation. Therefore, this review explores the pathophysiological mechanism of albuminuria in patients with DKD, the value of clinical diagnosis and prognosis, new progress and mechanisms of treatment, and multidrug therapy in patients who have type 2 diabetic kidney disease, providing a new perspective on the clinical diagnosis and treatment of DKD.

Uric acid mediates the relationship between mixed heavy metal exposure and renal function in older adult people.

Background: Population aging is a pivotal trend observed globally, and the exposure to heavy metals can exacerbate the aging process and lead to kidney damage. However, the impact of combined heavy metal exposure on renal function among older individuals remains elusive. Our study employs machine learning techniques to delve into the effects and underlying mechanisms of mixed exposure to heavy metals on the renal function of the aging population. Methods: This study extracted comprehensive data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2015 and 2020. A total of 3,175 participants aged 60 years and above, with complete information on six metals - lead, cadmium, manganese, cobalt, mercury, and selenium, along with relevant covariates, were included in the study. To assess the impact of single or mixed metal exposure on the renal function of older adult individuals, various statistical techniques were employed: multiple logistic regression, weighted quantitative sum (WQS) regression, Bayesian kernel machine regression (BKMR), and mediation effects analysis. Results: Multiple logistic regression revealed that selenium and manganese were protective factors for chronic kidney disease (CKD). Cobalt was a risk factor for CKD. High concentrations of lead, cadmium, and cobalt were risk factors for urinary albumin creatinine ratio (ACR). WQS analyses revealed that mixed metal exposure was positively correlated with estimated glomerular filtration rate (eGFR) but negatively correlated with CKD. Selenium and manganese can neutralize the effects of other metals on eGFR. Mixed metal exposure was positively correlated with ACR, with lead and cadmium having a substantial effect. Mediation analysis showed that uric acid (UA) had a mediating effect of 9.7% and -19.7% in the association between mixed metals exposure and proteinuria and CKD, respectively. Conclusion: The impact of heavy metals on renal function in the older adult differs from that of adolescents and adults. This study suggests that elevated levels of mixed metals exposure are linked to proteinuria and CKD, with UA serving as a mediating factor.

Influence of sodium/glucose cotransporter-2 inhibitors on the incidence of acute kidney injury: a meta-analysis.

Background: Sodium/glucose cotransporter-2 inhibitors (SGLT2i) are associated with cardiovascular benefits. The aim of this systematic review and meta-analysis is to summarize the influence of SGLT2i on the incidence of acute kidney injury (AKI), and to ascertain whether it is affected by confounding variables such as age, baseline renal function and concurrent use of renin-angiotensin-aldosterone system inhibitors (RAASi) or mineralocorticoid receptor antagonists (MRA). Methods: PubMed, Embase, and Cochrane Library databases were searched for randomized controlled trials comparing the influence of SGLT2i versus placebo/blank treatment on AKI in the adult population. A fixed-effect model was used if the heterogeneity was not significant; otherwise, a randomized-effect model was used. Results: Eighteen studies comprising 98,989 patients were included. Compared with placebo/blank treatment, treatment with SGLT2i significantly reduced the risk of AKI (risk ratio [RR]: 0.78, 95% confidence interval [CI]: 0.71 to 0.84, p < 0.001; I 2 = 0%). Subgroup analysis suggested consistent results in patients with diabetes, chronic kidney disease, and heart failure (for subgroup difference, p = 0.32). Finally, univariate meta-regression suggested that the influence of SGLT2i on the risk of AKI was not significantly modified by variables such as age (coefficient: 0.011, p = 0.39), baseline estimated glomerular filtration rate (coefficient: -0.0042, p = 0.13) or concomitant use of RAASi (coefficient: 0.0041, p = 0.49) or MRA (coefficient: -0.0020, p = 0.34). Conclusion: SGLT2i may be effective in reducing the risk of AKI, and the effect might not be modified by age, baseline renal function and concurrent use of RAASi or MRA.

Machine learning model for cardiovascular disease prediction in patients with chronic kidney disease.

Introduction: Cardiovascular disease (CVD) is the leading cause of death in patients with chronic kidney disease (CKD). This study aimed to develop CVD risk prediction models using machine learning to support clinical decision making and improve patient prognosis. Methods: Electronic medical records from patients with CKD at a single center from 2015 to 2020 were used to develop machine learning models for the prediction of CVD. Least absolute shrinkage and selection operator (LASSO) regression was used to select important features predicting the risk of developing CVD. Seven machine learning classification algorithms were used to build models, which were evaluated by receiver operating characteristic curves, accuracy, sensitivity, specificity, and F1-score, and Shapley Additive explanations was used to interpret the model results. CVD was defined as composite cardiovascular events including coronary heart disease (coronary artery disease, myocardial infarction, angina pectoris, and coronary artery revascularization), cerebrovascular disease (hemorrhagic stroke and ischemic stroke), deaths from all causes (cardiovascular deaths, non-cardiovascular deaths, unknown cause of death), congestive heart failure, and peripheral artery disease (aortic aneurysm, aortic or other peripheral arterial revascularization). A cardiovascular event was a composite outcome of multiple cardiovascular events, as determined by reviewing medical records. Results: This study included 8,894 patients with CKD, with a composite CVD event incidence of 25.9%; a total of 2,304 patients reached this outcome. LASSO regression identified eight important features for predicting the risk of CKD developing into CVD: age, history of hypertension, sex, antiplatelet drugs, high-density lipoprotein, sodium ions, 24-h urinary protein, and estimated glomerular filtration rate. The model developed using Extreme Gradient Boosting in the test set had an area under the curve of 0.89, outperforming the other models, indicating that it had the best CVD predictive performance. Conclusion: This study established a CVD risk prediction model for patients with CKD, based on routine clinical diagnostic and treatment data, with good predictive accuracy. This model is expected to provide a scientific basis for the management and treatment of patients with CKD.

Optical coherence tomography angiography for the differentiation of diabetic nephropathy from non-diabetic renal disease.

BACKGROUND: To provide a new non-invasive method for the differentiation of diabetic nephropathy (DN) from non-diabetic renal disease (NDRD) by assessing retinal microstructure using optical coherence tomography angiography (OCTA). METHODS: OCTA parameters were recorded and their relationship with DN was analysed. A differential diagnosis regression model for DN was established, and the diagnostic efficiency was evaluated. RESULTS: Based on the pathological results of renal biopsy, 31 DN patients and 35 NDRD patients were included. Multivariate logistic regression analysis showed that DN was independently associated with the following parameters: 15.3 mm-1 ≤ vessel density (VD) full < 17.369 mm-1 (odds ratio [OR]=8.523; 95% confidence interval [CI]=1.387-52.352; P = 0.021), VD full < 15.3 mm-1 (OR=8.202; 95% CI=1.110-60.623; P = 0.039), DM duration > 60 months (OR=7.588; 95% CI=1.569-36.692; P = 0.012), and estimated glomerular filtration rate < 60 mL/min/1.73 m2 (OR=24.484; 95% CI=4.308-139.142; P < 0.001). The area under the receiver operating characteristic curve was 0.911, indicating a high diagnostic efficiency. CONCLUSIONS: VD full < 17.369 mm-1, DM duration > 60 months, and eGFR < 60 mL/min/1.73 m2 may indicate the presence of DN. OCTA may be an effective non-invasive method for identifying DN and NDRD.

Arterial stiffness is associated with handgrip strength in relatively healthy Chinese older adults.

Background: Increased arterial stiffness and low handgrip strength (HGS) are associated with poor health outcomes and are a severe health risk for older adults. However, there is limited evidence and mixed results on whether there is an association between them. Therefore, this study focused on the association between arterial stiffness and HGS in relatively healthy older adults in Beijing, China. Methods: In 2016, 2,217 adult volunteers were recruited in Beijing. Brachial-ankle pulse wave velocity (baPWV) and the ankle-brachial index were measured using an automatic vascular profiling system. Carotid artery intima-media thickness and common carotid artery-internal diameter (CCAID) were evaluated using Doppler ultrasound, and HGS was measured with a dynamometer. Low HGS was determined using the Asian Sarcopenia Working Group 2019 criteria. Multivariate linear and logistic regressions evaluated the relationship between arterial stiffness and HGS. Results: Ultimately, 776 relatively healthy older adults (mean age 69.05 ± 6.46 years) were included. Based on the AWGS2019 criteria, 137 participants were defined as having low HGS. Compared to the normal HGS group, the low HGS group was older and had higher baPWV (p < 0.001) but lower CCAID, body mass index (BMI) and hemoglobin (Hb) (p < 0.05). The multiple linear regression analysis revealed that baPWV was negatively correlated with HGS (ß = -0.173, t = -2.587, p = 0.01). Multivariate logistic regression analysis showed that baPWV and CCAID were associated with an increased risk of low HGS (odds ratio (OR) per SD increase: 1.318, p = 0.007; OR per SD increase: 0.541, p < 0.001). Conclusion: Arterial stiffness and HGS were significantly negatively correlated in relatively healthy Chinese older adults. Low HGS is associated with increased arterial stiffness. Encouraging exercise training to improve HGS, thereby reducing arterial stiffness and the risk of cardiovascular events, may be a simple and effective intervention.

The relationship between diabetic retinopathy and diabetic nephropathy in type 2 diabetes.

Context: Diabetic retinopathy (DR) and diabetic nephropathy (DN), are major microvascular complications of diabetes. DR is an important predictor of DN, but the relationship between the severity of DR and the pathological severity of diabetic glomerulopathy remains unclear. Objective: To investigate the relationship between severity of diabetic retinopathy (DR) and histological changes and clinical indicators of diabetic nephropathy (DN) in patients with type 2 diabetes mellitus (T2DM). Methods: Patients with T2DM (n=272) who underwent a renal biopsy were eligible. Severity of DR was classified as non-diabetic retinopathy, non-proliferative retinopathy, and proliferative retinopathy (PDR). Relationship between DN and DR and the diagnostic efficacy of DR for DN were explored. Results: DN had a higher prevalence of DR (86.4%) and DR was more severe. The sensitivity and specificity of DR in DN were 86.4% and 78.8%, while PDR was 26.4% and 98.5%, respectively. In DN patients, the severity of glomerular lesions (p=0.001) and prevalence of KW nodules (p<0.001) significantly increased with increasing severity of DR. The presence of KW nodules, lower hemoglobin levels, and younger age were independent risk factors associated with more severe DR in patients with DN. Conclusion: DR was a good predictor of DN. In DN patients, the severity of DR was associated with glomerular injury, and presence of KW nodules, lower hemoglobin levels and younger age were independent risk factors associated with more severe DR. Trial registration: ClinicalTrails.gov, NCT03865914.

Progress in the study of aging marker criteria in human populations.

The use of human aging markers, which are physiological, biochemical and molecular indicators of structural or functional degeneration associated with aging, is the fundamental basis of individualized aging assessments. Identifying methods for selecting markers has become a primary and vital aspect of aging research. However, there is no clear consensus or uniform principle on the criteria for screening aging markers. Therefore, we combine previous research from our center and summarize the criteria for screening aging markers in previous population studies, which are discussed in three aspects: functional perspective, operational implementation perspective and methodological perspective. Finally, an evaluation framework has been established, and the criteria are categorized into three levels based on their importance, which can help assess the extent to which a candidate biomarker may be feasible, valid, and useful for a specific use context.

Validity and applicability of the global leadership initiative on malnutrition criteria in non-dialysis patients with chronic kidney disease.

Introduction: There are no standardized assessment criteria for selecting nutritional risk screening tools or indicators to assess reduced muscle mass (RMM) in the Global Leadership Initiative on Malnutrition (GLIM) criteria. We aimed to compare the consistency of different GLIM criteria with Subjective Global Assessment (SGA) and protein-energy wasting (PEW). Methods: In this study, nutritional risk screening 2002 first four questions (NRS-2002-4Q), Nutritional Risk Screening 2002 (NRS-2002), Malnutrition Universal Screening Tool (MUST), and Mini-Nutritional Assessment Short-Form (MNA-SF) tools were used as the first step of nutritional risk screening for the GLIM. The RMM is expressed using different metrics. The SGA and PEW were used to diagnose patients and classify them as malnourished and non-malnourished. Kappa (κ) tests were used to compare the concordance between the SGA, PEW, and GLIM of each combination of screening tools. Results: A total of 157 patients were included. Patients with Chronic kidney disease (CKD) stage 1-3 accounted for a large proportion (79.0%). The prevalence rates of malnutrition diagnosed using the SGA and PEW were 18.5% and 19.7%, respectively. The prevalence of GLIM-diagnosed malnutrition ranges from 5.1% to 37.6%, depending on the different screening methods for nutritional risk and the different indicators denoting RMM. The SGA was moderately consistent with the PEW (κ = 0.423, p < 0.001). The consistency among the GLIM, SGA, and PEW was generally low. Using the NRS-2002-4Q to screen for nutritional risk, GLIM had the best agreement with SGA and PEW when skeletal muscle index (SMI), fat-free mass index (FFMI), and hand grip strength (HGS) indicated a reduction in muscle mass (SGA: κ = 0.464, 95% CI 0.28-0.65; PEW: κ = 0.306, 95% CI 0.12-0.49). Conclusion: The concordance between the GLIM criteria and the SGA and PEW depended on the screening tool used in the GLIM process. The inclusion of RMM in the GLIM framework is important. The addition of HGS could further improve the performance of the GLIM standard compared to the use of body composition measurements.

Correlation between retinal vascular geometric parameters and pathologically diagnosed type 2 diabetic nephropathy.

Background: Diabetic nephropathy (DN) and diabetic retinopathy (DR) are common microvascular complications of diabetes. The purpose of this study was to investigate the correlation between retinal vascular geometric parameters and pathologically diagnosed type 2 DN and to determine the capacity of retinal vascular geometric parameters in differentiating DN from non-diabetic renal disease (NDRD). Methods: The study participants were adult patients with type 2 diabetes mellitus (T2DM) and chronic kidney disease who underwent a renal biopsy. Univariate and multivariable regression analyses were performed to evaluate associations between retinal vessel geometry parameters and pathologically diagnosed DN. Multivariate binary logistic regression analyses were performed to establish a differential diagnostic model for DN. Results: In total, 403 patients were examined in this cross-sectional study, including 152 (37.7%) with DN, 157 (39.0%) with NDRD and 94 (23.3%) with DN combined with NDRD. After univariate logistic regression, total vessel fractal dimension, arteriolar fractal dimension and venular fractal dimension were all found to be associated with DN. In multivariate analyses adjusting for age, sex, blood pressure, diabetes, DR and other factors, smaller retinal vascular fractal dimensions were significantly associated with DN (P < .05). We developed a differential diagnostic model for DN combining traditional clinical indicators and retinal vascular geometric parameters. The area under the curve of the model established by multivariate logistic regression was 0.930. Conclusions: Retinal vessel fractal dimension is of great significance for the rapid and non-invasive differentiation of DN. Incorporating retinal vessel fractal dimension into the diagnostic model for DN and NDRD can improve the diagnostic efficiency.

DNA methylation and whole-genome transcription analysis in CD4+ T cells from systemic lupus erythematosus patients with or without renal damage.

BACKGROUND: Lupus nephritis (LN) is the most common cause of kidney injury in systemic lupus erythematosus (SLE) patients and is associated with increased mortality. DNA methylation, one of the most important epigenetic modifications, has been reported as a key player in the pathogenesis of SLE. Hence, our article aimed to explore DNA methylation in CD4+ T cells from LNs to identify additional potential biomarkers and pathogenic genes involved in the progression of LN. METHODS: Our study enrolled 46 SLE patients with or without kidney injury and 23 healthy controls from 2019 to 2022. CD4+ T cells were sorted for DNA methylation genotyping and RNA-seq. Through bioinformatics analysis, we identified the significant differentially methylated CpG positions (DMPs) only in the LN group and validated them by Bisulfite PCR. Integration analysis was used to screen for differentially methylated and expressed genes that might be involved in the progression of LN, and the results were analyzed via cell experiments and flow cytometry. RESULTS: We identified 243 hypomethylated sites and 778 hypermethylated sites only in the LN cohort. Three of these DMPs, cg08332381, cg03297029, and cg16797344, were validated by Bisulfite PCR and could be potential biomarkers for LN. Integrated analysis revealed that the expression of BCL2L14 and IFI27 was regulated by DNA methylation, which was validated by azacytidine (5-aza) treatment. The overexpression of BCL2L14 in CD4+ T cells might induce renal fibrosis and inflammation by regulating the differentiation and function of Tfh cells. CONCLUSION: Our study identified novel aberrant DMPs in CD4+ T cells only in LN patients and DNA methylation-regulated genes that could be potential LN biomarkers. BCL2L14 is likely involved in the progression of LN and might be a treatment target.