Chronic kidney disease: Biomarker diagnosis to therapeutic targets

Differentiated metabolomic profiling reveals plasma amino acid signatures for primary glomerular disease

Primary glomerular disease (PGD) is an idiopathic cause of renal glomerular lesions that is characterized by proteinuria or hematuria and is the leading cause of chronic kidney disease (CKD). The identification of circulating biomarkers for the diagnosis of PGD requires a thorough understanding of the metabolic defects involved. In this study, ultra-high performance liquid chromatography-tandem mass spectrometry was performed to characterize the amino acid (AA) profiles of patients with pathologically diagnosed PGD, including minimal change disease (MCD), focal segmental glomerular sclerosis (FSGS), membranous nephropathy, and immunoglobulin A nephropathy. The plasma concentrations of asparagine and ornithine were low, and that of aspartic acid was high, in patients with all the pathologic types of PGD, compared to healthy controls. Two distinct diagnostic models were generated using the differential plasma AA profiles using logistic regression and receiver operating characteristic analyses, with areas under the curves of 1.000 and accuracies up to 100.0% in patients with MCD and FSGS. In conclusion, the progression of PGD is associated with alterations in AA profiles, The present findings provide a theoretical basis for the use of AAs as a non-invasive, real-time, rapid, and simple biomarker for the diagnosis of various pathologic types of PGD.

Dental implant considerations in patients with systemic diseases: An updated comprehensive review

BACKGROUND

Various medical conditions and the drugs used to treat them have been shown to impede or complicate dental implant surgery. It is crucial to carefully monitor the medical status and potential post-operative complications of patients with systemic diseases, particularly elderly patients, to minimize the risk of health complications that may arise.

AIM

The purpose of this study was to review the existing evidence on the viability of dental implants in patients with systemic diseases and to provide practical recommendations to achieve the best possible results in the corresponding patient population.

METHODS

The information for our study was compiled using data from PubMed, Scopus, Web of Science and Google Scholar databases and searched separately for each systemic disease included in our work until October 2023. An additional manual search was also performed to increase the search sensitivity. Only English-language publications were included and assessed according to titles, abstracts and full texts.

RESULTS

In total, 6784 studies were found. After checking for duplicates and full-text availability, screening for the inclusion criteria and manually searching reference lists, 570 articles remained to be considered in this study.

CONCLUSION

In treating patients with systemic conditions, the cost-benefit analysis should consider the patient's quality of life and expected lifespan. The success of dental implants depends heavily on ensuring appropriate maintenance therapy, ideal oral hygiene standards, no smoking and avoiding other risk factors. Indications and contraindications for dental implants in cases of systemic diseases are yet to be more understood; broader and hardcore research needs to be done for a guideline foundation.

Expanding the Role of Chiral Drugs and Chiral Nanomaterials as a Potential Therapeutic Tool

Chirality, the property of molecules having mirror-image forms, plays a crucial role in pharmaceutical and biomedical research. This review highlights its growing importance, emphasizing how chiral drugs and nanomaterials impact drug effectiveness, safety, and diagnostics. Chiral molecules serve as precise diagnostic tools, aiding in accurate disease detection through unique biomolecule interactions. The article extensively covers chiral drug applications in treating cardiovascular diseases, CNS disorders, local anesthesia, anti-inflammatories, antimicrobials, and anticancer drugs. Additionally, it explores the emerging field of chiral nanomaterials, highlighting their suitability for biomedical applications in diagnostics and therapeutics, enhancing medical treatments.

Optimization and validation of metabolomics methods for feline urine and serum towards application in veterinary medicine

BACKGROUND

Metabolomics is an emerging and powerful technology that offers a comprehensive view of an organism's physiological status. Although widely applied in human medicine, it is only recently making its introduction in veterinary medicine. As a result, validated metabolomics protocols in feline medicine are lacking at the moment. Since biological interpretation of metabolomics data can be misled by the extraction method used, species and matrix-specific optimized and validated metabolomic protocols are sorely needed.

RESULTS

Systematic optimization was performed using fractional factorial experiments for both serum (n = 57) and urine (n = 24), evaluating dilution for both matrices, and aliquot and solvent volume, protein precipitation time and temperature for serum. For the targeted (n = 76) and untargeted (n = 1949) validation of serum respectively, excellent instrumental, intra-assay and inter-day precision were observed (CV ≤ 15% or 30%, respectively). Linearity deemed sufficient both targeted and untargeted (R2 ≥ 0.99 or 0.90, respectively). An appropriate targeted recovery between 70 and 130% was achieved. For the targeted (n = 69) and untargeted (n = 2348) validation of the urinary protocol, excellent instrumental and intra-assay precision were obtained (CV ≤ 15% or 30%, respectively). Subsequently, the discriminative ability of our metabolomics methods was confirmed for feline chronic kidney disease (CKD) by univariate statistics (n = 41 significant metabolites for serum, and n = 55 for urine, p-value<0.05) and validated OPLS-DA models (R2(Y) > 0.95, Q2(Y) > 0.65, p-value<0.001 for both matrices).

SIGNIFICANCE

This study is the first to present an optimized and validated wholistic metabolomics methods for feline serum and urine using ultra-high performance liquid chromatography coupled to quadrupole-Orbitrap high-resolution mass spectrometry. This robust methodology opens avenues for biomarker panel selection and a deeper understanding of feline CKD pathophysiology and other feline applications.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Relationship between the longitudinal trajectory of the triglyceride-glucose index and the development of CKD: an 8-year retrospective longitudinal cohort study

Background

The triglyceride-glucose (TyG) index, a simple surrogate marker of insulin resistance, is significantly associated with chronic kidney disease (CKD). However, there is limited research on the longitudinal trajectory of TyG index over time and its relationship with CKD.

Objective

To analyse the characteristics of the longitudinal trajectory of the TyG index over time and its association with the development of CKD in a health check-up population.

Methods

Participants who underwent at least three annual health check-ups at the Health Management Center of Sichuan Provincial People's Hospital from 2015 to 2022 were included in this retrospective cohort study. The TyG index was calculated as ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]. The latent class mixed model (LCMM) was used to identify the TyG index trajectory of the study population. A Cox proportional hazard model was used to estimate the CKD incidence risk in different quartile groups and the association of changes in the TyG index trajectory with the development of CKD.

Results

A total of 4,921 participants were included in this study, and they were divided into four groups according to the quartiles of the baseline TyG index: Q1 (5.43-6.66), Q2 (6.67-7.04), Q3 (7.05-7.43), and Q4 (7.43-9.97). There was no difference in the risk of CKD occurrence among the TyG groups. Three different TyG index trajectories were identified in this study: a high-level group, middle-level stable group and low-level stable group, respectively. The incidence rate of CKD in the high-level TyG index trajectory group was 2.399 times greater than that in the low-level stable trajectory group (HR=2.399, 95% CI 1.167-4.935).

Conclusion

Individuals with long-term exposure to high TyG index levels had a significantly greater risk of CKD. Routine monitoring of the TyG index and its longitudinal trend will aid in the risk stratification of CKD in the general population and will be helpful for CKD prevention and targeted management.

Relationship between heavy metal concentrations and Chronic kidney disease in population of Hoveyzeh cohort study: A cross-sectional study in Iran

BACKGROUND

Chronic kidney disease (CKD) is a multifactorial disease whose prevalence is increasing worldwide. CKD affects 700 million to 1 billion people worldwide, with a prevalence of 9.1% to 13.4%. In Iran, the reported prevalence of CKD is 15.14%, even higher than the global prevalence. Some studies introduced heavy metals as possible risk factors of CKD. We conducted the first study in Iran to examine the relationship between 10 selected urinary heavy metals and CKD in the Hovayzeh cohort study population.

METHODS

In this cross-sectional study, urine samples were collected from two groups of ca ses (suffering from CKD) and controls (without CKD) with equal size (47 people each). Analysis of the 10 sellected heavy metals in the samples was conducted using inductively coupled plasma emission spectroscopy. Basic Information was obtained from the Howayizeh Cohort Study Center. The data was analyzed using SPSS-26 and Excel-2016 software.

RESULTS

There were no significant differences between urinary heavy metal concentrations of case and control groups (P < 0.05). While, the concentration of As, Cr, Cu, Mn, and Ni exceeded the reference limits of Germany, Canada, England, and Belgium. Se and Cd also surpassed the reference limits of England. After adjusting for confounding variables for each μg/l increase in urinary Cd, Ni, Pb, and Se the OR of CKD increased by 20.2%, 4.8%, 3.1%, and 2.6%, respectively. Although, these relationships were not statistically significant. In addition, two groups of heavy metals had a positive and significant correlation: (1) Se, Zn, As, Cu, and Cr; (2) Pb, Cd, and As; and (3) Cd and Ni.

CONCLUSION

we found no significant relationship between urinary heavy metal and CKD. However, there was significant positive correlation in some of urinary heavy metals may indicate their shared resources. Furthermore, the concentration of most heavy metals in the urine of the participants was higher than the reference limits of these metals in the urine of healthy people from other countries. Thus, the elevated levels of these metals could still pose a risk to human health. Therefore, it is necessary to conduct prospective studies with a larger sample size in this area.

Blood biomarkers improve the prediction of prevalent and incident severe chronic kidney disease

BACKGROUND

The prevalence of chronic kidney disease (CKD) is high. Identification of cases with CKD or at high risk of developing it is important to tailor early interventions. The objective of this study was to identify blood metabolites associated with prevalent and incident severe CKD, and to quantify the corresponding improvement in CKD detection and prediction.

METHODS

Data from four cohorts were analyzed: Singapore Epidemiology of Eye Diseases (SEED) (n = 8802), Copenhagen Chronic Kidney Disease (CPH) (n = 916), Singapore Diabetic Nephropathy (n = 714), and UK Biobank (UKBB) (n = 103,051). Prevalent CKD (stages 3-5) was defined as estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2; incident severe CKD as CKD-related mortality or kidney failure occurring within 10 years. We used multivariable regressions to identify, among 146 blood metabolites, those associated with CKD, and quantify the corresponding increase in performance.

RESULTS

Chronic kidney disease prevalence (stages 3-5) and severe incidence were 11.4% and 2.2% in SEED, and 2.3% and 0.2% in UKBB. Firstly, phenylalanine (Odds Ratio [OR] 1-SD increase = 1.83 [1.73, 1.93]), tyrosine (OR = 0.75 [0.71, 0.79]), docosahexaenoic acid (OR = 0.90 [0.85, 0.95]), citrate (OR = 1.41 [1.34, 1.47]) and triglycerides in medium high density lipoprotein (OR = 1.07 [1.02, 1.13]) were associated with prevalent stages 3-5 CKD. Mendelian randomization analyses suggested causal relationships. Adding these metabolites beyond traditional risk factors increased the area under the curve (AUC) by 3% and the sensitivity by 7%. Secondly, lactate (HR = 1.33 [1.08, 1.64]) and tyrosine (HR = 0.74 [0.58, 0.95]) were associated with incident severe CKD among individuals with eGFR < 90 mL/min/1.73 m2 at baseline. These metabolites increased the c-index by 2% and sensitivity by 5% when added to traditional risk factors.

CONCLUSION

The performance improvements of CKD detection and prediction achieved by adding metabolites to traditional risk factors are modest and further research is necessary to fully understand the clinical implications of these findings.

Metabolic Profiling as an Approach to Differentiate T-Cell Acute Lymphoblastic Leukemia Cell Lines Belonging to the Same Genetic Subgroup

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive tumor mainly affecting children and adolescents. It is driven by multiple genetic mutations that together define the leukemic phenotype. Interestingly, based on genetic alterations and/or deregulated expression, at least six genetic subgroups have been recognized. The TAL/LMO subgroup is one of the most represented genetic subgroups, characterizing 30-45% of pediatric T-ALL cases. The study of lipid and metabolic profiles is increasingly recognized as a valuable tool for comprehending the development and progression of tumors. In this study, metabolic and lipidomic analysis via LC/MS have been carried out on four T-ALL cell lines belonging to the TAL/LMO subgroup (Jurkat, Molt-4, Molt-16, and CCRF-CEM) to identify new potential metabolic biomarkers and to provide a subclassification of T-ALL cell lines belonging to the same subgroup. A total of 343 metabolites were annotated, including 126 polar metabolites and 217 lipid molecules. The statistical analysis, for both metabolic and lipid profiles, shows significant differences and similarities among the four cell lines. The Molt-4 cell line is the most distant cell line and CCRF-CEM shows a high activity in specific pathways when compared to the other cell lines, while Molt-16 and Jurkat show a similar metabolic profile. Additionally, this study highlighted the pathways that differ in each cell line and the possible enzymes involved using bioinformatic tools, capable of predicting the pathways involved by studying the differences in the metabolic profiles. This experiment offers an approach to differentiate T-ALL cell lines and could open the way to verify and confirm the obtained results directly in patients.

Renoprotective strategies

Kidney disease remains a condition with an increasing incidence, high morbidity and mortality associated with cardiovascular events. The incidence of end-stage renal disease is expected to increase. Despite of the technical improvement, dialysis never achieved a full clearance of the blood dialysis. Therefore, the demand for new renoprotective measures has never been greater. Here, we report new strategies for preventing renal damage.

Cross-sectional analyses of metabolites across biological samples mediating dietary acid load and chronic kidney disease

Chronic kidney disease (CKD) is a major public health burden, with dietary acid load (DAL) and gut microbiota playing crucial roles. As DAL can affect the host metabolome, potentially via the gut microbiota, we cross-sectionally investigated the interplay between DAL, host metabolome, gut microbiota, and early-stage CKD (TwinsUK, n = 1,453). DAL was positively associated with CKD stage G1-G2 (Beta (95% confidence interval) = 0.34 (0.007; 0.7), p = 0.046). After adjusting for covariates and multiple testing, we identified 15 serum, 14 urine, 8 stool, and 7 saliva metabolites, primarily lipids and amino acids, associated with both DAL and CKD progression. Of these, 8 serum, 2 urine, and one stool metabolites were found to mediate the DAL-CKD association. Furthermore, the stool metabolite 5-methylhexanoate (i7:0) correlated with 26 gut microbial species. Our findings emphasize the gut microbiota's therapeutic potential in countering DAL's impact on CKD through the host metabolome. Interventional and longitudinal studies are needed to establish causality.

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

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

Targeted metabolomic analysis of serum amino acids in heart failure patients

Heart failure (HF) has been recognized as a global epidemic with high rates of morbidity, hospitalization, and mortality. The role of amino acids, which provide the body with energy, in the development of HF is still unclear. The aim of this study was to explore changes in serum amino acids in patients with HF and identify potential biomarkers. First, the serum amino acid metabolism profiles of 44 patients with HF and 30 healthy controls (Con) were quantitatively measured. Then, candidate markers were identified through the utilization of T test, multivariate statistical analysis, and receiver operating characteristic (ROC) curve analysis. The results found that there were 11 amino acid levels that were significantly different between patients with HF and Con. Based on ROC curve analysis, the biomarkers of eight amino acids (Glutamic acid, Taurine, L-aspartic acid, L-ornithine, Ethanolamine, L-Serine, L-Sarcosine, and Cysteine) showed high sensitivity and specificity (AUC > 0.90), and binary logistic regression analysis was used in MetaboAnalyst 5.0. Among the amino acids examined, six exhibited notable alterations in accordance with the severity of HF. In conclusion, this study cannot only provide clinicians with an objective diagnostic approach for the early identification of HF, but also enhances comprehension of the underlying mechanisms involved in the pathogenesis of HF.

Design and discovery of a highly potent ultralong-acting GLP-1 and glucagon co-agonist for attenuating renal fibrosis

The role of co-agonists of glucagon-like peptide-1 receptor (GLP-1R) and glucagon receptor (GCGR) in chronic kidney disease (CKD) remains unclear. Herein we found that GLP-1R and GCGR expression levels were lower in the kidneys of mice with CKD compared to healthy mice and were correlated with disease severity. Interestingly, GLP-1R or GCGR knockdown aggravated the progression of kidney injury in both diabetic db/db mice and non-diabetic mice undergoing unilateral ureteral obstruction (UUO). Based on the importance of GLP-1R and GCGR in CKD, we reported a novel monomeric peptide, 1907-B, with dual-agonism on both GLP-1R and GCGR. The data confirmed that 1907-B had a longer half-life than long-acting semaglutide in rats or cynomolgus monkeys (∼2-3 fold) and exhibited better therapeutic contribution to CKD than best-in-class monoagonists, semaglutide, or glucagon, in db/db mice and UUO mice. Various lock-of-function models, including selective pharmacological activation and genetic knockdown, confirmed that 1907-B's effects on ameliorating diabetic nephropathy in db/db mice, as well as inhibiting kidney fibrosis in UUO mice, were mediated through GLP-1 and glucagon signaling. These findings highlight that 1907-B, a novel GLP-1R and GCGR co-agonist, exerts multifactorial improvement in kidney injuries and is an effective and promising therapeutic option for CKD treatment.

Identification of novel serum metabolic signatures to predict chronic kidney disease among Chinese elders using UPLC-Orbitrap-MS

BACKGROUND

Chronic kidney disease (CKD) is a major public health concern. However, validated and broadly applicable biomarkers for early CKD diagnosis are currently not available. We aimed to identify serum metabolic signatures at an early stage of CKD to provide a reference for future investigations into the early diagnostic biomarkers.

METHODS

Serum metabolites were extracted from 65 renal dysfunction (RD) patients and 121 healthy controls (discovery cohort: 12 RD patients and 55 health participants; validation cohort: 53 RD patients and 66 health participants). Metabolite extracts were analyzed by ultraperformance liquid chromatography coupled with quadrupole-electrostatic field orbital trap mass spectrometry (UPLC-QE-Orbitrap MS) for untargeted metabolomics. Orthogonal partial least squares-discriminant analysis (OPLS-DA) was performed to detect different compounds between groups. Receiver operating characteristic (ROC) curve analysis was carried out to determine the diagnostic value of the validated differential metabolites between groups. We referred to the Kyoto Encyclopedia of Gene and Genomes (KEGG) to elucidate the metabolic pathways of the validated differential metabolites.

RESULTS

A total of 22 and 23 metabolites had significantly different abundances in the discovery and validation cohort, respectively. Six of them (creatinine, L-proline, citrulline, butyrylcarnitine, 1-methylhistidine, and valerylcarnitine) in the RD group was more abundant than that of the health group in both cohorts. The combination of the six validated differential metabolites were able to accurately detect RD (AUC 0.86). Three of the six metabolites are involved in the metabolism of arginine and proline.

CONCLUSIONS

The present study highlights that creatinine, L-proline, citrulline, butyrylcarnitine, 1-methylhistidine, and valerylcarnitine are metabolite indicators with potential predictive value for CKD.

Downregulating ANGPTL3 by miR-144-3p promoted TGF-β1-induced renal interstitial fibrosis via activating PI3K/AKT signaling pathway

Despite observations of decreased ANGPTL3 (angiopoietin-like protein 3) levels in tubular atrophy and renal interstitial fibrosis (RIF), its functional implications and regulatory mechanisms in RIF remain unclear. This investigation employed unilateral ureteral obstruction (UUO) mice as in vivo model and human proximal kidney tubuloepithelial HK-2 cells under TGF-β1 treatment as in vitro model to explore RIF. The RIF extent was evaluated using H & E staining and Masson's trichrome staining. There was a significant decrease in ANGPTL3 levels and an increase in miR-144-3p, accompanied by heightened expressions of α-SMA, p-PI3K, p-AKT, Collagen I, and Fibronectin in the UUO mice and HK-2 cells treated with TGF-β1. Enhancing ANGPTL3 expression or suppressing miR-144-3p mitigated TGF-β1-induced cellular apoptosis, inflammation, and PI3K/AKT signaling pathway activation, as evidenced by altered levels of α-SMA, Collagen I, Fibronectin, and associated signaling markers. Using a bioinformatics approach, a miR-144-3p binding site was discovered on the ANGPTL3 mRNA, and this finding was subsequently confirmed through luciferase reporter assay. In HK-2 cells stimulated with TGF-β1, the suppression of ANGPTL3 negated the effects of inhibiting miR-144-3p. Under comparable conditions, the use of LY294002, an inhibitor of the PI3K/AKT pathway, nullified the effects caused by the knockdown of ANGPTL3. Collectively, these findings indicate that miR-144-3p exacerbates RIF through PI3K/AKT pathway activation by targeting ANGPTL3, highlighting a novel potential therapeutic target for RIF management.

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

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

Dioscorea nipponica Makino: A comprehensive review of its chemical composition and pharmacology on chronic kidney disease

Chronic kidney disease (CKD) is a widespread ailment that significantly impacts global health. It is characterized by high prevalence, poor prognosis, and substantial healthcare costs, making it a major public health concern. The current clinical treatments for CKD are not entirely satisfactory, leading to a high demand for alternative therapeutic options. Chinese herbal medicine, with its long history, diverse varieties, and proven efficacy, offers a promising avenue for exploration. One such Chinese herbal medicine, Dioscorea nipponica Makino (DNM), is frequently used to treat kidney diseases. In this review, we have compiled studies examining the mechanisms of action of DNM in the context of CKD, focusing on five primary areas: improvement of oxidative stress, inhibition of renal fibrosis, regulation of metabolism, reduction of inflammatory response, and regulation of autophagy.

Network Pharmacology Analysis and Machine-Learning Models Confirmed the Ability of YiShen HuoXue Decoction to Alleviate Renal Fibrosis by Inhibiting Pyroptosis

Purpose

YiShen HuoXue decoction (YSHXD) is a formulation that has been used clinically for the treatment of renal fibrosis (RF) for many years. We aimed to clarify therapeutic effects of YSHXD against RF and potential pharmacological mechanisms.

Materials and Methods

We used network pharmacology analysis and machine-learning to screen the core components and core targets of YSHXD against RF, followed by molecular docking and molecular dynamics simulations to confirm the reliability of the results. Finally, we validated the network pharmacology analysis experimentally in HK-2 cells and a rat model of RF established by unilateral ureteral ligation (UUO).

Results

Quercetin, kaempferol, luteolin, beta-sitosterol, wogonin, stigmasterol, isorhamnetin, baicalein, and dihydrotanshinlactone progesterone were identified as the main active components of YSHXD in the treatment of unilateral ureteral ligation-induced RF, with IL-6, IL1β, TNF, AR, and PTGS2 as core target proteins. Molecular docking and molecular dynamics simulations further confirmed the relationship between compounds and target proteins. The potential molecular mechanism of YSHXD predicted by network pharmacology analysis was confirmed in HK-2 cells and UUO rats. YSHXD downregulated NLRP3, ASC, NF-κBp65, Caspase-1, GSDMD, PTGS2, IL-1β, IL-6, IL-18, TNF-α, α-SMA and upregulated HGF, effectively alleviating the RF process.

Conclusion

YSHXD exerts important anti-inflammatory and anti-cellular inflammatory necrosis effects by inhibiting the NLRP3/caspase-1/GSDMD-mediated pyroptosis pathway, indicating that YSHXD represents a new strategy and complementary approach to RF therapy.

Identifying key genes for diabetic kidney disease by bioinformatics analysis

BACKGROUND

There are no reliable molecular targets for early diagnosis and effective treatment in the clinical management of diabetic kidney disease (DKD). To identify novel gene factors underlying the progression of DKD.

METHODS

The public transcriptomic datasets of the alloxan-induced DKD model and the streptozotocin-induced DKD model were retrieved to perform an integrative bioinformatic analysis of differentially expressed genes (DEGs) shared by two experimental animal models. The dominant biological processes and pathways associated with DEGs were identified through enrichment analysis. The expression changes of the key DEGs were validated in the classic db/db DKD mouse model.

RESULTS

The downregulated and upregulated genes in DKD models were uncovered from GSE139317 and GSE131221 microarray datasets. Enrichment analysis revealed that metabolic process, extracellular exosomes, and hydrolase activity are shared biological processes and molecular activity is altered in the DEGs. Importantly, Hmgcs2, angptl4, and Slco1a1 displayed a consistent expression pattern across the two DKD models. In the classic db/db DKD mice, Hmgcs2 and angptl4 were also found to be upregulated while Slco1a1 was downregulated in comparison to the control animals.

CONCLUSIONS

In summary, we identified the common biological processes and molecular activity being altered in two DKD experimental models, as well as the novel gene factors (Hmgcs2, Angptl4, and Slco1a1) which may be implicated in DKD. Future works are warranted to decipher the biological role of these genes in the pathogenesis of DKD.

Association between estimated glomerular filtration rate slope and cardiovascular disease among individuals with and without diabetes: a prospective cohort study

BACKGROUND

Previous studies have reported an association between a significant decline in estimated glomerular filtration rate (eGFR) over time and an increased risk of cardiovascular disease (CVD). This study aimed to investigate the association between the eGFR slope and CVD among individuals with and without diabetes.

METHODS

This prospective cohort study was conducted within the Tehran Lipid and Glucose Study (TLGS) framework. We studied 6919 adults aged 20-70 years, including 985 with diabetes and 5934 without diabetes. The eGFR slope was determined based on repeated measurements of eGFR through linear mixed-effects models. A multivariable Cox proportional hazard model was employed to evaluate the association between eGFR slope, both in continuous and categorical form, and the risk of CVD.

RESULTS

The slopes of eGFR exhibited a bell-shaped distribution, with a mean (standard deviation (SD)) of -0.63 (0.13) and - 0.70 (0.14) ml/min per 1.73 m2 per year in individuals with and without diabetes, respectively. During a median follow-up of 8.22 years, following the 9-year eGFR slope ascertainment period, a total of 551 CVD events (195 in patients with diabetes) were observed. Among individuals with diabetes, a steeper decline in eGFR slope was significantly associated with a higher risk of CVD events, even after adjusting for baseline eGFR, demographic factors, and traditional risk factors for CVD; slopes of (-1.05 to -0.74) and (-0.60 to -0.52) were associated with 2.12 and %64 higher risks for CVD, respectively, compared with a slope of (-0.51 to 0.16). Among individuals without diabetes, the annual eGFR slope did not show a significant association with the risk of CVD.

CONCLUSION

Monitoring the eGFR slope may serve as a potential predictor of CVD risk in individuals with diabetes.

CKD Urine Metabolomics: Modern Concepts and Approaches

One of the primary challenges regarding chronic kidney disease (CKD) diagnosis is the absence of reliable methods to detect early-stage kidney damage. A metabolomic approach is expected to broaden the current diagnostic modalities by enabling timely detection and making the prognosis more accurate. Analysis performed on urine has several advantages, such as the ease of collection using noninvasive methods and its lower protein and lipid content compared with other bodily fluids. This review highlights current trends in applied analytical methods, major discoveries concerning pathways, and investigated populations in the context of urine metabolomic research for CKD over the past five years. Also, we are presenting approaches, instrument upgrades, and sample preparation modifications that have improved the analytical parameters of methods. The onset of CKD leads to alterations in metabolism that are apparent in the molecular composition of urine. Recent works highlight the prevalence of alterations in the metabolic pathways related to the tricarboxylic acid cycle and amino acids. Including diverse patient cohorts, using numerous analytical techniques with modifications and the appropriate annotation and explanation of the discovered biomarkers will help develop effective diagnostic models for different subtypes of renal injury with clinical applications.

New Insights into the Nephroprotective Potential of Lercanidipine

Kidneys are responsible for many crucial biological processes in the human body, including maintaining the water-electrolyte balance, pH, and blood pressure (BP), along with the elimination of toxins. Despite this, chronic kidney disease (CKD), which affects more and more people, is a disease that develops insidiously without causing any symptoms at first. The main purpose of this article is to summarize the existing literature on lercanidipine, with a particular focus on its nephroprotective properties. Lercanidipine is a third-generation dihydropyridine (DHP) blocker of calcium channels, and as such it possesses unique qualities such as high lipophilicity and high vascular selectivity. Furthermore, it acts by reversibly inhibiting L-type and T-type calcium channels responsible for exerting positive renal effects. It has been shown to reduce tissue inflammation and tubulointerstitial fibrosis, contributing to a decrease in proteinuria. Moreover, it exhibited antioxidative effects and increased expression of molecules responsible for repairing damaged tissues. It also decreased cell proliferation, preventing thickening of the vascular lumen. This article summarizes studies simultaneously comparing the effect of lercanidipine with other antihypertensive drugs. There is still a lack of studies on the medications used in patients with CKD, and an even greater lack of studies on those used in patients with concomitant hypertension. Therefore, further studies on lercanidipine and its potential in hypertensive patients with coexisting CKD are required.

Biomarker identification and pathway analysis of Astragalus membranaceus and Curcuma zedoaria couplet medicines on adenine-induced chronic kidney disease in rats based on metabolomics

Background: Chronic kidney disease (CKD) is usually insidious, and most affected individuals are asymptomatic until the disease becomes advanced. The effective treatment of CKD would rely on the incorporation of multidisciplinary approaches. Astragalus membranaceus (AM) and Curcuma zedoaria (CZ) have been widely used in the treatment of CKD. However, the mechanism of AM and CZ in the treatment of CKD is still unclear.

Methods: This study was designed to evaluate the effects of AM and CZ on adenine-induced rats and to investigate the underlying mechanism by using metabolomic analysis. Addition of 0.75% adenine to the diet of rats for 3 weeks induced the animal model of CKD. The rats in the treatment group were treated with AM and CZ (2.1 g/kg/day) for 4 weeks. Blood and kidney samples were collected for biochemical and histological examination. Ultra-high-performance liquid chromatography/Q Exactive HFX mass spectrometer (UHPLC-QE-MS) was applied to analyze metabolic profiling variations in the kidney.

Results: The results showed that AM and CZ could significantly reduce serum creatinine (Scr) and blood urea nitrogen (BUN) levels in CKD rats and alleviate renal pathological injury. By comparing the endogenous components of the normal group and the model group in positive ion mode and negative ion mode, a total of 365 and 155 different metabolites were screened, respectively. A total of 117 and 73 metabolites with significantly different expressions were identified between model group and AM and CZ group in positive ion mode and negative ion mode, respectively. The pivotal pathways affected by AM and CZ included nicotinate and nicotinamide metabolism, and glycine, serine and threonine metabolism. Furthermore, significant changes in metabolites in CKD rats after AM and CZ therapies were observed, including L-Threonine, D-pantothenic acid, and nicotinamide. Moreover, we found that AM and CZ significantly reduced renal fibrosis and inflammation in CKD rats, which may be related to the regulation of SIRT1/JNK signaling pathway.

Conclusion: In conclusion, AM and CZ significantly reduced renal fibrosis and inflammation in CKD rats, which may be related to the regulation of SIRT1/JNK signaling pathway. Furthermore, L-Threonine, D-pantothenic acid, and nicotinamide may be potential biomarkers for the progression and treatment of CKD.

Pretransplant systemic metabolic profiles in allogeneic hematopoietic stem cell transplant recipients - identification of patient subsets with increased transplant-related mortality

Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is used in the treatment of high-risk acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS); however, the treatment has high risk of severe transplantation-related mortality (TRM). In this study, we examined pretransplantation serum samples derived from 92 consecutive allotransplant recipients with AML or MDS. Using nontargeted metabolomics, we identified 1274 metabolites including 968 of known identity (named biochemicals). We further investigated metabolites that differed significantly when comparing patients with and without early extensive fluid retention, pretransplantation inflammation (both being associated with increased risk of acute graft-versus-host disease [GVHD]/nonrelapse mortality) and development of systemic steroid-requiring acute GVHD (aGVHD). All three factors are associated with TRM and were also associated with significantly altered amino acid metabolism, although there was only a minor overlap between these three factors with regard to significantly altered individual metabolites. Furthermore, steroid-requiring aGVHD was especially associated with altered taurine/hypotaurine, tryptophan, biotin, and phenylacetate metabolism together with altered malate-aspartate shuttle and urea cycle regulation. In contrast, pretransplantation inflammation was associated with a weaker modulation of many different metabolic pathways, whereas extensive fluid retention was associated with a weaker modulation of taurine/hypotaurine metabolism. An unsupervised hierarchical cluster analysis based on the 13 most significantly identified metabolites associated with aGVHD identified a patient subset with high metabolite levels and increased frequencies of MDS/MDS-AML, steroid-requiring aGVHD and early TRM. On the other hand, a clustering analysis based on metabolites that were significantly altered for aGVHD, inflammation, and fluid retention comparison groups identified a patient subset with a highly significant association with TRM. Our study suggests that the systemic pretransplantation metabolic profiles can be used to identify patient subsets with an increased frequency of TRM.

Untargeted plasma 1H NMR-based metabolomic profiling in different stages of chronic kidney disease

Chronic kidney disease (CKD) is a serious public health issue affecting thousands of people worldwide. CKD diagnosis is usually made by Estimated Glomerular Filtration Rate (eGFR) and albuminuria, which limit the knowledge of the mechanisms behind CKD progression. The aim of the present study was to identify changes in the metabolomic profile that occur as CKD advances. In this sense, 77 plasma samples from patients with CDK were evaluated by 1D and 2D Nuclear Magnetic Resonance Spectroscopy (NMR). The NMR data showed significant changes in the metabolomic profile of CKD patients and the control group. Principal component analysis (PCA) clustered CKD and control patients into three distinct groups, control, stage 1 (G1)-stage 4 (G4) and stage 5 (G5). Lactate, glucose, acetate and creatinine were responsible for discriminating the control group from all the others CKD stages. Valine, alanine, glucose, creatinine, glutamate and lactate were responsible for the clustering of G1-G4 stages. G5 was discriminated by calcium ethylenediamine tetraacetic acid, magnesium ethylenediamine tetraacetic acid, creatinine, betaine/choline/trimethylamine N-oxide (TMAO), lactate and acetate. CKD G5 plasma pool which was submitted in MetaboAnalyst 4.0 platform (MetPA) analysis and showed 13 metabolic pathways involved in CKD physiopathology. Metabolic changes associated with glycolysis and gluconeogenesis allowed discriminating between CKD and control patients. The determination of involved molecules in TMAO generation in G5 suggests an important role in this uremic toxin linked to CKD and cardiovascular diseases. The aforementioned results propose the feasibility of metabolic assessment of CKD by NMR during treatment and disease progression.

Arterial spin labeling and diffusion-weighted MR imaging: quantitative assessment of renal pathological injury in chronic kidney disease

PURPOSE

The aim of the study was to investigate the performance of arterial spin labeling (ASL), diffusion-weighted imaging (DWI), and clinical biomarkers in assessing renal pathological injury in CKD.

MATERIALS AND METHODS

Forty-five biopsy-proven CKD patients and 17 healthy volunteers underwent DWI and ASL examinations. Renal cortical blood flow (RBF) and apparent diffusion coefficient (ADC) values were acquired. Correlations between RBF, ADC, serum creatinine (SCr), estimated glomerular filtration rate (eGFR), and pathological scores were assessed. The diagnostic efficacy of SCr, eGFR, RBF, and ADC in assessing renal pathological injury was assessed by ROC curve analysis.

RESULTS

The cortical RBF, ADC, SCr, and eGFR were significantly correlated with the renal histology score (all p < 0.01). The AUC values of SCr, eGFR, RBF, and ADC were 0.705 (95% confidence interval (CI): 0.536-0.827), 0.718 (0.552-0.839), 0.823 (0.658-0.916), and 0.624 (0.451-0.786), respectively, in discriminating the minimal-mild renal pathological injury group (N = 30) from the control group (N = 17). The diagnostic ability of ASL was significantly higher than that of DWI (p = 0.049) and slightly but not significantly higher than that of eGFR and SCr (p = 0.151 and p = 0.129, respectively). When compared with that of eGFR, the sensitivity of ASL in detecting early renal injury increased from 50 to 70% (p = 0.014). However, in differentiating between the minimal-mild and moderate-severe renal injury groups (N = 15), there was no significant difference in diagnostic ability among the four parameters (all p > 0.05).

CONCLUSION

ASL is practicable for noninvasive evaluation of renal pathology, especially for predicting early renal pathological injury in CKD patients.

Integrative phosphatidylcholine metabolism through phospholipase A2 in rats with chronic kidney disease

Dysregulation in lipid metabolism is the leading cause of chronic kidney disease (CKD) and also the important risk factors for high morbidity and mortality. Although lipid abnormalities were identified in CKD, integral metabolic pathways for specific individual lipid species remain to be clarified. We conducted ultra-high-performance liquid chromatography-high-definition mass spectrometry-based lipidomics and identified plasma lipid species and therapeutic effects of Rheum officinale in CKD rats. Adenine-induced CKD rats were administered Rheum officinale. Urine, blood and kidney tissues were collected for analyses. We showed that exogenous adenine consumption led to declining kidney function in rats. Compared with control rats, a panel of differential plasma lipid species in CKD rats was identified in both positive and negative ion modes. Among the 50 lipid species, phosphatidylcholine (PC), lysophosphatidylcholine (LysoPC) and lysophosphatidic acid (LysoPA) accounted for the largest number of identified metabolites. We revealed that six PCs had integral metabolic pathways, in which PC was hydrolysed into LysoPC, and then converted to LysoPA, which was associated with increased cytosolic phospholipase A2 protein expression in CKD rats. The lower levels of six PCs and their corresponding metabolites could discriminate CKD rats from control rats. Receiver operating characteristic curves showed that each individual lipid species had high values of area under curve, sensitivity and specificity. Administration of Rheum officinale significantly improved impaired kidney function and aberrant PC metabolism in CKD rats. Taken together, this study demonstrates that CKD leads to PC metabolism disorders and that the dysregulation of PC metabolism is involved in CKD pathology.

A nomogram for predicting the 4-year risk of chronic kidney disease among Chinese elderly adults

BACKGROUND

Chronic kidney disease (CKD) has become a major public health problem across the globe, leading to various complications. This study aimed to construct a nomogram to predict the 4-year risk of CKD among Chinese adults.

METHODS

The study was based on the China Health and Retirement Longitudinal Study (CHARLS). A total of 3562 participants with complete information in CHARLS2011 and CHARLS2015 were included, and further divided into the training cohort and the validation cohort by a ratio of 7:3. Univariate and multivariate logistic regression analyses were used to select variables of the nomogram. The nomogram was evaluated by receiver-operating characteristic curve, calibration plots, and decision curve analysis (DCA).

RESULTS

In all, 2494 and 1068 participants were included in the training cohort and the validation cohort, respectively. A total of 413 participants developed CKD in the following 4 years. Five variables selected by multivariate logistic regression were incorporated in the nomogram, consisting of gender, hypertension, the estimated glomerular filtration rate (eGFR), hemoglobin, and Cystatin C. The area under curve was 0.809 and 0.837 in the training cohort and the validation cohort, respectively. The calibration plots showed agreement between the nomogram-predicted probability and the observed probability. DCA indicated that the nomogram had potential clinical use.

CONCLUSIONS

A predictive nomogram was established and internally validated in aid of identifying individuals at increased risk of CKD.

Integrated analysis of comprehensive metabolomics and network pharmacology to reveal the mechanisms of abelmoschus manihot (L.) medik. in the treatment of cisplatin-induced chronic kidney disease

Background: Abelmoschus manihot (L.) Medik (“Huangkui” in Chinese, HK) has been widely used for the treatment of kidney diseases. Nephrotoxicity is the side effect of cisplatin (CDDP), which greatly limits its clinical application. Therefore, CDDP could be used to establish the chronic kidney disease (CKD) model. However, the protective effects of HK on CDDP-induced CKD have not been investigated.

Purpose: To explore the protective effect and underlying mechanisms of HK on multiple low-dose CDDP-induced CKD in rats by the integrated analysis of serum, kidney, and urine metabolomics and network pharmacology.

Methods: The CKD model was induced by multiple low-dose CDDP. Body weight, organ index, serum biochemical, and kidney histology were examined to evaluate the effect of HK. Serum, kidney, and urine were collected and profiled by HILIC/RPLC-Q-TOF/MS-based metabolomics. Potential biomarkers (PBs) were screened according to the criteria of VIP &gt;1, p &lt; 0.01, and FC &gt; 2, and then identified or assigned. The pathway analysis and PBs enrichment were conducted by MetaboAnalyst and ChemRICH. Furthermore, network pharmacology was adopted to dig out the active components and targets. Finally, the results from metabolomics and network pharmacology were integrated to confirm each other.

Results: HK could recover the CDDP-induced abnormal pharmacological and metabolic profile changes. A total of 187 PBs were screened and identified from the serum, kidney, and urine metabolomics. Pathway analysis showed that multiple metabolic pathways, mainly related to amino acid and lipid metabolisms, were involved in the nephroprotective effect of HK, and especially, HK could significantly alleviate the disorder of tryptophan metabolism pathway in serum, kidney, and urine. Meanwhile, network pharmacology analysis revealed that 5 components in HK and 4 key genes could be responsible for the nephroprotection of HK, which also indicated that the metabolism of tryptophan played an important role in HK against CKD.

Conclusion: HK has a nephroprotection on CDDP-induced CKD, mainly by restoring the dysregulation of tryptophan metabolism. Integrated analysis of serum, kidney, and urine metabolomics and network pharmacology was a powerful method for exploring pharmacological mechanisms and screening active components and targets of traditional Chinese medicine.

Serum Biomarkers of Renal Fibrosis: A Systematic Review

Chronic kidney disease (CKD) is a widely diffuse pathological condition which deeply impacts upon an affected patient's quality of life and its worldwide rate is predicted to further rise. The main biological mechanism underlying CKD is renal fibrosis, a non-reversible process representing, for the affected system, a point of no return of tissue damage and dysfunction, deeply reducing the possible therapeutic strategies at the disposal of physicians. The best tool clinicians can use to address the extent of renal fibrosis at any level (glomeruli, tubule-interstitium, vasculature) is kidney biopsy that, despite its overall safety, remains an invasive procedure showing some shortcomings. Thus, the identification of novel non-invasive renal fibrosis biomarkers would be of fundamental importance. Here, when systematically reviewing the available evidence on serological biomarkers associated with renal fibrosis evaluated in patients suffering from CKD in the last five years, we found that despite the presence of several promising biomarkers, the level of observed evidence is still very scattered. Probably, the use of multiple measures capable of addressing different aspects involved in this condition would be the most suitable way to capture the high complexity characterizing the renal fibrotic process, having consequently a great impact on clinical practice by maximizing prevention, diagnosis, and management.

Impact of Early Proteinuria Reduction in Glomerular Disease and Decline of Kidney Function: A Retrospective Cohort

Background: In glomerular disease, the degree of proteinuria is closely related to the progression of chronic kidney disease, and its reduction is associated with a slower decline in the glomerular filtration rate (eGFR) and consequent improvement in the renal prognosis. The aim of this study was to evaluate the impact of proteinuria reduction on the decline of the eGFR in patients with glomerular disease, during the first year after the diagnosis. Methods: This was a retrospective analysis of patients with primary glomerular disease, followed at the Nephrology Department of Centro Hospitalar Universitário Lisboa Norte, during 2019. We analyzed demographic, clinical and laboratorial characteristics (creatinine, GFR, urine analysis and quantification of proteinuria determined by the proteinuria/creatinuria ratio, in the first morning urine or a 24 h urine sample). The outcome assessed was the decline in renal function, defined as a reduction in the GFR ≥ 25%, during the follow-up period. Results: We analyzed 197 patients with glomerular disease, with a mean age of 41.7 ± 19.7 years and follow-up time of 6.5 ± 5.3 years. At the time of the diagnosis, the eGFR was 81.5 ± 49.8 mL/min/1.73 m2 and proteinuria was 3.5 g/24 h (IQR 5.8). At one-year follow-up, median proteinuria was 0.9 g/24 h (IQR 2.4). At the end of the follow-up, mean eGFR was 72.1 ± 43.3 mL/min/1.73 m2. Proteinuria (p = 0.435) and the eGFR (p = 0.880) at the time of diagnosis did not correlate with long-term decline in the eGFR. Proteinuria < 1 g/24 h (HR 0.45 (95% CI 0.25−0.83) p = 0.011) after the first year was protective against long-term decline in the eGFR. It maintained this association with the long-term eGFR decline, independently of the duration of the follow-up (HR 0.30 (95% CI 0.17−0.52) p < 0.001). Conclusions: Proteinuria reduction to lower than 1 g/24 h, during the first year after diagnosis, was a protective factor for the long-term decline of kidney function, having a more important role than proteinuria or the GFR at the time of the diagnosis.

Metabolomic changes in cats with renal disease and calcium oxalate uroliths

INTRODUCTION

There is a significant incidence of cats with renal disease (RD) and calcium oxalate (CaOx) kidney uroliths in domesticated cats. Foods which aid in the management of these diseases may be enhanced through understanding the underlying metabolomic changes.

OBJECTIVE

Assess the metabolomic profile with a view to identifying metabolomic targets which could aid in the management of renal disease and CaOx uroliths.

METHOD

This is a retrospective investigation of 42 cats: 19 healthy kidney controls, 11 with RD, and 12 that formed CaOx nephroliths. Cats were evaluated as adults (2 through 7 years) and at the end of life for plasma metabolomics, body composition, and markers of renal dysfunction. Kidney sections were assessed by Pizzolato stain at the end of life for detection of CaOx crystals. CaOx stone presence was also assessed by analysis of stones removed from the kidney at the end of life.

RESULTS

There were 791 metabolites identified with 91 having significant (p < 0.05, q < 0.1) changes between groups. Many changes in metabolite concentrations could be explained by the loss of renal function being most acute in the cats with RD while the cats with CaOx stones were intermediate between control and RD (e.g., urea, creatinine, pseudouridine, dimethylarginines). However, the concentrations of some metabolites differentiated RD from CaOx stone forming cats. These were either increased in the RD cats (e.g., cystathionine, dodecanedioate, 3-(3-amino-3-carboxypropyl) uridine, 5-methyl-2'-deoxycytidine) or comparatively increased in the CaOx stone forming cats (phenylpyruvate, 4-hydroxyphenylpyruvate, alpha-ketobutyrate, retinal).

CONCLUSIONS

The metabolomic changes show specific metabolites which respond generally to both renal diseases while the metabolomic profile still differentiates cats with RD and cats with CaOx uroliths.

Identification of differentially expressed genes and their major pathways among the patient with COVID-19, cystic fibrosis, and chronic kidney disease

The SARS-CoV-2 virus causes Coronavirus disease, an infectious disease. The majority of people who are infected with this virus will have mild to moderate respiratory symptoms. Multiple studies have proved that there is a substantial pathophysiological link between COVID-19 disease and patients having comorbidities such as cystic fibrosis and chronic kidney disease. In this study, we attempted to identify differentially expressed genes as well as genes that intersected among them in order to comprehend their compatibility. Gene expression profiling indicated that 849 genes were mutually exclusive and functional analysis was done within the context of gene ontology and key pathways involvement. Three genes (PRPF31, FOXN2, and RIOK3) were commonly upregulated in the analysed datasets of three disease categories. These genes could be potential biomarkers for patients with COVID-19 and cystic fibrosis, and COVID-19 and chronic kidney disease. Further extensive analyses have been performed to describe how these genes are regulated by various transcription factors and microRNAs. Then, our analyses revealed six hub genes (PRPF31, FOXN2, RIOK3, UBC, HNF4A, and ELAVL). As they were involved in the interaction between COVID-19 and the patient with CF and CKD, they could help researchers identify potential therapeutic molecules. Some drugs have been predicted based on the upregulated genes, which may have a significant impact on reducing the burden of these diseases in the future.

Host/microbiota interactions-derived tryptophan metabolites modulate oxidative stress and inflammation via aryl hydrocarbon receptor signaling

Aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that induces the expression of a broad range of downstream genes such as cytochromes P450 enzymes and cyclooxygenase-2. Recent research focuses are shifting from AhR activation induced by xenobiotics to its response patterns to physiological ligands that expand our understanding of how endogenous metabolites as ligands to modulate AhR signaling pathway under homeostasis and pathological conditions. With increasing interest in AhR and its endogenous ligands, it would seem advisable to summarize a variety of endogenous ligands especially host/gut microbiota-derived tryptophan metabolites. Mounting evidence has indicated that AhR play a critical role in the regulation of redox homeostasis and immune responses. In this review, we outline the canonical and non-canonical AhR signalling pathway that is mediated by host/gut microbiota-derived tryptophan metabolites. Through several typical endogenous AhR ligands, we investigated the molecular mechanisms of AhR-induced oxidative stress and inflammation in the pathological milieu, including diabetes, diabetic kidney disease and end-stage renal disease. Finally, we summarize and emphasize the limitations and breakthrough of endogenous AhR ligands from host/microbial tryptophan catabolites. This review might provide novel diagnostic and prognostic approach for refractory human diseases and establish new therapeutic strategies for AhR activation.

Emerging Role of Clinical Genetics in CKD

Chronic kidney disease (CKD) afflicts 15% of adults in the United States, of whom 25% have a family history. Genetic testing is supportive in identifying and possibly confirming diagnoses of CKD, thereby guiding care. Advances in the clinical genetic evaluation include next-generation sequencing with targeted gene panels, whole exome sequencing, and whole genome sequencing. These platforms provide DNA sequence reads with excellent coverage throughout the genome and have identified novel genetic causes of CKD. New pathologic genetic variants identified in previously unrecognized biological pathways have elucidated disease mechanisms underlying CKD etiologies, potentially establishing prognosis and guiding treatment selection. Molecular diagnoses using genetic sequencing can detect rare, potentially treatable mutations, avoid misdiagnoses, guide selection of optimal therapy, and decrease the risk of unnecessary and potentially harmful interventions. Genetic testing has been widely adopted in pediatric nephrology; however, it is less frequently used to date in adult nephrology. Extension of clinical genetic approaches to adult patients may achieve similar benefits in diagnostic refinement and treatment selection. This review aimed to identify clinical CKD phenotypes that may benefit the most from genetic testing, outline the commonly available platforms, and provide examples of successful deployment of these approaches in CKD.

Estimated Renal Metabolomics at Reperfusion Predicts One-Year Kidney Graft Function

Renal transplantation is the gold-standard procedure for end-stage renal disease patients, improving quality of life and life expectancy. Despite continuous advancement in the management of post-transplant complications, progress is still needed to increase the graft lifespan. Early identification of patients at risk of rapid graft failure is critical to optimize their management and slow the progression of the disease. In 42 kidney grafts undergoing protocol biopsies at reperfusion, we estimated the renal metabolome from RNAseq data. The estimated metabolites' abundance was further used to predict the renal function within the first year of transplantation through a random forest machine learning algorithm. Using repeated K-fold cross-validation we first built and then tuned our model on a training dataset. The optimal model accurately predicted the one-year eGFR, with an out-of-bag root mean square root error (RMSE) that was 11.8 ± 7.2 mL/min/1.73 m2. The performance was similar in the test dataset, with a RMSE of 12.2 ± 3.2 mL/min/1.73 m2. This model outperformed classic statistical models. Reperfusion renal metabolome may be used to predict renal function one year after allograft kidney recipients.

Advances in the Progression and Prognosis Biomarkers of Chronic Kidney Disease

Chronic kidney disease (CKD) is one of the increasingly serious public health concerns worldwide; the global burden of CKD is increasingly due to high morbidity and mortality. At present, there are three key problems in the clinical treatment and management of CKD. First, the current diagnostic indicators, such as proteinuria and serum creatinine, are greatly interfered by the physiological conditions of patients, and the changes in the indicator level are not synchronized with renal damage. Second, the established diagnosis of suspected CKD still depends on biopsy, which is not suitable for contraindication patients, is also traumatic, and is not sensitive to early progression. Finally, the prognosis of CKD is affected by many factors; hence, it is ineviatble to develop effective biomarkers to predict CKD prognosis and improve the prognosis through early intervention. Accurate progression monitoring and prognosis improvement of CKD are extremely significant for improving the clinical treatment and management of CKD and reducing the social burden. Therefore, biomarkers reported in recent years, which could play important roles in accurate progression monitoring and prognosis improvement of CKD, were concluded and highlighted in this review article that aims to provide a reference for both the construction of CKD precision therapy system and the pharmaceutical research and development.

Jolkinolide B alleviates renal fibrosis via anti-inflammation and inhibition of epithelial-mesenchymal transition in unilateral ureteral obstruction mice

Renal fibrosis is a critical pathological process lead to a progressive loss of renal function. Jolkinolide B (JB) is a natural compound with anti-inflammatory activity from Euphorbia fischeriana Steud. The study evaluated the effect of JB on renal fibrosis in mice with unilateral ureteral obstruction (UUO). The results showed that JB could decrease renal fibrotic area, reduce phosphorylation of NF-κB p65 and the release of TNF-α, IL-6 and IL-1β, restore the expression of vementin, α-SMA and E-cadherin, as well as TGF-β1 and p-smad2/3. In conclusion, JB might reduce renal fibrosis by inhibiting inflammation induced by NF-κB pathway and EMT mediated by TGF-β1/Smad pathway.

A comprehensive insight into autophagy and its potential signaling pathways as a therapeutic target in podocyte injury

As part of the glomerular filtration membrane, podocyte is terminally differentiated, structurally unique, and highly specialized in maintaining kidney function. Proteinuria caused by podocyte injury (foot process effacement) is the clinical symptom of various kidney diseases (CKD), including nephrotic syndrome. Podocyte autophagy has become a powerful therapeutic strategy target in ameliorating podocyte injury. Autophagy is known to be associated significantly with sirtuin-1, proteinuria, and podocyte injury. Various key findings in podocyte autophagy were reported in the past ten years, such as the role of endoplasmic reticulum (ER) stress in podocyte autophagy impairment, podocyte autophagy-related gene, essential roles of the signaling pathways: Mammalian Target of Rapamycin (mTOR)/ Phosphoinositide 3-kinase (PI3k)/ serine/threonine kinase 1 (Akt) in podocyte autophagy. These significant factors caused podocyte injury associated with autophagy impairment. Sirtuin-1 was reported to have a vital key role in mTOR signaling, 5'AMP-activated protein kinase (AMPK) regulation, autophagy activation, and various critical pathways associated with podocyte's function and health; it has potential value to podocyte injury pathogenesis investigation. From these findings, podocyte autophagy has become an attractive therapeutic strategy to ameliorate podocyte injury, and this review will provide an in-depth review on therapeutic targets he podocyte autophagy.

Exploring New Kingdoms: The Role of Extracellular Vesicles in Oxi-Inflamm-Aging Related to Cardiorenal Syndrome

The incidence of age associated chronic diseases has increased in recent years. Although several diverse causes produce these phenomena, abundant evidence shows that oxidative stress plays a central role. In recent years, numerous studies have focused on elucidating the role of oxidative stress in the development and progression of both aging and chronic diseases, opening the door to the discovery of new underlying mechanisms and signaling pathways. Among them, senolytics and senomorphics, and extracellular vesicles offer new therapeutic strategies to slow the development of aging and its associated chronic diseases by decreasing oxidative stress. In this review, we aim to discuss the role of extracellular vesicles in human cardiorenal syndrome development and their possible role as biomarkers, targets, or vehicles of drugs to treat this syndrome.

Preliminary demonstration of benchtop NMR metabolic profiling of feline urine: chronic kidney disease as a case study

Objective

The use of benchtop metabolic profiling technology based on nuclear magnetic resonance (NMR) was evaluated in a small cohort of cats with a view to applying this as a viable and rapid metabolic tool to support clinical decision making.

Results

Urinary metabolites were analysed from four subjects consisting of two healthy controls and two chronic kidney disease (CKD) IRIS stage 2 cases. The study identified 15 metabolites in cats with CKD that were different from the controls. Among them were acetate, creatinine, citrate, taurine, glycine, serine and threonine. Benchtop NMR technology is capable of distinguishing between chronic kidney disease case and control samples in a pilot feline cohort based on metabolic profile. We offer perspectives on the further development of this pilot work and the potential of the technology, when combined with sample databases and computational intelligence techniques to offer a clinical decision support tool not only for cases of renal disease but other metabolic conditions in the future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13104-021-05888-y.

Shenkang Injection and Its Three Anthraquinones Ameliorates Renal Fibrosis by Simultaneous Targeting IƙB/NF-ƙB and Keap1/Nrf2 Signaling Pathways

Oxidative stress and inflammation are important and critical mediators in the development and progression of chronic kidney disease (CKD) and its complications. Shenkang injection (SKI) has been widely used to treat patients with CKD. Although the anti-oxidative and anti-inflammatory activity was involved in SKI against CKD, its bioactive components and underlying mechanism remain enigmatic. A rat model of adenine-induced chronic renal failure (CRF) is associated with, and largely driven by, oxidative stress and inflammation. Hence, we identified the anti-oxidative and anti-inflammatory components of SKI and further revealed their underlying mechanism in the adenine-induced CRF rats. Compared with control rats, the levels of creatinine, urea, uric acid, total cholesterol, triglyceride, and low-density lipoprotein cholesterol in serum were significantly increased in the adenine-induced CRF rats. However, treatment with SKI and its three anthraquinones including chrysophanol, emodin, and rhein could reverse these aberrant changes. They could significantly inhibit pro-fibrotic protein expressions including collagen I, α-SMA, fibronectin, and vimentin in the kidney tissues of the adenine-induced CRF rats. Of note, SKI and rhein showed the stronger inhibitory effect on these pro-fibrotic protein expressions than chrysophanol and emodin. Furthermore, they could improve dysregulation of IƙB/NF-ƙB and Keap1/Nrf2 signaling pathways. Chrysophanol and emodin showed the stronger inhibitory effect on the NF-κB p65 protein expression than SKI and rhein. Rhein showed the strongest inhibitory effect on p65 downstream target gene products including NAD(P)H oxidase subunits (p47phox, p67phox, and gp91phox) and COX-2, MCP-1, iNOS, and 12-LO in the kidney tissues. However, SKI and rhein showed the stronger inhibitory effect on the significantly downregulated anti-inflammatory and anti-oxidative protein expression nuclear Nrf2 and its target gene products including HO-1, catalase, GCLC, and NQO1 in the Keap1/Nrf2 signaling pathway than chrysophanol and emodin. This study first demonstrated that SKI and its major components protected against renal fibrosis by inhibiting oxidative stress and inflammation via simultaneous targeting IƙB/NF-ƙB and Keap1/Nrf2 signaling pathways, which illuminated the potential molecular mechanism of anti-oxidative and anti-inflammatory effects of SKI.

Diagnosis and Treatment Rules of Chronic Kidney Disease and Nursing Intervention Models of Related Mental Diseases Using Electronic Medical Records and Data Mining

Objective

On the basis of electronic medical records, the data mining technology was adopted to explore the law of chronic kidney disease (CKD) and the intervention mode of mental health of patients.

Methods

Based on the electronic medical records, the corresponding data extraction, database establishment, and data cleaning of CKD were performed. After that, the related data analysis, frequency analysis, cluster analysis, and nonparametric analysis were used to explore the laws of CKD diagnosis and treatment and nursing intervention mode of mental illness. The most common causes of CKD were chronic glomerulonephritis (43.76%), aristolochic acid nephritis (16.34%), diabetic nephritis (12.87%), and hypertensive nephritis (11.58%). The major treatment method for end-stage patients was alternative therapies, accounting for 46%. Compared with the depression score before intervention, that of the patients after the mindfulness therapy (50.99 ± 9.77 vs. 47.01 ± 9.33, P=0.024 < 0.5) and target behaviour nursing intervention (52.21 ± 8.12 vs. 48.01 ± 9.33, P=0.032 < 0.05) was obviously decreased.

Conclusion

The data mining technology based on electronic records showed a good application prospect in the analysis of the diagnosis and treatment of CKD; and target behaviour nursing and mindfulness intervention were effective psychological intervention models.

[Triglyceride-glucose product is an independent risk factor for predicting chronic kidney disease in middle-aged and elderly population: a prospective cohort study]

OBJECTIVE

To explore the correlation of triglyceride-glucose product (TyG) index with chronic kidney disease (CKD) in elderly population in Lanzhou (Gansu Province, China).

METHODS

From May to September, 2011, a total of 3868 middleaged and elderly individuals without CKD from 3 communities in Lanzhou were selected as the cohort study population and were followed for an average of 3.1 years (from June, 2014 to August, 2015). After excluding those with missing follow-up data, a total of 3439 individuals were included for analysis, who were divided according to the quartile of TyG index into Q1 group (TyG≤8.47), Q2 group (TyG 8.48-8.84), Q3 group (TyG 8.85-9.20) and Q4 group (TyG>9.20). The estimated glomerular filtration rate (eGFR) and urinary albumin/creatinine ratio (UACR) were used to evaluate the renal function of the participants.

RESULTS

In this cohort, a high TyG index was found to correlate with a high risk of CKD (P < 0.05). Analysis of the follow-up data showed that the TyG index was significantly higher in patients who developed CKD during the follow-up than in those without CKD (P < 0.05). Logistic regression analysis showed that TyG index was an independent risk factor for abnormal eGFR and CKD (P < 0.05).

CONCLUSION

A high TyG index is an independent risk factor for CKD in middle-aged and elderly population.

Serum metabolomics of end-stage renal disease patients with depression: potential biomarkers for diagnosis

Background

End-stage renal disease (ESRD) is the final stage during the development of renal failure. Depression is the most common psychiatric disorder in patients with ESRD, which in turn aggravates the progression of renal failure, however, its underlying mechanism remains unclear. This study aimed to reveal the pathogenesis and to discover novel peripheral biomarkers for ESRD patients with depression through metabolomic analysis.

Methods

Ultra-high-performance liquid chromatography coupled with mass spectrometry (UPLC-MS) was used to explore changes of serum metabolites among healthy controls, ESRD patients with or without depression. The differential metabolites between groups were subjected to clustering analysis, pathway analysis, receiver operating characteristic (ROC) curve analysis.

Results

A total of 57 significant serum differential metabolites were identified between ESRD patients with or without depression, which were involved in 19 metabolic pathways, such as energy metabolism, glycerolipid metabolism, and glutamate-centered metabolism. Moreover, the area under the ROC curve of gentisic acid, uric acid, 5-hydroxytryptamine, 2-phosphoglyceric acid, leucyl-phenylalanine, propenyl carnitine, naloxone, pregnenolone, 6-thioxanthene 5'-monophosphate, hydroxyl ansoprazole, zileuton O-glucuronide, cabergoline, PA(34:2), PG(36:1), probucol and their combination was greater than 0.90.

Conclusions

Inflammation, oxidative stress and energy metabolism abnormalities, glycerolipid metabolism, and glutamate-centered metabolism are associated with the pathogenesis of ESRD with depression, which may be promising targets for therapy. Furthermore, the identified differential metabolites may serve as biomarkers for the diagnosis of ESRD patients with depression.

NMR-based metabolomics associated with chronic kidney disease in humans and animals: a one health perspective

Chronic kidney disease (CKD) is a renal dysfunction that can lead to high rates of mortality and morbidity, particularly when coupled with late diagnosis. CKD has become a major health problem due to its challenging detection at early stages when clear symptoms are yet to be presented. Thus, CKD is likely to be identified when the substantive conditions of the disease are manifest. In order to address the development of the disease and provide necessary treatments at the initial stage, the investigation of new biomarkers and metabolites associated with early detection of CKD are needed. Identified metabolites could be used to confirm the presence of the disease, obtain information on its mechanism and facilitate the development of novel pharmaceutical treatments. Such metabolites may be detected from biofluids and tissues using a range of analytical techniques. There are a number of metabolites that have been identified by mass spectrometry at high sensitivities, whilst the detection of metabolites directly from biofluids using NMR could present a more rapid way to expand our understanding of this disease. This review is focused on NMR-based metabolomics associated with CKD in humans and animals.

Magnetic detection of albuminuria using hematite nanorods synthesized via chemical hydrothermal method

Objectives

Albuminuria is a biomarker in the diagnosis of kidney disease which is due to the presence of high albumin in the urine and is one of the complications of diabetes. In recent years, the methods used to identify albuminuria have been expensive and time-consuming. Furthermore, another problem is the lack of accurate measurement of albuminuria. This problem leads to kidney isolation as well as a decrease in erythropoietin levels. Therefore, the main aim of our work is to design a magnetic nanobiosensor with better sensitivity to detect minimal levels of albuminuria.

Materials and Methods

In the present work, we synthesized Hematite Nano Rods (HNRs) using FeCl₃, NaOH and Cetyltrimethylammonium bromide (CTAB) precursors via the hydrothermal method. Then, HNRs were characterized using UV-vis spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), Transmission Electron Microscopy (TEM) and Vibrating Sample Magnetometer (VSM) techniques.

Results

The obtained results from clinical performance of the HNR nanobiosensor show that the magnetization changes of HNR in interaction with the albumin biomarker can determine the presence or absence of protein in biological samples. The accuracy and repeatability of the HNR nanobiosensor from the value of the R2 coefficient in the standard equation is 0.9743.

Conclusion

We obtained the standard curve through interaction of the HNRs with albumin protein. The standard equation is obtained by plotting the magnetization curve of a non-interacting sample to interacting samples in terms of protein concentration. The Bland-Altman statistical graph prove that the HNR nanobiosensor is as reliable as experimental methods.

1-Hydroxypyrene mediates renal fibrosis through aryl hydrocarbon receptor signalling pathway

BACKGROUND AND PURPOSE

In chronic kidney disease (CKD), patients inevitably reach end-stage renal disease and require renal transplant. Evidence suggests that CKD is associated with metabolite disorders. However, the molecular pathways targeted by metabolites remain enigmatic. Here, we describe roles of 1-hydroxypyrene in mediating renal fibrosis.

EXPERIMENTAL APPROACH

We analysed 5406 urine and serum samples from patients with Stage 1-5 CKD using metabolomics, and 1-hydroxypyrene was identified and validated using longitudinal and drug intervention cohorts as well as 5/6 nephrectomised and adenine-induced rats.

KEY RESULTS

We identified correlations between the urine and serum levels of 1-hydroxypyrene and the estimated GFR in patients with CKD onset and progression. Moreover, increased 1-hydroxypyrene levels in serum and kidney tissues correlated with decreased renal function in two rat models. Up-regulated mRNA expression of aryl hydrocarbon receptor and its target genes, including CYP1A1, CYP1A2 and CYP1B1, were observed in patients and rats with progressive CKD. Further we showed up-regulated mRNA expression of aryl hydrocarbon receptor and its three target genes, plus up-regulated nuclear aryl hydrocarbon receptor protein levels in mice and HK-2 cells treated with 1-hydroxypyrene, which caused accumulation of extracellular matrix components. Treatment with aryl hydrocarbon receptor short hairpin RNA or flavonoids inhibited mRNA expression of aryl hydrocarbon receptor and its target genes in 1-hydroxypyrene-induced HK-2 cells and mice.

CONCLUSION AND IMPLICATIONS

Metabolite 1-hydroxypyrene was demonstrated to mediate renal fibrosis through activation of the aryl hydrocarbon receptor signalling pathway. Targeting aryl hydrocarbon receptor may be an alternative therapeutic strategy for CKD progression.

Association of Circulating ANGPTL8 Levels With Renal Dysfunction: A Case-Control Study

Background: Chronic kidney disease (CKD) is recognized as a major public health problem with high morbidity and mortality worldwide. Recently, angiopoietin-like protein 8 (ANGPTL8) was found to regulate lipid metabolism. Previous studies suggested that serum ANGPTL8 levels increased in patients with diabetes, especially in diabetic patients with albuminuria. This study aimed to investigate the association between circulating levels of ANGPTL8 and kidney function in the general population. Methods: The subjects were patients with renal dysfunction [estimated glomerular filtration rate (eGFR) <60/min/1.73 m²] from Risk Evaluation of cAncers in Chinese diabeTic Individuals: a lONgitudinal study (the REACTION study). Each case was matched by age, sex, and body mass index (BMI) with one control whose eGFR was ≥ 90 ml/min/1.73 m². The case and control groups were compared using a paired t-test. Binary logistic regression analysis was used to calculate the odds ratio (OR) of renal dysfunction (RD). Results: Among 135 case-control pairs, circulating ANGPTL8 levels were elevated in patients with RD compared to control subjects [799.96 (410.12-1086.44) vs. 609.58 (365.13-740.06) pg/ml, p < 0.05]. Partial correlations showed that ANGPTL8 levels were negatively correlated with eGFR (r = -0.26, p < 0.05). Multivariable-adjusted binary logistic regression analysis showed that elevated ANGPTL8 levels were associated with an increased risk of RD (OR in quartile 4 vs. 1, 3.80; 95% CI, 1.71-8.41). Interestingly, the association between ANGPTL8 levels and RD was consistent with the overall findings in both nondiabetic individuals (OR, 1.44; 95% CI, 1.09 to 1.91) and diabetic patients (OR, 2.71; 95% CI, 1.13-6.49) in the subgroup analyses. Furthermore, the estimates for this association were also significant in females (OR, 2.12; 95% CI, 1.33-3.37), individuals aged > 60 years (OR, 1.55; 95% CI, 1.16-2.07), individuals with a BMI <24 (OR, 1.66; 95% CI, 1.16-2.39), and individuals without hyperlipidaemia (OR, 1.61; 95% CI, 1.16-2.23) (all p-values <0.05). Conclusion: Elevated circulating ANGPTL8 levels were associated with increased risk of RD in the general population, especially among females, individuals aged > 60 years, individuals with a BMI < 24, individuals without diabetes mellitus, individuals with diabetes mellitus (DM), and individuals without hyperlipidaemia. This finding implies that ANGPTL8 may play a role in the pathological process of RD.