Early-stage Diabetic Kidney Disease Research Articles

Hirudin delays the progression of diabetic kidney disease by inhibiting glomerular endothelial cell migration and abnormal angiogenesis

BackgroundIn the early stages of diabetic kidney disease (DKD), the pathogenesis involves abnormal angiogenesis in the glomerulus. Hirudin, as a natural specific inhibitor of thrombin, has been shown in previous studies to inhibit the migration of various tumor endothelial cells and abnormal angiogenesis. However, its role in DKD remains unclear. MethodsThe effects of hirudin in DKD were studied using spontaneous type 2 diabetic db/db mice (which develop kidney damage at 8 weeks). Network pharmacology was utilized to identify relevant targets. An in vitro high glucose model was established using mouse glomerular endothelial cells (MGECs) to investigate the effects of hirudin on the migration and angiogenic capacity of MGECs. ResultsHirudin can ameliorate kidney damage in db/db mice. Network pharmacology suggests its potential association with the VEGFA/VEGFR2 pathway. Western blot and immunohistochemistry demonstrated elevated protein expression levels of VEGFA, VEGFR2, AQP1, and CD31 in db/db mice, while hirudin treatment reduced their expression. In the MGECs high glucose model, hirudin may reverse the enhanced migration and angiogenic capacity of MGECs in a high glucose environment by altering the expression of VEGFA, VEGFR2, AQP1, and CD31. Moreover, the drug effect gradually increases with higher concentrations of hirudin. ConclusionsThis study suggests that hirudin can improve early-stage diabetic kidney disease kidney damage by inhibiting the migration and angiogenesis of glomerular endothelial cells, thereby further expanding the application scope of hirudin. Additionally, the study found increased expression of AQP1 in DKD, providing a new perspective for further research on the potential pathogenesis of DKD.

Simultaneous detection of multiple urinary biomarkers in patients with early-stage diabetic kidney disease using Luminex liquid suspension chip technology.

Several urinary biomarkers have good diagnostic value for diabetic kidney disease (DKD); however, the predictive value is limited with the use of single biomarkers. We investigated the clinical value of Luminex liquid suspension chip detection of several urinary biomarkers simultaneously. The study included 737 patients: 585 with diabetes mellitus (DM) and 152 with DKD. Propensity score matching (PSM) of demographic and medical characteristics identified a subset of 78 patients (DM = 39, DKD = 39). Two Luminex liquid suspension chips were used to detect 11 urinary biomarkers according to their molecular weight and concentration. The biomarkers, including cystatin C (CysC), nephrin, epidermal growth factor (EGF), kidney injury molecule-1 (KIM-1), retinol-binding protein4 (RBP4), α1-microglobulin (α1-MG), β2-microglobulin (β2-MG), vitamin D binding protein (VDBP), tissue inhibitor of metalloproteinases-1 (TIMP-1), tumor necrosis factor receptor-1 (TNFR-1), and tumor necrosis factor receptor-2 (TNFR-2) were compared in the DM and DKD groups. The diagnostic values of single biomarkers and various biomarker combinations for early diagnosis of DKD were assessed using receiver operating characteristic (ROC) curve analysis. Urinary levels of VDBP, RBP4, and KIM-1 were markedly higher in the DKD group than in the DM group (p < 0.05), whereas the TIMP-1, TNFR-1, TNFR-2, α1-MG, β2-MG, CysC, nephrin, and EGF levels were not significantly different between the groups. RBP4, KIM-1, TNFR-2, and VDBP reached p < 0.01 in univariate analysis and were entered into the final analysis. VDBP had the highest AUC (0.780, p < 0.01), followed by RBP4 (0.711, p < 0.01), KIM-1 (0.640, p = 0.044), and TNFR-2 (0.615, p = 0.081). However, a combination of these four urinary biomarkers had the highest AUC (0.812), with a sensitivity of 0.742 and a specificity of 0.760. The urinary levels of VDBP, RBP4, KIM-1, and TNFR-2 can be detected simultaneously using Luminex liquid suspension chip technology. The combination of these biomarkers, which reflect different mechanisms of kidney damage, had the highest diagnostic value for DKD. However, this finding should be explored further to understand the synergistic effects of these biomarkers.

EE364 Cost-Effectiveness of Artificial-Intelligence Enabled Kidney Disease Risk Stratification in US Veterans With Early-Stage Diabetic Kidney Disease

EE364 Cost-Effectiveness of Artificial-Intelligence Enabled Kidney Disease Risk Stratification in US Veterans With Early-Stage Diabetic Kidney Disease

The Potential of Huangqi Decoction for Treating Diabetic Kidney Disease

ABSTRACT Diabetic kidney disease (DKD) is a prevalent complication of diabetes mellitus that primarily affects the kidney microvasculature. According to the Traditional Chinese Medicine (TCM) theory, early-stage DKD is characterized by deficiencies in essence and Qi and is often accompanied by spleen and kidney deficiencies. Huangqi decoction (HQD), a classic Chinese herbal formula with historical use in treating thirst-related ailments, is described in Shiyin Yang's Renzhai Zhizhi Fang Lun. This review aimed to investigate the potential molecular mechanisms, pharmacological effects, and key targets of HQD to establish a theoretical and scientific foundation for further research and clinical applications. The bioactive compounds and targets of HQD were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, and compound-target and protein-protein interaction networks were constructed using Cytoscape and BisoGent, respectively. A total of 172 bioactive compounds were identified in HQD. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the hub targets indicated associations between diverse biological processes, cellular components, and molecular functions. These findings signify a promising avenue for the development of evidence-based treatments for DKD by leveraging the potential of TCM to enhance patient outcomes.

Predicting Osteoporotic Fracture in Patients With Early-Stage Diabetic Kidney Disease Using a Radiomic Model: A Longitudinal Cohort Study

ObjectiveThere is an urgent need for effective predictive strategies to accurately evaluate the risk of fragility fractures in elderly patients in the early stages of diabetic kidney disease (DKD). MethodsThis longitudinal cohort study included 715 older patients in the early stages of DKD diagnosed between January 2015 and August 2019. Patients were randomly allocated to a training cohort (n = 499) and a validation cohort (n = 216). The least absolute shrinkage and selection operator method was used to select key features for dual-energy x-ray absorptiometry-based radiomic analysis. A radiomic model was constructed using Cox proportional hazards regression. The performance of the radiomic model was compared with that of traditional fracture assessment tools through a receiver operating characteristic curve, calibration curve, and decision curve analysis. ResultsOver a mean follow-up period of 4.72 ± 1.60 years, 65 participants (9.09%) experienced incident fragility fractures. Seventeen features were ultimately selected to create the radiomic model. The calibration plots of this model demonstrated satisfactory agreement between the observed and predicted outcomes. Moreover, the radiomic model outperformed traditional fracture assessment tools in both the training and validation cohorts according to the area under the receiver operating characteristic curve and decision curve analysis. ConclusionsThe novel radiomic model has demonstrated a more effective prediction of fragility fracture in elderly patients in the early stages of DKDcompared to traditional fracture assessment tools.

A Real-World Precision Medicine Program Including the KidneyIntelX Test Effectively Changes Management Decisions and Outcomes for Patients With Early-Stage Diabetic Kidney Disease.

The KidneyIntelX is a multiplex, bioprognostic, immunoassay consisting of 3 plasma biomarkers and clinical variables that uses machine learning to predict a patient's risk for a progressive decline in kidney function over 5 years. We report the 1-year pre- and post-test clinical impact on care management, eGFR slope, and A1C along with engagement of population health clinical pharmacists and patient coordinators to promote a program of sustainable kidney, metabolic, and cardiac health. The KidneyIntelX in vitro prognostic test was previously validated for patients with type 2 diabetes and diabetic kidney disease (DKD) to predict kidney function decline within 5 years was introduced into the RWE study (NCT04802395) across the Health System as part of a population health chronic disease management program from [November 2020 to April 2023]. Pre- and post-test patients with a minimum of 12 months of follow-up post KidneyIntelX were assessed across all aspects of the program. A total of 5348 patients with DKD had a KidneyIntelX assay. The median age was 68 years old, 52% were female, 27% self-identified as Black, and 89% had hypertension. The median baseline eGFR was 62 ml/min/1.73 m2, urine albumin-creatinine ratio was 54 mg/g, and A1C was 7.3%. The KidneyIntelX risk level was low in 49%, intermediate in 40%, and high in 11% of cases. New prescriptions for SGLT2i, GLP-1 RA, or referral to a specialist were noted in 19%, 33%, and 43% among low-, intermediate-, and high-risk patients, respectively. The median A1C decreased from 8.2% pre-test to 7.5% post-test in the high-risk group (P < .001). UACR levels in the intermediate-risk patients with albuminuria were reduced by 20%, and in a subgroup treated with new scripts for SGLT2i, UACR levels were lowered by approximately 50%. The median eGFR slope improved from -7.08 ml/min/1.73 m2/year to -4.27 ml/min/1.73 m2/year in high-risk patients (P = .0003), -2.65 to -1.04 in intermediate risk, and -3.26 ml/min/1.73 m2/year to +0.45 ml/min/1.73 m2/year in patients with low-risk (P < .001). Deployment and risk stratification by KidneyIntelX was associated with an escalation in action taken to optimize cardio-kidney-metabolic health including medications and specialist referrals. Glycemic control and kidney function trajectories improved post-KidneyIntelX testing, with the greatest improvements observed in those scored as high-risk.

Enhanced trimethylamine metabolism and gut dysbiosis in type 2 diabetes mellitus with microalbumin.

Abnormal gut microbiota and blood trimethylamine-N-oxide (TMAO) metabolome have been reported in patients with type 2 diabetes mellitus (T2DM) and advanced diabetic nephropathy. This study aimed to investigate the gut microbiota profiles and a group of targeted urine metabolic characteristics in T2DM patients with or without microalbuminuria, to determine the correlation between the gut microbiota composition, trimethylamine (TMA) metabolism, and the clinical features during progression of diabetic kidney disease (DKD). This study included 26 T2DM patients with microalbuminuria (Micro), 26 T2DM patients with normoalbuminuria (Normo), and 15 healthy controls (HC). Urine and Fecal samples were detected using ultra performance liquid chromatography tandem mass spectrometry and 16S ribosomal DNA gene sequencing, respectively. The TMAO/TMA ratio decreased gradually during the HC-Normo-Micro transition. The levels of TMA, choline and betaine were significantly different between the HC group and the T2DM patients belonging to both Normo and Micro groups. At the operational taxonomic unit (OTU) level, the gut microflora diversity was significantly reduced in the Micro groups compared to the HC groups and the Normo groups. Taxonomic analyses revealed significant consumption in the relative abundances of eight bacterial genera and significant enrichment of two bacterial genera during the HC-Normo-Micro transition. Furthermore, the relative abundances of six bacterial genera, namely, Ruminococcus_1, [Eubacterium]_ruminantium_group, Roseburia, Faecalibacterium, Fusicatenibacter and Coprococcus_3 exhibited significant differences, and were associated with elevated urinary albumin creatinine ratio (UACR), TMAO/TMA, TMA and its precursors in the Micro group compared with the other groups. The imbalance of gut microbiota has occurred in patients with early-stage DKD, and the consumption of short-chain fatty acid-producing bacteria were associated with the accumulation of TMA and UACR.

Characterisation of the hydrogen sulfide system in early diabetic kidney disease.

A deficiency in hydrogen sulfide has been implicated in the development and progression of diabetic chronic kidney disease. The purpose of this study was to determine the effect of diabetes on the H2S system in early-stage diabetic kidney disease. We characterised gene and protein expression profile of the enzymes that regulate H2S production and degradation, and H2S production capacity, in the kidney from 10-week-old C57BL6J db/db mice (n=6), in age-matched heterozygous controls (n=7), and in primary endothelial cells (HUVECs) exposed to high glucose. In db/db mice renal H2S levels were significantly reduced (p=0.009). Protein expression of the H2S production enzymes was differentially affected by diabetes: Cystathionine β-synthase (CBS) was significantly lower in both db/db mice and high glucose treated HUVECS (p<0.0001; p= 0.0318) whereas 3-Mercatopyruvate sulfurtransferase (3-MST) expression was higher in the db/db kidney (p<0.0001), yet lower in the HUVECs (p=0.0001). Diabetes had no effect on the expression of Cystathionine γ-lyase (CSE) in the db/db kidney (p=ns), but was associated with reduced expression in the HUVECs (p=0.0004). Protein expression of degradation enzyme Sulfide quinone reductase (SQOR) was significantly higher in db/db kidney (p=0.048) and lower in the high glucose treated HUVECs (p= 0.008). Immunofluorescence studies revealed differential localization of the H2S enzymes in the kidney, including both tubular and vascular localisation, suggestive of functionally distinct actions in the kidney. The results of this study provide foundational knowledge for future research looking at the H2S system in both kidney physiology and the aetiology of chronic diabetic kidney disease.

Reduced Levels of the Antiaging Hormone Klotho are Associated With Increased Aortic Stiffness in Diabetic Kidney Disease

Aortic pulse wave velocity (Ao-PWV) predicts cardiovascular and kidney disease in type 2 diabetes (T2D). Klotho is a circulating antiaging hormone (sKlotho) with putative cardiorenal protective effects. The relationship between sKlotho and Ao-PWV in diabetic kidney disease (DKD) is unknown. In a cross-sectional cohort study, the correlation of sKlotho measured by a validated immunoassay, and Ao-PWV measured by applanation tonometry, was investigated in 172 participants with T2D and early stage DKD (all had estimated glomerular filtration rate [eGFR] >45 ml/min) on stable renin angiotensin system (RAS) inhibition. In cultured human aortic smooth muscle cells (HASMCs) stimulated with angiotensin II (AngII), the effects of recombinant human sKlotho pretreatment were assessed on intracellular calcium ([Ca2+]i) responses and expression of proteins associated with proosteogenic HASMC phenotypes. Mean (range) age of the cohort was 61.3 years (40-82) and 65% were male. Mean (±SD) Ao-PWV was 11.4 (±2.3) m/s, eGFR 78.8 (±23.5) and median (interquartile range) sKlotho of 358.5 (194.2-706.3) pg/ml. In multivariable linear regression analyses, we observed a statistically significant inverse relationship between sKlotho and Ao-PWV, which was independent of clinical risk factors for cardiorenal disease. Pretreatment of cultured HASMC with sKlotho significantly attenuated AngII-stimulated [Ca2+]i transients and reduced osteogenic collagen (Col1a2) expression. In individuals with T2D and early DKD, lower levels of sKlotho are associated with increased Ao-PWV. Taken together with the direct effect of sKlotho on mediators of aortic wall stiffness invitro, these findings may explain the enhanced risk of cardiorenal disease in DKD.

Association of D-dimer Level with Renal Parameters and Cardiovascular Events in Type 2 Diabetes Mellitus: A Retrospective Cohort Study

Introduction: D-dimer is a biomarker that can detect early stages of renal and cardiovascular dysfunction in Type 2 Diabetes Mellitus (T2DM). It serves as a key indicator and is readily available in laboratory settings, along with other risk factors. Aim: To investigate the association between D-dimer levels and renal parameters, as well as cardiovascular events, among T2DM subjects. Materials and Methods: This retrospective cohort study was conducted at Visnagar’s Nootan Medical College and Research Centre, Visnagar, Gujarat, India, involving subjects who visited the centre for health checks between September 2021 and December 2022. Screening was performed on all adult individuals with T2DM. Clinical records of 550 consecutive T2DM patients, aged between 18 and 80 years, receiving care at the centre were analysed. After applying exclusion criteria, 155 patients with T2DM diagnosis were enrolled. Parameters such as cystatin C, D-dimer, serum creatinine, urea, estimated Glomerular Filtration Rate (eGFR), and albuminuria were evaluated in all subjects. Bivariate logistic regression analysis was conducted to determine whether renal indicators are associated with high D-dimer levels, generating an odds ratio. Multivariate logistic regression analysis was then performed, correcting for sex and age, to determine which kidney indicators are linked to high D-dimer levels. Results: A total of 155 participants were included in this study, and were divided into high and low D-dimer groups. The mean ages of the low and high D-dimer groups were 40±13 years and 55±10 years, respectively. Compared to the low D-dimer group, the high D-dimer group had a higher frequency of males (p-value &lt;0.001). Patients with high D-dimer levels exhibited significantly increased levels of HbA1c, creatinine, urea, cystatin C, and UAE compared to patients with low D-dimer levels (p-value=0.001, p-value=0.001, p-value &lt;0.001, p-value &lt;0.001, and p-value=0.001, respectively). Conclusion: D-dimer may be beneficial in identifying patients with early-stage diabetic kidney disease, thereby promoting the early adoption of renal and cardioprotective therapy. Additionally, elevated D-dimer levels are associated with an increased risk of cardiovascular disease.

Assessment of urinary podocalyxin as an alternative marker for urinary albumin creatinine ratio in early stage of diabetic kidney disease in older patients

This study's objective is to evaluate the correlation relationship between Podocalyxin (PCX), an urinary marker of podocytes, urinary albumin-creatinine ratio (ACR) and the predictive value of PCX in the routine screen of early diabetic kidney disease (DKD) among older people. We also aimed to explore its prediction value despite of other metabolic factor and how PCX alters in the predictive power for early stage of diabetic nephropathy. In retrospective, 320 cases of older patients diagnosed with type 2 diabetes mellitus who met both inclusion and exclusion criteria were collected and divided with levels of urinary albumin, that is, normal albuminuria group, microalbuminuria group and healthy group. The correlation coefficient between PCX and ACR, and the odds ratio of PCX were gauged in the study. Area under the receiver operating characteristic (ROC) curve was also calculated. There were 188 patients in the normal group with urine ACR<30mg/g, and 132 patients in the microproteinuria group with urine ACR 30–300mg/g. 132 cases of DKD diagnosed with ACR, among them, 104 cases of DKD were predicted by PCX. The percentage correction value was 78.8%. The following parameters such as gender, age, course of disease, glycated hemoglobin, triglyceride, total cholesterol, BMI, blood pressure, uric acid, and eGFR were used as variables for adjustment to establish the prediction model of urine PCX and ACR. Multiple logistic regression test was carried out to evaluate against the predictive ability of the model. The area under the ROC curve corresponding to the regression model after adjustment is 0.952. Although factors such as the course of disease, HbA1C, UA, and eGFR could influence on the predictive ability of PCX, PCX still has a good ability to predict early DKD in older patients. Therefore, it could be used as a diagnostic indicator for early-stage DKD in older patients.

Molecular programs associated with glomerular hyperfiltration in early diabetic kidney disease

Hyperfiltration is a state of high glomerular filtration rate (GFR) observed in early diabetes that damages glomeruli, resulting in an iterative process of increasing filtration load on fewer and fewer remaining functional glomeruli. To delineate underlying cellular mechanisms of damage associated with hyperfiltration, transcriptional profiles of kidney biopsies from Pima Indians with type 2 diabetes with or without early-stage diabetic kidney disease were grouped into two hyperfiltration categories based on annual iothalamate GFR measurements. Twenty-six participants with a peak GFR measurement within two years of biopsy were categorized as the hyperfiltration group, and 26 in whom biopsy preceded peak GFR by over two years were considered pre-hyperfiltration. The hyperfiltration group had higher hemoglobin A1c, higher urine albumin-to-creatinine ratio, increased glomerular basement membrane width and lower podocyte density compared to the pre-hyperfiltration group. A glomerular 1240-gene transcriptional signature identified in the hyperfiltration group was enriched for endothelial stress response signaling genes, including endothelin-1, tec-kinase and transforming growth factor-β1 pathways, with the majority of the transcripts mapped to endothelial and inflammatory cell clusters in kidney single cell transcriptional data. Thus, our analysis reveals molecular pathomechanisms associated with hyperfiltration in early diabetic kidney disease involving putative ligand-receptor pairs with downstream intracellular targets linked to cellular crosstalk between endothelial and mesangial cells.

Identification of novel key genes and potential candidate small molecule drugs in diabetic kidney disease using comprehensive bioinformatics analysis.

Objective: The currently established diagnostic and prognostic tools for diabetic kidney disease (DKD) have limitations, which demands the necessity to find new genes and pathways associated with diagnosis and treatment. Our study aims to reveal the gene expression alteration and discover critical genes involved in the development of DKD, thus providing novel diagnostic molecular markers and therapeutic targets. Materials and methods: The differences of infiltrating immune cells within kidney were compared between healthy living donors and DKD patients. Besides, differentially expressed genes (DEGs) within kidney from healthy living donor, early stage DKD and advanced stage DKD samples were detected. Furthermore, the weighted co-expressed network (WGCNA) and protein-protein interaction (PPI) network were constructed, followed by recognition of core hub genes and module analysis. Receiver operating characteristic (ROC) curve analysis was implemented to determine the diagnostic value of hub genes, correlation analysis was employed to explore the association between hub genes and infiltrating immune cells, and certain hub genes was validated by quantitative real-time PCR and immunohistochemistry staining in cultured tubule cells and diabetic mice kidney. Finally, the candidate small molecules as potential drugs to treat DKD were anticipated through utilizing virtual screening and molecular docking investigation. Results: Our study revealed significantly higher proportion of infiltrating immune cells within kidney from DKD patients via probing the immune landscape by single-cell transcriptomics. Besides, 126 commonly shared DEGs identified among three group samples were enriched in immune biological process. In addition, the ROC curve analysis demonstrated the strong diagnostic accuracy of recognized hub genes (NFKB1, DYRK2, ATAD2, YAP1, and CHD3) from PPI network. Correlation analysis further confirmed the positive association between these hub genes with infiltrating natural killer cells. More importantly, the mRNA transcripts and protein abundance of YAP1 were significantly higher in high glucose-treated renal tubule cells and diabetic mice kidney, and the small molecules exhibiting the best binding affinities with YAP1 were predicted and acquired. Conclusion: Our findings for the first time indicate that NFKB1, DYRK2, ATAD2, YAP1, and CHD3 might be potential novel biomarkers and therapeutic targets for DKD, providing insights into the molecular mechanisms underlying the pathogenesis of DKD.

A kidney diagnostic's impact on physician decision-making in diabetic kidney disease.

Estimated glomerular filtration rate (eGFR) and albuminuria, the current standard-of-care tests that predict risk of kidney function decline in early-stage diabetic kidney disease (DKD), are only modestly useful. We evaluated the decision-making impact of an artificial intelligence-enabled prognostic test, KidneyIntelX, in the management of DKD by primary care physicians (PCPs). This was a prospective web-based survey administered among PCPs in the United States. We used conjoint analysis with multivariable logit models to estimate PCP preferences. The survey included hypothetical patient profiles with 6 attributes: albuminuria, eGFR, age, blood pressure (BP), hemoglobin A1c (HbA1c), and KidneyIntelX result. Each PCP viewed 8 patient profiles randomly selected from 42 unique profiles having 1 level from each attribute. For each patient, PCPs were asked to indicate whether they would prescribe a sodium-glucose cotransporter-2 (SGLT2) inhibitor, increase angiotensin receptor blocker (ARB) dose, and/or refer to a nephrologist. A total of 401 PCPs completed the survey (response rate, 8.8%). The relative importance of the top 2 attributes for each decision were HbA1c (52%) and KidneyIntelX result (23%) for prescribing SGLT2 inhibitors, BP (62%) and KidneyIntelX result (13%) for increasing ARB dose, and eGFR (42%) and KidneyIntelX result (27%) for nephrologist referral. A high-risk KidneyIntelX result was associated with significantly higher odds of PCPs prescribing SGLT2 inhibitors (odds ratio [OR], 1.64; 95% CI, 1.29-2.08), increasing ARB dose (OR, 1.49; 95% CI, 1.17-1.89), and referring to a nephrologist (OR, 2.47; 95% CI, 1.99-3.08) compared with no test. The KidneyIntelX test had greater relative importance than albuminuria and eGFR to PCPs in making treatment decisions and was second only to eGFR for nephrologist referrals. Because of its significant impact on decision-making, KidneyIntelX has high clinical utility in DKD management.

14-LB: Clinical Utility of KidneyIntelX on Patients with Early-Stage Diabetic Kidney Disease—A Real-World Evidence Study

Introduction: KidneyIntelX is a multiplex immunoassay of 3 plasma biomarkers with 7 clinical variables combined using machine-learning to generate a risk score for progressive decline in kidney function over 5 years in individuals with early-stage diabetic kidney disease (DKD) . Methods: A Population Health defined Mount Sinai approved care pathway for DKD patients informed by the KidneyIntelX test was introduced into the Mount Sinai Health System in New York, NY as part of a Real World Evidence (RWE) study (NCT04802395) . Decision impact of medication management (anti-hypertensives, SGLT2 inhibitors/GLP1 agonists) and specialist referral was tracked. An interim analysis was performed for 1) Assessing comparability between RWE and a published clinical validation cohort based on KidneyIntelX risk score distribution; 2) Determining if necessary EHR clinical fields were captured; 3) Identifying early evidence of KidneyIntelX impact on provider decision-making. Results: Between Mar-Nov 2021, 1,112 patients had KidneyIntelX test results, with post-test follow up to 36 weeks. The risk breakdown of RWE population was similar to the clinical validation cohort [High 14% vs. 17%, intermediate 40% vs. 37% and low risk 46% vs. 46%]. EHR record review for care changes confirmed ability to meet study objectives. Compared to patients scored low risk, there were changes in anti-hypertensives (OR 3.0; 95% CI 1.6-5.6) , initiation of SGLT2i/GLP-1a (OR 6.4; 95% CI 2.9-14) and increased referrals to nephrologists, endocrinologists, or dieticians (OR 2.8;95% CI 1.7-4.7) in patients scored as high-risk (Figure) . Conclusions: KidneyIntelX was successfully deployed in a health care system in a comparable population to the validation cohort with high data capture fidelity. Application of guideline-based therapies and specialist referral increased in the proportion to reported risk level by 3-6 and &amp;gt;2-fold, respectively. Disclosure J. Tokita: None. M. J. Donovan: Employee; Renalytix. R. Fields: None.

Association between TNF Receptors and KIM-1 with Kidney Outcomes in Early-Stage Diabetic Kidney Disease.

Clinical trials in nephrology are enriched for patients with micro- or macroalbuminuria to enroll patients at risk of kidney failure. However, patients with normoalbuminuria can also progress to kidney failure. TNF receptor-1, TNF receptor-2, and kidney injury marker-1 (KIM-1) are known to be associated with kidney disease progression in patients with micro- or macroalbuminuria. We assessed the value of TNF receptor-1, TNF receptor-2, and KIM-1 as prognostic biomarkers for CKD progression in patients with type 2 diabetes and normoalbuminuria. TNF receptor-1, TNF receptor-2, and KIM-1 were measured using immunoassays in plasma samples from patients with type 2 diabetes at high cardiovascular risk participating in the Canagliflozin Cardiovascular Assessment Study trial. We used multivariable adjusted Cox proportional hazards analyses to estimate hazard ratios per doubling of each biomarker for the kidney outcome, stratified the population by the fourth quartile of each biomarker distribution, and assessed the number of events and event rates. In patients with normoalbuminuria (n=2553), 51 kidney outcomes were recorded during a median follow-up of 6.1 (interquartile range, 5.8-6.4) years (event rate, 3.5; 95% confidence interval, 2.6 to 4.6 per 1000 patient-years). Each doubling of baseline TNF receptor-1 (hazard ratio, 4.2; 95% confidence interval, 1.8 to 9.6) and TNF receptor-2 (hazard ratio, 2.3; 95% confidence interval, 1.5 to 3.6) was associated with a higher risk for the kidney outcome. Baseline KIM-1, urinary albumin-creatinine ratio, and eGFR were not associated with kidney outcomes. The event rates in the highest quartile of TNF receptor-1 (≥2992 ng/ml) and TNF receptor-2 (≥11,394 ng/ml) were 5.6 and 7.0 events per 1000 patient-years, respectively, compared with 2.8 and 2.3, respectively, in the lower three quartiles. TNF receptor-1 and TNF receptor-2 are associated with kidney outcomes in patients with type 2 diabetes and normoalbuminuria. CANagliflozin cardioVascular Assessment Study (CANVAS), NCT01032629.

Real World Evidence and Clinical Utility of KidneyIntelX on Patients With Early-Stage Diabetic Kidney Disease: Interim Results on Decision Impact and Outcomes.

The lack of precision to identify patients with early-stage diabetic kidney disease (DKD) at near-term risk for progressive decline in kidney function results in poor disease management often leading to kidney failure requiring unplanned dialysis. The KidneyIntelX is a multiplex, bioprognostic, immunoassay consisting of 3 plasma biomarkers and clinical variables that uses machine learning to generate a risk score for progressive decline in kidney function over 5-year in adults with early-stage DKD. Our objective was to assess the impact of KidneyIntelX on management and outcomes in a Health System in the real-world evidence (RWE) study. KidneyIntelX was introduced into a large metropolitan Health System via a population health-defined approved care pathway for patients with stages 1 to 3 DKD between [November 2020 to March 2022]. Decision impact on visit frequency, medication management, specialist referral, and selected lab values was assessed. We performed an interim analysis in patients through 6-months post-test date to evaluate the impact of risk level with clinical decision-making and outcomes. A total of 1686 patients were enrolled in the RWE study and underwent KidneyIntelX testing and subsequent care pathway management. The median age was 68 years, 52% were female, 26% self-identified as Black, and 94% had hypertension. The median baseline eGFR was 59 ml/minute/1.73 m2, urine albumin-creatinine ratio was 69 mg/g, and HbA1c was 7.7%. After testing, a clinical encounter in the first month occurred in 13%, 43%, and 53% of low-risk, intermediate-risk, and high-risk patients, respectively and 46%, 61%, and 71% had at least 1 action taken within the first 6 months. High-risk patients were more likely to be placed on SGLT2 inhibitors (OR = 4.56; 95% CI 3.00-6.91 vs low-risk), and more likely to be referred to a specialist such as a nephrologist, endocrinologist, or dietician (OR = 2.49; 95% CI 1.53-4.01) compared to low-risk patients. The combination of KidneyIntelX, clinical guidelines and educational support resulted in changes in clinical management by clinicians. After testing, there was an increase in visit frequency, referrals for disease management, and introduction to guideline-recommended medications. These differed by risk category, indicating an impact of KidneyIntelX risk stratification on clinical care.

Urine tricarboxylic acid cycle signatures of early-stage diabetic kidney disease.

Urine tricarboxylic acid (TCA) cycle organic anions (OAs) are elevated in diabetes and may be biomarkers for diabetic kidney disease (DKD) progression. We assessed associations of 10 urine TCA cycle OAs with estimated glomerular filtration rate (eGFR) and eGFR slope. This study is ancillary to the Simultaneous Risk Factor Control Using Telehealth to SlOw Progression of Diabetic Kidney Disease (STOP-DKD) Trial-a randomized trial of pharmacist-led medication and behavior management in 281 patients with early to moderate DKD at Duke from 2014 to 2015. We used linear mixed models to assess associations of urine TCA cycle OAs with outcomes and modelled TCA cycle OAs as: (1) the average of z-scores for each OA; and (2) principal component (PC) scores derived by principal component analysis (PCA). Untargeted urine metabolomics were added for additional discovery. Among 132 participants with 24h urine samples (50% men; 58% Black; mean age 64years [SD 9]; mean eGFR 74ml/min/1.73m2 [SD 21] and medianurine albumin-to-creatinine [UACR] 20mg/g [IQR 8-95]), PCA identified 3 OA metabolite PCs. Malate, fumarate, pyruvate, α-ketoglutarate, lactate, succinate and citrate/isocitrate loaded positively on PC1; methylsuccinate, ethylmalonate and succinate loaded positively on PC2; and methylmalonate, ethylmalonate and citrate/isocitrate loaded negatively on PC3. Over a median follow-up of 1.8years (IQR, 1.2 to 2.2), higher average OA z-score was strongly associated with higher eGFR after covariate adjustment (p = 0.01), but not with eGFR slope (p = 0.9). Higher PC3, but not other PCs, was associated with lower eGFR (p < 0.001). Conditional random forests and smooth clipped absolute deviation models confirmed methylmalonate, citrate/isocitrate, and ethylmalonate, and added lactate as top ranked metabolites in models of baseline eGFR (R-squared 0.32 and 0.33, respectively). Untargeted urine metabolites confirmed association of urine TCA cycle OAs with kidney function. Thus, lower urine TCA cycle OAs, most notably lower methylmalonate, ethylmalonate and citrate/isocitrate, are potential indicators of kidney impairment in early stage DKD.

Assessment of urinary podocalyxin as an alternative marker for urinary albumin creatinine ratio in early stage of diabetic kidney disease in older patients

This study's objective is to evaluate the correlation relationship between Podocalyxin (PCX), an urinary marker of podocytes, urinary albumin-creatinine ratio (ACR) and the predictive value of PCX in the routine screen of early diabetic kidney disease (DKD) among older people. We also aimed to explore its prediction value despite of other metabolic factor and how PCX alters in the predictive power for early stage of diabetic nephropathy. In retrospective, 320 cases of older patients diagnosed with type 2 diabetes mellitus who met both inclusion and exclusion criteria were collected and divided with levels of urinary albumin, that is, normal albuminuria group, microalbuminuria group and healthy group. The correlation coefficient between PCX and ACR, and the odds ratio of PCX were gauged in the study. Area under the receiver operating characteristic (ROC) curve was also calculated. There were 188 patients in the normal group with urine ACR<30mg/g, and 132 patients in the microproteinuria group with urine ACR 30–300mg/g. 132 cases of DKD diagnosed with ACR, among them, 104 cases of DKD were predicted by PCX. The percentage correction value was 78.8%. The following parameters such as gender, age, course of disease, glycated hemoglobin, triglyceride, total cholesterol, BMI, blood pressure, uric acid, and eGFR were used as variables for adjustment to establish the prediction model of urine PCX and ACR. Multiple logistic regression test was carried out to evaluate against the predictive ability of the model. The area under the ROC curve corresponding to the regression model after adjustment is 0.952. Although factors such as the course of disease, HbA1C, UA, and eGFR could influence on the predictive ability of PCX, PCX still has a good ability to predict early DKD in older patients. Therefore, it could be used as a diagnostic indicator for early-stage DKD in older patients.

Особливості добового профілю артеріального тиску у хворих на цукровий діабет залежно від ендотеліальної дисфункції

Актуальність. Цукровий діабет (ЦД) — захворювання, що супроводжується оксидативним стресом, хронічним неспецифічним запаленням, пошкодженням судинної стінки, ендотеліальною дисфункцією. Особливістю перебігу артеріальної гіпертензії у хворих на ЦД є більш раннє формування діабетичної хвороби нирок (ДХН). Сьогодні здійснюється пошук маркерів ендотеліальної дисфункції, що дозволять виявляти ДХН на ранніх стадіях, коли зміни в нирках потенційно оборотні. Метою роботи було дослідити показники добового профілю артеріального тиску у хворих на ЦД та визначити їх взаємозв’язки з показниками швидкості клубочкової фільтрації й ендотеліальної функції за рівнем показників TGF-β1 (transforming growth factor beta-1 — трансформуючий фактор росту бета-1) та VCAM-1 (vascular cell adhesion molecule 1 — васкулярна молекула судинної адгезії 1). Матеріали та методи. У дослідження включені 124 хворі на ЦД, із них 66 пацієнтів із ЦД 1-го типу, 58 — із ЦД 2-го типу. Результати. Рівні показників ендотеліальної функції TGF-β1 та VCAM-1 у хворих на ЦД 1-го та 2-го типів кількісно залежали від показника швидкості клубочкової фільтрації. Між показниками ендотеліальної функції TGF-β1, VCAM-1 та показниками добового моніторування артеріального тиску виявлені сильні та середньої сили кореляційні зв’язки, у зв’язку з чим комплекс показників добового моніторування артеріального тиску та наявність ендотеліальної дисфункції можна вважати ранніми ознаками прогресування ДХН. Висновки. Для добового профілю артеріального тиску у хворих на ЦД на ранніх стадіях діабетичної нефропатії характерне вірогідне порушення циркадних ритмів. Недостатнє нічне зниження артеріального тиску у хворих на ЦД 1-го та 2-го типу характеризує наявність прогресування діабетичної нефропатії за показниками добового індексу артеріального тиску.