Onset Of Diabetic Kidney Disease Research Articles

Lipid metabolism disorder in diabetic kidney disease.

Diabetic kidney disease (DKD), a significant complication associated with diabetes mellitus, presents limited treatment options. The progression of DKD is marked by substantial lipid disturbances, including alterations in triglycerides, cholesterol, sphingolipids, phospholipids, lipid droplets, and bile acids (BAs). Altered lipid metabolism serves as a crucial pathogenic mechanism in DKD, potentially intertwined with cellular ferroptosis, lipophagy, lipid metabolism reprogramming, and immune modulation of gut microbiota (thus impacting the liver-kidney axis). The elucidation of these mechanisms opens new potential therapeutic pathways for DKD management. This research explores the link between lipid metabolism disruptions and DKD onset.

Impact of body mass index on adverse kidney events in diabetes mellitus patients: A systematic-review and meta-analysis.

The incidence of chronic kidney disease among patients with diabetes mellitus (DM) remains a global concern. Long-term obesity is known to possibly influence the development of type 2 diabetes mellitus. However, no previous meta-analysis has assessed the effects of body mass index (BMI) on adverse kidney events in patients with DM. To determine the impact of BMI on adverse kidney events in patients with DM. A systematic literature search was performed on the PubMed, ISI Web of Science, Scopus, Ovid, Google Scholar, EMBASE, and BMJ databases. We included trials with the following characteristics: (1) Type of study: Prospective, retrospective, randomized, and non-randomized in design; (2) participants: Restricted to patients with DM aged ≥ 18 years; (3) intervention: No intervention; and (4) kidney adverse events: Onset of diabetic kidney disease [estimated glomerular filtration rate (eGFR) of < 60 mL/min/1.73 m2 and/or microalbuminuria value of ≥ 30 mg/g Cr], serum creatinine increase of more than double the baseline or end-stage renal disease (eGFR < 15 mL/min/1.73 m2 or dialysis), or death. Overall, 11 studies involving 801 patients with DM were included. High BMI (≥ 25 kg/m2) was significantly associated with higher blood pressure (BP) [systolic BP by 0.20, 95% confidence interval (CI): 0.15-0.25, P < 0.00001; diastolic BP by 0.21 mmHg, 95%CI: 0.04-0.37, P = 0.010], serum albumin, triglycerides [standard mean difference (SMD) = 0.35, 95%CI: 0.29-0.41, P < 0.00001], low-density lipoprotein (SMD = 0.12, 95%CI: 0.04-0.20, P = 0.030), and lower high-density lipoprotein (SMD = -0.36, 95%CI: -0.51 to -0.21, P < 0.00001) in patients with DM compared with those with low BMIs (< 25 kg/m2). Our analysis showed that high BMI was associated with a higher risk ratio of adverse kidney events than low BMI (RR: 1.22, 95%CI: 1.01-1.43, P = 0.036). The present analysis suggested that high BMI was a risk factor for adverse kidney events in patients with DM.

Poor glycemic control is associated with more rapid kidney function decline after the onset of diabetic kidney disease.

The role of glycemic control and its variability on the rate of kidney function decline after the onset of diabetic kidney disease (DKD) remains unclear. The association between baseline HbA1c and rates of estimated GFR (eGFR) loss during follow-up was examined by mixed-effects linear regression in 530 individuals with type 1 diabetes and early-to-moderate DKD from the Preventing Early Renal Loss (PERL) trial, and 2,378 individuals with type 2 diabetes and established DKD from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. The benefit of intensive vs. standard glycemic control in slowing eGFR decline was examined in ACCORD. The associations between continuous glucose monitoring-derived short-term glycemic variability indices and rate of GFR decline were also evaluated in PERL. A higher baseline HbA1c was associated with a more negative eGFR slope in both PERL and ACCORD (-0.87 and -0.27 ml/min/1.73m2/year per Hba1c unit increment, p<0.0001 and p=0.0002, respectively). In both studies, the strength of this association progressively increased with increasing levels of albuminuria (p for interaction <0.05). Consistent with this, the benefit of intensive glycemic control on eGFR decline was greater in ACCORD participants with severe than in those with moderate albuminuria (+1.13 vs. +0.26 ml/min/1.73 m2/year, p=0.01). No independent associations were found in PERL between short-term glycemic variability indices and rate of eGFR decline. In both type 1 and type 2 diabetes, poor glycemic control is associated with a more rapid rate of GFR decline after DKD onset, especially in persons with severe albuminuria.

Metabolic Profiles of Type 2 Diabetes and Their Association With Renal Complications.

The components of metabolic syndrome (MetS) are interrelated and associated with renal complications in patients with type 2 diabetes (T2D). We aimed to reveal prevalent metabolic profiles in patients with T2D and identify which metabolic profiles were risk markers for renal progression. A total of 3556 participants with T2D from a hospital (derivation cohort) and 931 participants with T2D from a community survey (external validation cohort) were included. The primary outcome was the onset of diabetic kidney disease (DKD), and secondary outcomes included estimated glomerular filtration rate (eGFR) decline, macroalbuminuria, and end-stage renal disease (ESRD). In the derivation cohort, clusters were identified using the 5 components of MetS, and their relationships with the outcomes were assessed. To validate the findings, participants in the validation cohort were assigned to clusters. Multivariate odds ratios (ORs) of the primary outcome were evaluated in both cohorts, adjusted for multiple covariates at baseline. In the derivation cohort, 6 clusters were identified as metabolic profiles. Compared with cluster 1, cluster 3 (severe hyperglycemia) had increased risks of DKD (hazard ratio [HR] [95% CI]: 1.72 [1.39-2.12]), macroalbuminuria (2.74 [1.84-4.08]), ESRD (4.31 [1.16-15.99]), and eGFR decline [P < .001]; cluster 4 (moderate dyslipidemia) had increased risks of DKD (1.97 [1.53-2.54]) and macroalbuminuria (2.62 [1.61-4.25]). In the validation cohort, clusters 3 and 4 were replicated to have significantly increased risks of DKD (adjusted ORs: 1.24 [1.07-1.44] and 1.39 [1.03-1.87]). We identified 6 prevalent metabolic profiles in patients with T2D. Severe hyperglycemia and moderate dyslipidemia were validated as significant risk markers for DKD.

Effects of sleep duration and changes in body mass index on diabetic kidney disease: a prospective cohort study.

To examine the associations of sleep duration and changes in BMI with the onset of diabetic kidney disease (DKD). 2,959 participants with type 2 diabetes were divided into three groups based on sleep duration: short (<7 h/day), intermediate (7-9 h/day), or long (>9 h/day). Changes in BMI during follow-up were trisected into loss, stable, or gain groups. DKD was defined as either the urinary albumin/creatinine ratio (UACR) ≥ 3.39 mg/mmol or the estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73m², or both. Cox regression models were used to assess hazard ratios (HRs) and 95% confidence intervals (CIs). During a mean follow-up of 2.3 years, DKD occurred in 613 participants (20.7%). A J-shaped curve was observed between sleep duration and DKD. Compared to intermediate sleep duration, long sleep duration was associated with higher risks of DKD (HR 1.47; 95% CI: 1.19-1.81). In the joint analyses, compared to participants with intermediate sleep duration and stable BMI, long sleep duration with BMI gain had the highest risks of DKD (HR 2.04; 95% CI: 1.48-2.83). In contrast, short or intermediate sleep duration accompanied by decrease in BMI was associated with a reduced risk of DKD, with HRs of 0.50 (95% CI: 0.31-0.82) and 0.61 (95% CI:0.47-0.80), respectively. Long sleep duration is significantly associated with an increased risk of DKD, which is further amplified by obesity or BMI gain. These findings suggest that both proper sleep duration and weight control are essential to preventing DKD.

Effect of Prunetin on Streptozotocin-Induced Diabetic Nephropathy in Rats - a Biochemical and Molecular Approach.

In the modern era, chronic kidney failure due to diabetes has spread across the globe. Prunetin (PRU), a component of herbal medicines, has a broad variety of pharmacological activities; these may help to slow the onset of diabetic kidney disease. The anti-nephropathic effects of PRU have not yet been reported. The present study explored the potential nephroprotective actions of PRU in diabetic rats. For 28 days, nephropathic rats were given oral doses of PRU (20, 40, and 80 mg/kg). Body weight, blood urea, creatinine, total protein, lipid profile, liver marker enzymes, carbohydrate metabolic enzymes, C-reactive protein, antioxidants, lipid peroxidative indicators, and the expression of insulin receptor substrate 1 (IRS-1) and glucose transporter 2 (GLUT-2) mRNA genes were all examined. Histological examinations of the kidneys, liver, and pancreas were also performed. The oral treatment of PRU drastically lowered the blood glucose, HbA1c, blood urea, creatinine, serum glutamic-oxaloacetic transaminase, serum glutamic pyruvic transaminase, alkaline phosphatase, lipid profile, and hexokinase. Meanwhile, the levels of fructose 1,6-bisphosphatase, glucose-6-phosphatase, and phosphoenol pyruvate carboxykinase were all elevated, but glucose-6-phosphate dehydrogenase dropped significantly. Inflammatory marker antioxidants and lipid peroxidative markers were also less persistent due to this administration. PRU upregulated the IRS-1 and GLUT-2 gene expression in the nephropathic group. The possible renoprotective properties of PRU were validated by histopathology of the liver, kidney, and pancreatic tissues. It is therefore proposed that PRU (80 mg/kg) has considerable renoprotective benefits in diabetic nephropathy in rats.

Urine Immunoglobin G Greater Than 2.45 mg/L Has a Correlation with the Onset and Progression of Diabetic Kidney Disease: A Retrospective Cohort Study.

To further assess the correlation between urine immunoglobin G (IgG) greater than 2.45 mg/L and the onset and progression of diabetic kidney disease (DKD). One thousand and thirty-five patients with type 2 diabetes mellitus (T2DM) were divided into two groups based on the baseline levels of 24 h urinary albumin excretion (24 h UAE): one group with 24 h UAE < 30 mg/24 h and one with 24 h UAE ≥ 30 mg/24 h. The groups were subdivided using baseline levels of urine IgG (≤2.45 mg/L and >2.45 mg/L; hereafter, the Low and High groups, respectively). We used logistic regression to assess the risk of urine IgG and it exceeding 2.45 mg/L. Kaplan-Meier curves were used to compare the onset and progression time of DKD. The receiver operating characteristic curve was used to test the predictive value of urine IgG exceeding 2.45 mg/L. Urine IgG was an independent risk factor for the onset and progression of DKD. The rate and risk of DKD onset and progression at the end of follow-up increased significantly in the High group. The onset and progression time of DKD was earlier in the High group. Urine IgG exceeding 2.45 mg/L has a certain predictive value for DKD onset. Urine IgG exceeding 2.45 mg/L has a correlation with the onset and progression of DKD, and it also has a certain predictive value for DKD onset.

Vitamin D and Diabetic Kidney Disease.

Vitamin D is a hormone involved in many physiological processes. Its active form, 1,25(OH)2D3, modulates serum calcium-phosphate homeostasis and skeletal homeostasis. A growing body of evidence has demonstrated the renoprotective effects of vitamin D. Vitamin D modulates endothelial function, is associated with podocyte preservation, regulates the renin-angiotensin-aldosterone system, and has anti-inflammatory effects. Diabetic kidney disease (DKD) is a leading cause of end-stage kidney disease worldwide. There are numerous studies supporting vitamin D as a renoprotector, potentially delaying the onset of DKD. This review summarizes the findings of current research on vitamin D and its role in DKD.

ATR‐FTIR Spectroscopy for Early Detection of Diabetic Kidney Disease

AbstractCurrent screening methods for diabetic kidney disease (DKD), characterized by albumin excretion in urine, are expensive or only identify patients in late disease stages. Hence, there is need for a cost‐effective, quick, and portable screening tool which identifies patients at DKD onset. Here we report that ultracentrifugation coupled with infrared spectroscopy and machine learning can identify and quantify low level microalbuminuria in urine samples from a cohort of diabetic patients (n=155) and controls (n=22). Independent testing of the methods indicated that classification analysis discriminated between normo‐ and micro/macroalbuminuric samples with sensitivity of &gt;91 % and specificity of &gt;99 %. Regression methods quantified albumin concentration in the samples with error values of 17 and 44 mg/L for normo‐ and microalbuminuric patients. Using only 700 μL of sample, this approach identifies patients at an earlier stage of disease than a urinary dipstick, whilst also yielding results cheaper and faster than the albumin to creatinine ratio.

What’s New in the Molecular Mechanisms of Diabetic Kidney Disease: Recent Advances

Diabetic kidney disease (DKD) is the leading cause of chronic kidney disease, including end-stage kidney disease, and increases the risk of cardiovascular mortality. Although the treatment options for DKD, including angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, sodium-glucose cotransporter 2 inhibitors, and mineralocorticoid receptor antagonists, have advanced, their efficacy is still limited. Thus, a deeper understanding of the molecular mechanisms of DKD onset and progression is necessary for the development of new and innovative treatments for DKD. The complex pathogenesis of DKD includes various different pathways, and the mechanisms of DKD can be broadly classified into inflammatory, fibrotic, metabolic, and hemodynamic factors. Here, we summarize the recent findings in basic research, focusing on each factor and recent advances in the treatment of DKD. Collective evidence from basic and clinical research studies is helpful for understanding the definitive mechanisms of DKD and their regulatory systems. Further comprehensive exploration is warranted to advance our knowledge of the pathogenesis of DKD and establish novel treatments and preventive strategies.

Impaired Amino Acid Metabolism and Its Correlation with Diabetic Kidney Disease Progression in Type 2 Diabetes Mellitus.

Background: Metabolomics is useful in elucidating the progression of diabetes; however, the follow-up changes in metabolomics among health, diabetes mellitus, and diabetic kidney disease (DKD) have not been reported. This study was aimed to reveal metabolomic signatures in diabetes development and progression. Methods: In this cross-sectional study, we compared healthy (n = 30), type 2 diabetes mellitus (T2DM) (n = 30), and DKD (n = 30) subjects with the goal of identifying gradual altering metabolites. Then, a prospective study was performed in T2DM patients to evaluate these altered metabolites in the onset of DKD. Logistic regression was conducted to predict rapid eGFR decline in T2DM subjects using altered metabolites. The prospective association of metabolites with the risk of developing DKD was examined using logistic regression and restricted cubic spline regression models. Results: In this cross-sectional study, impaired amino acid metabolism was the main metabolic signature in the onset and development of diabetes, which was characterized by increased N-acetylaspartic acid, L-valine, isoleucine, asparagine, betaine, and L-methionine levels in both the T2DM and DKD groups. These candidate metabolites could distinguish the DKD group from the T2DM group. In the follow-up study, higher baseline levels of L-valine and isoleucine were significantly associated with an increased risk of rapid eGFR decline in T2DM patients. Of these, L-valine and isoleucine were independent risk factors for the development of DKD. Notably, nonlinear associations were also observed for higher baseline levels of L-valine and isoleucine, with an increased risk of DKD among patients with T2DM. Conclusion: Amino acid metabolism was disturbed in diabetes, and N-acetylaspartic acid, L-valine, isoleucine, asparagine, betaine, and L-methionine could be biomarkers for the onset and progression of diabetes. Furthermore, high levels of L-valine and isoleucine may be risk factors for DKD development.

405-P: Glycemic Control Impacts Renal Function Decline among People with Type 1 Diabetes after the Onset of Diabetic Kidney Disease

While poor glycemic control increases the risk of diabetic kidney disease (DKD) , its impact on renal function decline among those with established DKD is unclear. To examine this, we tested the relationship between baseline HbA1c and renal outcomes in the 3-year Preventing Early Renal Loss (PERL) trial (n=530) , which included persons with type 1 diabetes (T1D) and early-to-moderate DKD (eGFR 40-100 ml/min/1.73m2 and persistent albuminuria and/or ongoing GFR decline) . In Cox regression models, baseline HbA1c was associated (p&amp;lt;0.0001) with a higher risk of progression to ESKD or serum creatinine doubling (HR 1.87 per HbA1c unit increment, 95% CI 1.42-2.47) , and in mixed-effects linear regression models, with 0.87 and 0.51 ml/min/1.73m2/year higher rates of estimated glomerular filtration rate (eGFR) and iohexol GFR decline (p&amp;lt;0.00for both) . Baseline albumin excretion rate (AER) was a modifier of the HbA1c-GFR slope relationships (p for interaction &amp;lt;0.05) , such that HbA1c was associated with a higher rate of GFR decline among those with AER≥200 μg/min than among those with AER&amp;lt;20 or 20≤AER&amp;lt;200 (Fig.1) . Thus, worse glycemic control in PERL was a major determinant of GFR decline and ESKD risk after DKD onset, especially in persons with overt proteinuria. Efforts to normalize HbA1c should continue among such persons. Disclosure H.Shah: None. J.B.Mcgill: Advisory Panel; Gilead Sciences, Inc., Lilly Diabetes, MannKind Corporation, Novo Nordisk A/S, Provention Bio, Inc., Salix Pharmaceuticals, Consultant; Bayer AG, Boehringer Ingelheim International GmbH, Research Support; Dexcom, Inc., Novo Nordisk. I.B.Hirsch: Consultant; Abbott Diabetes, Bigfoot Biomedical, Inc., GWave, Roche Diabetes Care, Research Support; Beta Bionics, Inc., Insulet Corporation, Medtronic. C.Wu: None. A.Galecki: None. M.Mauer: None. A.Doria: Research Support; Novo Nordisk Foundation. Perl consortium: n/a. Funding National Institutes of Health UC4DK101108Juvenile Diabetes Research Foundation 17-2012-377The Leona M. and Harry B. Helmsley Charitable Trust 2018PG-T1D014

The Effects of Exercise Habit on Albuminuria and Metabolic Indices in Patients with Type 2 Diabetes Mellitus: A Cross-Sectional Study.

Background and Objectives: Diabetes mellitus (DM) can cause macrovascular and microvascular complications, potentially resulting in further life-threatening complications. In general, the global prevalence of type 2 DM is increasing. To date, the care of DM comprises three aspects: diet, medication and exercise; among them, exercise is the most economical. Albuminuria is associated with renal injury and the progress of chronic kidney disease (CKD). The effects of habitual exercise in patients with new onset of diabetic kidney disease (DKD) have not been generally recognized. Our aim was to conduct an observational study regarding the effects of regular exercise on proteinuria and associated metabolic indices in patients with newly diagnosed type 2 DM. To investigate the effects of an exercise habit on albuminuria and the metabolic indices including renal function, blood glucose, and plasma lipids among patients with newly diagnosed type 2 DM. Materials and Methods: A cross-sectional study was conducted on newly diagnosed DM patients in two teaching hospitals in Taiwan from 1 June to 31 December 2020. The DM patients participated in the Diabetes Shared Care Network. According to the DM care mode, the patients’ blood biochemical results were analysed. Based on exercise duration, the patients were divided into two groups, i.e., the exercise group (≥150 min per week) and the non-exercise group (<150 min per week). Clinical demographic features and laboratory examination including blood and urine biochemistries were determined. Results: A total of 229 patients including 99 males (43.2%) and 130 females (56.8%) participated in the study. The proportion of DM patients with normoalbuminuria was higher (p < 0.05) in the exercise group (69.8%) than in the non-exercise group (53.7%), and the proportion of DM patients with micro or macroalbuminuria was lower in the exercise group (30.2%) than in the non-exercise group (46.3%). Levels of glycated hemoglobin (HbA1c), fasting plasma glucose (FPG), triglycerides (TG) and high-density lipoprotein (HDL) were significantly different in both groups. Compared with the non-exercise group, lower HbA1c (6.89 ± 0.69 vs. 7.16 ± 1.05%) (p < 0.05), lower FPG (121.9 ± 25.7 vs. 140.5 ± 42.4 mg/dL) (p < 0.05), lower TG (115.6 ± 53.6 vs. 150.2 ± 15.4 mg/dL) (p < 0.05), and higher HDL (50.3 ± 11.4 vs. 44.1 ± 9.26 mg/dL) (p < 0.05) levels were noted in the exercise group. Conclusions: Regular exercise remains imperative and may bear an impact on albuminuria, blood glucose, and plasma lipids among type 2 DM patients. Therefore, medical staff and healthcare providers should encourage patients to maintain an exercise duration ≥150 min per week for preventing and controlling DM progression.

Pathophysiologic Mechanisms and Potential Biomarkers in Diabetic Kidney Disease.

Although diabetic kidney disease (DKD) remains the leading cause of end-stage kidney disease eventually requiring chronic kidney replacement therapy, the prevalence of DKD has failed to decline over the past 30 years. In order to reduce disease prevalence, extensive research has been ongoing to improve prediction of DKD onset and progression. Although the most commonly used markers of DKD are albuminuria and estimated glomerular filtration rate, their limitations have encouraged researchers to search for novel biomarkers that could improve risk stratification. Considering that DKD is a complex disease process that involves several pathophysiologic mechanisms such as hyperglycemia induced inflammation, oxidative stress, tubular damage, eventually leading to kidney damage and fibrosis, many novel biomarkers that capture one specific mechanism of the disease have been developed. Moreover, the increasing use of high-throughput omic approaches to analyze biological samples that include proteomics, metabolomics, and transcriptomics has emerged as a strong tool in biomarker discovery. This review will first describe recent advances in the understanding of the pathophysiology of DKD, and second, describe the current clinical biomarkers for DKD, as well as the current status of multiple potential novel biomarkers with respect to protein biomarkers, proteomics, metabolomics, and transcriptomics.

Association Between Duration of Diabetes Mellitus and Chronic Kidney Disease Staging Among Type II Diabetes Mellitus Patients in Padang Terap, Kedah, Malaysia

Background: Chronic kidney disease (CKD) is a global health burden with a high economic cost to health systems and diabetes mellitus (DM) is one of the significant predictors to the development of CKD. The study aimed to determine the association between the duration of DM and CKD staging among T2DM patients. Methods: A cross-sectional study was conducted using secondary data from the National Diabetes Registry’s (NDR) audited patients for the year of 2018 to 2020 at Padang Terap, Kedah. The eGFR was calculated from serum creatinine value and classified into six categories based on the KDIGO classification. Multinominal logistic regression analysis was used to determine the association. Results: A total of 963 patients were included in the study. The prevalence of CKD was 38.6%. The majority of T2DM patients were elderly Malay females. The prevalence of stage 1 was 6.95%, stage 2 was 5.4%, stage 3a was 12.35%, stage 3b was 8.10%, stage 4 was 3.86% and stage 5 was 1.93%. In the multivariable analysis, in model 1 (unadjusted) the p-value showed a significant association between duration of DM and CKD staging. By adjusting with other blocks of variables (Model 2 to Model 6) were also found to be in a significant association (p&lt;0.05). Conclusion: It is concluded that there was an association between the duration of DM and CKD staging. Early detection of CKD and glycemic control are essential to delay the onset of diabetic kidney disease. Diabetes control should be optimized to reduce diabetes-related complications and minimize adverse events.

Genetic variant of TGF-ß associated with decreased renal function in type II diabetes mellitus patient: single center pilot study in Indonesia

The interaction between genetic factors, blood glucose and hypertension plays a role in the onset of diabetic kidney disease (DKD) in type II diabetes mellitus (T2DM). Genetic variation of TGF-ß1 is associated with renal complication in T2DM with varying results between ethnicities. The Jambi Malay ethnic, which is the majority ethnic in Jambi Province, is an area that reports an increased prevalence of T2DM with DKD as the most frequent microvascular complications. In addition, previous study reported controlling blood glucose not associated with DKD indicating genetic may have play a role in DKD in this population. Studies related to genetic variation and decreased kidney function in T2DM patients has never been performed in this ethnic group. This study aimed to investigate the role of TGF-ß genetic variation as risk factor for decreased renal function in T2DM patients from Jambi Malay ethnicity. We conducted a cross sectional study involving 70 patients with T2DM. The inclusion criteria for renal complication based on a decrease in the glomerular filtration rate (GFR) of less than 60 mL/min/1.73. The genotyping method used was amplification refractory mutation system polymerase chain reaction (ARMS-PCR) for TGF-β1 rs1800470 T/C. Bivariate and multivariate analysis was performed to analyze phenotype and genotype association. The result of bivariate analysis showed T2DM patients with genotype CT (p:0.006; OR:0.125; 95% CI:0.027-0.575) and CC (p:0.007; OR:0.104; 95% CI:0.020-0.546) or C allele carrier (p:0.003; OR:0.117; 95% CI:0.027-0.500) had lower risk for decreased renal function than TT genotype. Multivariate analysis that included blood pressure and age variables showed the same finding for CT (p:0.007; OR:0.086; 95% CI:0.014-0.508) and CC genotype (p:0.022; OR:0.115; 95% CI:0.018-0.731). It is concluded from this study that T2DM patients with genotype CT, CC and carrier allele C have a lower risk for suffering kidney complications than genotype TT.

A Custom Target Next-Generation Sequencing 70-Gene Panel and Replication Study to Identify Genetic Markers of Diabetic Kidney Disease.

Diabetic kidney disease (DKD) has been pointed out as a prominent cause of chronic and end-stage renal disease (ESRD). There is a genetic predisposition to DKD, although clinically relevant loci are yet to be identified. We utilized a custom target next-generation sequencing 70-gene panel to screen a discovery cohort of 150 controls, DKD and DKD-ESRD patients. Relevant SNPs for the susceptibility and clinical evolution of DKD were replicated in an independent validation cohort of 824 controls and patients. A network analysis aiming to assess the impact of variability along specific pathways was also conducted. Forty-eight SNPs displayed significantly different frequencies in the study groups. Of these, 28 with p-values lower than 0.01 were selected for replication. MYH9 rs710181 was inversely associated with the risk of DKD (OR = 0.52 (0.28–0.97), p = 0.033), whilst SOWAHB rs13140552 and CNDP1 rs4891564 were not carried by cases or controls, respectively (p = 0.044 and 0.023). In addition, the RGMA rs1969589 CC genotype was significantly correlated with lower albumin-to-creatinine ratios in the DKD patients (711.8 ± 113.0 vs. 1375.9 ± 474.1 mg/g for TC/TT; mean difference = 823.5 (84.46–1563.0); p = 0.030). No biological pathway stood out as more significantly affected by genetic variability. Our findings reveal new variants that could be useful as biomarkers of DKD onset and/or evolution.

Real-World Diagnosis and Treatment of Diabetic Kidney Disease.

People with type2 diabetes mellitus (T2DM) and diabetic kidney disease (DKD) have increased morbidity and mortality risk. Angiotensin-converting enzyme inhibitors (ACEi) or angiotensinII receptor blockers (ARB) are recommended to slow kidney function decline in DKD. This representative, real-world data analysis of patients with T2DM was performed to detect onset of DKD and determine methods and timing of DKD diagnosis and time to initiation of ACEi/ARB therapy. Patients diagnosed with T2DM before January1, 2016 who developed DKD between January1, 2017 and June30, 2019 were identified from a longitudinal ambulatory electronic health record (EHR) dataset (Veradigm Inc). Each record was analyzed using the CLinical INTelligence engine (CLINT™, HealthPals, Inc.) to identify delays and gaps in diagnosing DKD. DKD was diagnosed through two reduced estimated glomerular filtration rate (eGFR; < 60mL/min/1.73m2) measurements at least 90days apart, a single elevated urine albumin-to-creatinine ratio (UACR; > 30mg/g) measurement, or ICD-9/10 diagnosis codes for DKD and/or albuminuria. Time to diagnose (TTD), time to treat (TTT), and diagnosis to treatment time were assessed. Of 6,499,409 patients with T2DM before January 2016, 245,978 developed DKD between January1, 2017 and June30, 2019. In this DKD cohort, ca. 50% were first identified through EHR diagnosis and ca. 50% by UACR or eGFR lab-based diagnosis. In patients who had UACR/eGFR assessed, more than 90% exhibited DKD-level results on the first diagnostic test. Average TTD after eGFR labs was 2years; average TTT with ACEi/ARB was 6-9months after DKD lab evidence. The majority of patients who developed DKD received ACEi/ARB therapy 6-7months after diagnosis. In a contemporary, large national cohort of patients with T2DM, progression to DKD was common but likely underrepresented. The low rate of DKD-screening labs, along with sizable delays in diagnosis of DKD and initiation of ACEi/ARB therapy, indicates that many patients who progress to DKD are not being properly treated.

Relationship Between the TyG Index and Diabetic Kidney Disease in Patients with Type-2 Diabetes Mellitus.

BackgroundDiabetic kidney disease (DKD) lacks a simple and relatively accurate predictor. The Triglyceride–Glucose (TyG) Index is a proxy of insulin resistance, but the association between the TyG Index and DKD is less certain. We investigated if the TyG Index can predict DKD onset effectively.Materials and MethodsCross-sectional and longitudinal analyses were undertaken. In total, 1432 type-2 diabetes mellitus (T2DM) patients were included in the cross-sectional analysis. The TyG Index (calculated by ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]) was split into three tertiles. Associations of the TyG Index with microalbuminuria and estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 were calculated. Longitudinally, 424 patients without DKD at baseline were followed up for 21 (range, 12–24) months. The main outcome was DKD prevalence as defined with eGFR <60 mL/min/1.73 m2 or continuously increased urinary microalbuminuria: creatinine ratio (>30 mg/mL) over 3 months. Cox regression was used to analyze the association between the TyG Index at baseline and DKD. Receiver operating characteristics curve (ROC) analysis was used to assess the sensitivity and specificity of the TyG Index in predicting DKD.ResultsIn cross-sectional analysis, patients with a higher TyG Index had a higher risk of microalbuminuria (OR = 2.342, 95% CI = 1.744–3.144, p < 0.001), and eGFR <60 mL/min/1.73 m2 (1.696, 95% CI =1.096–2.625, p = 0.018). Longitudinally, 94 of 424 participants developed DKD. After confounder adjustment, patients in the high tertile of the TyG Index at baseline had a greater risk to developing DKD than those in the low tertile (HR = 1.727, 95% CI = 1.042–2.863, p = 0.034). The area under the ROC curve was 0.69 (0.63–0.76).ConclusionThe TyG Index is a potential predictor for DKD in T2DM patients.Clinical TrialClinical Trials identification number = NCT03692884.

T-Cell Expression and Release of Kidney Injury Molecule-1 in Response to Glucose Variations Initiates Kidney Injury in Early Diabetes.

Half of the mortality in diabetes is seen in individuals <50 years of age and commonly predicted by the early onset of diabetic kidney disease (DKD). In type 1 diabetes, increased urinary albumin-to-creatinine ratio (uACR) during adolescence defines this risk, but the pathological factors responsible remain unknown. We postulated that early in diabetes, glucose variations contribute to kidney injury molecule-1 (KIM-1) release from circulating T cells, elevating uACR and DKD risk. DKD risk was assigned in youth with type 1 diabetes (n = 100; 20.0 ± 2.8 years; males/females, 54:46; HbA1c 66.1 [12.3] mmol/mol; diabetes duration 10.7 ± 5.2 years; and BMI 24.5 [5.3] kg/m2) and 10-year historical uACR, HbA1c, and random blood glucose concentrations collected retrospectively. Glucose fluctuations in the absence of diabetes were also compared with streptozotocin diabetes in apolipoprotein E -/- mice. Kidney biopsies were used to examine infiltration of KIM-1-expressing T cells in DKD and compared with other chronic kidney disease. Individuals at high risk for DKD had persistent elevations in uACR defined by area under the curve (AUC; uACRAUC0-10yrs, 29.7 ± 8.8 vs. 4.5 ± 0.5; P < 0.01 vs. low risk) and early kidney dysfunction, including ∼8.3 mL/min/1.73 m2 higher estimated glomerular filtration rates (modified Schwartz equation; Padj < 0.031 vs. low risk) and plasma KIM-1 concentrations (∼15% higher vs. low risk; P < 0.034). High-risk individuals had greater glycemic variability and increased peripheral blood T-cell KIM-1 expression, particularly on CD8+ T cells. These findings were confirmed in a murine model of glycemic variability both in the presence and absence of diabetes. KIM-1+ T cells were also infiltrating kidney biopsies from individuals with DKD. Healthy primary human proximal tubule epithelial cells exposed to plasma from high-risk youth with diabetes showed elevated collagen IV and sodium-glucose cotransporter 2 expression, alleviated with KIM-1 blockade. Taken together, these studies suggest that glycemic variations confer risk for DKD in diabetes via increased CD8+ T-cell production of KIM-1.