Neutrophil Percentage to Albumin Ratio is Associated With Diabetic Kidney Disease in Community Cohorts: A More In-Depth Insight Incorporating Machine Learning.

Clinical Challenges in Diagnosis and Management of Diabetic Kidney Disease

BackgroundThe Cardiac Metabolic Index (CMI) is a comprehensive metabolic indicator, but studies on its relationship with Diabetic Kidney Disease (DKD) are limited. We aim to explore the association between CMI and DKD.MethodsWe obtained participant-related data from the National Health and Nutrition Examination Survey (NHANES), including complete information on DKD, CMI, and other covariates. We employed weighted multivariable logistic regression models, restricted cubic spline (RCS) regression analysis, subgroup analyses, and interaction tests to explore the relationship between CMI and DKD. Additionally, we utilized receiver operating characteristic (ROC) curves to compare the performance of CMI in identifying DKD relative to a body shape index (ABSI), body roundness index (BRI), visceral adiposity index (VAI), and lipid accumulation product (LAP) indices.ResultsAccording to the logistic regression analysis, a positive correlation between CMI and DKD was observed among the 2371 participants included in the study (OR: 1.40, 95% CI: 1.19–1.66). RCS analysis indicated that this relationship is nonlinear. When CMI was converted from a continuous variable to quartiles, the prevalence of DKD in the highest quartile group showed a significant 84% increase compared to the lowest quartile group (OR: 1.84, 95% CI: 1.24–2.72). The area under the ROC curve of CMI for identifying DKD was 0.67, outperforming other indices. The results of subgroup analyses and interaction tests were stable.ConclusionElevated CMI is associated with an increased risk of DKD and can serve as a low-cost screening tool, allowing physicians to potentially identify high-risk diabetic patients early and implement timely interventions to slow the progression of DKD.

This investigation examined the possibility of a relationship between neutrophil-to-lymphocyte ratio (NLR) and diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM) patients. Adults with T2DM who were included in the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2020 were the subjects of the current cross-sectional investigation. Low estimated glomerular filtration rate (eGFR) (< 60 mL/min/1.73 m2) or albuminuria (urinary albumin-to-creatinine ratio (ACR) ≥ 30 mg/g) in T2DM patients were the diagnostic criteria for DKD. Weighted multivariable logistic regression models and generalized additive models were used to investigate the independent relationships between NLR levels with DKD, albuminuria, and low-eGFR. Additionally, we examined the relationships between DKD, albuminuria, and low-eGFR with other inflammatory markers, such as the aggregate index of systemic inflammation (AISI), systemic immune-inflammation index (SII), system inflammation response index (SIRI), and platelet-to-lymphocyte ratio (PLR) and monocyte-to-lymphocyte ratio (MLR). Their diagnostic capabilities were evaluated and contrasted using receiver operating characteristic (ROC) curves. 44.65% of the 7,153 participants who were recruited for this study were males. DKD, albuminuria, and low-eGFR were prevalent in 31.76%, 23.08%, and 14.55% of cases, respectively. Positive correlations were seen between the NLR with the prevalences of DKD, albuminuria, and low-eGFR. Subgroup analysis and interaction tests revealed that the associations of NLR with DKD, albuminuria, and low-eGFR were not significantly different across populations. In addition, MLR, SII and SIRI showed positive associations with the prevalence of DKD. ROC analysis discovered that when compared to other inflammatory markers (MLR, PLR, SII, SIRI, and AISI), NLR may demonstrate more discriminatory power and accuracy in assessing the risk of DKD, albuminuria, and low-eGFR. Compared to other inflammatory markers (MLR, PLR, SII, SIRI, and AISI), NLR may serve as the more effective potential inflammatory marker for identifying the risk of DKD, albuminuria, and low-eGFR in US T2DM patients. T2DM patients with elevated levels of NLR, MLR, SII, and SIRI should be closely monitored for their potential risk to renal function.

To explore and validate the association between the oxidative balance and prevalence of diabetic kidney disease (DKD) and mortality in patients with diabetes. A large and representative sample from the National Health and Nutrition Examination Survey (NHANES) from 2013 to 2016 was analyzed to study the potential association between Oxidative Balance Score (OBS) and prognosis of DKD in adult diabetic patients. Weighted multivariate logistic regression analysis was conducted to examine the relationship between OBS and DKD risk. Subgroup analysis, sensitivity analysis, and mediation effect analysis were conducted to explore the effect of the covariates and assess the robustness of the findings. Mendelian randomization (MR) was employed to evaluate the correlated relationship between mitochondrial reactive oxygen species (ROS) levels and DKD at the genetic level. The highest OBS quartile showed the most significant negative correlation with DKD compared to the lowest OBS quartile (OR = 0.62, 95% CI 0.41-0.92, P = 0.017). Higher OBS was associated with a reduced risk of DKD (OR = 0.96; 95% CI = 0.93, 0.98; P < 0.001) and mortality (P = 0.021 by log-rank) in diabetic patients. This association remained robust even after excluding individual OBS components. Subgroup analysis revealed the interaction of metabolic syndrome on OBS was significant. Mediation analyses revealed that OBS's effect on DKD was independent of blood uric acid and cholesterol. Restricted cubic spline (RCS) analysis indicated a typical L-shaped relationship between OBS and DKD risk. The physical activity was identified as the core variable predicting DKD risk by two machine learning algorithms. MR showed a potential correlated relationship between ROS and microalbuminuria in DKD. The high level of oxidative balance score was negatively correlated with the risk of DKD and mortality in diabetic patients.

Non-High-Density Lipoprotein Cholesterol to High-Density Lipoprotein Cholesterol Ratio (NHHR) is a significant indicator of atherosclerosis. However, its association with diabetic kidney disease (DKD) remains unclear. This study aims to explore the relationship between NHHR and the prevalence of DKD among the U.S. adults using data from the National Health and Nutrition Examination Survey (NHANES) spanning 1999 to 2020. Participants were selected based on the stringent inclusion and exclusion criteria. We utilized single-factor analysis, multivariate logistic regression, and smooth curve fitting to investigate the relationship between NHHR and DKD. Our study included 8,329 diabetic individuals, who were categorized into DKD and non-DKD groups based on the presence or absence of kidney damage. A significant difference in NHHR was observed between these groups. After adjusting for potential confounders, we found that NHHR was positively associated with the prevalence of DKD. Specifically, each one-unit increase in NHHR corresponded to a 6% rise in the prevalence of DKD, with this association remaining significant across stratified NHHR values. Threshold effect analysis revealed an inflection point at an NHHR of 1.75, beyond this point, each unit increase in NHHR was associated with a 7% increase in the prevalence of DKD. Subgroup analysis confirmed the robustness of these findings. Our study demonstrates a significant correlation between NHHR and DKD prevalence, suggesting that monitoring NHHR could be an effective strategy for reducing DKD prevalence.

Diabetic kidney disease (DKD) represents a significant microvascular complication associated with diabetes and serves as a major contributor to end-stage renal disease. While many studies have highlighted the renal protective effects of the anti-aging protein Klotho, the potential link between Klotho and DKD within individuals with diabetes remains a subject of debate, and comprehensive studies utilizing large population-based databases are still needed. This cross-sectional study, which is representative of the national population, examined data from US patients with diabetes aged 40-79years, collected during the 2007-2016 cycles of the National Health and Nutrition Examination Survey (NHANES). Serum α-Klotho levels were determined using enzyme-linked immunosorbent assay (ELISA) techniques. Given that serum Klorho levels are not normally distributed, our analysis is based on values converted from the natural logarithm of Klotho. To assess the association between Klotho levels and the prevalence of DKD, multivariate regression models were utilized, taking into account potential confounding factors. Furthermore, we applied smooth curve fitting and segmented regression analyses to investigate possible threshold effects and identify inflection points. Subgroup analyses and cross-tests were performed to assess the consistency of associations in the general population. The investigation included 4490 individuals with diabetes, with an median age of 60.0years and 48.2% of them being male. Among these participants, 1352 (30.1%) were diagnosed with DKD. The fully adjusted model (model3) indicated a significant inverse relationship between Klotho levels and DKD prevalence. Statistical analysis showed that in fully adjusted model 3, each 1-unit increase in log-transformed Klotho was associated with a 42% reduction in DKD prevalence [OR 0.58, 95%CI (0.42, 0.80), p = 0.002]. Further analysis using smooth curve fitting revealed a U-shaped relationship between Klotho levels and DKD prevalence, with an inflection point at 6.82 (after natural logarithm conversion). This study identified a U-shaped relationship between Klotho levels and the prevalence of DKD in middle-aged and older adults with diabetes in the USA, with an inflection point of 6.82 (after natural logarithm conversion). Prior to this threshold, the relationship between Klotho and DKD prevalence was negatively correlated, while after the inflection point, the relationship became positive. Future studies are recommended to investigate the causal relationship behind this relationship.

The aim of this cross-sectional study was to elucidate the associations between various domains of physical activity, such as occupation-related (OPA), transportation-related (TPA), leisure-time (LTPA) and overall physical activity (PA), and diabetic kidney disease. Our study encompassed 2,633 participants, drawn from the cross-sectional surveys of the National Health and Nutrition Examination Survey (NHANES) between 2007 and 2018, and employed survey-weighted logistic regression, generalized linear regression, and restricted cubic spline (RCS) analyses to ascertain the relationship between different domains of physical activity and diabetic kidney disease. After controlling for all confounders, multivariate logistic regression analyses revealed a lack of correlation between the various domains of physical activity and the prevalence of diabetic kidney disease. Multiple generalized linear regression analyses showed that durations of PA (β = 0.05, 95% CI, 0.01-0.09, P= 0.012) and TPA (β = 0.32, 95% CI, 0.10-0.55, P = 0.006) were positively associated with eGFR levels; and LTPA durations were inversely associated with UACR levels (β = -5.97, 95% CI, -10.50 - -1.44, P = 0.011). The RCS curves demonstrated a nonlinear relationship between PA, OPA, and eGFR, as well as a nonlinear correlation between PA and ACR. Subgroup and sensitivity analyses largely aligned with the outcomes of the multivariate generalized linear regression, underscoring the robustness of our findings. Our population-based study explored the association between different domains of physical activity and diabetic kidney disease. Contrary to our expectations, we found no significant association between the duration of physical activity across all domains and the prevalence of diabetic nephropathy. Nonetheless, renal function markers, including eGFR and UACR, exhibited significant correlations with the duration of total physical activity (TPA) and leisure-time physical activity (LTPA), respectively, among diabetic patients. Interestingly, our findings suggest that diabetic patients engage in physical activity to preserve renal function, ensuring moderate exercise durations not exceeding 35 hours per week.

Kidney Disease in People With Diabetes: The Expanding Epidemic

BackgroundSerum Klotho, a biomarker associated with anti-aging, has been implicated in kidney disease. However, there is a lack of robust evidence for the relationship between the serum Klotho and diabetic kidney disease (DKD). This study aimed to investigate the association of the serum Klotho levels with DKD and assess the relationship between serum Klotho and all-cause mortality in individuals with DKD.MethodsWe utilized data from the 2007–2016 National Health and Nutrition Examination Survey (NHANES), incorporating both cross-sectional and cohort study designs. The association between the serum Klotho and DKD was examined using weighted logistic regression models. To estimate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) for all-cause mortality, weighted Çox proportional hazards models were applied. Restricted cubic spline analysis was used to assess the linear or nonlinear relationships between the serum Klotho and DKD or all-cause mortality. Additionally, mediation analysis was conducted to determine whether the systemic immune-inflammatory index (SII) mediated the effect of serum Klotho on all-cause mortality.ResultsOur findings revealed a significant reverse association between serum Klotho and DKD after adjusting for sociodemographic and lifestyle factors in Model 2 (odds ratio [OR] 0.65, 95% CI 0.47–0.90, P = 0.01). However, this association was attenuated and lost statistical significance after further adjustment for comorbidities, SII, estimated glomerular filtration rate, and urine albumin/creatinine ratio in Model 3 (OR 0.65, 95% CI 0.32–1.31, P = 0.2). During an average follow-up period of 76 months, a total of 795 individuals (34%) experienced mortality. Weighted multivariate Cox regression models indicated that each one-unit increase in the serum Klotho was associated with a reduced risk of all-cause mortality (HR 0.48, 95% CI 0.29–0.82, P = 0.008) in DKD patients. Furthermore, restricted cubic spline analysis identified a nonlinear relationship between the serum Klotho and DKD (P for nonlinearity < 0.001), while a linear relationship was observed between serum Klotho and all-cause mortality (P for nonlinearity = 0.3480) among DKD populations. Stratified and interaction analysis confirmed the robustness of these core findings. Additionally, SII was found to partially mediate the association between serum Klotho and all-cause mortality, accounting for 5.7% of the effect.ConclusionsSerum Klotho is inversely associated with the prevalence of DKD and is also linked to reduced all-cause mortality in individuals with DKD.

Macrophage inflammatory protein-1β as a novel therapeutic target for renal protection in diabetic kidney disease

Rationale and Strategies for Early Detection and Management of Diabetic Kidney Disease

Previous research has shown a strong association between insulin resistance (IR) and both the onset and advancement of diabetic kidney disease (DKD). This research focuses on examining the relationship between IR and all-cause mortality in individuals with DKD. This study utilized data obtained from the National Health and Nutrition Examination Survey (NHANES), spanning the years 2001 to 2018. Insulin resistance was assessed using reliable indicators (HOMA-IR, TyG, TyG-BMI, and METS-IR). The relationship between IR indices and survival outcomes was evaluated through weighted multivariate Cox regression, Kaplan-Meier survival analysis, and restricted cubic spline (RCS) modeling. To examine non-linear associations, the log-likelihood ratio test was employed, with piecewise regression models used to establish confidence intervals and identify threshold values. Diagnostic precision and efficacy were gauged using Receiver Operating Characteristic (ROC) curves, Area Under the Curve (AUC) evaluations, and calibration plots. Moreover, to verify the consistency of our results, stratified analyses and interaction tests were conducted across variables including age, gender, Body Mass Index (BMI), hypertension, and cardiovascular status. This research involved a group of 1,588 individuals diagnosed with DKD. Over a median observation period of 74 months, 630 participants passed away. Using weighted multivariate Cox regression along with restricted cubic spline modeling, we identified non-linear associations between the four insulin resistance indices and all-cause mortality. An analysis of threshold effects pinpointed essential turning points for each IR index in this research: 1.14 for HOMA-IR, 9.18 for TyG, 207.9 for TyG-BMI, and 35.85 for METS-IR. It was noted that levels below these thresholds inversely correlated with all-cause mortality. In contrast, values above these points showed a significantly positive correlation, suggesting heightened mortality risks. The accuracy of these four IR metrics as indicators of all-cause mortality was confirmed through ROC and calibration curve analyses. In patients with DKD, an L-shaped association is noted between HOMA-IR and all-cause mortality, while TyG, TyG-BMI, and METS-IR exhibit U-shaped relationships. All four IR indices show good predictive performance.

Objective Given the significant impact of diabetic kidney disease (DKD) on morbidity and mortality in patients with type 2 diabetes mellitus (T2DM) and the potential preventive role of dietary factors, particularly dietary fiber, this study aimed to investigate the relationship between dietary fiber intake and the risk of DKD in adults with T2DM. Methods The medical records and other relevant data from patients with T2DM were retrieved from the United States National Health and Nutrition Examination Surveys (U.S. NHANES) from 2009 to 2018. Multivariate logistic regression and restricted cubic spline (RCS) regression were employed to investigate the relationship between dietary fiber intake and the risk of DKD in adult T2DM patients. Results The study involved 4,520 T2DM patients with a mean age of 59.16 years, consisting of 2,346 male patients (51.9%) and 2,174 female patients (48.1%). The prevalence of T2DM patients with DKD was 37.92% in the overall population. Regression analyses, after adjusting for confounders, showed that dietary fiber intake was negatively correlated with the prevalence of DKD. RCS analysis demonstrated a nonlinear negative correlation between the level of dietary fiber intake and the prevalence of DKD, with a threshold inflection point of 13.96 g/day. Subgroup analyses revealed that age, gender, race, smoking status, body mass index, hypertension, diabetes duration, glycosylated hemoglobin, and ACEI/ARB medication use did not significantly affect the negative correlations (p > 0.05). Conclusions Dietary fiber intake was negatively correlated with the prevalence of DKD in T2DM patients.

Background and Aims Diabetic kidney disease (DKD), occurs in 20–40% of patients with diabetes mellitus (DM), is the leading cause of end-stage renal disease (ESRD). DKD is a clinical diagnosis mainly based on the persistent albuminuria and reduced estimated glomerular filtration rate (eGFR) [1]. However, increased UACR and reduced eGFR are the final consequences due to DKD, novel biomarkers are critical for predicting DKD development. Osteopontin (OPN) is a profibrotic adhesion phosphoprotein that participates in cell chemotaxis, adhesion, migration, and proliferation, as well as extracellular matrix (ECM) hyperplasia. Hyperglycemia could enhance OPN gene expression through the activation of the renin-angiotensin system (RAS), mTOR pathway, NF-κB, and TGF-β pathway and then cause podocyte injury and ECM hyperplasia. Therefore, OPN upregulation is not only the result of various pathophysiological processes in DKD, but also results in kidney injury. Osteopontin (OPN) could predict incident DKD in DM patients [2], N-terminal OPN (ntOPN) has a stronger profibrotic adhesion effect than full-length OPN. This study aims to reveal the clinical benefit of ntOPN as a potential marker to identify DM patients at high risk of DKD, and establish ntOPN-based diagnostic and forecast models for renal outcomes in DM patients. Method We performed a cross-sectional study of 316 adults with Type 1 DM≥ 5 years or Type 2 DM, then followed by a prospective observational cohort study of 143 adult DM patients without renal involvement at baseline and follow-up for at least one year. During the follow-up period, the primary endpoint was “DKD occurrence”, defined as the presence of one of the following conditions in DM patients [3]: (1) repeat UACR ≥30 mg/g at least 2 of 3 measurements within 3 to 6 months; (2) eGFR &amp;lt;60 mL/min/1.73 m2 for more than three months; (3) renal pathological findings were consistent with DKD. The secondary endpoint was “DKD progression”, which included: (1) eGFR sustained decreased by at least 25%; (2) development of ESRD, and/or need for renal replacement therapy; (3) death from the renal cause. Logistic regression analysis was performed to analyze the relationship between parameters and the events of DKD occurrence and progression. Receiver operator characteristic (ROC) analysis was used to assess the predictive ability of established models for clinical endpoints. Results The median value of urinary ntOPN (UntOPN) was 44.15 ng/ml in the cross-sectional cohort, DKD prevalence was significantly higher in the high UntOPN group than in the low UntOPN group. The ROC curves of UntOPN, urinary neutrophil gelatinase-associated lipocalin (UNGAL), and their combination indicated that both combination and ntOPN alone perform better than UNGAL for DKD diagnosis (Fig. 1A). In the prospective cohort, UntOPN was an independent risk factor and further improved the predictive ability for DKD occurrence and DKD progression than UNGAL (Figs. 1B and 1C). Based on the parameters detected as risk factors for DKD occurrence and progression, we set up a series of multi-biomarker panels for DKD prediction using UntOPN, UNGAL, serum cystatin C, serum creatinine (Scr), UACR, and TCH/HDL-C ratio. Compared with the model of Scr + UACR, the area under ROC curve (AUC) of the six-biomarker model was higher, and also ranked the highest among the six ROC curves in predicting 1-year risk of DKD occurrence and DKD progression (Figs. 1B and 1C). Conclusion Our results showed that urinary ntOPN is associated with DKD development, and elevated urinary ntOPN is an independent predictor for DKD occurrence and progression. Compared with the traditional biomarkers of Scr + UACR, our multi-biomarker models based on urinary ntOPN performed better in predicting DKD development, which could provide more accurate tools for DKD risk prediction, thereby improving the renal prognosis in DM patients.

Association between endocrine disrupting chemicals exposure and diabetic kidney disease in adults: A national cross-sectional NHANES study.