Nonalbuminuric Diabetic Kidney Disease and Risk of All-Cause Mortality and Cardiovascular and Kidney Outcomes in Type 2 Diabetes: Findings From the Hong Kong Diabetes Biobank

Circulating metabolomic markers linking diabetic kidney disease and incident cardiovascular disease in type 2 diabetes: analyses from the Hong Kong Diabetes Biobank

AIMS/HYPOTHESIS

The aim of this study was to describe the metabolome in diabetic kidney disease (DKD) and its association with incident CVD in type 2 diabetes, and identify prognostic biomarkers.

METHODS

From a prospective cohort of individuals with type 2 diabetes, baseline sera (N=1991) were quantified for 170 metabolites using NMR spectroscopy with median 5.2 years of follow-up. Associations of chronic kidney disease (CKD, eGFR<60 ml/min per 1.73 m2) or severely increased albuminuria with each metabolite were examined using linear regression, adjusted for confounders and multiplicity. Associations between DKD (CKD or severely increased albuminuria)-related metabolites and incident CVD were examined using Cox regressions. Metabolomic biomarkers were identified and assessed for CVD prediction and replicated in two independent cohorts.

RESULTS

At false discovery rate (FDR)<0.05, 156 metabolites were associated with DKD (151 for CKD and 128 for severely increased albuminuria), including apolipoprotein B-containing lipoproteins, HDL, fatty acids, phenylalanine, tyrosine, albumin and glycoprotein acetyls. Over 5.2 years of follow-up, 75 metabolites were associated with incident CVD at FDR<0.05. A model comprising age, sex and three metabolites (albumin, triglycerides in large HDL and phospholipids in small LDL) performed comparably to conventional risk factors (C statistic 0.765 vs 0.762, p=0.893) and adding the three metabolites further improved CVD prediction (C statistic from 0.762 to 0.797, p=0.014) and improved discrimination and reclassification. The 3-metabolite score was validated in independent Chinese and Dutch cohorts.

CONCLUSIONS/INTERPRETATION

Altered metabolomic signatures in DKD are associated with incident CVD and improve CVD risk stratification.

Combination therapy for kidney disease in people with diabetes mellitus

Diabetic kidney disease (DKD), defined as co-existing diabetes and chronic kidney disease in the absence of other clear causes of kidney injury, occurs in approximately 20-40% of patients with diabetes mellitus. As the global prevalence of diabetes has increased, DKD has become highly prevalent and a leading cause of kidney failure, accelerated cardiovascular disease, premature mortality and global health care expenditure. Multiple pathophysiological mechanisms contribute to DKD, and single lifestyle or pharmacological interventions have shown limited efficacy at preserving kidney function. For nearly two decades, renin-angiotensin system inhibitors were the only available kidney-protective drugs. However, several new drug classes, including sodium glucose cotransporter-2 inhibitors, a non-steroidal mineralocorticoid antagonist and a selective endothelin receptor antagonist, have now been demonstrated to improve kidney outcomes in people with type 2 diabetes mellitus. In addition, emerging preclinical and clinical evidence of the kidney-protective effects of glucagon-like-peptide-1 receptor agonists has led to the prospective testing of these agents for DKD. Research and clinical efforts are geared towards using therapies with potentially complementary efficacy in combination to safely halt kidney disease progression. As more kidney-protective drugs become available, the outlook for people living with DKD should improve in the next few decades.

Development of Serum Lactate Level-Based Nomograms for Predicting Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients

Purpose

To establish nomograms integrating serum lactate levels and traditional risk factors for predicting diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM) patients.

Patients and methods

A total of 570 T2DM patients and 100 healthy subjects were enrolled. T2DM patients were categorized into normal and high lactate groups. Univariate and multivariate logistic regression analyses were employed to identify independent predictors for DKD. Then, nomograms for predicting DKD were established, and the model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration, and decision curve analysis (DCA).

Results

T2DM patients exhibited higher lactate levels compared to those in healthy subjects. Glucose, platelet, uric acid, creatinine, and hypertension were independent factors for DKD in T2DM patients with normal lactate levels, while diabetes duration, creatinine, total cholesterol, and hypertension were indicators in high lactate levels group (P<0.05). The AUC values were 0.834 (95% CI, 0.776 to 0.891) and 0.741 (95% CI, 0.688 to 0.795) for nomograms in both normal lactate and high lactate groups, respectively. The calibration curve demonstrated excellent agreement of fit. Furthermore, the DCA revealed that the threshold probability and highest Net Yield were 17-99% and 0.36, and 24-99% and 0.24 for the models in normal lactate and high lactate groups, respectively.

Conclusion

The serum lactate level-based nomogram models, combined with traditional risk factors, offer an effective tool for predicting DKD probability in T2DM patients. This approach holds promise for early risk assessment and tailored intervention strategies.

Association of eGFR slope with all-cause mortality, macrovascular and microvascular outcomes in people with type 2 diabetes and early-stage chronic kidney disease

AIMS

The association of estimated glomerular filtration rate (eGFR) slope with progression of complications in people with type 2 diabetes (T2D) and early-stage chronic kidney disease (CKD) is less clear.

METHODS

We identified 115,139 T2D participants without decreased eGFR (>60 mL/min/1.73 m2) between 2008 and 2015 from the electronic database of the Hong Kong Hospital Authority. eGFR slope calculated by linear-mixed effects model using 3-year eGFR measurements was categorized into quintiles. With Quintile 3 of eGFR slope as the reference group, we used Cox proportional or cause-specific models to investigate the association between eGFR slope and all-cause mortality, macrovascular and microvascular complications, as appropriate.

RESULTS

Over a median follow-up of 7.8 years, fastest eGFR declines (Quintile 1 with median eGFR slope: -4.32 mL/min/1.73 m2/year) were associated with increased risk of all adverse outcomes (adjusted hazard ratio [aHR] 1.36 to 2.97, all P < 0.0001), compared with less steep eGFR declines (Quintile 3: -1.08 mL/min/1.73 m2/year). Substantial eGFR increases (Quintile 5: 1.34 mL/min/1.73 m2/year) were associated with decreased risk of CKD and ≥ 40 % decline in eGFR (aHR [95 % CI] 0.65 [0.63, 0.67] and 0.85 [0.82, 0.89], respectively) and higher risk of death, CVD, DR and DN (aHR [95 % CI] 1.48 [1.40, 1.56], 1.19 [1.14, 1.25], 1.07 [1.004, 1.15] and 1.62 [1.37, 1.91], respectively).

CONCLUSIONS

In a cohort of T2D people without decreased eGFR, accelerated declines and increases in eGFR were associated with all-cause mortality, macrovascular and microvascular complications, supporting the potential prognostic utility of eGFR slope in T2D people with early-stage CKD.

Prevalence of Diabetic Kidney Disease with Different Subtypes in Hospitalized Patients with Diabetes and Correlation Between eGFR and LncRNA XIST Expression in PBMCs

INTRODUCTION

Diabetic kidney disease (DKD) has become the leading cause of end-stage kidney disease (ESKD) in most countries. Recently, long noncoding RNA XIST has been found involved in the development of DKD.

METHODS

A total of 1184 hospitalized patients with diabetes were included and divided into four groups based on their estimated glomerular filtration rate (eGFR) and urinary albumin to creatinine ratio (UACR): normal control group (nDKD), DKD with normoalbuminuric and reduced eGFR (NA-DKD), DKD with albuminuria but without reduced eGFR (A-DKD), and DKD with albuminuria and reduced eGFR (Mixed), and then their clinical characteristics were analyzed. Peripheral blood mononuclear cells (PBMCs) of patients with DKD were isolated, and lncRNA XIST expression was detected by real-time quantitative PCR.

RESULTS

The prevalence of DKD in hospitalized patients with diabetes mellutus (DM) was 39.9%, and the prevalence of albuminuria and decreased eGFR was 36.6% and 16.2%, respectively. NA-DKD, A-DKD, and Mixed groups accounted for 23.7%, 3.3%, and 12.9%, respectively. Women with DKD had considerably lower levels of lncRNA XIST expression in their PBMCs compared to nDKD. There was a significant correlation between eGFR level and lncRNA XIST expression (R = 0.390, P = 0.036) as well as a negative correlation between HbA1c and lncRNA XIST expression (R = - 0.425, P = 0.027) in female patients with DKD.

CONCLUSIONS

Our study revealed that 39.9% of DM inpatients who were admitted to the hospital had DKD. Importantly, lncRNA XIST expression in PBMCs of female patients with DKD was significantly correlated with eGFR and HbA1c.

Precision Medicine Approaches to Diabetic Kidney Disease: Personalized Interventions on the Horizon

Diabetic kidney disease (DKD) is a significant complication of diabetes that requires innovative interventions to address its increasing impact. Precision medicine is a rapidly emerging paradigm that shows excellent promise in tailoring therapeutic strategies to the unique profiles of individual patients. This abstract examines the potential of precision medicine in managing DKD. It explores the genetic and molecular foundations, identifies biomarkers for risk assessment, provides insights into pharmacogenomics, and discusses targeted therapies. Integrating omics data and data analytics provides a comprehensive landscape for making informed decisions. The abstract highlights the difficulties encountered during the clinical implementation process, the ethical factors to be considered, and the importance of involving patients. In addition, it showcases case studies that demonstrate the effectiveness of precision-based interventions. As the field progresses, the abstract anticipates a future characterized by the integration of artificial intelligence in diagnostics and treatment. It highlights the significant impact that precision medicine can have in revolutionizing the provision of care for DKD.

Diabetic Nephropathy: Update on Pillars of Therapy Slowing Progression

Management of diabetic kidney disease (DKD) has evolved in parallel with our growing understanding of the multiple interrelated pathophysiological mechanisms that involve hemodynamic, metabolic, and inflammatory pathways. These pathways and others play a vital role in the initiation and progression of DKD. Since its initial discovery, the blockade of the renin-angiotensin system has remained a cornerstone of DKD management, leaving a large component of residual risk to be dealt with. The advent of sodium-glucose cotransporter 2 inhibitors followed by nonsteroidal mineralocorticoid receptor antagonists and, to some extent, glucagon-like peptide 1 receptor agonists (GLP-1 RAs) has ushered in a resounding paradigm shift that supports a pillared approach in maximizing treatment to reduce outcomes. This pillared approach is like that derived from the approach to heart failure treatment. The approach mandates that all agents that have been shown in clinical trials to reduce cardiovascular outcomes and/or mortality to a greater extent than a single drug class alone should be used in combination. In this way, each drug class focuses on a specific aspect of the disease's pathophysiology. Thus, in heart failure, β-blockers, sacubitril/valsartan, a mineralocorticoid receptor antagonist, and a diuretic are used together. In this article, we review the evolution of the pillar concept of therapy as it applies to DKD and discuss how it should be used based on the outcome evidence. We also discuss the exciting possibility that GLP-1 RAs may be an additional pillar in the quest to further slow kidney disease progression in diabetes.

Update on Diabetic Kidney Disease (DKD): Focus on Non-Albuminuric DKD and Cardiovascular Risk

The classic description of diabetic kidney disease (DKD) involves progressive stages of glomerular hyperfiltration, microalbuminuria, proteinuria, and a decline in the estimated glomerular filtration rate (eGFR), leading to dialysis. In recent years, this concept has been increasingly challenged as evidence suggests that DKD presents more heterogeneously. Large studies have revealed that eGFR decline may also occur independently from the development of albuminuria. This concept led to the identification of a new DKD phenotype: non-albuminuric DKD (eGFR < 60 mL/min/1.73 m², absence of albuminuria), whose pathogenesis is still unknown. However, various hypotheses have been formulated, the most likely of which is the acute kidney injury-to-chronic kidney disease (CKD) transition, with prevalent tubular, rather than glomerular, damage (typically described in albuminuric DKD). Moreover, it is still debated which phenotype is associated with a higher cardiovascular risk, due to contrasting results available in the literature. Finally, much evidence has accumulated on the various classes of drugs with beneficial effects on DKD; however, there is a lack of studies analyzing the different effects of drugs on the various phenotypes of DKD. For this reason, there are still no specific guidelines for therapy in one phenotype rather than the other, generically referring to diabetic patients with CKD.

Risk of cardiovascular disease, death, and renal progression in diabetes according to albuminuria and estimated glomerular filtration rate

AIM

We aimed to examine risks of major cardiovascular events (MACEs), renal outcomes, and all-cause mortality in type 2 diabetes mellitus (T2DM) patients with different diabetic kidney disease (DKD) subtypes.

METHODS

A total of 36,509 participants with T2DM recruited from 20 community sites across mainland China were followed up during 2011-2016. DKD subtypes were categorized based on albuminuria (urinary albumin-to-creatinine ratio, UACR ≥ 30 mg/g) and reduced estimated glomerular filtration rate (eGFR < 60 ml/min/1.73 m²) as Alb^-/eGFR^-, Alb⁺/eGFR^-, Alb^-/eGFR⁺, and Alb⁺/eGFR⁺. Cox proportional hazard models were used to calculate hazard ratios (HRs) and 95% confidence intervals (95% CIs) of developing clinical outcomes in DKD subtypes.

RESULTS

More than half (53.5%) of participants with diabetes and reduced eGFR had normal UACR levels (Alb^-/eGFR⁺), termed as non-albuminuria DKD. These patients had a modest increase in the risks of MACEs (hazard ratio, HR 1.42 [95% CI 1.08;1.88]) and mortality (HR 1.42 [1.04;1.92]) compared with patients without DKD, whereas CKD progression was not significantly increased (HR 0.97 [0.60;1.57]). Participants with albuminuria (Alb⁺/eGFR^- or Alb⁺/eGFR⁺) had higher risks of clinical outcomes. Subgroup analysis revealed that the associations between non-albuminuria DKD and risks of MACEs and mortality were more evident in those aged <65 years.

CONCLUSION

Non-albuminuria DKD accounts for more than half of DKD cases with low eGFR in Chinese diabetes patients. Diabetes patients with albuminuria are at higher risks of developing clinical outcomes and warrant early intervention, as well as patients with non-albuminuria DKD with age < 65 years.

SGLT2 inhibitors reduce adverse kidney and cardiovascular events in patients with advanced diabetic kidney disease: A population-based propensity score-matched cohort study

BACKGROUND

There were limited data on the efficacy and safety profile on use of sodium-glucose co-transporter 2 receptor (SGLT2) inhibitors in diabetic patients with advanced chronic kidney disease (CKD). We aimed to evaluate the efficacy, in terms of improvement in glycemic profile, kidney function, prevention of adverse kidney and cardiovascular events, and the safety profile of SGLT2 inhibitors in a group of diabetic patients at CKD stage 3B-5 from a real-world population-based cohort.

METHODS

We performed a retrospective observational cohort study of type 2 diabetic patients at CKD stage 3B-5 who received SGLT2 inhibitors as compared to control from 1 January 2015 through 31 December 2021. Propensity score assignment by logistic regression and matching with control by the nearest score at 1:3 ratio was done. All patients were followed for 1 year. Outcomes were kidney-related adverse events and major adverse cardiovascular events (MACE), change in estimated glomerular filtration rate (eGFR), glycemic control, and side effects profiling.

RESULTS

We analyzed 1,450 SGLT2 inhibitor users. They had significantly lower rates of kidney-related adverse events (7.7 % versus 24.1 %, p < 0.001) and MACE (9.6 % versus 15.1 %, p < 0.001) as compared to control group. Their eGFR also significantly improved (0.4 ± 9.3 versus -5.5 ± 10.6 ml/min/1.73 m², p < 0.001). These patients also had a greater reduction in HbA1c (-0.40 ± 1.13 versus -0.04 ± 1.47 %, p < 0.001), and insulin requirement (-8.8 ± 35.2 versus 4.1 ± 19.4 units/day, p < 0.001). After adjusting for confounders, SGLT2 inhibitors protected against kidney-related adverse events (odds ratio [OR] 0.48, 95 % confidence interval [CI] 0.33 - 0.71, p < 0.001) and MACE (OR 0.47, 95 % CI 0.37 - 0.60, p < 0.001). Apart from a marginally higher rate of fungal urinary tract infection (0.08 ± 0.66 versus 0.03 ± 0.23 episodes per year, p < 0.001), SGLT2 inhibitor use was not associated with other side effects.

CONCLUSIONS

SGLT2 inhibitor improved kidney function, glycemic profile, and reduced adverse kidney-related and cardiovascular events in diabetic patients with advanced CKD.

Low Serum Dehydroepiandrosterone Is Associated With Diabetic Kidney Disease in Men With Type 2 Diabetes Mellitus

BACKGROUND

The associations of dehydroepiandrosterone (DHEA) and dehydroepiandrosterone sulfate (DHEAS) with diabetic kidney disease (DKD) remained unclear. Thus, this cross-sectional study aimed to explore the associations of DHEA and DHEAS with the risk of DKD in patients with T2DM.

METHODS

The information of 1251 patients with T2DM were included in this study. Serum DHEA and DHEAS were quantified using liquid chromatography-tandem mass spectrometry assays. Multivariate logistic regression analyses were used to assess the associations of DHEA and DHEAS with DKD as well as high urine albumin to creatinine ratio (ACR).

RESULTS

In men with T2DM, the risk of DKD decreased with an increasing DHEA concentration after adjustment for traditional risk factors; the fully adjusted OR (95% CI) for tertile3 vs tertile1 was 0.37 (0.19-0.70; P = 0.010 for trend). Similarly, when taking high ACR as the outcome, low DHEA levels were still significantly associated with increased odds of high ACR (OR, 0.37; 95% CI, 0.19-0.72 for tertile3 vs tertile1; P = 0.012 for trend). The restricted cubic spline showed that the risk of DKD gradually decreased with the increment of serum DHEA levels (P-overall = 0.007; P-nonlinear = 0.161). DHEAS was not independently associated with the risk of DKD in men. In contrast, no significant relationships were found between DHEA and DHEAS and the risk of DKD in women (all P > 0.05).

CONCLUSIONS

In men with T2DM, low serum DHEA levels were independently related to the risk of DKD after adjustment for traditional risk factors. Our finding highlights the potential role of DHEA in the development of DKD in men with T2DM.