Temporal variation of renal function in people with type 2 diabetes mellitus: A retrospective UK clinical practice research datalink cohort study

A SuperLearner approach for predicting diabetic kidney disease upon the initial diagnosis of T2DM in hospital

BACKGROUND

Diabetic kidney disease (DKD) is a serious complication of diabetes mellitus (DM), with patients typically remaining asymptomatic until reaching an advanced stage. We aimed to develop and validate a predictive model for DKD in patients with an initial diagnosis of type 2 diabetes mellitus (T2DM) using real-world data.

METHODS

We retrospectively examined data from 3,291 patients (1740 men, 1551 women) newly diagnosed with T2DM at Ningbo Municipal Hospital of Traditional Chinese Medicine (2011-2023). The dataset was randomly divided into training and validation cohorts. Forty-six readily available medical characteristics at initial diagnosis of T2DM from the electronic medical records were used to develop prediction models based on linear, non-linear, and SuperLearner approaches. Model performance was evaluated using the area under the curve (AUC). SHapley Additive exPlanation (SHAP) was used to interpret the best-performing models.

RESULTS

Among 3291 participants, 563 (17.1%) were diagnosed with DKD during median follow-up of 2.53 years. The SuperLearner model exhibited the highest AUC (0.7138, 95% confidence interval: [0.673, 0.7546]) for the holdout internal validation set in predicting any DKD stage. Top-ranked features were WBC_Cnt*, Neut_Cnt, Hct, and Hb. High WBC_Cnt, low Neut_Cnt, high Hct, and low Hb levels were associated with an increased risk of DKD.

CONCLUSIONS

We developed and validated a DKD risk prediction model for patients with newly diagnosed T2DM. Using routinely available clinical measurements, the SuperLearner model could predict DKD during hospital visits. Prediction accuracy and SHAP-based model interpretability may help improve early detection, targeted interventions, and prognosis of patients with DM.

Association of Urinary Epidermal Growth Factor, Fatty Acid-Binding Protein 3, and Vascular Cell Adhesion Molecule 1 Levels with the Progression of Early Diabetic Kidney Disease

INTRODUCTION

Diabetic kidney disease (DKD) is a common cause of chronic kidney disease with around 25-40% of patients with diabetes being affected. The course of DKD is variable, and estimated glomerular filtration rate (eGFR) and albuminuria, the currently used clinical markers, are not able to accurately predict the individual disease trajectory, in particular in early stages of the disease. The aim of this study was to assess the association of urine levels of selected protein biomarkers with the progression of DKD at an early stage of disease.

METHODS

We measured 22 protein biomarkers using the Mesoscale Discovery platform in 461 urine samples of the PROVALID cohort, an observational study of patients with type 2 diabetes mellitus followed at the primary health care level for a minimum of 4 years. Odds ratios (ORs) were estimated for the effect of marker values above median on fast progression using unadjusted and adjusted logistic regression models. RNA expression at the single-cell level in kidney biopsy samples obtained from a cohort of young persons with type 2 diabetes mellitus was in addition determined for markers showing significant associations with disease progression.

RESULTS

Increased urinary levels of epidermal growth factor (EGF) were linked to lower odds of fast progression (defined as annual eGFR decline greater than 2.58 mL/min per 1.73 m2) with an OR of 0.60 (95% CI: 0.46, 0.78). The association with outcome was even stronger when adjusting for a set of 14 baseline clinical parameters including age, biological sex, eGFR, body mass index, albuminuria, and HbA1c. Elevated urinary levels of fatty acid-binding protein 3 (FABP3) and vascular cell adhesion molecule 1 (VCAM1) were each significantly associated with fast progression with an OR of 1.44 (95% CI: 1.11, 1.87) and an OR of 1.41 (95% CI: 1.08, 1.83), respectively. Enriched expression of EGF and FABP3 was observed in distal convoluted tubular cells and VCAM1 in parietal epithelial cells at single-cell level from biopsies of patients with early DKD.

CONCLUSION

In summary, we show that lower urinary levels of EGF and higher urinary levels of FABP3 and VCAM1 are significantly associated with DKD progression in early-stage disease.

Genome-wide Analysis Reflects Novel 5-Hydroxymethylcytosines Implicated in Diabetic Nephropathy and the Biomarker Potential

Aim

Diabetic nephropathy (DN) has become the most common cause of end-stage renal disease (ESRD) in most countries. Elucidating novel epigenetic contributors to DN can not only enhance our understanding of this complex disorder, but also lay the foundation for developing more effective monitoring tools and preventive interventions in the future, thus contributing to our ultimate goal of improving patient care.

Methods

The 5hmC-Seal, a highly selective, chemical labeling technique, was used to profile genome-wide 5-hydroxymethylcytosines (5hmC), a stable cytosine modification type marking gene activation, in circulating cell-free DNA (cfDNA) samples from a cohort of patients recruited at Zhongnan Hospital, including T2D patients with nephropathy (DN, n = 12), T2D patients with non-DN vascular complications (non-DN, n = 29), and T2D patients without any complication (controls, n = 14). Differentially analysis was performed to find DN-associated 5hmC features, followed by the exploration of biomarker potential of 5hmC in cfDNA for DN using a machine learning approach.

Results

Genome-wide analyses of 5hmC in cfDNA detected 427 and 336 differential 5hmC modifications associated with DN, compared with non-DN individuals and controls, and suggested relevant pathways such as NOD-like receptor signaling pathway and tyrosine metabolism. Our exploration using a machine learning approach revealed an exploratory model comprised of ten 5hmC genes showing the possibility to distinguish DN from non-DN individuals or controls.

Conclusion

Genome-wide analysis suggests the possibility of exploiting novel 5hmC in patient-derived cfDNA as a non-invasive tool for monitoring DN in high risk T2D patients in the future.

Clonal hematopoiesis of indeterminate potential and diabetic kidney disease: a nested case-control study

Introduction

The disease trajectory of diabetic kidney disease (DKD) shows a high interindividual variability not sufficiently explained by conventional risk factors. Clonal hematopoiesis of indeterminate potential (CHIP) is a proposed novel cardiovascular risk factor. Increased kidney fibrosis and glomerulosclerosis were described in mouse models of CHIP. Here, we aim to analyze whether CHIP affects the incidence or progression of DKD.

Methods

A total of 1419 eligible participants of the PROVALID Study were the basis for a nested case-control (NCC) design. A total of 64 participants who reached a prespecified composite endpoint within the observation period (initiation of kidney replacement therapy, death from kidney failure, sustained 40% decline in estimated glomerular filtration rate or sustained progression to macroalbuminuria) were identified and matched to 4 controls resulting in an NCC sample of 294 individuals. CHIP was assessed via targeted amplicon sequencing of 46 genes in peripheral blood. Furthermore, inflammatory cytokines were analyzed in plasma via a multiplex assay.

Results

The estimated prevalence of CHIP was 28.91% (95% CI 22.91%–34.91%). In contrast to other known risk factors (albuminuria, hemoglobin A1c, heart failure, and smoking) and elevated microinflammation, CHIP was not associated with incident or progressive DKD (hazard ratio [HR] 1.06 [95% CI 0.57–1.96]).

Conclusions

In this NCC study, common risk factors as well as elevated microinflammation but not CHIP were associated with kidney function decline in type 2 diabetes mellitus.

Intra-individual variability of eGFR trajectories in early diabetic kidney disease and lack of performance of prognostic biomarkers

Studies reporting on biomarkers aiming to predict adverse renal outcomes in patients with type 2 diabetes and kidney disease (DKD) conventionally define a surrogate endpoint either as a percentage of decrease of eGFR (e.g. ≥ 30%) or an absolute decline (e.g. ≥ 5 ml/min/year). The application of those study results in clinical practise however relies on the assumption of a linear and intra-individually stable progression of DKD. We studied 860 patients of the PROVALID study and 178 of an independent population with a relatively preserved eGFR at baseline and at least 5 years of follow up. Individuals with a detrimental prognosis were identified using various thresholds of a percentage or absolute decline of eGFR after each year of follow up. Next, we determined how many of the patients met the same criteria at other points in time. Interindividual eGFR decline was highly variable but in addition intra-individual eGFR trajectories also were frequently non-linear. For example, of all subjects reaching an endpoint defined as a decrease of eGFR by ≥ 30% between baseline and 3 years of follow up, only 60.3 and 45.2% lost at least the same amount between baseline and year 4 or 5. The results were similar when only patients on stable medication or subpopulations based on baseline eGFR or albuminuria status were analyzed or an eGFR decline of ≥ 5 ml/min/1.73m²/year was used. Identification of reliable biomarkers predicting adverse prognosis is a strong clinical need given the large interindividual variability of DKD progression. However, it is conceptually challenging in early DKD because of non-linear intra-individual eGFR trajectories. As a result, the performance of a prognostic biomarker may be accurate after a specific time of follow-up in a single population only.

5-Hydroxymethylcytosines in Circulating Cell-Free DNA Reveal Vascular Complications of Type 2 Diabetes

BACKGROUND

Long-term complications of type 2 diabetes (T2D), such as macrovascular and microvascular events, are the major causes for T2D-related disability and mortality. A clinically convenient, noninvasive approach for monitoring the development of these complications would improve the overall life quality of patients with T2D and help reduce healthcare burden through preventive interventions.

METHODS

A selective chemical labeling strategy for 5-hydroxymethylcytosines (5hmC-Seal) was used to profile genome-wide 5hmCs, an emerging class of epigenetic markers implicated in complex diseases including diabetes, in circulating cell-free DNA (cfDNA) from a collection of Chinese patients (n = 62). Differentially modified 5hmC markers between patients with T2D with and without macrovascular/microvascular complications were analyzed under a case-control design.

RESULTS

Statistically significant changes in 5hmC markers were associated with T2D-related macrovascular/microvascular complications, involving genes and pathways relevant to vascular biology and diabetes, including insulin resistance and inflammation. A 16-gene 5hmC marker panel accurately distinguished patients with vascular complications from those without [testing set: area under the curve (AUC) = 0.85; 95% CI, 0.73-0.96], outperforming conventional clinical variables such as urinary albumin. In addition, a separate 13-gene 5hmC marker panel could distinguish patients with single complications from those with multiple complications (testing set: AUC = 0.84; 95% CI, 0.68-0.99), showing superiority over conventional clinical variables.

CONCLUSIONS

The 5hmC markers in cfDNA reflected the epigenetic changes in patients with T2D who developed macrovascular/microvascular complications. The 5hmC-Seal assay has the potential to be a clinically convenient, noninvasive approach that can be applied in the clinic to monitor the presence and severity of diabetic vascular complications.

Temporal variation of renal function in people with type 2 diabetes mellitus: A retrospective UK clinical practice research datalink cohort study

AIM

To characterize the longitudinal variability of estimated glomerular filtration rate (eGFR) in people with type 2 diabetes mellitus (T2DM), including variation between categories and individuals.

METHODS

People with T2DM and sufficient recorded serum creatinine measurements were identified from the Clinical Practice Research Datalink (T2DM diagnosis from 1 January 2009 to 1 January 2011 with 5 years follow-up); eGFR was calculated using the CKD-EPI equation.

RESULTS

In total, 7766 individuals were included; 32.8%, 50.2%, 12.4%, 4.0% and 0.6% were in glomerular filtration rate (GFR) categories G1, G2, G3a, G3b and G4, respectively. Overall, eGFR decreased by 0.44 mL/min/1.73 m2 per year; eGFR increased by 0.80 mL/min/1.73 m2 between index and year 1, then decreased by 0.75 mL/min/1.73 m2 annually up to year 5. Category G1 showed a steady decline in eGFR over time; G2, G3a and G3b showed an increase between index and year 1, followed by a decline. Category G4 showed a mean eGFR increase of 1.85 mL/min/1.73 m2 annually. People in categories G3-G4 moved across a greater number of GFR categories than those in G1 and G2. Individual patients' eGFR showed a wide range of values (change from baseline at year 5 varied from -80 to +59 mL/min/1.73 m2 ).

CONCLUSION

Overall, eGFR declined over time, although there was considerable variation between GFR categories and individuals. This highlights the difficulty in prescribing many glucose-lowering therapies, which require dose adjustment for renal function. The study also emphasizes the importance of regular monitoring of renal impairment in people with T2DM.