Linking Kidney and Cardiovascular Complications in Diabetes-Impact on Prognostication and Treatment: The 2019 Edwin Bierman Award Lecture

Design and methodology of the PRIMETIME 1 cohort study: PRecIsion MEdicine based on kidney TIssue Molecular interrogation in diabetic nEphropathy

Background

Clinical features of diabetic kidney disease alone cannot differentiate between the histopathology that defines diabetic nephropathy (DN) and non-diabetic nephropathy (NDN). A kidney biopsy is necessary to make the definitive diagnosis of DN. However, there is no consensus on when to perform a kidney biopsy in individuals with diabetes and kidney disease. Furthermore, the implications of NDN versus DN for management, morbidity and kidney prognosis are unclear. To address the gap in knowledge, we aimed to create a national retrospective cohort of people with diabetes and a performed kidney biopsy.

Methods

Adults diagnosed with diabetes in Denmark between 1996 and 2020 who had a kidney biopsy performed were included. The cohort was established by linking a nationwide diabetes registry with the Danish Pathology Registry. Data from 11 national registries and databases were compiled. The type of kidney disease was classified using a three-step analysis of Systematized Nomenclature of Medicine codes reported in relation to the histopathological examinations of kidney tissue. The final cohort and classification of kidney disease was as follows: out of 485 989 individuals with diabetes 2586 were included, 2259 of whom had type 2 diabetes. We were able to classify 599 (26.5%) with DN, 703 (31.1%) with NDN and 165 (7.3%) with mixed disease in individuals with type 2 diabetes. In individuals with type 1 diabetes, 132 (40.4%) had DN, 73 (22.3%) NDN and 39 (11.9%) mixed disease. The remaining could not be classified or had normal histology. The overall median (Q1-Q3) follow-up time was 3.8 (1.6-7.2) years.

Conclusions

This cohort is a novel platform based on high-quality registry data for important longitudinal studies of the impact of kidney disease diagnosis on prognosis. With regular updates of data from the Danish registries, the presented follow-up will increase over time and is only limited by emigration or death.

Precision Medicine and/or Biomarker Based Therapy in T2DM: Ready for Prime Time?

Approximately 30-40% of people with type 2 diabetes mellitus develop chronic kidney disease. This is characterised by elevated blood pressure, declining kidney function and enhanced cardiovascular morbidity and mortality. Increased albuminuria and decreasing estimated glomerular function has to be evaluated regularly to diagsnose kidney disease. New biomarkers may facilitate early diagnosis and provide infomation on undlying pathology thereby supporting early precision intervention for the optimal benefit. A number of biomarkers have been suggested but are not yet implemented in clinical practice. iI the future such bimarkers may pave the way for personalized treatment.

HbA1c and beyond

The Kidney Disease: Improving Global Outcomes (KDIGO) Clinical Practice Guideline on Diabetes Management in Chronic Kidney Disease from 2020 comes at an opportune time when progress in diabetes technology and therapeutics offers new options to manage the large population of patients with diabetes and chronic kidney disease (CKD) at high risk of poor health outcomes. Management of haemoglobin A1c is important in diabetes, but an enlarging base of evidence from large clinical trials has demonstrated important new treatments offering organ protection and not just glucose management, such as sodium-glucose cotransporter 2 inhibitors and glucagon-like peptide-1 receptor agonists. It is the ambition that the guideline can help to optimize the clinical care of people with diabetes and CKD by integrating new options with existing management strategies based on high-quality evidence. Here, the focus has been on comprehensive care of patients with diabetes and CKD, glycaemic monitoring and targets, antihyperglycaemic therapies in patients with diabetes and CKD, and new developments since the guideline was published offering new opportunities and a wider target population for the new interventions.

Finerenone efficacy in patients with chronic kidney disease, type 2 diabetes and atherosclerotic cardiovascular disease

AIMS

Finerenone, a selective, non-steroidal mineralocorticoid receptor antagonist, improves cardiovascular (CV) and kidney outcomes in patients with type 2 diabetes (T2D) and chronic kidney disease (CKD). This subgroup analysis of FIDELITY, a pre-specified, pooled, individual patient-data analysis of FIDELIO-DKD (NCT02540993) and FIGARO-DKD (NCT02545049), compared finerenone vs. placebo in patients with and without baseline history of atherosclerotic CV disease (ASCVD).

METHODS AND RESULTS

Outcomes included a composite CV outcome [CV death, non-fatal myocardial infarction, non-fatal stroke, or hospitalization for heart failure (HHF)]; CV death or HHF; a composite kidney outcome (kidney failure, sustained estimated glomerular filtration rate decrease ≥57%, or kidney-related death); all-cause mortality; and safety by baseline history of ASCVD.Of 13 026 patients, 5935 (45.6%) had a history of ASCVD. The incidence of the composite CV outcome, CV death or HHF, and all-cause mortality was higher in patients with ASCVD vs. those without, with no difference between groups in the composite kidney outcome. Finerenone consistently reduced outcomes vs. placebo in patients with and without ASCVD (P-interaction for the composite CV outcome, CV death or HHF, the composite kidney outcome, and all-cause mortality 0.38, 0.68, 0.33, and 0.38, respectively). Investigator-reported treatment-emergent adverse events were consistent between treatment arms across ASCVD subgroups.

CONCLUSION

Finerenone reduced the risk of CV and kidney outcomes consistently across the spectrum of CKD in patients with T2D, irrespective of prevalent ASCVD.

Precision diagnostic approach to predict 5-year risk for microvascular complications in type 1 diabetes

Background

Individuals with long standing diabetes duration can experience damage to small microvascular blood vessels leading to diabetes complications (DCs) and increased mortality. Precision diagnostic tailors a diagnosis to an individual by using biomedical information. Blood small molecule profiling coupled with machine learning (ML) can facilitate the goals of precision diagnostics, including earlier diagnosis and individualized risk scoring.

Methods

Using data in a cohort of 537 adults with type 1 diabetes (T1D) we predicted five-year progression to DCs. Prediction models were computed first with clinical risk factors at baseline and then with clinical risk factors and blood-derived molecular data at baseline. Progression of diabetic kidney disease and diabetic retinopathy were predicted in two complication-specific models.

Findings

The model predicts the progression to diabetic kidney disease with accuracy: 0.96 ± 0.25 and 0.96 ± 0.06 area under curve, AUC, with clinical measurements and with small molecule predictors respectively and highlighted main predictors to be albuminuria, glomerular filtration rate, retinopathy status at baseline, sugar derivatives and ketones. For diabetic retinopathy, AUC 0.75 ± 0.14 and 0.79 ± 0.16 with clinical measurements and with small molecule predictors respectively and highlighted key predictors, albuminuria, glomerular filtration rate and retinopathy status at baseline. Individual risk scores were built to visualize results.

Interpretation

With further validation ML tools could facilitate the implementation of precision diagnosis in the clinic. It is envisaged that patients could be screened for complications, before these occur, thus preserving healthy life-years for persons with diabetes.

Funding

This study has been financially supported by Novo Nordisk Foundation grant NNF14OC0013659.

Roles of Mineralocorticoid Receptors in Cardiovascular and Cardiorenal Diseases

Mineralocorticoid receptor (MR) activation in the heart and vessels leads to pathological effects, such as excessive extracellular matrix accumulation, oxidative stress, and sustained inflammation. In these organs, the MR is expressed in cardiomyocytes, fibroblasts, endothelial cells, smooth muscle cells, and inflammatory cells. We review the accumulating experimental and clinical evidence that pharmacological MR antagonism has a positive impact on a battery of cardiac and vascular pathological states, including heart failure, myocardial infarction, arrhythmic diseases, atherosclerosis, vascular stiffness, and cardiac and vascular injury linked to metabolic comorbidities and chronic kidney disease. Moreover, we present perspectives on optimization of the use of MR antagonists in patients more likely to respond to such therapy and review the evidence suggesting that novel nonsteroidal MR antagonists offer an improved safety profile while retaining their cardiovascular protective effects. Finally, we highlight future therapeutic applications of MR antagonists in cardiovascular injury.