Proteomics for prediction of disease progression and response to therapy in diabetic kidney disease

The past decade has resulted in multiple new findings of potential proteomic biomarkers of diabetic kidney disease (DKD). Many of these biomarkers reflect an important role in the (patho)physiology and biological processes of DKD. Situations in which proteomics could be applied in clinical practice include the identification of individuals at risk of progressive kidney disease and those who would respond well to treatment, in order to tailor therapy for those at highest risk. However, while many proteomic biomarkers have been discovered, and even found to be predictive, most lack rigorous external validation in sufficiently powered studies with renal endpoints. Moreover, studies assessing short-term changes in the proteome for therapy-monitoring purposes are lacking. Collaborations between academia and industry and enhanced interactions with regulatory agencies are needed to design new, sufficiently powered studies to implement proteomics in clinical practice

Treating diabetic complications; from large randomized clinical trials to precision medicine

In the last decades, many large randomized controlled trials have been conducted to assess the efficacy and safety of new interventions for the treatment of diabetic kidney disease (DKD). Unfortunately, these trials failed to demonstrate additional kidney or cardiovascular protection. One of the explanations for the failure of these trials appears to be the large variation in drug response between individual patients. All trials to date tested a drug which was targeted to a large heterogeneous population assuming that every individual will show a similar beneficial respond to the drug. Post hoc analyses from the past clinical trials, however, suggest that individual patients show a marked variation in drug response. This highlights the need to personalize treatment taking proper account of the characteristics and preferences of individual patients. Transitioning to a personalized therapy approach will have implications for clinical trial designs, drug registration and its use in clinical practice. Successful implementation of personalized medicine thus requires engagement of multiple stakeholders including academic community, pharmaceutical industry, regulatory agencies, health policy makers, physicians and patients. This supplement of Diabetes Obesity and Metabolism provides a summary on the state-of-the-art of personalized medicine in diabetic kidney disease from the views of various stakeholders

A kidney perspective on the mechanism of action of sodium glucose co-transporter 2 inhibitors

Sodium glucose co-transporter (SGLT) 2 inhibitors reduce the risk of kidney failure in patients with and without type 2 diabetes (T2D). Although the precise underlying mechanisms for these nephroprotective effects are incompletely understood, various hypotheses have been proposed including reductions in intraglomerular pressure through restoration of tubuloglomerular feedback, blood pressure reduction and favorable effects on vascular function, reduction in tubular workload and hypoxia, and metabolic effects resulting in increased autophagy. Here, we review these mechanisms, which may also explain the beneficial effects of SGLT2 inhibitors on kidney function in patients without T2D

Time for clinical decision support systems tailoring individual patient therapy to improve renal and cardiovascular outcomes in diabetes and nephropathy

The current guideline treatment for patients with diabetes and nephropathy to lower the high risk of renal and cardiovascular (CV) morbidity and mortality is based on results of clinical studies that have tested new drugs in large groups of patients with diabetes and high renal/CV risk. Although this has delivered breakthrough therapies like angiotensin receptor blockers, the residual renal/CV risk remains extremely high. Many subsequent trials have tried to further reduce this residual renal/CV risk, without much success. Post hoc analyses have indicated that these failures are, at least partly, due to a large variability in response between and within the patients. The current 'group approach' to designing and evaluating new drugs, as well as group-oriented drug registration and guideline recommendations, does not take this individual response variation into account. Like with antibiotics and cancer treatment, a more individual approach is warranted to effectively optimize individual results. New tools to better evaluate the individual risk change have been developed for improved clinical trial design and to avoid trial failures. One of these tools, the composite multiple parameter response efficacy score , is based on monitoring changes in all available risk factors and integrating them into a prediction of ultimate renal and CV risk reduction. This score has also been modelled into a clinical decision support system for use in monitoring and changing the therapy in individual patients to protect them from renal/CV events. In conclusion, future treatment of renal/CV risk in diabetes should transition from an era of 'one size fits all' into the new era of 'a fit for each size'

Rationale and design of a randomised phase III registration trial investigating finerenone in participants with type 1 diabetes and chronic kidney disease: The FINE-ONE trial

AIMS: Despite guideline-recommended treatments, including renin angiotensin system inhibition, up to 40 % of individuals with type 1 diabetes develop chronic kidney disease (CKD) putting them at risk of kidney failure. Finerenone is approved to reduce the risk of kidney failure in individuals with type 2 diabetes. We postulate that finerenone will demonstrate benefits on kidney outcomes in people with type 1 diabetes. METHODS: FINE-ONE (NCT05901831) is a randomised, placebo-controlled, double-blind phase III trial of 7.5 months\u27 duration in ∼220 adults with type 1 diabetes, urine albumin/creatinine ratio (UACR) of ≥ 200-\u3c 5000 mg/g (≥ 22.6-\u3c 565 mg/mmol) and eGFR of ≥ 25-\u3c 90 ml/min/1.73 m RESULTS: The primary endpoint is relative change in UACR from baseline over 6 months. UACR is used as a bridging biomarker (BB), since the treatment effect of finerenone on UACR was associated with its efficacy on kidney outcomes in the type 2 diabetes trials. Based on regulatory authority feedback, UACR can be used as a BB for kidney outcomes to support registration of finerenone in type 1 diabetes, provided necessary criteria are met. Secondary outcomes include incidences of treatment-emergent adverse events, treatment-emergent serious adverse events and hyperkalaemia. CONCLUSIONS: FINE-ONE will evaluate the efficacy and safety of finerenone in type 1 diabetes and CKD. Finerenone could become the first registered treatment for CKD associated with type 1 diabetes in almost 30 years. TRIAL REGISTRATION: ClinicalTrials.gov NCT05901831