Precision medicine approaches for diabetic kidney disease:opportunities and challenges

The prevalence of end-stage kidney disease (ESKD) continuously increases worldwide. The increasing prevalence parallels the growth in the number of people with diabetes, which is the leading cause of ESKD. Early diagnosis of chronic kidney disease (CKD) in patients with diabetes and appropriate intervention is important to delay the progression of kidney function decline and prevent ESKD. Rate of CKD progression and response to treatment varies among patients with diabetes, highlighting the need to tailor individual treatment. In this review, we describe recent advances and areas for future studies with respect to precision medicine in diabetic kidney disease (DKD). DKD is a multi-factorial disease that is subject in part to genetic heritability, but is also influenced by various exogenous mediators, such as environmental or dietary factors. Genetic testing so far has limited utility to facilitate early diagnosis, classify progression or evaluate response to therapy. Various biomarker-based approaches are currently explored to identify patients at high risk of ESKD and to facilitate decision-making for targeted therapy. These studies have led to discovery and validation of a couple of inflammatory proteins such as circulating tumour necrosis factor receptors, which are strong predictors of kidney disease progression. Moreover, risk and drug-response scores based on multiple biomarkers are developed to predict kidney disease progression and long-term drug efficacy. These findings, if implemented in clinical practice, will pave the way to move from a one-size-fits-all to a one-fit-for-everyone approach

Prediction of the Effects of Empagliflozin on Cardiovascular and Kidney Outcomes Based on Short-Term Changes in Multiple Risk Markers

Aims: The EMPA-REG OUTCOME trial demonstrated that the sodium-glucose cotransporter-2 inhibitor (SGLT2) empagliflozin reduces the risk of cardiovascular (CV) and kidney outcomes in patients with type 2 diabetes. We previously developed the parameter response efficacy (PRE) score, which translates drug effects on multiple short-term risk markers into a predicted long-term treatment effect on clinical outcomes. The main objective of this study was to assess the accuracy of the PRE score in predicting the efficacy of empagliflozin in reducing the risk of CV and kidney outcomes. Methods: Short-term (baseline to 6-months) changes in glycated hemoglobin (HbA1c), systolic blood pressure (SBP), urinary-albumin-creatinine-ratio (UACR), hemoglobin, body weight, high-density-lipoprotein (HDL) cholesterol, low-density-lipoprotein (LDL) cholesterol, uric acid, and potassium were determined among 7020 patients with type 2 diabetes and established CV disease in the EMPA-REG OUTCOME trial. The beta-coefficients, derived from a Cox proportional hazards model in a pooled database consisting of 6355 patients with type 2 diabetes, were applied to the short-term risk markers in the EMPA-REG OUTCOME trial to predict the empagliflozin-induced impact on CV (defined as a composite of non-fatal myocardial infarction, non-fatal stroke, or CV death) and kidney (defined as a composite of doubling of serum creatinine or end-stage kidney disease) outcomes. Results: Empagliflozin compared to placebo reduced HbA1c (0.6%), SBP (4.2 mmHg), UACR (13.0%), body weight (2.1 kg), uric acid (20.4 μmol/L), and increased hemoglobin (6.6 g/L), LDL-cholesterol (0.1 mmol/L) and HDL-cholesterol (0.04 mmol/L) (all p<0.01). Integrating these effects in the PRE score resulted in a predicted relative risk reduction (RRR) for the CV outcome of 6.4% (95% CI 1.4–11.7), which was less than the observed 14.7% (95% CI 1.3–26.4%) RRR. For the kidney outcome, the PRE score predicted a RRR of 33.4% (95% CI 26.2–39.8); the observed RRR was 46.9% (95% CI 26.8–61.5). In a subgroup of 2,811 patients with UACR ≥30 mg/g at baseline, the PRE score predicted RRR was 40.8% (95% CI 31.2–49.1) vs. the observed RRR of 40.8% (95% CI 12.4–60.0) for the kidney outcome. Conclusions: Integrating multiple short-term risk marker changes in the PRE score underestimated the effect of empagliflozin on CV and kidney outcomes, suggesting that the currently used risk markers do not fully capture the effect of empagliflozin. In patients with increased albuminuria, the PRE score adequately predicted the effect of empagliflozin on kidney outcomes

A novel drug response score more accurately predicts renoprotective drug effects than existing renal risk scores

Background: Risk factor-based equations are used to predict risk of kidney disease progression in patients with type 2 diabetes order to guide treatment decisions. It is, however, unknown whether these models can also be used to predict the effects of drugs on clinical outcomes. Methods: The previously developed Parameter Response Efficacy (PRE) score, which integrates multiple short-term drug effects, was first compared with the existing risk scores, Kidney Failure Risk Equation (KFRE) and The Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) renal risk score, in its performance to predict end-stage renal disease (ESRD; KFRE) and doubling of serum creatinine or ESRD (ADVANCE). Second, changes in the risk scores were compared after 6 months' treatment to predict the long-term effects of losartan on these renal outcomes in patients with type 2 diabetes and chronic kidney disease. Results: The KFRE, ADVANCE and PRE scores showed similarly good performance in predicting renal risk. However, for prediction of the effect of losartan, the KFRE risk score predicted a relative risk change in the occurrence of ESRD of 3.1% [95% confidence interval (CI) -5 to 12], whereas the observed risk change was -28.8% (95% CI -42.0 to -11.5). For the composite endpoint of doubling of serum creatinine or ESRD, the ADVANCE score predicted a risk change of -12.4% (95% CI -17 to -7), which underestimated the observed risk change -21.8% (95% CI -34 to -6). The PRE score predicted renal risk changes that were close to the observed risk changes with losartan treatment [-24.0% (95% CI -30 to -17) and -22.6% (95% CI -23 to -16) for ESRD and the composite renal outcome, respectively]. Conclusion: A drug response score such as the PRE score may assist in improving clinical decision making and implement precision medicine strategies

Prediction of the Effects of Liraglutide on Kidney and Cardiovascular Outcomes Based on Short-Term Changes in Multiple Risk Markers

Aims: The LEADER trial demonstrated that the glucagon-like peptide-1 receptor agonist (GLP1-RA) liraglutide reduces kidney and cardiovascular (CV) risk in patients with type 2 diabetes. We previously developed a Parameter Response Efficacy (PRE) score that translates multiple short-term risk marker changes, from baseline to first available follow-up measurement, into a predicted long-term drug effect on clinical outcomes. The objective of this study was to assess the accuracy of the PRE score in predicting the efficacy of liraglutide in reducing the risk of kidney and CV outcomes. Methods: Short-term changes in glycated hemoglobin (HbA1c), systolic blood pressure (BP), urinary-albumin-creatinine-ratio (UACR), hemoglobin, body weight, high-density-lipoprotein (HDL) cholesterol, low-density-lipoprotein (LDL) cholesterol, and potassium were monitored in the LEADER trial. Associations between risk markers and kidney or CV outcomes were established using a multivariable Cox proportional hazards model in a separate pooled database of 6,355 patients with type 2 diabetes. The regression coefficients were then applied to the short-term risk markers in the LEADER trial to predict the effects of liraglutide on kidney (defined as a composite of doubling of serum creatinine or end-stage kidney disease) and CV (defined as a composite of non-fatal myocardial infarction, non-fatal stroke, and CV death) outcomes. Results: Liraglutide compared to placebo reduced HbA1c (1.4%), systolic BP (3.0 mmHg), UACR (13.2%), body weight (2.3 kg), hemoglobin (2.6 g/L), and increased HDL-cholesterol (0.01 mmol/L) (all p-values <0.01). Integrating multiple risk marker changes in the PRE score resulted in a predicted relative risk reduction (RRR) of 16.2% (95% CI 13.7–18.6) on kidney outcomes which was close to the observed RRR of 15.5% (95% CI -9.0–34.6). For the CV outcome, the PRE score predicted a 7.6% (95% CI 6.8–8.3) RRR, which was less than the observed 13.2% (95% CI 3.2–22.2) RRR. Conclusion: Integrating multiple short-term risk markers using the PRE score adequately predicted the effect of liraglutide on the composite kidney outcome. However, the PRE score underestimated the effect of liraglutide for the composite CV outcome, suggesting that the risk markers included in the PRE score do not fully capture the CV benefit of liraglutide

Advancing personalized medicine in type 2 diabetes through better prediction of drug efficacy

Current clinical practice guidelines for patients with type 2 diabetes (T2DM) are primarily based on evidence from clinical trials and population-based studies. These guidelines emphasized the importance of improving glycemic control and controlling other risk factors, such as blood pressure and cholesterol level, to reduce the risk of micro- and macrovascular complications. However, the guidelines do not account for individual variability in response to drugs used to manage these risk factors. This is problematic since many patients do not respond adequately to drugs used to manage kidney and cardiovascular complications. As a result, many patients with T2DM do not respond adequately to these drugs and are unnecessarily exposed to potential side effects. Therefore, the development of personalized treatment strategies that consider individual variability is crucial to improving outcomes in T2DM care. In this thesis, we demonstrated the importance of targeting multiple risk factors as part of comprehensive risk management in T2DM. We validated the multiple Parameter Response Efficacy (PRE) score, which predicts the long-term drug effects on kidney and cardiovascular endpoints, based on short-term drug-induced changes on multiple risk markers. This score could be implemented in clinical trials to predict the long-term effect of drugs on clinical outcomes at a population level. If further validated, the score may predict the drug effect at an individual level. Finally, at an individual level, we also showed a multivariable risk-based approach outperformed the treatment strategy using a single surrogate (e.g., HbA1c or UACR) to guide the treatment initiation of a sodium-glucose co-transporter-2 inhibitor

The importance of targeting multiple risk markers in patients with type 2 diabetes: A post-hoc study from the CANVAS programme

Aims: To investigate the extent to which improvements in multiple cardiovascular risk markers are associated with a lower risk of cardiovascular and kidney outcomes in patients with type 2 diabetes and high cardiovascular risk participating in the CANVAS programme. Materials and methods: Clinically relevant improvements in cardiovascular risk factors were defined as a reduction in glycated haemoglobin ≥1.0%, systolic blood pressure ≥10 mmHg, body weight ≥3 kg, urinary-albumin-creatinine ratio ≥30%, uric acid ≥0.5 mg/dl, and an increase in haemoglobin of ≥1.0 g/dl from baseline to week 26. Participants were categorized according to the number of improvements in cardiovascular risk markers: zero, one, two, three, or four or more risk marker improvements. The Cox proportional hazard regression adjusted for treatment assignment, demographic variables and laboratory measurements was performed to determine the association between the number of risk marker improvements and risk of a composite cardiovascular, heart failure or kidney outcomes. Results: We included 9487 (93.5%) participants with available data at baseline and week 26. After week 26, 566 composite cardiovascular, 370 heart failure/cardiovascular death and 153 composite kidney outcomes occurred. The multivariable adjusted hazard ratios associated with four or more improvements in risk markers versus no risk marker improvement were 0.67 (95% CI 0.48, 0.92), 0.58 (95% CI 0.39, 0.87) and 0.49 (95% CI 0.25, 0.96) for the three outcomes respectively. We observed a trend of decreased hazard ratios across subgroups of increasing number of risk marker improvements (p for trend =.008,.02 and.047, respectively). Conclusions: In patients with type 2 diabetes, improvements in multiple risk markers were associated with a reduced risk of cardiovascular and kidney outcomes as compared with no risk marker improvement

Initiation of the SGLT2 inhibitor canagliflozin to prevent kidney and heart failure outcomes guided by HbA1c, albuminuria, and predicted risk of kidney failure

BACKGROUND: Sodium glucose co-transporter-2 (SGLT2) inhibitors reduce the risk of kidney and heart failure events independent of glycemic effects. We assessed whether initiation of the SGLT2 inhibitor canagliflozin guided by multivariable predicted risk based on clinical characteristics and novel biomarkers is more efficient to prevent clinical outcomes compared to a strategy guided by HbA1c or urinary-albumin-creatinine ratio (UACR) alone. METHODS: We performed a post-hoc analysis of the CANVAS trial including 3713 patients with available biomarker measurements. We compared the number of composite kidney (defined as a sustained 40% decline in eGFR, chronic dialysis, kidney transplantation, or kidney death) and composite heart failure outcomes (defined as heart failure hospitalization or cardiovascular (CV) death) prevented per 1000 patients treated for 5 years when canagliflozin was initiated in patients according to HbA1c ≥ 7.5%, UACR, or multivariable risk models consisting of: (1) clinical characteristics, or (2) clinical characteristics and novel biomarkers. Differences in the rates of events prevented between strategies were tested by Chi2-statistic. RESULTS: After a median follow-up of 6.1 years, 144 kidney events were recorded. The final clinical model included age, previous history of CV disease, systolic blood pressure, UACR, hemoglobin, body weight, albumin, estimated glomerular filtration rate, and randomized treatment assignment. The combined biomarkers model included all clinical characteristics, tumor necrosis factor receptor-1, kidney injury molecule-1, matrix metallopeptidase-7 and interleukin-6. Treating all patients with HbA1c ≥ 7.5% (n = 2809) would prevent 33.0 (95% CI 18.8 to 43.3 ) kidney events at a rate of 9.6 (95% CI 5.5 to 12.6) events prevented per 1000 patients treated for 5 years. The corresponding rates were 5.8 (95% CI 3.4 to 7.9), 16.6 (95% CI 9.5 to 22.0) (P < 0.001 versus HbA1c or UACR approach), and 17.5 (95% CI 10.0 to 23.0) (P < 0.001 versus HbA1c or UACR approach; P = 0.54 versus clinical model). Findings were similar for the heart failure outcome. CONCLUSION: Initiation of canagliflozin based on an estimated risk-based approach prevented more kidney and heart failure outcomes compared to a strategy based on HbA1c or UACR alone. There was no apparent gain from adding novel biomarkers to the clinical risk model. These findings support the use of risk-based assessment using clinical markers to guide initiation of SGLT2 inhibitors in patients with type 2 diabetes