Relation of Serum and Urine Renal Biomarkers to Cardiovascular Risk in Patients with Type 2 Diabetes Mellitus and Recent Acute Coronary Syndromes (From the EXAMINE Trial)

Abstract

A deeper understanding of the interplay between the renal axis and cardiovascular (CV) disease is needed in type 2 diabetes mellitus (T2DM). We aimed to explore the prognostic value of a comprehensive panel of renal biomarkers in patients with T2DM at high CV risk. We evaluated the prognostic performance of both serum (Cystatin C) and urine renal biomarkers (neutrophil gelatinase-associated lipocalin, kidney injury molecule-1 protein, and indices of urinary protein excretion) in 5,380 patients with T2DM and recent acute coronary syndromes in the EXAMINE trial. Patients requiring dialysis within 14 days were excluded. Single- and multimarker covariate-adjusted Cox proportional hazards models were developed to predict times to events. Primary endpoint was composite nonfatal myocardial infarction, nonfatal stroke, or CV death. Median age was 61 years, 68% were men, and mean baseline estimated glomerular filtration rate (eGFR) was 74 mL/min/1.73 m2. During median follow-up of 18 months, 621 (11.5%) experienced the primary endpoint and 326 (6.1%) patients had died. All renal biomarkers were robustly associated with adverse CV events in step-wise fashion, independent of baseline eGFR. However, in the multimarker prediction model, only Cystatin C (per 1 SD) was associated with the primary endpoint (hazard ratio [HR] 1.28 [1.14 to 1.45]; p ≤ 0.001), death (HR 1.51 [1.30 to 1.74]; p ≤ 0.001), and heart failure hospitalization (HR 1.20 [0.96 to 1.49]; p = 0.11). Association between Cystatin C and the primary endpoint was similar in baseline eGFR above and below 60 mL/min/1.73 m2 (Pinteraction > 0.05). In conclusion, serum and urine renal biomarkers, when tested alone, independently predict long-term adverse CV events in high-risk patients with T2DM. In an integrative panel of renal biomarkers, only serum Cystatin C remained independently associated with subsequent CV risk. Renal biomarkers informing various aspects of kidney function may further our understanding of the complex interplay between diabetic kidney disease and CV disease.