Additional Contribution of Emerging Risk Factors to the Prediction of the Risk of Type 2 Diabetes: Evidence From the Western New York Study

Abstract

To examine whether several biomarkers of endothelial function and inflammation improve prediction of type 2 diabetes over 5.9 years of follow-up, independent of traditional risk factors. A total of 1,455 participants from the Western New York Study, free of type 2 diabetes at baseline, were selected. Incident type 2 diabetes was defined as fasting glucose exceeding 125 mg/dl or on antidiabetic medication at the follow-up visit. Sixty-one people who met the case definition (8/1,000 person years) were identified and individually matched with up to three controls on gender, race, year of study enrollment, and baseline fasting glucose (<110 or 110-125 mg/dl). Biomarkers were measured from frozen baseline samples. In conditional logistic regression analyses accounting for traditional risk factors (age, family history of diabetes, smoking, drinking status, and BMI), E-selectin was positively related (3rd vs. 1st tertile: odds ratio 2.77, 95% confidence interval (CI) 1.13-6.79, P for linear trend = 0.023) and serum albumin was inversely related (3rd vs. 1st tertile: odds ratio 0.36, 95% CI 0.14-0.93, P for linear trend = 0.032) to type 2 diabetes incidence. The addition of E-selectin, serum albumin, and leukocyte count to a basic risk factor model including only traditional risk factors significantly increased the area under the receiver operating characteristic curve (AUC) (from 0.646 to 0.726, P value = 0.04). These results support the role of endothelial dysfunction and subclinical inflammation as important mechanisms in the etiopathogenesis of type 2 diabetes; moreover, they indicate that novel biomarkers may improve the prediction of type 2 diabetes beyond the use of traditional risk factors alone.