Use of Multiple Metabolic and Genetic Markers to Improve the Prediction of Type 2 Diabetes: the EPIC-Potsdam Study

Abstract

OBJECTIVEWe investigated whether metabolic biomarkers and single nucleotide polymorphisms (SNPs) improve diabetes prediction beyond age, anthropometry, and lifestyle risk factors.RESEARCH DESIGN AND METHODSA case-cohort study within a prospective study was designed. We randomly selected a subcohort (n = 2,500) from 26,444 participants, of whom 1,962 were diabetes free at baseline. Of the 801 incident type 2 diabetes cases identified in the cohort during 7 years of follow-up, 579 remained for analyses after exclusions. Prediction models were compared by receiver operatoring characteristic (ROC) curve and integrated discrimination improvement.RESULTSCase-control discrimination by the lifestyle characteristics (ROC-AUC: 0.8465) improved with plasma glucose (ROC-AUC: 0.8672, P < 0.001) and A1C (ROC-AUC: 0.8859, P < 0.001). ROC-AUC further improved with HDL cholesterol, triglycerides, γ-glutamyltransferase, and alanine aminotransferase (0.9000, P = 0.002). Twenty SNPs did not improve discrimination beyond these characteristics (P = 0.69).CONCLUSIONSMetabolic markers, but not genotyping for 20 diabetogenic SNPs, improve discrimination of incident type 2 diabetes beyond lifestyle risk factors.

Development of a new scoring system for predicting the 5 year incidence of type 2 diabetes in Japan: the Toranomon Hospital Health Management Center Study 6 (TOPICS 6)

“…Combining information on FPG or impaired fasting glucose with a simple diabetes risk score has been reported to increase predictive ability [7,8,[12][13][14][15][16][17]. A study reported that screening models using the combination of HbA 1c , BMI and FPG accurately identified individuals at risk of future clinically diagnosed diabetes [22], although the factors that remained significant were different from those found in the present study.…”

“…On the other hand, adding complex data such as the results of oral glucose tolerance tests and measurements of insulin levels and inflammatory markers into a simple clinical model only minimally improves risk prediction while increasing cost and inconvenience [10,19]. Similarly, adding genetic information to conventional risk factors does not appear to greatly refine the prediction of diabetes risk [14,20,21].…”

“…Introducing HbA 1c into a prediction model has been suggested to be effective in screening for future diabetes [14][15][16][22][23][24][25][26][27][28], and a few models to predict the development of diabetes have recently been developed that concurrently include measurements of FPG, HbA 1c and other blood markers [15,25,29]. After revising the diagnostic criteria for type 2 diabetes by introducing HbA 1c in 2010 [30], the ADA published guidelines and recommendations for diagnosing diabetes based on published data or derived from expert consensus [31].…”

“…Various rules have been developed to predict the incidence of diabetes in different ethnic groups [2][3][4][5]. Routine clinical markers available without laboratory testing have been shown to be predictive of the development of diabetes [6][7][8][9][10][11][12][13][14][15][16][17][18] and adding biochemical measures, in particular fasting plasma glucose (FPG), improves predictive accuracy [7,8,[12][13][14][15][16][17]. On the other hand, adding complex data such as the results of oral glucose tolerance tests and measurements of insulin levels and inflammatory markers into a simple clinical model only minimally improves risk prediction while increasing cost and inconvenience [10,19].…”

The potential of novel biomarkers to improve risk prediction of type 2 diabetes

“…A substantial increment of c statistics is possible if these prediction models do not contain a measure of glycaemia [75]. However, protein-based biomarkers that not only lead to statistically significant, but also to clinically relevant improvements of model accuracy remain to be identified for models that already consider glucose or HbA 1c [18,35,[76][77][78][79][80], as summarised in a recent review [39].…”