Genetic Risk Score Enhances Coronary Artery Disease Risk Prediction in Individuals With Type 1 Diabetes
OBJECTIVE Individuals with type 1 diabetes are at a high lifetime risk of coronary artery disease (CAD) calling for early interventions. This study explores the use of a genetic risk score (GRS) for CAD risk prediction, compares it to established clinical markers and investigates its performance according to the age and pharmacological treatment. <p>RESEARCH DESIGN AND METHODS This study in 3,295 individuals with type 1 diabetes from the Finnish Diabetic Nephropathy Study (467 incident CAD, 14.8 years follow-up) employed three risk scores: a GRS, a validated clinical score and their combined score. Hazard ratios (HR) were calculated with Cox regression and model performances compared with Harrel’s C-index. </p> <p>RESULTS A HR of 6.7 for CAD was observed between the highest and the lowest 5<sup>th</sup> percentile of the GRS (<i>P</i>=1.8×10<sup>-6</sup>). The performance of GRS (C-index [C] 0.562) was similar to HbA<sub>1c</sub> (C=0.563, <i>p</i>-value for difference 0.96), HDL (C=0.571, <i>P</i>=0.6) and total cholesterol (C=0.594, <i>P</i>=0.1). The GRS was not correlated with the clinical score (<i>r</i>=-0.013, <i>P</i>=0.5). The combined score outperformed the clinical score (C=0.813 vs C=0.820, <i>P</i>=0.003). The GRS performed better in individuals below the median age (38.6 years) compared to those above (C=0.637 vs C=0.546). </p> <p>CONCLUSIONS A GRS identified individuals at high risk of CAD and worked better in younger individuals. GRS was also an independent risk factor for CAD with a predictive power comparable to that of HbA<sub>1c</sub>, HDL and total cholesterol and, when incorporated into a clinical model, modestly improved the predictions. The GRS promises early risk stratification in clinical practice by enhancing the prediction of CAD. </p>