Abstract P195: Lipoprotein and Metabolite Biomarkers for Coronary and Peripheral Artery Disease: Blood Biomarker Profiling of 32,000 Individuals From Five Prospective Studies

• Published in: Circulation (New York, N.Y.) N.Y.), 2020-03, Vol.141 (Suppl_1)
• Main Authors: Tikkanen, Emmi, Mustelin, Linda, Aittomaki, Viljami, Kalimeri, Maria, Jousilahti, Pekka, Perola, Markus, Ala-Korpela, Mika J, Salomaa, Veikko V, Würtz, Peter
• Format: Article
• Language: English
• ISSN: 0009-7322; 1524-4539
• DOI: 10.1161/circ.141.suppl_1.P195

Abstract only Background: Coronary artery disease (CAD) and peripheral artery disease (PAD) share pathogenesis, but the evidence of metabolic risk factors underlying PAD risk is limited. We conducted detailed metabolic profiling of incident CAD and PAD to identify novel risk factors and clarify pathogenesis for these diseases. Methods: We measured circulating blood biomarkers using an NMR metabolomics in four large prospective studies from Finland (national FINRISK and Health 2000 studies, total n = 32,607). We used Cox proportional hazard modelling to estimate associations between biomarkers and incident CAD and PAD ( n events = 2010 and 464, respectively, during the median follow-up time of 14 years). Results: High VLDL-C increased the risk for CAD (HR=1.30, 95% CI 1.24-1.35 per SD-change), but not PAD (HR=1.09, 95% CI 0.99-1.21). Moreover, LDL-C and apolipoprotein B were only associated with CAD (HR=1.13, 95% CI 1.08-1.19; HR=1.29, 95% CI 1.23-1.35), whereas high triglycerides in LDL and VLDL increased the risk for both endpoints. Glycolysis-related metabolites (glucose, lactate, pyruvate and glycerol), amino acids (phenylalanine, alanine and glutamine) and inflammation biomarker glycoprotein acetyls (GlycA) showed stronger associations with PAD. Biomarker score showed stronger risk discrimination of high-risk individuals for incident PAD when compared to traditional CVD risk factors, suggesting that measuring these biomarkers could help to detect high-risk individuals better than currently used risk factors. Conclusions: We identified novel biomarkers for cardiovascular endpoints showed that the associations of these biomarkers were actually stronger for PAD compared to the CAD. Novel biomarkers could be used to guide the development of new therapies and improve the detection of high-risk individuals for these diseases. Figure. Associations between metabolic biomarkers and incident PAD and CAD.