Association of N-Acetyl Asparagine with QTc in Diabetes: A Metabolomics Study
Giacomo Gravina,
Melissa Y. Y. Moey,
Edi Prifti,
Farid Ichou,
Olivier Bourron,
Elise Balse,
Fabio Badillini,
Christian Funck-Brentano,
Joe-Elie Salem
Affiliations
Giacomo Gravina
Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, 41390 Gothenburg, Sweden
Melissa Y. Y. Moey
Department of Cardiovascular Sciences, East Carolina University (ECU) Health Medical Center, East Carolina University, Greenville, NC 27834, USA
Edi Prifti
IRD, Unité de Modélisation Mathématique et Informatique des Systèmes Complexes, Sorbonne Université, UMMISCO, F-93143 Bondy, France
Farid Ichou
ICAN Omics, Foundation for Innovation in Cardiometabolism and Nutrition (ICAN), Hôpital Pitié-Salpêtrière, F-75013 Paris, France
Olivier Bourron
Sorbonne Université Médecine, Assistance Publique Hôpitaux de Paris (APHP), Service de Diabétologie, Hôpital Pitié-Salpêtrière, INSERM UMRS_1138, Centre de Recherche des Cordeliers, Institute of Cardiometabolisme and Nutrition (ICAN), F-75013 Paris, France
Elise Balse
Institute of Cardiometabolism and Nutrition (ICAN), INSERM, Sorbonne Université, UMR_S1166, F-75013 Paris, France
Fabio Badillini
AMPS LLC, New York, NY 10041, USA
Christian Funck-Brentano
Department of Pharmacology and Clinical Investigation Centre (CIC-1901), Pitié-Salpêtrière Hospital, AP-HP, Sorbonne Université, INSERM, F-75013 Paris, France
Joe-Elie Salem
Department of Pharmacology and Clinical Investigation Centre (CIC-1901), Pitié-Salpêtrière Hospital, AP-HP, Sorbonne Université, INSERM, F-75013 Paris, France
Changes in the cardio-metabolomics profile and hormonal status have been associated with long QT syndrome, sudden cardiac death and increased mortality. The mechanisms underlying QTc duration are not fully understood. Therefore, an identification of novel markers that complement the diagnosis in these patients is needed. In the present study, we performed untargeted metabolomics on the sera of diabetic patients at a high risk of cardiovascular disease, followed up for 2.55 [2.34–2.88] years (NCT02431234), with the aim of identifying the metabolomic changes associated with QTc. We used independent weighted gene correlation network analysis (WGCNA) to explore the association between metabolites clusters and QTc at T1 (baseline) and T2 (follow up). The overlap of the highly correlated modules at T1 and T2 identified N-Acetyl asparagine as the only metabolite in common, which was involved with the urea cycle and metabolism of arginine, proline, glutamate, aspartate and asparagine. This analysis was confirmed by applying mixed models, further highlighting its association with QTc. In the current study, we were able to identify a metabolite associated with QTc in diabetic patients at two chronological time points, suggesting a previously unrecognized potential role of N-Acetyl asparagine in diabetic patients suffering from long QTc.