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Genetic Tools for Coronary Risk Assessment in Type 2 Diabetes: A Cohort Study From the ACCORD Clinical Trial.
Morieri, Mario Luca; Gao, He; Pigeyre, Marie; Shah, Hetal S; Sjaarda, Jennifer; Mendonca, Christine; Hastings, Timothy; Buranasupkajorn, Patinut; Motsinger-Reif, Alison A; Rotroff, Daniel M; Sigal, Ronald J; Marcovina, Santica M; Kraft, Peter; Buse, John B; Wagner, Michael J; Gerstein, Hertzel C; Mychaleckyj, Josyf C; Parè, Guillaume; Doria, Alessandro.
Afiliação
  • Morieri ML; Section on Genetics and Epidemiology, Research Division, Joslin Diabetes Center, Boston, MA.
  • Gao H; Department of Medicine, Harvard Medical School, Boston, MA.
  • Pigeyre M; Section on Genetics and Epidemiology, Research Division, Joslin Diabetes Center, Boston, MA.
  • Shah HS; Department of Medicine, Harvard Medical School, Boston, MA.
  • Sjaarda J; Department of Pathology and Molecular Medicine and Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada.
  • Mendonca C; Section on Genetics and Epidemiology, Research Division, Joslin Diabetes Center, Boston, MA.
  • Hastings T; Department of Medicine, Harvard Medical School, Boston, MA.
  • Buranasupkajorn P; Department of Pathology and Molecular Medicine and Population Health Research Institute, McMaster University, Hamilton, Ontario, Canada.
  • Motsinger-Reif AA; Section on Genetics and Epidemiology, Research Division, Joslin Diabetes Center, Boston, MA.
  • Rotroff DM; Section on Genetics and Epidemiology, Research Division, Joslin Diabetes Center, Boston, MA.
  • Sigal RJ; Section on Genetics and Epidemiology, Research Division, Joslin Diabetes Center, Boston, MA.
  • Marcovina SM; Department of Medicine, Harvard Medical School, Boston, MA.
  • Kraft P; Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
  • Buse JB; Bioinformatics Research Center and Department of Statistics, North Carolina State University, Raleigh, NC.
  • Wagner MJ; Bioinformatics Research Center and Department of Statistics, North Carolina State University, Raleigh, NC.
  • Gerstein HC; Departments of Medicine, Cardiac Sciences, and Community Health Sciences, Cumming School of Medicine, and Faculties of Medicine and Kinesiology, University of Calgary, Calgary, Alberta, Canada.
  • Mychaleckyj JC; Department of Medicine, University of Washington, and Northwest Lipid Metabolism and Diabetes Research Laboratories, Seattle, WA.
  • Parè G; Departments of Epidemiology and Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA.
  • Doria A; Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC.
Diabetes Care ; 41(11): 2404-2413, 2018 Nov.
Article em En | MEDLINE | ID: mdl-30262460
ABSTRACT

OBJECTIVE:

We evaluated whether the increasing number of genetic loci for coronary artery disease (CAD) identified in the general population could be used to predict the risk of major CAD events (MCE) among participants with type 2 diabetes at high cardiovascular risk. RESEARCH DESIGN AND

METHODS:

A weighted genetic risk score (GRS) derived from 204 variants representative of all the 160 CAD loci identified in the general population as of December 2017 was calculated in 5,360 and 1,931 white participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) and Outcome Reduction With Initial Glargine Intervention (ORIGIN) studies, respectively. The association between GRS and MCE (combining fatal CAD events, nonfatal myocardial infarction, and unstable angina) was assessed by Cox proportional hazards regression.

RESULTS:

The GRS was associated with MCE risk in both ACCORD and ORIGIN (hazard ratio [HR] per SD 1.27, 95% CI 1.18-1.37, P = 4 × 10-10, and HR per SD 1.35, 95% CI 1.16-1.58, P = 2 × 10-4, respectively). This association was independent from interventions tested in the trials and persisted, though attenuated, after adjustment for classic cardiovascular risk predictors. Adding the GRS to clinical predictors improved incident MCE risk classification (relative integrated discrimination improvement +8%, P = 7 × 10-4). The performance of this GRS was superior to that of GRS based on the smaller number of CAD loci available in previous years.

CONCLUSIONS:

When combined into a GRS, CAD loci identified in the general population are associated with CAD also in type 2 diabetes. This GRS provides a significant improvement in the ability to correctly predict future MCE, which may increase further with the discovery of new CAD loci.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença da Artéria Coronariana / Marcadores Genéticos / Diabetes Mellitus Tipo 2 / Angiopatias Diabéticas / Estudos de Associação Genética Tipo de estudo: Clinical_trials / Diagnostic_studies / Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Diabetes Care Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Marrocos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença da Artéria Coronariana / Marcadores Genéticos / Diabetes Mellitus Tipo 2 / Angiopatias Diabéticas / Estudos de Associação Genética Tipo de estudo: Clinical_trials / Diagnostic_studies / Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Diabetes Care Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Marrocos