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Assessment of multifactorial coronary artery disease by utilizing genomic data.
Duodecim ; 133(8): 776-81, 2017.
Article en En | MEDLINE | ID: mdl-29240343
The scientific advances in the past few years have enabled individualized prevention and treatment of diseases on the basis of genome-wide information. For example, dozens of genomic regions affecting the risk for coronary artery disease have been identified. Both Finnish and international longitudinal studies show that the risk assessment of coronary artery disease can be significantly improved if the estimate is based both on the newly discovered hereditary risk factors and the long-recognized traditional risk factors, e.g. age, gender, smoking, blood pressure, and serum lipid levels. In this review, by using coronary artery disease as an example, we present recent research aiming at enhancing the use of genome information in combination with traditional risk factors for the assessment of the risk for common disease of public health importance. We introduce the KardioKompassi tool, developed by us, which comprehensively utilizes the genetic profile of an individual in combination with conventional health information to assess the risk for coronary artery disease. We also discuss the prospects and opportunities provided by the newly developed next-generation risk prediction tools to promote health."
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Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedad de la Arteria Coronaria / Pruebas Genéticas / Genómica Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Europa Idioma: En Revista: Duodecim Año: 2017 Tipo del documento: Article
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Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedad de la Arteria Coronaria / Pruebas Genéticas / Genómica Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Europa Idioma: En Revista: Duodecim Año: 2017 Tipo del documento: Article