Value of Multiomics Over Clinical Risk Factors in Hypertension Prediction

20251 citationsJournal Articlehybrid Open Access

Authors

Matti A. Vuori · Turku University Hospital

Matti O. Ruuskanen · University of Turku

Pekka Jousilahti · Finnish Institute for Health and Welfare

Veikko Salomaa · Finnish Institute for Health and Welfare

Li-Fang Yeo · Turku University Hospital

Anni Kauko · University of Turku

Felix Vaura

Abstract

The best prediction combination model for incident hypertension was the clinical model augmented with a polygenic risk score. These data suggest that polygenic risk scores provide limited incremental value over clinical risk factors when assessing risk of incident hypertension.

Topics & Keywords

Blood Pressure and Hypertension Studies Genetic Associations and Epidemiology Machine Learning in Healthcare

Publication Details

Published in: Hypertension

Volume 83, Issue 2, pp. e25358-e25358

DOI: 10.1161/hypertensionaha.125.25358

Field-Weighted Citation Impact: 1.39

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Value of Multiomics Over Clinical Risk Factors in Hypertension Prediction

Authors

Abstract

Topics & Keywords

Publication Details