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A mechanistic model for atherosclerosis and its application to the cohort of Mayak workers.

PLoS ONE 12:e0175386 (2017)
Verlagsversion Forschungsdaten DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
We propose a stochastic model for use in epidemiological analysis, describing the age-dependent development of atherosclerosis with adequate simplification. The model features the uptake of monocytes into the arterial wall, their proliferation and transition into foam cells. The number of foam cells is assumed to determine the health risk for clinically relevant events such as stroke. In a simulation study, the model was checked against the age-dependent prevalence of atherosclerotic lesions. Next, the model was applied to incidence of atherosclerotic stroke in the cohort of male workers from the Mayak nuclear facility in the Southern Urals. It describes the data as well as standard epidemiological models. Based on goodness-of-fit criteria the risk factors smoking, hypertension and radiation exposure were tested for their effect on disease development. Hypertension was identified to affect disease progression mainly in the late stage of atherosclerosis. Fitting mechanistic models to incidence data allows to integrate biological evidence on disease progression into epidemiological studies. The mechanistic approach adds to an understanding of pathogenic processes, whereas standard epidemiological methods mainly explore the statistical association between risk factors and disease outcome. Due to a more comprehensive scientific foundation, risk estimates from mechanistic models can be deemed more reliable. To the best of our knowledge, such models are applied to epidemiological data on cardiovascular diseases for the first time.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Cardiovascular-disease; Production-association; Inflammatory Response; Ionizing-radiation; Carcinogenesis; Macrophage; Risk; Cancer; Atherogenesis; Instability
Sprache englisch
Veröffentlichungsjahr 2017
HGF-Berichtsjahr 2017
ISSN (print) / ISBN 1932-6203
Zeitschrift PLoS ONE
Quellenangaben Band: 12, Heft: 4, Seiten: , Artikelnummer: e0175386 Supplement: ,
Verlag Public Library of Science (PLoS)
Verlagsort Lawrence, Kan.
Begutachtungsstatus Peer reviewed
POF Topic(s) 30504 - Mechanisms of Genetic and Environmental Influences on Health and Disease
Forschungsfeld(er) Radiation Sciences
PSP-Element(e) G-501100-004
G-501100-005
PubMed ID 28384359
Scopus ID 85017098564
Erfassungsdatum 2017-04-25