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Symianakis, P.G.* ; Kalafati, I.P.* ; Amerikanou, C.* ; Brekou, D.* ; Dimitriou, M.* ; Farmaki, A.E.* ; Giannakopoulou, O.* ; Giardoglou, P.* ; Grigoriou, E.* ; Kafyra, M.* ; Kanoni, S.* ; Kariakli, V.E.* ; Katsareli, E.A.* ; Marouli, E.* ; Ntalla, I.* ; Pogosova, N.A.* ; Theodoraki, E.V.* ; Tsota, M.* ; Alexandrou, A.* ; Amfilochiou, A.* ; Hatziagelaki, E.* ; Kaliora, A.C.* ; Kokkinos, A.* ; Kolovou, G.* ; Rallidis, L.S.* ; Stamatelopoulos, K.* ; Tentolouris, N.* ; Thanopoulou, A.* ; Triantafyllou, K.* ; Trovas, G.* ; Dimas, A.S.* ; Mamakou, V.* ; Rouskas, K.* ; Deloukas, P.* ; Zeggini, E. ; Dedoussis, G.V.*

The HUA BioResource: A national infrastructure for genetic and phenotypic insights into BMI and obesity in Greece.

IEEE J. Biomed. Health Inform., DOI: 10.1109/JBHI.2026.3741223 (2026)
Verlagsversion DOI
Open Access Hybrid
Creative Commons Lizenzvertrag
The HUA BioResource (HUABR) is one of the first large-scale multicohort resources in Greece, integrating genetic and phenotypic data across 16 national studies. This paper presents the first comprehensive description of the HUA BioResource (HUABR), outlining its structure, data collection methodology, and research potential. The repository serves as a critical resource for investigating the interplay between genetics, lifestyle, and body mass index (BMI), enabling advanced analyses of obesity and obesity-related cardiometabolic disorders. Initial findings highlight significant associations between BMI and genetic predisposition as well as lifestyle, contextual and clinical factors, with polygenic risk scores (PRSs) enhancing obesity prediction models. By creating one of the first databases with unified, multidisciplinary data for Greek citizens, the HUA Bioresource fosters international collaborations and advances precision medicine, public health, and targeted prevention strategies.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Bmi ; Body Mass Index ; Diet ; Genetics ; Greek ; Hua Bioresource ; Huabr ; Lifestyle ; Personalized Medicine ; Prs
ISSN (print) / ISBN 2168-2194
e-ISSN 2168-2208
Zeitschrift IEEE Journal of Biomedical and Health Informatics
Verlag IEEE
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Translational Genetics (ITG)