Yalaev, Bulat,
Tyurin, Anton,
Prokopenko, Inga,
Karunas, Aleksandra,
Khusnutdinova, Elza,
Khusainova, Rita (2022) . Using the
polygenic score (PGS) approach, we combined the effects of bone mineral density (BMD) DNA loci
Timasheva, Yanina,
Kochetova, Olga,
Balkhiyarova, Zhanna,
Korytina, Gulnaz,
Prokopenko, Inga,
Nouwen, Arie (2025) , we evaluated the prognostic capability of a
polygenic score model for MetS risk, both independently
Timasheva, Y.,
Balkhiyarova, Z.,
Avzaletdinova, D.,
Rassoleeva, I.,
Morugova, T.V.,
Korytina, G.,
Prokopenko, I.,
Kochetova, O. (2023) ability of the model containing
polygenic scores for the variants associated with T2D in our dataset
Savelieva, Olga,
Karunas, Alexandra,
Prokopenko, Inga,
Balkhiyarova, Zhanna,
Gilyazova, Irina,
Khidiyatova, Irina,
Khusnutdinova, Elza (2025) by genetic variability. The
polygenic score (PGS) approach enables an individual risk of asthma
Kazantseva, Anastasiya,
Davydova, Yuliya,
Enikeeva, Renata,
Mustafin, Rustam,
Malykh, Sergey,
Lobaskova, Marina,
Kanapin, Alexander,
Prokopenko, Inga,
Khusnutdinova, Elza (2023) The risk of depression could be evaluated through its multifactorial nature using the
polygenicKazantseva, A.V.,
Davydova, Yu. D.,
Enikeeva, R.F.,
Yakovleva, D.V.,
Mustafin, R.N.,
Lobaskova, M.M.,
Malykh, S.B.,
Khusnutdinova, E.K. (2023) polygenic score (PGS) approach has been performed mainly in Western Europeans and is scarce in Russians
Ivanova, E.,
Gilyazova, I.,
Pavlov, V.,
Izmailov, A.,
Gimalova, G.,
Karunas, A.,
Prokopenko, I.,
Khusnutdinova, E. (2022) The
polygenic scores (PGSs) are developed to help clinicians in distinguishing individuals at high