TY - JOUR
T1 - Genotype imputation and polygenic score estimation in northwestern Russian population
AU - Kolosov, Nikita
AU - Rezapova, Valeriia
AU - Rotar, Oxana
AU - Loboda, Alexander
AU - Freylikhman, Olga
AU - Melnik, Olesya
AU - Sergushichev, Alexey
AU - Stevens, Christine
AU - Voortman, Trudy
AU - Kostareva, Anna
AU - Konradi, Alexandra
AU - Daly, Mark J.
AU - Artomov, Mykyta
PY - 2022/6
Y1 - 2022/6
N2 - Numerous studies demonstrated the lack of transferability of polygenic score (PGS) models across populations and the problem arising from unequal presentation of ancestries across genetic studies. However, even within European ancestry there are ethnic groups that are rarely presented in genetic studies. For instance, Russians, being one of the largest, diverse, and yet understudied group in Europe. In this study, we evaluated the reliability of genotype imputation for the Russian cohort by testing several commonly used imputation reference panels (e.g. HRC, 1000G, HGDP). HRC, in comparison with two other panels, showed the most accurate results based on both imputation accuracy and allele frequency concordance between masked and imputed genotypes. We built polygenic score models based on GWAS results from the UK biobank, measured the explained phenotypic variance in the Russian cohort attributed to polygenic scores for 11 phenotypes, collected in the clinic for each participant, and finally explored the role of allele frequency discordance between the UK biobank and the study cohort in the resulting PGS performance.
AB - Numerous studies demonstrated the lack of transferability of polygenic score (PGS) models across populations and the problem arising from unequal presentation of ancestries across genetic studies. However, even within European ancestry there are ethnic groups that are rarely presented in genetic studies. For instance, Russians, being one of the largest, diverse, and yet understudied group in Europe. In this study, we evaluated the reliability of genotype imputation for the Russian cohort by testing several commonly used imputation reference panels (e.g. HRC, 1000G, HGDP). HRC, in comparison with two other panels, showed the most accurate results based on both imputation accuracy and allele frequency concordance between masked and imputed genotypes. We built polygenic score models based on GWAS results from the UK biobank, measured the explained phenotypic variance in the Russian cohort attributed to polygenic scores for 11 phenotypes, collected in the clinic for each participant, and finally explored the role of allele frequency discordance between the UK biobank and the study cohort in the resulting PGS performance.
U2 - 10.1371/journal.pone.0269434
DO - 10.1371/journal.pone.0269434
M3 - Article
C2 - 35763490
AN - SCOPUS:85133134430
SN - 1932-6203
VL - 17
JO - PLoS ONE
JF - PLoS ONE
IS - 6 June
M1 - e0269434
ER -