Genotype imputation and polygenic score estimation in northwestern Russian population

Area of Science:

• Population Genetics
• Genomic Medicine
• Bioinformatics

Background:

• Polygenic score (PGS) models often lack transferability across diverse populations.
• Genetic studies historically underrepresent various ethnic groups, including Russians.
• Accurate genotype imputation is crucial for reliable PGS in understudied populations.

Purpose of the Study:

• To evaluate genotype imputation reliability in a Russian cohort using different reference panels.
• To assess the performance of polygenic score models in the Russian population.
• To investigate the impact of allele frequency differences on PGS accuracy.

Main Methods:

• Tested imputation accuracy using HRC, 1000G, and HGDP reference panels.
• Built polygenic score models using UK Biobank GWAS data.
• Measured explained phenotypic variance for 11 traits in the Russian cohort.

Main Results:

• The HRC reference panel demonstrated superior imputation accuracy and allele frequency concordance for the Russian cohort.
• Polygenic scores showed varying performance, influenced by allele frequency discordance between reference and study populations.
• Identified key factors affecting PGS transferability in this underrepresented group.

Conclusions:

• Genotype imputation using the HRC panel is reliable for the Russian cohort.
• Allele frequency differences significantly impact polygenic score performance across populations.
• Improving genetic data representation is essential for equitable genomic medicine.