VarSome - Company News

Expanding population frequency data in VarSome: Introducing Korean and Japanese frequency databases

Written by Lyndsey Fletcher | Aug 7, 2026, 11:02:56 AM

Accurate variant interpretation depends on access to representative population frequency data. In VarSome v13.18, we’ve expanded our population frequency resources through the integration of KRIBB KOVA and ToMMo jMorp, which offer population allele frequency data from the Korean and Japanese populations, respectively. These datasets help laboratories interpret variants with greater confidence by offering ancestry-specific context, supporting more equitable genomic analysis for increasingly diverse populations.

Population frequency data is one of the most important sources of evidence in clinical variant interpretation. It helps laboratories distinguish between rare variants that may be disease-causing and common variants that are more likely to be benign.

However, population frequency databases, similarly to other genomic data sources, tend to contain a disproportionate amount of data from individuals of European descent1. As genomic testing becomes increasingly accessible and commonplace, this imbalance becomes more impactful; many genetic variants appear at higher frequencies within specific populations compared to what is reflected within larger databases. This means that variants that are in fact common in one population can appear to be artificially rare, reducing confidence in variant filtering and interpretation.

Not only does this impact variant interpretation for labs and clinics within underrepresented regions, it is increasingly becoming a global challenge. It is now estimated that over 3.7% of the world’s population are international migrants, living outside their country of birth, rising from 2.8% at the start of the 21st century2. This demographic shift highlights the growing need for more informative data to ensure a better understanding of how our genes influence our health.

Why diverse datasets are needed for modern genomics

There are many examples of genetic variants that are exceedingly rare in one population, yet are common and impactful in others.

The APOL1 gene, for example, contains variants that dramatically increase the risk of severe end-stage kidney disease and focal segmental glomerulosclerosis. However, these variants are so rare in those of European descent that studies within this population missed the association. In individuals of West African ancestry, these variants and the associated conditions were far more common, likely due to the variants playing a protective role against infection by Trypanosoma brucei3.

Another example is that of Brugada syndrome, which results in sudden cardiac death, and most frequently occurs in Asian populations. A number of genes are associated with this condition, and a wide range of variants had been previously classified as pathogenic. A 2019 reassessment of these pathogenic variants found that 14 of them were found at a minor allele frequency ≥ 0.001 in Asian populations specifically, suggesting that they are too common in some ancestries to be disease-causing4.

How VarSome is addressing this challenge

Every patient deserves to benefit from genomic medicine, and accurate variant interpretation requires reference data that reflects real diversity. To address this, VarSome v13.18 introduces two new population frequency databases, KRIBB KOVA and ToMMo jMorp, which offer population allele frequency data from the Korean and Japanese populations, respectively.

KRIBB KOVA (Korean Variant Archive)5, developed by the Korea Research Institute of Bioscience and Biotechnology (KRIBB), contains allele frequency data derived from healthy Korean individuals. It provides a population-specific reference for variants observed in patients of Korean ancestry.

ToMMo jMorp (Japanese Multi Omics Reference Panel)6, developed by the Tohoku Medical Megabank Organization (ToMMo), is a comprehensive Japanese reference database combining genomic and other omics data.

Leveraging East Asian genomic data to improve variant interpretation

In 2025, a study published in Scientific Reports showcased the impact of leveraging population allele frequencies from Korean and Japanese cohorts, including from KOVA and jMorp, when identifying variants associated with hearing loss. The study assessed variants found in the Deafness Variants Database and, using data from East Asian populations, the authors reclassified several pathogenic or likely pathogenic variants as benign, likely benign, or of uncertain significance. Over 3,000 variants of uncertain significance were reclassified as benign, and several East Asian founder alleles were identified7.

Why it matters

Together, these datasets expand the population frequency evidence available within VarSome, giving laboratories access to more representative frequency information when analysing data from those of Korean or Japanese ancestry. They are also valuable for labs serving increasingly diverse populations, including diaspora communities and cosmopolitan cities, where ancestry-specific reference data can provide important context.

Variant interpretation depends on bringing together multiple lines of evidence beyond population frequency, including predicted functional impact, clinical evidence, inheritance patterns, and computational predictions. VarSome integrates these evidence sources into a single interpretation workflow, and by incorporating these new population frequency databases directly into the platform, users can now benefit from immediate access to ancestry-specific data alongside other relevant evidence without having to consult external resources independently.

This integration directly strengthens the clinical and research utility of VarSome, giving users richer context when assessing variant pathogenicity and improving confidence in classification decisions. This represents a meaningful step toward making VarSome the most complete and globally representative variant interpretation platform available.


References:

  1. Fatumo S, Chikowore T, Choudhury A, Ayub M, Martin AR, Kuchenbaecker K. A roadmap to increase diversity in genomic studies. Nat Med. 2022 Feb;28(2):243-250. doi: 10.1038/s41591-021-01672-4. Epub 2022 Feb 10. PMID: 35145307; PMCID: PMC7614889.
  2. International Organization for Migration. International migrants: numbers and trends. In: World Migration Report 2026. Chapter 2: Migration and migrants: a global overview. Geneva: International Organization for Migration; 2026 [cited 2026 Aug 3]. Available from: https://worldmigrationreport.iom.int/what-we-do/world-migration-report-2026/chapter-2/international-migrants-numbers-and-trends
  3. Genovese G, Tonna SJ, Knob AU, Appel GB, Katz A, Bernhardy AJ, Needham AW, Lazarus R, Pollak MR. A risk allele for focal segmental glomerulosclerosis in African Americans is located within a region containing APOL1 and MYH9. Kidney Int. 2010 Oct;78(7):698-704. doi: 10.1038/ki.2010.251. Epub 2010 Jul 28. PMID: 20668430; PMCID: PMC3001190.
  4. Chen CJ, Lu TP, Lin LY, Liu YB, Ho LT, Huang HC, Lai LP, Hwang JJ, Yeh SS, Wu CK, Juang JJ, Antzelevitch C. Impact of Ancestral Differences and Reassessment of the Classification of Previously Reported Pathogenic Variants in Patients With Brugada Syndrome in the Genomic Era: A SADS-TW BrS Registry. Front Genet. 2019 Jan 4;9:680. doi: 10.3389/fgene.2018.00680. PMID: 30662450; PMCID: PMC6328444.
  5. Lee S, Seo J, Park J, Nam JY, Choi A, Ignatius JS, Bjornson RD, Chae JH, Jang IJ, Lee S, Park WY, Baek D, Choi M. Korean Variant Archive (KOVA): a reference database of genetic variations in the Korean population. Sci Rep. 2017 Jun 27;7(1):4287. doi: 10.1038/s41598-017-04642-4.
  6. Tadaka S, Saigusa D, Motoike IN, Inoue J, Aoki Y, Shirota M, Koshiba S, Yamamoto M, Kinoshita K. jMorp: Japanese Multi Omics Reference Panel. Nucleic Acids Res. 2018 Jan 4;46(D1):D551-D557. doi: 10.1093/nar/gkx978. PMID: 29069501; PMCID: PMC5753289.
  7. Joo SY, Jang SH, Kim JA, Kim SJ, Choi JY, Jung J, Gee HY. Leveraging underrepresented population data improves interpretation of genetic variants associated with hearing loss. Sci Rep. 2025 Sep 29;15(1):33842. doi: 10.1038/s41598-025-18852-8.