Clinically significant DNA variation from the GENCOV and HostSeq COVID-19 genome sequencing studies
Clinical Snapshot
PICO Framework
| P — Population | Canadian participants from GENCOV and HostSeq COVID-19 genome sequencing studies |
| I — Intervention | Manual variant classification and annotation using custom workflows |
| C — Comparator | ClinVar database classifications for pathogenic/likely pathogenic variants |
| O — Outcomes | Concordance rates between manual classifications and ClinVar, identification of discrepancies in pathogenic variant classifications |
Bottom Line
This cross-sectional study of 1956 pathogenic variants from Canadian COVID-19 genome sequencing cohorts reveals significant gaps in the ClinVar database, with 35% of expert-classified pathogenic variants absent and 31% showing classification discrepancies. The findings highlight critical limitations in current genetic variant databases that directly impact clinical decision-making. For Australian clinicians, this underscores the importance of expert genetic counselling and the need for caution when interpreting variant significance, particularly for patients from diverse ethnic backgrounds. The study supports ongoing efforts to improve international variant sharing and emphasises that negative database searches do not exclude pathogenicity. Clinicians should consider multiple evidence sources and seek specialist genetic advice when interpreting variants of uncertain significance, especially given the potential for database incompleteness demonstrated in this large-scale analysis.
Key Findings
P Value: Not reported
Effect Size: 69% concordance rate for pathogenic/likely pathogenic variants
Primary Outcome: Concordance between manual variant classification and ClinVar database
Nnt Or Sensitivity: 65% of manually classified P/LP variants found in ClinVar, 35% absent from database
Confidence Interval: Not reported
Clinical Application
Highly feasible - highlights need for improved variant database curation and periodic reassessment of classifications Relevant to Australian genetic testing practices, supports need for local variant databases and improved international data sharing. Aligns with NHMRC guidelines on genomic data sharing and TGA oversight of genetic testing Patients undergoing genetic testing for Mendelian diseases, particularly those of European and diverse ancestry
Abstract
BACKGROUND: Vast amounts of genome sequencing data generated from large-scale research studies like HostSeq provide an opportunity to summarise the spectrum of pathogenic variation in a subset of the Canadian population. Sharing variant-level data with public databases, like ClinVar, is crucial for advancing our understanding of genomic variants related to Mendelian diseases. However, such entries are often incomplete or contain discrepancies which render interpretation and classifications less useful. METHODS: The GENCOV and HostSeq cohorts were annotated and summarised using custom workflows to identify variants with a pathogenic and likely pathogenic (P/LP) classification in ClinVar. These variants were further filtered using custom gene panels, gnomAD frequency, variant type, gene-disease relationship and the number of reputable ClinVar laboratory submissions. Manually assessed variants from the GENCOV study were compared with ClinVar classifications to identify discrepancies. RESULTS: A total of 1956 unique variants were manually classified as P/LP through the GENCOV study. Of these, 65% (1276) were also identified in ClinVar, and among those, 69% (889) had concordant P/LP classifications. The manual assessment of unique exonic variants in GENCOV yielded a higher number of putative P/LP variants (1595), including truncating and missense variants compared with the 127 unique exonic P/LP variants in HostSeq. CONCLUSION: These results highlight that a large proportion of P/LP variation is either absent or has conflicting evidence for pathogenicity in ClinVar, emphasising the importance of periodic reassessment, discrepancy resolution and updates to ensure completeness and accuracy of public databases.
References
- 1.Frangione, E., Mahajan, R., De Los Rios, J., Casalino, S., Aujla, N., Arnoldo, S., Binnie, A., Borgundvaag, B., Dagher, M., Devine, L., Faghfoury, H., Friedman, S. M., Fung, C. Y. J., Khan, Z., Morgan, G., Richardson, D., Stern, S., Taher, A., Taher, J., & Lerner-Ellis, J. (2026). Clinically significant DNA variation from the GENCOV and HostSeq COVID-19 genome sequencing studies. Journal of Medical Genetics. https://doi.org/10.1136/jmg-2025-111029
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