Unbiased phenotype and genotype matching maximizes gene discovery and diagnostic yield

Jonathan Rips, Orli Halstuk, Adina Fuchs, Ziv Lang, Tal Sido, Shiri Gershon-Naamat, Bassam Abu-Libdeh, Simon Edvardson, Somaya Salah, Oded Breuer, Mohamad Hadhud, Sharon Eden, Itamar Simon, Mordechai Slae, Nadirah S. Damseh, Abdulsalam Abu-Libdeh, Marina Eskin-Schwartz, Ohad S. Birk, Julia Varga, Ora Schueler-FurmanChaggai Rosenbluh, Orly Elpeleg, Shira Yanovsky-Dagan, Hagar Mor-Shaked, Tamar Harel*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Purpose: Widespread application of next-generation sequencing, combined with data exchange platforms, has provided molecular diagnoses for countless families. To maximize diagnostic yield, we implemented an unbiased semi-automated genematching algorithm based on genotype and phenotype matching. Methods: Rare homozygous variants identified in 2 or more affected individuals, but not in healthy individuals, were extracted from our local database of ∼12,000 exomes. Phenotype similarity scores (PSS), based on human phenotype ontology terms, were assigned to each pair of individuals matched at the genotype level using HPOsim. Results: 33,792 genotype-matched pairs were discovered, representing variants in 7567 unique genes. There was an enrichment of PSS ≥0.1 among pathogenic/likely pathogenic variant-level pairs (94.3% in pathogenic/likely pathogenic variant-level matches vs 34.75% in all matches). We highlighted founder or region-specific variants as an internal positive control and proceeded to identify candidate disease genes. Variant-level matches were particularly helpful in cases involving inframe indels and splice region variants beyond the canonical splice sites, which may otherwise have been disregarded, allowing for detection of candidate disease genes, such as KAT2A, RPAIN, and LAMP3. Conclusion: Semi-automated genotype matching combined with PSS is a powerful tool to resolve variants of uncertain significance and to identify candidate disease genes.

Original languageAmerican English
Article number101068
JournalGenetics in Medicine
Issue number4
Early online date6 Jan 2024
StatePublished - Apr 2024

Bibliographical note

Publisher Copyright:
© 2024 American College of Medical Genetics and Genomics


  • Exome sequencing
  • Genotype matching
  • HPO terms
  • KAT2A
  • Phenotype similarity scores
  • Variants of uncertain significance


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