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The need for a robust and efficient method to identify GDRs is essential as a majority of patients with a suspected Mendelian condition lack a precise diagnosis.
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Identifying Gene–Disease Relationships in the Clinical Exome

The six-month study combined computational indexing of 9.5 million full-text genomic publications with a systematic literature review

Genomenon Inc.

Genomenon is a genomic health IT company that keeps pace with the constant advancements made in genomics and connects that research to patient DNA to help diagnose and treat patients with rare genetic diseases and cancer.

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Published:Mar 14, 2024
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ANN ARBOR, MI — At the recently held 2024 ACMG Annual Clinical Genetics meeting, Genomenon presented data demonstrating how computational indexing of millions of published abstracts and full-text references combined with a systematic literature review can be used to rapidly and accurately characterize gene–disease relationships (GDRs) and to resolve variants of uncertain significance (VUS). 

The study was completed in less than six months and identified 10,745 germline GDRs and 5,973 germline GDRs with positive associations between a disease and gene. Each GDR is accompanied by well-documented scientific evidence curated by Genomenon’s team of genetic scientists. 

Why is it important to identify gene–disease relationships?

The need for a robust and efficient method to identify GDRs is essential as more than 50 percent of patients with a suspected Mendelian condition lack a precise diagnosis. The number of VUSs is also growing exponentially due to increased genetic testing and sequencing. In recent weeks, for example, the NIH’s All of Us research program released nearly a quarter of a million clinical-grade genome sequences along with more than 275 million previously unreported genetic variants.

“With an onslaught of new sequencing data, it is becoming increasingly urgent to rapidly and accurately curate and characterize VUS and GDRs across all genes associated with the clinical exome,” said Mark J. Kiel, MD, PhD, Genomenon’s chief scientific officer. "The results we presented demonstrate the power of integrating computational indexing with expert curation of scientific evidence to achieve this goal. This approach allowed us to increase the speed and accuracy of defining variant pathogenicity, which is essential to keep pace with the publication of new variants and improve the precision of genetic diagnoses.”

There was substantial agreement between the results of the Genomenon study and ClinGen. Most discrepancies were due to new evidence being published after the last ClinGen curation. This gap reflects the value of combining computational power and human expertise to enable more timely identification of novel GDRs accompanied by well-documented evidence. 

When Genomenon results were compared with aggregated results from twelve submitting groups in ClinGen's Gene Curation Coalition (GenCC) database, there was a level of disagreement (14 percent) that was consistent with internal disagreement among the submitting groups.

Challenges in curating and interpreting gene datasets   

Genomenon, in collaboration with The Broad Institute and the INADcure Foundation, developed new estimates of the global prevalence of Phospholipase A2 group VI (PLA2G6)-associated neurodegeneration. The study used a literature-based approach that gathered variants through Genomenon’s Mastermind Search Companion and variant databases. 

The estimates revealed a significant underdiagnosis of PLA2G6-associated neurodegeneration as well as a higher carrier frequency of PLA2G6 variants in African and Asian populations. 

The company also presented a poster describing the use of homologous annotation to interpret variants in CALM1, CALM2, and CALM3 genes. These genes encode an identical calmodulin protein, are located on different chromosomes, and are associated with severe calmodulinopathies. The presence of disease-causing genes with homologous counterparts compounds the challenges with variant interpretation, evidence curation, and diagnostic interpretation. 

Curation of the CALM variant dataset using homologous annotation enabled the reconciliation of variant annotations across the three genes. The study demonstrated that there is only a 27 percent match of genetic variants listed in current databases and those found in the literature. This indicates that if there isn’t 100 percent coverage of the three genes, a variant in one gene that is not present in another poses the risk of a missed diagnosis. 

- This press release was originally published on the Genomenon, Inc., website