Diagnostic testing laboratories are valuable partners for disease gene discovery: 5‐year experience with GeneMatcher

Abstract

Although the rates of disease gene discovery have steadily increased with the expanding use of genome and exome sequencing by clinical and research laboratories, only ~16% of genes in the genome have confirmed disease associations. Here we describe our clinical laboratory's experience utilizing GeneMatcher, an online portal designed to promote disease gene discovery and data sharing. Since 2016, we submitted 246 candidates from 243 unique genes to GeneMatcher, of which 111 (45%) are now clinically characterized. Submissions meeting our candidate gene‐reporting criteria based on a scoring system using patient and molecular‐weighted evidence were significantly more likely to be characterized as of October 2021 versus genes that did not meet our clinical‐reporting criteria (p = 0.025). We reported relevant findings related to these newly characterized gene–disease associations in 477 probands. In 218 (46%) instances, we issued reclassifications after an initial negative or candidate gene (uncertain) report. We coauthored 104 publications delineating gene–disease relationships, including descriptions of new associations (60%), additional supportive evidence (13%), subsequent descriptive cohorts (23%), and phenotypic expansions (4%). Clinical laboratories are pivotal for disease gene discovery efforts and can screen phenotypes based on genotype matches, contact clinicians of relevant cases, and issue proactive reclassification reports.

Seven years since the launch of the Matchmaker Exchange: The evolution of genomic matchmaking

“…This can connect clinical laboratories to investigators capable of molecular and functional analysis, and ultimately facilitate a diagnosis for a patient. Proof of this can be found in three papers in this special issue that report on robust clinical laboratory experiences using the MME, including those from Ambry Genetics (Towne et al, 2022), GeneDx (McWalter et al, 2022) and Illumina (Taylor et al, 2022). All three laboratories use GeneMatcher for their matchmaking services; GeneDx submitted entries spanning 3507 genes, 908 (26%) of which have been validated as causal through evidence built from matchmaking; Ambry Genetics submitted cases spanning 243 unique genes with 111 (45%) now clinically characterized; Illumina has submitted 69 unique genes with 21 (30%) leading to publications or active collaborations with publication planned.…”

Considerations for reporting variants in novel candidate genes identified during clinical genomic testing

“…From this review, it was clear that evaluation of the types and strengths of evidence for novel candidate genes is just as complex, if not more so, than evaluation of evidence of variant pathogenicity. Indeed, some laboratories have developed extensive scoring and weighting systems for the evaluation of novel candidate genes, 31,34,35 while others have more streamlined criteria or lean more heavily on statistical analysis and/or internal and external matchmaking. 32,33…”

“…These are not rare occurrences: recently, a research group described matching immediately upon submission to MME to an existing cohort with phenotypic and genetic similarities for almost ~10% of their novel candidate genes 51 Finally, many large-scale clinical and hybrid clinical-research genomic testing efforts are already identifying, sharing, and reporting results in novel candidate genes and have described substantial benefits in identifying a genetic diagnosis for their patients. 28,[31][32][33]51,56 Thus we strongly encourage clinical laboratories and research programs to proactively identify, share, and report variants in novel candidate genes.…”

Integrated multi-omics for rapid rare disease diagnosis on a national scale

“…With genomic testing increasingly performed through clinical pathways, identifying gene candidates should form an integral part of diagnostic analysis. Several diagnostic laboratories have now reported their experience of systematically contributing to gene discovery 37 – 39 and while this requires additional resourcing, wider implementation will both reduce the time to gene discovery and expand the effort.…”