Strategies to Uplift Novel Mendelian Gene Discovery for Improved Clinical Outcomes

Abstract

Rare genetic disorders, while individually rare, are collectively common. They represent some of the most severe disorders affecting patients worldwide with significant morbidity and mortality. Over the last decade, advances in genomic methods have significantly uplifted diagnostic rates for patients and facilitated novel and targeted therapies. However, many patients with rare genetic disorders still remain undiagnosed as the genetic etiology of only a proportion of Mendelian conditions has been discovered to date. This article explores existing strategies to identify novel Mendelian genes and how these discoveries impact clinical care and therapeutics. We discuss the importance of data sharing, phenotype-driven approaches, patient-led approaches, utilization of large-scale genomic sequencing projects, constraint-based methods, integration of multi-omics data, and gene-to-patient methods. We further consider the health economic advantages of novel gene discovery and speculate on potential future methods for improved clinical outcomes.

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

“…Our laboratory submits to GeneMatcher if the existing knowledge of the gene function is consistent with the proband's reported clinical presentation and there is compelling evidence for the variant pathogenicity. This process selects for high‐confidence, potentially disease‐causing variants representing the strongest candidates and is consistent with the “gene‐to‐patient” model proposed by Seaby et al (2021), to reduce the burden of sifting through large volumes of unvetted variants (“analytical noise”). The resulting connections ideally lead to peer‐reviewed publications and sufficient evidence to confirm new gene–disease associations (Figure 1).…”

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

“…Genes that meet reporting criteria for our uncharacterized genes are entered into GeneMatcher on a rolling basis. This process allows us to enter high-confidence, potentially disease-causing variants representing the strongest candidates and is consistent with the "gene-to-patient" model proposed by Seaby et al (2021) to reduce the burden of sifting through large volumes of unvetted variants ("analytical noise"). A thoughtful approach to identifying what variants are the most likely to be disease-causing in a proband is needed before submitting to GeneMatcher to ensure the highest positive outcomes to matches.…”

“…This creates a more meaningful contribution to data-sharing compared to automated 'data dumping' practices where every rare variant in an uncharacterized gene is entered. Broad data deposits without evaluating the potential clinical relevance can create analytical noise and superfluous communications (Seaby, 2021). Follow-up communications to screen matches are laborious, so contributors to GeneMatcher should have standardized methods to appropriately vet candidate genes before submitting.…”

A gene-to-patient approach uplifts novel disease gene discovery and identifies 18 putative novel disease genes

“…1 Making molecular genetic diagnoses is hugely important to patients and their families and can pave the way for therapeutic options, cascade testing, and family planning. 2 However, most patients with rare diseases (up to 70% depending on clinical specialty) lack a definitive, molecular diagnosis. 3 Clinical genetic testing often involves application of a gene panel either as the ordered test or by the analysis strategy applied to exome and genome sequencing.…”