How to Build a Smarter Panel

At Ambry, we offer many different options for genetic testing, sometimes more than one for the same disease, which we call “panels”. Ambry’s multi-gene testing panels are comprised of genes that have a threshold of evidence between a gene and the disorder for which a patient is being tested.  These panels are made up of genes that are known to be associated with a genetic disorder.  Patients suspected of a genetic disorder are then tested to see if we find a mutation, or pathogenic change in their DNA, in one of the genes on our test panel.   The diagnosis of a genetic disorder in a patient can inform appropriate next steps in the patient’s treatment and surveillance.  These results further empower other family members that may also be at risk for the same genetic condition. We put a lot of work into making sure that every panel at Ambry provides both the doctor and their patient with clear, actionable results that lead to a diagnosis.

In order to insure we provide panels with the most well characterized genes with known genetic conditions, we meticulously review the literature for evidence of gene-disease association and use an in-house scoring system to classify a gene as “characterized” or “uncharacterized”. Ambry’s smartly curated panels focus our tests on genes that have the best chance to return clinically relevant information, which we refer to as “gene classification or clinical validity”.

So, how do we build these smart panels?

Find all the genes

After deciding to build a new panel, the first thing the gene classification team does is cast a very wide net for genes that may be responsible for a disease, generating a list of typically 100’s of genes that other researchers have studied and published on in peer-reviewed scientific journals. The next step is to look deeper into the respective publications on the genes and ask some questions such as “Do we believe there are mutations responsible for this disease in a given gene?” or “Are there other support lines of evidence such as functional studies to correlate with the clinical findings?”

Score every gene

After gathering the evidence, the gene classification team summarizes all findings, and looks at individual genes according to Ambry’s gene classification scheme. In our gene classification scheme, sections are scored for strength of evidence; the combined score provides a final total that defines the “tier” category for the gene of  definitive, strong, moderate, limited, or weak. Genes that are characterized as strong or definitive for a condition are added to our panel offerings.  Genes that score as moderate are sometimes put on panels if the evidence appears to be moving towards strong with the provision of additional published cases. 

Read more about Ambry’s gene classification scheme

Update the genes

Ambry strives to keeps all of our panels up to date, by making sure each gene has its own review period. Every 6 months to a year, the team asks themselves, “Are there any genes with more evidence for this disorder we should add to our panel?”  or “Is there evidence that any of the genes previously added should be removed?”” Panels can get out of date, newly discovered genes can become characterized, and panels that do not reflect the latest scientific findings can quickly become obsolete.

We have found that our gene classification system works!!!  From a review of our own internal data panel data and a comparison of genes that underwent our gene classification vetting, we have found that genes that are characterized as definitive have more mutations and pathogenic alterations than genes in the lower classification tiers where less evidence between gene-disease relationship was observed.

Reduce Ambiguity

Ultimately, having smart, evidence-based gene selection for panels reduces variants of uncertain significance and ambiguity in reporting results of patients. The larger the panel, the more likely it is that one or more genes on that panel will lead to VUS. With smarter panels, Ambry can be more confident that our answer will be “yes,” or “no,” instead of “We are not sure.”



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