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Emory Team Proposes Algorithm for Choosing Between Single-Gene, Panel, Exome Diagnostic Testing

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NEW YORK (GenomeWeb) – A team at Emory University has developed a testing algorithm that can help clinicians decide which type of sequencing-based molecular diagnostic test – single-gene, gene panel, or exome and genome testing – is most appropriate for their patient.

The testing algorithm is part of a review published in Genetics in Medicine last week by the Emory researchers, several of whom are affiliated with Emory Genetics Laboratory, about the pros and cons of the three types of sequencing tests. All three tests still have a place in clinical diagnostics, they wrote, although a single whole-genome sequencing test may replace them in the future when NGS technology improves and prices come down.

According to Yuan Xue, one of the authors and a director of molecular genetics at Emory Genetics Laboratory, many doctors are overwhelmed by the choice of tests afforded by next-gen sequencing and often hold misconceptions about what they can achieve.

"The most important message I want to deliver is the limitation of the technology, and why panel [testing] is still important at this time," even as more and more clinical labs start offering exome and genome testing, Xue told Clinical Sequencing News. "Next-gen sequencing is very exciting, but it cannot do everything."

For one, next-gen sequencing cannot detect all types of disease-relevant changes and needs to be complemented by other technologies to detect the whole spectrum of mutations, Xue said, such as Sanger sequencing and array CGH.

For example, most NGS technology currently cannot analyze trinucleotide repeats or epigenetic changes that are associated with certain disorders, such as Fragile X, Prader-Willi, and Angleman syndrome, and it has trouble detecting deletions and duplications with high confidence.

Exome sequencing in particular has many gaps in coverage and misses exons in a large number of genes, including those with medical relevance, so false negative results are more likely. To overcome this problem, several laboratories, including EGL, have recently started to offer so-called medical exomes that fill in gaps of coverage for at least the most clinically relevant genes, and many labs fill in gaps in NGS gene panels by Sanger sequencing.

NGS-based tests also currently require that positive results be confirmed by a secondary method, such as Sanger sequencing, although some NGS results that fulfill criteria, such as a certain level of coverage, no longer require such confirmation, Xue said.

In addition to the technical challenges associated with next-gen sequencing, the ability to interpret the test results is often limited. Testing for the greatest number of genes available is thus not always the best approach, Xue said.

For example, a number of clinical genetics labs offer gene panels for epilepsy, with the number of genes ranging from 70 to almost 400. While physicians might be tempted to order the largest panel, they need to keep in mind that many of the genes have not been proven to be disease-associated, "so if you find a sequencing variant [in those genes], you don't know how to interpret those," Xue said, and will end up with variants of unknown significance, or VUS.

The problem of VUS scales for exome and genome sequencing, she said, as an even larger number of genes is included in the analysis. "Not only is it not helpful, it can add more work, more headaches, and more confusion to the clinicians and to their patients," she said.

Another caveat with exome and genome sequencing is the possibility of incidental findings, the return of which is still controversial in the field and requires informed consent, she said, a fact that some doctors might not be aware of.

The testing algorithm developed by Xue and her colleagues is designed to help doctors choose the most appropriate test for their patient and is already in use by some clinicians. It is based on a similar scheme proposed by researchers at Duke University last year, which did not include panel testing. Xue said panels should still be available as an option, at least for the time being.

An important component of the decision process is a thorough clinical evaluation of the patient prior to testing, she said. "Sometimes you hear people say, 'maybe we just do exome sequencing − that can replace a clinical evaluation,' and that's not true," she said, adding that the clinical information is needed to interpret the sequencing results.

According to the testing algorithm, patients with distinct clinical features that point to a disease that has been associated with a single gene should receive a single-gene test, and those suspected to have a triplet repeat or epigenetic disorder should receive appropriate testing for that.

Single-gene tests are surprisingly effective: the authors noted that the Duke study showed that almost 50 percent of patients received a diagnosis from such traditional testing, most of them at their first or second visit.

Both cost and turnaround time for single-gene tests are lower than for NGS panels or exome tests − according to Xue, single-gene tests cost on the order of hundreds of dollars, whereas panels and exomes cost several thousand dollars − and the results are easier to interpret.

For patients with clinical features suggesting a disease that is associated with several genes, a gene panel should be ordered, according to the algorithm, which may be complemented by exon CNV analysis. Panels will result in fewer VUS, are less likely to deliver incidental findings, and have better coverage than exome sequencing, Xue and colleagues said in the review.

Exome or genome sequencing should be reserved for disorders with extremely high genetic heterogeneity, such as intellectual disability or autism; patients with broad clinical features that do not give clinicians a starting point; or when no panels are available, according to the algorithm.

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