A study published online this week in the Journal of the American Medical Association suggests that there is a ways to go in generating and interpreting information from whole-genome sequences in the clinical setting.
"We need to be very honest about what we can and cannot do at this point in time," co-senior author Euan Ashley, a medicine and genetics researcher at Stanford University, said in a statement.
"It's clear that if we sequence enough cases, we can change someone's life. But with this opportunity comes the responsibility to do this right," Ashley said. "Our hope is that the identification of specific hurdles will allow researchers in this field to focus their efforts on overcoming them to make this technique clinically useful."
As part of a study on the utility and consistency, coverage, and reliability of whole-genome sequencing (WGS) in a clinical setting, he and his colleagues examined data for a dozen healthy men and women from different ethnic backgrounds who had their genomes sequenced with Illumina instruments at the Stanford University Medical Center between late 2011 and early 2012. Nine study participants were also sequenced using Complete Genomics technology.
"In this exploratory study of 12 volunteer adults, the use of WGS was associated with incomplete coverage of inherited disease genes, low reproducibility of detection of genetic variation with the highest potential clinical effects, and uncertainty about clinically reportable findings," the study's authors wrote.
"In certain cases, WGS will identify clinically actionable genetic variants warranting early medical intervention," they added. "These issues should be considered when determining the role of WGS in clinical medicine."
While the team got highly consistent results when identifying disease-related genotypes involving previously reported variants — confidently calling around 99 to 100 percent of such variants — the results were murkier for small insertions and deletions, which showed genotyping concordance just over half of the time.
The WGS approach also missed a small but significant fraction of potential risk SNPs, researchers reported. They determined that some 10 to 19 percent of genes known for contributing to inherited diseases were not adequately covered in whole-genome sequence data, though that coverage varied somewhat depending on the sequencing platform used.
"These off-the-shelf genome sequencing techniques were developed to provide generally good coverage of most of the genome," co-first author Frederick Dewey, a post-doctoral researcher in Ashley's Stanford lab, said in a statement.
"But there are some regions that remain to be covered well that we care very deeply about," he said. "We still need to supplement this information with additional sequencing in some regions to make clinically usable decisions."
The researchers used Illumina instruments to do WGS on DNA isolated from blood samples from 12 individuals, following data analysis and clinical interpretation protocols set out through the Stanford Genomic Medicine Application Pilot Project. For nine individuals, they also did Complete Genomics genome sequencing.
The data was evaluated not only by investigators but also by genetic counselors, primary care physicians, and a molecular pathologist.
The team looked for variants implicated in inherited disease, common diseases, and drug response as well as rarer mutations or structural variations using information from the ClinVar database, the Human Gene Mutation Database, and other sources.
Following such analyses, the group was left with between two to six variants per person that were deemed appropriate for further clinical testing. Those follow-up tests, recommended by physicians and medical geneticists who reviewed the data, each carried an additional price tag. For participants in the current study, those tests cost from roughly $350 up to almost $800 per person.
In 11 of the 12 genomes, for example, the team tracked down variants that are believed to influence drug response.
The analysis of the WGS data also unearthed a BRCA1 deletion in the genome of a female participant with no family history of breast or ovarian cancer. After verifying that result through follow up testing, the woman received preventative treatment to diminish her risk of developing those cancers.
Such findings are prompting enthusiasm about the clinical potential of WGS, despite the potential complications associated with applying the approach.
Even so, the study's authors noted that it remains to be seen how often such clinically actionable genetic alterations or variants are found through sequencing on individuals who are not presenting with any obvious medical conditions.
"It's not possible to predict from a study of 12 people how often this type of clinically actionable discovery will occur, but it definitely supports the use of this technology," Dewey said in a statement.
Still, he noted that it "remains significantly harder to use whole-genome sequencing for disease prediction than for disease diagnosis."
The researchers also tallied up the time associated with analyzing and interpreting each individual's WGS data, demonstrating that this can take as long as 100 hours per patient depending on the clinical question at hand. For every variant selected for follow-up, they reportedly spent roughly an hour scouring available publications and variant databases to determine its clinical relevance.
They noted that while the price of generating the necessary data has dropped dramatically in recent years, that time investment by clinicians, researchers, and/or genetic counselors could significantly ratchet up the cost of using WGS in the clinic.
In the current study, for example, the team estimated that the price of sequencing each person's genome and scrutinizing variants with potential clinical significance came in at around $15,000, on average, without accounting for infrastructure and data storage costs.
The data also prompted the study's authors to reclassify dozens of suspected disease contributors in variant databases from disease-causative variants to variants conferring less significant disease risk or variants of unknown significance. Several other causative mutations were reclassified to being "very likely pathogenic," they noted.
Findings from the study are expected to inform future efforts to apply WGS in a personalized medicine setting for those interested in using individuals' genetic data to diagnose disease, target therapy, predict treatment outcomes, and so on.
For their part, the Stanford team plans to apply the information to its GenePool effort — a growing collection of WGS data on healthy individuals that's aimed at understanding and applying genomics in the clinic.
"Our intention in doing this analysis was to draw a line describing where we are with this technology at this point in time and identify how best to move forward," Ashley said, noting that WGS "has the power to be absolutely transformative in the clinic."
In an accompanying editorial in JAMA, the Maine Dartmouth Family Medicine Residency's William Gregory Feero discussed findings from the study and their implications for the clinical WGS field.
He noted that the "[m]edical application of genomic and personalized medicine technologies hold out the real promise of improved decision making and patient outcomes by providing an increased knowledge of the determinants of health and disease at the level of the individual patient."
"A question facing potential early adopters of genome sequencing as an adjunct to patient care is whether or not having WGS data, at this time, will decrease uncertainty and improve outcomes or merely exponentially increase the complexity of clinical care," Feero concluded.