Genomic data sharing requires standardization of lab, clinical info

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Michael Watson, executive director of the American College of Medical Genetics and Genomics (ACMG), knows about the value of sharing laboratory and clinical genomic data in order to deliver the best possible patient care.

Watson contends that genomic data sharing is critical to advancing medical breakthroughs for the estimated 5,000 to 7,000 rare genetic diseases, each of which can vary dramatically and be caused by a multitude of different genetic changes.

“I was a laboratory director for 20 years and rare diseases are not easy,” says Watson. “No one person, no one institution, and no one state will ever have enough data to really inform them to the degree that they could be informed to improve healthcare.”

That’s the stark realization behind the new position statement that ACMG issued last week calling call for “broad sharing” of laboratory and clinical data derived from individuals who have undergone genomic testing.

“Information that underpins healthcare service delivery should be treated neither as intellectual property nor as a trade secret when other patients may benefit from the knowledge being widely available,” according to ACMG’s position statement.

Also See: Why data sharing will help advance genomic treatment

However, Watson is the first to acknowledge that translating genetic information into healthcare use is a significant challenge.

“It’s relatively straightforward to put out a position statement—implementing what you’re recommending is the hard part,” he says. “It takes lots and lots of data from people all over the country, both labs and clinics, to get the kind of information we need to help everybody improve the way they deliver care.”

ACMG’s position statement makes the case that extensive data sharing is necessary and to improve care by making available the best data possible by which:

• Key clinical attributes of the phenotype of those with genetic diseases can be described

• The qualitative strength of the association between genetic diseases and the underlying causative genes can be established

• The classification of genomic variants across the range of benign to pathogenic can be established

• Differences in variant interpretation among laboratories can be reconciled

• The appropriate classification of variants of uncertain significance can be made

• Standards used in variant classification can be improved

“Broad data sharing is going to be important,” Watson adds. “But, I think we’re still trying to figure out how we do that.”

At the same time, the ACMG notes that the “analytical challenges of migrating and integrating clinical and laboratory data across the genome are daunting.” To address these challenges, the group calls for the standardization of laboratory and clinical information to enable data compatibility as well as interoperability between systems.

“If you’re going to work out of an electronic health record system, you need that kind of consistency across labs and clinics all over the country so that the data that is put in the EHR is fully compatible with everybody else’s,” Watson says.

He points to the Precision Medicine Initiative, an effort to map the genomes of a million or more Americans and make the data available to researchers. Specifically, PMI is going to leverage EHRs to help gather data for the national research cohort, with information about the study’s volunteers that can be derived from their records in terms of medical diagnoses, lab results, and what medications they are on.

Nonetheless, standards by which labs assess genomic variant classification are also important to ultimately individualize and tailor treatments for patients, according to Watson.

“If you look at the Precision Medicine Initiative, it is predicated on being able to take information out of electronic health records,” concludes Watson. “That’s a pretty complex problem to get your arms around in the absence of underlying standards.”

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