Heidi Rehm has been using disease-targeted gene panels to diagnose patients in her clinical molecular genetics practice for a decade. Having adopted next-generation sequencing approaches two years ago, and whole-genome and whole-exome sequencing for some patients in the past year, she is a pioneer in applying genomics in the clinic.

Rehm, who is chief laboratory director of the molecular medicine lab at the Partners HealthCare Center for Personalized Genetic Medicine and an assistant professor at Harvard Medical School, will present her experiences at the Genomics in Medicine Symposium at the Molecular Med conference in San Francisco on February 12. She recently spoke to NYGC contributor Christie Rizk.

How have genetic and genomic sequencing technologies helped you improve patient outcomes?

The biggest area of testing we do today is for cardiomyopathy. It's a dominant disorder, so first-degree relatives are all at risk, and it's adult onset so they don't know if they are at risk or not. We do testing that will allow them to know whether they are or aren't at risk, and may determine the placement of the intra-cardiac device that can save their lives. Sometimes [testing] determines specific treatment approaches for the [affected person]. One gene allows for enzyme replacement therapy, so patients have gotten on that because of certain results.

In the field of hearing loss, there are different forms of hearing loss — some are syndromic, others are not. Our patients who are finding out they're at risk for eye disease associated with their hearing loss are getting early treatment for that and changing how they manage the hearing loss.

Another big area for us is cancer treatment, particularly lung cancer, and tests that dictate whether chemotherapy or tyrosine kinase inhibitors are most appropriate.

What's an example of genomic data having informed a medical decision?

The first whole-genome case we did was a family with five children with hearing loss. We first took a targeted approach, [testing] 19 genes causative for hearing loss. That was negative. Then we went to whole-genome. We initially didn't find the cause. We then ran a new expanded panel for hearing loss and identified a huge deletion—the cause of their hearing loss.

We found that the cause of that hearing loss was also associated with infertility. There's a known intervention for dealing with the infertility, so we were also able to return that result to the family and that will come in handy clinically as those individuals go on to have a family.

As far as disease-targeted testing, there's a disease that mimics the cardiac presentation of cardiomyopathy called Fabry disease. Fabry disease involves effects on the heart as well as renal impact and neurosensory issues, but some patients can have only the cardiac effects and it can present like hypertrophic cardiomyopathy. We added the gene for this disease into our hypertrophic panel and about 2 percent of patients turn out positive. That's the one gene for which there's enzyme replacement therapy. A number of cases now have been found to have this Fabry disease gene mutation and they've been able to be put on enzyme replacement therapy that has slowed and even regressed their disease.

Is the turnaround time on whole-genome sequencing analysis fast enough that results can be returned in time to make treatment decisions?

That's still a point for improvement. With the release of the [Illumina] HiSeq 2500 and other sequencers, the turnaround time for sequencing is getting quicker. But there are a number of steps in the process—sample prep, time on the sequencer, Sanger confirmation, interpretation, alignment, and variant calling. Even the computational steps can sometimes take a week. There have been examples where within 72 hours a result was rendered using the HiSeq 2500 to rapidly analyze a genome. But today most exome sequencing is turned around in three to six months, even though theoretically it can be achieved faster.

The speed of computational analyses and algorithms will get faster, and the instruments are already getting faster. The need to develop confirmation assays will diminish, so the interpretive process will get quicker, and there are a lot of pieces of the process that are all on their own path to improved efficiency.

Are the costs still prohibitively high for patients to do this testing on a regular basis? Or are insurance companies paying?

It varies, but people are having success getting insurance to pay for it. One of the things they're showing is that [with the approach that says], "Well, I'm going to start with that test, and if it's negative I'm going to go to that test, and if it's negative I'm going to go to that test, and so on," you'll pay $50,000. Or you could order a whole-exome or whole-genome and pay $9,000. So we're already seeing the rationale for how this can be more cost-effective than disease-targeted testing for some disorders.

If a healthy person wanted to make whole-genome testing a part of their preventive healthcare, would the insurance companies pay for that?

It's very unlikely, even in cases where it's so obvious that it would save that patient money. For example, in cardiomyopathy, [when] we test the proband and we find a mutation, according to clinical guidelines all the family members who are 50 percent at risk need to be screened with an echocardiogram and an EKG once a year. You're talking over $1,000 cost to them. And [the insurance companies] won't pay for a $400 test that has a 50 percent chance of saying there's no need to do that [more expensive testing] in a year. There are these broad policies about not covering tests in healthy individuals that they need to rethink.

In the accountable care era, the health institutions are getting a set amount per patient, not getting paid per test. Physicians really have to think strategically about what is in the best interest of the patient as well as what's most cost-effective. So the paradigm is changing. Hopefully the insurers will learn this, but in the movement toward accountable care, I think the physicians will be driving this as well.

What else is standing in the way of genetic sequencing and genomic technology being put to widespread use in the clinic?

Once we get genome analysis down to below $500, it's really going to be a no-brainer—you no longer have to make an argument over whether this is cost effective because, spread across a patient's lifetime, there's not doubt that spending $500 or $1,000 or even more than that, will be cost-effective.

One of the weaknesses of genomic sequencing now is that there are so many genetic variants we don’t understand, and we need incredibly large datasets to be able to understand them. The only way we're going to be able to get these large datasets is if everybody gets sequenced, and ideally sequenced with connection to their electronic health records so that we gather these structured and informative phenotypes on an ongoing basis for millions of individuals.

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Christie Rizk is a reporter and editor based in New York. She is a regular contributor to the New York Genome Center, and her work has appeared in Genome Technology magazine, Techonomy, Reuters, and The Brooklyn Paper.