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Whole Genome Sequencing Heads for Consumers – Rodrigo Martinez of Veritas Genetics

By JESSICA DaMASSA, WTF HEALTH

DNA testing companies like 23andMe and Ancestry have made DNA testing mainstream, with adoption skyrocketing among consumers. Meanwhile, health tech startups like Veritas Genetics are starting to push the trend even further – from genotyping to whole genome sequencing. What’s the difference? Well, genotyping looks at less than half of 1% of your genome, while whole genome sequencing looks at over 99% of your genome.

Veritas is betting that consumers are ready for what’s revealed by looking at more than 6.4 billion letters of DNA and are promising that the value of that information will only get richer as time goes on and the science that makes sense of our genome achieves new breakthroughs.

In fact, Veritas is positioning their $999 test as “a resource for life” and Rodrigo Martinez, their Chief Marketing & Design Officer who I chat with here, shares a vision for the future that includes asking Alexa to scan your genome before taking medications or risking allergic reactions to foods.

This is fascinating proposition for the future of health (investors are jazzed too, having poured $50M into the company), but ethical questions abound. How do you make this information useful and actionable? How do you handle situations where major health issues are reveled? And what about data privacy? This is about as personal as personal health information can get. Rodrigo weighs in…

Is Medicine a Big Data Problem?

Human beings are big data. We aren’t just 175 pounds of meat and bone. We aren’t just piles of hydrogen and carbon and oxygen.  What makes us all different is how it’s all organized and that is information.

We can no longer treat people based on simple numbers like weight, pulse, blood pressure, and temperature. What makes us different is much more complicated than that.

We’ve known for decades that we are all slightly different genetically, but now we can increasingly see those differences. The Hippocratic oath will require doctors to take this genetic variability into account.

I’m not saying there isn’t a place for hands-on medicine, empathy, psychology and moral support. But the personalized handling of each patient is becoming much more complicated.  The more data we can gather, the more each individual is different from others.

In our genome, we have approximately 3 billion base pairs in each of our trillions of cells.  We have more than 25,000 genes in that genome, sometimes called the exome.  Each gene contains instructions on how to make a useful protein.  And then there are long stretches of our genomes that regulate those protein-manufacturing genes.

In the early days, some researchers called this “junk DNA” because they didn’t know what it did.  But this was foolish because why would evolution conserve these DNA sequences between genes if they did nothing?  Now we know they too do things that make us unique.

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Stopping 23andMe Will Only Delay the Revolution Medicine Needs

Genetic testing is a powerful tool. Two years ago, with the help of my colleagues, it was this tool that helped us identify a new disease. The disease, called Ogden Syndrome, caused the death of a four-month old child named Max. But the rules and regulations for genetic testing in the US, laid down in the CLIA (Clinical Laboratory Improvement Amendments), meant I could not share the results of the family’s genetic tests with them.

Since that time, I have advocated performing all genetic testing involving humans such that results can be returned to research participants. This I believe should extend beyond research, and some private companies, like 23andMe, are helping to do just that.

For as little as US $99, people around the world can send a sample of their saliva to 23andMe to get their DNA sequenced. Their Personal Genome Service (PGS) analyses parts of a person’s genome. This data is then compared with related scientific data and 23andMe’s own database of hundreds of thousands of individuals to spot genetic markers, which the company claims “reports on 240 health condition and traits”.

Earlier this month, however, as I had feared, the US Food and Drug Administration (FDA) has ordered 23andMe to stop marketing their service. In a warning letter, FDA said: “23andMe must immediately discontinue marketing the PGS until such time as it receives FDA marketing authorisation for the device.” By calling PGS “a device”, the FDA fears that people may self-medicate based on results they receive from 23andMe.

Somehow the US and UK governments find it acceptable to store massive amounts of data about their own citizens and that of the rest of the world. They are happy spending billions on such mass surveillance. But if the same people want to spend their own money to advance genomic medicine and possibly improve their own health in the process, they want to stop them.

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How Useful Is Personal Genomics? A Case Study

How much can you help yourself by getting your genome sequenced?

A lot, a little, not at all?

Scenario 1 (big help): You discover you have a greatly elevated risk of Disease X. You do various things to reduce that risk that actually reduce it.

Scenario 2: (a little help): You discover you have a greatly elevated risk of Rare Disease X. You do various things to reduce that risk but they don’t help. At least, when Disease X starts, you will be less upset.

Scenario 3 (no help): You discover that you have a greatly elevated risk for a common easily-noticed disease (such as obesity). You already watched your weight, this changes nothing. Scenario 4 (harm): You discover that you have a greatly elevated risk of Scary Disease X (e.g., bipolar disorder). It is depressing news. Later studies show that the gene/disease association was a mistake. (Many gene/disease associations have failed to replicate.)

A recent Wired article tries to answer this question for one person: Raymond McCauley, a bioinformatics scientist who had his genome sequenced four years ago and learned he was “four or five times more likely than most people to develop age-related macular degeneration (AMD)”. The article says “of all the ailments described in the 23andme profile, AMD has one of the strongest genetic associations”. If I found this in my genetic profile, I would want to know the confidence interval of the increased risk. Is it a factor of 4.5 plus or minus 1? Or 4.5 plus or minus 8? This isn’t easy to figure out. In addition to the question of variability, there can easily be bias (= estimate is too high). Let’s say I do 100 gene/disease association studies.

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Why Getting to a Digital Health Care System Is Going to Be Harder Than We Thought Ten Years Ago

A leading scientist once claimed that, with the relevant data and a large enough computer, he could “compute the organism” – meaning completely describe its anatomy, physiology, and behavior. Another legendary researcher asserted that, following capture of the relevant data, “we will know what it is to be human.” The breathless excitement of Sydney Brenner and Walter Gilbert —voiced more than a decade ago and captured by the skeptical Harvard geneticist Richard Lewontin [1]– was sparked by the sequencing of the human genome. Its echoes can be heard in the bold promises made for digital health today.

The human genome project, while an extraordinary technological accomplishment, has not translated easily into improved medicine nor unleashed a torrent of new cures. Perhaps the most successful “genomics” company, Millennium Pharmaceuticals, achieved lasting success not by virtue of the molecular cures they organically discovered, but by the more traditional pipeline they shrewdly acquired (notably via the purchase of LeukoSite, which ultimately yielded Campath and Velcade).

The enduring lesson of the genomics frenzy was succinctly captured by Brown and Goldstein, when they observed, “a gene sequence is not a drug.”

Flash forward to today: technologists, investors, providers, and policy makers all exalt the potential of digital health [2]. Like genomics, the big idea – or leap of faith — is that through the more complete collection and analysis of data, we’ll be able to essentially “compute” healthcare – to the point, some envision, where computers will become the care providers, and doctors will at best be customer service personnel, like the attendants at PepBoys, interfacing with libraries of software driven algorithms.

A measure of humility is in order. Just as a gene sequence is not a drug, information is not a cure. Getting there will take patience, persistence, money and aligned interests. The most successful innovators in digital health will see the promise of the technology, but also accept, embrace, and ideally leverage the ambiguity of disease, the variability of patients, and the complexities of clinical care.
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