Exclusive: Navigenics Co-Founder on Consumer Genomics (Part II)



In Part II of Bio-IT World Editor-in-Chief Kevin Davies' exclusive interview with Dietrich Stephan, the co-founder and chief science officer of Navigenics discusses the kinds of genotyping information the company will furnish when it launches its service to the public next year, the promise of full-genome sequencing, and the inevitable comparisons with 23andMe. Part I of the interview is here.

PART II

KD: You're going to launch by offering a comprehensive SNP (single-nucleotide polymorphism) analysis. Will a full-genome sequence tell you that much more than a SNP chip?

Stephan: The worldwide health burden is caused by a handful of diseases. Heart disease, diabetes, obesity, prostate cancer, multiple sclerosis - all things we or our families are going to get - probably account for 90 percent of the disease burden in the human species. Less than 10 percent of diseases are very rare Mendelian mutations identified over the last 15 years. So from that perspective -- and if you believe those common diseases are predominantly caused by common variants floating around in the population -- and the association studies published to date support that assumption -- then you can get most of the information you want out of high-density SNP scans. We'll be doing one million polymorphisms, and using linkage disequilibrium and communicate on those common risk factors.

If you look at it that way, whole-genome sequencing might only provide [another] 10 percent. For example, we currently think autism is caused by private or rare mutations and we haven't found a whole-genome association signal to date. So autism might be teased out using a sequencing strategy rather than a genotyping strategy. On a practical level, the biggest bang for the buck is to use a one-million SNP array, capture the common variants, then slowly layer in more and more density.


KD: What have you learned from other direct-to-consumer genetic services, including the IBM Genographic Project?

Stephan: We've learned a lot from all those companies. For example, we've learned from the National [Geographic] Genographic Project that over 500,000 people have bought [the $99 kit], are interested in a genealogy strategy, and are not uncomfortable sending their DNA through the mail. It's also been valuable learning that the direct-to-consumer approach can work if privacy and anonymity are maintained. We've learned from DNA Direct that people are comfortable using a telephone [counseling] approach. That was valuable.

From some others, we've learned that if you can't maintain the highest-quality standards, people will quickly ferret that out and it's going to hurt the field. So from Day 1, we're making sure that every nuance of this operation is perfect. We've seen congressional hearings, FDA guidances, and we're following all those paths.

KD: Many people are interested in how Navigenics will compare to 23andMe.

Stephan: I've spent time talking to [23andMe co-founders] Anne [Wojcicki] and Linda [Avey] and, as I understand it, we're very complementary. Navigenics is focused squarely on medical risk assessment on actionable conditions. As I understand what they are doing, 23andMe is focused on ancestry genealogy, and that's going to be their space.

For example, we're calculating all ancestry in the background, so we can give ancestry-specific risk assessments -- but that won't be visible to the person -- just so we can refine risks. We don't want to dilute what we do best, by doing these offshoots.

KD: There's been a surge of whole-genome mapping papers in top journals this year. Are we close to really being able to gauge the risk factors for common diseases by surveying SNPs?

Stephan: What we've built in-house is a team of expert geneticists, epidemiologists, statisticians, computational biologists, and bioinformatics folks who vet every paper published in the world and try to understand whether that paper is real or not. Was the study appropriately powered? Was the case-control cohort correctly phenotyped? Or were they appropriately matched? Was the technology robust? Were the algorithms of the correct generation? Were the effects in the same direction with the same allele across multiple replication cohorts?

For example, and with no disrespect to the Wellcome Trust folks, whom we applaud for making their data available [2007 Nature paper identifying genes for seven common diseases], but their strongest association in bipolar disease did not make it through our quality control criteria. When we looked at the distribution of AAs, ABs and BBs of the associated SNP in their study population, we saw overlap in those clusters and [conclude] the association may have been a false positive. Because of that possibility, it won't be on the Navigenics menu. We really feel like a lot of this stuff is being pumped through peer review with little critical evaluation of how it was done.

KD: I presume you've volunteered your own DNA for genotyping to test the service?

Stephan: No one who's taken it is frightened or scared when they get their results back. It's all probabilistic -- just like a cholesterol test. People have an intuitive [understanding of] testing and they're not scared. One thing that was insightful to me was just how high the average lifetime risk for some diseases is. The average lifetime risk for Type 2 diabetes is 30 percent.
[In my case] for example, great news! I don't carry an ApoE4 allele. That has major implications on my stress levels and how I live my life going forward. I don't have to focus on implementing the promising prevention therapies coming online. I also learned that -- my mom died of breast cancer... for common [gene] variants, I'm loaded over the general population so that might at some point [encourage me] to get a checkup...

We have 20 conditions we're launching with -- I found I was average loaded for obesity... this is a validator to me, I'm in the average ballpark for body mass index. I'm below average for Type 2 diabetes.

KD: How will you communicate these genotyping results to the public?

Stephan: We'll have a very intuitive dashboard to provide you with an intuitive sense of what you should be focusing on in terms of managing your health proactively. It will encompass lots of information, supported in specific ways, taking into account average lifetime risk, how you're loaded relative to the general population, age of onset, a number of different nuances... Another aspect is that because we'll have the whole genome captured in a [high-density] way, we can update you with respect to predispositions to that disorder as they are published.

KD: How will you safeguard privacy of people's genetic data?

Stephan: Our position is that your genome belongs to you and you alone. We'll deliver the information directly to the person... and have strategies in place as to how the person should talk to their physician. There'll be printable materials to take into their physician. Clearly, GINA (the Genetic Information Nondiscrimination Act of 2007) plays a big role, and since it passed in the House, and the President said twice he'd sign it, we believe GINA is going to pass before the end of the summer... But our position is that GINA is critical, privacy is critical, and consumers who get this information need to be advised.

Subscribe to Bio-IT World magazine.

Click here to login and leave a comment.  

0 Comments

Add Comment

Text Only 2000 character limit

Page 1 of 1



White Papers & Special Reports

sgi whp 2
Managing the Modern Genomics Data Flood
Sponsored by SGI

Managing and storing the perfect storm of multi-disciplined data pouring from next generation sequencers and other omics instruments is a central challenge in life sciences. Discover in this paper how the SGI ArcFiniti storage solution, optimized for unstructured genomics and life sciences data can: 

  • Reduce costs, proactively protect data integrity, and deliver the high performance I/O required for genomics data processing and analysis.  
  • Effectively manage capacities from 156TB to 1.4PB as a disk based, integrated hardware and software platform 


sgi - whp 1
Turning Genomics Data into Practical Insight
Sponsored by SGI

With worldwide sequencing capacity approaching 13 quadrillion DNA bases annually turning genomics data into knowledge is a true computational challenge. Read this paper and learn how the SGI UV coherent shared memory platform can:  

  • Speed results time while cost competitively tackling the most difficult computational problems across all omics disciplines. 
  • Push performance by scaling to extraordinary levels, up to 256 sockets (2,560 cores, 4,096 threads) per single system (one OS image). 

Provide support for up to 16TB of coherent shared memory in a single system image enabling extreme efficiency across a wide range of compute demands. 



accerlys-logo_2012_wh
New Complimentary Market Survey…
Collaborations and Communications Within Drug Discovery Research
Sponsored by Accelrys
This survey was conducted by the Cambridge Healthtech Media Group in January, 2012. It was sponsored by Accelrys related to their HEOS initiative to gather valid information around externalizing collaborative research while improving communications in the cloud. With 310 qualified industry respondents the survey findings reveal useful usage and trends patterns.  An insightful follow-on discussion and webinar related to this survey, and the HEOS by Scynexis SaaS portal is also available on the Bio-IT World website for complementary viewing.
 


Job Openings

tessella logo 
Scientific Software Engineer
Boston MA
$70,000 to $95,000
 
Apply at http://jobs.tessella.com   

oxford nanopore logo 


Early Access Collaborations ManagersClick here to find out more and apply   

Oxford Nanopore's GridION technology, VP, Sales and Marketing Click to  Apply  

For reprints and/or copyright permission, please contact  Tim McLucas, (781) 972-1342, tmclucas@healthtech.com .