Genomic Medicine and Family History

Increased attention is being paid to the predictive power of family health history, in terms of its value relative to cost, the quality of data standards being developed, and a sense that this information is as valuable to people as it is to doctors. The speed at which we've been able to translate genomic discovery into pragmatic interventions is being hotly debated due to the 10th anniversary of the completion of the draft human genome. Both the mainstream press (the New York Times, Wired, the Economist, and Good Morning America) and scientific journals (New England Journal of Medicine pieces by Collins and Varmus) have discussed the current dearth of new treatments based on genomic discoveries and the limited use of genetic factors in predicting disease risk. However, some things are clear to us at 5AM:

• we are discovering more about how genes relate to disease
• we are able to produce volumes of data dramatically faster and cheaper than even wildly imagined 10 years ago
• we are not equipped to understand, interpret and apply knowledge from the data explosion as effectively as we would like.

Prominent among the discussions is that there is something tangible and intuitive to most people (especially those without advanced scientific degrees, like me) - one's family history is a factor in what will happen to us and our progeny. Evidence is being delivered regularly (JAMA and NEJM) that supports self-reported family history as a more reliable method for classifying risk expectations than the evidence being generated by genome wide association studies. Dr. Collins reports that it is "the cheapest genetic test" on the market today in his book, "The DNA of Life," and is generally useful, even promoting the use of the Surgeon General's tool that we developed. While Nicholas Wade in the NY Times indicated that family history is old-fashioned to support his assertion that genomic progress has been too slow, we'd contend that it's a component to inform clinicians, researchers, and the general public today. Even when (if?) genetic factors become more useful, family health history should always be taken into account and be made part of the equation.

5AM's mission is to make the web the place where life science professionals work and succeed (and exposing failed ideas as fast as possible counts!). We have tackled issues such as those suggested by the lack of quality of biospecimens or associated clinical data (see Wired's Libraries of the Flesh), bringing together geographically disparate, multi-disciplinary teams and companies around a common problem (supporting the Ivy Genomic Based Medicine effort from a workflow as well as computational perspective), and making the data academics are creating readily sharable. Of all the challenges in the life sciences, there is not one root cause and no single company, agency, or institution that will be able to "solve it."

What seems incredibly clear to us, and we don't think we're alone, is that tackling small pieces of the problem can be more valuable, and deliver results more quickly, than waiting for the revolution to take over. Incremental change that brings education, information, and technology into the hands of clinicians and researchers and the people and patients they serve, is worthwhile. Improving human health will be a long journey, but we look forward to joining with our colleagues and partners in making incremental and effective steps forward. Making a more informed choice today than yesterday is the value we seek to deliver.

A couple reasons why

As a person who lives with a chronic disease, I (selfishly) feel especially close to and compelled by the work we do at 5AM. In theory, I want to do everything I can to help the really brilliant people out there who are seeking to cure disease, find better treatments, simplify, share, find, help, fund...make human health better. I want our technologies to help facilitate greatness. In practice, our work can still feel pretty removed from helping people, let alone improving health – when you’re working on a service to support ISO 21090 data types in HL7 messaging, it takes deliberation to recall that that service will be used by a researcher seeking answers in the massive amount of public data that’s out there in the world.

In dark moments, when I feel like a pincushion and consider my doctors vampires, that remove feels too vast – I (selfishly) want to be in there, I want to be doing something now to find a cure, relieve suffering, fix it. But I’m a software geek, not a scientist. So I remember that there’s a great need for technology in all of this. That’s why we founded 5AM – because we created research software for a hospital (it’s still in use today), using our software expertise to help the researchers more effectively manage their research, and better see the information in their data. It was amazingly simple – there was a need! – we could help! – and that’s still the case today. And will be the case for a long time, really, until our collective work is done.

Below are some of my go-to feel-good reminders of why we do the work we do. What’s so great about life science technology? What’s so great about science software? What’s so great about Health IT? Here are some reasons we work in this field…

• Because sharing information increases knowledge, and everyone is starting to get it - witness The Community Health Data Initiative and so many other such efforts.
• Because crowdsourcing has value, and people are willing to share deeply personal information to get answers - as in Patients Like Me.
• Because the HeLA cells are explored in mainstream media (Smithsonian and RadioLab, at least....).
• Because the Personal Genome Project pushes the idea of the personal and the value of the genome to a new extreme.
• Because the dream/hope/idea of personalized medicine continues to diffuse (in the media and collaboratives).
• Because doctors and patients distill the meaning of "healthIT" to its essence. And blog about it! (Dr. Val et al, Dr. Halamka....)
• Personal gene sequencing? $1000. Home-made PCR? Priceless.
• Because dancing people make us smile.
• Because genetic sequencing is so accepted, we’ll use it to determine dog-poop violators.

Your turn....

Constant Improvement Rewarded - 2010 Great Place to Work

I was fortunate to be able to represent 5AM today at the Washington Business Journal's Great Place to Work event. As a technology company focused on making the web the place where life science professional work and succeed, we, like all the great companies present, are dependent on our people to "dream the dreams" and, in our case, build them. Software for Life is our mantra, and we thank our teams for making 5AM thrive. The award was based on a survey of employees and while anonymous, one quote was pulled out and I'll share a snippet "...I've never worked anywhere that follows through on so many promises." We look forward to continuing that tradition and have great needs for building our engineering teams. Please join us!

My 23andMe Results - Part I

I got my 23andMe results about 3 weeks ago. I had been waffling for a while about whether to get this done, but the $299 sale (after Henry Louis Gates plugged it on Oprah) for both the Ancestry and Health Editions got me to sign up. Little did I know that several weeks later it would be on sale for $99 for DNA Day!

I'm reasonably healthy but have a few nagging issues that I thought the test might shed some light on. However, I am well aware that these results generally assess risk of disease and do not directly diagnose it. Still, the general idea is attractive and I like the idea of being able to learn something about myself and share that information with my family. By writing this blog I am clearly veering into the area of sharing some of that information with you, too. But I am still weighing the options about how much I plan to reveal publicly. That's going to be part of the fun in writing this series of blog entries.

If you get the combined Ancestry/Health tests then, obviously, you get two kinds of results. I'll address the ancestry results in a separate post, but it essentially uses Y chromosome information to track paternal ancestry and mitochondrial DNA information to track maternal ancestry. I'll have to admit right now that I don't know much about genealogy and this kind of ancestral genomics, but we can learn together, right?

I reviewed my Health results and found some interesting stuff which really drove home what kind of information you can (or cannot) get from these kinds of genetics tests. For some conditions, 23andMe has what it calls 'Established Research Reports'. These reports give you a risk assessment for how likely you are to get a particular condition in your lifetime, based on your genotype. This can then be compared to the average risk across the general population.

For instance, for Crohn's disease, I have an 85 out of 10,000 chance of getting the disease in my lifetime, compared with an average risk of 53 in 10,000. It then tells me that the heritability of Crohn's disease is 50-60%, which means that about half of contributions to risk comes from genetic factors and half comes from environmental or other factors. Lastly, it shows the individual genetic variations (SNPs, or single nucleotide polymorphisms) that contributed to my risk, as in the image below:

You can see from this that there are 12 SNPs that they include in their Crohn's disease risk calculation. The ones in red are ones for which I have a so-called risk allele, and the ones in green are where I don't. Each of the alleles I have for each of those SNPs contributes to the overall risk for me. They do this based on scientific studies that look at the prevalence of these alleles in populations of people with and without Crohn's disease.

So this example is, in the end, pretty uninteresting. My risk is slightly greater than average, but still small. I know a little about Crohn's disease and if I started having those kinds of symptoms I'd go to my doctor to get looked at. But I'd have done that regardless of whether I'd seen these 23andMe results. I don't think there's anything I can do about this result except shrug and say "that's interesting."

I'll probably show some more of these kinds of results. But in general, most of my results looked like this, in that the differences between my risk and the average risk were relatively modest.

23andMe also has 'Preliminary Research Reports' which give you some information about diseases that are less well studied. Most of these results were also interesting but not dramatically so. I'll show some of these in future posts, too.

Lastly, after mulling this over for a bit, I thought I'd try an experiment. There's been a lot of blog-talk about whether people are ready for direct access to their genetic information or whether this data should be regulated and be reviewed with a physician or genetic counselor. In general, I support an individual's right to access this kind of information. But I also agree that the results can be complicated and confusing and that I might well benefit from an expert's opinion.

So I called my primary care physician's office and told the appointment-taker I wanted to discuss my 23andMe results with my doctor. She said 'ok' and scheduled an appointment for next week. It's not totally clear whether she even knew what 23andMe was, however. I'm pretty sure that when a person making appointments at a doctor's office asks why you want to see the doctor that they really just want to know whether (a) you have something where you should be seen in the next day or so, or whether (b) you can wait til next week. Since I didn't say I had a fever or was throwing up, she picked (b).

Now I have no idea how much my doctor knows about genetics or whether he's ever heard of 23andMe. And I don't know how he'll respond when I tell him I'm writing a blog about this experience. I'll post more after that appointment and after I have more time to go over my results. Thanks for reading!

Walgreen's, Pathway Genomics, FDA, and the Media: Fail?

No doubt anybody reading this is aware of the announcement yesterday that Pathway Genomics plans to sell their direct-to-consumer genetic health/ancestry test in Walgreen's pharmacies across the U.S. Well, that was yesterday. Today I opened the newspaper to find that they are canceling that plan, at least for now, because of objections from the FDA.

The Genomics Law Report has had several detailed blog posts in the last couple of days that cover all sorts of angles on this, and it's excellent commentary, as always.

I find this development ridiculous. I think the news media has overlooked the fact that this test was already available for purchase over the internet with apparent tacit acceptance from the FDA, and that similar tests from 23andMe and Navigenics, among others, have been available for years. That's right, since 2007! In addition, the Pathway test from Walgreen's delivers its results on the internet regardless of how you bought the kit in the first place, in much the same way 23andMe and Navigenics are doing already.

It's probably true that this move would have made this kind of test available to some people who might not have known about it before. But it was already widely available using the same internet storefront technology that Amazon.com and others use ubiquitously. Does the FDA worry that people who shop at Walgreen's are somehow less able to deal with these results than people who shop on the internet? Or are they worried that they have fiddled around on what to do about direct-to-consumer genetics tests and this announcement was obvious evidence of that?

What is this, the suede denim secret police, with all the liberal/fascist illogic that implies? Personally, I would like to see some leadership from Francis Collins, and his ultimate boss, Barack Obama, on this. Both are supposed proponents of freedom of information and openness in research and government. If they, and the leadership of the department of Health and Human Services, don't provide some guidance on this I'll consider it a real failure

It's true that these tests are starting to provide medical information and clearly should be regulated in some way to keep out the scam artists and charlatans. But I have a real suspicion of any argument that keeps people from knowing something about their own body and genetic makeup, especially when it seems to be done in a haphazard and ad-hoc manner.

This is not personalized medicine

Remarks by our CEO, Brent Gendleman, when he introduced a personalized medicine session at today's BIO-IT World Expo...

"10 fingers, 10 toes, that's all that used to matter. Not now. Now, only seconds old, the exact time and cause of my death was already known."

This is from a scene in the great film "Gattaca," which details the narrator's birth. A needle-pick in his heel yields blood for a genetic test, and the results appear instantly in a printout. While the mother cuddles the newborn, a nurse seriously reads out his fate: "Neurological condition, 60% probability. Manic depression, 42% probability. Attention defecit disorder, 89% probability. Heart disease..." (a serious look) "99% probability. Early fatal potential. Life expectancy: 30.2 years."

This is not personalized medicine.

When I think about personalized medicine, these important genetic tests are a key component. They provide my doctor with the ability to know me, and to know people like me. This helps us understand how my behavior impacts my health, and to identify the best medicines for me, and the medicines I should stay away from.

When I think about personalized medicine, I think about my doctor and me being able to take my information and share it with the research community – to serve research, me, and people like me.

Personalized medicine is not only about breaking down the silos we’ve been talking about today – between and among bioinformatics and standards and interoperability and health-it and massive data and researchers and clinicians. It’s about making our work personal.

You know, most of us do incredible work in our silos, and we know that one day we’ll be able to let information flow through from one “track” to another. We work with so many fabulous people at the NCI, developing solutions to help cure cancer. One of our partners, a researcher for whom we’re providing research software, was reporting his results to his contract officer. The contract officer asked if he was meeting his deadlines and deliverables, and he replied “No, we’re not on schedule. We’re trying to lengthen the survival curve for these people.” He said the contract officer was silent, and replied, “I’m sorry. You know, sometimes I forget that what we’re doing can have that kind of impact.”

Personalized medicine is about establishing a cohesive community, where we learn from each other, we take advantage of our respective strengths, to make informed choices and take care of people.

Scrummy Science: Benefits of the Agile Model

In case you hadn’t picked up on this already, 5AM is an Agile shop. Take a quick glance at our Glassbox Software Development Process and you’ll see the unmistakable scrum methodology featured prominently on the top of our development process diagram. Although Agile-Scrum is now a well-established process in software development, those of us coming from a science/bioinformatics background are not as familiar with the concept. Another thing we believe in here at 5AM is that bringing good science and good engineering together is better than the sum of the parts – the two complement and enable one another. It’s this belief and our commitment to Agile development that led us to ask ourselves, “can our science projects benefit from following an Agile model?” That’s the experiment we’re pursuing now and this is a bit of our story so far.

The first step in the process has been to train almost all of us bioinformatics types in the basics of Scrum. Since it’s not a package in R and has never appeared in an episode of Battlestar Galactica – most of us knew very little about it. I myself took Scrum Master training here in the Bay Area. As exotic as the title “Scrum Master” sounds, I was disappointed to find the training did not involve breaking boards or making a pilgrimage to an ancient monastery in the Himalayas. What it did involve was passing little red balls around as efficiently as possible, measuring the “points” value of everything on my desk and ranking countries by how “fun” they are. To the uninitiated, this might all seem a bit crazy, but the activities were showing us the core elements of Scrum – how to work effectively as a team, how to measure progress and stay agile. Thanks to Lyssa Adkins for leading a great workshop.

Now back in the real world of juggling p-values rather than rubber balls, we have started to map the day to day efforts of our science projects to an Agile process. Some parts fit really well – in fact, they’re things we were doing already. Scrum’s short iterations with a focus on delivering “working software” at the end of each sprint is analogous to the iterative approach that our bioinformatics team takes towards data analysis and other projects in which we frequently share results and calibrate next steps with our clients. Scrum makes this more formal, but it’s easy to imagine tweaking what we do now to fit Scrum. The Scrum roles are also fairly familiar. Typically we have a primary investigator or business development professional (for us, this person is usually a client) who plays the role of Product Owner. Our teams also tend to be small, cross-functional and everyone pulls their own weight – values shared by Scrum.

Other aspects of Scrum are things we don’t do, but probably should. The Product and Sprint Backlogs are prioritized lists of tasks that need to be completed to produce the “product”. We usually have something like this in our science projects, but the prioritization piece is sometimes missing. I think back on all the times that each data analysis led to “just one more” interesting question to answer which drove us on a depth-first search to nowhere. A process that forces you to prioritize every new task and periodically review the list as a whole is a road map towards common sense. Scrum’s focus on measuring progress through points and visualizing progress through Burndown Charts is new, but again, not a bad idea. It might be a challenge to turn open-ended undertakings like “research oligo design tools” into quantifiable tasks, but I’m fairly confident it can be done – and it will be an improvement. And just as important as making tasks measurable is identifying when they’re “done”. This often goes unappreciated in our science projects, but Scrum forces us to address it.

So far, so good - maybe Agile science isn’t such a stretch after all! But before suffering from “premature exubaration” (as my sometimes off-color former boss liked to say), there are a few elements of Scrum that we still haven’t quite figured out. First, there’s the strict timeboxing of tasks. In Scrum, once the team has agreed to what they’re going to accomplish in an iteration, the team is expected to stick to this commitment and deliver. A typical iteration time is two weeks. How many science projects have I been on where priorities and tasks completely change in just days, let alone weeks? What’s the solution: shorter iterations, more discipline/more thoughtful tasks or get rid of the timeboxing altogether? Another issue we run into is the allocation of our team members. Often our team is made up of sub-contractors or 5AM employees who have only a fairly small commitment to the project – say at the 25% level. Can team members truly participate in Scrum with so little time available for the project?

So, our consensus opinion right now is Agile science has promise, but there are still some pieces we need to figure out. Like most things in life, proof will be in the execution. We’ll only really know how well Scrum works for us after using it on a few projects. We will periodically update you on our progress and hope that you’ll share your experiences and insights with us as well.