Way to go CVS Caremark!

I just learned that CVS Caremark has decided to put some pharmacogenomics testing in place for a variety of clinical areas, including cancer, cardiovascular disease and HIV.   This is an alliance with Generation Health.   I am a CVS Caremark customer (thank you, Stanford), and I am thrilled to learn that they are doing this.   It raises the possibility that PGx penetration will happen not by FDA decree or government reimbursement agencies, but by pharmacy benefits companies that see real value to them and their customers.  It will be very interesting to see how this goes.   CVS Caremark is a big company that serves 60 million people.   If their competitors follow suit, we may see the benefits of pharmacogenomics reaching patients much sooner than might occur if we wait for other routes to materialize.

FDA looking for leads in pharmacogenetics.

I was excited to see the announcement of the relabeling of clopidogrel (a.k.a. Plavix) by the FDA.   The FDA exerts much of its influence on drug companies and medical practitioners by approving the “label” that describes the uses, doses, cautions, and much other information about using a medication.  It is the folded up piece of paper that is always inserted into your medication packaging (thus it is also known as the “package insert”), that then unfolds into a huge poster-sized document with tiny font and lots of information.  It is a legal document which specifies what the drug company can claim about the drug, and how physicians are supposed to use it (give or take some “off label” uses, but that is another topic).   I’m sure it is the star of many lawsuits.

In any case, there has been accumulating evidence that certain genetics variants of CYP2C19 that reduce its activity are associated with differential success of clopidogrel at preventing myocardial infarctions (heart attacks).  Also, drugs that inhibit CYP2C19 also reduce the effectiveness of clopidogrel.  Thus, the FDA modified the label for clopidogrel and warned about concomitant use of medications that interact with CYP2C19 and also mentioned that the genetic variants present in a patient may warrant careful assessment of whether to use the drug, and how much to use.  This is another success for pharmacogenetics!

The pharmacogenetics database we are developing,  PharmGKB, is focused on gathering evidence for the role of genetics in drug response.  PharmGKB staff have  a good working relationship with some FDA scientists, and we are all very interested in finding out about other drugs for which there is mounting emerging evidence that genetics may play an important role.  In some cases, the FDA may even launch a process to determine if the label should be modified in light of new evidence.  If you come across compelling scientific evidence for genetic determinants of drug response, let us know at feedback@pharmgkb.org.  We will gather together responses and assess them on a regular basis–we will even alert our friends at the FDA to those that are reaching a critical point!

You can see a list of drugs with specific FDA language about genetics on PharmGKB.

A magazine for biocomputation = BCR

One of the research projects that I help direct is devoted to improving and disseminating the use of physics-based simulation in biology–at all levels:  molecular, cellular, tissue and organism.   It is called Simbios (National Center for Physics-based Simulation of Biological Structures, http://simbios.stanford.edu/) and I may write about it more in the future.  We have done cool things like release software for simulating human motion, superfast molecular calculations on graphics cards, and other things.   But one of the coolest things about Simbios is that part of our dissemination plan is the distribution of a magazine entitled “Biomedical Computation Review” or BCR.   It was the brainchild of my colleague, David Paik, when we were writing the grant, and it is ably managed by David and Kathy Miller, the managing editor.   We tried to model it on the MIT Technology Review, which has great coverage of “techy” stuff from all over, and creates a sense of community among techies (ostensibly MIT alums, but I have no connection to MIT and enjoy it very much).  BCR is available online, but I really recommend that you contact us for a physical subscription because it is fun to hold and read, and it can be read in many places where internet or computers might not be handy or convenient.  We have some regular columns and most issues have a theme such as curricula in biomedical computation, women in biocomputing, human vs. machines, and other fun topics.  If you have ideas, let us know.  We are contemplating an upgrade in the web presence of the magazine.

CMS made a mistake in not approving genetics for warfarin.

I am very disappointed that the federal medical reimbursement folks have not approved the use of genetic tests to make warfarin dosing more precise.    This would be an opportunity for CMS to start the personalized medicine revolution, and to make the public aware that we physicians can do better than guessing in the use of dangerous medications.  We were part of an effort published in February that showed very clearly that genetics helps predict much more accurate doses of warfarin, and that 40% of patients are at risk for over- or under-dosing without this information.   I am not an expert on the CMS approval process, but I would wager that there are MANY things reimbursed for which there is not a similar level of likely cost-effectiveness.   Here was an opportunity for the new administration to take leadership, and it was a lost opportunity.

Way to go, Shirley.

My soon-to-be-graduated student, Shirley Wu, had a good day the other day.  First, I signed her PhD dissertation, making it very likely that she will graduate in 2 weeks from Stanford with a PhD in Biomedical Informatics.  It was a great thesis on machine learning methods to detect functions in protein structures.   An early paper is already out, and one is in preparation.   Second, she wrote a blog entry entitled “Open Letter to Oprah” where she expressed her disappointment that Oprah is supporting the non-scientific and dangerous crusade against vaccines lead by Jenny McCarthy, and this got a fair amount of attention, including more than 5000 links and tweats and whatevers in the first 24 hours.   So Shirley had a good day.  Congratulations.

Sorry for inactivity: distracted by stimulus

I apologize that I have not posted more recently.  I, like virtually every other biomedical scientist in the United States, have been busy writing grant proposals for the NIH portion of the federal government’s stimulus package.  There are a number of calls for proposals, and part of the fun in the last month has been trying to figure out the odds of success for each, and how to match the requirements.   They include:

• Administrative supplements to existing grants with no change in scope–these are not peer reviewed, but are at the discretion of NIH staff.
• Extensions to existing grants that extend the scope–these will be peer-reviewed
• “Challenge grants” that are entirely new and should propose exciting science.
• “Grand opportunity” grants that are entirely new and should propose exciting science that is more expensive
• Summer research grants for students

These are all great opportunities, and they all are on a timescale such that they must be spent in 2 years.  That is a very short time for new efforts, and so I would think that NIH would mostly select existing projects to just accelerate.   Anyway, with so many proposals, the chances of success for any individual proposal will be low.  I am involved in at least 7 different proposals from the above list.   I am excited about all the projects, and if they are all funded, will pursue them with vigor.  It is entirely possible that I will go 0/7.

The beneficial affect of this, however, has been to get people together and thinking boldly.  This may lead to good things entirely separately from whether or not they attract stimulus funding.   So this last month has been quite stimulating.   And I think time spent on these proposals is not wasted, even if they are not funded immediately by the stimulus programs.

Signing reviews and even publishing them?

Shirley Wu pointed out an interesting entry by Luis Von Ahn arguing that reviews should be published.  This comes to me right after an interesting discussion with a colleague who routinely signs his reviews (which are typically done anonymously) so that the authors know who he is.  Both make the point that by either publishing to everyone or signing, it ensure that the quality of the review is good (your name is on it, afterall) and that you don’t take cheap shots (believe me, this is common in anonymous reviews) and that there is an opportunity for scholarly debate over the paper.  I have signed my reviews occasionally (usually for positive reviews, I must admit).   I am considering doing it routinely now.

There are downsides.  First, I don’t want to make every review I do a review that “keeps on giving.”  I am asked to do many reviews and if all of them are the start of a potential long-winded dialogue, I will decline a much higher percent.  (I am currently probably accepting 20% of requests, just to make sure I get my day job done).    Second, I have tenure but it may be asking too much for an untenured junior faculty member to speak frankly and expect their colleagues to respect their effort, and not hold it against them later when writing letters for appointments and promotions.   Finally, we don’t have a good system to allocate credit for quality reviews, and if the level of effort were to be increased, we would certainly need to consider ways to reward those who do a good job reviewing.   Part of this would be self-correcting because the “record” would show who is doing a good job, and potentially the reviews could be as “famous” as the papers themselves.

The technology is in place with online resources to trivially support a full audit trail of initial paper, reviews, and then final paper.  This would certainly be a fascinating repository of information.   Historians of science might love it.  Students might learn a ton from it.  I think the physics community does something like this, but I am not sure.  My colleague Chris Lee at UCLA has fascinating ideas in this area, but I don’t know if he has published on it.

But the first step for me is to sign the review, and I may try doing this–even for negative reviews.   After that, we can see about publishing the reviews–there, I am mostly concerned about logistics, time commitment and efficiency.

Genetic privacy

As you can see from my slides in the‘Translational Bioinformatics‘ posting, I highlighted three papers that I think create an interesting dance of ideas.   The first one from Homer et al showed that IF you have the genotype data from a single individual and a mixture of up to 1000 others, then you can determine if that first individual is part of the mixture.

What’s the big deal?   Well previously it was assumed that the mixture of 1000 was too complex to unravel, and so people released data on mixtures freely into the public.  With this paper, it is now slightly dangerous to do that–if someone has a DNA sample and is wondering if someone else is part of the sample of 1000, they can do it.  Basically, because we measure 500,000 different SNPs, we can use each SNP to slightly alter our confidence that the individual is or isn’t in the mixture.  No single SNP proves it, but 500,000 together make confidence very high.

As a result, NIH’s genome-wide database dbGAP stopped publishing the aggregate data that was heretofore thought to be secure.  One could argue that this is overkill because of all the other things that have to be true to allow re-identification (having a DNA sample from someone, genotyping them).   The paper was written with forensic applications in mind:  I have a DNA sample from a potential perp, is there any chance that this perp contributed to the DNA mixture at the scene of the crime?   Also, if they already have the DNA and genotypes, what further loss of privacy could there be?  Well, in theory, knowledge that the person participated in a disease-related study could give information about a disease they have that they didn’t want to share.  It’s all remote and not very likely, but this paper shows it’s possible and it was a big wake up call for many.  For me, not so much–I am on the record saying that DNA anonymity is basically a fiction and we should use social (not technical) means to stop abuse of the information.
So in the next paper, I showed an article by Nyholt et al in which these principles are applied, kind of.   Jim Watson donated his DNA to be sequenced and it was released to public, but for some reason he didn’t want his APOE genotype to be released (some APOE alleles are associated with increased risk for Alzheimer’s disease).  So they redacted that part of his sequence.  In this paper, the authors showed that there is plenty of correlation between different parts of the genome (Linkage Disequilibrium = LD is the official confusing term) so that they could infer the APOE genotypes.  As a courtesy, they informed the folks who distributed the genome and gave them a chance to remove a much larger 2 Megabase chunk of the sequence to make this kind of correlation analysis less easy.   However the point was made:  be careful what you release, because you may be releasing more than you think.

Finally, on a whimsical note, I presented a paper by Christley et al showing that the same Jim Watson genome can be compressed with some clever data compression techniques into a small 4.1 Megabytes–easily small enough to email to a friend as an attachment.  So the full circle (?) is achieved:  we identify genomes, we infer things about them, and then we email them to our friends.   Genome security?  Forget about it…Or else pass laws and stuff.

Translational bioinformatics

I define translational bioinformatics as the field where bioinformatics meets clinical medicine.  Work in translational bioinformatics will typically include informatics methodolgy, clinical concepts (drugs, diseases, symptoms, diagnosis), and molecules (genes, proteins, DNA, RNA, small molecules, drugs).   The Second AMIA Summit on Translational Bioinformatics just ended yesterday, and I predict great things for this meeting–it has all the right ingredients to become an important venue for this emerging field.  It was organized by  Atul Butte last year (first ever) and was followed up by  Yves Lussier this year.   Peter Tarczy-Hornoch will organize it next year, again in SF.

I had the pleasure both years of presenting a “Year in Review” talk in which I picked out some papers that I thought were important, interesting, visionary, whatever.   This process is obviously filled with pitfalls and the only claim that I can make is that these papers represented alot of outstanding others as representatives.  I no doubt missed many critical papers, and please let me know about them as comments to this post.

In future postings, I will give a sense of what I said for each of the key areas I highlighted yesterday:

• Literature mining
• Genetic Privacy
• Genes x Environment
• Genes + drugs/small molecules
• Schizophrenia
• Gene networks for understanding disease
• Stem cell biology
• Potpourri

For now, this year’s talk is available .  Last year’s talk is also available. Comments are welcome.   I will post the full bibliography as soon as I can assemble it in a reasonable format.  I had the privilege of reviewing the full Table of Contents from many journals, and of course there is a nagging worry that I missed entire journals.  There is an interesting dynamics in the interplay of methods and biological results, as well.  That deserves some discussion in a future post as well.

Call for great translational bioinformatics papers 3/08-3/09

Friends,

I have agreed once again to give a talk at the AMIA Summit on Translational Bioinformatics ) on the “year in review” highlighting some of the most important papers in our field of translational bioinformatics.  Last year’s talk is online.

I am writing to request that you nominate papers that you think are important for me to include from the last 12-15 months.  Nominations of your own papers are fine, but much less compelling than nominations of others’ papers (you can collude though…).   Here are the criteria:

• I define translational bioinformatics broadly, but expect it to involve molecular-level (genes, small molecules) data AND clinical-level data (diseases, symptoms, drugs)
• I define bioinformatics as the creation and application of novel methods of analysis/discovery

I have been trolling the sites myself, but want to make sure I ask colleagues in bioinformatics for their thoughts.

I would like to highlight papers that have done a good, creative job at the above, and have a chance to become “classics” over the next 10-20 years.   I expect to discuss about ~15 papers in “1-2 slide” detail and then to have another list of 10 “noteworthy but not discussed in detail” papers.

I would like these nominations by 5 PM on 3/11.  Thanks for your help.  If you don’t want to post publically, you can send to me by email at russ.altman-at-stanford.edu.