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DBL%20Hendrix%20small.png College chemistry, 1983

Derek Lowe The 2002 Model

Dbl%20new%20portrait%20B%26W.png After 10 years of blogging. . .

Derek Lowe, an Arkansan by birth, got his BA from Hendrix College and his PhD in organic chemistry from Duke before spending time in Germany on a Humboldt Fellowship on his post-doc. He's worked for several major pharmaceutical companies since 1989 on drug discovery projects against schizophrenia, Alzheimer's, diabetes, osteoporosis and other diseases. To contact Derek email him directly: derekb.lowe@gmail.com Twitter: Dereklowe

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March 23, 2012

The Ultimate in Personalized Medicine

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Posted by Derek

I wanted to mention this news, since it's really the most wildly advanced form of "personalized medicine" that the world has yet seen. As detailed in this paper, Stanford professor Michael Snyder spent months taking multiple, powerful, wide-ranging looks at his own biochemistry: genomic sequences, metabolite levels, microRNAs, gene transcripts, pretty much the whole expensive high-tech kitchen sink. No one's ever done this to one person over an extended period - heck, until the last few years, no one's ever been able to do this - so Snyder and the team were interested to see what might come up. A number of odd things did:

Snyder had a cold at the first blood draw, which allowed the researchers to track how a rhinovirus infection alters the human body in perhaps more detail than ever before. The initial sequencing of his genome had also showed that he had an increased risk for type 2 diabetes, but he initially paid that little heed because he did not know anyone in his family who had had the disease and he himself was not overweight. Still he and his team decided to closely monitor biomarkers associated with the diabetes, including insulin and glucose pathways. The scientist later became infected with respiratory syncytial virus, and his group saw that a sharp rise in glucose levels followed almost immediately. "We weren't expecting that," Snyder says. "I went to get a very fancy glucose metabolism test at Stanford and the woman looked at me and said, 'There's no way you have diabetes.' I said, 'I know that's true, but my genome says something funny here.' "

A physician later diagnosed Snyder with type 2 diabetes, leading him to change his diet and increase his exercise. It took 6 months for his glucose levels to return to normal. "My interpretation of this, which is not unreasonable, is that my genome has me predisposed to diabetes and the viral infection triggered it," says Snyder, who acknowledges that no known link currently exists between type 2 diabetes and infection.

There may well be a link, but it may well also only be in Michael Snyder. Or perhaps in him and the (x) per cent of the population that share certain particular metabolic and genomic alignments with him. Since this is an N of 1 experiment if ever there was one, we really have no idea. It's a safe bet, though, that as this sort of thing is repeated, that we'll find all sorts of unsuspected connections. Some of these connections, I should add, will turn out to be spurious nonsense, noise and artifacts, but we won't know which are which until a lot of people have been studied for a long time. By "lot" I really mean "many, many thousands" - think of how many people we need to establish significance in a clinical trial for something subtle. Now, what if you're looking at a thousand subtle things all at once? The statistics on this stuff will eat you (and your budget) alive.

But all of these technologies are getting cheaper. It's not around the corner, but I can imagine a day when people have continuous blood monitoring of this sort, a constant metabolic/genomic watchdog application that lets you know how things are going in there. Keep in mind, though, that I have a very lively imagination. I don't expect this (for better or worse) in my own lifetime. The very first explorers are just hacking their way into thickets of biochemistry larger and more tangled than the Amazon jungle - it's going to be a while before the shuttle vans start running.

Comments (26) + TrackBacks (0) | Category: Biological News


COMMENTS

1. carlos on March 23, 2012 7:47 AM writes...

just wanted to add something more to what you mention here, and that is that recently a very interesting paper was published in the NEJM
http://www.nejm.org/doi/full/10.1056/NEJMoa1113205
showing how far we are to having a hint of understanding of what really goes on in our bodies.
Please read it, their conclusion is
quote
....Intratumor heterogeneity can lead to underestimation of the tumor genomics landscape portrayed from single tumor-biopsy samples and may present major challenges to personalized-medicine and biomarker development.
unquote

Permalink to Comment

2. Anon on March 23, 2012 8:32 AM writes...

Too much politics in medicine to even imagine this on a wide scale in our lifetimes....

Permalink to Comment

3. PPedroso on March 23, 2012 9:12 AM writes...

@1 Carlos,

Derek commented on that paper a few days ago in this very same blog! :)

Permalink to Comment

4. Former MedChemist on March 23, 2012 9:32 AM writes...

Another reminder that the plural of anecdote is not data.

Permalink to Comment

5. libfree on March 23, 2012 9:41 AM writes...

30 years or less. I know it's a bold prediction, but I already have a device that monitors my sleep and sends that data to my iphone. I see heart rate, oxygen saturation, ect. being monitored routinely in the next 10 years. Actual blood monitoring will take significantly longer. But by the time we get to 30 years from now, we'll have petascale computing on whatever replaces our iphones and processing it will be a lot easier. I'm excited that I'll see it if I don't die in some tragic alcohol related accident.

Permalink to Comment

6. Anonymous on March 23, 2012 9:42 AM writes...

Here's a similarly interesting analysis
http://bit.ly/GIvpiR
http://amzn.to/q49HdC

Permalink to Comment

7. Hasufin on March 23, 2012 10:56 AM writes...

There are many drugs that would probably be best administered as a slow trickle, or automatically in response to certain events. We're starting to have devices that can do this, like insulin pumps.

I think that we'll see implants that can respond to specific events, and which can monitor vitals and eventually provide more indepth information. The reasons for this will vary, but in time it'll provide us with great real-time information on the human body.

Permalink to Comment

8. Matthew Herper on March 23, 2012 11:01 AM writes...

That's interesting. I do expect it within your lifetime -- though not soon. The big hurdles isn't the omics, or the monitoring, or the computer, but instead changing the health system so that this could actually happen on a wide scale.

Permalink to Comment

9. libfree on March 23, 2012 11:40 AM writes...

@matthew Herper has it. Once we start collecting the data, how do we share it? Will my insurance company get that info and deny me coverage? I see this as a major hurdle.

Permalink to Comment

10. milkshake on March 23, 2012 11:44 AM writes...

there is also risk in over-diagnosing and over-treating potential health problems in people who are otherwise doing fine. Keep in mind that doctors are not that different from car mechanics

Permalink to Comment

11. Derek Lowe on March 23, 2012 11:56 AM writes...

Matthew (#8), I'm not so sure. I think that even if we waved the magic wand, and said that everyone in the US could have this right now, and we'd go mine the asteroids to pay for it, we still wouldn't know what to do with the data yet. There are thousands of variables, none of them really independent, all of them contextual, and any of them potentially important. I think that we might be mining those asteroids before we get it all figured out.

That said, these studies can really help out by suggesting some important things that we've overlooked (or never seen in the first place), which could be implemented in the broader population sooner. . .like, maybe ten to twenty years.

Permalink to Comment

12. Dave on March 23, 2012 6:21 PM writes...

Imagine the real time monitoring of blood levels of thousands of biomarkers as input to the deployment of an array of drugs at the critical moment in the various physiological cycles and responses of the body and its ecological systems.
From time to time, you get a call on your cell phone telling you to "go relax" or "go run a mile"
(or "go get some rock 'n roll") SO that those factors which you can choose to alter are altered to allow your best response to the therapy (or maintenance dosing). All by a chip in your arm.

Permalink to Comment

13. John on March 23, 2012 6:40 PM writes...

Derek, ask your friendly neighborhood machine learning PhD what they think. The main problem to date has been not nearly enough data, but once we get it our statistical methods are really pretty good. N=1 subjects isn't a problem if you've got data from N=10000 immune events, and your target is only that one patient.

Permalink to Comment

14. sgcox on March 23, 2012 6:42 PM writes...

#12 dave: I think such a device is a good idea. But only if it says "she is look interested, have a drink now, damm the liver !" or "this black diamond slope is really good for you, knees can handle it". Otherwise, it can be easily replaced by a generic device randomly posting "say no to calories, go to the gym" ?

I am still looking for the DNA test ever said to anybody: stop worring about this and that, just enjoy the life !

Permalink to Comment

15. dearieme on March 23, 2012 9:07 PM writes...

Could my genome tell me that I'm not the sort of chap who would enjoy Chateau Petrus? That would save me from wasting so much money.

Permalink to Comment

16. Anonymous on March 23, 2012 9:09 PM writes...

I thought Roche was supposed to be the king of "personalized medicine"??? The fact is, their R&D (especially med. chem) over in Nutley, NJ is simply put..."personalized non-sense"!!! DOH!

Permalink to Comment

17. gippgig on March 24, 2012 12:05 AM writes...

Note that if you prepare a shotgun DNA/cDNA library under normal conditions and the person later gets a disease subtractive hybridization should immediately identify the pathogen. This would be a good way to determine which organisms cause what fraction of diseases as well as to identify unknown pathogens (especially worth considering for people who are going into remote areas (i.e., tropical rain forests)).

Permalink to Comment

18. Nile on March 24, 2012 6:08 AM writes...

Libfree (#9) makes a dangerous point: better information works against patients in an adversarial economy.

Knowing more might help you plan your life, and it will help your treatment immeasurably but this is only true if you have either (a) unlimited resources for treatment or (b) an equitable distribution of resources in a pool that represents a full range of phenotypes.

(b) Should be available in an insurance-funded healthcare model - insurance works on pooling risk - but, in practice, the insurer is always a more powerful entity than any individual in the insured pool. Hence, overcharging, undertreatment, and rescission. Or outside the pool: cherry-picking and exclusion are built in failure modes of all insurance models.

All funding systems in healthcare run up against the failure mode 'exhaustion of funds' and, in practice, they all fail in implementing a cap on individual funding which is agreeable and acceptable to all. Even 'Treat the Politburo Chairman with all the resources of the State' fails that test.

But an insurance-based model seems to be unique among healthcare systems in its innate tendency to resist scientific advances that would benefit the patients directly *and* improve the economic efficiency of the system. Or, worse, react in ways that are damaging to both.

This is a matter of concern in England as well as in America: we have now embarked upon a decisive (and irrevocable) policy to break up the National Health Service and move to an insurance-based healthcare model. So better diagnostic and predictive data is now a danger to the individual in England, as well as in the USA.

Ironically, the tiny minority of individuals in the insurance industry (and their investor community) who will benefit from this financially are just as screwed as the rest of us, even though they gain enough money to pay directly for treatments that we will be excluded from.

Screwed? Let me explain:

The sharp point of the screw is the misuse of better diagnostics and predictive data to exclude individuals from treatment; but the cutting spiral thread is that there will be far, far fewer new treatments developed - mass exclusion means that the new information will almost always reveal treatment opportunities in subpopulations that are too small to generate a profitable return on the R&D costs. Not 'too small, because too few people in the general population have that phenotype for it to be worth investigating' but 'too small because insurers will exclude all the people who could be treated from insurance funding, and the remaining millionares who can self-fund their treatment do not constitute a viable market'.

There are parallels to be drawn between you, us, and our distant colleagues in agricultural biochemistry who developed the first cost-effective insecticides: a milestone in human progress, eliminating one of the major causes of starvation and disease.

They had good reason to be proud; but they were horrified to discover that they had also contributed to the invention of nerve gas... Which has, to date, killed fewer people than the annual death toll, within the USA, from curable diseases that other countries - far less wealthy than America - find it to be equitable, affordable, and economically-justifiable to treat.

What proportion of our discoveries this year will worsen this?

Permalink to Comment

19. Nile on March 24, 2012 6:08 AM writes...

Libfree (#9) makes a dangerous point: better information works against patients in an adversarial economy.

Knowing more might help you plan your life, and it will help your treatment immeasurably but this is only true if you have either (a) unlimited resources for treatment or (b) an equitable distribution of resources in a pool that represents a full range of phenotypes.

(b) Should be available in an insurance-funded healthcare model - insurance works on pooling risk - but, in practice, the insurer is always a more powerful entity than any individual in the insured pool. Hence, overcharging, undertreatment, and rescission. Or outside the pool: cherry-picking and exclusion are built in failure modes of all insurance models.

All funding systems in healthcare run up against the failure mode 'exhaustion of funds' and, in practice, they all fail in implementing a cap on individual funding which is agreeable and acceptable to all. Even 'Treat the Politburo Chairman with all the resources of the State' fails that test.

But an insurance-based model seems to be unique among healthcare systems in its innate tendency to resist scientific advances that would benefit the patients directly *and* improve the economic efficiency of the system. Or, worse, react in ways that are damaging to both.

This is a matter of concern in England as well as in America: we have now embarked upon a decisive (and irrevocable) policy to break up the National Health Service and move to an insurance-based healthcare model. So better diagnostic and predictive data is now a danger to the individual in England, as well as in the USA.

Ironically, the tiny minority of individuals in the insurance industry (and their investor community) who will benefit from this financially are just as screwed as the rest of us, even though they gain enough money to pay directly for treatments that we will be excluded from.

Screwed? Let me explain:

The sharp point of the screw is the misuse of better diagnostics and predictive data to exclude individuals from treatment; but the cutting spiral thread is that there will be far, far fewer new treatments developed - mass exclusion means that the new information will almost always reveal treatment opportunities in subpopulations that are too small to generate a profitable return on the R&D costs. Not 'too small, because too few people in the general population have that phenotype for it to be worth investigating' but 'too small because insurers will exclude all the people who could be treated from insurance funding, and the remaining millionares who can self-fund their treatment do not constitute a viable market'.

There are parallels to be drawn between you, us, and our distant colleagues in agricultural biochemistry who developed the first cost-effective insecticides: a milestone in human progress, eliminating one of the major causes of starvation and disease.

They had good reason to be proud; but they were horrified to discover that they had also contributed to the invention of nerve gas... Which has, to date, killed fewer people than the annual death toll, within the USA, from curable diseases that other countries - far less wealthy than America - find it to be equitable, affordable, and economically-justifiable to treat.

What proportion of our discoveries this year will worsen this?

Permalink to Comment

20. Matthew Herper on March 24, 2012 8:18 AM writes...

Derek -- I guess my thought is that the technology to collect the -omics data and the computers to analyze it are all not that far off. The question is how you get phenotypic data to make it make sense. I have no doubt this will start to happen given a few decades. But genomics is still searching for its entry points into the clinic. And right now even the improved EHRs we're imagining are pretty messy.

Permalink to Comment

21. Farmer Geddon on March 24, 2012 9:00 AM writes...

..he initially paid that little heed because he did not know anyone in his family who had had the disease..

That's the problem with family histories, you assume your mother was faithful to her husband !!

Permalink to Comment

22. luysii on March 24, 2012 12:42 PM writes...

We are only beginning to understand the importance of modifier genes on what, at first glance, appeared to be clear cut examples of single gene mutations causing disease. For example;

Cell vol. 145 pp. 1036 – 1048 ’11 sequenced some 9,000,000 positions of DNA. This didn’t make a big splash (but its implications might). Just a single paper, buried in the middle of the 24 June ’11 Cell — it didn’t even rate an editorial.

As a neurologist, I treated a lot of patients with epilepsy (recurrent convulsions, recurrent seizures). 2% of children and 1% of adults have it (meaning that half of the kids with it will outgrow it, as did the wife of an old friend I saw this afternoon). Some forms of epilepsy run in families with strict inheritance (like sickle cell anemia or cystic fibrosis). 20 such forms have been tied down to single nucleotide polymorphisms (SNPs) in 20 different genes coding for protein (there are other kinds of genes) — all is explained in the background material above). 17/20 of these SNPs are in a type of protein known as an ion channel. These channels are present in all our cells, but in neurons they are responsible for the maintenance of a membrane potential across the membrane, which has the ability change abruptly causing an nerve cell to fire an impulse. In a very simplistic way, one can regard a convulsion (epileptic seizure) as nerve cells gone wild, firing impulses without cease, until the exhausted neurons shut down and the seizure ends.

However, the known strictly hereditary forms of epilepsy account for at most 1 – 2% of all people with epilepsy. The 9,000,000 determinations of DNA sequence were performed on 237 ion channel genes, but just those parts of the genes actually coding for amino acids (these are the exons). They studied 152 people with nonhereditary epilepsy (also known as idiopathic epilepsy) and, most importantly, they looked at the same channels in 139 healthy normal people with no epilepsy at all.

Looking at the 17/237 ion channels known to cause strictly hereditary epilepsy they found that 96% of cases of nonhereditary (idiopathic) epilepsy had one or more missense mutations (an amino acid at a given position different than the one that should be there). Amazingly, 70% of normal people also had missense mutations in the 17. Looking at the broader picture of all 237 channels, they found 300 different mutations in the 139 normals, of which 23 were in the 17. Overall they found 989 SNPs in all the channels in the whole group, of which 415 were nonsynonumous.

Well what about mutational load? Suppose you have more than one mutation in the 17 genes. 77% the cases with idiopathic epilepsy had 2 or more mutations in the 17, but so did 30% of the people without epilepsy at all.

Why didn't normal people carrying the mutations NOT have epilepsy? Presumably because of modifier mutations (or just polymorphisms) in other genes. This is why sequencing the profs expression profiles and gene profiles aren't likely to tell us much (until we sequencing everything in everybody, and even then . . . ).

If you want more see https://luysii.wordpress.com/2011/07/17/weve-found-the-mutation-causing-your-disease-not-so-fast-says-this-paper/

Permalink to Comment

23. MIMD on March 24, 2012 6:14 PM writes...

#4 Former MedChemist

Re: "Another reminder that the plural of anecdote is not data."

In medicine, though, one must remember not to dismiss "anecdotes" out of hand, especially regarding adverse events, as they may in fact be risk management-relevant incident reports.

Permalink to Comment

24. aldehyde on March 25, 2012 11:46 AM writes...

This wouldn't just be for telling you to go to the gym, read into the article a little bit. If we had vast amounts of data from these sensors that had monitored people as they developed and fought off various viruses, bacterial infections, chronic diseases etc the recognition would get much better. And treatment providers would have a much better sense of what is going on during emergencies.

Permalink to Comment

25. Morten G on March 26, 2012 7:52 AM writes...

With nanopore sequencing technology doing this will get even cheaper: http://news.sciencemag.org/sciencenow/2012/03/dna-sequencing-without-the-fuss.html?rss=1

About time too. My mom got sick in Mexico (fever, lethargy, shortness of breath), was admitted to hospital when she got back. Doctors figure either an infection or a blood clot. Start her on antibiotics, scan for blood clots. No clots. So it's probably a bacteria, a virus, or a parasite. Let's see if the antibiotics make her better. Done. No, the antibiotics didn't make her better. Let's see if it doesn't pass on it's own then.

Look up the papers on colony collapse disorder and Israeli paralysis virus and you'll see how important and useful this stuff will be for research on human disease (Israeli paralysis virus in the US not fault of Israelis btw. George W Bush + Australian bees).

Permalink to Comment

26. Student on March 26, 2012 4:02 PM writes...

I agree with Milkshake. I also believe that they aren't capable/trained to analyze the data. Hopefully IBM-Watson will be able to phase out MDs diagnostic "skills" in the next 20-30 years.
I've seen the med students cheat with software like Epocrates, so it's just a matter of time betore someone puts 1 and 1 together.

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