Cycling--and cycling ideas

On December 13 we posted about the Big Surprise release of a research paper that showed that exercise is good for you, indeed, better than medicine.  Not good news for doctors (or the corporations that own them or sell pills through them).  We commented about how well known this was.

A regular reader, John Vokey, pointed out a very nice recent article in the British Medical Journal, by the arch skeptic Ben Goldacre and David Spiegelhalter, about how we know whether something that's obvious is actually true.  Here is a link to that piece.  He's a widely known writer and commentator, as well as a practicing physician in Britain, who has written a great deal about similar aspects of how we use data and how this affects medicine.  He writes about 'Bad Pharma' to try to correct such things (see link below his picture for more).

Ben Goldacre

While it is obvious that exercise is good for your health, and we have some good physiological and physical reasons and mechanisms to back up that statement, in our post we noted that the correlation between health and exercise may not be so simple.  For example, you have to already be healthy to exercise so the correlation may be a result not a cause of better health.

Goldacre takes something bluntly obvious, that wearing a helmet when bicycling is good for your health (that is, in terms of injuries).  He shows that even this is neither so obvious nor simple.   Just to illustrate the point, if you ride more often or more often in traffic because you feel safer when you wear a helmet, even with the same per-mile (or, in Goldacre's UK, per kilometre) risk there will be more rather than fewer cycling-related injuries: the population at-risk has grown.  Or drivers may cut closer to you seeing that you are helmeted.  And so on.  As John Vokey pointed out in his comment, that brief but to-the-point article is a fine lesson in statistical reasoning.

If something as apparently simple as the risk of cycling with vs without a helmet is not so simple, then how much more complex will other sorts of causation, epidemiological, genetic, and evolutionary are supposed cause-and-effect scenarios be?  A due respect for this complexity should routinely temper conclusions from simple study designs (or, in the case of evolution, almost pure surmises about natural selection in the distant past).

Yet pressures, and perhaps natural tendencies in our boastful current culture, seem to be doing just the opposite: leading investigators to make ever-quicker and ever more grandiose claims about their findings.  This is used for self-promotion in general, in seeking grant support, and in the rush to the media.  And science journalists often show little, sometimes almost zero sense of skepticism or even circumspection, about such claims.

The issues we face in science are nowadays very complex and subtle, and we know from even simple examples, such as the one Goldacre used to illustrate the pitfalls of statistical reasoning, that our conclusions can be very wrong, even in very simple ways.   We try to make conclusions in science, but we should do that by starting with respect for the complexity of the problem.

On being at home where we live

We use this blog to present issues we feel are interesting....and points we believe are important.  Often that means critiques of things we see around us. Those can be stronger or weaker as we see the situation through our own, fallible, eyes.

But it is all too easy to fall into critic-mode, fail to appreciate what is good about our areas of knowledge, and value what, in historical terms, a life of science really represents compared to what most of our species have had to endure.

This, if anything, should reinforce the burden every scholar or scientist feels: not to waste the opportunity, or act too selfishly, but to work towards a common good--the common good we routinely voice as a profession but to which we have it in our power to make a better approximation.

In recognition of the need to 'be at home where you live', we reproduce a poem we recently learned of, by the wonderful pastoral, common-man's poet, William Wordsworth. It is even fitting for the season.

Here, 'home' includes more than one's collection of Big Data, grants, or other score counts, and shows what one can find even in a simple poem.

Weaver at his loom; Van Gogh

Nuns Fret Not at Their Convent’s Narrow Room
By William Wordsworth

Nuns fret not at their convent’s narrow room;
And hermits are contented with their cells;
And students with their pensive citadels;
Maids at the wheel, the weaver at this loom,
Sit blithe and happy; bees that soar for bloom,
High as the highest Peak of Furness-fells,
Will murmur by the hour in foxglove bells:
In truth the prison, into which we doom
Ourselves, no prison is: and hence for me,
In sundry moods, ’twas pastime to be bound
Within the Sonnet’s scanty plot of ground;
Pleased if some Souls (for such there needs must be)
Who have felt the weight of too much liberty,
Should find brief solace there, as I have found.

The FDA's new 'ban' on antibiotic use in animals needs more teeth

The CDC estimates that 2 million people in the US every year contract antibiotic resistant infections, and 23,000 die as a result.  Antibiotic resistant bacteria -- another on the list of looming crises we're smart enough to do something about but are doing far too little far too slowly.  So it would be good if, as reported by New York Times, the US Food and Drug Administration had announced what will be a major policy to slow down the routine overuse of antibiotics in the food supply.  But it seems unlikely.

For decades, healthy cows, pigs and chickens have been given antibiotics to maintain their health and to boost their growth, and more recently, so have farmed fish, but this is a major cause of the waning effectiveness of antibiotics. There seem to be multiple pathways leading from antibiotic use in animals to antibiotic resistance in humans.*  

Chicken house; Wikimedia Commons

 Low dose, prolonged use of antibiotics in animals creates ideal conditions for the selection and growth of antibiotic resistance.  How they spread from animals to humans is difficult to document and probably there are numerous pathways, but it does seem sometimes be possible by consumption of food carrying resistant bacteria, and indeed farm workers often harbor antibiotic resistant strains of gut bacteria that indicate they originated in animals on the farm, but so can people who eat meat or fish contaminated with resistant bacteria.  There is evidence of horizontal transfer of resistance genes, too, from bacteria most often found in animals to those that prefer human hosts.

The 'ban'
Now the FDA says it is effectively banning the use in food animals of those antibiotics that are medically important in human health, and that are used solely to enhance animal growth. A second piece of the new regulations is that a licensed veterinarian will be required to oversee antibiotic use if the grower wants to deliver these drugs to prevent illness.  The changes will become effective over the next three years.

How will it work?  The FDA is requesting that drug makers change antibiotic labels to exclude their use in animal growth promotion.  Whether they do this or not is entirely voluntary.  Given the huge vested interest drug manufacturers have in selling antibiotics to food producers -- 70-80% of antibiotics in the US are used in the food supply** -- and that farmers have in promoting fast growth in their animals, whether this will actually work is an open question, and there are many doubters. Though, the two pharmaceuticals that make the majority of antibiotics have said they will comply.

Comply or not, there are loopholes.  A food producer can claim that the same daily use of low doses of antibiotics now meant to enhance growth is required to prevent illness, which would mean it's allowed.  Thus, it's possible that nothing will change.  Many critics would much prefer that antibiotics be allowed only to treat infection, and would like to see the FDA ban the preventive use of antibiotics. 

Why we need a policy that works
It is important that we have a policy that works.  Maryn McKenna describes the dire consequences of losing antibiotics in her sobering, excellent recent piece for Wired, ("When We Lose Antibiotics, Here's Everything Else We'll Lose Too").  Not only will we lose the obvious, the ability to treat infection, but also, as she writes, we'll lose the ability to treat cancer when it requires suppressing the immune response, to do organ transplants, kidney dialysis because it relies on an implanted portal into the blood stream, many kinds of surgery, Caesarian sections will be risky, and much more.  As she points out, in the pre-antibiotic era, "one out of every nine skin infections killed" -- life will be a lot more dangerous again. 

And, clearly, the way animals are raised for food on industrial farms will also have to change.  But there are many arguments in favor of this already, even apart from the antibiotic resistance issue.  Animals raised in the kinds of crowded conditions pig or cattle or chickens are too often raised in increases their risk of illness.  And, these animals are often raised on feed that that also makes them more susceptible; smaller farms, and more humane conditions would greatly reduce the need for antibiotics.  And, as McKenna also points out, many crops depend on antibiotics as well.  When fruit or vegetable diseases now controlled with antibiotics can no longer be, that will be another major problem.

So, the FDA may be taking a desirable first step, but the stakes in public health terms are very high.  If the critics turn out to be right about the loopholes, there's a lot to lose. 

-----

*Smith, DL et al., Animal antibiotic use has an early but important impact on the emergence of antibiotic resistance in human commensal bacteria, PNAS, 2001. 

Marshall, BM; Levy, SB., Food Animals and Antimicrobials: Impacts on Human Health, Clinical Microbiology Reviews, 2011. 

**Mellon M, Benbrook C, Benbrook K L. Hogging It: Estimates of Antimicrobial Abuse in Livestock. Cambridge, MA: Union of Concerned Scientists; 2001. 

National Research Council, Committee on Drug Use in Food Animals. The Use of Drugs in Food Animals: Benefits and Risks. Washington, DC: Natl. Acad. Press; 1999.

Innovation-stimulation: will it work? Definitely worth a try!

Francis Collins has for some reason decided that NIH should try really, really this time, to stimulate research 'innovation' by moving at least a bit away from costly, wasteful, excessive but incremental big project grants, to dedicating a goodly chunk of NIH external research funding to individual investigators rather than large groups.  Here is the Nature story about it.

Alpine ibex climbing Cingino Dam in Italy (source: every other web site)

The NIH has been experimenting with funding high-risk, high-reward science with four separate pilot programs, including the Pioneer awards.  According to the Nature piece,

The NIH currently spends less than 5% of its US$30-billion budget on grants for individual researchers, including the annual Pioneer awards, which give seven people an average of $500,000 a year for five years. In contrast, the NIH’s most popular grant, the R01, typically awards researchers $250,000 per year for 3‒5 years, and requires a large amount of preliminary data to support grant applications.

Expanding the program is clearly a move in a good direction.  Big projects have their place, but have become as much a reflexive strategy for self-perpetuation as they are truly justified by their results history (which, by and large, isn't all that good or has reached diminishing returns).

Of course, individual independent investigators are just people, trend-following herd animals like most of us are.  Once the new program is in place, every investigator will flock to the trough.  Most will propose routine, safe projects even if they assert that they're 'innovative'.

Those proposals that really are innovative will involve risk in two main senses.  First, they mainly will involve procedures or strategies that are to the area and/or to the investigator, truly new, unclear, or untried.  Second, if the work is really innovative, most of it won't get completed on time, won't yield much in the way of publications, and -- worse -- won't find anything really new.

But is that outcome really 'worse'?  We think just the opposite!  If not much is invested in a project, not much is lost if it was truly creative but failed.  By contrast much is currently invested in huge projects that are so safe that they hardly generate commensurate returns.  Indeed, the reason for the failure of a really exploratory study may provide more useful knowledge than most 'positive' studies' findings.  And most potentially innovative ideas are, and turn out to deserve to be, busts.  That is why we call the ones that succeed innovative: they can change how we think.

This NIH policy change won't change crush of competition to keep the grants flowing, and will make it hard to see what is really innovative, in the inevitable panicky rush to get one's salary covered and keep the lab operating.  It takes experience, perhaps, but not undue cynicism, to predict that this new policy will be gamed and strategized.  The overpopulation of investigators still need funding (or jobs!), and will flood to the new trough, finding all sorts of reasons why their work is innovative.   Do you think it could be otherwise, or that such discussions are not taking place already at brown-bag lunches in departments across the country?

Place limits
Unless we limit how much funding any one investigator can have, don't give these new grants to people who already have a grant or impose some such restrictions, we will largely see just be a game of musical chairs.  New labels, same stuff.  After all, who will be reviewing and administering these applications?  It will be the same people who have brought you big-scale non-innovation all these years.  Unless today's heavy hitters are able to reverse the politics back to the old way (making sure their big-projects don't get curtailed!), NIH will make it a new System, with all the bureaucratic politics and cumbersomeness that that involves.  If their career has been spent in the current treadmill, how many will even be able to think in truly innovative ways?  We are, after all, middle-class people who need to earn a living as things now stand. What else can you expect?

Still, the change should be better than what we currently have!  The amount of funds wasted in the new way will be less than the amount being thrown away in the current rush to Big Science, the seeking of huge projects too big to kill and thus to provide career safety for the lucky investigators and their labs and fancy equipment.  As long as in the new way, the funds for individual researchers are enough to let them do good work but not enough to let them get comfortably entrenched, or for their administrators to depend on the overhead, then it's got a chance to make a real difference.

Of course, this will work even better if those who are training graduate students and post-docs inculcate innovative thinking.  If the grants are big enough just to enable faculty to hire students and technical staff to do the work, they may work less well.  What we need are grants to individuals that are small enough that the recipients will actually have to roll up their sleeves and do some of their own work.

We would suggest a fillip that should be tried:  Give grants to graduate students to do their own truly independent project, not just to be serfs on their mentors' project. Independent, free-standing funding for dissertations.  Labs should be their professors' places of training, not just their playgrounds.

Finally, we know that too-few and too-small will not really work well (compare western science to most of Eastern European, Indian, or South American science in the '80s, for example).  But unrelenting vigilance will be required to prevent coalescence once again into fewer, bigger projects.

If it can be done and really done properly, this could be a salubrious change, in directions we have to approve of, since we've been criticizing the current big-science mode for years. But we have to be patient, because innovation is very hard to come by.

Hippocrates knew it. Galen knew it. EVERYBODY knows it! (So why are we still paying for research on it?)

It is totally fair to say that everybody knows that exercise is good for you, and overindulgence isn't.  Not all the details are known and they probably change over time and place, because there are various ways to exercise and various ways to eat, drink, and be merry.

But around 400 BC Hippocrates (whoever he/they was/were) clearly observed, knew, and stated that moderation in all things is good for health and longevity, and that exercise is part of that.  500 years later (yet still 2000 years ago), Galen was also very clear about the same points, and this from his own very extensive observation.  Yes!  "Evidence-based medicine" isn't new!

Hippocrates; Rubens engraving; Wikipedia

If we could give every individual the right amount of nourishment and exercise, not too little and not too much, we would have found the safest way to health. 

Eating alone will not keep a man well; he must also take exercise.                   -Hippocrates

And, Galen's view, as described by Jack Berryman in "Motion and rest: Galen on exercise and health" (The Lancet, vol 380:9838, pp 210-11):

Galen (c 129—210 AD), who borrowed much from Hippocrates, structured his medical “theory” upon the “naturals” (of, or with nature—physiology), the “non-naturals” (things not innate—health), and the “contra-naturals” (against nature—pathology). Central to Galen's theory was hygiene (named after the goddess of health Hygieia) and the uses and abuses of Galen's “six things non-natural”. Galen's theory was underpinned by six factors external to the body over which a person had some control: air and environment; food (diet) and drink; sleep and wake; motion (exercise) and rest; retention and evacuation; and passions of the mind (emotions). Galen proposed that these factors should be used in moderation since too much or too little would put the body in imbalance and lead to disease or illness.

Galen; Wikipedia

So, if we all already know this, and have known it for millennia, why are we as societies still paying for researchers to design even more studies so they could show this yet again, and again, and again, and...?  The latest instance is covered in a recent NY Times story reporting a study published in the British Medical Journal in October ("Comparative effectiveness of exercise and drug interventions on mortality outcomes: metaepidemiological study", Naci and Ioannidis, BMJ 2013:347).

The authors looked at studies of the effect of exercise on mortality from heart disease, chronic heart failure, stroke or diabetes and found that exercise was either as good as the standard drug treatment or better, except in the case of chronic heart failure.  The results show that exercise can be very effective, although medicine is the usual treatment prescribed (naturally).   

The results also underscore how infrequently exercise is considered or studied as a medical intervention, Dr. Ioannidis said. “Only 5 percent” of the available and relevant experiments in his new analysis involved exercise. “We need far more information” about how exercise compares, head to head, with drugs in the treatment of many conditions, he said, as well as what types and amounts of exercise confer the most benefit and whether there are side effects, such as injuries. Ideally, he said, pharmaceutical companies would set aside a tiny fraction of their profits for such studies.

But he is not optimistic that such funding will materialize, without widespread public pressure.

The bottom line is that we already know exercise is good for you, don't we?**  It is problematic that we yet need 'far more information', the usual researcher's plaint.  How many details do we need to know about, already knowing that they are largely ephemeral, when there are actual serious unanswered disease questions that we might study?  If half or more of diseases are in a sense treatable, preventable, or delayable with exercise rather than drugs, MRIs and CAT scans, surgery or other approaches, then why do we still allow doctors to meddle as much as they do?  Why do we still have to spend public funds, essentially to feed schools of public health, to keep on doing what are essentially retreads of the same old studies (with fancier and costlier statistical packages and other exciting technologies to make us seem wise and innovatively insightful)--when there are real, devastating disease problems with real unknowns that could be addressed more intensely? 

This is not to mention how much disease would be reduced if we had the societal guts to address poverty.  Real unsolved disease problems may be harder to design studies to understand, actually requiring new thinking rather than just designing some new sampling and questionnaires and the like.  But at least it would be a more real kind of 'research'.

One answer is that this is how the system, and what is basically its rote means of self-perpetuation works.  Science is a social phenomenon not just an objective one.  An institutionalized system doesn't insist on moving beyond essentially safe problems that we have a sufficient knowledge of, to face up to ones we don't yet understand.  That's riskier for professors needing salaries and publications, and administrators needing the overhead funding.  It's part of the fat in the system.

And fat, as we've known since Hippocrates, isn't good for you!


** Actually, despite this post, no, we don't really know this that quite as clearly as you might think!  We do certainly have lots of good mechanistic and physiological reasons why exercise is good, but some fraction of the association of exercise with health may be due to confounding: those who exercise are already healthier than average, or know or care more bout health, or they wouldn't do it (e.g., if they were too overweight, or had troublesome joints, etc.).  So those who exercise are not a random sample. Is it the exercise itself that does them good?   In any case, Galen thought so: he went to the gym regularly because he knew it was good for him!

What domestication can and can't tell us about evolution

Domestication is the harnessing of one species by and for the benefit of another, usually via selective breeding. Humans are master domesticators, but we're not the only ones.  There are ants that farm fungi, and milk aphids, but it has also been suggested that the Melissotarsus ant in continental Africa and Madagascar has domesticated a scale insect for its meat but if not for meat, some other nutritional benefit such as of waxy secretions from the scale insect. Whether these ant/domesticate relationships depend on genetic changes is not clear, at least to us.

Two key differences are, first, that humans work teleologically, or so we assume!  That is, the 'artificial selection' that the domesticators had some end in mind--more yield, more easy harvestability, drought resistance, and so on.  Secondly, we presume that in the past, as now, this process involved not just purposive breeding, but strong selection -- much faster and more directed than natural selection.  If domestication was slow or inadvertent, then the resulting genetic picture may differ.

Humans appear to have begun to domesticate plants and animals ~12,000 years ago, and a new review in Nature Reviews Genetics ("Evolution of crop species: genetics of domestication and diversification," Meyer and Purugganan, online 18 Nov 2013) reports that recent work has identified genetic signatures of that artificial selection in plants, and of subsequent diversification of these crops.  These studies "reveal the functions of genes that are involved in the evolution of crops that are under domestication, the types of mutations that occur during this process and the parallelism of mutations that occur in the same pathways and proteins, as well as the selective forces that are acting on these mutations and that are associated with geographical adaptation of crop species."

Charles Darwin, of course, based much of his argument about evolution and natural selection in The Origin of Species on observations about artificial selection from the breeding of plants and animals for food.  He writes of this explicitly in these frequently quoted words from his autobiography:

..After my return to England it appeared to me that by following the example of Lyell in Geology, and by collecting all facts which bore in any way on the variation of animals and plants under domestication and nature, some light might perhaps be thrown on the whole subject. My first note-book was opened in July 1837. I worked on true Baconian principles, and without any theory collected facts on a wholesale scale, more especially with respect to domesticated productions, by printed enquiries, by conversation with skilful breeders and gardeners, and by extensive reading. When I see the list of books of all kinds which I read and abstracted, including whole series of Journals and Transactions, I am surprised at my industry. I soon perceived that selection was the keystone of man's success in making useful races of animals and plants. But how selection could be applied to organisms living in a state of nature remained for some time a mystery to me.

Fifteen months after I had begun my systematic enquiry, I happened to read for amusement Malthus on Population, and being well prepared to appreciate the struggle for existence which everywhere goes on from long-continued observation of the habits of animals and plants, it at once struck me that under these circumstances favourable variations would tend to be preserved, and unfavourable ones to be destroyed. The result of this would be the formation of a new species.

Here, then, I had at last got a theory by which to work; but I was so anxious to avoid prejudice, that I determined not for some time to write even the briefest sketch of it.   

Indeed, after the Origin, Darwin published two hefty volumes of the effects of artifical selection on plants and animals.

Now, in a modern parallel, Meyer and Purugganan argue that understanding of the genetic underpinnings of domestication can shed light on evolutionary processes, in general, specifically because domesticated crops are recent, selection was strong, and (presumably) consistently directional, and there is good archaeological and historic evidence of the origin, spread and diversification of domesticated crops.

Humans first began to domesticate plants about 12,000 years ago in the Middle East and Fertile Crescent, but plants were also domesticated elsewhere, in China, Mesoamerica, South America, sub-Saharan Africa, and North America from 10,000 to 6000 years ago as well.  Many of these were independent of each other, and involved totally different species, providing, in principle at least, multiple independent views of the genomic aspect of the process.  Artificial selection often involves genetic changes that reduce a plant's fitness in the wild, and species that are completely domesticated cannot survive without human intervention in their reproduction and growth. The process may be rapid, or may take thousands of years.

After domestication, in the "improvement phase", the species can diversify and spread, involving genetic and phenotypic changes that allow adaptation to different ecosystems and climates, generally as a response to selection pressure on chosen traits.  Many such traits have been selected for, but generally they have to do with increasing quality, yield and ease of farming.  Milk yield in dairy animals, tameness or ability to reproduce under domestication, for example.  Or, in grasses, the evolution of larger seeds than in wild grasses, and crucially, a non-shattering rachis.

Commonly observed traits accompanying domestication and diversification; Table 1, Meyer and Purugganan, 2013

When wild wheat is ripe, for example, the rachis (the stem on which the wheat shafts grow) easily shatters, allowing seeds to disperse in a wind or when otherwise disturbed.  This wouldn't be desirable in a crop plant, which the farmer wants to be able to harvest at his or her chosen time, and domesticated wheat has a history of selection for a less brittle rachis so that the seed remains in situ until ready for harvest.
 

Hulled wheat vs free-threshing wheat (wild vs domesticated); Wikimedia

Genes associated with domestication and diversification have been identified with fine-mapping or GWAS, primarily in maize and rice, although, say Meyer and Parugganan, identifying causal mutations has been difficult, although some functional studies have been done.  In addition, they point out, it can be difficult to distinguish mere correlation with domestication and diversification with causation. 

The first "domestication gene" identified was teosinte branched1 (tb1) which is responsible for differences in the shoot of wild and domesticated maize.  Not all changes can be traced to a single gene, however.  Hundreds of domestication genes and loci have been identified in other plants as well, largely in cereal crops, although, for many of the same reasons that genes 'for' disease and other traits can be hard to identify, the specific genes responsible and their functions are often difficult to narrow down--just as we have trouble finding 'the' gene or genes 'for' human traits. 

Architecture of domesticated maize vs wild teosinte; Doesbley, 2003

Even with complications, however, Murray and Parugganan evaluate the role in domestication or diversification of 60 specific genes that have been functionally validated and/or included in population genetic studies.  They note that many of these are regulatory genes that control the timing, amount, or cell-context of the gene's usage.  And, many of the genetic changes correlated with domestication and diversification are nonsense mutations or frameshift indels that alter the protein coded for by a gene, and result in the "large phenotypic effects that are observed during crop evolution."

Among the genes the authors identify with domestication are those involved in regulation of inflorescence development (an inflorescence is the cluster of flowers on a stem that will become seeds; see image above), vegetative growth habit and height, seed pigment, size, casing, nitrogen access and efficiency, and fruit flavor in strawberry, and so forth. Diversification genes include those involved in fruit shape and size, inflorescence architecture, color, starch composition, dwarfism, flowering time, and more. 

It is difficult to know whether a mutation is a precursor to domestication or diversification, or simply happened to arise at around the same time.  People might have noticed a precursor and chosen to breed it, for example.  Some are present in the wild plant but at much lower frequency than in the cultivated plant, which suggests that it, in conjunction with other genetic changes, may be associated with domestication. 

It's possible that because domestication is selection on a trait not a gene, the underlying genetic architecture of a trait is different in different species.  This is certainly true for many phenotypes not related to domestication, so wouldn't be unexpected.  Murray and Parugganan suggest that finding such parallelisms can explain the genetic basis for Darwin's idea of "analogous variations" and for Russian botanist and geneticist of the early 20th century, Nikolay Vavilov's idea of the Law of Homologous Series (I can't resist noting here that Gary Nabhan writes beautifully about Vavilov's life and work in his 2009 book, "Where Our Food Comes From: Retracing Nikolay Vivilov's Quest to End Famine").  This can happen by phenogenetic drift, or by parallel evolution.

This paper is an excellent reprise of the state of knowledge of crop domestication -- with one quibble. Murray and Parugganan write that "Domestication provides a fascinating model for the study of evolution..."  Darwin thought so, too, but artificial selection, the basis for domestication, is directed, strong, and often fast.  Not only is natural selection generally much weaker, but it is not directed and evolution by natural selection is typically slow.  With complex causation, strong selection should often have very different genomic consequences compared to weak selection -- the former being more single-gene or at least simpler in nature.  But even with relatively simple causation that could be picked out at a specific gene level by artificial selection, slow natural selection may not be so gene-specific.

In addition, much of evolution seems not to happen by natural selection but instead by genetic drift or other forms of selection (organismal selection, niche selection, and so forth), while domestication is due to strong, directed artificial selection.  Thus, the lessons of domestication aren't always a good model for evolution in general.

Indeed, while Darwin thought of domestication as a good model, Alfred Wallace, the co-discoverer of evolution did not.  He noted, in his letter read to the Linnean Society ("On the Tendency of Varieties to depart indefinitely from the Original Type"), in 1858 along with Darwin's, announcing their co-discovery,

     One of the strongest arguments which have been adduced to prove the original and permanent distinctness of species is, that varieties produced in a state of domesticity are more or less unstable, and often have a tendency, if left to themselves, to return to the normal form of the parent species; and this instability is considered to be a distinctive peculiarity of all varieities, even of those occurring among wild animals in a state of nature, and to constitute a provision for preserving unchanged the originally created distinct species....

     It will be observed that this argument rests entirely on the assumption, that varieties occurring in a state of nature are in all respects analogous to or even identical with those of domestic animals, and are governed by the same laws as regards their permanence or further variation.  But it is the object of the present paper to show that this assumption is altogether false, that there is a general principle in nature which will cause many varieties to survive the parent species, and to give rise to successive variations departing further and further from the original type, and which also produces, in domesticated animals, the tendency of varieties to return to the parent form.

Selection is a far more curious phenomenon than it is typically given credit for being.  It is too easy for us to compress time in our minds and think of natural selection as if it were artificial, strong and directed.   But the beasts and foliage of nature may, like a Rousseau painting, be a thicket of meandering change, sometimes for inscrutable reasons.

Sometime geneticist Joe Terwilliger on genetics

We may recently have given the false impression that geneticist Joe Terwilliger gives less priority to science, or at least good science, than to other perhaps more frivolous pursuits (he is Abe Lincoln every February, for example, and tuba player the rest of the time -- unless he's cleaning up bean debacles as a diplomat, or being a basketball and language coach to Dennis Rodman), so we wanted to help correct any such misconceptions here.  Perhaps to that end, Joe (now known in South Korea, we're afraid, as "sometime geneticist Joe Terwilliger") suggested we republish a blog post he first posted on his own short-lived blog in 2008.  He recently dug this up again and says that few could disagree, even 5 years later.

Joe as Abe on the balcony (but not of Ford's Theater)

The point is that sometimes there is a lot of convenient hard-of-hearing even in science, which fancies itself to be an objective search for truth. Some of the details in Joe's post are out-of-date but we, and he, think that the basic thrust is not.  In a sense that makes the conclusion all the more cogent, because the same modes of thinking about genomic causation are still predominant, despite the vastly costly but essentially consistent results in the five years since 2008.  And, as Joe points out, he and Ken had much the same message in 2000.

One not-so-subtle change, we will note, is that promises by NIH Director Francis Dr Collins, and many others in presumably responsible positions, have steadily altered  their due date, which recedes into the distance like, say, an oasis as you grope for water, the fences if you want your pitchers to have a better earned run average, or a preacher's promises of ultimate salvation, if you weekly plunk coins into the basket.

So perhaps the lesson is that under these circumstances, rather than just dismiss critics, science--actual science as it's supposed to be--should feel a need to take stock of what it's doing.  But we leave it to you to judge.

And if you hear about Joe in other contexts in weeks to come, remember that he was a sometime geneticist here first:


The Rise and Fall of Human Genetics and the Common Variant - Common Disease Hypothesis
By Joe Terwilliger
Nov 2008

There is an enormity of positive press coverage for the Human Genome Project and its successor, the HapMap Project, even though within the field the initial euphoric party when the first results came out has already done a full 180 to be replaced by the hangover that inevitably follows such excesses.

For those of you not familiar with the history of this field and the controversies about its prognosis which were present from the outset, I refer you to a review paper I and a colleague wrote back in 2000 at the height of the controversy - Nature Genetics 26, 151 - 157 . The basic gist of the argument put forward for the HapMap project was the so-called common variant/common disease hypothesis (CV/CD) which proposed that "most of the genetic risk for common, complex diseases is due to disease loci where there is one common variant (or a small number of them)" [Hum Molec Genet 11:2417-23]. Under those circumstances it was widely argued that using the technologies being developed for the HapMap project, that one would be able to identify these genes using "genome-wide association studies" (GWAS), basically by scoring the genotype for each individual in a cross sectional study for each of 500,000 to 1,000,000 individual marker loci - the argument being that if common variants explained a large fraction of the attributable risk for a given disease, that one could identify them by comparing allele frequencies at nearby common variants in affected vs unaffected individuals. This point was contested by researchers only with regard to how many markers you might have to study for this to work if that model of the true state of nature applied. Many overly optimistic scientists initially proposed 30,000 such loci would be sufficient, and when Kruglyak suggested it might take 500,000 such markers people attacked his models, yet today the current technological platforms use 1,000,000 and more markers, with products in the pipelines to increase this even more, because it quickly became clear that the earlier models of regular and predictable levels of linkage disequiblrium were not realistic, something that should have been clear from even the most basic understanding of population genetics, or even empirical data from lower organisms.

Today such studies are widespread, having been conducted for virtually every disease under the sun, and yet the number of common variants with appreciable attributable fractions that have been identified is miniscule. Scientists have trumpetted such results as have been found for Crohn's disease, in which 32 genes were detected using panels of thousands of individuals genotyped at hundreds of thousands of markers - this sounds great until you start looking at the fine print, in which it is pointed out that all of these loci put together explain less than 10% of the attributable risk of disease, and for various well-known statistical reasons, this is a gross overestimate of the actual percentage of the variance explained. Most of these loci individually explain far less than half a percent of the risk, meaning that while this may be biologically interesting, it has no impact at all on public health as most of the risk remains unexplained. This is completely opposite to the CV/CD theory proposed as defined above. In fact, this is about the best case for any complex trait studied, with virtually every example dataset I have personally looked at there is absolutely nothing discovered at all.

At the beginning of the euphoria for such association studies, the example "poster child" used to justify the proposal was the relationship between variation at the ApoE gene and risk of Alzheimer disease. In an impressively gutsy paper recently, a GWAS study was performed in Alzheimer disease and published as an important result, with a title that sent me rolling on the floor in tears laughing: "A high-density whole-genome association study reveals that APOE is the major susceptibility gene for sporadic late-onset Alzheimer's disease" [ J Clin Psychiatry. 2007 Apr;68(4):613-8 ] - in an amazingly negative study they did not even have the expected number of false positive findings - just ApoE and absolutely nothing else... And the authors went on to describe how important this result was and claimed this means they need more money to do bigger studies to find the rest of the genes. Has anyone ever heard of stopping rules, that maybe there aren't any common variants of high attributable fraction??? This was a claim that Ken Weiss and I put forward many times over the past 15 years, and Ken has been making this point for a decade before that even, in his book, "Genetic variation and human disease", which anyone working in this field should read if they are not familiar with the basic evolutionary theory and empirical data which show why noone should ever have expected the CV/CD hypothesis to hold...

In many other fields, the studies that have been done at enormous expense have found absolutely nothing, and in what Ken Weiss calls a form of Western Zen (in which no means yes), the failure of one's research to find anything means they should get more money to do bigger studies, since obviously there are things to find but they did not have big enough studies with enough patients or enough markers - it could not possibly be that their hypotheses are wrong, and should be rejected... It is a truly bizarre world where failure is rewarded with more money - but when it comes to promising upper-middle-aged men (i.e. Congress) that they might not die if they fund our projects, they are happy to invest in things that have pretty much now been proven not to work...

While in a truly bizarre propaganda piece, Francis Collins, in a parting sycophantic commentary (J Clin Invest. 2008 May;118(5):1590-605) claimed that the controversy about the CV/CD hypothesis was "... ultimately resolved by the remarkable success of the genetic association studies enabled by the HapMap project." He went on to list a massive table of "successful" studies, including loci for such traits as bipolar, Parkinson disease and schizophrenia, and of course the laughable success of ApoE and Alzheimer disease. To be objective about these claims, let me quote from what researchers studying those diseases had to say.

Parkinson disease: "Taken together, studies appear to provide substantial evidence that none of the SNPs originally featured as PD loci (sic from GWAS studies) are convincingly replicated and that all may be false positives...it is worth examining the implications for GWAS in general." Am J Hum Genet 78:1081-82

Schizophrenia: "...data do not provide evidence for involvement of any genomic region with schizophrenia detectable with moderate [sic 1500 people!] sample size" Mol Psych 13:570-84

Bipolar AND Schizophrenia: "There has been great anticipation in the world of psychaitric research over the past year, with the community awaiting the results of a number of GWAS's... Similar pictures emerged for both disorders - no strong replications across studies, no candidates with strong effect on disease risk, and no clear replications of genes implicated by candidate gene studies." - Report of the World Congress of Psychiatric Genetics.

Ischaemic stroke: "We produced more than 200 million genotypes...Preliminary analysis of these data did not reveal any single locus conferring a large effect on risk for ischaemic stroke." Lancet Neurol. 2007 May;6(5):383-4.

And the list goes on and on of traits for which nothing was found, with the authors concluding they need more money for bigger studies with more markers. It is really scary that people are never willing to let go of hypotheses that did not pan out. Clearly CV/CD is not a reasonable model for complex traits. Even the diseases where they claim enormous success are not fitting with the model - they get very small p-values for associations that confer relative risks of 1.03 or so - not "the majority of the risk" as the CV/CD hypothesis proposed.

One must recall that in the intial paper proposing GWAS by Risch and Merikangas (Science 1996 Sep 13;273(5281):1516-7) - a paper which, incidentally, pointed out that one always has more power for such studies when collecting families rather than unrelated individuals - the authors stated that "despite the small magnitude of such (sic: common variants in)genes, the magnitude of their attributable risk (the proportion of people affected due to them) may be large because they are quite frequent in the population (sic: meaning >>10% in their models), making them of public health significance." The obvious corollary of this is that if they are not quite frequency, they are NOT having high attributable fraction and are therefore NOT of public health significance.

And yet, you still have scientists claiming that the results of these studies will lead to a scenario in which "we will say to you, 'suppose you have a 65% chance of getting prostate cancer when you're 65. If you start taking these pills when you're 45, that percent will change to 2". Amazing claims when the empirical evidence is clear that the majority of the risk of the majority of complex diseases is not explained by anything common across ethnicities, or common in populations... (Leroy Hood, quoted in the Seattle Post-Intelligencer). Francis Collins recently claimed that by 2020, "new gene-based designer drugs will be developed for ... ALzheimer disease, schizophrenia and many other conditions", and by 2010, "predictive genetic tests will be available for as many as a dozen common conditions". This does not jibe with the empirical evidence... In Breast Cancer for example, researchers claimed that knowledge of the BRCA1 and BRCA2 genes (which confer enormously high risk of breast cancer to carriers) was uninteresting as it had such a small attributable fraction in the population. Of course now they have performed GWAS studies and examined tens of thousands of individuals and have identified several additional loci which put together have a much smaller attributable fraction than BRCA1 and BRCA2, yet they claim this proves how important GWAS is. Interesting how the arguments change to fit the data, and everything is made to sound as if it were consistent with the theory.

I suggest that people go back and read "How many diseases does it take to map a gene with SNPs?" (2000) 26, 151 - 157. There are virtually no arguments we made in that controversial commentary 8 years ago which we could not make even stronger today, as the empirical data which has come up since then basically supports our theory almost perfectly, and refutes conclusively the CV/CD hypothesis, despite Francis Collins' rather odd claims to the contrary...

In the end, these projects will likely continue to be funded for another 5 or 10 years before people start realizing the boy has been crying wolf for a damned long time... This is a real problem for science in America, however, as NIH is spending big money on these rather non-scientific technologically-driven hypothesis-free projects at the expense of investigator-initiated hypothesis-driven science. Even more tragically training grants are enormously plentiful meaning that we are training an enormous number of students and postdocs in a field for which there will never be job opportunities for them, even if things are successful. Hypothesis-free science should never be allowed to result in Ph.D. degrees if one believes that science is about questioning what truth is and asking questions about nature, while engineering is about how to accomplish a definable task (like sequencing the genome quickly and cheaply). The mythological "financial crisis" at NIH is really more a function of the enormous amounts of money going into projects that are predetermined to be funded by political appointees and government bureaucrats rather than the marketplace of ideas through investigator-initiated proposals. Enormous amounts of government funding into small numbers of projects is a bad idea - one which began with Eric Lander's group at MIT proposing to build large factories for the sequencing of the genome rather than spreading it across sites, with the goal of getting it done faster (an engineering goal) instead of getting more sites involved so that perhaps better scientific research could have come along the way. This has led to a scenario years later in which the factories now want to do science and not just engineering, which is totally contrary to their raison d'etre, and leads to further concentrations of funding in small numbers of hands when science is better served, perhaps by a larger number of groups receiving a smaller amount of money so that more brains are working in different directions thinking of novel and innovative ideas not reliant on pure throughput. Human genetics has transformed from a field with low funding, driven by creative thinking into a field driven by big money and sheep following whatever shepherd du jour is telling them they should do (i.e. innovative means doing what they current trend is rather than something truly original and creative). This is bad for science, and also is bad science. GWAS has been successful technologically, and it has resoundingly rejected the CV/CD hypothesis through empirical data. If we accept this and move on, we can put the HapMap and HGP where it belongs, in the same scientific fate as the Supercollider, and let us get back to thinking instead of throwing money at problems that are fundamentally biological and not technological!

(most notably in terms of the big money NIH is sending into these non-scientific technologically-driven hypothesis-free studies, rather than investigator initiated hypothesis-driven science - one of the main causes of the "funding crisis" at NIH where a tiny portion of new grants are funded - get rid of the big science that is not working - like the supercollider! - and there is no funding crisis)