Science vs "Science"

It's got a lot to do with how you get your information, whether you trust science or not. And it's got a lot to do with whether you're exposed to real science or "science."

Like this "science"...



This product has been "proven by science," so we're fools not to buy it! I find that if I'm not watching a Nova or Nature or an episode of anything with Morgan Freeman or Stephen Hawking, most everything else that talks of science on the television is trying to sell me something. Most everything else is "science."

It seems like every beauty product advertisement is using "science" to convince me that I'm butt ugly and that to fix it (or prevent it from worsening) I should give them my perfectly good dollars. It's "science" after all.

I'm kind of stunned that it's legal for for-profits to cry "science" when it's their own study, when they merely asked opinions as evidence for effectiveness, or when they didn't do any studies at all. Science isn't allowed to be so biased. Science is supposed to want to improve your life first and foremost, not con you out of your money.

I'm not just thinking about this today because I've been hibernating this February, plopped in front of the tube, absorbing horrifying beauty ads through my aging, sagging wrinkled face. (I really should take care of it better by smearing money all over it.) I'm thinking about all this right now because of my friend Alice Roberts's nice piece "Childbirth: why I take the scientific approach to having a baby" posted on the Guardian Saturday.

Trends to move childbirth out of the hospital setting have put pressure on mothers and fathers to make decisions about what to do when it's time for theirs. You'd assume that because there's a movement to move things home that it's because some smart, science-minded, compassionate folks have figured out that it's healthier. If you can't stand the draconian and bloated government/insurance mogul-run healthcare system, a movement might feed your existing suspicions or opinions that there could be better ways to have a baby than by blindly following orders that these profit-motivated fascists at hospitals bark at us. 

But why assume that home childbirth folks are any less biased, less vested, less driven by self-interests? I don't know but it just seems so common for people to give rebels the benefit of the doubt more often than tradition, than institutions. (Something about "honest signaling" might have just popped into your mind if you've been trained in evolutionary theory.) What Alice found is that information on, that is, data or evidence for, what's healthiest--home or hospital or otherwise (birthing centers, for example)--is kind of difficult to come by!

For starters, she writes, 

"This is partly because the overall risks of maternal and neonatal death are now very small (about five per 100,000 women die in childbirth and four per 1,000 babies), so large numbers of mums are needed to assess relative risks. Maternity provision differs between countries, so looking at risks in other countries, even in Europe and the US, may not be terribly helpful."

Within that small risk there is a lot of jockeying for your support. So the second reason, she says, that makes it hard to find information is, 

"the politics of birth. It can be quite hard for mums-to-be to access impartial evidence and advice when it seems there are plenty of people wanting to influence your decision in one way or the other. Evangelical advocates of home birth often talk about the importance of women's choice and empowerment, as well as instilling distrust in obstetricians. For me, being empowered to make a decision requires access to good evidence and the freedom to make up my own mind. And whilst "maternal satisfaction" is often put forward as an important factor to be taken into consideration, I want to know what the relative risks are. And if there's not yet enough evidence to assess that – I want to know that too."

You'd think we all do. You'd think we all want to know the answer to "where and how will the risks be lowest for having my baby?" But we don't all hold  the belief that it's our right to know the answer to that, the way Alice knows it is, the way Alice demonstrates that it is. And it's not just an issue about the dissenters and the movements spinning information and evidence so we'll see things their way--a very real problem that Alice walks us through in the article. It's the doctors too.

Since the article's been posted in various places I've seen commenters complain how they asked their doctors for papers and numbers to help them make their birth plans and the doctors wouldn't go there. I've never had to make a birth plan but I've had similar experiences with doctors like when, for example, I asked for non-hormonal birth control options because I saw no reason to continue ingesting the stuff when the risks for long-term use aren't known and I was now married and ready to stop taking the pill. My doctor laughed at my question, laughed when I asked for a diaphragm or anything like it, and tried to convince me without any scientific evidence that the pill was fine to take your whole life.

Do I think medical decisions should lie completely in patients' hands? Of course not. We can't all be doctors. But they've got to be better ambassadors of science. They've got to be the best. They've got to be science.

It can't be up to us to figure it out for ourselves, not just because we shouldn't have to but because some of us are terrible at it when we try. This includes bright young people at my university, one for example who had a whole textbook on reproductive biology to answer this homework essay question: Write the life story of an egg. Because she cited it, I know that instead of using her high quality resource, she went straight to livestrong.com for all of her information.

Because of movements like the anti-vaccinators and all the people without celiac disease who won't eat gluten, it's easy to worry that unscientific trends with birth will dial back mortality rates to medieval ones. Heck, it's tempting to worry that when videos like this get around to some people who love all things PALEO, they will make it so.

No wonder so many of us can't trust climate scientists and evolutionary scientists. When it comes to our health, "science" has an agenda that's not always first and foremost what's best for us. When it comes to our beauty, "science" smells like money. If this is all we know of "science" then I'm less surprised of the push back against biology, ecology, climate, space exploration, etc... that to us scientists seems downright ridiculous.

If we're going to get non-scientists on board with real science, we need to take the word back.

The mouse that roared, or the lion that peeped?

The Mouse that Roared was a funny comedy film, decades ago, about a little Alpine principality (the Duchy of Grand Fenwick) that managed to bring the US to its knees, to win major concessions.  The idea was to declare war on us, to lose, and then be the beneficiary of all the largesse we dump on those we defeat.

In science as in other areas of human endeavor, especially in a society slavishly obsessed with the 'business model' and 'competitiveness' and the bottom line--even in universities, we want to get the most bang for the buck as this little mouse of a country did by roaring at the huge US.  Science as it is practiced today raises some relevant issues.

The other day we criticized a very big study about calcium intake and heart disease risk, and it was but one of many critiques we have made again and again (and again) here on MT.  Our point was that sloppy designs and non-definitive results, that have to be repeated again and again (and again) with ever larger scales and for ever larger budgets, are becoming more of the rule than the exception.

In our areas of (we hope) knowledge, we blog away at the practice of ever increased scale for ever diminished payoff.  Examples are massive GWAS to find hundreds of miniscule, ephemeral possibly-causal genetic effects.  Despite fervent denials and claims of success, that's what's afoot in biomedical and other sciences.  It's the way we build careers, maintain labs and reputations, and earn our nice academic salaries.

But that is not the same as roaring lions of discovery.  Real progress.  We need ever larger, ever repeated studies because what we're trying to find are unclear, non-definitive, or (generally) minor effects.  It is more like fiscal lions generating peeps of results (but then roaring about them as if they were lions).

This kind of hyperbole is in the science news every day.  Indeed, the fact that there is a science news is part of the story, because the news outlets need to sell and the news needs stories, and investigators need the publicity to get their grants and make their careers, so we have a positive-feedback system where the big begets bigger, and the brag begets bragger.  We have come to something ColdWar-like: Mutually Assured Dependence.

As in the other day's post's example, larger and larger studies are needed if the effects we want to find are smaller and smaller.  And that also generally means that they are part of complex interactions in multi-factorial causal systems.  A small cause's effect depends on the other causes present or not present.  Even a cause that's always present, but is small, requires large studies to detect.

By contrast, truly major causes can be detected, replicably and reliably by small studies, that don't cost that much money and don't have to be endlessly repeated.  They are the mice that roar.  The late curmudgeonly David Horrobin said something to the effect that if you can't find it in samples of 30, it's not worth finding.  That's an exaggeration....but how much of one?

But our culture today is about spawning nearly mute lions.  We harp on this because lots of your money is paying for this kind of research.  Instead, we should be able to  provide smaller funding to more people, hoping somebody will make lucky or insightful discoveries, or being less socialistic, we could really pour funds at problems that really are genetic or more clearly addressable with accountable impact in the case of  public health or evolutionary science.  Maybe truly genetic diseases could be prevented or cured more effectively and more quickly if we did that.

Nothing's perfect.  First, pouring money into what should be soluble problems could be like the War on Cancer and other government allotments:  There may only be so many good researchers, and they may already be funded, for these problems.  And, as is manifestly clear, anytime there is a pot of dough, the hogs rush frantically to the trough so one would have to have strong constraints so the funds don't get divided up among a crowd of claimants generating chaff.  In fact, this is how the system largely works now, with me-too being a major modus operandi. And, ironically, those who would rail against socializing funding (equalizing distribution, etc.) may not realize that to a great extent that is what our system currently does.  It's how all the med schools keep their research factories in operation 24/7--by investigators flocking to wherever the funds are, inventing whatever rationales for their own ideas that we can think of.  In a way, because it is also intensely competitive, it is a form of capitalistic socialism, a strange beast!

Instead, we build empires of hoarse lions, omitting the potentially much more cost-effective mice who, like humble miners' canaries, could lead us out of the most troubling problems we face.

The shelf life of a banana

We're in New York where I'm working with collaborators on a project in which we're developing  software to simulate complex genetic systems, so that knowing the 'truth' we can investigate some of the  questions being pursued these days in both epidemiological and evolutionary genetics.  Simulations don't generate actual reality, but when they generate what is very similar, one can hopefully make inferences about the truth, and in this arena the truth is in some ways unknowable.  The idea of simulation is to improve our ability to guess the truth from data, when things are complex as they clearly are here.

For some years our collaborators (Joe Terwilliger and Joe Lee at Columbia University) have been saying that much of the discussion of problems is needlessly about  limitations in the available genetic data.  GWAS and other similar genomic approaches to the genetic causes of traits like disease, and the results of evolution, have used increasingly extensive kinds of data.  For example, more sites of the genome are used to try to infer causation in parts of the genome that are near to those sites (we can refer to these as 'mapping markers').

Genetics has been going from one fad to another.  We first had mapping with limited sets of markers, that suggest regions of the genome that could be causally involved in some question (like adaptation to diet, or the risk of diabetes).  But the implicated regions of the genome were large, and many functional elements are in the region.  We couldn't easily identify the actual causal site or sites in the region.

Then someone discovers that there is more use of the genome than as an intermediate code for protein (that's messenger RNA, mRNA), but the RNA itself has direct function; some, called microRNA, (miRNA) affects the translation of mRNA into protein.  Someone else discovers that gene regulatory sites are important in the genome to control the expression of protein-coding regions.  Somebody else probes interactions among genes, claiming that these 'networks' are higher-order functional units.  Then it's found that chunks of DNA are duplicated or lost in some people but not others (called 'copy number variation', or CNV). Others explore the modification of DNA by various chemical means in cells, that affect which genes are expressed; this is called 'epigenetics'.

All of these things become 'omicizied--in the scramble for money, attention, and yes, even to actually do some real science, analytic platforms are developed for detecting these various elements in the genome: special genomewide tests for epigenetic sites, or non-coding RNA, or rapid sequencing methods for the protein-coding parts of the genome (called 'exome sequencing').

Many people recognize that these are temporary stop-gaps.  In part, those who think that CNV will be the killer-discovery that explains a huge fraction of the cause of diabetes or autism, or that miRNA is the key to regulation, argue about and develop special molecular and statistical tools for detecting it.

Even those specializing in one or another of these fads, or subsets of genetically related causation, know that the tools are rather temporary.  The individual applications are discovering complex causal elements, but everyone knows that in total they still promise only to account for a fraction of causation of the traits of interest.  They are holding actions, and this is openly acknowledged.  They keep the funds and research moving, and feed the technology companies, so they can develop the next level to genomic methods.  We know this, but we are institutionalized so we can't wait for better tools.  We must keep the factories moving with these methods.

But they have the shelf-life of a banana.

It's easy, and perhaps correct, to be cynical of the great hype machinery that keeps the system in high gear.  It's costly, but we need to be paid, the tech companies need to sell something today while they develop a tool for tomorrow.  We need to keep the graduate student pipeline flowing.

For years in our various talks and mini-courses and papers, Joe Terwilliger and I have been saying that rather than spending too much time arguing about the best way to use and analyze these kinds of bananas, we should just assume that whole genome sequences will be available for everybody in the population. Given the lock that the science establishment has on funds, and the way that technology makes serious increases in the amount of data we can generate and analyze, and the way that leads to drop in cost, it seems likely that barring international catastrophe, ubiquitous sequence data will be available.

This is now viewed by some as a kind of inevitable end point: finally we'll have all the data we need from a genomic point of view, and we can then really, truly, identify all the genetic causation that is involved in diabetes, cancer, how you vote, or whether you respond negatively to being sexually abused.

There are a couple of problems with this view.  First, the system will need to continue to produce and sell new gear, so clearly new things will be discovered that need documentation.  That itself means that even whole genome sequencing is likely to have the shelf life of a banana.  The kinds of things we measure will be shown to be incomplete, and in that sense 'out of date'.  The way we measure the trait--like diabetes or cancer--will be elaborated in this way, so that prior measures will be denigrated as primitive.  We'll have to do the same megastudies over again.

But no matter how comprehensive these tools and data will become--and some have already gone beyond genes, even whole genomes, to enumeration of all cellular processes and so on, as though in recognition that genomes really aren't the answer, but that the research machinery must march on--they will not in themselves solve the main issue that we face:  causation is often clearly complex, changeable, statistically elusive, and not really reducible to an enumerable set of causes.  In addition to making sure that each step is only a partial step--rarely if ever reaching the point where something is actually 'solved' (because that would put us out of business)--we have not really come to grips with the fluid and complex nature of causation of the traits we're interested in.

The more contributing 'causes' there are for a trait, and the weaker that each is on its own, the more unstable their actual effects will be, and the harder to estimate accurately, the less useful such estimates will be as predictors.  In a sense, the trait may be the same, but its causes always substantially different.  The problem is dealing with the trait, rather than attempting to enumerate its ephemeral causes.  How to do that is for the future, if we would really come to grips with it.  That, we think, is where real innovation, rather than the kinds of technical improvements that are steadily being made, will have to come.

Whether in a population that is already 7 billion strong, it will be good to continue to nibble away at the causes of traits that affect us as we age, or whether we'll just be creating countless new problems due to stress on resources and so on, is essentially a philosophical question.

The "Me!" parade, or is there a better way to think about funding realities?

So, proposed new budgets are suggesting a $1.6 billion, or 5% or so cut in NIH research funding.  What we've seen in regard to the NSF budget is somewhat different: it may increase modestly, but with the  funds clearly targeted to investment in science interactions,  infrastructure, and education. These seem reasonable and not parochial, but of course NSF budgets are generally much less than NIH grants, and less often cover faculty salaries the way NIH does.

We knew about the NIH proposal because as soon as the proposed budget cuts were announced, we've been besieged by the "Me!" parade of  'urgent'  messages from professional societies urging us (with nice assistance in the form of convenient links) to write our congressmen in outrage, to protest the very nerve of suggesting that research take a hit!

But why does this instant email lobbying go on?  Millions are homeless or even jobless, or have no health care, or have disorders that don't require exotic research to alleviate, and to keep the economy from total free-fall the feds had to go into debt that they now have to figure out how to get out of, and if cuts have to go across the board.  Given this, why can't we be realistic and even good citizens to boot, and realize that a 5% cut in funds is not a cataclysm for science, somewhat less serious than being homeless, and  something to which we should respond to constructively, and with good grace?

If everyone in our society  feels  it's an automatic given that we'll protest anything disadvantageous to our personal selves, we'll descend into more internecine strife than the current situation is going to cause anyway.  Science has grown fat (and complacent?) on grant largess over recent decades, but have we delivered to society in commensurate terms?  Or have we become self-satisfied and ever willing to ask for more, bigger, longer, grander funds for feathering our own nests, with universities and research institutes living on the overhead that we (as their sales force) bring in?  Are the new data and findings in NIH-funded projects--which are very interesting, to be sure--our private playground, or are they really what the public tax base should be used for?  Are measures of public health improving as a result--if they're improving at all?

Investigators will certainly be able to manage, if we must, on less, and we think this could even be good in several ways.  Rather than lobby for more funds, why not lobby for more grants, even if they're smaller, and of shorter duration than they've become?  That way new investigators, young investigators, and people who actually have clever new ideas can have a better chance!  Why not cap the amounts any given lab can have, or stop projects that have been continued too long, or have grown too large, or have reached diminishing returns--and divide the savings up among people who offer something new?  Why not do more centralizing and sharing of costly hi-tech resources, and be more stringent about funding hi-tech but low-thoughtfulness projects?

Maybe schools that have grown fat on overhead with inflated but unpaid (soft-money) faculty, driven to flood the system with relentless grant applications, will have to develop a new sense of socially responsible mission, even if this means shrinking in size, and paying more attention (heavens!) to teaching.  The reversal of a 30-year trend towards growth for its own sake would not be an entirely bad thing. With the current age distribution, phasing back could be done as people retire and simply aren't replaced.  We don't need as many graduate students in an environment that is not able to grow exponentially--even if students are the trophies we like to wave about to demonstrate our importance.

Maybe departments will have to think about importance rather than dollars, when they hire new faculty.  Maybe as we tighten our belts, it will push the blood back to our brains, and the constraint will force new, creative thinking, and a new day for science that is both innovative and socially responsible.

2020 visions, or 20-20 hindsight?

For an article in Nature this week ("2020 Visions"), a number of "leading researchers and policy-makers" were asked to comment on what their field is going to look like in ten years. "We invited them to identify the key questions their disciplines face, the major roadblocks and the pressing next steps."

Well, Nature is a commercial operation, not as unlike, say, People Magazine, as it may wish to be viewed as, and it often looks like it, too. As it does here, since only incremental science can even generally be predicted (for example, that the price of whole-genome DNA sequencing will drop dramatically, and that as a consequence we'll all be hungering to do it in almost any kind of study, whether justified or not). So, this article is essentially free advertising for the respondents. The futuristic bravado is limited, as in a way it must be. But let's suspend our disbelief and see if we can go with their premise for a minute.

The respondents include a university president, an astronomer, a chemist, a paleontologist, a computer scientist, someone from the NIH, a geneticist and so on. We aren't qualified to comment on the specifics of Google's director of research's vision of the future, but we can say, in general, that this is an odd exercise, as prognostication generally turns out to be a wish-list in disguise (right, we can't even go with the premise for a whole minute!). So, prognosticators on the future of personalized medicine, say, are advocating for their own view of the future. Or rather, of the present. One interviewee comments about how rare genetic variation will be found to have much more predictive power for disease than common variants--exactly what one might expect given the failure of 'common' variants to solve all the world's problems, and the next level of ramped-up DNA-variation-based promises that have been growing in recent years, not coincidentally nor disinterestedly along with the technologies being sold for ever-cheaper whole-genome sequences. This is essentially rationalizing for more of the same, since although there may be new findings for disorders with clearly known causal genes, generally rare variants will be very difficult to assign causal effect to (for example, suppose it's only seen in one patient?). So rare variants will not be very useful in public health terms, yet public health funds are going to be demanded for this work. We have to assume that the leading experts in the areas we know a lot less about are doing the same kind of nest-feathering.

Of course, any scientists can each be expected to be excited about, and to want to promote, their own field of interest. If we didn't think it important, it would be depressing to go to work every day. And these days, as things are structured, science is expensive and has become a kind of competitive commercial Get-Grants enterprise. But journalism, even science journalism, should bear the responsibility of calling things by their true names, and asking seriously about vested interests and so on.

But, the Nature piece is provocative in the following sense. A deeply embedded belief (truth?) one hears over and over again about science is that major discoveries over the centuries have been accidental. They can't be planned or predicted. Geniuses must be given free rein to think, tinker, experiment, and their eureka moments will follow.

If this is really true, how likely is it still to happen in today's vested-interest, continuity-driven funding-based arena? Big-money science today is goal-oriented--with the goals often dictated by the patron (NIH, the military, etc.)--and those goals are generally very specific and incremental, with every step carefully planned even years ahead of time. Knowledge is gained, for sure, but it was gained by Victorian beetle collectors, too, which didn't go very far. On the way, unexpected things are certainly to be found, but even they usually are within the incremental rather than conceptually door-opening.

Given the way science is funded these days, that's the way it has to be. So, there's less and less room for real luck and serendipity, as the 'visions' of the 2020 visionaries show in a round-about sort of way. Does this mean no progress will be made? Of course not, but it is a different kind of science.

Personally, we think that centralization of high-cost technology (like high-throughput DNA sequencing), and distribution of more, but smaller though longer-term grants to more different investigators, especially junior investigators, with less detail required in grant proposals, and with promotion and tenure and overhead disconnected from individual grantees' would increase the 'ecological' diversity of science and raise the probability of major new discoveries. Less intense pressure to hustle, more time to think, but there should be eventual accountability and project-termination criteria, too--unlike much of the Big Science that is being constructed, with guarantees of continuity in mind.

Nothing ensures any particular level of dramatic discovery, but as scientists we should want the odds to be as high as possible. Institutionalized enterprize may not be the best way to make that happen.