Thursday, April 20, 2017

Some genetic non-sense about nonsense genes

The April 12 issue of Nature has a research report and a main article about what is basically presented as the discovery that people typically carry doubly knocked-out genes, but show no effect. The idea as presented in the editorial (p 171) notes that the report (p235) uses an inbred population to isolate double knockout genes (that is, recessive homozygous null mutations), and look at their effects.  The population sampled, from Pakistan, has high levels of consanguineous marriages.  The criteria for a knockout mutation was based on the protein coding sequence.

We have no reason to question the technical accuracy of the papers, nor their relevance to biomedical and other genetics, but there are reasons to assert that this is nothing newly discovered, and that the story misses the really central point that should, I think, be undermining the expensive Big Data/GWAS approach to biological causation.

First, for some years now there have been reports of samples of individual humans (perhaps also of yeast, but I can't recall specifically) in which both copies of a gene appear to be inactivated.  The criteria for saying so are generally indirect, based on nonsense, frameshift, or splice-site mutations in the protein code.  That is, there are other aspects of coding regions that may be relevant to whether this is a truly thorough search to see that whatever is coded really is non-functional.  The authors mention some of these.  But, basically, costly as it is, this is science on the cheap because it clearly only addresses some aspects of gene functionality.  It would obviously be almost impossible to show either that the gene was never expressed or never worked. For our purposes here, we need not question the finding itself.  The fact that this is not a first discovery does raise the question why a journal like Nature is so desperate for Dramatic Finding stories, since this one really should be instead a report in one of many specialty human genetics journals.

Secondly, there are causes other than coding mutations for gene inactivation. They have to do with regulatory sequences, and inactivating mutations in that part of a gene's functional structure is much more difficult, if not impossible, to detect with any completeness.  A gene's coding sequence itself may seem fine, but its regulatory sequences may simply not enable it to be expressed. Gene regulation depends on epigenetic DNA modification as well as multiple transcription factor binding sites, as well as the functional aspects of the many proteins required to activate a gene, and other aspects of the local DNA environment (such as RNA editing or RNA interference).  The point here is that there are likely to be many other instances of people with complete or effectively complete double knockouts of genes.

Thirdly, the assertion that these double KOs have no effect depends on various assumptions.  Mainly, it assumes that the sampled individuals will not, in the future, experience the otherwise-expected phenotypic effects of their defunct genes.  Effects may depend on age, sex, and environmental effects rather than necessarily being a congenital yes/no functional effect.

Fourthly, there may be many coding mutations that make the protein non-functional, but these are ignored by this sort of study because they aren't clear knockout mutations, yet they are in whatever data are used for comparison of phenotypic outcomes.  There are post-translational modification, RNA editing, RNA modification, and other aspects of a 'gene' that this is not picking up.

Fifthly, and by far most important, I think, is that this is the tip of the iceberg of redundancy in genetic functions.  In that sense, the current paper is a kind of factoid that reflects what GWAS has been showing in great, if implicit, detail for a long time: there is great complexity and redundancy in biological functions.  Individual mapped genes typically affect trait values or disease risks only slightly.  Different combinations of variants at tens, hundreds, or even thousands of genome sites can yield essentially the same phenotype (and here we ignore the environment which makes things even more causally blurred).

Sixthly, other samples and certainly other populations, as well as individuals within the Pakistani data base, surely carry various aspects of redundant pathways, from plenty of them to none.  Indeed, the inbreeding that was used in this study obviously affects the rest of the genome, and there's no particular way to know in what way, or more importantly, in which individuals.  The authors found a number of basically trivial or no-effect results as it is, even after their hunt across the genome. Whether some individuals had an attributable effect of a particular double knockout is problematic at best.  Every sample, even of the same population, and certainly of other populations, will have different background genotypes (homozygous or not), so this is largely a fishing expedition in a particular pond that cannot seriously be extrapolated to other samples.

Finally, this study cannot address the effect of somatic mutation on phenotypes and their risk of occurrence.  Who knows how many local tissues have experienced double-knockout mutations and produced (or not produced) some disease or other phenotype outcome.  Constitutive genome sequencing cannot detect this.  Surely we should know this very inconvenient fact by now!

Given the well-documented and pervasive biological redundancy, it is not any sort of surprise that some genes can be non-functional and the individual phenotypically within a viable, normal range. Not only is this not a surprise, especially by now in the history of genetics, but its most important implication is that our Big Data genetic reductionistic experiment has been very successful!  It has, or should have, shown us that we are not going to be getting our money's worth from that approach.  It will yield some predictions in the sense of retrospective data fitting to case-control or other GWAS-like samples, and it will be trumpeted as a Big Success, but such findings, even if wholly correct, cannot yield reliable true predictions of future risk.

Does environment, by any chance, affect the studied traits?  We have, in principle, no way to know what environmental exposures (or somatic mutations) will be like.  The by now very well documented leaf-litter of rare and/or small-effect variants plagues GWAS for practical statistical reasons (and is why usually only a fraction of heritability is accounted for).  Naturally, finding a single doubly inactivated gene may, but by no means need, yield reliable trait predictions.

By now, we know of many individual genes whose coded function is so proximate or central to some trait that mutations in such genes can have predictable effects.  This is the case with many of the classical 'Mendelian' disorders and traits that we've known for decades.  Molecular methods have admirably identified the gene and mutations in it whose effects are understandable in functional terms (for example, because the mutation destroys a key aspect of a coded protein's function).  Examples are Huntington's disease, PKU, cystic fibrosis, and many others.

However, these are at best the exceptions that lured us to think that even more complex, often late-onset traits would be mappable so that we could parlay massive investment in computerized data sets into solid predictions and identify the 'druggable' genes-for that Big Pharma could target.  This was predictably an illusion, as some of us were saying long ago and for the right reasons.  Everyone should know better now, and this paper just reinforces the point, to the extent that one can assert that it's the political economic aspects of science funding, science careers, and hungry publications, and not the science itself, that leads to the persistence of drives to continue or expand the same methods anyway.  Naturally (or should one say reflexively?), the authors advocate a huge Human Knockout Project to study every gene--today's reflex Big Data proposal.**

Instead, it's clearly time to recognize the relative futility of this, and change gears to more focused problems that might actually punch their weight in real genetic solutions!

** [NOTE added in a revision.  We should have a wealth of data by now, from many different inbred mouse and other animal strains, and from specific knockout experiments in such animals, to know that the findings of the Pakistani family paper are to be expected.  About 1/4 to 1/3 of knockout experiments in mice have no effect or not the same effect as in humans, or have no or different effect in other inbred mouse strains.  How many times do we have to learn the same lesson?  Indeed, with existing genomewide sequence databases from many species, one can search for 2KO'ed genes.  We don't really need a new megaproject to have lots of comparable data.]

Wednesday, April 12, 2017

Reforming research funding and universities

Any aspect of society needs to be examined on a continual basis to see how it could be improved.  University research, such as that which depends on grants from the National Institutes of Health, is one area that needs reform. It has gradually become an enormous, money-directed, and largely self-serving industry, and its need for external grant funding turns science into a factory-like industry, which undermines what science should be about, advancing knowledge for the benefit of society.  

The Trump policy, if there is one, is unclear, as with much of what he says on the spur of the moment. He's threatened to reduce the NIH budget, but he's also said to favor an increase, so it's hard to know whether this represents whims du jour or policy.  But regardless of what comes from on high, it is clear to many of us with experience in the system that health and other science research has become very costly relative to its promise and too largely mechanical rather than inspired.

For these reasons, it is worth considering what reforms could be taken--knowing that changing the direction of a dependency behemoth like NIH research funding has to be slow because too many people's self-interests will be threatened--if we were to deliver in a more targeted and cost-efficient way on what researchers promise.  Here's a list of some changes that are long overdue.  In what follows, I have a few FYI asides for readers who are unfamiliar with the issues.

1.  Reduce grant overhead amounts
FYI:  Federal grants come with direct and indirect costs.  Direct costs pay the research staff, the supplies and equipment, travel and collecting data and so on.  Indirect costs are worked out for each university, and are awarded on top of the direct costs--and given to the university administrators.  If I get $100,000 on a grant, my university will get $50,000 or more, sometimes even more than $100K.  Their claim to this money is that they have to provide the labs, libraries, electricity, water, administrative support and so on, for the project, and that without the project they'd not have these expenses. Indeed, an indicator of the fat that is in overhead is that as an 'incentive' or 'reward', some overhead is returned as extra cash to the investigator who generated it.]

University administrations have notoriously been ballooning.  Administrators and their often fancy offices depend on individual grant overhead, which naturally puts intense pressure on faculty members to 'deliver'.  Educational institutions should be lean and efficient. Universities should pay for their own buildings and libraries and pare back bureaucracy. Some combination of state support, donations, and bloc grants could be developed to cover infrastructure, if not tied to individual projects or investigators' grants. 

2.  No faculty salaries on grants
FYI:  Federal grants, from NIH at least, allow faculty investigators' salaries to be paid from grant funds.  That means that in many health-science universities, the university itself is paying only a fraction, often tiny and perhaps sometimes none, of their faculty's salaries.  Faculty without salary-paying grants will be paid some fraction of their purported salaries and often for a limited time only.  And salaries generate overhead, so they're now well paid: higher pay, higher overhead for administrators!  Duh, a no-brainer!]

Universities should pay their faculty's salaries from their own resources.   Originally, grant reimbursement for faculty investigators' salaries were, in my understanding, paid on grants so the University could hire temporary faculty to do the PI's teaching and administrative obligations while s/he was doing the research.  Otherwise, if they're already paid to do research, what's the need? Faculty salaries paid on grants should only be allowed to be used in this way, not just as a source of cash.  Faculty should not be paid on soft money, because the need to hustle one's salary steadily is an obvious corrupting force on scientific originality and creativity. 

3.  Limit on how much external funding any faculty member or lab could have
There is far too much reward for empire-builders. Some do, or at least started out doing, really good work, but that's not always the case and diminishing returns for expanding cost is typical.  One consequence is that new faculty are getting reduced teaching and administrative duties so they can (must!) write grant applications. Research empires are typically too large to be effective and often have absentee PIs off hustling, and are under pressure to keep the factory running.  That understandably generates intense pressure to play it safe (though claiming to be innovative); but good science is not a predictable factory product. 

4.  A unified national health database
We need health care reform, and if we had a single national health database it would reduce medical costs and could be anonymized so research could be done, by any qualified person, without additional grants.  One can question the research value of such huge databases, as is true even of the current ad hoc database systems we pay for, but they would at least be cost-effective.

5. Temper the growth ethic 
We are over-producing PhDs, and this is largely to satisfy the game of the current faculty by which status is gained by large labs.  There are too many graduate students and post-docs for the long-term job market.  This is taking a heavy personal toll on aspiring scientists.  Meanwhile, there is inertia at the top, where we have been prevented from imposing mandatory retirement ages.  Amicably changing this system will be hard and will require creative thinking; but it won't be as cruel as the system we have now.

6. An end to deceptive publication characteristics  
We routinely see papers listing more authors than there are residents in the NY phone book.  This is pure careerism in our factory-production mode.  As once was the standard, every author should in principle be able to explain his/her paper on short notice.  I've heard 15 minutes. Those who helped on a paper such as by providing some DNA samples, should be acknowledged, but not listed as authors. Dividing papers into least-publishable-units isn't new, but with the proliferation of journals, it's out of hand.  Limiting CV lengths (and not including grants on them) when it comes to promotion and tenure could focus researchers' attention on doing what's really important rather than chaff-building.  Chairs and Deans would have to recognize this, and move away from safe but gameable bean-counting.  

FYI: We've moved towards judging people internally, and sometimes externally in grant applications, on the quantity of their publications rather than the quality, or on supposedly 'objective' (computer-tallied) citation counts.  This is play-it-safe bureaucracy and obviously encourages CV padding, which is reinforced by the proliferation of for-profit publishing.  Of course some people are both highly successful in the real scientific sense of making a major discovery, as well as in publishing their work.  But it is naive not to realize that many, often the big players grant-wise, manipulate any counting-based system.  For example, they can cite their own work in ways that increase the 'citation count' that Deans see.  Papers with very many authors also lead to red-claiming that is highly exaggerated relative to the actual scientific contribution.  Scientists quickly learn how to manipulate such 'objective' evaluation systems.] 

7.  No more too-big-and-too-long-to-kill projects
The Manhattan Project and many others taught us that if we propose huge, open-ended projects we can have funding for life.  That's what the 'omics era and other epidemiological projects reflect today.  But projects that are so big they become politically invulnerable rarely continue to deliver the goods.  Of course, the PIs, the founders and subsequent generations, naturally cry that stopping their important project after having invested so much money will be wasteful!  But it's not as wasteful as continuing to invest in diminishing returns.  Project duration should be limited and known to all from the beginning.

8.  A re-recognition that science addressing focal questions is the best science
Really good science is risky because serious new findings can't be ordered up like hamburgers at McD's.  We have to allow scientists to try things.  Most ideas won't go anywhere.  But we don't have to allow open-ended 'projects' to scale up interminably as has been the case in the 'Big Data' era, where despite often-forced claims and PR spin, most of those projects don't go very far, either, though by their size alone they generate a blizzard of results. 

9. Stopping rules need to be in place  
For many multi-year or large-scale projects, an honest assessment part-way through would show that the original question or hypothesis was wrong or won't be answered.  Such a project (and its funds) should have to be ended when it is clear that its promise will not be met.  It should be a credit to an investigator who acknowledges that an idea just isn't working out, and those who don't should be barred for some years from further federal funding.  This is not a radical new idea: it is precedented in the drug trial area, and we should do the same in research.  

It should be routine for universities to provide continuity funding for productive investigators so they don't have to cling to go-nowhere projects. Faculty investigators should always have an operating budget so that they can do research without an active external grant.  Right now, they have to piggy-back their next idea by using funds in their current grant, and without internal continuity funding, this is naturally leads to safe 'fundable'  projects, rather than really innovative ones.  The reality is that truly innovative projects typically are not funded, because it's easy for grant review panels to fault-find and move on the safer proposals.

10. Research funding should not be a university welfare program
Universities are important to society and need support.  Universities as well as scientists become entrenched.  It's natural.  But society deserves something for its funding generosity, and one of the facts of funding life could be that funds move.  Scientists shouldn't have a lock on funding any more than anybody else. Universities should be structured so they are not addicted to external funding on grants. Will this threaten jobs?  Most people in society have to deal with that, and scientists are generally very skilled people, so if one area of research shrinks others will expand.

11.  Rein in costly science publishing
Science publishing has become what one might call a greedy racket.  There are far too many journals, rushing out half-way reviewed papers for pay-as-you-go authors.  Papers are typically paid for on grant budgets (though one can ask how often young investigators shell out their own personal money to keep their careers).  Profiteering journals are proliferating to serve the CV-padding hyper-hasty bean-counting science industry that we have established.  Yet the vast majority of papers have basically no impact.  That money should go to actual research.

12.  Other ways to trim budgets without harming the science 
Budgets could be trimmed in many other ways, too:  no buying journal subscriptions on a grant (universities have subscriptions), less travel to meetings (we have Skype and Hangout!), shared costly equipment rather than a sequencer in every lab.  Grants should be smaller but of longer duration, so investigators can spend their time on research rather than hustling new grants. Junk the use of 'impact' factors and other bean-counting ways of judging faculty.  It had a point once--to reduce discrimination and be more objective, but it's long been strategized and manipulated, substituting quantity for quality.  Better evaluation means are needed.  

These suggestions are perhaps rather radical, but to the extent that they can somehow be implemented, it would have to be done humanely.  After all, people playing the game today are only doing what they were taught they must do.  Real reform is hard because science is now an entrenched part of society.  Nonetheless, a fair-minded (but determined!) phase-out of the abuses that have gradually developed would be good for science, and hence for the society that pays for it.

***NOTES:  As this was being edited, NY state has apparently just made its universities tuition-free for those whose families are not wealthy.  If true, what a step back towards sanity and public good!  The more states can get off the grant and other grant and strings-attached private donation hooks, the more independent they should be able to be.

Also, the Apr 12 Wall St Journal has a story (paywall, unless you search for it on Twitter) showing the faults of an over-stressed health research system, including some of the points made here.  The article points out problems of non-replicability and other technical mistakes that are characteristic of our heavily over-burdened system.  But it doesn't go after the System as such, the bureaucracy and wastefulness and the pressure for 'big data' studies rather than focused research, and the need to be hasty and 'productive' in order to survive.

Wednesday, March 29, 2017

The (bad) luck of the draw; more evidence

A while back, Vogelstein and Tomasetti (V-T) published a paper in Science in which it was argued that most cancers cannot be attributed to known environmental factors, but instead were due simply to the errors in DNA replication that occur throughout life when cells divide.  See our earlier 2-part series on this.

Essentially the argument is that knowledge of the approximate number of at-risk cell divisions per unit of age could account for the age-related pattern of increase in cancers of different organs, if one ignored some obviously environmental causes like smoking.  Cigarette smoke is a mutagen and if cancer is a mutagenic disease, as it certainly largely is, then that will account for the dose-related pattern of lung and oral cancers.

This got enraged responses from environmental epidemiologists whose careers are vested in the idea that if people would avoid carcinogens they'd reduce their cancer risk.  Of course, this is partly just the environmental epidemiologists' natural reaction to their ox being gored--threats to their grant largesse and so on.  But it is also true that environmental factors of various kinds, in addition to smoking, have been associated with cancer; some dietary components, viruses, sunlight, even diagnostic x-rays if done early and often enough, and other factors.

Most associated risks from agents like these are small, compared to smoking, but not zero and an at least legitimate objection to V-T's paper might be that the suggestion that environmental pollution, dietary excess, and so on don't matter when it comes to cancer is wrong.  I think V-T are saying no such thing.  Clearly some environmental exposures are mutagens and it would be a really hard-core reactionary to deny that mutations are unrelated to cancer.  Other external or lifestyle agents are mitogens; they stimulate cell division, and it would be silly not to think they could have a role in cancer.  If and when they do, it is not by causing mutations per se.  Instead mitogenic exposures in themselves just stimulate cell division, which is dangerous if the cell is already transformed into a cancer cell.  But it is also a way to increase cancer by just what V-T stress: the natural occurrence of mutations when cells divide.

There are a few who argue that cancer is due to transposable elements moving around and/or inserting into the genome where they can cause cells to misbehave, or other perhaps unknown factors such as of tissue organization, which can lead cells to 'misbehave', rather than mutations.

These alternatives are, currently, a rather minor cause of cancer.  In response to their critics, V-T have just published a new multi-national analysis that they suggest supports their theory.  They attempted to correct for the number of at-risk cells and so on, and found a convincing pattern that supports the intrinsic-mutation viewpoint.  They did this to rebut their critics.

This is at least in part an unnecessary food-fight.  When cells divide, DNA replication errors occur.  This seems well-documented (indeed, Vogelstein did some work years ago that showed evidence for somatic mutation--that is, DNA changes that are not inherited--and genomes of cancer cells compared to normal cells of the same individual.  Indeed, for decades this has been known in various levels of detail.  Of course, showing that this is causal rather than coincidental is a separate problem, because the fact of mutations occurring during cell division doesn't necessarily mean that the mutations are causal. However, for several cancers the repeated involvement of specific genes, and the demonstration of mutations in the same gene or genes in many different individuals, or of the same effect in experimental mice and so on, is persuasive evidence that mutational change is important in cancer.

The specifics of that importance are in a sense somewhat separate from the assertion that environmental epidemiologists are complaining about.  Unfortunately, to a great extent this is a silly debate. In essence, besides professional pride and careerism, the debate should not be about whether mutations are involved in cancer causation but whether specific environmental sources of mutation are identifiable and individually strong enough, as x-rays and tobacco smoke are, to be identified and avoided.  Smoking targets particular cells in the oral cavity and lungs.  But exposures that are more generic, but individually rare or not associated with a specific item like smoking, and can't be avoided, might raise the rate of somatic mutation generally.  Just having a body temperature may be one such factor, for example.

I would say that we are inevitably exposed to chemicals and so on that will potentially damage cells, mutation being one such effect.  V-T are substantially correct, from what the data look like, in saying that (in our words) namable, specific, and avoidable environmental mutations are not the major systematic, organ-targeting cause of cancer.  Vague and/or generic exposure to mutagens will lead to mutations more or less randomly among our cells (maybe, depending on the agent, differently depending on how deep in our bodies the cells are relative to the outside world or other means of exposure).  The more at-risk cells, the longer they're at risk, and so on, the greater the chance that some cell will experience a transforming set of changes.

Most of us probably inherit mutations in some of these genes from conception, and have to await other events to occur (whether these are mutational or of another nature as mentioned above).  The age patterns of cancers seem very convincingly to show that.  The real key factor here is the degree to which specific, identifiable, avoidable mutational agents can be identified.  It seems silly or, perhaps as likely, mere professional jealousy, to resist that idea.

These statements apply even if cancers are not all, or not entirely, due to mutational effects.  And, remember, not all of the mutations required to transform a cell need be of somatic origin.  Since cancer is mostly, and obviously, a multi-factor disease genetically (not a single mutation as a rule), we should not have our hackles raised if we find what seems obvious, that mutations are part of cell division, part of life.

There are curious things about cancer, such as our large body size but delayed onset ages relative to the occurrence of cancer in smaller, and younger animals like mice.  And different animals of different lifespans and body sizes, even different rodents, have different lifetime cancer risks (some may be the result of details of their inbreeding history or of inbreeding itself).  Mouse cancer rates increase with age and hence the number of at-risk cell divisions, but the overall risk at very young ages despite many fewer cell divisions (yet similar genome sizes) shows that even the spontaneous mutation idea of V-T has problems.  After all, elephants are huge and live very long lives; why don't they get cancer much earlier?

Overall, if if correct, V-T's view should not give too much comfort to our 'Precision' genomic medicine sloganeers, another aspect of budget protection, because the bad luck mutations are generally somatic, not germline, and hence not susceptible to Big Data epidemiology, genetic or otherwise, that depends on germ-line variation as the predictor.

Related to this are the numerous reports of changes in life expectancy among various segments of society and how they are changing based on behaviors, most recently, for example, the opiod epidemic among whites in depressed areas of the US.  Such environmental changes are not predictable specifically, not even in principle, and can't be built into genome-based Big Data, or the budget-promoting promises coming out of NIH about such 'precision'.  Even estimated lifetime cancer risks associated with mutations in clear-cut risk-affecting genes like BRCA1 mutations and breast cancer, vary greatly from population to population and study to study.  The V-T debate, and their obviously valid point, regardless of the details, is only part of the lifetime cancer risk story.

ADDENDUM 1
Just after posting this, I learned of a new story on this 'controversy' in The Atlantic.  It is really a silly debate, as noted in my original version.  It tacitly makes many different assumptions about whether this or that tinkering with our lifestyles will add to or reduce the risk of cancer and hence support the anti-V-T lobby.  If we're going to get into the nitty-gritty and typically very minor details about, for example, whether the statistical colon-cancer-protective effect of aspirin shows that V-T were wrong, then this really does smell of academic territory defense.

Why do I say that?  Because if we go down that road, we'll have to say that statins are cancer-causing, and so is exercise, and kidney transplants and who knows what else.  They cause cancer by allowing people to live longer, and accumulate more mutational damage to their cells.  And the supposedly serious opioid epidemic among Trump supporters actually is protective, because those people are dying earlier and not getting cancer!

The main point is that mutations are clearly involved in carcinogenesis, cell division life-history is clearly involved in carcinogenesis, environmental mutagens are clearly involved in carcinogenesis, and inherited mutations are clearly contributory to the additional effects of life-history events.  The silly extremism to which the objectors to V-T would take us would be to say that, obviously, if we avoided any interaction whatsoever with our environment, we'd never get cancer.  Of course, we'd all be so demented and immobilized with diverse organ-system failures that we wouldn't realize our good fortune in not getting cancer.

The story and much of the discussion on all sides is also rather naive even about the nature of cancer (and how many or of which mutations etc it takes to get cancer); but that's for another post sometime.

ADDENDUM 2
I'll add another new bit to my post, that I hadn't thought of when I wrote the original.  We have many ways to estimate mutation rates, in nature and in the laboratory.  They include parent-offspring comparison in genomewide sequencing samples, and there have been sperm-to-sperm comparisons.  I'm sure there are many other sets of data (see Michael Lynch in Trends in Genetics 2010 Aug; 26(8): 345–352.  These give a consistent picture and one can say, if one wants to, that the inherent mutation rate is due to identifiable environmental factors, but given the breadth of the data that's not much different than saying that mutations are 'in the air'.  There are even sex-specific differences.

The numerous mutation detection and repair mechanisms, built into genomes, adds to the idea that mutations are part of life, for example that they are not related to modern human lifestyles.  Of course, evolution depends on mutation, so it cannot and never has been reduced to zero--a species that couldn't change doesn't last.  Mutations occur in plants and animals and prokaryotes, in all environments and I believe, generally at rather similar species-specific rates.

If you want to argue that every mutation has an external (environmental) cause rather than an internal molecular one, that is merely saying there's no randomness in life or imperfection in molecular processes.  That is as much a philosophical as an empirical assertion (as perhaps any quantum physicist can tell you!).  The key, as  asserted in the post here, is that for the environmentalists' claim to make sense, to be a mutational cause in the meaningful sense, the force or factor must be systematic and identifiable and tissue-specific, and it must be shown how it gets to the internal tissue in question and not to other tissues on the way in, etc.

Given how difficult it has been to chase down most environmental carcinogenic factors, to which exposure is more than very rare, and that the search has been going on for a very long time, and only a few have been found that are, in themselves, clearly causal (ultraviolet radiation, Human Papilloma Virus, ionizing radiation, the ones mentioned in the post), whatever is left over must be very weak, non tissue-specific, rare, and the like.  Even radiation-induced lung cancer in uranium minors has been challenging to prove (for example, because miners also largely were smokers).

It is not much of a stretch to simply say that even if, in principle, all mutations in our body's lifetime were due to external exposures, and the relevant mutagens could be identified and shown in some convincing way to be specifically carcinogenic in specific tissues, in practice if not ultra-reality, then the aggregate exposures to such mutations are unavoidable and epistemically random with respect to tissue and gene.  That I would say is the essence of the V-T finding.

Quibbling about that aspect of carcinogenesis is for those who have already determined how many angels dance on the head of a pin.

Friday, March 24, 2017

Paid To Prey (PTP) journals

In the bad old days if you as a scientist had something worth saying, a journal would (after vetting through a mainly fair confidential review system) publish it.  If you had good things to say, whether or not you had grants, your ideas were heard, and you could make a career on the basis of the depth of your thought, your careful results, and so on.

If you needed funds to do your research, such as to travel or run a laboratory, well, you needed a grant to do your work.  This was the system we all knew.  You had to have funding, but you couldn't just pay your way through to publishing.  Also, if you were junior, start-up funds were typically made available if you needed them, to give you a leg up and a chance to get your career going.

Publishing has always had costs, of course, but the journals survived by library and personal subscriptions, often based on professional society memberships, where the fees were modest, especially for the most junior members.

Now what we have is a large pay-to-play (PTP) industry.  Pay-to-play journals are almost synonymous with corruption.  The mass of nearly-criminal ones prey on the career fears of desperate students, post-docs, and faculty (especially junior faculty, perhaps).  Even the honest PTP journals, of which there are many, essentially prey on investigators, and taxpayers, but the horde of dishonorable ones are no better than highwaymen, robbing the most vulnerable.  A story in the NY Times exposes some of the schemes and scams of the dishonorable PTPers.  But it doesn't go nearly far enough.

How cruel is this rat race?  Where does the PTP money come from?
We have every moral as well as fiscal right to ask where the PTP subscriptions are coming from.  Are low-paid, struggling post-docs, students, junior or even more senior faculty members using their own personal funds to keep in the publication score-counting game?  How much taxpayer money goes, even via legitimate grants, to these open-source publishers rather than to the research costs for which these grants were intended.  In the past, you might have had to pay for color figures, or for reprints, and these costs did come generally from grant funds, but they were not very expensive.  And of course grants often pay for faculty salaries (a major corruption of the system that nobody seems able to fix and on which too many depend to criticize).

The idea of open-source journals sounded good, and not like a private-profiteering scam.  But too many have turned out to be the latter, chickens laying golden eggs even for the better journals, when there is profit to be made. The original, or at least more publicly proclaimed open-source idea was that even if you couldn't afford a subscription or didn't have access to a university library--especially, for example, if you were in a country with a paucity of science resources--you would have access to the world's top science anyway.  But even if the best of the open-source organizations are non-profit, non-predatory PTP operations, and how would we know?, we are clearly preying on the fears of those desperate for careers in heavily oversubscribed, heavily Malthusian overpopulated science industries.

There is no secret about that, but too many depend on the growth model for there to be an easy fix, except the painful one of budget cuts.  The system is overloaded and overworked and that suggests that even if everyone were doing his/her best, sloppy or even corrupt work would make it through the minimal PTP quality control sieve.  And that makes it easy to see why many may be paying with personal funds or submitting sloppy (or worse) work--and too much of it, too fast.

There isn't any obvious solution in an overheated hyper-competitive system.  We do have the web, however, and one might suggest shutting down the PTP industry, or at least somehow closing its predatory members, and using the web to publicize new findings.  Perhaps some of the open review sources, like ArXiv, can deal with some of the peer reviewing issues to maintain a quality standard.

Of course, Deans and Chairs would have to actually do the work of evaluating the quality of their faculty members' works (beyond 'impact factors', grant totals, paper counts, and so on) to reward quality of thought rather than any quantity-based measures.  That would require the administrators to actually think, know their fields, and take the time to do their jobs.  Perhaps that's too much to ask of a system now sometimes proudly proclaiming it's on the 'business model'.

But what we're seeing is what we deserve because we've let it happen.

Thursday, March 16, 2017

Higher resolution discrimination: The GOP wants to allow employers to require genetic testing

This morning, Ed Yong published an article that takes on issues that we at the The Mermaid's Tale care very deeply about.
Link to article
The consequences for important medical research are not going to be pretty.

And I can't help but be angry about this for threatening to take away the fun of genetics too. If we can't have some control over our genetic testing, we can't do it for fun, for education, for finding out more about ourselves, for the awe of it, for innerspace exploration in the technology age. They're taking that away from us by eroding GINA.

I have lots of other thoughts... like about how this fits in so nicely with (not all of) the right's racist/eugenics inclinations.

And juxtapose this view from the political right where there is full-on acceptance of actually-more-than-genetics-can-even-deliver against their anti-science politics and policy...

It's like science is totally fine for Republicans as long as Mother Nature is a dictator.

If it's more complicated than that, then deny it, defund it, bulldoze it. The reality is, genetics is largely probabilistic; it is not a dictatorship. It's just so hard to convince people that it isn't. The ideological drive to justify behavioral differences and socioeconomic inequality with Nature above all is just too strong. If it's Nature, then we don't have to do the hard work of addressing the problems because Nature is Nature is Nature. This is really old thinking that really new knowledge (both through lots of science and lots of lived experience and lots of humanities and lots of art) has overturned but has not managed to catch on all that well. Along with new knowledge we get increasing understanding of genetics so these ancient beliefs can just be spouted by politicians using new-fangled science jargon.

This is really hard to write about today as all the stories about the proposed (and highly probable) budget cuts to science and the arts are blasting through my newsfeeds. It's overwhelming me today. I'm feeling hopeless and angry on behalf of science, art, knowledge, medicine, humanity, humans, children, teenagers, grown-ups, geezers. It's too much today.

But, back to Ed's article, I do need to put this here because it mentions that I have taught with 23andMe and longtime readers of the MT might know about that:

I don't teach with 23andMe anymore. I was doing it for as long as my university would pay for the kits. It was totally voluntary and students had to read Misha Angrist's book and endure long discussions and pass a quiz before deciding whether to go through with the testing. It was so powerful for teaching evolution, genetics, anthropology, etc... and we critiqued the hell out of it. My university said I needed to pay for the kits through course fees from now on. Before any of these threats to GINA, I decided not to do that and to stop using 23andMe. Now, even if my university reconsidered and funded the kits, I still wouldn't take it up again as a teaching tool.

Tuesday, February 28, 2017

Replacing the Affordable Care Act -- what's so complicated?

Nobody knew health care could be so complicated? Er, except everybody but Mr Trump.  And yes, it's a huge behemoth of a system, but the devil is in the detail.  It's when you throw in all the special interests, political considerations, back-scratching, etc. that it quickly gets complicated.  But before all that happens, there are only three basic choices when it comes to providing medical insurance, and they are easy to grasp.  Choosing among them, though, has become much more of a political choice than an unloaded purely economic one.

Here's what we had before the Affordable Care Act (ACA): private insurance, either from one's employer or purchased individually.  For this to work, of course, just as any other business, insurance companies must make a profit, and that's harder when customers get sick; purchasers actually using their insurance isn't good for the bottom line.  That's why there's so much talk about people with "pre-existing conditions".  These are people who insurers know will cost them money and that's why people with "pre-existing conditions" were essentially uninsurable before the ACA, except as members of large employee pools comprised primarily of healthy people who had to buy in as a condition of their employment.  And that's why insurance companies used to charge women, older people, smokers, and so on more; they were more likely to cost money.  And that's why insurance companies also had policies such as lifetime caps on benefits.  To stay in business, insurers have to make a profit.  It's their reason for being.  This system can work well for healthy people and insurance companies.

The second option is something like the ACA, where everyone, pre-existing condition or not, can buy insurance -- an appropriate thing to point out on Rare Disease Day 2017.  As with auto  insurance, the only way this is financially viable is if everyone is required to buy in; just as good drivers subsidize unsafe drivers, healthy people subsidize people more likely to use healthy insurance.  Thus, the hated "mandate", the requirement that everyone buy in or be penalized on their taxes.  Many detractors of the ACA believe the mandate can simply be eliminated, that a replacement for the ACA can cover as many people, as cheaply, without one.  But, that's impossible. This is the same kind of privitized system that has worked without major snags for many years in Switzerland, for example. There, insurance is compulsory, and insurance companies must offer a basic plan which they aren't allowed to profit from although people can purchase bells and whistles, which is how the insurers make a profit.

The third option is the public option, often these days described as Medicare for all.  Government-supplied health insurance, paid for by tax dollars.  It's cheaper than the first two options in large part because it's non-profit, and the infrastructure required by private insurers to validate or deny claims doesn't exist.  National health has worked well in many rich countries for decades, keeping costs down and providing access to medical care to all.

And that's it.  There's no other "terrific" "cheaper" alternative anyone has thought of that can replace the ACA. The only options are a system that's totally private; something like the ACA with its mandate; and national health.  Unfortunately, this wasn't very well explained when President Obama was working on the Affordable Care Act, and it's not being explained now.  The Republicans in control of Congress aren't going to give us national health; and while it seems that many of them would be happy going back to what we used to have before the ACA, opinion polls are showing that people are less and less happy with that option.  Will Trumpcare be Obamacare renamed, then?  We'll have to wait and see.  

In any case, whatever system we adopt, we've still got problems.  Although the rising cost of medical care in the United States has slowed some with the ACA, at almost 18% of GDP health care spending here is the most expensive in the world, far exceeding that of any other high-income country, most of which have national health care (e.g., source).  In part it's because of the high cost of medical care, the higher use of expensive technology (e.g., MRI's, mammograms and C sections) and the exorbitant cost of pharmaceuticals.  And this is even with limitations imposed by insurance companies to control costs.  In addition, the cost of individual premiums has soared for people who aren't eligible for government subsidies to help cover the cost of insurance, in part, because fewer healthy people have purchased insurance than companies anticipated.  And deductibles and co-pays have risen sharply.  Insurance companies still have to turn a profit to stay in the health insurance marketplace.


Source
And, all this spending hasn't made us healthier than people in countries that spend even considerably less.


Source

So,  even if Trumpcare is as terrific and as cheap as we've been promised, it's hard to see how it will cut the high cost of medical care, and make us a healthier nation.  That is complicated, especially when private profit, rather than public health, is its fundamental basis.

Friday, February 24, 2017

Reproductive Health Funding and Why it Matters

Conflict and war can have an enormous impact on demography and population health. When active fighting breaks out in an area it can lead to large and chaotic population movements - if you’ve been paying attention to the news about conflict in the Middle East you’ve most likely seen images of huge populations fleeing countries like Syria and Iraq and the resulting influx of millions of refugees arriving in places such as Europe.

The chaotic settings in which these populations find shelter are often rife with sanitation, hygiene and other problems. Difficult, strategic decisions must be made on behalf of humanitarian agencies regarding how best to allocate limited funding to properly address the needs of these populations. Unfortunately reproductive health isn’t normally a high priority – although it really should be. One of the best ways to improve the health of a population is to address morbidity and mortality in very early childhood. Everyone in a population goes through the childbirth bottleneck. Everyone has a biological mother. Targeting these age and sex groups can have far-reaching impacts.

An IDP (internally displaced person) camp along the Thailand-Myanmar border. Photo by Suphak Nosten


Most of my work focuses on health issues along the Myanmar-Thailand border and while there has been a decrease in fighting recently, in the very near past there was active civil war and sporadic flows of refugees seeking safety in the mountains on the Thai side of the border. By the early 1980s there were many small refugee and internally displaced person camps scattered along the border. In the mid-1990s (between 1994 and 1998) most of these smaller camps were consolidated into one of 9 currently existing camps. Today, Maela refugee camp, roughly 60 kilometers north of Mae Sot, Thailand, is the largest of these camps with a current population of roughly 37,000. It has been in existence now for over 30 years.

One thing that is easy to miss in an age of constant news bombardment is that these populations, these refugee camps, don’t just disappear with the news cycle. Sometimes refugee camps last for a very long time. Today there are second-generation refugees who were born, and continue to live, in Maela camp.

Shoklo Malaria Research Unit, a field station of the Mahidol-Oxford Tropical Medicine Research Unit, operated the only antenatal clinic in Maela camp until this past December (2016). Recently we analyzed records and data from our experiences in providing contraceptives to refugee women in this long, drawn-out refugee setting. Given the current dire refugee situation of the world, we thought our experiences might have relevance not only for the current refugee situation but also for the future, given that many people will likely be living in large refugee settings for the foreseeable future.

The first thing that became obvious from our analysis is that obtaining a good understanding of basic demographics can be rather difficult.  Information really is a first casualty of war – gaining a handle on data about the population can be difficult even decades later. Furthermore, population counts can have political implications, or conversely, population estimates are sometimes the result of political sentiments.  For Maela camp there are two main sources of population counts – one comes from the humanitarian agency that provides food (the Thai-Burma Border Consortium (TBBC)) and the other is from the United Nations High Commissioner for Refugees (UNHCR) that provides humanitarian and social services. Until very recently UNHCR counts have systematically been much smaller than TBBC counts.

Population estimates have varied widely by the reporting source. We estimated the reproductive age female population for Maela camp by year using data from both TBBC (black) and UNHCR (blue) population estimates.  A loess curve (solid line) is fit to the data points and 95% confidence intervals for the curve are shown in dark gray.


Our data also show that, when provided in a socio-cultural appropriate manner, men and women in refugee settings willingly uptake contraceptives. The population we work with can properly be considered a high fertility (or natural fertility) population meaning that, with some exception, families are large and people are happy with that. But even in a high fertility population contraceptives have important health implications.  Men and women should be able to regulate their family size and spacing if they choose. Unintended pregnancies can result in incredible burdens, especially in already difficult settings, with health consequences for children, families, and entire communities leading to intergenerational transfers of poverty and nutritional deficits [1,2]. Households with few working-age adults and many dependents tend to be households with economic and nutritional deficiencies.




We also note that funding has a huge impact on the uptake of contraceptives and even the type of contraceptives that are chosen. Yes, men and women in the camp chose to readily use contraceptives, but the availability of contraceptives and the type of contraceptives available were directly influenced by funding. In this setting and in others, most of that funding could best be described as “rescue funding”, with reproductive health services normally operating on small and dwindling budgets but occasionally being “rescued” by a new source of funding. Given the importance of reproductive health (including the availability of contraceptives) and the dependence of reproductive health services on funding, funding agencies should carefully consider what they fund and should give careful consideration to funding cuts.


It is hard to draw direct, causal relationships between something like reproductive health funding and reductions in morbidity and mortality because there are complex relationships between health care delivery and health outcomes. However, we do know that during the time that SMRU operated the antenatal clinic in Maela camp both maternal and neonatal mortality decreased drastically. From 1986 to 1990 there were about 499 maternal deaths for every 100,000 births while in 2006 – 2010 there were 79 per 100,000 births [3].  In 1996 there were approximately 43.5 deaths for every 1,000 neonates and by 2011 there were 6 per 1,000 [4,5].

When funding was available, refugees in Maela camp willingly chose to use contraceptives leading to safer, better-planned pregnancies, which leads to health improvements of mother and child. A focus on reproductive health in conflict and refugee settings is extremely important and can have a drastic impact on population health. When people are given the opportunity to be more in charge of important parts of their lives, they are more likely to break out of difficult poverty cycles, and subsequently go on to live healthier lives. We believe this is a good thing.

photo by Suphak Nosten


1. Wagmiller Jr RL, Adelman RM. Childhood and intergenerational poverty: The long-term consequences of growing up poor [Internet]. Columbia University Academic Commons. 2009. Available: http://hdl.handle.net/10022/AC:P:8870

2. Corak M. Do poor children become poor adults? Lessons from a cross country comparison of generational income mobility [Internet]. IZA Discussion Paper. 2006. Available: http://ftp.iza.org/dp1993.pdf

3. McGready R, Boel M, Rijken MJ, Ashley E a., Cho T, Moo O, et al. Effect of early detection and treatment on malaria related maternal mortality on the north-western border of Thailand 1986-2010. PLoS One. 2012;7. doi:10.1371/journal.pone.0040244

4. Luxemburger C, McGready R, Kham A, Morison L, Cho T, Chongsuphajaisiddhi T, et al. Effects of malaria during pregnancy on infant mortality in an area of low malaria transmission. Am J Epidemiol. 2001;154: 459–465. 

5. Turner C, Carrara V, Aye Mya Thein N, Chit Mo Mo Win N, Turner P, Bancone G, et al. Neonatal Intensive Care in a Karen Refugee Camp: A 4 Year Descriptive Study. PLoS One. 2013;8: 1–9. doi:10.1371/journal.pone.0072721


Friday, February 3, 2017

Save the Planet? Nonsense! But still.....

One hears a lot of Doomsday pleas that we should cut back on our consumption of carbon fuels, eat less meat, fish less, and so on--or else!  Or else what?  Or else, as it's often expressed, we'll destroy the planet!  Scientists speaking to each other about agricultural sustainability or climate change use less excessively inflammatory rhetoric, though even they can engage in catastrophism when the public media cameras are on.  Concern for the future is understandable, but exaggeration is not sensible if you stop to think about it. Crying "Wolf!" can backfire, because the Earth is not in imminent danger!




Human activity, even if we let our population rise to 10 or more billion and burn every single last chunk of coal and drop of oil, will not destroy the Earth.  No amount of energy conservation and sustainability will save the Earth from destruction, because it's not headed that way anyhow, and people haven't the power to destroy it (though, would we be able to come close with a nuclear WWIII?).

Indeed, it's possible that imminent catastrophe rhetoric reinforces the reactionary view that this is scientific nonsense and we should just close climate-change government-sponsored web sites and de-fund environmental science.

Part of the problem is that this is like the frog in a boiling kettle: the water gets hot so gradually that the frog doesn't notice it until it's too late.  We humans are not very good at long-term thinking or planning, perhaps because longterm thinking wasn't possible or useful as we evolved, when each day's food, safety and mates were what was at stake.  When change is slow, as global warming is, people often feel less inclined to self-denial today in exchange for a viable tomorrow.

In addition, sociologically speaking, climate change messages can be seen as a scientific or 'left-wing' elite telling everyone else that they have to scale-down, while at least some have noticed the fact that the same elite fly all over the world to have meetings, promote their books, and deliver their message (and flying is among the worst CO2 polluters).

In fact, most of what is being said by science, even taking scientists' vanities, frailties, and grant-hungers into account, is basically right.  The climate clearly is changing, the seas rising, agricultural patterns changing, many species endangered.  Of course, there have always been changes in patterns of rainfall, temperature, and vegetation, though the time scale generally has been glacially slow, so to speak, with the possible occasional exception of major meteorite strikes or huge volcanic eruptions etc.  The current speed is one reason human activity seems surely to be at least partially responsible.
Another important point isn't that climate is changing, but that the pace we're seeing today may not be reversible even if our behavior is contributing, because our ability to change the course of geoclimate might be limited.

But that doesn't mean that the science-deniers and their ilk hiding their head in the sand are right. They're as self-willed ignorant as scientists say they are.  They are pretending that the science is wrong, when the real truth is that they don't like the answers the science is giving us.

The real risk
If climate is always changing, and Save the Earth is a misleading slogan, the problem is that even if the Earth is not in danger, we are!  And that is the very, very personal and selfishly short-sighted reason that we should slow down global warming if we can, increase use of renewable energies, keep funding climate sciences, and so on.  Let's take a look at the wolf that really is at our door, and making enough evidentiary noise that we can't miss it.  What is at stake is not the Earth, but the kind of constancy we, like any species, rightfully feel comfortable with.

In fact, climate change does pose very serious, very real, and potentially dire risks. There are at least a few likely, foreseeable consequences of climate change:
1. Threatened lifestyles.  On the more mundane side, having to change where and how we live, what we eat, how we interact with each other, and so on, are major dislocations of lifestyle.  Being animals, we like our 'territory' to be familiar and feel safe.  The levels of ill-will and unhappiness that would ensue major cultural upsets due to climate change and its consequences, would be upsetting to a great many people. There may indeed be changed patterns of wealth, lifestyle, disease in us and/or our animal and plant food sources.  We may exhaust some minerals vital to our technological support systems. Even peacefully, gradually adapting to a lower-consuming lifestyle could avoid this, but would be disruptive; even if we lived very well in lower-consuming times in the past, social and psychological factors will be strained if our life-ways are changed too much or too fast. 
2.  Mass dislocation.  Most cities and urban concentrations are near natural waterways.  That's because they were founded over many centuries when water-borne trade and transport of goods etc., the stuff that makes concentrated populations possible, was the only real means of large-scale transportation.  So, if water levels rise along coasts and major lakes or rivers, or if waterways dry up, there will be dislocations that make todays middle east refugees look like tiddly-winks by comparison.  If tens of millions of Londoners and New Yorkers (not to mention residents of China or India) need to relocate, they'll have to go where there already are people.  This mass internal migration will be seen by the 'recipients' as 'Yugely' more of a threat than refugees today pose. 
3.  Exacerbated inequality and suffering.  Other large-scale dislocations of many sorts will mean economic deprivation for some who were well off, and new privilege for others.  Climate change alters agricultural areas, drying some up and making others flourish. Food being one thing people really do fight over, one can anticipate major economic dislocation and very large-scale competition for the new food producing areas, by those whose breadbaskets dried up.  This means war and potentially on a massive scale.  With 10 billion people, and industrial-scale weaponry (including nukes), the suffering will potentially be massively unprecedented.
In the overall scheme of things, a few island populations imminently needing relocation is an enormous event for the islanders but not a terribly large event globally.  But when cities become inundated, and food hard to come by, when refugees number in the many millions, and they're armed, well, that may be a definition of Arm-aggedon (forgive the pun).

We should be talking turkey to the public. Even if climate change is human-accelerated, it is not the first time there has been major climate change.  The Earth, and even the human species, will survive it.  Scientists should not be pressed by the intentionally uneducated into over-stating the case.  The planet is not in danger.  But in a sense there really is a wolf knocking at the door, and it is worth saving the planet as we know it.

What is in danger is our way of life.  And that's something humans kill for.

Friday, January 27, 2017

Evolution as a pachinko history: what is 'random'?

We discussed a Japanese pachinko machine in an earlier post, a pinball machine, as an example of the difference between randomness and determinism, in an evolutionary context.   Here we want to use pachinko machine imagery in a different way.

The prevailing, often unstated but just-under-the-surface assumption is that every trait in life is here because of natural selection.  Of course, for a trait to be here at all, bearers of its ancestral states up to the present (or, at least, the recent past) were successful enough to have reproduced.  It would not be here if it were otherwise, unless, for example, it's itself harmful, or without function but connected to a much better, related trait since genes are usually used in many different bodily contexts and may be associated with both beneficial and harmful traits.  Most sensible evolutionary geneticists know that many or even most sites in genomes tolerate variation that has either no effect or effects so small that in realistic population sizes they change in frequency essentially by chance.





However, the widespread default assumption that there must be an adaptive explanation for every trait usually also tacitly assumes that probabilism doesn't make much difference.  Some alert evolutionary biologists will acknowledge that one version among contemporary but equivalent versions of a trait can evolve by chance relative to other versions.  But the insistence, tacit or expressed, is that natural selection, treated essentially as a force, is responsible.  The very typical view is that the trait arose because of selection 'for' it, and that's why it's here.  And speaking of 'here', here's where a pachinko analogy may be informative.

If a bevy of metal balls tumbles through the machine, each bouncing off the many pins, they will end up scattered across the bottom ledge of the machine (the gambling idea is to have them end up in a particular place, but that's not our point here).  So let's take a given ball and ask 'Why did it end up where it did?"





The obvious and clearly true answer is 'Gravity is responsible'.  That is the analogue of 'selection is responsible'.   But it is rather an empty answer.  One can always say that what's here must be here because it was favored (that is, not excluded) by fitness considerations: its ancestral bearers obviously reproduced!  We can define that as 'adaptation' and indeed in a sense that is what is done every day, almost thoughtlessly.

Gravity is, like the typical if tacit assumption about natural selection, a deterministic force for all practical purposes here.  But why did this ball end up in this particular place?  One obvious answer is that each starts out in a slightly different place at the top, and no two balls are absolutely identical. However, each ball makes a different path from the top to the bottom of the obstacle course it faces. Yes, it is gravity that determines that they go down (adapt), but not how they go down.

In fact, each ball takes a different path, zigging and zagging at each point based on what happens, essentially by chance, at that point.   This one might think of as local ecosystems on the evolutionary path of any organism, that are beyond its control.  So, in the end, even if the entire journey is deterministic, in the sense that every collision is, the result is not one that can, in practice, be understood except by following the path of each ball (each trait, in the biological analogy).  And this means that the trajectory cannot be predicted ahead of time. And in turn, this means that our interpretation of what a trait we see today was selected 'for' is often if not usually either basically just a guess or, more often, equates what the trait does today to what it was selected to be, expressed as if it were an express train from then to now.

And this doesn't consider another aspect of the chaotic and chance-affected nature of evolutionary adaptation: the interaction with the other balls bouncing around at the same time in such an obstacle course.  Collisions are in every meaningful sense in the game of life, if not pachinko, chance events that affect selective ones, even were we to assume that selection is simple, straightforward, and deterministic.

The famous argument by Gould and Lewontin that things useful for one purpose, such as 'spandrels' in cathedral roofs, are incidental traits that provide the options for future adaptations--life exploits today with what yesterday produced for whatever reason even if just by chance.  The analogy or metaphor has been questioned, but that is not important here.  What is important is that contingencies of this nature are chance events, relative to what builds on them.  Selectionism as a riposte to creationism is fine but hyper-selectionism becomes just another often thought-free dogma.  Darwin gave us inspiration and insight, but we should think for ourselves, not in 19th century terms.

A far humbler, and far less 'Darwinian' (but not anti-Darwinian!), explanation of life is called for if we really want to understand evolution as a subtle often noisy process, rather than as a faith.  Instead, even serious biologists freely invent--and that's an apt word for it--selective accounts, as if true explanations, for almost any trait one might mention. It's invented because some reason is imagined without any direct evidence other than present-day function, but then treated as if directly observed, which is rarely possible. Here is an interview that I just came across that in a different way makes some of the same points we are trying to make here.

Everything here today is 'adaptive' in the sense that it has worked up to now.  Everything here today is also a 4 billion year successful lineage, that all made its way through the pachinko pins.  But these are almost vacuous tautologies.  Understanding life requires understanding one's biases in trying to force simple solutions on complicated reality.

Thursday, January 19, 2017

Relatedness is relative: How can I be 85% genetically similar to my mom, but only related to her by half?

First of all, no. I am not the lovechild of star-crossed siblings, or even cousins, or even second cousins. 

This is a gee-whiz kind of post. But the issues are not insignificant.

Hear me out with the background, first, before I get to the part where my eyes bug out of my head and I pull out my kid's Crayola box and start drawing.

If you've learned about sociobiology, or evolutionary psychology, or inclusive fitness, or kin selection, or the evolution of cooperation and even "altruism," or if you've read The Selfish Gene, or if you've been able to follow the debate about levels of selection (which you can peek at here)...

... then you've heard that you're related to your parents by 1/2, to your siblings by 1/2 as well, to your grandparents and grandchildren by 1/4, to your aunts and uncles and nieces and nephews by 1/4 as well, and to your first cousins by 1/8 and so on and so forth.  (Here's some more information.)

So, for example. For evolution (read: adaptationism) to explain how cooperative social behavior could be adaptive in the genetic sense, we use the following logic provided by Bill Hamilton, which became known as "Hamilton's Rule": 

The cost to your cooperation or your prosocial behavior (C) must be less than its benefit to you (B), reproductively speaking, relative to how genetically related (r) you are to the individual with whom you're cooperating. That could have come out smoother. Oh, here you go:

C < rB, or B > C/r

If you're helping out your identical genetic twin (r=1.0), then as long as the benefit to you is greater than the cost, it's adaptive.

C < B, or B > C

If you're helping out your daughter (r = 0.5) then as long as the benefit to you is greater than twice the cost, it's adaptive.

C < (1/2)B, or B > 2C

So already, the adaptive risk to helping out your daughter or your brother is quite higher. And it's even harder to justify the cooperation between individuals and their sibs' kids, and grandkids, especially ESPECIALLY non-kin. But, of course creatures do it! And so do we.

As relatedness gets more distant and distant, we go from 2 times the cost, to 4 times, 8 times, 16, 32, 64 etc... You can see why people like to say "the math falls away" or "drops off" at first or second cousins when they're explaining where the arbitrary line of genetic "kin" is drawn.  If you offer up a curious, "we're all related, we're all kin," someone out of this school of thought that's focused on explaining the evolution of and genes for social behavior may clue you in by circumscribing "kin" as the members of a group that are r = 1/8 or r = 1/16 but usually not less related than that.

This has long bothered me because we're all genetically related and so much cooperation beyond close kin is happening. And it's been hard for me, as someone who sees everything as connected, to read text after text supporting "kin selection" and "kin recognition" (knowing who to be kind to and who to avoid bleeping), to get past the fact that we're arbitrarily deciding what is "kin" and it seems to be for convenience. I'm not doubting that cooperation is important for evolutionary reasons. Quite the contrary! It's just that why is there so much math, based in so many potentially unnecessary assumptions about genes for behavior, gracing so many pages of scientific literature for explaining it or underscoring its importance? 

(It could just be that as an outsider and a non-expert I just don't understand enough of it and if I only did, I wouldn't be gracing this blog with my questions. But let's get back to my reason for posting anyway because it's potentially useful.)

Right. So. Even for folks who aren't part of evolution's academic endeavor, it's obvious to most that we're one half dad and one half mom. The sperm carries one half of a genome, the egg another, and together they make a whole genome which becomes the kid. Voila!

There's even an adorable "Biologist's Mother's Day" song about how we've got half our moms' genome... 


... but there's biology above and beyond the genes we get from mom (and not from dad). And that song is great for teaching us that the rest of the egg and the gestational experience in utero provide so much more to the development of the soon-to-be new human. So "slightly more than half of everything" is thanks to our mothers. Aw!

But, genetically, the mainstream idea is still that we're 50% our mom. 

I teach very basic genetics because I teach evolution and anthropology.And I'm not (usually) a dummy.* I get it. It's a fact! I'm half, genetically, my mom and I'm also half my dad. 

r = 0.5

Okay! But, given these facts about relatedness and how it's imagined in evolutionary biology, facts that I never ever questioned, I hope you can see why this report from 23andMe (personal genomics enterprise) blew my mind:

Percent similarity to Holly Dunsworth over 536070 SNPs (single nucleotide polymorphisms or, effectively/rather, a subset of known variants in the genome; Click on the image to enlarge).
I am 85% like my mom and I am at least 76% like my students and friends who are sharing with me on 23andMe. Names of comparisons have been redacted. As far as I know, this kind of report is no longer offered by 23andMe. I spat back in 2011/12 and the platform has evolved since.

Okay, first of all, it is a huge relief that, of all the people I'm sharing with on 23andMe, the one who squeezed me out of her body is the most genetically similar to me. Science works.

But that number there, with my mother, it is not 50%. It's quite a bit bigger than that. It says I'm over 85% the same as her.

What's more, I am also very similar to every single person I'm sharing with on the site, including example accounts from halfway around the world. Everyone is at least 60-ish% genetically similar to me, according to 23andMe. I know we're all "cousins," but my actual cousins are supposed to be 1/8th according to evolutionary biology. How can my mom be related to me by only one half? How can my actual cousins be only an eighth (which is 12.5%)? 

What is up with evolutionary biology and this whole "r" thing?

Hi. Here is where, if they weren't already, people just got really annoyed with me. Evolutionary biology's "relatedness" or "r" is not the same as genetic similarity like that reported by 23andMe.

Okay!

But why not? 

Let me help unpack the 85% genetic similarity with my mom. Remember, it's not because I'm inbred (which you have to take my word for, but notice that most everyone on there is over 70% genetically similar to me so...).

It's because my mom and dad, just like any two humans, share a lot in common genetically. Some of the alleles that I inherited from my dad are alleles that my mom inherited from her parents. So, not only is everything I got from her (50%) similar to her, but so are many of the parts that I got from my dad. 

Let me get out my kid's arts supplies.

Here is a pretty common view of relatedness, genetically. In our imagination, parents are not related (r = 0) which can lead our imagination to think that their alleles are distinct. Here there are four distinct alleles/variants that could be passed onto offspring, with each offspring only getting one from mom and one from dad. In this case, the sperm carrying the orange variant and the egg with the blue variant made the baby.


1. (Please, if you're horrified by the "r" business in these figures, read the post for explanation.)
But few genes have four known alleles, at least not four that exist at an appreciable frequency. Some could have three. What does that look like? 

The green allele doesn't exist in the next example. As a result of there being only three variants for this gene or locus, mom and dad must share at least one allele, minimum. That means, they look related and that means that, depending on which egg and sperm make the kid, the kid could be more related to mom than to dad. 


2. (Please, if you're horrified by the "r" business in these figures, read the post for explanation.)
Now here's where people who know more than I do about these things say that the kid is not more related to mom than dad because she got only one allele from mom and that keeps her at r = 0.5. 

Well, that's just insane. What does it matter whether she got the allele from mom or dad? I thought genes were selfish? (Sorry, for the outburst.)

Again, I realize I'm annoying people and probably much worse--like stomping all over theory and knowledge and science--by mixing up the different concepts of genetic similarity (e.g. 50%) with "r" (e.g. 0.5) and horribly misunderstanding all the nuance (and debate) about "r," but I'm doing it because I'm desperately trying to know why these two related ideas are, in fact, distinct. 

One last pathetic cartoon. 

In this third example, as is common in the genome, there are only two alleles/variants in existence (at an appreciable frequency, so not accounting for constant accumulation of de novo variation). An example of such a gene with only two known alleles is the "earwax gene" ABCC11 (there's a wet/waxy allele and dry/crumbly one). Here, the two alleles are orange and blue. Most humans in the species will have at least one allele in common with their mate for a gene with two alleles, and it's not because most humans are inbred, unless we want to redefine inbreeding to include very distant relatives (aside: which may be how the term is used by experts). 


3. (Please, if you're horrified by the "r" business in these figures, read the post for explanation.)
But as a result of the chance segregation of either the blue or orange allele into each of the gametes, two people with the same genotype can make a kid with the same genotype. 

And of course, making a kid with your same genotype is the only possible outcome if you and your mate are both homozygous (i.e. where both copies are of the same variant so that leaves no chance for variation in offspring unless there is a new mutation). 

So, I wandered a little bit away from my point with these drawings, but I had to because I wanted to get down from where my imagination has me (us?) with "r" versus how things really are with reproduction. We are baby-making with vastly similar genomes to ours, so we are making babies with vastly similar genomes to ours. 

So, I do see why biology says I'm related to my mom by one half. But, on the other hand, what does it matter if I got the thing I have in common with my mom from my mom or whether I got it from my dad? Because I got it. Period. It lives. Period. 

[Inserted graf January 20, '17] Saying it matters where I got the similarity to my mom keeps us at r = 0.5. Saying it matters only that I inherited DNA like hers keeps us always, all of us, at r > 0.5 with our parents and our kids because any two babymakers share much of their genome.

And the fact that this (see 2 and 3) happens so often is why I'm a lot more than 50% genetically like my mom, and the same can be said about my genetic similarity to my dad without him even spitting for 23andMe. 

So, here we are. I don't understand why our relatedness to one another, based on genetic similarity, is not "r."

I hope it's for really beautifully logical reasons and not something political. 

Because...

If "r" was defined by genetic similarity, then would cooperating with my 76% genetically similar students and friends be more adaptive than the credit I currently get from evolutionary biology for cooperating with my own flesh and blood son? 

If "r" was defined by genetic similarity, then could we use the power of math and theoretical biology to encourage broader cooperation among humans beyond their close kin? 

So many questions.

Maybe I should re-learn the math and learn all the other math.

Nah. Not myself. At least, it wouldn't come fast enough for my appetite. Maybe someone who already knows the math could leave a comment and we could go from there... 

And it would be worth it, you know, because despite my relatively weaker math skills, I bet we're more than 50% genetically similar.





*from 23andMe: "You have 321 Neanderthal variants. You have more Neanderthal variants than 96% of 23andMe customers."