Illness as big data problem? The bicameral mind

Supercomputer; Wikimedia

We attended a very interesting discussion of Alzheimer's disease the other day, by an historian of science.  The speaker gave his overview of the history of the disease, from 1906 when it was first described by Dr Alois Alzheimer to today, 107 years and billions of research dollars later.  After much discussion of what we've learned and what we still don't know, it seemed we pretty much all agreed that dementia is a tough problem, predicting who will get it is a tough problem, and while some progress has been made in understanding the early onset form of Alzheimer's, we've got a long way to go in the development of treatment for the disease, whether early or late onset.

And then a physicist in the room spoke up.  He didn't understand why people were so pessimistic about our ability to eventually understand the disease.  Or any disease.  He himself is certain that with the incredible computing power we've got now we'll be able to understand, and predict, them all. A few others in the room signed on to that, none of them physicists, but similarly optimistic.

A piece has just been published at Wired online (18 March 2013) that says much the same.  Richard Barker: "Illness just became another big data problem."  Barker describes the case of an infant born with a rare form of type 1 diabetes for whom the proper treatment is begun once the child is genotyped and his particular mutation identified. 

So diabetes isn't just diabetes: it's a cluster of diseases with different causes and different remedies. This story is just a glimpse of a quiet medical revolution: from defining diseases by the symptoms they cause or the part of the body affected, to the underlying molecular mechanism.

Further, if this child had been sequenced at birth, as our children, or grandchildren, or great-grandchildren will be, his illness would have been identified before he was even ill, and his treatment would have been started immediately.  This day is coming.

An anthropological question:  fad, fact, or cultural bias?
This all sounds very hopeful.  But history shows how at any given era there is a working model of how to do things, and basically everyone except mavericks follow suit.  We want to be in on things, to be doing what seems right, to have support from our fellows, and the comfort all of this brings.  We often stick to this even if there is no real evidence that it is working or evidence that it may not be the best approach.  The long-lasting nature of Galenic (four-humours) medicine is one example.  Armies routinely train for the last war, and pay a price for it.  Religions, though supposedly based on ultimate divinely given truths, form sects and alter their doctrine.

At the same time, it may be--especially in science--that the current way, though imperfect, is the result of centuries of improvement and is the best we can do at any given time.  Certainly we'll not just quit because we know our methods have imperfections!  So, it is fair to ask: is illness now just a data crunching problem?

Well, we can pretty much eliminate infectious diseases right off the bat.  While there may be identifiable genetic susceptibility that explain a small minority of resistance to some infectious diseases, this is by far overwhelmed by other factors that predispose people to infection, like poverty and bad luck.  That makes a lot of illness around the world not reducible to a data crunching, at the individual level.  There's certainly a lot of population-based data crunching that can model risk and explain it in populations, but no amount of sequencing of infants at birth will identify those who will be at highest risk come the next epidemic. 

Then there are complex diseases, like heart disease, or type 2 diabetes or asthma or schizophrenia or autism or hypertension or stroke or most cancers.  Sequencing can't now, and although it's not fashionable to say so, many believe will never be able to predict accurately who's at risk of most of these diseases, for reasons that we write about here all the time.  They're complex, they're polygenic, everyone has a different and unique genome, and a different pathway to disease, environmental factors are causal, and inherently unpredictable.  And so forth.

So now we've pretty much eliminated the big causes of death around the world from the illness as big data problem model.  What's left?

Mendelian diseases, like the form of diabetes Barker described, or the thousands of other primarily very rare and usually pediatric diseases that really are genetic, many of which are now, and will eventually be, identifiable and usually (but not always) predictable with genetic data.  But, many such diseases and disorders are themselves very complex -- cystic fibrosis is a well-studied and well-characterized example, with over 1000 different implicated alleles, all in the same gene, identified to date.

Studies of unexplained genetic disorders, that is where there is familial risk and some cases have an identified gene, have about a 25% success rate for identifying a causal mutation.  Granted, by now it's probably the toughest, rarest disorders that are left to explain -- and/or those without effective enough advocacy groups to have lobbied for funding; but some of these will be explained, while others will not, because there can be numerous pathways to the same phenotype, and what's causal for one individual won't explain it in another.  This is something we know very well already.

Late spring wildflowers; Wikimedia

That complexity isn't always reducible is an idea approached from a completely different angle in a beautiful piece in Aeon Magazine on March 19, by Olivia Laing.  Now a writer, she describes her one time life as an herbalist, trained in the ways of western medicine to understand the molecular properties of the herbs she prescribed for sick patients, and her growing discomfort with the idea that it was all reducible to molecules.

She tells the story of how it had been believed that the Neanderthal buried their dead with flowers, or may even have used flowers medicinally, based on pollen finds in caves in which skeletons were found.  It was a beautiful idea, she writes, except that it was probably wrong.  The pollen was more likely blown in by the wind, or carried in on a rodent's fur. 

I confess to finding this story pleasing, not disappointing. It exposes the depths of our fantasies about people and plants, showing how pattern-driven we are, and how addicted to stories. At the same time, it reveals the baffling complexity of the natural world, its resistance to understanding. No matter what meanings we ascribe to them, plants maintain their mystery. I might not handle them daily anymore, but I like to think of them growing in the fields and waysides of the world: rue and cockspur, nettle and rosemary, rising from the soil year after year to spell out a code we may not ever completely crack.

The problem of the bicameral mind
It has often been said that humans have a 'bicameral' mind: one half is devoted to particular things, with analytic functions, the other to more overall or holistic impressions.  Whether this is literally true or accurate, in science we can trace two similar main kinds of thinking about Nature back through history.

One is the qualitative, enumerative, reductionist particularistic view of causation: causes are individual forces or 'things' and the job of science is to identify them and how they work. To do that, we have to isolate them, and to do that we must reduce our observations to the most rudimentary level--such as molecules, where the causes actually operate. We do this through experimental designs and so on.  We do it because complexity obscures individual causes.  This is the gene mapping approach, the number-crunching idea that we'll just overwhelm Nature with our computers and force it to yield its individual causes.  Mendelian genetics has been an exemplar of this worldview since the turn of the 20th century. It assumes great regularity in Nature, and that the scale of our data and so on are all that prevents us from identifying causes.

The other view is quantitative, and basically holds that Nature works through complex interactions at higher levels than rudimentary forces.  A building cannot be understood by enumerating its bricks, beams, and wires, even if those things are needed and in that rudimentary sense 'cause' or explain the building. But interactions of very complex forms are instead viewed by quantitative minds as the organizing principles, or higher-level 'causes', that we need to understand.  Quantitative genetics as separate from Mendelian genetics has always been a major component of biology, and was basically Darwin's view of evolution.  It treats genetic and evolutionary causation in aggregate, without attempting to enumerate its components.  This view today, though currently held by the vast minority because it's under siege by the reductionist majority, would be that which argues that computer crunching is not what we need: what we need is more innovative thinking about how complex causation works and/or is to be understood and manipulated.

This qualitative/quantitative dichotomization is an oversimplified characterization, and we don't mean to suggest that the world is just a contest between opposites that will ultimate resolve (that's a view of philosophers such as Hagel, and thinkers like Marx).  Still, it reflects widespread differences in world views--of communication between our two brain hemispheres, one might say.

There are attractions and attributes to these different points of view and their intermediaries.  How they will resolve, or if they will, remains to be seen.

Reducible Complexity: reply to the IDeologs

The gaggle that continue to raid evolutionary biology blogs, patrolling for things that can be naively or intentionally misinterpreted as evidence for their theological views, specifically 'Intelligent Design' (ID), loves to concentrate on complex traits.  They claim such traits cannot have evolved because the independent components won't function on their own and the whole breaks down without them.  They call that Irreducible Complexity:  since you can't take any components of complex traits away and still be viable, such traits could not have arisen gradually by natural selection.  Therefore (the IDeologs say), Intelligent Design is true.  But this is false on several grounds, not all of them even recognized by biologists, who often defend evolution by needlessly agreeing to do it on the IDeologs' turf.

First, it is IDiotic to argue that if an evolutionary claim is false, therefore creationism is true.  That is simply a logical fallacy.  If evolution as biologists see it were being misperceived, that in no way provides evidence for any specific counter explanation.  Only an IDeolog would make such an argument.  It would be just as sensible--that is, as nonsensical--to say that our misperception proved that life came to earth from a parallel universe in a spaceship made of banana peels.  We get things wrong or understand them incompletely in evolutionary biology, which is why it remains an active science, but that is not evidence that evolution didn't happen.

Second, the major IDiotic argument about the need for completeness was one Darwin was aware of and even speculated on in regard to the eye, a favorite irreducible complexity example cited from that time to the present day.  Darwin suggested ways that primitive light sensitivity could have evolved bit by bit.  In what was really striking prescience, his basic speculations have been shown to be about right, because species alive today with 'partial' vision have been found, and genetic components of vision are shared among species with simple as well as complex light reception.  Even saying 'partial' vision is a subtle misnomer, because each species uses what it has: the light sensitivity of a worm or bacterium is not partial for their uses, and to use the adjective suggests the IDiological view that humans are at an intended pinnacle, that our vision is somehow more complete or real than a clam's.  That's an egocentric misperception of evolution.

Complexity is reducible!  It always has been.  It's a central aspect of life.   Right here and now
Thirdly, and perhaps even more important than the first two reasons why the anti-evolutionary IDeology is just plain wrong is that complexity is typically reducible!  The basic IDeologs' premise doesn't have to be refuted because it's not true.

What we know very well is that most traits of organisms are, in fact, the result of multiple interacting factors (gene networks, the  polymeric, cooperative nature of DNA and proteins, signaling and receptors systems, gene regulation, and multipart proteins, etc.).  And, eyes, too.  That is a central fact, and a main point of MT (the blog and the book).  We know from thousands of studies (yes, even the GWAS and other 'omics' studies whose excesses we love to point out) that complex traits really are complex at the gene level.

The same studies also show by their very nature--by the very fact that we are doing so many of them in the first place--that each person will have a different genotype, a different set of variants, involved--even if they have the 'same' trait, like stature, insulin levels, blood pressure, or behavior.  That is why personalized genetic medicine is unlikely to work nearly as well as advertised.  Personalized medicine almost assumes irreducible complexity: enumerate the parts and then any variation in the trait must be due to a broken part that can be identified.  But that isn't how Nature works.

Reducible complexity is true even of vision: Color-blind people are people and they have vision, yet they are missing functional light-sensitive genes (e.g., genes that are used in red or green detection, or overall light sensitivity). Visual acuity varies in all sorts of ways among perfectly viable people.

This is typical of biological traits.  And recent studies have clearly shown that each of us is walking around with numerous completely inactivated genes, whose 'damaged' sequence variants we have inherited--from parents who somehow had managed without them.  One recent paper found that around 165 different genes were completely inactivated (both copies not working) in a typical person.  And there are many others in which one of our two copies is not working normally.  The combination of inactive genes would be different for each person, but the truth is that we do not normally need all the genes in our genome.  That tolerance of variation is exactly the working material that biologists have known is at the basis for evolution from Darwin's own time.

Confirming this in another way, and also very clearly, is that it is routine that a gene experimentally inactivated in a laboratory animal, like a mouse, has serious effects in some strains but little or even no effect in others. A mutation causing a serious disease in humans may do nothing when the same mutation is tested in a mouse, or it may have similarly bad effects only in some strains.  That's one of the notorious problems with mouse models for human traits: mice and people share many traits but we make them differently to various extents. There is more than one way to make the same trait.  Complexity is reducible.

The reducibility of a trait, to put it in terms even an IDeolog could understand, depends on the combination of genes being viable, not on every gene having the most functionally efficient variants.  The importance of component cooperation, a favorite MT word, is in part that various types of cooperation are viable.  That aspect of redundancy and variation is one of the central reasons that complexity could evolve in the first place, exactly in the general fashion argued by Darwin and since.  No biologist suggests that an eye just emerged wholesale from the primeval slime.

But there's more.  Studies of the nature and evolution of genomes shows very clearly that genetic mechanisms arise largely by means that generate redundancy as well as alternative pathways to given outcomes, as cells respond to their local environment.  Gene duplication occasionally leads to individuals with two copies of a gene where in their ancestors there was only one (this happens in species generally, not particular to humans in any way).  That can provide redundancy, so that one of the copies can acquire mutations that alter what the gene does, while the other copy keeps plugging along with the original function.  The new function can be due to mutations in the  protein code of one of the copies, or the DNA sequences that regulate when and where the gene is used.

For these reasons, traits are the result of many different genetic contributions, all varying among individuals, each reaching similarly viable traits with different combinations of that variation.  Those combinations that aren't functional don't survive or reproduce; those that have an advantage may do better.  Over time, the mix of variation, including even the number and set of contributing genes, allow traits to evolve new or altered function.

This is how evolution works, gradually producing new or varied traits.  We understand this because we are aware that complexity is often, or even typically, reducible.  Although it hasn't been put this way before to our knowledge, this is nothing more than a modern understanding of classical evolutionary ideas.

The IDeologs claim that reduced complexity could not have existed in a stepwise, bit by bit, assembly of a new trait from parts that would not work on their own--that evolution couldn't get from there to here. But the deeper truth is that evolution is both there ('incomplete') and here ('complete') today and has been that way at any or even every time in the past.   It isn't just that things have to be assembled over time by different steps, but that they exist at any given time in various steps or stages of 'completeness.'  To a great extent, biological complexity is  inherently reducible at any time as well as over time.

And one more reason:  Of course, we needn't have gone through all of this to convince you that complexity was reducible, after all.  That is because the IDeologs disprove their own irreducibility argument by their very existence:  one can function as a human being even with a brain that allows you intentionally not to use it to recognize the realities of the world--by not using the thinking complexity they were born with!  We would apply this to those who lead the movement, and do or should know better, but not those who they naively lure into adopting its know-nothing IDeology.


Finally, we may make sport of intentionally or willfully self-deluded critics of evolution.  For any of those who are sincere but naive, one can only say that it's too bad, and poignant, too, that science shows the evolutionary nature of life, rather than the comforting existence of a benign divinity who graced the earth with our presence.  How nice if that could be true!  How hard it makes it to understand the injustices and suffering in the world.  But science is about the real world, not the one we might wish for.