The power of delusion -- genetic causality

What was reported as a dramatic event came this week, if we are to believe, in the official recognition of the fact that human genes co-operate as complex systems, not as some sort of "one gene, one function" machine tools.

Here's the heart of the New York Times article today (7/2/07) by Denis Caruso, identified
as follows: "Denise Caruso is executive director of the Hybrid Vigor Institute, which studies collaborative problem-solving. E-mail: dcaruso@nytimes.com."
A Challenge to Gene Theory, a tougher Look at Biotech

The $73.5 billion global biotech business may soon have to grapple with a discovery that calls into question the scientific principles on which it was founded.

Last month, a consortium of scientists published findings that challenge the traditional view of how genes function. The exhaustive four-year effort was organized by the United States National Human Genome Research Institute and carried out by 35 groups from 80 organizations around the world. To their surprise, researchers found that the human genome might not be a “tidy collection of independent genes” after all, with each sequence of DNA linked to a single function, such as a predisposition to diabetes or heart disease.

Instead, genes appear to operate in a complex network, and interact and overlap with one another and with other components in ways not yet fully understood. According to the institute, these findings will challenge scientists “to rethink some long-held views about what genes are and what they do.”

[T]he report is likely to have repercussions far beyond the laboratory. The presumption that genes operate independently has been institutionalized since 1976, when the first biotech company was founded. In fact, it is the economic and regulatory foundation on which the entire biotechnology industry is built.

But when it comes to innovations in food and medicine, belief can be dangerous.

Overprescribing antibiotics for virtually every ailment has given rise to “superbugs” that are now virtually unkillable.

The principle that gave rise to the biotech industry promised benefits that were equally compelling. Known as the Central Dogma of molecular biology, it stated that each gene in living organisms, from humans to bacteria, carries the information needed to construct one protein.

The scientists who invented recombinant DNA in 1973 built their innovation on this mechanistic, “one gene, one protein” principle.

Because donor genes could be associated with specific functions, with discrete properties and clear boundaries, scientists then believed that a gene from any organism could fit neatly and predictably into a larger design — one that products and companies could be built around, and that could be protected by intellectual-property laws.

In the United States, the Patent and Trademark Office allows genes to be patented on the basis of this uniform effect or function.

In the context of the consortium’s findings, this definition now raises some fundamental questions about the defensibility of those patents.

“We’re learning that many diseases are caused not by the action of single genes, but by the interplay among multiple genes,” Ms. Caulfield said.

Even more important than patent laws are safety issues raised by the consortium’s findings. ...

“Because gene patents and the genetic engineering process itself are both defined in terms of genes acting independently,” he said, “regulators may be unaware of the potential impacts arising from these network effects.”

With no such reporting requirements, companies and regulators alike will continue to “blind themselves to network effects,” he said.

Now, the field of "Systems Dynamics", celebrating its 50th anniversary this week, is devoted to studying how to describe, analyze, and design complex systems made up of many components interacting in "non-linear" ways -- which is to say, interacting so that any given "function" is carried out by many different components acting in concert.

This property, which I've been calling a "scale-invariant" design principle, can be found at all levels of life, or any computer system, from cellular components to genetic "circuits" to humans in a sports team or office, to scientists themselves doing research, to the role individual corporations have in the ecology of the economy.

The big question in my mind isn't really that genes interact and cooperate in getting their chores done -- it's that our best researchers took 31 years to figure this out, working together, in the face of what is sure to be seen, in hindsight, of overwhelming evidence that it is true.

This gets me back to yesterday's post on "The Power of Yarn", and the single sentence that captured the essence of that for me in the Yarn Harlot's story " There are some truths. Things that just are the way they are, and no amount of desperate human optimism will change them."

One of these truths is that living things operate in complex ecologies, not designed to make life easy to analyze. Another such truth is that "feedback is important" and that, again quoting the yarn harlot,

See how 10 is bigger than 9? See how there is no way that 10 can be made smaller than 9?

I've been asserting almost daily that the "scientific method" has a major weakness, as practiced, in that it focuses our attention on separable parts and analysis based on the General Linear Model, that assumes critically that causality is not circular - that is, that there are no feedback loops. Unfortunately for those who wish for such simplicity, Life is dense with such feedback loops, if not actually defined by such loops.

It is an astonishing fact of life, which the Times article reveals, that the desire for life to be simpler is so powerful that it can cause 10,000 "trained" scientists, with PhD's, to take 30 years to finally collectively observe what others outside their mutual-blindness-field already knew.

As I've said, textbooks such as "Feedback Control of Dynamic Systems" are in their 5th editions in Control System Engineering, but biologists, and much of public health's biomedical research community, discount that literature to the point of invisibility and effectively treat it with contempt. To them, this literature does not exist. When seen, it "comes as news to them", and is promptly forgotten, because it conflicts with the shared myth of their culture, and cultural myths always win out over boring contrary evidence.

Science, as an enterprise, as practiced by real people in the real world, is not immune or exempt from such behavior. I really must tip my hat to the late Dorothy Nelkin, who gave a graduate seminar back in the 70's or so at Cornell in "The Sociology of Science", for awakening me to this fact, which, as a physicist by training, was "news to me."

Similarly, Science, as an enterprise, and Medical Science as well, should not be astonished, but often are, that people outside their internally-blinding-fields have less regard for the collective ability to discern truth than the scientists inside the myth-field would expect. In fact, it sometimes appears from outside that the "scientific method", as practiced, produces a type of "idiot-savant" who can see with tremendous power along such a narrow trajectory that they have almost complete peripheral blindness. Their history of crashed theories and trail of mistaken certainties are painfully evident to outsiders, but almost invisible from within.

If confronted with the trail of past casualties of the "scientific method" we get a response that "see, it works!" when , as with biology, in only 30 years they get around to being forced to see something that makes their life more inconvenient and part of their training irrelevant or impotent. Comfortable delusion wins out, especially if shared with everyone nearby and only challenged by distant outsiders who are clearly ignorant fools.

So, yet, it is true, that some biologists have started to realize that in some cases Life involves complex systems and feedback. Perhaps in another 30-50 years, this will be dealt with, and, golly, they might realized that feedback crosses the vertical hierarchy and "local" events may in fact be determined by "distal" factors or even social factors. But I won't hold my breath, because, (a) I can't hold it that long, and (b) this fact would be so inconvenient, and such a problem, that it will find some way to be rejected yet again for another 30 years.

Yesterday, somehow prompted by doing the Time's Sunday Crossword puzzle, I came across a history of how the US Military stubbornly refused to see that airplanes could possibly damage ships at sea - a fact that flew in the face of existing "doctrine." Just as Semmelweiss was ostracized and removed for his myth-challenging assertion that it was doctors' dirty hands that were causing women to die in labor or surgery, so Billy Mitchell was court-martialed for convincing the military that their official doctrine had clay feet.

It is a little puzzling that very good researchers, who wouldn't think of peeking at the identifiers of samples in doing a double-blind experiment to defend against bias, can operate in a world with such huge, collective bias against certain ideas and be oblivious to it and resistant to the meta-idea that such bias exists and that they, caught up in that non-level playing field, have a huge effective bias affecting their results that they are unaware of and not properly countering.

If they knew it was there, yes, the would adjust for it. I love scientists. Part of my heritage is science. They're good researchers, but they're simply not familiar with the power of context to focus and blind and bias their very own selves to facts that are trying to leap off the page. Stephen Jay Gould documented much of the power of this effect so well in The Mismeasure of Man, but most scientists haven't read that, or think it doesn't apply to them because "they're very careful."

This is the heart of all the work in high-reliability systems as well-- how to overcome collectively formed mental models and myths and paradigms that have taken hold and are now blinding everyone to facts they should be seeing, but aren't.

Well, maybe at last, with computer modeling and the power of interactive animations, researchers may realize at last that bias comes in many sizes, and the larger models are almost as hard to see from those embedded within them as gravity waves.

It's not just scientists that are prone to this, but many of the rest of us have a little more humility or experience and realize our judgement is not 100% reliable. Scientists when they have checked off the boxes within their own tiny trajectory that has now become their entire world seem, collectively, to lack such humility - sort of an iatrogenic side-effect of the PhD process and of hanging around a very non-diverse crowd that shares the same viewpoint.

These silos of tertiary specialization are the source of much friction, particularly if it is not recognized that the distortion of the perspective of the silo is causing the blindness.

More on this in some later post. It's too important to breeze by, and core to the frustrating battle between religion and science over large-scale social processes.

This is the challenge all organizations, all cultures, all s-loops face -- how to achieve dynamic stability, to be resistant to type-1 errors of being too gullible and believing flashes in the pan, but of being still capable of avoiding type-2 errors - of being to stubbornly fixed on a particular data value, or mental model, or paradigm, or goal-set, or identity that it cannot accept any feedback at all and there is no reasonable way to get updates up to the top where they do any good.

This is perhaps the single largest core cybernetic challenge for a survival-enhancing model.


Wade