Artistic tendencies linked to 'schizophrenia gene'

We're all familiar with the stereotype of the tortured artist. Salvador Dali's various disorders and Sylvia Plath's depression spring to mind. Now new research seems to show why: a genetic mutation linked to psychosis and schizophrenia also influences creativity.

The finding could help to explain why mutations that increase a person's risk of developing mental illnesses such as schizophrenia and bipolar syndrome have been preserved, even preferred, during human evolution, says Szabolcs Kéri, a researcher at Semmelweis University in Budapest, Hungary, who carried out the study.

Kéri examined a gene involved in brain development called neuregulin 1, which previous studies have linked to a slightly increased risk of schizophrenia. Moreover, a single DNA letter mutation that affects how much of the neuregulin 1 protein is made in the brain has been linked to psychosis, poor memory and sensitivity to criticism.

About 50 per cent of healthy Europeans have one copy of this mutation, while 15 per cent possess two copies.

Creative thinking

To determine how these variations affect creativity, Kéri genotyped 200 adults who responded to adverts seeking creative and accomplished volunteers. He also gave the volunteers two tests of creative thinking, and devised an objective score of their creative achievements, such as filing a patent or writing a book.

People with two copies of the neuregulin 1 mutation – about 12 per cent of the study participants – tended to score notably higher on these measures of creativity, compared with other volunteers with one or no copy of the mutation. Those with one copy were also judged to be more creative, on average, than volunteers without the mutation. All told, the mutation explained between 3 and 8 per cent of the differences in creativity, Kéri says.

Exactly how neuregulin 1 affects creativity isn't clear. Volunteers with two copies of the mutation were no more likely than others to possess so-called schizotypal traits, such as paranoia, odd speech patterns and inappropriate emotions. This would suggest that the mutation's connection to mental illness does not entirely explain its link to creativity, Kéri says.

Dampening the brain

Rather, Kéri speculates that the mutation dampens a brain region that reins in mood and behaviour, called the prefrontal cortex. This change could unleash creative potential in some people and psychotic delusions in others.

Intelligence could be one factor that determines whether the neuregulin 1 mutation boosts creativity or contributes to psychosis. Kéri's volunteers tended to be smarter than average. In contrast, another study of families with a history of schizophrenia found that the same mutation was associated with lower intelligence and psychotic symptoms.

"My clinical experience is that high-IQ people with psychosis have more intellectual capacity to deal with psychotic experiences," Kéri says. "It's not enough to experience those feelings, you have to communicate them."

Intelligence's influence

Jeremy Hall, a geneticist at the University of Edinburgh in the UK who uncovered the link between the neuregulin 1 mutation and psychosis, agrees that the gene's effects are probably influenced by cognitive factors such as intelligence.

This doesn't mean that psychosis and creativity are the same, though. "There's always been this slightly romantic idea that madness and genius are the flipside to the same coin. How much is that true? Madness is often madness and doesn't have as much genetic association with intelligence," Hall says.

Bernard Crespi, a behavioural geneticist at Simon Fraser University in Burnaby, British Columbia, Canada, is holding his applause for now. "This is a very interesting study with remarkably strong results, though it must be replicated in an independent population before the results can be accepted with confidence," he says.

Molecule's constant efforts keep our memories intact

Our mind often seems like a gigantic library, where memories are written on parchment and stored away on shelves. Once filed, they remain steadfast and inviolate over time, although some may eventually become dusty and forgotten.

Now, Reut Shema, Yadin Dudai and colleagues from the Weizmann Institute of Science have found evidence that challenges this analogy. According to their work, our memory is more like a dynamic machine - it requires a constant energy supply to work. Cut the power and memories are lost.

Shema found that the plug that powers our memories is an enzyme called PKMzeta. This molecule is vital for a process called long-term potentiation (LTP) where a the strength of a synapse - the connection between two nerve cells - is increased in the face of new experiences. This process, and thus PKMzeta, fuels the production and storage of new memories.

Shema demonstrated the importance of PKMzeta by inactivating it in the brains of rats. He trained the rats to avoid the taste of the artificial sweetener saccharin and then injected the part of their brains that control taste with a chemical called ZIP that stops PKMZeta from doing its thing.

The results were striking - ZIP erased the rodents' memories of what they'd learnt. It even killed off the relevant memories when the rats were injected a month after their training. In human terms, that's the equivalent of erasing memories that were several years old.

Even if the rats were given trials to reinforce their aversion to saccharin, they forgot all about it once ZIP was brought into play. Rehearsal didn't 'immunise' them against the loss of PKMzeta.

More surprising still, the process seemed to be irreversible, at least within the duration of the experiment. Twelve days after ZIP was administered, the rats still had no recollection of the supposed unpleasant taste of saccharin. Their memories had not just been clouded over, they seemed to have been truly erased.

ZIP has no effect on how well the rats created new memories - if they were injected before they were taught to avoid saccharin, they picked things up just as well. But it seems that PKMZeta is vital for the continuing existence of new memories.

If results can be generalised to other parts of the brain, and indeed, to humans, they suggest that memories are not simply writ once on our mental network and left to be retrieved. They exist because of ongoing processes in the brain. Long after they are created, memories are still incredibly vulnerable to loss, perhaps even irreversibly so.

This impermanence may actually be beneficial - it could render the entire network more flexible and make it easier for new experience to be added to the mix.

Reference: Shema, Sacktor & Dudai. 2007. Rapid erasure of long-term memory associations in cortex by an inhibitor of PKMzeta. Science 317: 951-953.

Most questions of whether and how language shapes thought start with the simple observation that languages differ from one another. And a lot! Let's take a (very) hypothetical example. Suppose you want to say, "Bush read Chomsky's latest book." Let's focus on just the verb, "read." To say this sentence in English, we have to mark the verb for tense; in this case, we have to pronounce it like "red" and not like "reed." In Indonesian you need not (in fact, you can't) alter the verb to mark tense. In Russian you would have to alter the verb to indicate tense and gender. So if it was Laura Bush who did the reading, you'd use a different form of the verb than if it was George. In Russian you'd also have to include in the verb information about completion. If George read only part of the book, you'd use a different form of the verb than if he'd diligently plowed through the whole thing. In Turkish you'd have to include in the verb how you acquired this information: if you had witnessed this unlikely event with your own two eyes, you'd use one verb form, but if you had simply read or heard about it, or inferred it from something Bush said, you'd use a different verb form.

Your brain, after all, is encased in darkness and silence in the vault of the skull. Its only contact with the outside world is via the electrical signals exiting and entering along the super-highways of nerve bundles. Because different types of sensory information (hearing, seeing, touch, and so on) are processed at different speeds by different neural architectures, your brain faces an enormous challenge: what is the best story that can be constructed about the outside world?

Series: Digested read Previous | Index The Case for God by Karen Armstrong

John Crace

May the words of my mouth and the meditations of my heart make Dawkins and Hitchens burn in Hell, O Lord my Rock and my Redeemer. Amen.

Much of what we say about God these days is facile. The concept of God is meant to be hard. Too often we get lost in what Greeks called logos (reason) rather than interpreting him through mythoi - those things we know to be eternally true but can't prove. Like Santa Claus. Religion is not about belief or faith; it is a skill. Self-deceit does not always come easily, so we have to work at it.

Our ancestors, who were obviously right, would have been surprised by the crude empiricism that reduces faith to fundamentalism or atheism. I have no intention of rubbishing anyone's beliefs, so help me God, but Dawkins's critique of God is unbelievably shallow. God is transcendent, clever clogs. So we obviously can't understand him. Duh!

I'm going to spend the next 250 pages on a quick trawl of comparative religion from the pre-modern to the present day. It won't help make the case for God, but it will make me look clever and keep the publishers happy, so let's hope no one notices!

The desire to explain the unknowable has always been with us and the most cursory glance at the cave paintings at Lascaux makes it clear these early Frenchies didn't intend us to take their drawings literally. Their representations of God are symbolic; their religion a therapy, a sublimation of the self. Something that fat bastard Hitchens should think about.

Much the same is true of the Bible. Astonishingly, the Eden story is not a historical account, nor is everything else in the Bible true. The Deuteronomists were quick to shift the goalposts of the meaning of the Divine when problems of interpretation and meaning were revealed. So should we be. Rationalism is not antagonistic to religion. Baby Jesus didn't want us to believe in his divinity. That is a misrepresentation of the Greek pistis. He wanted everyone to give God their best shot and have a singalong Kumbaya.

We'll pass over Augustine and Original Sin, because that was a bit of a Christian own goal, and move on to Thomas Aquinas, in whom we can see that God's best hope is apophatic silence. We can't say God either exists or doesn't exist, because he transcends existence. This not knowing is proof of his existence. QED. A leap of faith is in fact a leap of rationality. Obviously.

Skipping through the Kabbalah, introduced by the Madonna of Lourdes and Mercy (1459 - ), through Erasmus and Copernicus, we come to the Age of Reason. It was unfortunate that the church rejected Galileo, but that was more of a post-Tridentine Catholic spat than a serious error and it didn't help that a dim French theologian, Mersenne, conflated the complexities of science with intelligent design, but we'll skip over that.

Things came right with Darwin. Many assume he was an atheist; in reality he was an agnostic who, despite being a lot cleverer than Dawkins, could not refute the possibility of a God. Therefore God must exist, or we drift into the terrible nihilism of Sartre where we realise everything is pointless. Especially this book.

The modern drift to atheism has been balanced by an equally lamentable rise in fundamentalism. Both beliefs are compromised and misconceived. The only logical position is apophatic relativism, as stated in the Jeff Beck (1887- ) lyric, "You're everywhere and nowhere, Baby. That's where you're at."

I haven't had time to deal with the tricky issues of the after-life that some who believe in God seem to think are fairly important.

But silence is often the best policy - geddit, Hitchens? And the lesson of my historical overview is that the only tenable religious belief is one where you have the humility to constantly change your mind in the face of overwhelming evidence to the contrary.

God is the desire beyond this desire, who exists because I say so, and the negation of whose existence confirms his transcendence. Or something like that.

And if you believe this, you'll believe anything.

The digested read, digested:

The case dismissed.

Evolution is a tinkerer. When novel features evolve, old parts are co-opted for new roles.

Illustration: Alison Schroeer

Open any biology textbook with decent evolution coverage, and you’ll find a version of a familiar diagram—a bat’s wing, a dolphin’s fin, a horse’s leg, a human’s arm. These vertebrate-limb structures are homologous, their similarities the result of shared origins in an ancestral mammal with a general-purpose limb. Evolution has modified each, but all have a common internal structure, a common embryological origin, and a fossil history that reveals a shared phylogenetic origin.

Comparative biology seems to make it clear that the limbs of invertebrates such as insects have different origins. There is little correspondence to what we see in our own structure: Insect limbs lack bones altogether. Embryologically, insect limbs arise as repeated segmental bulges in the cuticle. The comparative evolutionary history of vertebrates and invertebrates is most telling. The ancient chordate ancestors of our finned or limbed modern vertebrates were completely limbless, little more than undulating ribbons of eel-like swimmers, and our appendages are evolutionary novelties, less than 500 million years old. The arthropods, on the other hand, have been flourishing elaborate limbs for as long as they appear in the fossil record, beginning with tracks laid down in the pre-Cambrian, easily 500 million years ago. The last common ancestor of insects and mammals was a legless worm, and each of our lineages independently worked out how to build limbs, so they can’t be homologous.

The same can be said of other structures, like our eyes: The mirror eyes of scallops, the compound eyes of arthropods, and the camera eyes of chordates each represent a unique and unlinked solution to the problem of vision. We would not call a dragonfly eye and a human eye homologous—they seem so different, in so many ways, and the evidence suggests that our last common ancestor was eyeless, with little more than photosensitive spots.

And yet…

A curious phenomenon has nagged at biologists for the past few decades, as they have acquired better tools for probing deeper into the molecular biology of diverse organisms. Where they once assumed that the passage of vast amounts of time, over half a billion years in this case, would have produced divergences in the molecular patterns that govern animal forms as radical as those seen in the forms themselves, it now seems that something else transpired. As we discover more about the molecular basis of building structures like limbs and eyes, we’re finding more instances of homologous molecular players being recruited to do similar jobs in morphological features that are not themselves homologous.

Take insect and vertebrate limbs. They evolved independently, but the molecules that stake out the orientation and location of the various tissues within both kinds of limbs are homologous to an impressive degree. For example, a gene named distal-less in flies affects the tips of the limbs most strongly. A homologous mouse gene called Dlx, revealed as such by their nearly identical sequences, is similarly important in regulating the formation of the most distal elements of the limb.

The similarities go further. The dorsal-ventral boundaries of the vertebrate limb bud and the insect wing disc are established by a gene called fringe; other axes and boundaries are defined by genes in the wingless, apterous, hedgehog, and decapentaplegic families, and they operate in roughly similar ways in both groups of animals. This is like discovering that two cultures have independently invented a game like basketball, and then finding that while the games look vastly different in play, the court dimensions are the same, right down to the distance of the three-point line and the diameter of the center circle. It should make one question how independent their origins actually are.

The underlying similarities in eyes are even more striking. Eyes have evolved dozens of times and diverged wildly, as in the compound eyes of insects and the camera eyes of vertebrates, and have also on occasion converged on similar solutions. The octopus eye and the human eye superficially resemble each other from the outside, but structurally the tissues of each are organized in profoundly different ways, with different arrangements of cells in the retina, different kinds of photosensitive cells, and very different optic nerves. Dig deeper still, however, and all these eyes—octopus eyes, human eyes, fly eyes, spider eyes, flatworm eyespots—have a common master regulator gene, called Pax-6 in vertebrates and eyeless in flies. Wherever the animal expresses this gene, it initiates a cascade of activity that leads to the formation of an eye. And the genes are interchangeable! Extract Pax-6 from a mouse, inject it and express it in the limb of a fly, and the confused tissues of the fly will respond by assembling an eye—a fly’s eye—on its limb.

The photoreceptor types in the eyes were once thought to be distinct. Invertebrates have rhabodomeric cells that use a special version of the photopigment called r-opsin, and activate cells by a particular pathway called a phospholipase-C cascade. We vertebrates have ciliary cells, c-opsin, and a phosphodiesterase pathway. These are fundamental differences, and scientists have not changed their minds about the large differences between the two, but they have discovered an enlightening fact. Many animals have both! In our eyes, we primarily use the ciliary photoreceptors for vision, but we also maintain a set of rhabdomeric photoreceptors that have the job of sensing light to set circadian rhythms. Some invertebrates also have both, but they use the rhabdomeric receptors for vision and the ciliary receptors for circadian rhythms. It is not a difference in kind, but a difference in specialization and emphasis that distinguishes the visual systems of each lineage.

To make sense of the apparent conflict between anatomical divergence and a shared genetic inheritance, three biologists—Neil Shubin, Cliff Tabin, and Sean Carroll—have proposed that we need a new concept that they call deep homology. Evolution is a tinkerer that cobbles together new functions from old ones, and the genome is a kind of parts bin of recyclable elements. When new features evolve, the parts in the bin are co-opted to operate in new roles. As a result, the same parts appear in anatomically and evolutionarily distinct structures because it is faster and easier to reuse an old gene network that almost does what is needed, than it is to spend another few million years evolving a distinct gene for the function.

This makes these master genes precisely analogous to the stock of goods found in a hobbyist’s electronics store. Standard subunits—oscillators, op-amps, field effect transistors, switches, rheostats, and so forth—will get incorporated into many different kinds of projects; whether she is building a radio or a synthesizer or a burglar alarm, the hobbyist will find it easier to just grab an oscillator integrated circuit off the shelf than to design her own. We could sample devices built by different hobbyists with different purposes, and when we rummaged about in their insides, we would find the same subunits incorporated into novel, larger assemblies.

This is what we’re seeing in biology, too. We find an evolutionary novelty, like the vertebrate limb, and we can determine that it arose uniquely in our lineage. At the same time, we find a deeper heritage of shared genes that we hold in common with all other animals—a metazoan tool kit upon which we all draw to evolve.

An unconventional approach to analyzing molecular sequences allows researchers to construct larger evolutionary trees.

Organizing the world’s species into branches on a phylogenetic tree is a major goal of biologists trying to understand how life evolved. DNA-sequencing technologies are providing them with more information than ever with which to accomplish this goal, but with less than 1 percent of all species currently placed in any kind of phylogeny, there is still much work to be done. In a recent paper in Science, researchers at the University of Texas at Austin introduced new tree-building software that could expand the tree of life and change our understanding of evolution.

One way to construct evolutionary trees is with software that compares and interprets discrepancies between the molecular sequences of different species using various statistical techniques. The robustness of the math driving these techniques largely determines the speed and accuracy of a given tree-building method. Thus taking a mathematically well-grounded approach to constructing evolutionary trees can limit a method’s scope. “The statisticians who have been developing these methods have been really trying to get the mathematics right,” explains Tandy Warnow, a phylogeneticist at the University of Texas at Austin. “And getting the mathematics right really does tend to limit you to small datasets.” Many programs are only fast enough to handle about 20 molecular sequences at a time—a paltry number considering the datasets biologists are trying to analyze are usually anywhere from a few hundred to a few thousand sequences.

To find out just how slow these programs were, Warnow attempted to run them on a data set of 100 sequences. “They looked like they were not going to complete for months and months and months,” she says. Larger datasets, then, could take decades.

“There is a clear and desperate need for methods that compute phylogenetic trees much faster,” says Antonis Rokas, a biologist at Vanderbilt University, adding that scientists ultimately hope to build trees containing millions of species.

To address the problem, Warnow and her colleagues developed a tree-building program called SATé capable of processing 1,000 sequences in 24 hours. She refers to the statistical method used by SATé as “not completely kosher” in her field, because in order to up the speed and power of the software, her team used mathematical techniques without solid theoretical grounding. “We’re not following a mathematically rigorous approach,” she says. But the risk paid off: SATé constructed trees with a high degree of accuracy from simulated datasets as well a real one whose tree structure had already been determined.

SATé solves another problem common among tree-building programs. Some species’ DNA changes so quickly that their molecular sequences from generation to generation can be quite different and thus more difficult for software to compare. But SATé is able to handle many of these rapidly evolving species and by doing so opens previously impenetrable datasets to new types of phylogenetic analysis.

“This is certainly a big step in the right direction,” Rokas says. “And I expect this software to be used more and more.”

Because Warnow’s team developed SATé using mathematical methods they don’t yet completely understand, it is still a mystery how the program is able to deal with rapidly evolving sequences so successfully. “We have something that works well but doesn’t really yet have an explanation,” Warnow says. According to her, learning how the program works will require the attention of a strong probabilist.

“The difficulty is finding mathematicians interested in the biological problems,” explains Rokas. But if mathematicians can determine why SATé is able to outperform other tree-building methods, Warnow may be able to improve upon the design of SATé to consider even larger sets of data and move closer to the goal of constructing a tree of life containing all species.

Rokas explains that Warnow’s research is so successful because she understands the practical considerations facing biologists. “I want software that is easy and that runs quickly so that I can train my students to use it,” he says. SATé, which works on a laptop computer, was made to do just that. “We designed it so that it was really going to be easy for anyone to use,” Warnow explains.

By taking a step away from the mathematically well-understood approach to molecular phylogenetics, Warnow’s team was able to address the needs of researchers like Rokas. SATé enables scientists to handle real-world databases of a wider range of species, and, according to Warnow, this could lead to new scientific discoveries and have broad implications for evolutionary biology. What remains to be seen is how far Warnow can push mathematicians to solve the problems necessary to move SATé—and our understanding of evolution—forward.

Aristotle analyzed virtues into moral and intellectual virtues (or dianoetic virtues, from the Greek aretai dianoetikai). In the Posterior Analytics and Nicomachean Ethics he identified five intellectual virtues as the five ways the soul arrives at truth by affirmation or denial. He grouped them into three classes:

• Theoretical
  • Sophia - wisdom of the eternal and unchangeable, philosophical wisdom.
  • Episteme - scientific knowledge, empirical knowledge.
  • Nous - intuitive understanding.
• Practical
  • Phronesis - practical wisdom/prudence.
• Productive
  • Techne - craft knowledge, art, skill.

Subjacent intellectual virtues in Aristotle:

• Euboulia - deliberating well, deliberative excellence; thinking properly about the right end.
• Sunesis - understanding, sagacity, astuteness, consciousness of why something is as it is. For example, the understanding you have of why a situation is as it is, prior to having phronesis.
• Gnomê - judgement and consideration; allowing us to make equitable or fair decisions.
• Deinotes - cleverness; the ability to carry out actions so as to achieve a goal.