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Archive for the ‘DRD2’ Category

liqorsto

Sign on the window reads, “10% off for rs1800497 TT“ … on account of the way their DRD2 receptors seem to be less responsive … which, naturally, makes them prone to needing to drink (buy) more to feel the same pleasure as CC people. It’s just the free market at work right?

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As a big fan of black and white photography, I’m intrigued by the concept of “Splitting” or so-called “black and white” thinking.  It’s something we all do to different degrees … when we avoid dealing with the “shades of gray” and group things in our life into “all good” or “all bad” groups.

Psychologists have considered this cognitive tendency to be a normal part of cognitive development (eg. good guys vs. bad guys), a response to stress, and also a part of various psychopathologies (funny, how psychiatrists have a tendency to group us into the “normal” and “abnormal”, huh?).

Is there anything wrong with seeing the world in black and white?  Perhaps, if you label mildly annoying people as “bad”, you’ll soon have no friends … but otherwise, I’m not sure.  Simplicity can be soothing.

I mean, our brains have a strong tendency to work at the extremes … for example, when it comes to cognition and movement.  We’re wired with so-called striatonigral (Go) and striatopallidal (NoGo) neural pathways that are engaged when cognition is transduced into action.  In the primal world of our ancestors, we didn’t survive very long if we danced around fretfully pondering the costs and benefits of running, or not running, from saber tooth tigers!  So, it’s no surprise, that we’re inherently uncomfortable in the wishy-washy, indecisive, muddling middle ground when making a decision.  We want to “go” or “freeze”, “do it” or “don’t”, “good” or “bad” … just make a f**king decision already.

Here’s a link to some current research on the “Go” and “NoGo” brain systems … and their genetic underpinnings (eg. the DRD2 protein is active when we are flummoxed with uncertainty which keeps us lingering in the NoGo state). Hey, our genome got us here … in one piece … it helped us stay alive … that’s not necessarily a bad thing.

thanks for the pic amadeus

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If you’re a coffee drinker, you may have noticed the new super-sized portions available at Starbucks.  On this note, it may be worth noting that caffeine is a potent psychoactive substance of which – too much – can turn your buzz into a full-blown panic disorder.  The Diagnostic and Statistical Manual for psychiatry outlines a number of caffeine-related conditions mostly involving anxieties that can arise when the natural alertness-promoting effects are pushed to extremes.  Some researchers have begun to explore the way the genome interacts with caffeine and it is likely that many genetic markers will surface to explain some of the individual differences in caffeine tolerance.

Here’s a great paper, “Association between ADORA2A and DRD2 Polymorphisms and Caffeine-Induced Anxiety” [doi: 10.1038/npp.2008.17] wherein polymorphisms in the adenosine A2A receptor (ADORA2A encodes the protein that caffeine binds to and antagonizes) – as well as the dopamine D2 receptor (DRD2 encodes a protein whose downstream signals are normally counteracted by A2A receptors) — show associations with anxiety after the consumption of 150mg of caffeine (about an average cup of coffee – much less than the super-size, super-rich cups that Starbucks sells).  The variants, rs5751876 (T-allele), rs2298383 (T-allele) and rs4822492 (G-allele) from the ADORA2A gene as well as rs1110976 (-/G genotype) from the DRD2 gene showed significant increases in anxiety in a test population of 102 otherwise-healthy light-moderate regular coffee drinkers.

My own 23andMe data only provides a drop of information suggesting I’m protected from the anxiety-promoting effects.  Nevertheless, I’ll avoid the super-sizes.
rs5751876 (T-allele)  C/C – less anxiety
rs2298383 (T-allele) – not covered
rs4822492 (G-allele) – not covered
rs1110976 (-/G genotype) – not covered

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gambling genes

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MFrankIf you’re interested in the neurobiology of learning and decision making, then you might be interested in this brief interview with Professor Michael Frank who runs the Laboratory of Neural Computation and Cognition at Brown University.

From his lab’s website: “Our research combines computational modeling and experimental work to understand the neural mechanisms underlying reinforcement learning, decision making and working memory. We develop biologically-based neural models that simulate systems-level interactions between multiple brain areas (primarily basal ganglia and frontal cortex and their modulation by dopamine). We test theoretical predictions of the models using various neuropsychological, pharmacological, genetic, and neuroimaging techniques.”

In this interview, Dr. Frank provides some overviews on how genetics fits into this research program and the genetic results in his recent research article “Prefrontal and striatal dopaminergic genes predict individual differences in exploration and exploitation”. Lastly, some lighthearted, informal thoughts on the wider implications and future uses of genetic information in decision making.

To my mind, there is no one else in the literature who so seamlessly and elegantly interrelates genetics with the modern tools of cognitive science and computational neurobiology.  His work really allows one to cast genetic variation in terms of its influence on neural computation – which is the ultimate way of understanding how the brain works.  It was a treat to host this interview!

Click here for the podcast and here, here, here for previous blog posts on Dr. Frank’s work.

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vix

In 1802, in a letter to then Secretary of the Treasury, Albert Gallatin, Thomas Jefferson warned that, “If the American people ever allow private banks to control the issue of their money, first by inflation and then by deflation, the banks and corporations that will grow up around them (around the banks), will deprive the people of their property until their children will wake up homeless on the continent their fathers conquered.” (source)  Although the US now does have a central government bank, Jefferson’s warning still chillingly echoes through our current crisis as we teeter on this very brink.

The reasons why the US financial system lies stricken now (not to mention many times before) are complex for sure, but for a neuroscience & genetics buff like myself, its fun to consider the underlying mechanisms of human biology and behavior within a macroeconomic framework.  What role for the brain and human nature? How does our understanding of human social and emotional behavior reconcile with the premise of so-called “rational” behavior of investors and consumers in a marketplace? Can we regulate and design a debacle-proof economic system that accounts for human social and emotional influences on otherwise rational behavior? Luckily, if you are interested in these questions, you need only to pick up a copy of “Animal Spirits: How Human Psychology Drives the Economy, and Why It Matters for Global Capitalism” by George Akerlof and Robert Shiller, who cover this very topic in great detail and provide a broad framework for neuropsychological research to inform macroeconomic policy.  A lofty and distant goal indeed, but perhaps the only way forward from such spectacular wreckage of the current system.

One such aspect of so-called “animal  spirits” could be, for example – fear – which has been blamed many times for financial panics and is covered in great measure by Akerlof and Shiller.  During the depths of the great depression, FDR famously tried to shake people loose from their animal spirits by suggesting “Only Thing We Have to Fear Is Fear Itself” (listen to the audio).   As another example, consider the chart at the top of the post – a 5yr trace of the VIX an index of volatility in the price of stock options over time.  In a bull or a bear market, when there are clear economic signals that stock prices should rise or fall, the VIX is rather low – since people feel relatively certain about the overall direction of the market.  Note however, what happened in the fall of 2008, when the heady days of the housing boom ended and our current crisis began – the VIX rockets toward 100% volatility – indicating rather dramatic swings in future earnings estimates and hence, tremendous uncertainty about the future direction of the market.  Indeed, for high flying investors (who may reside in tall buildings with windows that open) the VIX is sometimes referred to as the fear index.

What – in terms of brain mechanisms – might underlie such fear – which seems to stem from the uncertainty of whether things will get better or worse?  What do we know about how humans react to uncertainty and how humans process uncertainty?  What brain systems and mechanisms are at play here? One recent report that uses genetic variation as a tool to peer into such brain mechanisms suggests that dopamine signaling modulates different brain areas and our propensity to respond in conditions of low and high uncertainty.

In their article, “Prefrontal and striatal dopaminergic genes predict individual differences in exploration and exploitation“, [doi:10.1038/nn.2342] Michael Frank and colleagues examine individual differences in a so-called exploration/exploitation dilemma.  In their ‘‘temporal utility integration task’’, individuals could maximize their rewards by pressing “stop” on a rotating dial which can offer greater rewards when individuals press faster, or when individuals learn to withold and wait longer, and, in a third condition when rewards are uncertain.  The authors liken the paradigm to a common life dilemma when there are clear rewards to exploiting something you know well (like the restaurant around the corner), but, however, there may be more rewards obtained by exploring the unknown (restaurants on the other side of town).  In the case of the VIX and its massive rise on the eve of our nations financial calamity, investors were forced to switch from an exploitation strategy (buy housing-related securities!!!) to an exploration strategy (oh shit, what to do?!!).

The neurobiological model hypothesized by Frank and colleagues predicts that the striatum will be important for exploitation strategies and find supporting data in gene associations with the striatally-enriched DARPP-32 gene (a marker for dopamine D1-dependent signalling) and DRD2 for the propensity to respond faster and slower, respectively, in the exploitative conditions (rs907094 & rs1800496).  For the exploratory conditions, the team found an association with the COMT gene which is well-known to modulate neural function in the prefrontal cortex (rs4680). Thus, in my (admittedly loose) analogy, I can imagine investors relying on their striata during the housing boom years and then having to rely more on their prefrontal cortices suddenly in the fall of 2008 when it was no longer clear how to maximize investment rewards.  Egregious bailouts were not yet an option!

Click here and here to read more breakthrough neuroeconomics & genetic research from Michael Frank and colleagues.  Here and here for more on Shiller and Keynes.

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The selection and dosing of medication in psychiatry is far from scientific – even though a great deal of hard science goes into the preclinical design and clinical development. One reason, among many, has to do with the so-called ‘inverted-U-shaped’ relationship between the dose of a psychoactive compound and an individuals’ performance. Some folks show dramatic improvement with a given dose (their system may be functioning down at the low side of the inverted U mountain and hence, and added boost from medication may send their system up in performance), while others may actually get worse (those who are already at the peak of the inverted U mountaintop). How can a psychiatrist know where the patient is on this curve – will the medication boost raise or topple their patient’s functioning ? Some insight comes in the form of a genetic marker closely linked to the DRD2 gene, that as been shown to predict response to a dopaminergic drug.

Michael Cohen and colleagues, in their European Journal of Neuroscience paper (DOI: 10.1111/j.1460-9568.2007.05947.x) entitled, “Dopamine gene predicts the brain‘s response to dopaminergic drug” began with a polymorphism linked to the DRD2 gene wherein one allele (TaqA1+) is associated with fewer DRD2 receptors in the striatum (these folks should show improvement when given a DRD2 agonist) while folks with the alternate allele (TaqA1-) were predicted to show a falling off of their DRD2 function in response to additional DRD2 stimulation. The research team then asked participants to perform a cognitive task – a learning task where subjects use feedback to choose between a ‘win’ or ‘not win’ stimulus – that is well known to rely on proper functioning of DRD2-rich frontal and striatal brain regions.

Typically, DRD2 agonists impair reversal learning and, as expected, subjects in the low DRD2 level TaqA1+ genetic group actually got “more” impaired – or perseverated longer on rewarding stimuli and required more trials to switch on the go and figure out which stimulus was the “win” stimulus. Similarly, when differences in brain activity between baseline and positive “you win” feedback was measured, subjects in the drug treated, TaqA1+ genetic group showed an increase in activity in the putamen and the medial orbitofrontal cortex while subjects in the TaqA1- showed decreases in brain actiity in these regions. The authors suggest that the TaqA1+ group generally has a somewhat blunted response to positive feedback (sore winners) but that the medication enhanced the frontal-striatal reaction to positive feedback. Functional connectivity analyses showed that connectivity between the frontal cortex and striatum was worsened by the DRD2 agonist in the TaqA1+ genetic group and improved in the TaqA1- group.

Although the interpretations of these data are limited by the complexity of the systems, it seems clear that the TaqA1 genetic marker has provided a sort of index of baseline DRD2 function that can be useful in predicting an individual’s relative location on the theoretical inverted-U-shaped curve.

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