Archive for the ‘Dopamine’ Category

Cheap? Yes. Fake? Not at all.  It’s another genetic study on the placebo effect and it highlights the fact that our brains are not static input-out machines that were built from scratch using a genetic blueprint.  Rather, what we expect and believe matters … a lot.

How does it work?  Nobody knows for sure, but dopamine has been implicated in synaptic mechanisms that are used to register the fulfillment or violation of expectations.  For example, if you believe that a certain something will happen … and something better happens, your brain produces a burst of dopamine.  If something worse happens, then you get a drop in dopamine.  Your expectations and beliefs influence your dopamine levels.

Apparently, some of us metabolize dopamine faster vs. slower which may be related to a weaker vs. stronger placebo response.  For example, my rs4680 GG fast dopamine metabolizing genotype says, the “medicine in my mind” is not very strong.  But, on the other hand, I do watch A LOT of Grey’s Anatomy.

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Wobble base pair guanine uracil (GU)

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Hands shake and wobble as the decades pass … moreso in some.

A recently evolved “T” allele (rs12720208) in the  3′ untranslated region (3′ UTR) of the FGF20 gene has been implicated in the risk of Parkinson’s Disease … namely by creating a wobbly G:U base-pair between microRNA-433 (miR-433) and the FGF20 transcript.  Since the normal function of microRNA-433 is to repress translation of proteins (such as FGF20), it is suspected that the PD risk “T” allele carriers make relatively more FGF20 … which, in turn … leads to the production of higher levels of alpha-synuclein (the main component of Lewy body fibrils, a pathological marker of diseases such as PD).  This newly evolved T-allele has also been associated with brain structural differences in healthy individuals.

My hands will shake and wobble as the decades pass … but not because I carry the G:U wobble pairing between miR-433:FGF20.  My 23andMe profile shows that I carry 2 C alleles and will produce the thermodynamically favorable G:C pairing.  Something to keep in mind as I lose my mind in the decades to come.

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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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** PODCAST accompanies this post**

I have a little boy who loves to run and jump and scream and shout – a lot.  And by this, I mean running – at full speed and smashing his head into my gut,  jumping – off the couch onto my head,  screaming – spontaneous curses and R-rated body parts and bodily functions.  I hope you get the idea.  Is this normal? or (as I oft imagine) will I soon be sitting across the desk from a school psychologist pitching me the merits of an ADHD diagnosis and medication?

Of course, when it comes to behavior, there is not a distinct line one can cross from normal to abnormal.  Human behavior is complex, multi-dimensional and greatly interpreted through the lens of culture.  Our present culture is highly saturated by mass-marketing, making it easy to distort a person’s sense of “what’s normal” and create demand for consumer products that folks don’t really need (eg. psychiatric diagnoses? medications?).   Anyhow, its tough to know what’s normal.  This is an important issue to consider for those (mass-marketing hucksters?) who might be inclined to promote genetic data as “hard evidence” for illness, disorder or abnormality of some sort.

With this in mind, I really enjoyed a recent paper by Stollstorff et al., “Neural response to working memory load varies by dopamine transporter genotype in children” [doi:10.1016/j.neuroimage.2009.12.104] who asked how the brains of healthy children functioned, even though they carry a genotype that has been widely associated with the risk of ADHD.  Healthy children who carry genetic risk for ADHD. Hmm, might this be my boy?

The researchers looked at a 9- vs. 10-repeat VNTR polymorphism in the 3′-UTR of the dopamine transporter gene (DAT1).  This gene – which encodes the very protein that is targeted by so many ADHD medications – influences the re-uptake of dopamine from the synaptic cleft.  In the case of 10/10 genotypes, it seems that DAT1 is more highly expressed, thus leading to more re-uptake and hence less dopamine in the synaptic cleft.  Generally, dopamine is needed to enhance the signal/noise of neurotransmission, so – at the end of the day – the 10/10 genotype is considered less optimal than the 9/9-repeat genotype.  As noted by the researchers, the ADHD literature shows that the 10-repeat allele, not the 9-repeat, is most often associated with ADHD.

The research team asked these healthy children (typically developing children between 7 and 12 years of age) to perform a so-called N-back task which requires that children remember words that are presented to them one-at-a-time.  Each time a new word is presented, the children had to decide whether that word was the same as the previous word (1-back) or the previous, previous word (2-back).  Its a maddening task and places an extreme demand on neural circuits involved in active maintenance of information (frontal cortex) as well as inhibition of irrelevant information that occurs during updating (basal ganglia circuits).

As the DAT1 protein is widely expressed in the basal ganglia, the research team asked where in the brain was variation in the DAT1 (9- vs. 10-repeat) associated with neural activity?  and where was there a further difference between 1-back and 2-back?  Indeed, the team finds that brain activity in many regions of the basal ganglia (caudate, putamen, substantia nigra & subthalamic nucleus) were associated with genetic variation in DAT1.  Neat!  the gene may be exerting an influence on brain function (and behavior) in healthy children, even though they do not carry a diagnosis.  Certainly, genes are not destiny, even though they do influence brain and behavior.

What was cooler to me though, is the way the investigators examined the role of genetic variation in the 1-back (easy or low load condition) vs. 2-back (harder, high-load condition) tasks.  Their data shows that there was less of an effect of genotype on brain activation in the easy tasks.  Rather, only when the task was hard, did it become clear that the basal ganglia in the 10/10 carriers was lacking the necessary brain activation needed to perform the more difficult task.  Thus, the investigators reveal that the genetic risk may not be immediately apparent under conditions where heavy “loads” or demands are not placed on the brain.  Cognitive load matters when interpreting genetic data!

This result made me think that genes in the brain might be a lot like genes in muscles.  Individual differences in muscle strength are not associated with genotype when kids are lifting feathers.  Only when kids are actually training and using their muscles, might one start to see that some genetically advantaged kids have muscles that strengthen faster than others.  Does this mean there is a “weak muscle gene” – yes, perhaps.  But with the proper training regimen, children carrying such a “weak muscle gene” would be able to gain plenty of strength.

I guess its off to the mental and physical gyms for me and my son.

** PODCAST accompanies this post** also, here’s a link to the Vaidya lab!

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pointer to: Computational Models of Basal Ganglia Function where Kenji Doya provides computational explanations for neuromodulators and their role in reinforcement learning. In his words, “Dopamine encodes the temporal difference error — the reward learning signal. Acetylcholine affects learning rate through memory updates of actions and rewards. Noradrenaline controls width or randomness of exploration. Serotonin is implicated in “temporal discounting,” evaluating if a given action is worth the expected reward.”

This type of amazing research provides a pathway to better understand how genes contribute to how the brain “works” as a 3-dimensional biochemical computational machine.

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labyrinthine circuit board lines
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Amidst a steady flow of upbeat research news in the behavioral-genetics literature, there are many inconvenient, uncomfortable, party-pooping sentiments that are more often left unspoken.  I mean, its a big jump – from gene to behavior – and just too easy to spoil the mood by reminding your colleagues that, “well, everything is connected to everything” or “that gene association holds only for that particular task“.  Such may have been the case often times in the past decade when the so-called imaging-genetics literature emerged to parse out a role for genetic variation in the structure and functional activation of the brain using various neuroimaging methods.  Sure, the 5HTT-LPR was associated with amygdala activation during a face matching task, but what about other tasks (and imaging modalities) and other brain regions that express this gene.  How could anyone (let alone NIMH) make sense out of all of those – not to mention the hundreds of other candidate genes poised for imaging-genetic research?

With this in mind, it is a pleasure to meet the spoiler-of-spoilers! Here is a research article that examines a few candidate genetic polymorphisms and compares their findings across multiple imaging modalities.  In his article, “Neural Connectivity as an Intermediate Phenotype: Brain Networks Under Genetic Control” [doi: 10.1002/hbm.20639] Andreas Meyer-Lindenberg examines the DARPP32, 5HTT and MAOA genes and asks whether their associations with aspects of brain structure/function are in any way consistent across different neuroimaging modalities.  Amazingly, the answer seems to be, yes.

For example, he finds that the DARPP32 associations are consistently associated with the striatum and prefrontal-striatal connectivity – even as the data were collected using voxel-based morphometry, fMRI in separate tasks, and an analysis of functional connectivity.  Similarly, both the 5HTT and MAOA gene promoter repeats also showed consistent findings within a medial prefrontal and amygdala circuit across these various modalities.

This type of finding – if it holds up to the spoilers & party poopers – could radically simplify the understanding of how genes influence cognitive function and behavior.  As suggested by Meyer-Lindenberg, “features of connectivity often better account for behavioral effects of genetic variation than regional parameters of activation or structure.”  He suggests that dynamic causal modeling of resting state brain function may be a powerful approach to understand the role of a gene in a rather global, brain-wide sort of way.  I hope so and will be following this cross-cutting “connectivity” approach in much more detail!

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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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Mother and Child
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The roles of nature and nurture in child development have never been easy to disentangle.  Parents, in particular, seem to know this all too well, when it comes to their own children.  For example, when one of my children throws a tantrum, my wife can be mercilessly quick to point out that “those are your genes at work “.  I for one, can’t help but admire Mother Nature’s sense of justice (or is it humor?) as I’m forced to grapple with an unreconcilable 5-year old.  What can I do?  How can I get some type of optimal gene-by-environment (parenting style) going here?  Afterall, they are MY genes (expressed in said unreconcilable 5-year old) right?  Can I break out of the infinitely recurrent loop of me (my genes) trying to positively interact with my child (also my genes).  What’s a stubborn parent of a stubborn child to do?

In thinking about this, it was great to read a recent article by Lee and colleagues entitled, “Association of maternal dopamine transporter genotype with negative parenting: evidence for gene x environment interaction with child disruptive behavior” [doi: 10.1038/mp.2008.102].  In this article, the team examined how children (4 to 7 years old)  interacted with their mothers during a session where they were induced to cooperate in tasks involving free play with specific toys, tasks involving organizing items in a room and several pencil and paper tasks.  A set of observations were made (through 1-way glass) on aspects of parenting (negative feedback or contact, positive feedback and encouragement, and, total number of maternal commands).

In principle, the complexities of whose genes & behavior is influencing whose in such a situation are vast.  The authors point out that such interactions can be divided into passive GxE wherein children with certain genes (lets say genes for stubborness) may have inherited those genes from parents who exhibit a stubborn (negative) parenting style – hence leading to correlations in child genotype and parenting style.  Alternatively, such correlations can occur when a child (perhaps a stubborn child) evokes negative parenting response from a parent who did not (as my wife claims) transmit said stubborness genes – an example of an evocative GxE interaction.  In this study, the team examined the mother’s genotype at a 40-bp repeat polymorphism in the 3’UTR of the dopamine transporter (DAT) gene.  This is an apt candidate gene, since animal models of DAT loss-of-function show disrupted maternal behavior.

As an initial step, the team evaluated whether maternal genotype was correlated with maternal parenting style.  They found that the 10-repeat allele of the DAT gene was associated with more of a negative style of parenting.  However, the association of the 10-repeat allele of DAT was rather stronger in mothers whose children were categorized as disruptive than among mothers whose children were categorized as compliant – an example of an interaction of the mother’s genotype with her child’s disruptive behavior (which itself may be due to genes inherited by her – and so on – and so on).

Hard to pin down the genetic blame somewhere here.  Maddening actually.  Maddening enough to make dealing with my unreconcilable 5-year old seem a simple and welcoming task.

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U.S. Treasury Secre...

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Amidst the current economic panic, I’m feeling more shocked than usual when listening to the flip-flopping, falsehoods, fabrications, backstepping, about-facing and unabashed spin-doctoring spewing forth from the news media. If watched long enough, one may even develop empathy for Henry Paulson who carries the weight of the global economy on his shoulders. Nevertheless, what do we know about making mistakes ? Not necessarily global financial catastrophies, but little everyday mistakes. Why do some of us learn from our mistakes ? What’s going on in the brain ? Enter Michael Frank, Christopher D’Lauro and Tim Curran, in their paper entitled, “Cross-task individual differences in error processing: Neural, electrophysiological and genetic components” [Cognitive, Affective, & Behavioral Neuroscience (2007), 7 (4), 297-308]. Their paper provides some amazing insight into the workings of human error-processing.

It has been known for some time that when you make a mistakke – oops! – mistake, that there are various types of electrical current that emanate from the frontal midline (cingulate cortex) of your brain.  The so-called error related negativity (ERN) occurs more strongly when you are more focused on being correct and also seems to be more strong in people with certain personality traits (apparently not news commentators or politicians) while the error positivity (Pe) occurs more strongly when you become consciously aware that you made an error (perhaps not functioning in news commentators or politicians). Perhaps the ERN and Pe are basic neural mechanisms that facilitate an organisms adaptive ability to stop and say, “hey, wait a minute, maybe I should try something new.” The Frank et al., paper describes a relation between learning and dopamine levels, and suggests that when dopamine levels dip – as happens when our expectations are violated (“oh shit!, I bought stock in Lehman Brothers) – that this may facilitate the type of neural activity that causes us to stop and rethink things. To test whether dopamine might play a role in error processing, the team examined a common variant (rs4680) in the catechol-o-methyl transferase gene, a gene where A-carriers make a COMT enzyme that is slower to breakdown dopamine (a bulky methionine residue near the active site) than G-allele-carriers. Subjects performed a learning task where correct responses could be learned by either favoring positive feedback or avoiding negative feedback as compared to neutral stimuli. The team suspected that regardless of COMT genotype, however, there would be no COMT association with learning strategy, since COMT influences dopaminergic activity in the frontal cortex, and not in the striatum, which is the region that such reinforcement learning seems to be stored.

Interestingly, the team found that the error positivity (Pe) was higher in participants who were of the A/A genotype, but no difference in genetic groups for the error related negativity (ERN). This suggests that A/A subjects deploy more attentional focus when they realize they have made an error. Lucky folks ! My 23andMe profile shows a GG at this site, so it seems that when I make errors, I may have a normal ERN, but the subcortical dopamine that dips as a result does not (on average) result in much greater attentional focus. Oh well, I guess its the newsmedia pool for me.

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2nd third of 19th centuryImage via Wikipedia

You see a masterpiece while I see splatters of paint on a canvas. Why – in neural terms – do we see the same painting and feel so subjectively different ?

Understanding the neural crosstalk between visual inputs (the raw neural activity generated in the retina) and our complex internal states (needs, desires, fears etc.) of an organism is a research problem that is long on philosophy but rather difficult to address experimentally. Professors P. Read Montague and Brooks King-Casas provide a conceptual overview to how such neural crosstalk might be collected, analyzed and understood in terms of basic computational processes that underlie human decision making. In their article, “Efficient statistics, common currencies and the problem of reward-harvesting“, [doi: 10.1016/j.tics.2007.10.002] they provide an historical review of some of the major conceptual frameworks and give examples of how basic research in the area of reinforcement learning (dopamine serves as a reinforcement signal since it is released in the ventral striatum when you get more than you were expecting) might serve as a core cellular mechanism underlying the inter-linking of incoming sensory information with internal states.  Dr. Montague’s book on decision making is also a fun experience & great introduction to the burgeoning area of neuroeconomics.

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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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Holiday time is full of all things delicious and fattening. Should I have a little chocolate now, or wait till later and have a bigger dessert ? Of course, this is not a real forced choice (in my case, the answer too often seems – alas – “I’ll have both!”), but there are many times in life when we are forced to decide between ‘a little now’ or ‘more later’. Sometimes, its clear that the extra $20 in your pocket now would be better utilized later on, after a few years of compound interest. Other times, its not so clear. Consider the recent ruling by the Equal Employment Opportunity Commission, which allows employers to drop retirees’ health coverage once they turn 65 and become eligible for Medicare. Do I save my resources now to provide for my geezerdom healthcare spending, or do I enjoy (spend) my resources now while I’m young and able ? How do I make these decisions ? How does my life experience and genome interact to influence the brain systems that support these computations ? Boettiger and company provide some insight to these questions in their paper, “Immediate Reward Bias in Humans: Fronto-Parietal Networks and a Role for the Catechol-O-Methyltransferase 158Val/Val Genotype(DOI). The authors utilize an assay that measures a subject’s preference for rewards now or later and use functional brain imaging to seek out brain regions where activity is correlated to preferences for immediate rewards. Dopamine rich brain regions such as the posterior parietal cortex, dorsal prefrontal cortex and rostral parahippocampal gyrus showed (+) correlations while the lateral orbitofrontal cortex showed a (-) correlation. Variation in the dopaminergic enzyme COMT at the rs165688 SNP also showed a correlation with preferences for immediate reward as well as with brain activation. The authors’ results suggest that improving one’s ability to weigh long-term outcomes is a likely therapeutic avenue for helping impulsive folks (like me) optimize our resource allocation. I have not yet had my genome deCODEd or Google-ed, but strongly suspect I am a valine/valine homozygote.

Indeed it seems I am a GG (Valine/Valine) at this site according to 23andMe !

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Fred Sanford
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Mouse models of complex neurological illness are a powerful means to dissect molecular pathways and treatment paradigms. Current mouse models for the tremors and movement difficulties seen in Parkinson disease include genes such as parkin, alpha-synuclein, LRRK2, PINK1 and DJ-1. These models however, do not show the motor control problems and spontaneous degeneration of dopamine neurons as seen in PD in human patients. A new mouse model as reported by Kittappa and colleagues, unlike previous models, does, however, show amazing verisimilitude to PD. In their paper, “The foxa2 Gene Controls the Birth and Spontaneous Degeneration of Dopamine Neurons in Old Age(DOI) the authors find that mice with only a single copy of the foxa2 gene acquire motor deficits and a late-onset degeneration of dopamine neurons. The age-related spontaneous cell death preferentially affects dopamine producing neurons in the substantia nigra that are affected in PD. The link between genetic risk and environmental exposure to oxidative toxins, a known risk factor in PD, is remarkably straightforward as foxa2 appears to be a regulator of superoxide dismutase, a potent protective scavenger of damage-inducing free radicals. More amazingly still, the authors demonstrate that foxa2 plays a key role in the birth of dopamine neurons – thus opening up new therapeutic possibilities of simultaneously producing new neurons and blocking apoptotic death of old ones. This fox brings new hope for treatment !

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Deep-fried onion rings arranged in a line on a...Image via Wikipedia To go out tonight or stay home? Hillary or Barack? Curly fries or onion rings? How do I make these important choices and why will others decide differently? Although there are many reasons for not stressing-out and over-thinking one’s decisions (except for really important choices like curly fry vs. onion ring), it turns out that variation in your genome, in particular, 3 dopaminergic genes (DARPP-32, DRD2 and COMT: rs907094, rs1800496, rs4680) are influencing your tendency to ‘go for it’ or not to go for it. Frank and colleagues, in their paper, “Genetic triple dissociation reveals multiple roles for dopamine in reinforcement learning“, give an in-depth treatment of the neurobiology underlying decision making and reinforcement learning. After carefully reviewing the basic biology of dopaminergic synapses and selecting 3 candidate genetic variants, they find that each is associated with an independent aspect of decision making in a learning paradigm. The paper is an excellent example of how genetic variation can be linked to specific neural processes. Now bring on the curly fries – no wait – the onion rings.

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