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Posts Tagged ‘inhibition’

Tuning in to the gene-environment interaction every weeknight at 8pm on channel 6

Posted in GABRA2, tagged , , on May 23, 2011| Leave a Comment »

Teenagers are (in)famous for their hysterics.  They are biologically mature, but society and their parents don’t allow them the freedom they desire.  Toss in a steady diet of advertisement-laced TV … often for alcohol (an average of 301/year in 2007 – up from 216 in 2001), and you’ve got an enduring (not endearing) epic struggle.

Now toss the human genome … into the drowsy parents-watching-teenagers-watching beer ads on TV (until drowsy parents fall asleep and the real fun begins).  Will it lead to a night of harmless fun? or a lifetime struggle full of rehab and alcohol addiction?

The research article, “Role of GABRA2 in Trajectories of Externalizing Behavior Across Development and Evidence of Moderation by Parental Monitoring” suggests that some of the genetic risk for alcoholism is foreshadowed in, or somewhat overlapping with, the externalizing behaviors of teenagers.  Furthermore, the role of parental oversight can interact with, and reduce this genetic risk.

Here we present analyses aimed at delineating the pathways of risk associated with GABRA2 OMIM 137140. This gene was originally associated with adult alcohol dependence in the Collaborative Study on the Genetics of Alcoholism (COGA) project.13 The association with adult alcohol dependence has been replicated in several independent samples.14–17 Subsequent analyses of GABRA2 in the COGA sample also yielded evidence of association with other forms of drug dependence,18,19 antisocial personality disorder,20 and childhood conduct disorder,19 leading to the hypothesis that GABRA2 may be involved in the predisposition to alcohol dependence through general externalizing pathways.21

Importantly, parental monitoring has been shown to moderate the importance of genetic effects on substance use across adolescence.29,30 In a population-based sample of twins aged 14 and 17 years, as parental monitoring increased, genetic effects on substance use significantly decreased.30

Using data on externalizing behavior as reported at 9 time points between ages 12 and 22 years, we used person-oriented latent class analysis to identify 2 classes of trajectories of externalizing behavior; most of the sample (83%) showed a decrease in externalizing behavior from early adolescence to adulthood, while 17% of the sample showed consistent elevated levels of externalizing behavior that persisted into adulthood. The individuals showing this pattern of persistently high externalizing behavior were significantly more likely to carry the variant of GABRA2 that was originally associated with increased risk for adult alcohol dependence in the COGA sample13 (though we note that there is inconsistency as to the risk allele across studies).39

What might be the mechanism by which GABRA2 affects risk for externalizing behavior? All of the outcomes that have been associated with GABRA2 (adult alcohol dependence, drug dependence, adult antisocial behavior, childhood conduct problems, adolescent externalizing behavior) are characterized by aspects of impulsivity.

Importantly, we find evidence that the association between GABRA2 and trajectories of externalizing behavior is moderated by parental monitoring; the effect of the genotype on externalizing behavior is stronger under conditions of lower parental monitoring and weaker under conditions of higher parental monitoring.

“Parental monitoring?” … I dunno what that exactly involves … I’m usually pretty busy just looking for the remote control.  Here is a genomic beer ad.

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Genes in the brain are like genes in muscles

Posted in Basal Ganglia, Caudate nucleus, DAT, Dopamine, Putamen, Substantia nigra, Subthalamic nucleus, tagged , , , , , , , , , , , , , , , , on March 5, 2010| 1 Comment »

wotd044
Image by theloushe via Flickr

** 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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GPR6 teaches B.F. Skinner that actions have consequences

Posted in G-protein, GPR6, Striatum, tagged , , , , , , , , on November 24, 2007| Leave a Comment »

B.F.Image via Wikipedia

I’m not sure what Skinner would have thought, but its clear that, nowadays, mechanisms of behavior can be understood in terms of dynamic changes in neural systems and, furthermore, that individual differences in these neural dynamics are heavily regulated by genetic variation. Consider the recent paper by Lobo et al., “Genetic control of instrumental conditioning by striatopallidal neuron–specific S1P receptor Gpr6” (DOI). The authors use molecular genetics to seek out and find key genetic regulators of a specific and fundamental form of learning – operant or instrumental conditioning, pioneered by B.F. Skinner – wherein an individual performs an act and, afterwards, receives (+ or -) reinforcing feedback. This type of learning is distinct from classical conditioning where, for example, Pavlov’s dogs heard a bell before dinner and eventually began to salivate at the sound of the bell. In classical conditioning, the cue comes before the target, whereas in operant conditioning, the feedback comes after the target. Interestingly, the brain uses very different neural systems to process these different temporal contingencies and Lobo and company dive straight into the specific neural circuits – striatopallidal medium spiny neurons – to identify genes that are differentially expressed in these cells as compared to other neurons and, in particular, striatonigral medium spiny neurons. The GPR6 gene was found to be the 6th most differentially expressed gene in these cells and resultant knockout mice, when placed in an operant chamber, were much faster than control animals in learning the bar press association with a sugar pellet reward. The expression of GPR6 in striatopallidal cells predicts that they should have a normal function in inhibiting or slowing down such associations, so it makes sense that the GPR6 knockout animals are faster to learn these associations. This is one of the first genes whose function seems specifcially linked to a core cognitive process – Skinner might have been impressed after reading the paper.

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