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.

Humans are spiritual creatures – there’s no denyin’.  How & why we got this way is one of THE BIG questions of all time.  Since our genome shapes the development of our brain and its interaction with our culture, its not a surprise to see that, from time to time, folks will look for and find genetic links to various forms of spiritual and religious behavior.  Here’s a recent paper from Kenneth Kendler’s research team at the Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine entitled, “A Developmental Twin Study of Church Attendance and Alcohol and Nicotine Consumption: A Model for Analyzing the Changing Impact of Genes and Environment” [link to abstract].  An analysis of more than 700 pairs of twins found that the correlation between alcohol and nicotine consumption and church attendance (more church predicts less smokin’ and drinkin’) is more than 50% influenced by genetic factors – in adults.  In children and teens, the genetic contribution to the correlation is much less and the strength of the correlation stems more from shared environmental factors (parents, school etc.).  Is there a gene for going to church? Nope.  Are there genes that shape a person’s inclination toward novelty or conscientiousness? More likely so.  Are they distributed across all races and cultures? Yep.  Lots to ponder next Sunday morning.

A recent GWAS study identified the 3′ region of the liver- (not brain) expressed PECR gene (rs7590720(G) and rs1344694(T)) on chromosome 2 as a risk factor for alcohol dependency.  These results, as reported by Treutlein et al., in “Genome-wide Association Study of Alcohol Dependence” were based on a population of 487 male inpatients and a follow-up re-test in a population of 1024 male inpatients and 996 control participants.

The authors also asked whether lab rats who – given the choice between water-based and ethanol-spiked beverages over the course of 1 year – showed differential gene expression in those rats that were alcohol preferrers vs. alcohol non-preferring rats.  Among a total of 542 genes that were found to be differentially expressed in the amygdala and caudate nucleus of alcohol vs. non-alcohol-preferring rat strains,  a mere 3 genes – that is the human orthologs of these 3 genes – did also show significant association with alcohol dependency in the human populations.  Here are the “rat genes” (ie. human homologs that show differential expression in rats and association with alcohol dependency in humans): rs1614972(C) in the alcohol dehydrogenase 1C (ADH1C) gene, rs13273672(C) in the GATA binding protein 4 (GATA4) gene, and rs11640875(A) in the cadherin 13 (CDH13) gene.

My 23andMe profile gives a mixed AG at rs7590720, and a mixed GT at rs1344694 while I show a mixed CT at rs1614972, CT at rs13273672 and AG at rs11640875.  Boooring! a middling heterozygote at all 5 alcohol prefer/dependency loci.   Were these the loci for chocolate prefer/dependency I would be a full risk-bearing homozygote.

Many thanks to Dr. Christina S. Barr from the National Institutes of Health/National Institute on Alcohol Abuse and Alcoholism-Laboratory of Clinical and Translational Studies, National Institutes of Health Animal Center for taking the time to comment on her team’s recent publication, “Functional CRH variation increases stress-induced alcohol consumption in primates” [doi:10.1073/pnas.0902863106] which was covered here.  On behalf of students and interested readers, I am so grateful to her for doing this!  Thank you Dr. Barr!

For readers who are unfamiliar with the extensive literature on this topic, can you give them some basic background context for the study?

“In rodents, increased CRH system functioning in parts of the brain that drive anxious responding (ie, amygdala) occurs following extended access to alcohol and causes animals to transition to the addicted state.  In rodent lines in which genetic factors drive increased CRH system functioning, those animals are essentially phenocopies of those in the post-dependent state.  We had a variant in the macaque that we expected would drive increased CRH expression in response to stress, and similar variants may exist in humans.  We, therefore, hypothesized that this type of genetic variation may interact with prior stress exposure to increase alcohol drinking.”

Can you tells us more about the experimental design strategy and methods?

“This was a study that relied on use of archived NIAAA datasets. The behavioral and endocrine data had been collected years ago, but we took a gene of interest, and determined whether there was variation. We then put a considerable amount of effort into assessing the functional effects of this variant, in order to have a better understanding of how it might relate to individual variation. We then genotyped archived DNA samples in the colony for this polymorphism.”

“I am actually a veterinarian in addition to being a neuroscientist- we have the “3 R’s”. Reduce, refine, and replace…..meaning that animal studies should involve reduced numbers, should be refined to minimize pain/distress and should be replaced with molecular studies if possible.  This is an example of how you can marry use of archived data and sophisticated molecular biology techniques/data analysis to come up with a testable hypothesis without the use of animal subjects. (of course, it means you need to have access to the datasets….;)”

How do the results relate to broader questions and your field at large?

“I became interested in this system because it is one that appears to be under intense selection.  In a wide variety of animal species, individuals or strains that are particularly stress-reactive may be more likely to survive and reproduce successfully in highly variable or stressful environments. Over the course of human evolution, however, selective pressures have shifted, as have the nature and chronicity of stress exposures.  In fact, in modern society, highly stress-reactive individuals, who are no less likely to be eaten by a predator (predation not being a major cause of mortality in modern humans), may instead be more likely to fall susceptible to various-stress related disorders, including chronic infections, diabetes, heart disease, accelerated brain aging, stress-related psychiatric disorders, and even drug and alcohol problems. Therefore, these genetic variants that are persistent in modern humans may make individuals more vulnerable to “modern problems.”

I do hope this helps. Let me know if it doesn’t, and I will try to better answer your questions.”

THANK YOU AGAIN VERY MUCH DR. BARR!!

It has been reported that cigarettes can impart some calm and clarity from racing thoughts and mental fog. Patients with schizophrenia, who often experience cognitive disorganization, are 2-4 times more likely than the general population to smoke, and also seem to prefer stronger brands of cigarettes. This is not surprising since nicotine can raise levels of dopamine indirectly via stimulation of alpha4/beta2 high affinity nicotinic acetyl choline receptors (nAChR) expressed widely in the parietal cortex of the human brain. In an open access article entitled, “Association of attentional network function with exon 5 variations of the CHRNA4 gene“, Georg Winterer and colleagues demostrate that individuals who vary in a synonymous G/A variant (rs1044396) in the CHRNA4 gene – an snp which has previously been associated with nicotine dependence – show differential brain activity in the parietal cortex. When asked to remain alert and respond to rare visual “oddball” stimuli (visual oddball detection task), subjects with the AA genotype showed robust brain activity in the parietal cortex while subjects with the GG genotype showed very little change in activity. This finding reveals where in the brain – circuits connecting to the parietal cortex – may be especially important in mediating self-medication and even in the management of side-effects in psychiatric pharmacotherapy. Although rs1044396 is not measured in my 23andMe profile, the neighboring rs3787138 showing tight LD is measured and reveals that I am a boring, middle of the road heterozygote. As such, I do admit that I could use some mind-clearing relief from time to time – but, the yellow teeth are not quite worth it.

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.

Uhl and colleagues present a genome-wide search for SNPs that distinguish smokers (nicotine dependence) – and perhaps more importantly – successful smoking quitters, in their recent article in the free and open-access journal BioMed Central. As pointed out in the article, this work is a step closer to personalized “efforts to match vulnerable individuals with the prevention and treatment strategies most likely to work for them.” A set of genetic variants that distinguish nicotine dependence from a control population with no personal history of smoking or substance abuse was identified and a novel set of variants that distinguish folks who’ve had success after using the patch and other self-help methods are exciting new tools that were produced by the study.

I much enjoyed Helen Mayberg’s October 13th podcast, “Paths to Recovery in Major Depression: Insights from Functional Neuroimaging” hosted by Science & the City, the webzine of the NY Academy of Science. One comment that stuck with me was her mention of ‘brain-based algorithms’ for the diagnosis and treatment of mental illness. Indeed, from her talk, there are many brain regions involved in the regulation of mood and that individuals who experience depression may show poor activity in any or all of these brain regions. Also, Dr. Mayberg shows that these various brain regions may be more or less responsive to drug- vs. talk-based therapies. This seems like a major step forward in personalized medicine in psychiatry and perhaps might be augmented by other biomarkers. Presently, scanning is somewhat cumbersome relative to current drug-trial-and-error regimens, but the benefits of recovery far, far outweigh the costs of a lifetime of chronic illness.