You mean these types of executives?  No … well, sort of, maybe.  Some people can control their thoughts and actions better than others.

Individuals vary widely in their abilities to control their own thoughts and actions. Some people seem ruled by impulses, while others manage successfully to regulate their behaviors. From the perspective of cognitive psychology, such variation reflects individual differences in executive functions, a collection of correlated but separable control processes that regulate lower-level cognitive processes to shape complex performance.

Results indicated that executive functions are correlated because they are influenced by a highly heritable (99%) common factor that goes beyond general intelligence or perceptual speed, and they are separable because of additional genetic influences unique to particular executive functions. This combination of general and specific genetic influences places executive functions among the most heritable psychological traits.

Why the heck! if a genetic variant is associated with poor health, is it floating around in human populations?

A complex question, made moreso by the fact that our modern office-bound, get-married when you’re 30, live to 90+ lifestyle is so dramatically different than our ancestors. In the area of mental health, there are perhaps a few such variants – notably the deaded APOE E4 allele – that are worth losing sleep over, perhaps though, after you have lived beyond 40 or 50 years of age.

Another variant that might be worth consideration – from cradle-to-grave – is the so-called 5HTTLPR a short stretch of concatenated DNA repeats that sits in the promoter region of the 5-HTT gene and – depending on the number of repeats – can regulate the transcription of 5HTT mRNA.  Much has been written about the unfortunateness of this “short-allele” structural variant in humans – mainly that when the region is “short”, containing 14 repeats, that folks tend to be more anxious and at-risk for anxiety disorders.  Folks with the “long” (16 repeat variant) tend to be less anxious and even show a pattern of brain activity wherein the activity of the contemplative frontal cortex is uncorrelated from the emotionally active amygdala.  Thus, 5HTTLPR “long” carriers are less likely to be influenced, distracted or have their cognitive processes disrupted by activity in emotional centers of the brain.

Pity me, a 5HTTLPR “short”/”short”  who greatly envies the calm, cool-headed, even-tempered “long”/”long” folks and their uncorrelated PFC-amygdala activity.  Where did their genetic good fortune come from?

Klaus Peter Lesch and colleagues say the repeat-containing LPR DNA may be the remnants of an ancient viral insertion or transposing DNA element insertion that occurred some 40 million years ago.  In their article entitled, “The 5-HT transporter gene-linked polymorphic region (5-HTTLPR) in evolutionary perspective:  alternative biallelic variation in rhesus monkeys“, they demonstrate that the LPR sequences are not found in primates outside our simian cousins (baboons, macaques, chimps, gorillas, orangutans).  More recently, the ancestral “short” allele at the 5HTTLPR acquired some additional variation leading to the rise of the “long” allele which can be found in chimps, gorillas, orangutans and ourselves.

So I missed out on inheriting “CCCCCCTGCACCCCCCAGCATCCCCCCTGCACCCCCCAGCAT” (2 extra repeats of the ancient viral insertion) which could have altered the entire emotional landscape of my life.  Darn, to think too, that it has been floating around in the primate gene pool all these years and I missed out on it.  Drat!

In an earlier post on Williams Syndrome, we delved into the notion that sometimes a genetic variant can lead to enhanced function – such as certain social behaviors in the case of WS.  A mechanism that is thought to underlie this phenomenon has to do with the way in which information processing in the brain is widely distributed and that sometimes a gene variant can impact one processing pathway, while leaving another pathway intact, or even upregulated.  In the case of Williams Syndrome a relatively intact ventral stream (“what”) processing but disrupted dorsal stream (“where”) processing leads to weaker projections to the frontal cortex and amygdala which may facilitate gregarious and prosocial (a lack of fear and inhibition) behavior.  Other developmental disabilities may differentially disrupt these 2 visual information processing pathways.  For instance, developmental dyspraxia contrasts with WS as it differentially disrupts the ventral stream processing pathway.

A recent paper by Woodcock and colleagues in their article, “Dorsal and ventral stream mediated visual processing in genetic subtypes of Prader–Willi syndrome” [doi:10.1016/j.neuropsychologia.2008.09.019] ask how another developmental disability – Prader-Willi syndrome – might differentially influence the development of these information processing pathways.  PWS arises from the lack of expression (via deletion or uniparental disomy) of a cluster of paternally expressed genes in the 15q11-13 region (normally the gene on the maternally inherited chromosome is silent, or imprinted – related post here).  By comparing PWS children to matched controls, the team reports evidence showing that PWS children who carry the deletion are slightly more impaired in a task that depends on the dorsal “where” pathway whilst some sparing or relative strength in the ventral “what” pathway.

In an effort to discover genes that contribute to individual differences in brain structure, the authors took on the task of statistically analyzing the some 31,622 voxels (per brain) obtained from high-resolution structural brain scans; with 448,293 Illumina SNP genotypes (per person) with minor allele frequencies greater than 0.1 (common variants); in 740 unrelated healthy caucasian adults.  When performed on a voxel-by-voxel basis, this amounts to some 14 billion statistical tests.

Yikes!  A statistical nightmare with plenty of room for false positive results, not to mention the recent disillusionment with the common-variant GWAS approach?  Certainly.  The authors describe these pitfalls and other scenarios wherein false data is likely to arise and most of the paper addresses the pros and cons of different statistical analysis strategies – some which are prohibitive in their computational demands.  Undaunted, the authors describe several approaches for establishing appropriate thresholds and then utilize a ‘winner take all’ analysis strategy wherein a single ‘most-associated winning snp’ is identified for each voxel, which when clustered together in hot spots (at P = 2 x 10e-10), can point to specific brain areas of interest.

Using this analytical approach, the authors report that 8,212 snps were identified as ‘winning, most-associated’ snps across the 31,622 voxels.  They note that there was not as much symmetry with respect to winning snps in the left hemispere and corresponding areas in the right hemisphere, as one might have expected.  The 2 most significant snps across the entire brain and genome were rs2132683 and rs713155 which were associated with white matter near the left posterior lateral ventricle.  Other notable findings were rs2429582 in the synaptic (and possible autism risk factor) CADPS2 gene which was associated with temporal lobe structure and rs9990343 which sits in an intergenic region but is associated with frontal lobe structure.  These and several other notable snps are reported and brain maps are provided that show where in the brain each snp is associated.

As in most genome-wide studies, one can imagine that the authors were initially bewildered by their unexpected findings.  None of the ‘usual suspects’ such as neurotransmitter receptors, transcription factors, etc. etc. that dominate the psychiatric genetics literature.  Bewildered, perhaps, but maybe thats part of the fun and excitement of discovery!  Very exciting stuff to come I’ll bet as this new era unfolds!

Obviously, Wolfe was a gifted artist, despite whatever psychiatric diagnosis was suggested at the time.  Nevertheless, clinical psychiatrists might be quick to point out that such work reflects the presence of an underlying thought disorder (loss of abstraction ability, tangentiality, loose associations, derailment, thought blocking, overinclusive thinking, etc., etc.) – despite the undeniable aesthetic beauty in the work.  As an ardent fan of such art,  it made me wonder just how “well ordered” my own thoughts might be.  Given to being rather forgetful and distractable, I suspect my thinking process is just sufficiently well ordered to perform the routine tasks of day-to-day living, but perhaps not a whole lot more so.  Is this bad or good?  Who knows.

However, Krug et al., in their recent paper, “The effect of Neuregulin 1 on neural correlates of episodic memory encoding and retrieval” [doi:10.1016/j.neuroimage.2009.12.062] do note that the brains of unaffected relatives of persons with mental illness show subtle differences in various patterns of activation.  It seems that when individuals are using their brains to encode information for memory storage, unaffected relatives show greater activation in areas of the frontal cortex compared to unrelated subjects.  This so-called encoding process during episodic memory is very important for a healthy memory system and its dysfunction is correlated with thought disorders and other aspects of cognitive dysfunction.  Krug et al., proceed to explore this encoding process further and ask if a well-known schizophrenia risk variant (rs35753505 C vs. T) in the neuregulin-1 gene might underlie this phenomenon.  To do this, they asked 34 TT, 32 TC and 28 CC individuals to perform a memory (of faces) game whilst laying in an MRI scanner.

The team reports that there were indeed differences in brain activity during both the encoding (storage) and retrieval (recall) portions of the task – that were both correlated with genotype – and also in which the CC risk genotype was correlated with more (hyper-) activation.  Some of the brain areas that were hyperactivated during encoding and associated with CC genotype were the left middle frontal gyrus (BA 9), the bilateral fusiform gyrus and the left middle occipital gyrus (BA 19).  The left middle occipital gyrus showed gene associated-hyperactivation during recall.  So it seems, that healthy individuals can carry risk for mental illness and that their brains may actually function slightly differently.

As an ardent fan of Art Brut, I confess I hoped I would carry the CC genotype, but alas, my 23andme profile shows a boring TT genotype.  No wonder my artwork sucks.  More on NRG1 here.

** 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!

The A-to-T SNP rs7794745 in the CNTNAP2 gene was found to be associated with increased risk of autism (see Arking et al., 2008).  Specifically, the TT genotype, found in about 15% of individuals, increases these folks’ risk by about 1.2-1.7-fold.  Sure enough, when I checked my 23andMe profile, I found that I’m one of these TT risk-bearing individuals.  Interesting, although not alarming since me and my kids are beyond the age where one typically worries about autism.  Still, one can wonder if such a risk factor might have exerted some influence on the development of my brain?

The recent paper by Tan et al., “Normal variation in fronto-occipital circuitry and cerebellar structure with an autism-associated polymorphism of CNTNAP2” [doi:10.1016/j.neuroimage.2010.02.018 ] suggests there may be subtle, but still profound influences of the TT genotype on brain development in healthy individuals.  According to the authors, “homozygotes for the risk allele showed significant reductions in grey and white matter volume and fractional anisotropy in several regions that have already been implicated in ASD, including the cerebellum, fusiform gyrus, occipital and frontal cortices. Male homozygotes for the risk alleles showed greater reductions in grey matter in the right frontal pole and in FA in the right rostral fronto-occipital fasciculus compared to their female counterparts who showed greater reductions in FA of the anterior thalamic radiation.”

The FA (fractional anisotropy – a measurement of white-matter or myelination) results are consistent with a role of CNTNAP2 in the establishment of synaptic contacts and other cell-cell contacts especially at Nodes of Ranvier – which are critical for proper function of white-matter tracts that support rapid, long-range neural transmission.  Indeed, more severe mutations in CNTNAP2  have been associated with cortical dysplasia and focal epilepsy (Strauss et al., 2006).

Subtle changes perhaps influencing long-range information flow in my brain – wow!

More on CNTNAP2 … its evolutionary history and role in language development.

For a great many reasons, research on mental illness is focused on the frontal cortex.  Its just a small part of the brain, and certainly, many things can go wrong in other places during brain/cognitive development, but, it remains a robust finding, that when the frontal cortex is not working well, individuals have difficulties in regulating thoughts and emotions.  Life is difficult enough to manage, let alone without a well functioning frontal cortex.  So its no surprise that many laboratories look very closely at how this region develops prenatally and during childhood.

One of the more powerful genetic methods is the analysis of gene expression via microarrays (here is a link to a tutorial on this technology).  When this technology is coupled with extremely careful histological analysis and dissection of cortical circuits in the frontal cortex, it begins to become possible to begin to link changes in gene expression with the physiological properties of specific cells and local circuits in the frontal cortex. The reason this is an exciting pursuit is because the mammalian neocortex is organized in a type of layered fashion wherein 6 major layers have different types of connectivity and functionality.  The developmental origins of this functional specificity are thought to lie in a process known as radial migration (here is a video of a neuron as it migrates radially and finds its place in the cortical hierarchy).  As cells are queued out of the ventricular zone, and begin their migration to the cortical surface, they are exposed to all sorts of growth factors and morphogens that help them differentiate and form the proper connectivities.  Thus, the genes that regulate this process are of keen interest to understanding normal and abnormal cognitive development.

Here’s an amazing example of this – 2 papers entitled, “Infragranular gene expression disturbances in the prefrontal cortex in schizophrenia: Signature of altered neural development?” [doi:10.1016/j.nbd.2009.12.013] and “Molecular markers distinguishing supragranular and infragranular layers in the human prefrontal cortex [doi:10.1111/j.1460-9568.2007.05396.x] both by Dominique Arion and colleagues.  In both papers, the authors ask, “what genes are differentially expressed in different layers of the cortex?”.  This is a powerful line of inquiry since the different layers of cortex are functionally different in terms of their connectivity.  For example, layers II-III (the so-called supragranular layers) are known to connect mainly to other cortical neurons – which is different functionally than layers V-VI (the so-called infragranular layers) that connect mainly to the striatum (layer V) and thalamus (layer VI).  Thus, if there are genes whose expression is unique to a layer, then one has a clue as to how that gene might contribute to normal/abnormal information processing.

The authors hail from a laboratory that is well-known for work over many years on fine-scaled histological analysis of the frontal cortex at the University of Pittsburgh and used a method called, laser capture microdissection, where post-mortem sections of human frontal cortex (area 46) were cut to separate the infragraular layer from the supragranular layer.  The mRNA from these tissue sections was then used for DNA microarray hybridization.  Various controls, replicate startegies and in-situ tissue hybridizations were then employed to validate the initial microarray results.

In first paper, the where the authors compare infra vs. supragranular layers, they report that 40 genes were more highly expressed in the supragranular layers (HOP, CUTL2 and MPPE1 were among the most enriched) and 29 genes were highly expressed in the infragranular layers (ZNF312, CHN2, HS3ST2 were among the most enriched).  Other differentially expressed genes included several that have previously been implicated in cortical layer formation such as RLN, TLX-NR2E1, SEMA3E, PCP4, SERPINE2, NR2F2/ARP1, PCDH8, WIF1, JAG1, MBP.  Amazing!! A handful of genes that seem to label subpopulations of projection neurons in the frontal cortex.  Polymorphic markers for these genes would surely be powerful tools for imaging-genetic studies on cognitive development.

In the second paper, the authors compare infra vs. supragranular gene expression in post-mortem brains from patients with schizophrenia and healthy matched controls. Using the same methods, the team reports both supra- and infragranular gene expression changes in schizophrenia (400 & 1200 differences respectively) – more than 70% of the differences appearing to be reductions in gene expression in schizophrenia. Interestingly, the team reports that the genes that were differentially expressed in the infragranular layers provided sufficient information to discriminate between cases and controls, whilst the gene expression differences in the supragranular layers did not.  More to the point, the team finds that 51 genes that were differentially expressed in infra- vs. supragranular expression were also differentially expressed in cases vs. controls  (many of these are also found to be associated in population genetic association studies of schiz vs. control as well!).  Thus, the team has identified layer (function) -specific genes that are associated with schizophrenia.  These genes, the ones enriched in the infragranular layers especially, seem to be at the crux of a poorly functioning frontal cortex.

The authors point to 3 such genes (SEMA3E, SEMA6D, SEMA3C) who happen to members of the same gene family – the semaphorin gene family.  This gene family is very important for the neuronal guidance (during radial migration), morphology, pruning and other processes where cell shape and position are regulated.  The authors propose that the semaphorins might act as “integrators” of various forms of wiring during development and in adulthood.  More broadly, the authors provide a framework to understand how the development of connectivity on the frontal cortex is regulated by genetic factors – indeed, many suspected genetic risk factors play a role in the developmental pathways the authors have focused on.

***PODCAST ACCOMPANIES THIS POST***

In his undergraduate writings while a student at Harvard in the early 1900′s E. E. Cummings quipped that, “Japanese poetry is different from Western poetry in the same way as silence is different from a voice”.  Isabelle Alfandary explores this theme in Cummings’ poetry in her essay, “Voice and Silence in E. E. Cummings’ Poetry“,  giving some context to how the poet explored the meanings and consequences of voice and silence.  Take for example, his poem “silence”

silence

.is
a
looking

bird:the

turn
ing;edge, of
life

(inquiry before snow

e.e. cummings

Lately, it seems that the brain imaging community is similarly beginning to explore the meanings and consequences of the brain when it speaks (activations whilst performing certain tasks) and when it rests quietly.  As Cummings beautifully intuits the profoundness of silence and rest,  I suppose he might have been intrigued by just how very much the human brain is doing when we are not speaking, reading, or engaged in a task. Indeed, a community of brain imagers seem to be finding that the brain at rest has quite a lot to say – moreso in people who carry certain forms of genetic variation (related posts here & here).

A paper by Perrson and colleagues “Altered deactivation in individuals with genetic risk for Alzheimer’s disease” [doi:10.1016/j.neuropsychologia.2008.01.026] asked individuals to do something rather ordinary – to pay attention to words – and later to then respond to the meaning of these words (a semantic categorization task). This simple endeavor, which, in many ways uses the very same thought processes as used when reading poetry, turns out to activate regions of the temporal lobe such as the hippocampus and other connected structures such as the posterior cingulate cortex.  These brain regions are known to lose function over the course of life in some individuals and underlie their age-related difficulties in remembering names and recalling words, etc.  Indeed, some have described Alzheimer’s disease as a tragic descent into a world of silence.

In their recordings of brain activity of subjects (60 healthy participants aged 49-79), the team noticed something extraordinary.  They found that there were differences not in how much the brain activates during the task – but rather in how much the brain de-activates – when participants simply stare into a blank screen at a small point of visual fixation.  The team reports that individuals who carry at least one copy of epsilon-4 alleles of the APOE gene showed less de-activation of their their brain (in at least 6 regions of the so-called default mode network) compared to individuals who do not carry genetic risk for Alzheimer’s disease.  Thus the ability of the brain to rest – or transition in and out of the so-called default mode network – seems impaired in individuals who carry higher genetic risk.

So, I shall embrace the poetic wisdom of E. E. Cummings and focus on the gaps, empty spaces, the vastness around me, the silences, and learn to bring my brain to rest.  And in so doing, perhaps avoid an elderly descent into silence.

***PODCAST ACCOMPANIES THIS POST***