Archive for the ‘Frontal cortex’ Category

One day, each of us may have the dubious pleasure of browsing our genomes.  What will we find?   Risk for this?  Risk for that?  Protection for this? and that?  Fast twitching muscles & wet ear wax?  Certainly.  Some of the factors will give us pause, worry and many restless nights.  Upon these genetic variants we will likely wonder, “why me? and, indeed, “why my parents (and their parents) and so on?”

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!

Enhanced by Zemanta

Read Full Post »

An historic find has occurred in the quest (gold-rush, if you will) to link genome variation with brain structure-function variation.  This is the publication of the very first genome-wide (GWAS) analysis of individual voxels (voxels are akin to pixels in a photograph, but are rather 3D cubes of brain-image-space about 1mm on each side) of brain structure – Voxelwise genome-wide association study (vGWAS) [doi: 10.1016/j.neuroimage.2010.02.032] by Jason Stein and colleagues under the leadership of Paul M. Thompson, a  leader in the area of neuroimaging and genetics – well-known for his work on brain structure in twin and psychiatric patient populations.

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!

Reblog this post [with Zemanta]

Read Full Post »

Recreated :File:Neuron-no labels2.png in Inksc...
Image via Wikipedia

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.

Reblog this post [with Zemanta]

Read Full Post »

One of the complexities in beginning to understand how genetic variation relates to cognitive function and behavior is that – unfortunately – there is no gene for “personality”, “anxiety”, “memory” or any other type of “this” or “that” trait.  Most genes are expressed rather broadly across the entire brain’s cortical layers and subcortical systems.  So, just as there is no single brain region for “personality”, “anxiety”, “memory” or any other type of “this” or “that” trait, there can be no such gene.  In order for us to begin to understand how to interpret our genetic make-up, we must learn how to interpret genetic variation via its effects on cells and synapses – that go on to function in circuits and networks.  Easier said than done?  Yes, but perhaps not so intractable.

Here’s an example.  One of the most well studied circuits/networks/systems in the field of cognitive science are so-called basal-ganglia-thalamcortical loops.  These loops have been implicated in a great many forms of cognitive function involving the regulation of everything from movement, emotion and memory to reasoning ability.  Not surprisingly, neuroimaging studies on cognitive function almost always find activations in this circuitry.  In many cases, the data from neuroimaging and other methodologies suggests that one portion of this circuitry – the frontal cortex – plays a role in the representation of such aspects as task rules, relationships between task variables and associations between possible choices and outcomes.  This would be sort of like the “thinking” part of our mental life where we ruminate on all the possible choices we have and the ins and outs of what each choice has to offer.  Have you ever gone into a Burger King and – even though you’ve known for 20 years what’s on the menu – you freeze up and become lost in thought just as its your turn to place your order?  Your frontal cortex is at work!

The other aspect of this circuitry is the subcortical basla ganglia, which seems to play the downstream role of processing all that ruminating activity going on in the frontal cortex and filtering it down into a single action.  This is a simple fact of life – that we can be thinking about dozens of things at a time, but we can only DO 1 thing at a time.  Alas, we must choose something at Burger King and place our order.  Indeed, one of the hallmarks of mental illness seems to be that this circuitry functions poorly – which may be why individuals have difficulty in keeping their thoughts and actions straight – the thinking clearly and acting clearly aspect of healthy mental life.  Certainly, in neurological disorders such as Parkinson’s Disease and Huntington’s Disease, where this circuitry is damaged, the ability to think and move one’s body in a coordinated fashion is disrupted.

Thus, there are at least 2 main components to a complex system/circuits/networks that are involved in many aspects of learning and decision making in everyday life.  Therefore, if we wanted to understand how a gene – that is expressed in both portions of this circuitry – inflenced our mental life, we would have to interpret its function in relation to each specific portion of the circuitry.  In otherwords, the gene might effect the prefrontal (thinking) circuitry in one way and the basla-ganglia (action-selection) circuitry in a different way.  Since we’re all familiar with the experience of walking in to a Burger King and seeing folks perplexed and frozen as they stare at the menu, perhaps its not too difficult to imagine that a gene might differentially influence the ruminating process (hmm, what shall I have today?) and the action selection (I’ll take the #3 combo) aspect of this eveyday occurrance (for me, usually 2 times per week).

Nice idea you say, but does the idea flow from solid science?  Well, check out the recent paper from Cindy M. de Frias and colleagues “Influence of COMT Gene Polymorphism on fMRI-assessed Sustained and Transient Activity during a Working Memory Task.” [PMID: 19642882].  In this paper, the authors probed the function of a single genetic variant (rs4680 is the Methionine/Valine variant of the dopamine metabolizing COMT gene) on cognitive functions that preferentially rely on the prefronal cortex as well as mental operations that rely heavily on the basal-ganglia.  As an added bonus, the team also probed the function of the hippocampus – yet a different set of circuits/networks that are important for healthy mental function.  OK, so here is 1 gene who is functioning  within 3 separable (yet connected) neural networks!

The team focused on a well-studied Methionine/Valine variant of the dopamine metabolizing COMT gene which is broadly expessed across the pre-frontal (thinking) part of the circuitry and the basal-ganglia part of the circuitry (action-selection) as well as the hippocampus.  The team performed a neuroimaging study wherein participants (11 Met/Met and 11 Val/Val) subjects had to view a series of words presented one-at-a-time and respond if they recalled that a word was a match to the word presented 2-trials beforehand  (a so-called “n-back task“).  In this task, each of the 3 networks/circuits (frontal cortex, basal-ganglia and hippocampus) are doing somewhat different computations – and have different needs for dopamine (hence COMT may be doing different things in each network).  In the prefrontal cortex, according to a theory proposed by Robert Bilder and colleagues [doi:10.1038/sj.npp.1300542] the need is for long temporal windows of sustained neuronal firing – known as tonic firing (neuronal correlate with trying to “keep in mind” all the different words that you are seeing).  The authors predicted that under conditions of tonic activity in the frontal cortex, dopamine release promotes extended tonic firing and that Met/Met individuals should produce enhanced tonic activity.  Indeed, when the authors looked at their data and asked, “where in the brain do we see COMT gene associations with extended firing? they found such associations in the frontal cortex (frontal gyrus and cingulate cortex)!

Down below, in the subcortical networks, a differerent type of cognitive operation is taking place.  Here the cells/circuits are involved in the action selection (press a button) of whether the word is a match and in the working memory updating of each new word.  Instead of prolonged, sustained “tonic” neuronal firing, the cells rely on fast, transient “phasic” bursts of activity.  Here, the modulatory role of dopamine is expected to be different and the Bilder et al. theory predicts that COMT Val/Val individuals would be more efficient at modulating the fast, transient form of cell firing required here.   Similarly, when the research team explored their genotype and brain activity data and asked, “where in the brain do we see COMT gene associations with transient firing? they found such associations in the right hippocampus.

Thus, what can someone who carries the Met/Met genotype at rs4680 say to their fellow Val/Val lunch-mate next time they visit a Burger King?  “I have the gene for obesity? or impulsivity? or “this” or “that”?  Perhaps not.  The gene influences different parts of each person’s neural networks in different ways.  The Met/Met having the advantage in pondering (perhaps more prone to annoyingly gaze at the menu forever) whist the Val/Val has the advantage in the action selecting (perhaps ordering promptly but not getting the best burger and fries combo).

Reblog this post [with Zemanta]

Read Full Post »

Gravestone of Samuel Coleridge-Taylor,Wallington
Image by sludgegulper via Flickr

Few events are as hard to understand as the loss of a loved one to suicide – a fatal confluence of factors that are oft scrutinized – but whose analysis can provide little comfort to family and friends.  To me, one frightening and vexing aspect of what is known about the biological roots of depression, anxiety, impulsivity and other mental traits and states associated with suicide, is the way in which early life (even prenatal) experience can influence events in later life.  As covered in this blog here and here, there appear to be very early interactions between emotional experience in early life and the methylation of specific points in the genome.  Such methylation – often referred to as epigenetic marks – can regulate the expression of genes that are important for synaptic plasticity and cognitive development.

The recent paper, “Alternative Splicing, Methylation State, and Expression Profile of Tropomyosin-Related Kinase B in the Frontal Cortex of Suicide Completers” is a recent example of a link between epigenetic marks and suicide.  The team of Ernst et al., examined gene expression profiles from the frontal cortex and cerebellum of 28 males lost to suicide and 11 control, ethnically-matched control participants.  Using a subject-by-subject comparison method described as “extreme value analysis” the team identified 2 Affymetrix probes: 221794_at and 221796_at – that are specific to NTRK2 (TRKB) gene – that showed significantly lower expression in several areas of the frontal cortex.  The team also found that these probes were specific to exon 16 – which is expressed only in the TRKB.T1 isoform that is expressed only in astrocytes.

Further analysis showed that there were no genetic differences in the promoter region of this gene that would explain the expression differences, but, however, that there were 2 methylation sites (epigenetic differences) whose methylation status correlated with expression levels (P=0.01 and 0.004).  As a control, the DNA-methylation at these sites was not correlated with TRKB.T1 expression when DNA and RNA was taken from the cerebellum (a control since the cerebellum is not thought to be directly involved in the regulation of mood).

In the case of TRKB.T1 expression, the team reports that more methylation at these 2 sites in the promoter region is associated with less TRKB.T1 expression in the frontal cortex.  Where and when are these marks laid down?  Are they reversible?  How can we know or suspect what is happening to our epigenome (you can’t measure this by spitting into a cup as with current genome sequencing methods)? To me, the team has identified an important clue from which such follow-up questions can be addressed.  Now that they have a biomarker, they can help us begin to better understand our complex and often difficult emotional lives within a broader biological context.

Reblog this post [with Zemanta]

Read Full Post »

DCDC2 (gene)
Image via Wikipedia

A recent analysis of brain structure in healthy individuals who carry a common 2,445-bp deletion in intron 2 of the doublecortin domain containing 2 (DCDC2) gene found that heterozygotes for the deletion showed higher grey matter volumes for several brain areas known to be involved in the processing of written and spoken language (superior, medial and inferior temporal cortex, fusiform, hippocampal / parahippocampal, inferior occipito-parietal, inferior and middle frontal gyri, especially in the left hemisphere) [doi:10.1007/s11682-007-9012-1].  The DCDC2 gene sits within a well known locus frequently found to be associated with developmental dyslexia, and associations of reading disability with DCDC2 have been confirmed in population-based studies.  dcdc2rnai Further work on DCDC2 (open access) shows that the DNA that is deleted in the 2,445-bp deletion in intron 2 carries a number of repeating sequences to which developmental transcription factors bind and that inhibition of DCDC2 results in altered neuronal migration (the right-hand panel shows altered radial migration when DCDC2 is inhibited).  Perhaps the greater grey matter volumes are related to this type of neuronal migration finding?  Will be interesting to follow this story further!

Reblog this post [with Zemanta]

Read Full Post »

[picapp src=”e/7/8/1/Children_Attend_Classes_9572.jpg?adImageId=4955179&imageId=1529412″ width=”380″ height=”253″ /]

This year, my 5 year-old son and I have passed many afternoons sitting on the living room rug learning to read.  While he ever so gradually learns to decode words, eg. “C-A-T”  sound by sound, letter by letter – I can’t help but marvel at the human brain and wonder what is going on inside.  In case you have forgotten, learning to read is hard – damn hard.  The act of linking sounds with letters and grouping letters into words and then words into meanings requires a lot of effort from the child  (and the parent to keep discomfort-averse child in one place). Recently, I asked him if he could spell words in pairs such as “MOB & MOD”, “CAD & CAB”, “REB & RED” etc., and, as he slowly sounded out each sound/letter, he informed me that “they are the same daddy“.  Hence, I realized that he was having trouble – not with the sound to letter correspondence, or the grouping of the letters, or the meaning, or handwriting – but rather – just hearing and discriminating the -B vs. -D sounds at the end of the word pairs.  Wow, OK, this was a much more basic aspect of literacy – just being able to hear the sounds clearly.  So this is the case, apparently, for many bright and enthusiastic children, who experience difficulty in learning to read.  Without the basic perceptual tools to hear “ba” as different from “da” or “pa” or “ta” – the typical schoolday is for naught.

With this in mind, the recent article, “Genetic determinants of target and novelty-related event-related potentials in the auditory oddball response” [doi:10.1016/j.neuroimage.2009.02.045] caught my eye.  The research team of Jingyu Liu and colleagues asked healthy volunteers just to listen to a soundtrack of meaningless beeps, tones, whistles etc.  The participants typically would hear a long stretch of the same sound eg. “beep, beep, beep, beep” with a rare oddball “boop” interspersed at irregular intervals.  The subjects were instructed to simply press a button each time they heard an oddball stimulus.  Easy, right?  Click here to listen to an example of an “auditory oddball paradigm” (though not one from the Liu et al., paper).  Did you hear the oddball?  What was your brain doing? and what genes might contribute to the development of this perceptual ability?

The researchers sought to answer this question by screening 41 volunteers at 384 single nucleotide polymorphisms (SNPs) in 222 genes selected for their metabolic function in the brain.  The team used electroencephalogram recordings of brain activity to measure differences in activity for “boop” vs. “beep” type stimuli – specifically, at certain times before and after stimulus onset – described by the so-called N1, N2b, P3a, P3b component peaks in the event-related potentials waveforms.  800px-Erp1Genotype data (coded as 1,0,-1 for aa, aA, AA) and EEG data were plugged into the team’s home-grown parallel independent components analysis (ICA) pipeline (generously provided freely here) and several positives were then evaluated for their relationships in biochemical signal transduction pathways (using the Ingenuity Pathway Analysis toolkit.  A very novel and sophisticated analytical method for certain!

The results showed that certain waveforms, localized to certain areas of the scalp were significantly associated with the perception of various oddball “boop”-like stimuli.  For example, the early and late P3 ERP components, located over the frontal midline and parieto-occipital areas, respectively, were associated with the perception of oddball stimuli.  Genetic analysis showed that several catecholaminergic SNPs such as rs1800545 and rs521674 (ADRA2A), rs6578993 and rs3842726 (TH) were associated with both the early and late P3 ERP component as well as other aspects of oddball detection.

Both of these genes are important in the synaptic function of noradrenergic and dopaminergic synapses. Tyrosine hydroxylase, in particular, is a rate-limiting enzyme in catecholamine synthesis.  Thus, the team has identified some very specific molecular processes that contribute to individual differences in perceptual ability.  In addition to the several other genes they identified, the team has provided a fantastic new method to begin to crack open the synaptic complexities of attention and learning.  See, I told you learning to read was hard!

Reblog this post [with Zemanta]

Read Full Post »

Older Posts »