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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!

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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!

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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.

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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).

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Gravestone of Samuel Coleridge-Taylor,Wallington
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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.

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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!

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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!

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Kali
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Joseph LeDoux‘s book, “Synaptic Self: How Our Brains Become Who We Are” opens with his recounting of an incidental glance at a t-shirt, “I don’t know, so maybe I’m not” (a play on Descartes’ cogito ergo sum) that prompted him to explore how our brain encodes memory and how that leads to our sense of self.  More vividly, Elizabeth Wurtzel, in “Prozac Nation” recounts, “Nothing in my life ever seemed to fade away or take its rightful place among the pantheon of experiences that constituted my eighteen years. It was all still with me, the storage space in my brain crammed with vivid memories, packed and piled like photographs and old dresses in my grandmother’s bureau. I wasn’t just the madwoman in the attic — I was the attic itself. The past was all over me, all under me, all inside me.” Both authors, like many others, have shared their personal reflections on the fact that – to put it far less eloquently than LeDoux and Wurtzl – “we” or “you” are encoded in your memories, which are “saved” in the form of synaptic connections that strengthen and weaken and morph through age and experience.  Furthermore, such synaptic connections and the myriad biochemical machinery that constitute them, are forever modulated by mood, motivation and your pharmacological concoction du jour.

Well, given that my “self” or “who I think of as myself” or ” who I’m aware of at the moment writing this blog post” … you get the neuro-philosophical dilemma here … hangs ever so tenuously on the biochemical function of a bunch of tiny little proteins that make up my synaptic connections – perhaps I should get to know these little buggers a bit better.

OK, how about a gene known as kalirin – which is named after the multiple-handed Hindu goddess Kali whose name, coincidentally, means “force of time (kala)” and is today considered the goddess of time and change (whoa, very fitting for a memory gene huh?).  The imaginative biochemists who dubbed kalirin recognized that the protein was multi-handed and able to interact with lots of other proteins.  In biochemical terms, kalirin is known as a “guanine nucleotide exchange factor” – basically, just a helper protein who helps to activate someone known as a Rho GTPase (by helping to exchange the spent GDP for a new, energy-laden GTP) who can then use the GTP to induce changes in neuronal shape through effects on the actin cytoskeleton.  Thus, kalirin, by performing its GDP-GTP exchange function, helps the actin cytoskeleton to grow.  The video below, shows how the actin cytoskeleton grows and contracts – very dynamically – in dendrites that carry synaptic spines – whose connectivity is the very essence of “self”.  Indeed, there is a lot of continuing action at the level of the synapse and its connection to other synapses, and kalirin is just one of many proteins that work in this dynamic, ever-changing biochemical reaction that makes up our synaptic connections.

In their paper”Kalirin regulates cortical spine morphogenesis and disease-related behavioral phenotypes” [doi: 10.1073/pnas.0904636106] Michael Cahill and colleagues put this biochemical model of kalirin to the test, by examining a mouse whose version of kalirin has been inactivated.  Although the mice born with this inactivated form are able to live, eat and breed, they do have significantly less dense patterns of dendritic spines in layer V of the frontal cortex (not in the hippocampus however, even though kalirin is expressed there).  Amazingly, the deficits in spine density could be rescued by subsequent over-expression of kalirinHmm, perhaps a kalirin medication in the future? Further behavior analyses revealed deficits in memory that are dependent on the frontal cortex (working memory) but not hippocampus (reference memory) which seems consistent with the synaptic spine density findings.

Lastly, the authors point out that human kalirin gene expression and variation has been associated with several neuro-psychiatric conditions such as schizophrenia, ADHD and Alzheimer’s Disease.   All of these disorders are particularly cruel in the way they can deprive a person of their own self-perception, self-identity and dignity.  It seems that kalirin is a goddess I plan on getting to know better.  I hope she treats “me” well in the years to come.

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Pyramidal cell -  A human neocortical pyramida...
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Among the various (and few) significant results of recent landmark whole-genome analyses (involving more than 54,000 participants) on schizophrenia (covered here and here), there was really just one consistent result – linkage to the 6p21-22 region containing the immunological MHC loci.  While there has been some despair among professional gene hunters, one man’s exasperation can sometimes be a source of great interest and opportunity for others – who – for many years – have suspected that early immunological infection was a key risk factor in the development of the disorder.

Such is the case in the recent paper, “Prenatal immune challenge induces developmental changes in the morphology of pyramidal neurons of the prefrontal cortex and hippocampus in rats” by Baharnoori et al., [doi: 10.1016/j.schres.2008.10.003].  In this paper, the authors point out that Emil Kraepelin, who first described the disorder we now call schizophrenia, had suggested that childhood inflammation of the head might be an important risk factor.  Thus, the immunopathological hypothesis has been around since day 0 – a long time coming I suppose.

In their research article, Baharnoori and colleagues have taken this hypothesis and asked, in a straightforward way, what the consequences of an immunological challenge on the developing brain might look like.  To evaluate this question, the team used a Sprague-Dawley rat model and injected pregnant females (intraperitoneally on embryonic day 16) with a substance known as lipopolysaccharide (LPS) which is known to mimic an infection and initiate an immune response (in a manner that would normally depend on the MHC loci found on 6p21-22). Once the injections were made, the team was then able to assess the consequences to various aspects of brain and behavior.

In this paper, the team focused their analysis on the development of the frontal cortex and the hippocampus – 2 regions that are known to function poorly in schizophrenia.  They used a very, very focused probe of development – namely the overall shape, branching structure and spine formations on pyramidal cells in these regions – via a method known as Golgi-Cox staining.  The team presents a series of fantastically detailed images of single pyramidal cells (taken from postnatal day 10, 35 and 60) from animals who’s mothers were immunologically challenged and those who were unexposed to LPS.

Briefly, the team finds that the prenatal exposure to LPS had the effect of reducing the number of dendritic spines (these are the aspects of a neuron that are used to make synaptic connections with other neurons) in the developing offspring.  Other aspects of neuronal shape were also affected in the treated animals – basically amounting to a less branchy, less spiny – less connectable – neuron.  If that’s not a basis for a cognitive disorder than what else is?  Indeed, the authors point out that such spines are targets – in early development – for interneurons that are essential for long-range gamma oscillations that help distant brain regions function together in a coherent manner (something that notably does not happen in schizophrenia).

Thus, there is many a reason (54,000 strong) to want to better understand the neuro-immuno-genetic-developmental mechanisms that can alter neuronal structure.  Exciting progress in the face of recent genetic setbacks!
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Few genes have been studies as intensely as apolipoprotein E (APOE).  In particular, one of its variants, the epsilon-4 allele has been especially scrutinized because it is correlated with an earlier onset (about 10 years earlier than average) of Alzheimer’s Disease.  Among the many roles of APOE – its just a tiny cholesterol binding protein – are those as participant in synaptic plasticity, early neural development, damage-response and other processes – all of which share the need for the synthesis and movement of neuronal membranes (see the fluid mosaic model) and their component parts – such as cholesterol.   Hence, whenever neural membranes are being synthesized (plasticity & development) or damaged (overstimulation and other sources of oxidative damage) the tiny APOE is there to help with its membrane stabilizing cholesterol molecule in hand. Over the course of a lifetime, routine damage to neuronal membranes adds up (particularly in the hippocampus where constant storage-recall memory functions place enormous demands on synaptic plasticity systems), and individuals (such as epsilon-4 carriers) may simply show more wear-and-tear because their version of APOE is not as optimal as the other forms (epsilon-2 and -3).

apoeWith this etiological model in mind, perhaps you would like to take better care of you cell membranes (much like your car mechanic implores to change your car’s spark plugs and oil to keep the engine clean on the inside).  Moreover, perhaps you would like to do-so especially if you knew that your APOE system was less optimal than average.  Indeed, results from the recent REVEAL study suggest that folks who are in their 50’s are not unduly distressed to make this genetic inquiry and find out their genotypic status at this APOE polymorphism – even though those who discovered that they were epsion-4 carriers reported more negative feelings, understandably.  Still, with a number of education and intervention strategies available, an optimistic outlook can prevail.

Furthermore, there are ever newer diagnostic strategies that can improve the rather weak predictive power of the genetic test.  For example, cognitive assessments that measure hippocampal-dependent aspects of memory or visual orienting have been shown to be valid predictors of subsequent dementia – even moreso in populations that carry the APOE epsilon-4 allele.  Other forms of neuroimaging that directly measure the structure and function of the hippocampus also have tremendous sensitivity (here for a broad review of imaging-genetics of AD) and can, in principle, provide a more predictive view into one’s distant future.

On the very cutting edge of this imaging-genetic crystal ball technology, lies a recent paper entitled, “Distinct patterns of brain activity in young carriers of the APOE-e4 allele” by Fillippini and colleagues [doi: 10.1073/pnas.0811879106].  Here, the research team asks whether individuals in their late 20’s show structural/functional brain differences that are related to APOE genotype.  They employ various forms of imaging analysis such as a comparison of brain activity when subjects were performing a novel vs. familiar memory task and also an analysis of so-called resting state networks – which reflect a form of temporal coherence (brain areas that oscillate in-sync with each other when subjects are lying still and doing nothing in the scanner).  For the analysis of the memory task, the team found that APOEe4 carriers showed more activation in the hippocampus as well as other brain regions like the anterior midbrain and cerebellum.  When the team analysed a particular resting state network – the default mode network – they found differences in the medial temporal lobe (containing head of the hippocampus and amygdala) as well as the medial prefronal cortex.  According to the paper, none of these differences could be explained by differences in the structure or resting perfusion of the young-adult brains in the study.

Wow, these results seem to suggest that decades before any mild cognitive impairments are observable, there are already subtle differences in the physiology of the APOEe4 brain – all of which could be detected using the data obtained in 6 minutes of rest. 6 minutes of rest and spit in a cup – what does the future hold?

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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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facial expressions
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One of the difficulties in understanding mental illness is that so many aspects of mental life can go awry – and its a challenge to understand what abnormalities are directly linked to causes and what abnormalities might be consequences or later ripples in a chain reaction of neural breakdown.  Ideally, one would prefer to treat the fundamental cause, rather than only offer palliative measures for symptoms that arise from tertiary neural inefficiencies. In their research article entitled, “Evidence That Altered Amygdala Activity in Schizophrenia Is Related to Clinical State and Not Genetic Risk“, [doi: 10.1176/appi.ajp.2008.08020261] (audio link) Rasetti and colleagues explore this issue.

Specifically, they focus on the function of the amygdala and its role in responding to, and processing, social and emotional information.  In schizophrenia, it has been found that this brain region can be somewhat unresponsive when viewing faces displaying fearful expressions – and so, the authors ask whether the response of the amygdala to fearful faces is, itself, an aspect of the disorder that can be linked to underlying genetic risk (a type of core, fundamental cause).

To do this, the research team assembled 3 groups of participants: 34 patients, 29 of their unaffected siblings and 20 demographically and ethnically matched control subjects.  The rationale was that if a trait – such as amygdala response – was similar for the patient/sibling comparison and dissimilar for the patient/control comparison, then one can conclude that the similarity is underlain by the similarity or shared genetic background of the patients and their siblings.  When the research team colected brain activity data in response to a facial expression matching task performed in an MRI scanner, they found that the patient/sibling comparison was not-similar, but rather the siblings were more similar to healthy controls instead of their siblings.  This suggests that the trait (amygdala response) is not likely to be directly related to core genetic risk factor(s) of schizophrenia, but rather related to apsects of the disorder that are consequences, or the state, of having the disorder.

A follow-up study using a different trait (prefrontal cortex activity during a working memory task) showed that this trait was similar for the patient/sibling contrast, but dissimilar for the patient/control contrast – suggesting that prefrontal cortex function IS somewhat linked to core genetic risk.  Congratulations to the authors on this very informative study!

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Neuregulin 1Image via Wikipedia Nowadays, as many folks peer into the vast tangled thicket of their own genetic code, they, as I, assuredly wonder what it all means and how best to ascertain their health risks. One core theme that emerges from repeated forays into one’s own data is that many of us carry a scads of genetic risk for illness, but somehow, find ourselves living rather normal, healthy lives. How can this be ? A recent example of this entails a C/T snp (c) located in the 5′ flanking region of the neuregulin 1 gene which has been repeatedly associated with schizophrenia. Axel Krug and colleagues recently reported in their paper, “Genetic variation in the schizophrenia-risk gene neuregulin1 correlates with differences in frontal brain activation in a working memory task in healthy individuals” that T/C variation at this snp is associated with activation of the frontal cortex in healthy individuals. Participants were asked to keep track of a series of events and respond to a particular event that happened “2 events ago” . These so-called n-back tasks are not easy for healthy folks, and demand a lot of mental focus – a neural process that depends heavily on circuits in the frontal cortex. Generally speaking, as the task becomes harder, more activity in the frontal cortex is needed to keep up. In this case, individuals with the TT genotype seemed to perform the task while using somewhat less activity in the frontal cortex, rather than the risk-bearing CC carriers. As someone who has tried and failed to succeed at these tasks many times before, I was sure I would be a CC, but the 23andMe data show me to be a non-risk carrying TT. Hmmm … maybe my frontal cortex is just underactive.

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PhotoImage via Wikipedia Like most parents, I enjoy watching my children develop and marvel at the many similarities they bear to myself and my wife. The reshuffling of physical and behavioral features is always a topic of discussion and is the definitive icebreaker during uncomfortable silences with the inlaws. In some cases, the children are blessed with the better traits, but in other cases, there’s no option but to cringe when, “Look – wow, he really has your nose – hmmm”, is muttered. Most interesting, is the unfolding of patterns of behavior that unfold slowly with age. Differences in temperament and personality can instill great pride in parents but also can be a grating source of friction. One of my F1’s has recently taken to sessions of shrill, spine rattling, screaming which I hope will pass soon.

Why ? Many parents ask. “Have WE been raising him/her to do this ? – surely that’s what the neighbors must think”. “Is it something in the family ? I heard Aunt Marie was a bit of a screamer as a child – hmmm.”

In one of several of their landmark studies on the genetic regulation of pediatric brain development, Jay Giedd and colleagues, now provide in their recent paper, “Variance Decomposition of MRI-Based Covariance Maps Using Genetically-Informative Samples and Structural Equation Modeling”, a core framework on the relative contribution of genes vs. environment for the developing cortex. The paper is part of an ongoing longitudinal study of pediatric brain development at the Child Psychiatry branch at NIMH. Some 600 children participated – including identical twins, fraternal twins, siblings and singleton children.

The team used an analytical approach known as MACAAC (Mapping Anatomical Correlations Across the Cerebral Cortex) to ask how much does the variation in a single part of the brain co-vary with other parts ? Then the team used structural equation modeling to explore how much this co-variation might differ across identical twins vs. fraternal vs. siblings vs. age-matched singleton children. In locations where there is an high genetic contribution to co-variation in cortical thickness, identical twins should co-vary more tightly than fraternal twins or siblings etc. In this way, the team were able to parse out the relative influence of genes vs. environment to the developing brain.

In general terms, the team reports that a single genetic factor accounts for the majority of variation in cortical thickness, which they note may be consistent with a major mechanism of development of cortical layers involving the migration of neurons along radial glia. Genetic co-variances across separate locations in the brain were highest in the frontal cortex, middle temporal gyrus and left supramarginal gyrus. Interestingly, when environmental covariations were observed, they were usually restricted to just one hemisphere, while genetic covariations were often observed bilaterally.

Figure 5 of this paper is really incredible, it shows which areas of the cortex are more influenced by genes vs. environment. If I can just find the areas involved in screaming, the next time one of my neighbors looks askance at my F1, I’ll be able to explain.

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inside my brain
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Every student can recall at least one stereotypical professor who – while brilliant – kept the students amused with nervous and socially inept behavior. Let’s face it, if you’re in academia, you’re surrounded by these – uh, nerds – and, judging by the fact that you are reading (not to mention writing) this blog right now – probably one of them. So, its natural to ask whether there might be a causal connection between emotionality, on the one hand, and cognitive performance on the other. Research on the neuromodulator serotonin shows that it plays a key role in emotional states – in particular, anxiety. Might it exert effects on cognitive performance ? In their paper, “A functional variant of the tryptophan hydroxylase 2 gene impacts working memory: A genetic imaging study“, (DOI: 10.1016/j.biopsycho.2007.12.002) Reuter and colleagues use a genetic variation a G to T snp (rs4570625) in the tryptophan hydroxylase 2 gene, a rate limiting biosynthetic isoenzyme for serotonin to evaluate its effect on a cognitive task. They ask subjects (who are laying in an MRI scanner) to perform a rather difficult cognitive task called the N-back task where the participant must maintain a running memory queue of a series of sequentially presented stimuli. Previous research shows that individuals with the GG genotype show higher scores on anxiety-related personality traits and so Reuter and team ask whether these folks activate more or less of their brain when performing the N-back working memory task. It turns out that the GG group showed clusters of activity in the frontal cortex that showed less activation than the TT group. The authors suggest that the GG group can perform the task using by recruiting less of their brains – hence suggesting that perhaps there just might be a genetic factor that accounts for a possible negative correlation between efficient cognitive performance and emotionality.

My 23andMe profile shows a GG here – nerd to the hilt – what will I use the rest of my PFC for ? Something else to worry about.

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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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Saimiri sciureus.
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Behavioral geneticists are fond of noting that more than half of the risk for mental illness is heritable, and, fonder of the number of specific risk factors that have been identified. What is much less well known however is how these heritable factors interact with the environment to potentiate risk. Psychiatrists, on the other hand, rightly point out that children and adults who experience traumatic and social stress are also at greater risk for psychiatric illness. Indeed, brain imaging has shown a number of anatomical regions where activity declines in subjects and patients alike who experience trauma or other difficult experience. In their recent paper, “Stress-induced changes in primate prefrontal profiles of gene expression,” Karssen and colleagues take a major step towards bridging the gene-by-experience puzzle and examine how gene expression changes in response to socially stressful experience. Using a squirrel monkey model, an experimental group of males was subjected to intermittent social separation and also exposure to new roommates – conditions known to elevate cortisol levels. Using a (note the caveat here) human microarray platform and several signal analysis protocols, the investigators present several hundred genes differentially (interestingly mostly down-regulated) expressed in the frontal cortex. So – the question begs – were any of the genes identified in the Karssen study the same, or in the same pathways, as known genetic risk factors ? Yes – well sort of. The authors present several genes, including a few involved in GABA signaling, that had previously been linked via gene expression studies to mood disorders in humans. Certainly, these are attractive candidates for family- and population-based association studies.

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Daniel Weinberger and company have a new installment in-press at Biological Psychiatry in their epic program to untangle the genetic basis of schizophrenia – “Heritability of Brain Morphology Related to Schizophrenia: A Large-Scale Automated Magnetic Resonance Imaging Segmentation Study.” Like all complex illness, schizophrenia is regulated by a variety of environmental sources (perinatal complications, stress & substance abuse are a few) and equally regulated by heritable factors. Although several specific genes for schizophrenia have been painstakingly identified, the genes are expressed widely throughout the brain – making it difficult to pinpoint where in the brain the gene interacts with the environment to exert its detrimental effects. To solve this problem, Weinberger and colleagues pioneered a method known as imaging-genetics where they look at how individual genetic differences correlate with differences in brain structure or functional activity (if you ever have a chance to volunteer for an fMRI brain imaging study – go for it – it’ll be one of the top 10 weirdest experiences of your life). In their latest report, the team pioneers a new “fully-automated whole brain segmentation” technique to show that the genetic factors that put individuals at risk may be functioning vis-a-vis the hippocampus and neocortex. This narrows the search space a lot! and is a major step forward in beginning to localize where in the brain the genetic risk originates.

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The DISC1 mouse is a major step forward in a translational research path towards understanding how genes contribute to the risk of complex mental disorders such as schizophrenia. The latest mouse (see PNAS – Dominant-negative DISC1 transgenic mice display schizophrenia-associated phenotypes detected by measures translatable to humans by Hikida et al.) attempts to replace the normal mouse gene with a human mutation. The deficits parallel human abnormalities in a remarkable way. Note, however, that Joseph Gogos and colleagues (including my one-time boss Maria Karayiorgou) have shown (see PNAS -Disc1 is mutated in the 129S6/SvEv strain and modulates working memory in mice by Hiroko et al.) that an ostensibly normal mouse inbred strain (normal, that is, if you’re inbred for one, and a mouse, for another) carries a truncated form of DISC1. Both of these mouse models show deficits in frontal cortex dependent behaviors but, together, they also demonstrate how the many interacting genes in the background can modify and ameliorate the effects of a single mutation. Do the genes that modify DISC1 in mice modify risk in humans?

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