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Posts Tagged ‘Gene expression’

By Richard Wheeler (Zephyris) 2007. The three ...
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File this story under “the more you know, the more you don’t know” or simply under “WTF!”  The new paper, “Microduplications of 16p11.2 are associated with schizophrenia” [doi:10.1038/ng.474] reveals that a short stretch of DNA on chromosome 16p11.2 is – very rarely – duplicated and – more rarely – deleted.  In an analysis of 8,590 individuals with schizophrenia, 2,172 with developmental delay or autism, 4,822 with bipolar disorder and 30,492 controls, the the microduplication of 16p11.2 was strongly associated with schizophrenia, bipolar and autism while the reciprocal microdeletion was strongly associated with developmental delay or autism – but not associated with schizophrenia or bipolar disorder.

OK, so the title of my post is misleading (hey, its a blog) since there are clearly many additional factors that contribute to the developmental outcome of autism vs. schizophrenia, but this stretch of DNA seems to hold clues about early development of brain systems that go awry in both disorders.  Here is a list of the brain expressed genes in this 600 kbp region (in order from telomere-side to centromere-side): SPN, QPRT, C16orf54, MAZ, PRRT2, C16orf53, MVP, CDIPT, SEZ6L2, ASPHD1, KCTD13, TMEM219, TAOK2, HIRIP3, INO80E, DOC2A, FLJ25404, FAM57B, ALDOA, PPP4C, TBX6, YPEL3, GDPD3, MAPK3, CORO1A.

Any guess as to which one(s) are the culprits?  I’ll go with HIRIP3 given its role in chromatin structure regulation – and the consequent regulation of under- (schiz?)/over- (autism) growth of synapses. What an amazing mystery to pursue.

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Daniel R. Weinberger, M.D., Chief of the Clinical Brain Disorders Branch and Director of the Genes, Cognition and Psychosis Program, National Institute of Mental Health  discusses the background, findings and general issues of genes and mental illness in this brief interview on his paper, “A primate-specific, brain isoform of KCNH2 affects cortical physiology, cognition, neuronal repolarization and risk of schizophrenia”.  Click  HERE for the podcast and HERE for the original post.

Thanks again to Dr. Weinberger for his generous participation!

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creb1According to Joseph LeDoux, “One of the most important contributions of modern neuroscience has been to show that the nature/nurture debate operates around a false dichotomy: the assumption that biology, on one hand, and lived experience, on the other, affect us in fundamentally different ways” (ref).  Indeed.  While I know not where the current debate stands, I’d like to point to a fantastic example of just how inextricably linked the genome is to the environment.  In their recent paper, “A Biological Function for the Neuronal Activity-Dependent Component of Bdnf Transcription in the Development of Cortical Inhibition” [doi:10.1016/j.neuron.2008.09.024]  Hong et al., ask what happens when you take away the ability of a given gene to respond to the environment.  This is not a traditional “knockout” experiment – where the gene is inactivated from the moment of conception onwards – but rather a much more subtle type of experimental manipulation.  What happens when you prevent nurture from exerting an effect on gene expression?

The team focused on the BDNF gene whose transcription can be initiated from any one of eight promoter sites (I-XIII).  These sites vary in activity depending on the phase of development and/or the tissue or type of cell – all of which make for a complex set of instructions able to turn the BDNF gene on and off in precise developmental and/or tissue-specific ways.  In the case of promoter IV, it appears to be triggered in the cortex in response to Ca++ release that occurs when neurons are firing – a phenomena called, “neuronal activity dependent transcription” – a top example of how the environment can influence gene expression.  Seeing as how BDNF promoter IV is important for this type of environment-induced gene expression, the team asked what happens when you remove this particular promoter?

To do this, the team constructed – keep in mind that these are – mice that contain mutations in several of the Calcium (Ca++) response elements in the promoter IV region.  They introduced point mutations so that the Ca++ sensitive protein CREB could not bind to the promoter and activate gene expression.  OK, so what happens?

Firstly, the team reports that the mutant mice are more or less indistinguishable from controls in appearance, gait, growth rate, brain size and can also reproduce and transmit the mutations.  WOW! Is that one strike AGAINST nurture? The team then shows that BDNF levels are more than 50% reduced in cultured neurons, but that levels of other immediate early genes are NOT affected (as expected).  In living animals, the effects were similar when they asked how much gene expression occurs in the sensory cortex when animals are exposed to light (after an extended period of darkness).  OK, so there are few effects, so far, other than lower levels of nurture-induced BDNF expression – hmmm. Looking more closely however, the team found that the mutant mice generated lower levels of inhibitory neuron activity – as measured by the firing of miniature inhibitory postsynaptic currents.  Follow-on results showed that the total number of inhibitory neurons (parvalbumin and NPY + GABAergic cells) was no different than controls and so it would seem that the activity dependence of BDNF is important for the maintenance of inhibitory synapses.

Hence, the team has found that what “nurture” does (via the BDNF promoter IV in this case) is to exert an effect on the connectivity of inhibitory neurons.  Wow, thanks mother nurture!  Although it may seem like an obscure role for something as important as THE environment, the team points out that the relative balance of excitation-to-inhibition (yin-yang as covered here for Rett syndrome) is crucial for proper cognitive development.

To explore the notion of inhibory/excitation balance further, check out this (TED link) video lecture, where Michael Merzenich describes this imbalance as a “signal-to-noise” problem wherein some children’s brains are rather noisy (due to any number of genetic/environmental reasons – such as, perhaps, poorly maintained inhibitory connections).  This can make it harder to develop and function in life.  Perhaps someday, the genetic/environment research like that of Hong and colleagues will inform the rehabilitative strategies developed by Merzenich.

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In previous posts, we have explored some of the basic molecular (de-repression of chromatin structure) and cellular (excess synaptogenesis) consequences of mutations in the MeCP2 gene – a.k.a the gene whose loss of function gives rise to Rett syndrome.  One of the more difficult aspects of understanding how a mutation in a lowly gene can give rise to changes in cognitive function is bridging a conceptual gap between biochemical functions of a gene product — to its effects on neural network structure and dynamics.  Sure, we can readily acknowledge that neural computations underlie our mental life and that these neurons are simply cells that link-up in special ways – but just what is it about the “connecting up part” that goes wrong during developmental disorders?

In a recent paper entitled, “Intact Long-Term Potentiation but Reduced Connectivity between Neocortical Layer 5 Pyramidal Neurons in a Mouse Model of Rett Syndrome” [doi: 10.1523/jneurosci.1019-09.2009] Vardhan Dani and Sacha Nelson explore this question in great detail.  They address the question by directly measuring the strength of neural connections between pyramidal cells in the somatosensory cortex of healthy and MeCP2 mutant mice.  In earlier reports, MeCP2 neurons showed weaker neurotransmission and weaker plasticity (an ability to change the strength of interconnection – often estimated by a property known as “long term potentiation” (LTP – see video)).   In this paper, the authors examined the connectivity of cortical cells using an electrophysiological method known as patch clamp recording and found that early in development, the LTP induction was comparable in healthy and MeCP2 mutant animals, and even so once the animals were old enough to show cognitive symptoms.  During these early stages of development, there were also no differences between baseline neurotransmission between cortical cells in normal and MeCP2 mice.  Hmmm – no differences? Yes, during the early stages of development, there were no differences between genetic groups – however – once the team examined later stages of development (4 weeks of age) it was apparent that the MeCP2 animals had weaker amplitudes of cortical-cortical excitatory neurotransmission.  Closer comparisons of when the baseline and LTP deficits occurred, suggested that the LTP deficits are secondary to baseline strength of neurotransmission and connectivity in the developing cortex in MeCP2 animals.

So it seems that MeCP2 can alter the excitatory connection strength of cortical cells.  In the discussion of the paper, the authors point out the importance of a proper balance of inhibition and excitation (yin and yang, if you will) in the construction or “connecting up part” of neural networks.  Just as Rett syndrome may arise due to such a problem in the proper linking-up of cells – who use their excitatory and inhibitory connections to establish balanced feedback loops – so too may other developmental disorders such as autism, Down’s syndrome, fragile X-linked mental retardation arise from an improper balance of inhibition and excitation.

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The cognitive and emotional impairments in the autism spectrum disorders can be difficult for parents and siblings to understand and cope with.  Here are some graphics and videos that might assist in understanding how genetic mutations and epigenetic modifications can lead to various forms of social withdrawl commonly observed in the autism spectrum disorders in children.

In this post, the focus is just on the MecP2 gene – where mutations are known to give rise to Rett Syndrome – one of the autism spectrum disorders.  I’ll try and lay out some of the key steps in the typical bare-bones-link-infested-blogger-fashion – starting with mutations in the MecP2 gene.  Disclaimer: there are several fuzzy areas and leaps of faith in the points and mouse model evidence below, and there are many other genes associated with various aspects of autism spectrum disorders that may or may not work in this fashion.  Nevertheless, still it seems one can begin to pull a mechanistic thread from gene to social behavior Stay tuned for more on this topic.

1. The MecP2 gene encodes a protein that binds to 5-Methylcytosine – very simply – a regular cytosine reside with an extra methyl group added at position 5.  Look at the extra -CH3 group on the cytosine residue in the picture at right.  See?  That’s a 5-methylcyctosine residue – and it pairs in the DNA double helix with guanosine (G) in the same fashion as does the regular cyctosine reside (C). 5methC OK, now, mutations in the gene that encode the  MecP2 gene – such as those found at Arginine residue 133 and Serine residue 134 impair the ability of the protein to bind to these 5-Methylcyctosine residues.  bindingMecP2The figure at left illustrates this, and shows how the MecP2 protein lines up with the bulky yellow 5-Methylcytosine residues in the blue DNA double helix during binding.

2. When the MecP2 protein is bound to the methylated DNA, it serves as a binding site for another type of protein – an HDAC or histone deacetylase. The binding of MecP2 and HDAC (and other proteins (see p172 section 5.3 of this online bookChromatin Structure and Gene Expression“)).  The binding of the eponymously named HDAC’s leads to the “de-acetylation” of proteins known as histones.  The movie below illustrates how histone “de-acetylation” leads to the condensation of DNA structure and repression or shutting down of gene expression (when the DNA is tightly coiled, it is inaccessible to transcription factors).  Hence: DNA methylation leads (via MecP2, HDAC binding) to a repression on gene expression.


3. When mutated forms of MecP2 cannot bind, the net result is MORE acetylation and MORE gene expression. As covered previously here, this may not be a good thing during brain development since more gene expression can induce the formation of more synapses and – possibly – lead to neural networks that fail to grow and mature in the “normal” fashion. The figure at right toomanysynapsessuggests that neural networks with too many synapses may not be appropriately connected and may be locked-in to sub-optimal architectures.  Evidence for excessive synaptogenesis is abundant within the autism spectrum disorders.  Neuroligins – a class of genes that have been implicated in autism are known to function in cell & synaptic adhesion (open access review here), and can alter the balance of excitation/inhibition when mutated – which seems consistent with this heuristic model of neural networks that can be too adhesive or sticky.

4. Cognitive and social impairment can result from poor-functioning neural networks containing, but not limited to the amygdala. The normal development of neural networks containing the forntal cortex and amygdala are important for proper social and emotional function.  The last piece of the puzzle then would be to find evidence for developmental abnormalities in these networks and to show that such abnormalities mediate social and/or emotional function.  Such evidence is abundant.

Regarding the effects of MecP2 however, we can consider the work of Adachi et al., who were able to delete the MecP2 gene – just in the amygdala – of (albeit, an adult) mouse.  Doing so, led to the disruption of various emotional behaviors – BUT NOT – of various social interaction deficits that are observed when MecP2 is deleted in the entire forebrain.  This was the case also when the team infused HDAC inhibitors into the amygdala suggesting that loss of transcriptional repression in the adult amygdala may underlie the emotional impariments seen in some autism spectrum disorders.  Hence, such emotional impairments (anxiety etc.) might be treatable in adults (more on this result later and its implications for gene-therapy).

Whew!  Admittedly, the more you know – the more you don’t know.  True here, but still amazing to see the literature starting to interlink across human-genetic, mouse-genetic, human-functional-imaging levels of analysis. Hoping this rambling was helpful.

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The homunculus (argument) is a pesky problem in cognitive science – a little guy who might suddenly appear when you propose a mechanism for decision making, spontaneous action or forethought  etc. – and would take credit for the origination of the neural impulse.  While there are many mechanistic models of decision making that have slain the little bugger – by invoking competition between past experience and memory as the source of new thoughts and ideas – one must always tread lightly, I suppose, to be wary that cognitive mechanisms are based completely in neural properties devoid of a homuncular source.

Still, the human mind must begin somewhere.  After all, its just a ball of cells initially, and then a tube and then some more folds, layers, neurogenesis and neural migration  etc. before maturing – miraculously – into a child that one day looks at you and says, “momma” or “dada”.  How do these neural networks come into being?  Who or what guides their development toward that unforgettable, “momma (dada)” moment?  A somewhat homuncluar “genetic program” – whose instructions we can attribute to millions of years of natural selection?  Did early hominid babies say “momma (dada)?  Hmmm. Seems like we might be placing a lot of faith in the so-called “instructions” provided by the genome, but who am I to quibble.

On the other hand, you might find that the recent paper by Akhtar et al., “Histone Deacetylases 1 and 2 Form a Developmental Switch That Controls Excitatory Synapse Maturation and Function” [doi:10.1523/jneurosci.0097-09.2009] may change the way you think about cognitive development.  The team explores the function of two very important epigenetic regulators of gene expression – histone deacetylases 1,2 (HDAC1, HDAC2) on the functionality of synapses in early developing mice and mature animals.  By epigenetic, I refer to the role of these genes in regulating chromatin structure and not via direct, site-specific DNA binding.  The way the HDAC genes work is by de-acetylating – removing acetyl groups – thus removing a electrostatic repulsion of acetyl groups (negative charge) on histone proteins with the phosphate backbone of DNA (also a negative charge).  When the histone proteins carry such an acetyl group, they do NOT bind well to DNA (negative-negative charge repulsion) and the DNA molecule is more open and exposed to binding of transcription factors that activate gene expression.  Thus if one (as Akhtar do) turns off a de-acetylating HDAC gene, then the resulting animal has a genome that is more open and exposed to transcription factor binding and gene expression.  Less HDAC = more gene expression!

What were the effects on synaptic function?  To summarize, the team found that in early development (neonatal mouse hippocampal cells) cells where the HDAC1 or 2 genes were turned off (either through pharmacologic blockers or via partial deletion of the gene(s) via lentivirus introduction of Cre recombinase) had more synapses and more synaptic electrical activity than did hippocampal cells from control animals.  Keep in mind that the HDACs are located in the nucleus of the neuron and the synapses are far, far away.  Amazingly – they are under the control of an epigenetic regulator of gene expression;  hence, ahem, “epigenetic puppetmasters”.  In adult cells, the knockdown of HDACs did not show the same effects on synaptic formation and activity.  Rather the cells where HDAC2 was shut down showed less synaptic formation and activity (HDAC1 had no effect).  Again, it is amazing to see effects on synaptic function regulated at vast distances.  Neat!

The authors suggest that the epigenetic regulatory system of HDAC1 & 2 can serve to regulate the overall levels of synaptic formation during early cognitive development.  If I understand their comments in the discussion, this may be because, you don’t necessarily want to have too many active synapses during the formation of a neural network.   Might such networks might be prone to excitotoxic damage or perhaps to being locked-in to inefficient circuits?  The authors note that HDACs interact with MecP2, a gene associated with Rett Syndrome – a developmental disorder (in many ways similar to autism) where neural networks underlying cognitive development in children fail to progress to support higher, more flexible forms of cognition.  Surely the results of Akhtar et al., must be a key to understanding and treating these disorders.

Interestingly, here, the controller of these developmental phenotypes is not a “genetic program” but rather an epigenetic one, whose effects are wide-spread across the genome and heavily influenced by the environment.  So no need for an homunculus here.

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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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FTM_phase_locking_v4_0**PODCAST accompanies this post** In the brain, as in other aspects of life, timing is everything.  On an intuitive level, its pretty clear, that, since neurons have to work together in widely distributed networks, they have a lot of incentive to talk to each other in a rhythmic, organized way. Think of a choir that sings together vs. a cacophony of kids in a cafeteria – which would you rather have as your brain? A technical way of saying this could be, “Clustered bursting oscillations, with in-phase synchrony within each cluster, have been proposed as a binding mechanism. According to this idea, neurons that encode a particular stimulus feature synchronize in the same cluster.”  A less technical way of saying this was first uttered by Carla Shatz who said, “Neurons that fire together wire together” and “Neurons that fire apart wire apart“.  So it seems, that the control over neural timing and synchronicity – the rushing “in” of Na+ ions and rushing “out” of K+ ions that occur during cycles of depolarization and repolarization of an action potential take only a few milliseconds – is something that neurons would have tight control over.

With this premise in mind, it is fascinating to ponder some recent findings reported by Huffaker et al. in their research article, “A primate-specific, brain isoform of KCNH2 affects cortical physiology, cognition, neuronal repolarization and risk of schizophrenia” [doi: 10.1038/nm.1962].  Here, the research team has identified a gene, KCNH2, that is both differentially expressed in brains of schizophrenia patients vs. healthy controls and that contains several SNP genetic variants (rs3800779, rs748693, rs1036145) that are associated with multiple different patient populations.  Furthermore, the team finds that the risk-associated SNPs are associated with greater expression of an isoform of KCNH2 – a kind of special isoform – one that is expressed in humans and other primates, but not in rodents (they show a frame-shift nucleotide change that renders their ATG start codon out of frame and their copy non-expressed).  Last I checked, primates and rodents shared a common ancestor many millenia ago. Very neat – since some have suggested that newer evolutionary innovations might still have some kinks that need to be worked out.

In any case, the research team shows that the 3 SNPs are associated with a variety of brain parameters such as hippocampal volume, hippocampal activity (declarative memory task) and activity in the dorsolateral prefrontal cortex (DLPFC). The main suggestion of how these variants in KCNH2 might lead to these brain changes and risk for schizophrenia comes from previous findings that mutations in this gene screw up the efflux of K+ ions during the repolarization phase of an action potential.  In the heart (where KCNH2 is also expressed) this has been shown to lead to a form of “long QT syndrome“.  Thus, the team explores this idea using primary neuronal cell cultures and confirms that greater expression of the primate isoform leads to non-adaptive, quickly deactivating, faster firing patterns, presumably due to the extra K+ channels. 

The authors hint that fast & extended spiking is – in the context of human cognition – is thought to be a good thing since its needed to allow the binding of multiple input streams.  However, in this case, the variants seem to have pushed the process to a non-adaptive extreme.  Perhaps there is a seed of an interesting evolutionary story here, since the innovation (longer, extended firing in the DLPFC) that allows humans to ponder so many ideas at the same time, may have some legacy non-adaptive genetic variation still floating around in the human lineage.  Just a speculative muse – but fun to consider in a blog post.

In any case, the team has substantiated a very plausible mechanism for how the genetic variants may give rise to the disorder.  A scientific tour-de-force if there ever was one.

On a personal note, I checked my 23andMe profile and found that while rs3800779 and rs748693 were not assayed, rs1036145 was, and I – boringly – am a middling G/A heterozygote.  In this article, the researchers find that the A/As showed smaller right-hippocampal grey matter volume, but the G/A were not different that the G/Gs.  During a declarative memory task, the GGs showed little or no change in hippocampal activity while the AA and GA group showed changes – but only in the left hippocampus.  In the N-back task (a working memory task), the AA’s showed more changes in brain activation in the right DLPFC compared to the GGs and GAs.

For further edification, here is a video showing the structure of the KCNH2-type K+ channel.  Marvel at the tiny pore that allows red K+ ions to leak through during the repolarization phase of an action potential.   **PODCAST accompanies this post**

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In the lowly worm Caenorhabdritis elegans, it has been long possible to understand the exact lineage of each of its 959 somatic cells.  That is, one can know for each and every cell, who its parental cell was, and grand-parental cell etc., back until the very first cell division (feast your eyes on these movies of  C. elegans development).  Similarly, it is possible to follow what networks of genes are transcribed (turned on/off) as these cellular divisions and differentiations occur.  In this sense, one can reconstruct the transcriptional events occuring within the nucleus of a cell with outward changes in cell structure and migration as the lowly li’l worm develops.

If, for example, there were genes that led to abberant behavior in the worm, then it would be possible to query when and where such a gene was expressed and under who’s transcriptional control.  Such  a tool would be powerful and useful indeed – especially if there were genetically-based abberant behavioral disorders in worms.  Nice to be a lowly worm (psychiatrist) these days.

So, what about human brains? and human genes that have been correlated with changes in brain structure, brain activity and/or brain disorders?  Are there tools that allow us to reconstruct an outward cellular lineage and correlate it with a transcriptional lineage?  Where might genes for abberant brain function lie in such a lineage?  – perhaps early in the course of brain development, with many subsequent genes under its control and whose expression mediates the development of many daughter and granddaugter cells?  Or perhaps mental illness risk genes have little regulatory oversight and have rather specific effects on a small number of specialized cells later in the course of development?  Wouldn’t we like to know!

With this query in mind, it was fun to read a recent article entitled, “The organization of the transcriptional network in specific neuronal classes” by Winden et al., [free access doi: 10.1038/msb.2009.46].  This article describes an amazing bioinformatic open-public use tool called, “Weighted Gene Co-Expression Network Analysis” which seems to have been developed in the lab of Steve Horvath at UCLA (one of the co-authors).  The authors examined the gene expression data from an array of 12 different adult neuronal cell types (this analysis was performed using mouse brain tissue) and used the WGCNA method to organize the patterns of gene expression and then asked how they relate to different cell morphologies and physiological attributes (such as firing patterns).  In this way, they are beginning to construct a genetic road map of mammalian brain development that is much like that for C. elegans.

To me, the really exciting thing about this particular analysis (they also have used this method to compare gene expression in a brain-region-specific way in humans vs. chimpanzees) is that the different cell types in the brain perform different – here comes the punchline computations! Thus, if there be a genetic code for neuron structure/function (and from the work of Horvath and colleagues, it looks like there be), then it should be possible to begin to assign these module-specific genetic factors to computations or computational properties of the brain – and have a more mechanistic synthesis of genetic influences on cognition.

A few examples from the paper include different transcriptional co-expression networks (modules) for glutamateric and GABAergic cell types, which have distinct functions in the regulation of neural dynamics (ie. computation).  Further analysis yielded different co-expression modules for the development of different types of interneurons.  The team also finds different co-expression modules for aspects of cell-firing and synaptic structure which would very likely have effects on neural-network dynamics.  Also, there is an analysis of the RGS4 knockout mouse and a query into the specificity of the co-expression module that contains RGS4 (very few abberant gene expression changes outside the RGS4 module) which – since RGS4 has been associated with schizophrenia – reveals clues on the expected consequences of RGS4 mutations in humans.

There is really too much to cover in a single blog post, so am going to dig in to the data in more detail and report back later.  An amazing tool graciously shared with the community!

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Just a salute to Carol L. Thompson and her colleagues at the Allen Institute for Brain Science (Seattle, WA) on their paper entitled,  “Genomic Anatomy of the Hippocampus” [doi: 10.1016/j.neuron.2008.12.008] or (email the corresponding author for a copy).

This paper (and much of the work from the Allen Institute) could be filed under the lonstanding cry heard among grad students, “if every neuron is connected to every neuron, how will we ever make sense of the brain?”  The present paper is an excellent example of how cells within a particular structure – in this case the hippocampus – can be specialized in terms of their structure and connectivity.  Not surprisingly, the differences in structure and connectivity are driven, in part, by differential gene expression, which this group has ably made sense of.  There are a number of great figures that tell the story, but for me, the $$ shot is Figure 3 showing that their “statistical reduction” analysis of 20,000 unique transcripts in the mouse brain led to the identification and 3D-reconstruction of 9 discrete zones of gene expression within the hippocampus.  Further analysis of cell adhesion genes (cadherins, collagens, IgG superfamily) and axon guidance genes (ephrins, slits, robos, semaphorins) showed that these 9 regions differ in their combinatorial expression of these molecules.  Thus, the 9 regions of the hippocampus may reflect different zones in incoming (afferent) and outgoing (efferent) neural transmission (they confirm this for CA3 projections to the lateral septum using retrograde labeling).

At some point in the future, as genetic associations with memory and other hippocampal functions are identified, it may be possible to use this type of atlas (there is a human Allen Brain Atlas atlas in the works) to better understand what functional subdivisions and therefore, what type of circuitry is involved in individual differences in hippocampal function.  A possibility I hope I’ll not soon forget.

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OK, there’s not really a “coolest” part of the brain, but, some areas are pretty darn weird & wild.  Consider the cingulate cortex (shown here).  Electrical stimulation of the pACC region in humans can produce overwhelming fear – even a feeling that death is imminent – while stimulation of white matter tracts adjacent to area 25 can relieve treatment resistent depression. Activity in the MCC region is often associated – not with emotion – but with motor planning and selection of actions.  Stimulation of this area evoked the feeling of “I felt something, as though I was going to leave.” Interestingly, this region also contains a unique type of large neuron known as a von Economo cell,  found in humans and Bonobo chimpanzees, but not other primate species – leading some to speculate that this area must contribute to something that makes us uniquely human.  The PCC and RSC regions seem to be involved in how your brain computes where you are in 3-dimensional space, since activity in the PCC rises when participants mentally navigate pathways and routes of travel or assess the “self-relevance” of sensory stimuli, while lesions in RSC lead to topographic disorientation.  Whew, that’s a lot of functionality !  Indeed, with so many functions, its not surprising that this region is often linked to mental illness of all sorts.  In schizophrenia, for example, patients have difficulty controlling their actions (MCC regions have been implicated) as well as their emotions (ACC regions have been implicated) and maintaining a coherent sense of “self” (PCC & RSC regions have also been implicated).

Since we know that this brain region is implicated in mental illness and we know that mental illness arises – in part – due to genetic risk, it is of interest to begin to understand how genetic factors might relate to the development of structure, connectivity and function of the 4 sub-regions of the cingulate cortex.  With this in mind, it was great to see a recent paper from Brent Vogt and colleagues at the Cingulum Neurosciences Institute [doi: 10.1002/hbm.20667] which has begun to examine differential gene expression in these 4 subregions !  They examined the expression of an array of neurotransmitter receptors (at the protein level actually) and asked whether the expression of the receptors was able to differentiate (as lesions, activity and architectonics do) the 4 subregions.  In a word – yes – with the ACC region showing highest AMPA receptor expression and lowest GABA-A receptor expression.  This was very different from the MCC region which had the lowest AMPA receptor expression while PCC had the highest cholinergic M1 receptor expression.

This seems a great foundation for future studies that will continue to dissect the many interconnected – yet separable – functions of the cingulate cortex.  The “holy grail” of which might be to understand the evolutionary origins of the von Economo cells which are unique to our human lineage.  The genome encodes the story – we just need to learn to read it aloud.

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Animated Brain. The brain is divided into the ...Image via Wikipedia A look at almost any gene expression pattern in the brain will most certainly confuse you. This is in contrast to functional imaging studies that often show that the brain is organized into neat, aesthetically pleasing functional circuits. Why don’t genes show similar neat expression patterns that reflect a common functional organization ? Some clues to this can be found in the recent paper, “A survey of genetic human cortical gene expression” by Myers and company (DOI). Their joint analysis of individual variation at the level of genome sequence (Affy 500K array) and mRNA-expression (Illumina Refseq-8 Expression BeadChip) shows that most of the correlations between gene sequence and gene expression are between genetic variants that are far away from the genes whose expression they are correlated with (so-called, trans, effects). The team found 433 SNP-transcript pairs (99 transcripts) that showed a significant specific empirical cis association and 16,701 SNP-transcript pairs (2,876 transcripts) that showed a significant trans association. This result is similar to a previous study using mice DOI that found that the expression of the mouse strain-specific genes was driven mainly by cis-acting regulatory elements, whereas the brain region-specific genes were mainly regulated by trans-acting regulators. Thus, it seems that a given non-coding snp variant may be more likely to influence expression outside its local (50kb) neighborhood than close by. The authors generously provide access to this important data for folks who would like to query candidate snps. Manga !

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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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In a recent free and open BMC report on gene expression in non-smokers vs. current smokers vs. quitters, Chari and colleagues identify a class of genes whose expression “appears to be permanently altered despite prolonged smoking cessation.” Frighteningly, a number of genes encoding DNA repair enzymes are irreversibly altered … definitely not good to mutagenize your genome and then knock out the repairman. Worse yet, another gene that popped up was calcium binding tyrosine-(Y) phosphorylation regulated (CABYR) a gene that is found in the sperm flagellum, lung and brain (these are all tissues with cells that are rich in microtubules and dynein motors – so perhaps CABYR plays a smoking-related role in the lung in ciliary clearance of mucous). Wait a minute, did someone say sperm cell ? Ouch – no more cigarettes please. Although, the effects of smoking on CABYR expression were reversible, I don’t need a direct mutagenic hit there to make me wince, just thinking about that is enough.

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