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Posts Tagged ‘schizophrenia’

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We all have social networks.  Your friends and family are a network of relationships.  The neural networks in your brain that carry out computations involved in social interactions are another type of “social network”.  These two networks are obviously related – in so far as your ability to self-reference and understand your own internal thoughts and feelings predicts how well you can understand and predict the internal thoughts and feelings of others – and thus how extensive your network of friends and family is likely to be.  The structure of your brain networks may even be related to how many friends you have on facebook.

According to Lencz and colleagues, there is a genetic association between the T-allele of rs1344706 and the structure and connectivity of the neural networks that carry out self-referential processing in the brain … in the so-called “default mode network” that is associated with “stimulus independent” mental activity and with social cognition such as when you are attributing mental states to others.

Interestingly, the T-allele of this SNP – residing in the zinc finger protein 804A gene – has been previously associated with schizophrenia (SZ).

From Lencz and colleagues:

“To our knowledge, this is also the first study to identify a genetic correlate of multiple brain regional GM volumes comprising the default mode network.”

The default mode network comprises regions that show synchronized activity at ‘resting’ baseline, in the absence of specific stimulation (Raichle et al, 2001). Ongoing work has implicated this network in the development of self-referential thought (Spreng and Grady, 2010), which has been specifically implicated in the developmental psychopathology of SZ (Nelson et al, 2009).

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Everyone has a birthday right. Its the day you (your infant self) popped into the world and started breathing, right?  But what about the day “you” were born – that is – “you” in the more philosophical, Jungian, spiritual, social, etc. kind of a way when you became aware of being in some ways apart from others and the world around you.  In her 1997 paper, “The Basal Ganglia and Cognitive Pattern Generators“, Professor Ann Graybiel writes,

The link between intent and action may also have a quite specific function during development. This set of circuits may provide part of the neural mechanism for building up cognitive patterns involving recognition of the self. It is well documented that, as voluntary motor behaviors develop and as feedback about the consequences of these behaviors occurs, the perceptuomotor world of the infant develops (Gibson 1969). These same correlations among intent, action, and consequence also offer a simple way for the young organism to acquire the distinction between actively initiated and passively received events. As a result, the infant can acquire the recognition of self as actor. The iterative nature of many basal ganglia connections and the apparent involvement of the basal ganglia in some forms of learning could provide a mechanism for this development of self-awareness.

As Professor Graybiel relates the “self” to function in the basal-ganglia and the so-called cortico-thalamic basal-ganglia loops – a set of parallel circuits that help to properly filter internal mental activity into specific actions and executable decisions – I got a kick out of a paper that describes how the development of the basal-ganglia can go awry for cells that are born at certain times.

Check out the paper, “Modular patterning of structure and function of the striatum by retinoid receptor signaling” by Liao et al.   It reveals that mice who lack a certain retinoic acid receptor gene (RARbeta) have a type of defective neurogenesis in late-born cells that make up a part of the basal ganglia (striatum) known as a striosome.  Normally, the authors say, retinoic acid helps to expand a population of late-born striosomal cells, but in the RARbeta mutant mice, the rostral striosomes remain under-developed.   When given dopaminergic stimulation, these mutant mice showed slightly less grooming and more sterotypic behaviors.

So when was “my self’s” birthday?  Was it when these late-born striosomal cells were, umm, born?  Who knows, but I’m glad my retinoic acid system was intact.

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

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

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

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

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

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

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

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Some quick sketches that might help put the fast-growing epigenetics and cognitive development literature into context.  Visit the University of Utah’s Epigenetics training site for more background!

The genome is just the A,G,T,C bases that encode proteins and other mRNA molecules.  The “epi”genome are various modification to the DNA – such as methylation (at C residues) – and acetylation of histone proteins.   These changes help the DNA form various secondary and tertiary structures that can facilitate or block the interaction of DNA with the transcriptional machinery.

When DNA is highly methylated, it generally is less accessible for transcription and hence gene expression is reduced.  When histone proteins (purple blobs that help DNA coil into a compact shape) are acetylated, the DNA is much more accessible and gene expression goes up.

We know that proper epigenetic regulation is critical for cognitive development because mutations in MeCP2 – a protein that binds to methylated C residues – leads to Rett syndrome.  MeCP2 is normally responsible for binding to methylated DNA and recruiting histone de-acetylases (HDACs) to help DNA coil and condense into a closed form that is inaccessible for gene expression (related post here).

When DNA is accessible for gene expression, then it appears that – during brain development – there are relatively more synaptic spines produced (related post here).  Is this a good thing? Rett syndrome would suggest that – NO – too many synaptic spines and too much excitatory activity during brain development may not be optimal.  Neither is too little excitatory (too much inhibitory) activity and too few synaptic spines.  It is likely that you need just the right balance (related post here). Some have argued (here) that autism & schizophrenia are consequences of too many & too few synapses during development.

The sketch above illustrates a theoretical conjecture – not a scenario that has been verified by extensive scientific study. It tries to explain why epigenetic effects can, in practice, be difficult to disentangle from true (changes in the A,G,T,C sequence) genetic effects.  This is because – for one reason – a mother’s experience (extreme stress, malnutrition, chemical toxins) can – based on some evidence – exert an effect on the methylation of her child’s genome.  Keep in mind, that methylation is normal and widespread throughout the genome during development.  However, in this scenario, if the daughter’s behavior or physiology were to be influenced by such methylation, then she could, in theory, when reaching reproductive age, expose her developing child to an environment that leads to altered methylation (shown here of the grandaughter’s genome).  Thus, an epigenetic change would look much like there is a genetic variant being passed from one generation to the next, but such a genetic variant need not exist (related post here, here) – as its an epigenetic phenomenon.  Genes such as BDNF have been the focus of many genetic/epigenetic studies (here, here) – however, much, much more work remains to determine and understand just how much stress/malnutrition/toxin exposure is enough to cause such multi-generational effects.  Disentangling the interaction of genetics with the environment (and its influence on the epigenome) is a complex task, and it is very difficult to prove the conjecture/model above, so be sure to read the literature and popular press on these topics carefully.

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The recent paper, “Comparative genomics of autism and schizophrenia” by Bernard Crespi and colleagues provides a very exciting take on how genetic data can be mined to understand cognitive development and mental illness.  Looking at genetic association data for autism and schizophrenia, the authors point out that 4 loci are associated with both schizophrenia and autism – however, with a particular twist.  In the case of 1q21.1 and 22q11.21 it seems that genetic deletions are associated with schizophrenia while duplications at this locus are associated with autism.  At 16p11.2 and 22q13.3  it seems that duplications are associated with schizophrenia and deletions are associated with autism.  Thus both loci contain genes that regulate brain development such that too much (duplication) or too little (deletion) of these genes can cause brain development to go awry.  The authors point to genes involved in cellular and synaptic growth for which loss-of-function in growth inhibition genes (which would cause overgrowth) have been associated with autism while loss-of-function in growth promoting genes (which would cause undergrowth) have been associated with schizophrenia.  Certainly there is much evidence for overproduction of synapses in the autism-spectrum disorders and loss of synapses in schizophrenia.  Crespi et al., [doi:10.1073/pnas.0906080106]

Other research covered (here, here) demonstrates the importance of the proper balance of excitatory and inhibitory signalling during cortical development.

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pointer to symptommedia.org – fantastic video resource of specific symptoms of mental illness.

“The intention of these clips are to be used in the classroom setting as visual compliments to the written description of symptoms for psychological phenomena found in the DSM handbook.”

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ruler - STUPID INCOMPETENT MANUFACTURERS
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One of the difficult aspects of understanding mental illness, is separating the real causes of the illness from what might be secondary or tertiary consequences of having the illness.  If you think about a car whose engine is not running normally, there may be many observable things going wrong (pinging sound, stalling, smoke, vibration, overheating, loss of power, etc.) – but, what is the real cause of the problem?  What should be done to fix the car? – a faulty sparkplug or timing belt perhaps?  Such is often the problem in medicine, where a fundamental problem can lead to a complex, hard-to-disentangle, etiology of symptoms.  Ideally, you would fix the core problem and then expect the secondary and tertiary consequences to normalize.

This inherent difficulty, particularly in mental illness, is one of the reasons that genetic research is of such interest.  Presumably, the genetic risk factors are deeper and more fundamentally involved in the root causes of the illness – and hence – are preferable targets for treatment.  The recent paper, “Widespread Reductions of Cortical Thickness in Schizophrenia and Spectrum Disorders and Evidence of Heritability” [Arch Gen Psychiatry. 2009;66(5):467-477] seeks to ascertain whether one aspect of schizophrenia – a widespread and well-documented thinning of the neocortex – is due to genetic risk (hence something that is closer to a primary cause) or – rather – if cortical thinning is not due to genetics, and so more of a secondary consequence of things that go wrong earlier in the development of the illness.

To explore this idea, the team of Goldman et al., did something novel.  Rather than examine the differences in cortical thickness between patients and control subjects, the team evaluated the cortical thickness of 59 patients and 72 unaffected siblings as well as 196 unrelated, matched control participants.  If the cortical thickness of the siblings (who share 50% of their genetic variation) was more similar to the patients, then it would suggest that the cortical thinning of the patients was under genetic control and hence – perhaps – a biological trait that is more of a primary cause.  On the other hand, if the cortical thickness of the siblings (who share 0% of their genetic variation) was more similar to that of the healthy control participants, then it would suggest that cortical thinning was – perhaps more of a secondary consequence of some earlier deficit.

The high-resolution structural neuroimaging allowed the team to carefully assess cortical thickness – which is normally between a mere 2 and 4 millimeters – across different areas of the cortex.  The team reports that, for the most part, the cortical thickness measures of the siblings were more similar to the unrelated controls – thus suggesting that cortical thickness may not be a direct component of the genetic risk architecture for schizophrenia.  Still, the paper discusses several candidate mechanisms which could lead to cortical thinning in the illness – some of which might be assessed in the future using other imaging modalities in the context of their patient/sibling/control experimental design.

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The neuregulin-1 (NRG1) gene is widely known as one of the most well-replicated genetic risk factors for schizophrenia.  Converging evidence shows that it is associated with schizophrenia at the gene expression and mouse model levels which are consistent with its molecular functions in neural development.   However, in several recent genome-wide association studies (GWAS), there appeared nary a blip of association at the 8p12 locus where NRG1 resides.  What gives?

While there are many possibilities for this phenomenon (some discussed here), the recent paper, “Support for NRG1 as a Susceptibility Factor for Schizophrenia in a Northern Swedish Isolated Population” by Maaike Alaerts and colleagues, suggest that the typical GWAS study may not adequately probe genetic variation at a fine enough scale – or, if you will, use a netting with sufficiently small holes.  By holes, I mean both the physical distance between genetic markers and the frequency with which they occur in populations.  While GWAS studies may use upwards of 500,000 markers – that’s a pretty fine scale net for a 3,000,000,000bp genome (about 6,000bp apart) – Alaerts and colleagues set forth with slightly finer-scale netting.  They focus on a 157kb region that is about 60kb upstream from the start of the NRG1 gene and construct a net consisting of 37 variants between the markers rs4268087 and rs17601950 (average spacing about 5kb).  They used the tagger program to select markers that account for all haplotypes whose frequency is higher than 1.5%.  Thus – even though there are still more than 500 possible snps in the region Alaerts and colleagues are exploring, they are using a slightly finer netting than a typical GWAS.

The results of their analysis (using GENEPOP) of 486 patients and 514 ethnically matched control participants from northern Sweden did reveal significant associations in an area slightly downstream (about 50kb closer to the start point of the NRG1 gene) than the location of the “previously often replicated variants”, suggesting that the region does confer some risk for schizophrenia, but, that diagnostic markers for such risk will be different for different populations.  More telling however are the very weak effects of the haplotypes that show significant association.  Those haplotypes with the most significance show meager differences in how often they are observed in patients vs. controls.  For example, one haplotype was observed in 5% of patients vs. 3% of controls. Others examples were, 11 vs. 9, 25 vs. 22 and 40% vs. 35% – revealing the very modest (krill sized) effects that single genetic variants can have in conferring risk toward mental illness.

However, there are potentially lots of krill in the genomic sea!

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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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pointer to: download Power Point presentation hosted on the HUGO website entitled, “From the human genome to human behaviour: how far have we travelled?” (both English and Russian text) – by Ian Craig and Nick Yankovsky, Education Council Human Genome Organisation.

Covers recent findings on MAOA and 5HTT several and others also covered here.

Congrats to Hsien on the new position!

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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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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!
mineshaft_comic

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1/365 [dazed & confused]
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pointer to: Daniel MacArthur and Neil Walker’s (@ Genetic Future bog) in-depth coverage of various critiques on the recent back-to-back-to-back Nature magazine trifecta (covered here) on GWAS results for schizophrenia.  Rough going for the global corsortia and a major f**king bummer for folks like myself who have been hoping that these vast studies would provide a solid basis for genome-based cognitive intervention strategies in the future.  Some of the discussion in the comments section points to the weakness in the diagnostic criteria, which is a topic also covered here recently.

Perhaps there is hope in the brain systems / imaging-based approaches that are taking off as genome technology spreads into cognitive and imaging science. Tough to scan 10’s of thousands of people however. Double F**K!

I guess DSM-based psychiatric genetics is just about dead for the time being.  The announcement of the soon to shutter deCODE Genetics and its 5-year stock price captures the failure of this endeavor.

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Its not often that Nature magazine publishes a triple-back-to-back-to-back, so take note if you’re interested in the genetics of mental illness. The 3 papers – [doi:10.1038/nature08185] involving 3,322 individuals with schizophrenia and 3,587 controls, [doi:10.1038/nature08186] 4,999 cases and 15,555 controls and [doi:10.1038/nature08192] 8,008 cases and 19,077 controls – are as massive and powerful as any genome-wide effort to-date.  The results?  Overall a common result showing linkage to the major histocompatibility complex or so-called ‘MHC genes’ located on chromosome 6.  What to these genes do? and what’s the relevence to mental illness?

Here’s a quickie immunology primer on the biological function of the major histocompatibility genes.  They encode proteins whose molecular function is display short peptides on the surface of aptly named antigen presenting cells in the immune system (think of your hand as an MHC protein holding onto an apple (the short peptide) and holding it out or presenting it to someone (an Helper T-Cell).  This act of “presentation” is done so that the Helper T-Cells can determine whether such peptides are “self” or “non-self”.  If such displayed peptides are non-self (such as a virus, endotoxin or bacterium), then the helper T-Cells will sound the alarm and initiate a T- or B-Cell based immune response aimed specifically at the offending invader.  The movies below show the MHC proteins in their place displaying antigen peptides on the cell surface for binding with a helper T-Cell.


So, what does this have to do with mental illness? Although there are other non-immunological genes interspersed among the MHC genes, there is good reason to begin to explore the role of external infection and early development.  The authors of one paper note that,  “Schizophrenia patients are more likely, compared to the general population, to have been born in the winter or the spring. Although infections such as influenza and measles have been proposed as a possible mechanism for this distortion, a clear association between infectious agents and schizophrenia has not been demonstrated.”

The more we know, the more we don’t know.  Hopefully more early environment data will be analyzed.

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RICHMOND, CANADA - FEBRUARY 12:  Simon Whitfie...
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While often the object of scorn from its capitalistic southern neighbor, the Canada Foundation for Innovation has just awarded Dr. David Kennedy a large research grant to deploy both neuroimaging and genetic markers in the development of personalised treatment for schizophrenia – through a program dubbed “neuroIMAGENE“.  Dr. Kennedy suggests that this technological strategy may actually save money in the long run by helping physicians select the proper medication and dosage.

Capitalistic scorn huh? This news comes as the U.S. healthcare flagship GE healthcare flushes its own personalized medicine effort all the while nary a Canadian bank requires bailout largesse.  Indeed.

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The basic helix-loop-helix transcription factor, neurogenin-1 is known to regulate neural development and neurite outgrowth.  As such, it makes for a particularly interesting point to begin to understand mental illness and its complex developmental origins.  The recent paper by Ho et al., “Basic helix–loop–helix transcription factor NEUROG1 and schizophrenia: Effects on illness susceptibility, MRI brain morphometry and cognitive abilities ” [doi: 10.1016/l.schres.2008.08.009] makes for a very interesting read since this gene resides in the midst of the chromosome 5q31 region – which has been a risk hotspot in a number of previous linkage studies – and – two snps in NEUROG1 (the C-allele of rs2344484 and the G-allele of rs8192558) have also been associated with the disorder.

The authors report that in a sample of 392 patients and 226 control subjects, the major alleles of rs2344484 and rs8192558 were more prevalent among patients.  Furthermore, some of the participants underwent structural MR brain imaging which allowed the research team to examine where in the brain such genetic risk might arise from.  Interestingly, the team found that both patients and control subjects who carried the C-allele of rs2344484 showed somewhat smaller volumes of grey matter.  For example, in Table 3 there were 145 CC,CT individuals with an average of 662 cubic centimeters of grey matter while the 28 participants with the TT genotype showed an average volume of 682 cu.cm.  This allele was also found to be associated with poorer cognitive abilities in these C-carrier participants.

As pointed out by the research team, NEUROG1 is expressed early in the development of the human brain and is implicated in the differentiation of cortical progenitor cells and of glutamatergic excitatory cells in deep layers of the cortex.  Thus, the role of variation in a transcription factor – a gene that regulates the expression of other genes – in the risk of schizophrenia can be very early and with very broadly effects on the neocortex.

How to treat such an early deficit? Would be interesting to discuss further.  My own 23andMe profile shows a CT heterozygote which places me within the higher risk, but more common genotypic pool.  Hmmm.  What to make of that?

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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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One of the mental functions many of us take for granted is memory – that is – until we’re at the grocery store.  If you’re like me, you dart out of the house confident that you don’t need a list since you’re just going to “pick up a few things” – only to return home and discover (hours later when you’re comfortably ensconced on the couch) that you forgot the ice cream.  Damn, why can’t I have a more efficient working memory system ?  What’s the matter with my lateral frontal cortex ?  Can I (should I) blame it on my genes ? What genes specifically ?

One group recently reported the use of the so-called BOLD-response (blood oxygen level dependent) as a means to sift through the human genome and identify genes that mediate the level of brain activity in the lateral frontal cortex that occur during a working memory task – somewhat akin to remembering a list of groceries.  Steven Potkin and associates in their paper, “Gene discovery through imaging-genetics: identification of two novel genes associated with schizophrenia” [doi: 10.1038/mp.2008.127] examine the level of brain activity in 28 patients with schizophrenia (a disorder where mental function in the lateral frontal cortex is disrupted) and correlate this brain activity (difference between short and long list) with genetic differences at 100,000 snps spread across the autosomes.

They identify 2 genes (that pass an additional series of statistical hurdles designed to weed-out false positive results) RSRC1 and ARHGAP18, heretofore, never having been connected to mental function.  Although neither protein is neuron or brain-specific in its expression, ARHGAP18 is a member of the Rho/Rac/Cdc42-like GTPase activating (RhoGAP) gene family which are well known regulators of the actin cytoskeleton (perhaps  a role in synaptic plasticity ?) and RSRC1 is reported to bind to actin homologs. Also, RSRC1 may play a role in forebrain development since it is expressed in cdc34+ stem cells that migrate under the control of TGF-alpha (As an aside, yours truly co-published a paper showing that TGF-alpha is regulated by early maternal care – possible connection ? Hmm).  A last possibility is a role in RNA splicing which many SR-proteins like RSRC1 function in – which also could be important for synaptic function as many mRNA’s are stored in synaptic terminals.

The authors’ method is completely novel and they seem to have discovered 2 new points from which to further explore the genetic basis of mental disability.  It will be of great interest to see where the research leads next.

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Karyogram of a human maleImage via Wikipedia Doctor David Ledbetter gives an eloquent editorial overview in his piece, “Cytogenetic Technology: Genotype and Phenotype” [doi: 10.1056/NEJMe0806570] on the renaissance underway in the field of medical cytogenetics. The use of high density arrays for genome-wide copy number variation has identified a slew of new sites showing recurrent microdeletion that are reliably found in patients with mental developmental disabilities (autism, mental retardation, schizophrenia to name a few). Ledbetter suggests that the ‘genotype first’ process of diagnosis is now much more effective with the help of the new arrays. He notes, “a pediatrician has the option of ordering this test as an adjunct to or replacement of a standard karyotype and can expect a much higher yield of clinically significant results”. This is an exciting realization of the long-awaited promise of genetics in medicine.

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