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Posts Tagged ‘Gene expression’

Mother Nature
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The current buzz about about GWAS  and longevity and GWAS in general has stirred up many longstanding inconvenient issues that arise when trying to interpret the results of very large, expensive and worthwhile genetic studies.  Its seems that Mother Nature does not give up her secrets without a fight.

One of the most common “inconvenient issues” is the fact that so many of the SNPs that come out of these studies are located far away from protein-encoding exons.  This ubiquitous observation is almost always followed with, “well, maybe its in linkage disequilibrium with a more functional SNP” or something along these lines – wherein the authors get an automatic pass.  OK by me.

Another “inconvenient issue” is the fact that many of these SNPs are of minimal effect and don’t exactly add up or interact to account for the expected heritability.  This problem of “missing heritability” is a big one (see some new insights in the latest issue of Nature Genetics) leading many to suspect that the effects of genes are dependent on complex interactions with each other and the environment.

A recent paper, “A map of open chromatin in human pancreatic islets” [doi:10.1038/ng.530] by Gaulton and colleagues caught my eye because it seems to shed light on both of these particular inconvenient issues.  The authors find that the diabetes risk variant rs7903146 in the TCF7L2 gene is both located in an intron and subject to epigenetic regulation (our sedentary, high-fat, high-stress lives can potentially interact with the genome by causing epigenetic change).

It appears that the T-allele of the intronic rs7903146 is correlated with a more open, transcription-prone form of DNA/chromatin than is the C-allele. The authors confirmed this using both chromatin mapping and gene expression assays on pancreatic islet cells harvested from non-diabetic donors and islet cell-lines.  The results suggest that the risk-conferring T-allele of this intronic SNP may be driving expression (gain-of-function) of the TCF7L2 gene.  What types of environmental stimuli might also impact the opening and closing of chromatin at this location?

This type of interplay of environment, genome and epigenome is probably rampant in the area of brain and behavior – so perhaps the study of diabetes will provide some clues to the many GWAS SNPs that are far away from exons. More on the genetics of epigenetics here.

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Nucleosome structure.
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pointer to the NOVA program on epigenetics “Ghost in Your Genes” (YouTube link here).  Fantastic footage.  Great intro to epigenetics and so-called trans-generational effects and the inheritance of epigenetic marks – which, in some cases – are left by adverse or stressful experience.  A weird, wild, game-changing concept indeed – that my grandchildren could inherit epigenetic changes induced in my genome by adverse experience.

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

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

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wotd044
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** PODCAST accompanies this post**

I have a little boy who loves to run and jump and scream and shout – a lot.  And by this, I mean running – at full speed and smashing his head into my gut,  jumping – off the couch onto my head,  screaming – spontaneous curses and R-rated body parts and bodily functions.  I hope you get the idea.  Is this normal? or (as I oft imagine) will I soon be sitting across the desk from a school psychologist pitching me the merits of an ADHD diagnosis and medication?

Of course, when it comes to behavior, there is not a distinct line one can cross from normal to abnormal.  Human behavior is complex, multi-dimensional and greatly interpreted through the lens of culture.  Our present culture is highly saturated by mass-marketing, making it easy to distort a person’s sense of “what’s normal” and create demand for consumer products that folks don’t really need (eg. psychiatric diagnoses? medications?).   Anyhow, its tough to know what’s normal.  This is an important issue to consider for those (mass-marketing hucksters?) who might be inclined to promote genetic data as “hard evidence” for illness, disorder or abnormality of some sort.

With this in mind, I really enjoyed a recent paper by Stollstorff et al., “Neural response to working memory load varies by dopamine transporter genotype in children” [doi:10.1016/j.neuroimage.2009.12.104] who asked how the brains of healthy children functioned, even though they carry a genotype that has been widely associated with the risk of ADHD.  Healthy children who carry genetic risk for ADHD. Hmm, might this be my boy?

The researchers looked at a 9- vs. 10-repeat VNTR polymorphism in the 3′-UTR of the dopamine transporter gene (DAT1).  This gene – which encodes the very protein that is targeted by so many ADHD medications – influences the re-uptake of dopamine from the synaptic cleft.  In the case of 10/10 genotypes, it seems that DAT1 is more highly expressed, thus leading to more re-uptake and hence less dopamine in the synaptic cleft.  Generally, dopamine is needed to enhance the signal/noise of neurotransmission, so – at the end of the day – the 10/10 genotype is considered less optimal than the 9/9-repeat genotype.  As noted by the researchers, the ADHD literature shows that the 10-repeat allele, not the 9-repeat, is most often associated with ADHD.

The research team asked these healthy children (typically developing children between 7 and 12 years of age) to perform a so-called N-back task which requires that children remember words that are presented to them one-at-a-time.  Each time a new word is presented, the children had to decide whether that word was the same as the previous word (1-back) or the previous, previous word (2-back).  Its a maddening task and places an extreme demand on neural circuits involved in active maintenance of information (frontal cortex) as well as inhibition of irrelevant information that occurs during updating (basal ganglia circuits).

As the DAT1 protein is widely expressed in the basal ganglia, the research team asked where in the brain was variation in the DAT1 (9- vs. 10-repeat) associated with neural activity?  and where was there a further difference between 1-back and 2-back?  Indeed, the team finds that brain activity in many regions of the basal ganglia (caudate, putamen, substantia nigra & subthalamic nucleus) were associated with genetic variation in DAT1.  Neat!  the gene may be exerting an influence on brain function (and behavior) in healthy children, even though they do not carry a diagnosis.  Certainly, genes are not destiny, even though they do influence brain and behavior.

What was cooler to me though, is the way the investigators examined the role of genetic variation in the 1-back (easy or low load condition) vs. 2-back (harder, high-load condition) tasks.  Their data shows that there was less of an effect of genotype on brain activation in the easy tasks.  Rather, only when the task was hard, did it become clear that the basal ganglia in the 10/10 carriers was lacking the necessary brain activation needed to perform the more difficult task.  Thus, the investigators reveal that the genetic risk may not be immediately apparent under conditions where heavy “loads” or demands are not placed on the brain.  Cognitive load matters when interpreting genetic data!

This result made me think that genes in the brain might be a lot like genes in muscles.  Individual differences in muscle strength are not associated with genotype when kids are lifting feathers.  Only when kids are actually training and using their muscles, might one start to see that some genetically advantaged kids have muscles that strengthen faster than others.  Does this mean there is a “weak muscle gene” – yes, perhaps.  But with the proper training regimen, children carrying such a “weak muscle gene” would be able to gain plenty of strength.

I guess its off to the mental and physical gyms for me and my son.

** PODCAST accompanies this post** also, here’s a link to the Vaidya lab!

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Diagram to illustrate Minute Structure of the ...
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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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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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Last year I dug a bit into the area of epigenetics (indexed here) and learned that the methylation (CH3) and acetylation (OCCH3) of genomic DNA & histones, respectively, can have dramatic effects on the structure of DNA and its accessibility to transcription factors – and hence – gene expression.  Many of the papers I covered suggested that the environment can influence the degree to which these so-called “epigenetic marks” are covalently bonded onto the genome during early development.  Thus, the thinking goes, the early environment can modulate gene expression in ways that are long-lasting – even transgenerational.  The idea is a powerful one to be sure.  And a scary one as well, as parents who read this literature, may fret that their children (and grandchildren) can be epigenetically scarred by early nutritional, physical and/or psycho-social stress.  I must admit that, as a parent of young children myself, I began to wonder if I might be negatively influencing the epigenome of my children.

I’m wondering how much physical and/or social stress is enough to cause changes in the epigenome?  Does the concern about epigenetics only apply to exposure to severe stress?  or run of the mill forms of stress?  How much do we know about this?

This year, I hope to explore this line of inquiry further.  For starters, I came across a fantastic paper by Fraga et al., entitled, “Epigenetic differences arise during the lifetime of monozygotic twins” [doi:10.1073/pnas.0500398102].   The group carries out a remarkably straightforward and time honored approach – a twin study – to ask how much identical twins differ at the epigenetic level.  Since identical twins have the same genome sequence, any differences in their physiology, behavior etc. are, strictly speaking, due to the way in which the environment (from the uterus to adulthood) shapes their development.  Hence, the team of Fraga et al., can compare the amount and location of methyl (CH3) and acetyl (OCCH3) groups to see whether the environment has differentially shaped the epigenome.

An analysis of some 40 identical twin pairs from ages 3-74 years old showed that – YES – the environment, over time, does seem to shape the epigenome (in this case of lymphocytes).  The most compelling evidence for me was seen in Figure 4 where the team used a method known as Restriction Landmark Genomic Scanning (RLGS) to compare patterns of methylation in a genome-wide manner.  Using this analysis, the team found that older twin pairs had about 2.5 times as many differences as did the epigenomes of the youngest twin pairs.  These methylation differences also correlated with gene expression differences (older pairs also had more gene expression differences) and they found that the individual who showed the lowest levels of methylation also had the highest levels of gene expression.  Furthermore, the team finds that twin pairs who lived apart and had more differences in life history were more likely to have epigenetic differences.  Finally, measures of histone acetylation seemed consistent with the gradient of epigenetic change over time and life-history distance.

Thus it seems that, as everyday life progresses, the epigenome changes too.  So, perhaps, one does not need extreme forms of stress to leave long-lasting epigenetic marks on the genome?  Is this true during early life (where the team did not see many differences between pairs)?  and in the brain (the team focused mainly on lymphocytes)?  Are the differences between twins due to the creation of new environmentally-mediated marks or the faulty passage of existing marks from dividing cell-to-cell over time?  Will be fun to seek out information on this.

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