A big money political circus with $500 million spent on lobbying in 2010 alone!  Can a wave of new personal informatic and genomic tools take root and grow amidst a corporate money-fueled politicized regulatory environment?  I hope so, but the paradigm shift to personalized-genomic-medicine definitely stirs up some thorny conflicts between our individual rights of freedom, privacy and access to healthcare vs. the profit models of corporations vs. government policy.

The info graphic is here at Many Eyes.  Here is a related post on possible innovation-crushing regulation and below is a video summary of how “We the People” lost control of our democratic process.

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… from the debunking analysis:

The key comparison here comes from the two extremes: 2 alleles vs. 0. People with 2 alleles are 4 percentage points (more precisely, 3.6 percentage points) more likely to report themselves as very satisfied with their lives. The standard error of this difference in proportions is sqrt(.41*(1-.41)/862+.37*(1-.37)/509) = 0.027, so the difference is not statistically significant at a conventional level.

more on this totally over-hyped gene here.

So, what happens if I publish my genome sequence online … does anyone else get a benefit? or incur a cost?  My children?  My siblings?  What if I were an identical twin?

Do twins favor being more similar? … in which case, maybe, they might see positive externalities?

Are the epigenomes of identical twins similar?

How does your genome influence your economic behavior?

Reading the book makes me feel liberated from the medical labels that are all too readily slapped on healthy people.  There is much that is healthy about sadness and many reasons and contexts in which its quite natural.  From now on, instead of trying to escape from, or rid myself of sadness, I will embrace it and let myself feel it and work through it.  Who knows, maybe this is a good first step in a healthy coping process.

If depressed emotional states are more a part of the normal range of emotions (rather than separate disordered states) then does this allow us to make predictions about the underlying genetic bases for these states?    Perhaps not.   However, on page 172, the authors apply their critical view to the highly cited Caspi et al., article (showing that 5HTT genotype interacts with life stress in the presentation of depressive illness – critiqued here).  They note that the incidence of depression at 17% in the sample is much too high – most certainly capturing a lot of normal sadness.  Hence, the prevalent short allele in the 5HTT promoter might be better thought of as a factor that underlies how healthy people respond to social stress – rather than as a drug target or risk factor for psychiatric illness.

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.

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).

In their forecast “The World in 2010” special issue, the Economist points to “The looming crisis in human genetics” wherein scientists will reluctantly acknowledge that, even with super-cheap genome sequencing tools, we may not soon understand how genetic variation contributes to complex illness.  The argument is a valid one to be sure, but only time will tell.

A paper I read recently, reminded me of the long hard slog ahead in the area of genomics and psychiatric illness.  The authors in “Association of the Glutamate Transporter Gene SLC1A1 With Atypical Antipsychotics–Induced Obsessive-compulsive Symptoms” [Kwon et al., (2009) Arch Gen Psychiatry 66(11)] are trying to do something very important.  They would like to understand why certain (most) psychiatric medications have adverse side-effects and how to steer patients clear of adverse side-effects.  This is because, nowadays, a patient learns via a drawn-out trial-and-error ordeal about which medications he/she can manage the benefits/costs.

Specifically, the authors focused their efforts on so-called obsessive-compulsive symptoms that can arise from treatment with atypical antipsychotic medications.  Working from 3 major medical centers (Samsung Medical Center, Seoul National University Hospital and Asan Medical Center) Kwon et al., were able to cobble together a mere 40 patients who display these particular adverse side-effects and matched them with 54 patients based on several demographic and medication-based criteria.  Keep in mind that most genetic studies use upwards of 1,000 samples and still – hardly – are able to obtain significant effects.

Nevertheless, the authors note that the glutamate transporter gene (SLC1A1 or EAAC1) is a most logical candidate gene, being a located in a region mapped for obsessive-compulsive disorder risk and also a gene that appears to be down-regulated in response to atypical anti-psychotic treatment (particularly clozapine).  A series of statistical association tests for 10 SNPs in this gene reveal that two SNPs (rs2228622 and rs3780412) and a 3-SNP haplotype (the A/C/G haplotype at rs2228622-rs3780413-rs3780412) showed modestly significant association (about 4-fold higher risk) with the adverse symptoms.

To me, this is a very noteworthy finding.  A lot of work went into a very important problem – perhaps THE most pressing problem for patients on anti-psychotic medications today – and the results, while only of modest significance, are probably biologically valid.  The authors point out that rs2228622 and rs3780412 have previously been associated with OCD in other studies.

But when you compare these modest results (that these authors fought hard to obtain) with the big promises of the genomic era (as noted in the Economist article), well then, the results seem rather diminutive.  Will all patients who carry the risk haplotype be steered away from atypical antipsychotics?  Will big pharma (the authors of this paper disclose a great many ties to big pharma) support the fragmentation of their blockbuster drug markets into a hundred sub-populations?  I doubt it.  But some doctors and patients will experiment and continue to explore this avenue of inquiry – and it will take a long time to work out.  Better check back in 2020.

pointer to: The Neurocritic’s coverage on the association of low-efficiency alleles of MAOA and credit card debt.  Will there be a genotype box to check on future credit card applications? More posts on MAOA here.