Just a few excerpts from a lecture by the renown social psychologist Paul Ekman who is known for his work on the biology of human emotion.  Here he relates conceptual bridges between the writings of Charles Darwin and HH The Dalai Lama.  Ekman notes that both Darwin and HH The Dalai Lama intuit the existence of an organic natural source of compassion wherein humans are compelled to relieve the suffering of others so that the discomfort we feel when seeing others in pain can be relieved.  HH The Dalai Lama further suggests that these emotions are spontaneous, but compassion can be enhanced through PRACTICE!

Seems that science and ancient traditions can have a fascinating way of re-informing each other.

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.

It sounds simple on paper – just collect lots of folks with disorder X and look at their genomes in reference to a demographically matched healthy control population.  Voila! whatever is different is a candidate for genetic risk.  Apparently, not so.

The missing heritability problem that clouds the birth of the personal genomes era refers to the baffling inability to find enough common genetic variants that can account for the genetic risk of an illness or disorder.

There are any number of reasons for this … (i) even as any given MZ and DZ twin pair shares genetic variants that predispose them toward the similar brains and mental states, it may be the case that different MZ and DZ pairs have different types of rare genetic variation thus diluting out any similar patterns of variation when large pools of cases and controls are compared …  (ii) also, the way that the environment interacts with common risk-promoting genetic variation may be quite different from person to person – making it hard to find variation that is similarly risk-promoting in large pools of cases and controls … and many others I’m sure.

One research group recently asked whether the type of common genetic variation(SNP vs. CNV) might inform the search for the missing heritability.  The authors of the recent paper, “Genome-wide association study of CNVs in 16,000 cases of eight common diseases and 3,000 shared controls” [doi:10.1038/nature08979] looked at an alternative to the usual SNP markers – so called common copy number variants (CNVs) – and asked if these markers might provide a stronger accounting for genetic risk.  While a number of previous papers in the mental health field have indeed shown associations with CNVs, this massive study (some 3,432 CNV probes in 2000 or so cases and 3000 controls) did not reveal an association with bipolar disorder.  Furthermore, the team reports that common CNV variants are already in fairly strong linkage disequilibrium with common SNPs and so perhaps may not have reached any farther into the abyss of rare genetic variation than previous GWAS studies.

Disappointing perhaps, but a big step forward nonetheless!  What will the personal genomes era look like if we all have different forms of rare genetic variation?

If you’ve started to notice the arrival of spring blossoms, you may have wondered, “how do the blossoms know when its spring?“  Well, it turns out that its not the temperature, but rather, that plants sense the length of the day-light cycle in order to synchronize their  own life cycles with the seasons.  According to the photoperiodism entry for wikipedia, “Many flowering plants use a photoreceptor protein, such as phytochrome or cryptochrome, to sense seasonal changes in night length, or photoperiod, which they take as signals to flower.”

It turns out that humans are much the same. Say wha?!

Yep, as the long ago descendants of single cells who had to eek out a living during day (when the sun emits mutagenic UV radiation) and night cycles, our very own basic molecular machinery that regulates the transcription, translation, replication and a host of other cellular functions is remarkably sensitive – entrained – in a clock-like fashion to the rising and setting sun.  This is because, in our retinas, there are light-sensing cells that send signals to the suprachiasmatic nucleus (SCN) which then – via the pineal gland – secretes systemic hormones such as melatonin that help synchronize cells and organs in your brain and body.  When this process is disrupted, folks can feel downright lousy, as seen in seasonal affective disorder (SAD), delayed sleep phase syndrome (DSPS) and other circadian rhythm disorders.

If you’re skeptical, consider the effects of genetic variation in genes that regulate our circadian rhythms, often called “clock” genes – very ancient genes that keep our cellular clocks synchronized with each other and the outside environment.  Soria et al., have a great paper entitled, “Differential Association of Circadian Genes with Mood Disorders: CRY1 and NPAS2 are Associated with Unipolar Major Depression and CLOCK and VIP with Bipolar Disorder” [doi: 10.1038/npp.2009.230] wherein they reveal that normal variation in these clock genes is associated with mood regulation.

A few of the highlights reported are rs2287161 in the CRY1 gene,  rs11123857 in the NPAS2 gene, and rs885861 in the VIPR2 gene – where the C-allele, G-allele and C-allele, respectively, were associated with mood disorders.

I’m not sure how one would best interpret genetic variation of such circadian rhythm genes.  Perhaps they index how much a person’s mood could be influenced by changes or disruptions to the normal rhythm??  Not sure.  My 23andMe data shows the non-risk AA genotype for rs11123857 (the others are not covered by 23andMe).

Coping with fear and anxiety is difficult.  At times when one’s life, livelihood or loved one’s are threatened, we naturally hightenen our senses and allocate our emotional and physical resources for conflict.  At times, when all is well, and resources, relationships and relaxation time are plentiful, we should unwind and and enjoy the moment.  But most of us don’t.  Our prized cognitive abilities to remember, relive and ruminate on the bad stuff out there are just too well developed – and we suffer – some more than others  (see Robert Saplosky’s book “Why Zebras Don’t Get Ulcers” and related video lecture (hint – they don’t get ulcers because they don’t have the cognitive ability to ruminate on past events).  Such may be the flip side to our (homo sapiens) super-duper cognitive abilities.

Nevertheless, we try to understand our fears and axieties and understand their bio-social-psychological bases. A recent paper entitled, “A Genetically Informed Study of the Association Between Childhood Separation Anxiety, Sensitivity to CO2, Panic Disorder, and the Effect of Childhood Parental Loss” by Battaglia et al. [Arch Gen Psychiatry. 2009;66(1):64-71] brought to mind many of the complexities in beginning to understand the way in which some individuals come to suffer more emotional anguish than others.  The research team addressed a set of emotional difficulties that have been categorized by psychiatrists as “panic disorder” and involving sudden attacks of fear, sweating, racing heart, shortness of breath, etc. which can begin to occur in early adulthood.

Right off the bat, it seems that one of the difficulties in understanding such an emotional state(s) are the conventions (important for $$ billing purposes) used to describe the relationship between “healthy” and “illness” or “disorder”.  I mean, honestly, who hasn’t experienced what could be described as a mild panic disorder once or twice?  I have, but perhaps that doesn’t amount to a disorder.  A good read on the conflation of normal stress responses and disordered mental states is “Transforming Normality into Pathology: The DSM and the Outcomes of Stressful Social Arrangements” by Allan V. Horwitz.

Another difficulty in understanding how and why someone might experience such a condition has to do with the complexities of their childhood experience (not to mention genes). Child development and mental health are inextrictably related, yet, the relationship is hard to understand.  Certainly, the function of the adult brain is the product of countless developmental unfoldings that build upon one another, and certainly there is ample evidence that when healthy development is disrupted in a social or physical way, the consequences can be very unfortunate and long-lasting. Yet, our ability to make sense of how and why an individual is having mental and/or emotional difficulty is limited.  Its a complex, interactive and emergent set of processes.

What I liked about the Battaglia et al., article was the way in which they acknowledged all of these complexities and – using a multivariate twin study design – tried to objectively measure the effects of genes and environment (early and late) as well as candidate biological pathways (sensitivity to carbon dioxide).  The team gathered 346 twin pairs (equal mix of MZ and DZ) and assessed aspects of early and late emotional life as well as the sensitivity to the inhalation of 35% CO2 (kind of feels like suffocating and is known to activate fear circuitry perhaps via the ASC1a gene).   The basic notion was to parcel out the correlations between early emotional distress and adult emotional distress as well as with a very specific physiological response (fear illicited by breathing CO2).  If there were no correlation or covariation between early and late distress (or the physiological response) then perhaps these processes are not underlain by any common mechanism.

However, the team found that there was covariation between early life emotion (criteria for separation anxiety disorder) and adult emotion (panic disorder) as well as the physiological/fear response illicited by CO2.  Indeed there seems to be a common, or continuous, set of processes whose disruption early in development can manifest as emotional difficulty later in development.  Furthermore, the team suggests that the underlying unifying or core process is heavily regulated by a set of additive genetic factors.  Lastly, the team finds that the experience of parental loss in childhood increased (but not via an interaction with genetic variation) the strength of the covariation between early emotion, late emotion and CO2 reactivity.  The authors note several limitations and cautions to over-interpreting these data – which are from the largest such study of its kind to date.

For individuals who are tangled in persistent ruminations and emotional difficulties, I don’t know if these findings help.  They seem to bear out some of the cold, cruel logic of life and evolution – that our fear systems are great at keeping us alive when we’ve had adverse experience in childhood, but not necessarily happy.  On the other hand, the covariation is weak, so there is no such destiny in life, even when dealt unfortunate early experience AND genetic risk.  I hope that learning about the science might help folks cope with such cases of emotional distress.

DON’T tell the grant funding agencies

Let’s say we ask a population of folks to perform a task – perhaps a word memory task – and then we use neuroimaging to identify the areas of the brain that (i) were associated with performance of the task, and (ii) were not only associated with performance, but were also associated with genetic variation in the population.  Indeed, there are already examples of just this type of “imaging-genetic” study in the literature.  Such studies form a crucial translational link in understanding how genes (whose biochemical functions are most often studied in animal models) relate to human brain function (usually studied with cognitive psychology). However, do these genes relate to just this task? What if subjects were recalling objects? or feelings?  What if subjects were recalling objects / experiences / feelings / etc. from their childhoods?  Of course, there are thousands of common cognitive operations one’s brain routinely performs, and, hence, thousands of experimental paradigms that could be used in such “imaging-genetic” gene association studies.  At more than $500/hour (some paradigms last up to 2 hours) in imaging costs, the translational genes-to-cognition endeavor could get expensive!

DO tell the grant funding agencies that this may not be a problem any longer.

The recent paper by Liu and colleagues “Prefrontal-Related Functional Connectivities within the Default Network Are Modulated by COMT val158met in Healthy Young Adults” [doi: 10.1523/jneurosci.3941-09.2010] suggests an approach that may simplify matters.  Their approach still involves genotyping (in this case for rs4680) and neuroimaging.  However, instead of performing a specific cognitive task, the team asks subjects to lay in the scanner – and do nothing.  That’s right – nothing – just lay still with eyes closed and just let the mind wander and not to think about anything in particular – for a mere 10 minutes.  Hunh?  What the heck can you learn from that?

It turns out that one can learn a lot.  This is because the neural pathways that the brain uses when you are actively doing something (a word recall task) are largely intact even when you are doing nothing.  Your brain does not “turn off” when you are laying still with your eyes closed and drifting in thought.  Rather, your brain slips into a kind of default pattern, described in studies of  “default networks” or “resting-state networks” where wide-ranging brain circuits remain dynamically coupled and actively exchange neural information.  One really great paper that describes these networks is a free-and-open article by Hagmann et al., “Mapping the Structural Core of Human Cerebral Cortex” [doi: 10.1371/journal.pbio.0060159] from which I’ve lifted their Figure 1 above.  The work by Hagmann et al., and others show that the brain has a sort of “connectome” where there are thousands of “connector hubs” or nodes that remain actively coupled (meaning that if one node fires, the other node will fire in a synchronized way) when the brain is at rest and when the brain is actively performing cognitive operations.  In a few studies, it seems that the strength of functional coupling in certain brain areas at rest is correlated (positively and negatively) with the activation of these areas when subjects are performing a specific task.

In the genetic study reported by Liu and colleagues, they found that genotype (N=57) at the dopaminergic COMT gene correlated with differences in the functional connectivity (synchronization of firing) of nodes in the prefrontal cortex.  This result is eerily similar to results found for a number of specific tasks (N-back, Wisconsin Card Sorting, Gambling, etc.) where COMT genotype was correlated with the differential activation of the frontal cortex during the task.  So it seems that one imaging paradigm (lay still and rest for 10 minutes) provided comparable insights to several lengthy (and diverse) activation tasks.  Perhaps this is the case. If so, might it provide a more direct route to linking genetic variation with cognitive function?

Liu and colleagues do not comment on this proposition directly nor do they seem to be over-interpreting their results in they way I have editorialized things here.  They very thoughtfully point out the ways in which the networks they’ve identified and similar and different to the published findings of others.  Certainly, this study and the other one like it are the first in what might be a promising new direction!

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.

A recent GWAS study identified the 3′ region of the liver- (not brain) expressed PECR gene (rs7590720(G) and rs1344694(T)) on chromosome 2 as a risk factor for alcohol dependency.  These results, as reported by Treutlein et al., in “Genome-wide Association Study of Alcohol Dependence” were based on a population of 487 male inpatients and a follow-up re-test in a population of 1024 male inpatients and 996 control participants.

The authors also asked whether lab rats who – given the choice between water-based and ethanol-spiked beverages over the course of 1 year – showed differential gene expression in those rats that were alcohol preferrers vs. alcohol non-preferring rats.  Among a total of 542 genes that were found to be differentially expressed in the amygdala and caudate nucleus of alcohol vs. non-alcohol-preferring rat strains,  a mere 3 genes – that is the human orthologs of these 3 genes – did also show significant association with alcohol dependency in the human populations.  Here are the “rat genes” (ie. human homologs that show differential expression in rats and association with alcohol dependency in humans): rs1614972(C) in the alcohol dehydrogenase 1C (ADH1C) gene, rs13273672(C) in the GATA binding protein 4 (GATA4) gene, and rs11640875(A) in the cadherin 13 (CDH13) gene.

My 23andMe profile gives a mixed AG at rs7590720, and a mixed GT at rs1344694 while I show a mixed CT at rs1614972, CT at rs13273672 and AG at rs11640875.  Boooring! a middling heterozygote at all 5 alcohol prefer/dependency loci.   Were these the loci for chocolate prefer/dependency I would be a full risk-bearing homozygote.

It was a great pleasure to speak with Professor Garet Lahvis from the Department of Behavioral Neuroscience at the Oregon Health and Science University, and learn more about how the biology of empathy and social behaviors in general can be approached with animal models that are suitable for genetic studies.  The podcast is HERE and the post on his lab’s recent paper, “Empathy Is Moderated by Genetic Background in Mice” is HERE.  Thank you again Dr. Lahvis!

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

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

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

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

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