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Posts Tagged ‘23andMe’

meme23andmedudeohyeahmeme

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American Omic

funkyamericangothic

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legarement

The “T” allele of rs1378810 in your DNAJC13 gene has been associated with a slight benefit (less than 0.4% variance) in general cognitive ability. You can check your 23andMe profile.*  What? You’re a TT? Ooooh … nobody is impressed. But let’s not make light of our DNAJ genes just yet.

Consider the critical role of DNAJC5, a so-called cysteine-string protein (because it encodes a protein with an array of cysteine residues). This protein helps synaptic vesicles fuse and un-fuse so that your neurons can release and re-cycle tiny packets of neurotransmitters – which is how neurons send signals to one another. Yeah, vesicle fusion is really important … and is happening like a quadriillion times right now in your brain.

Mutations in the cysteine string of DNAJC5 have been associated with Huntington’s disease.

[artwork credit]

*Interpreting 23andMe data here can be confusing because 23andMe lists an A or T as possible alleles but one isn’t always sure which strand the research literature refers to and if that strand is the same strand that 23andMe is reading from. Luckily SNPedia points out that an rs1378810 TT is in tight linkage disequilibrium with rs2133692 TT (T or C alleles) so you can check this genotype on 23andMe to infer your rs1378810 genotype. My 23andMe profile says AA at rs1378810 and TT at rs2133692, so I think I have the slightly beneficial TT genotype … but I’m really not sure. Confused? Me too. But like the research suggests, this genotype really doesn’t add much to one’s general cognitive ability.

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Colm O’Dushlaine rocked his 23andMe profile … hard! … and then shared it with the world.

Totally. Awesome.

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Check out the Interpretome! developed by students and staff at Stanford University.

- I have 17 European alleles and 3 East Asian alleles … the genetic proof is in … white boys can’t jump.
– I have 17 out of 32 Type 2 Diabetes risk alleles … put down those carbs now … and 19 out of 30 Coronary Artery Disease risk alleles … and go for a jog.
– I have a combined Risk of Narcolepsy: 2.92 … but the score jumps to 85 with an issue of GENETICS in my hand.
- I’m not exactly on the leading edge of human evolution … a 72/110 of positive selection score.
- I’d better start saving for a long-ass retirement … probability of extreme longevity: 78.2

More on the interpretome here, here and here!

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Wobble base pair guanine uracil (GU)

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Hands shake and wobble as the decades pass … moreso in some.

A recently evolved “T” allele (rs12720208) in the  3′ untranslated region (3′ UTR) of the FGF20 gene has been implicated in the risk of Parkinson’s Disease … namely by creating a wobbly G:U base-pair between microRNA-433 (miR-433) and the FGF20 transcript.  Since the normal function of microRNA-433 is to repress translation of proteins (such as FGF20), it is suspected that the PD risk “T” allele carriers make relatively more FGF20 … which, in turn … leads to the production of higher levels of alpha-synuclein (the main component of Lewy body fibrils, a pathological marker of diseases such as PD).  This newly evolved T-allele has also been associated with brain structural differences in healthy individuals.

My hands will shake and wobble as the decades pass … but not because I carry the G:U wobble pairing between miR-433:FGF20.  My 23andMe profile shows that I carry 2 C alleles and will produce the thermodynamically favorable G:C pairing.  Something to keep in mind as I lose my mind in the decades to come.

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“Listen Eric, you should think about how useful your newfangled Personal Genome is going to be.  There are a lot of reasons why all this information doesn’t tell you much”

“For example, have you thought about epigenetic effects that might be environmentally induced and can be transmitted across multiple subsequent generations?  Genotypes of individuals in previous generations might even be a better predictor of phenotype than an individual’s own genotype.”

“I know that Copy-Number Polymorphic (CNP) duplications are highly variable among individual and are considered inaccessible by most existing genotyping and sequencing technologies, but I’m still getting my genome sequenced anyway.”

“Can you please help Eric understand that rare variants and large variants (deletions, duplications and inversions) are individually rare, but collectively common in the human population might account for much more of heritability than common variation.  Nothing is known about these rare variants!”

“Yeah, Eric doesn’t realize that a very large number of closely linked genes can exhibit context-dependent and non-additive effects.”

“Gene by environment innnterraaaaactiiooon … coooool.”

–real science here.

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Crocus (cropped)
Image by noahg. via Flickr

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).

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An historic find has occurred in the quest (gold-rush, if you will) to link genome variation with brain structure-function variation.  This is the publication of the very first genome-wide (GWAS) analysis of individual voxels (voxels are akin to pixels in a photograph, but are rather 3D cubes of brain-image-space about 1mm on each side) of brain structure – Voxelwise genome-wide association study (vGWAS) [doi: 10.1016/j.neuroimage.2010.02.032] by Jason Stein and colleagues under the leadership of Paul M. Thompson, a  leader in the area of neuroimaging and genetics – well-known for his work on brain structure in twin and psychiatric patient populations.

In an effort to discover genes that contribute to individual differences in brain structure, the authors took on the task of statistically analyzing the some 31,622 voxels (per brain) obtained from high-resolution structural brain scans; with 448,293 Illumina SNP genotypes (per person) with minor allele frequencies greater than 0.1 (common variants); in 740 unrelated healthy caucasian adults.  When performed on a voxel-by-voxel basis, this amounts to some 14 billion statistical tests.

Yikes!  A statistical nightmare with plenty of room for false positive results, not to mention the recent disillusionment with the common-variant GWAS approach?  Certainly.  The authors describe these pitfalls and other scenarios wherein false data is likely to arise and most of the paper addresses the pros and cons of different statistical analysis strategies – some which are prohibitive in their computational demands.  Undaunted, the authors describe several approaches for establishing appropriate thresholds and then utilize a ‘winner take all’ analysis strategy wherein a single ‘most-associated winning snp’ is identified for each voxel, which when clustered together in hot spots (at P = 2 x 10e-10), can point to specific brain areas of interest.

Using this analytical approach, the authors report that 8,212 snps were identified as ‘winning, most-associated’ snps across the 31,622 voxels.  They note that there was not as much symmetry with respect to winning snps in the left hemispere and corresponding areas in the right hemisphere, as one might have expected.  The 2 most significant snps across the entire brain and genome were rs2132683 and rs713155 which were associated with white matter near the left posterior lateral ventricle.  Other notable findings were rs2429582 in the synaptic (and possible autism risk factor) CADPS2 gene which was associated with temporal lobe structure and rs9990343 which sits in an intergenic region but is associated with frontal lobe structure.  These and several other notable snps are reported and brain maps are provided that show where in the brain each snp is associated.

As in most genome-wide studies, one can imagine that the authors were initially bewildered by their unexpected findings.  None of the ‘usual suspects’ such as neurotransmitter receptors, transcription factors, etc. etc. that dominate the psychiatric genetics literature.  Bewildered, perhaps, but maybe thats part of the fun and excitement of discovery!  Very exciting stuff to come I’ll bet as this new era unfolds!

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According to wikipedia, “Jean Philippe Arthur Dubuffet (July 31, 1901 – May 12, 1985) was one of the most famous French painters and sculptors of the second half of the 20th century.”  “He coined the term Art Brut (meaning “raw art,” often times referred to as ‘outsider art’) for art produced by non-professionals working outside aesthetic norms, such as art by psychiatric patients, prisoners, and children.”  From this interest, he amassed the Collection de l’Art Brut, a sizable collection of artwork, of which more than half, was painted by artists with schizophrenia.  One such painting that typifies this style is shown here, entitled, General view of the island Neveranger (1911) by Adolf Wolfe, a psychiatric patient.

Obviously, Wolfe was a gifted artist, despite whatever psychiatric diagnosis was suggested at the time.  Nevertheless, clinical psychiatrists might be quick to point out that such work reflects the presence of an underlying thought disorder (loss of abstraction ability, tangentiality, loose associations, derailment, thought blocking, overinclusive thinking, etc., etc.) – despite the undeniable aesthetic beauty in the work.  As an ardent fan of such art,  it made me wonder just how “well ordered” my own thoughts might be.  Given to being rather forgetful and distractable, I suspect my thinking process is just sufficiently well ordered to perform the routine tasks of day-to-day living, but perhaps not a whole lot more so.  Is this bad or good?  Who knows.

However, Krug et al., in their recent paper, “The effect of Neuregulin 1 on neural correlates of episodic memory encoding and retrieval” [doi:10.1016/j.neuroimage.2009.12.062] do note that the brains of unaffected relatives of persons with mental illness show subtle differences in various patterns of activation.  It seems that when individuals are using their brains to encode information for memory storage, unaffected relatives show greater activation in areas of the frontal cortex compared to unrelated subjects.  This so-called encoding process during episodic memory is very important for a healthy memory system and its dysfunction is correlated with thought disorders and other aspects of cognitive dysfunction.  Krug et al., proceed to explore this encoding process further and ask if a well-known schizophrenia risk variant (rs35753505 C vs. T) in the neuregulin-1 gene might underlie this phenomenon.  To do this, they asked 34 TT, 32 TC and 28 CC individuals to perform a memory (of faces) game whilst laying in an MRI scanner.

The team reports that there were indeed differences in brain activity during both the encoding (storage) and retrieval (recall) portions of the task – that were both correlated with genotype – and also in which the CC risk genotype was correlated with more (hyper-) activation.  Some of the brain areas that were hyperactivated during encoding and associated with CC genotype were the left middle frontal gyrus (BA 9), the bilateral fusiform gyrus and the left middle occipital gyrus (BA 19).  The left middle occipital gyrus showed gene associated-hyperactivation during recall.  So it seems, that healthy individuals can carry risk for mental illness and that their brains may actually function slightly differently.

As an ardent fan of Art Brut, I confess I hoped I would carry the CC genotype, but alas, my 23andme profile shows a boring TT genotype.  No wonder my artwork sucks.  More on NRG1 here.

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Recreated :File:Neuron-no labels2.png in Inksc...
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The A-to-T SNP rs7794745 in the CNTNAP2 gene was found to be associated with increased risk of autism (see Arking et al., 2008).  Specifically, the TT genotype, found in about 15% of individuals, increases these folks’ risk by about 1.2-1.7-fold.  Sure enough, when I checked my 23andMe profile, I found that I’m one of these TT risk-bearing individuals.  Interesting, although not alarming since me and my kids are beyond the age where one typically worries about autism.  Still, one can wonder if such a risk factor might have exerted some influence on the development of my brain?

The recent paper by Tan et al., “Normal variation in fronto-occipital circuitry and cerebellar structure with an autism-associated polymorphism of CNTNAP2” [doi:10.1016/j.neuroimage.2010.02.018 ] suggests there may be subtle, but still profound influences of the TT genotype on brain development in healthy individuals.  According to the authors, “homozygotes for the risk allele showed significant reductions in grey and white matter volume and fractional anisotropy in several regions that have already been implicated in ASD, including the cerebellum, fusiform gyrus, occipital and frontal cortices. Male homozygotes for the risk alleles showed greater reductions in grey matter in the right frontal pole and in FA in the right rostral fronto-occipital fasciculus compared to their female counterparts who showed greater reductions in FA of the anterior thalamic radiation.”

The FA (fractional anisotropy – a measurement of white-matter or myelination) results are consistent with a role of CNTNAP2 in the establishment of synaptic contacts and other cell-cell contacts especially at Nodes of Ranvier – which are critical for proper function of white-matter tracts that support rapid, long-range neural transmission.  Indeed, more severe mutations in CNTNAP2  have been associated with cortical dysplasia and focal epilepsy (Strauss et al., 2006).

Subtle changes perhaps influencing long-range information flow in my brain – wow!

More on CNTNAP2 … its evolutionary history and role in language development.

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If you’re a coffee drinker, you may have noticed the new super-sized portions available at Starbucks.  On this note, it may be worth noting that caffeine is a potent psychoactive substance of which – too much – can turn your buzz into a full-blown panic disorder.  The Diagnostic and Statistical Manual for psychiatry outlines a number of caffeine-related conditions mostly involving anxieties that can arise when the natural alertness-promoting effects are pushed to extremes.  Some researchers have begun to explore the way the genome interacts with caffeine and it is likely that many genetic markers will surface to explain some of the individual differences in caffeine tolerance.

Here’s a great paper, “Association between ADORA2A and DRD2 Polymorphisms and Caffeine-Induced Anxiety” [doi: 10.1038/npp.2008.17] wherein polymorphisms in the adenosine A2A receptor (ADORA2A encodes the protein that caffeine binds to and antagonizes) – as well as the dopamine D2 receptor (DRD2 encodes a protein whose downstream signals are normally counteracted by A2A receptors) — show associations with anxiety after the consumption of 150mg of caffeine (about an average cup of coffee – much less than the super-size, super-rich cups that Starbucks sells).  The variants, rs5751876 (T-allele), rs2298383 (T-allele) and rs4822492 (G-allele) from the ADORA2A gene as well as rs1110976 (-/G genotype) from the DRD2 gene showed significant increases in anxiety in a test population of 102 otherwise-healthy light-moderate regular coffee drinkers.

My own 23andMe data only provides a drop of information suggesting I’m protected from the anxiety-promoting effects.  Nevertheless, I’ll avoid the super-sizes.
rs5751876 (T-allele)  C/C – less anxiety
rs2298383 (T-allele) – not covered
rs4822492 (G-allele) – not covered
rs1110976 (-/G genotype) – not covered

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silver copy of a 1930 penny
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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.

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Where da rodents kick it
Image by Scrunchleface via Flickr

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.

 

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This year, my 5 year-old son and I have passed many afternoons sitting on the living room rug learning to read.  While he ever so gradually learns to decode words, eg. “C-A-T”  sound by sound, letter by letter – I can’t help but marvel at the human brain and wonder what is going on inside.  In case you have forgotten, learning to read is hard – damn hard.  The act of linking sounds with letters and grouping letters into words and then words into meanings requires a lot of effort from the child  (and the parent to keep discomfort-averse child in one place). Recently, I asked him if he could spell words in pairs such as “MOB & MOD”, “CAD & CAB”, “REB & RED” etc., and, as he slowly sounded out each sound/letter, he informed me that “they are the same daddy“.  Hence, I realized that he was having trouble – not with the sound to letter correspondence, or the grouping of the letters, or the meaning, or handwriting – but rather – just hearing and discriminating the -B vs. -D sounds at the end of the word pairs.  Wow, OK, this was a much more basic aspect of literacy – just being able to hear the sounds clearly.  So this is the case, apparently, for many bright and enthusiastic children, who experience difficulty in learning to read.  Without the basic perceptual tools to hear “ba” as different from “da” or “pa” or “ta” – the typical schoolday is for naught.

With this in mind, the recent article, “Genetic determinants of target and novelty-related event-related potentials in the auditory oddball response” [doi:10.1016/j.neuroimage.2009.02.045] caught my eye.  The research team of Jingyu Liu and colleagues asked healthy volunteers just to listen to a soundtrack of meaningless beeps, tones, whistles etc.  The participants typically would hear a long stretch of the same sound eg. “beep, beep, beep, beep” with a rare oddball “boop” interspersed at irregular intervals.  The subjects were instructed to simply press a button each time they heard an oddball stimulus.  Easy, right?  Click here to listen to an example of an “auditory oddball paradigm” (though not one from the Liu et al., paper).  Did you hear the oddball?  What was your brain doing? and what genes might contribute to the development of this perceptual ability?

The researchers sought to answer this question by screening 41 volunteers at 384 single nucleotide polymorphisms (SNPs) in 222 genes selected for their metabolic function in the brain.  The team used electroencephalogram recordings of brain activity to measure differences in activity for “boop” vs. “beep” type stimuli – specifically, at certain times before and after stimulus onset – described by the so-called N1, N2b, P3a, P3b component peaks in the event-related potentials waveforms.  800px-Erp1Genotype data (coded as 1,0,-1 for aa, aA, AA) and EEG data were plugged into the team’s home-grown parallel independent components analysis (ICA) pipeline (generously provided freely here) and several positives were then evaluated for their relationships in biochemical signal transduction pathways (using the Ingenuity Pathway Analysis toolkit.  A very novel and sophisticated analytical method for certain!

The results showed that certain waveforms, localized to certain areas of the scalp were significantly associated with the perception of various oddball “boop”-like stimuli.  For example, the early and late P3 ERP components, located over the frontal midline and parieto-occipital areas, respectively, were associated with the perception of oddball stimuli.  Genetic analysis showed that several catecholaminergic SNPs such as rs1800545 and rs521674 (ADRA2A), rs6578993 and rs3842726 (TH) were associated with both the early and late P3 ERP component as well as other aspects of oddball detection.

Both of these genes are important in the synaptic function of noradrenergic and dopaminergic synapses. Tyrosine hydroxylase, in particular, is a rate-limiting enzyme in catecholamine synthesis.  Thus, the team has identified some very specific molecular processes that contribute to individual differences in perceptual ability.  In addition to the several other genes they identified, the team has provided a fantastic new method to begin to crack open the synaptic complexities of attention and learning.  See, I told you learning to read was hard!

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Zebra Zen
Image by digitalART2 via Flickr

In Robert Sapolsky’s book, “Why Zebras Don’t Get Ulcers“, he details a biological feedback system wherein psychological stress leads to the release of glucocorticoids that have beneficial effects in the near-term but negative effects (e.g. ulcers, depression, etc.) in the long-term.  The key to getting the near-term benefits and avoiding the long-term costs – is to be able to turn OFF the flow of glucocorticoids.  This is normally dependent on circuitry involving the frontal cortex and hippocampus, that allow individuals to reset their expectations and acknowledge that everything is OK again.  Here’s the catch (i.e. mother nature’s ironic sense of humor). These very glucocorticoids can initiate a kind of reorganization or ‘shrinkage’ to the hippocampus  – and this can disable, or undermine the ability of the hippocampus to turn OFF the flow of glucocorticoids.  Yes, that’s right, the very switch that turns OFF glucocorticoid flow is disabled by exposure to glucocorticoids!  Can you imagine what happens when that switch (hippocampus) get progressively more disabled?  Your ability to turn OFF glucocorticoids gets progressively worse and the negative effects of stress become more and more difficult to cope with.

Sounds depressing.  Indeed it is, and there are many findings of reduced hippocampal volume in various depressive illnesses.  The complex problem at hand, then, is how to reverse the runaway-train-like (depression leads to glucocorticoids which leads to smaller hippocampus which leads to more depression) effects of stress and depression?

One new avenue of research has been focused on the ability of the hippocampus to normally produce new cells – neurogenesis – throughout life.  Might such cells be useful in reversing hippocampal remodeling (shrinkage)?  If so, what molecules or genes might be targeted to drive this process in a treatment setting?

The recent paper by Joffe and colleagues, “Brain derived neurotrophic factor Val66Met polymorphism, the five factor model of personality and hippocampal volume: Implications for depressive illness” [doi: 10.1002/hbm.20592] offers some key insights.  They examined 467 healthy participants of the Brain Resource International Database (a personalized medicine company with a focus on brain health) using personality tests, structural brain imaging and genotyping for an A-to-G variation (valine-to-methionine) polymorphism in the BDNF gene.  They report that lower volume of the hippocampus was associated with higher scores of neuroticism (worriers) – but, this negative relationship was not found in all people – just those who carry the A- or methionine-allele.  Thus, those individuals who carry the G/G (valine/valine) genotype of BDNF may be somewhat more protected from the negative (hippocampal remodeling) effects of psychological stress.  Interestingly, the BDNF gene seems to play a role in brain repair!  So perhaps this neuro-biochemical pathway can be explored to further therapeutic benefit.  Exciting!!

By the way, the reason zebras don’t get ulcers, is because their life revolves around a lot of short term stressors (mainly hungry lions) where the glucocorticoid-stress system works wonderfully to keep them alive.  Its only homo sapiens who has enough long-term memory to sit around in front of the TV and incessantly fret about the mortgage, the neighbors, the 401K etc., who have the capacity to bring down all the negative, toxic effects of chronic glucocorticoids exposure upon themselves. My 23andMe profile shows that I am a G/G valine/valine … does this mean I’m free to worry more?  Now I’m worried.  More on BDNF here.

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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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Image representing 23andMe as depicted in Crun...
Image via CrunchBase

pointer to: Great Q&A on Freakonomics with 23andMe founder Anne Wojcicki. Nice overview of peoples’ concerns and interests in personal genomes.

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pointer to Jen S. McCabe’s blog on healthcare management and gracious video share of her experience with her 23andMe personal genome data.

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old class photo with grandpa, 1923
Image by freeparking via Flickr

Back in the day, when the fam would get together at my parents’ house, I would enjoy shuffling through their box of old photos.  Looking at childhood pictures of myself and relatives, it was natural to compare our adult selves to the old pictures and look for similarities – emotional expressions, gestures, etc. – that have carried on through the years and are (were) a part of who we are (became) today.  It’s always amazing what you think you can see, and if you’re like me, you may be somewhat amazed by how much of your adult self was already in full swing as a child.  The manner in which the developing brain confers such stability over time and over generations (now I see my own childhood traits in my son – yikes!) is of course a timeworn question among families and scientists alike.

That the genome would contribute to cross generational parent-child similarities in personality and temperament is fairly obvious, but not so apparent is how the genome interacts with the environment to exert an influence on psychological development.  Along this line of inquiry, a research article entitled, “Influence of RGS2 on anxiety-related temperament, personality, and brain function” by Smoller and colleagues [free access] provides an amazing perspective – from a single gene.  RGS2, eponymously named as a regulator of G-protein signaling, was first identified as a factor that regulates emotional behavior in mice [PMID] and subsequently as a risk factor for schizophrenia [PMID] as well as anxiety disorders in humans [PMID].  In the current study, the team examined the temperament of children (119 families), personality of adults (744 undergraduates) and brain activity in adults (55 participants) to ascertain whether the adult risk for anxiety conferred by RGS2 might be related to actions of the gene that occur much earlier in development – such as on the systems that regulate temperament in children.  Specifically, they focused on behavioral inhibition in children (shy, avoidant, restrained in novel situations) and introversion in adults – as these traits have been associated with increased risk for anxiety disorders.

What is so interesting to me is that RGS2 (particularly the G allele of the 3’UTR SNP rs4606) was found to be associated with both childhood temperament and adult personality.  Thus, an introverted adult who looks through an old photo album and sees themselves to have been a shy or inhibited child, may be experiencing – to a small degree – the effects of the RGS2 gene.  The team suggests, via additional brain imaging-genetic studies, that RGS2 is of particular relevance to activity in circuits containing the insular cortex and amygdala – when subjects perform an emotional face matching task.

My own 23andme record does not contain the rs4606 SNP but does contain the data for rs1819741 where a T allele was significantly associated with introversion.  Since I’m a C/T heterozygote, I guess I’ll have to look a bit harder at my old pictures to see signs of behavioral inhibition.

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