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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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Corticotropin-releasing hormone
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According to the authors of  “Protective effect of CRHR1 gene variants on the development of adult depression following childhood maltreatment: replication and extension”  [PMID: 19736354], theirs is “the first instance of Genes x Environment research that stress has been ascertained by more than 1 study using the same instrument“.  The gene they speak of is the Corticotropin-releasing hormone receptor 1 (CRHR1) gene (SNPs rs7209436, rs110402, rs242924 which can form a so-called T-A-T haplotype which has been associated with protection from early life stress (as ascertained using the Childhood Trauma Questionnaire CTQ)).

The research team examined several populations of adults and, like many other studies, found that early life stress was associated with symptoms of depressive illness but, like only 1 previous study, found that the more T-A-T haplotypes a person has (0,1,or 2) the less likely they were to suffer these symptoms.

Indeed, the CRHR1 gene is an important player in a complex network of hormonal signals that regulate the way the body (specifically the hypothalamic pituitary adrenal axis) transduces the effects of stress.  So it seems quite reasonable to see that individual differences in ones ability to cope with stress might correlate with genotype here.   The replication seems like a major step forward in the ongoing paradigm shift from “genes as independent risk factors” to “genetic risk factors being dependent on certain environmental forces”.  The authors suggest that a the protective T-A-T haplotype might play a role in the consolidation of emotional memories and that CRHR1 T-A-T carriers might have a somewhat less-efficient emotional memory consolidation (sort of preventing disturbing memories from making it into long-term storage in the first place?) – which is a very intriguing and testable hypothesis.

On a more speculative note … consider the way in which the stress responsivity of a developing child is tied to its mother’s own stress responsivity.  Mom’s own secretion of CRH from the placenta is known to regulate gestational duration and thus the size, heartiness and stress responsiveness of her newborn.  The genetic variations are just passed along from generation to generation and provide some protection here and there in an intertwined cycle of life.

The flowers think they gave birth to seeds,
The shoots, they gave birth to the flowers,
And the plants, they gave birth to the shoots,
So do the seeds they gave birth to plants.
You think you gave birth to the child.
None thinks they are only entrances
For the life force that passes through.
A life is not born, it passes through.

anees akbar

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Twin studies have long suggested that genetic variation is a part of healthy and disordered mental life.  The problem however – some 10 years now since the full genome sequence era began – has been finding the actual genes that account for this heritability.

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?

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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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Georgetown University's main campus taken from...
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It was a delight to speak with Professor Vaidya this morning on her recent article, Neural response to working memory load varies by dopamine transporter genotype in children.  An understanding of how a single genetic variant can relate to brain function, behavior and clinical intervention involves the synthesis of a great many points of view (molecular, neural, systems, pharmacological and psychological).  Professor Vaidya provides an outstanding example of this type of synthesis in her discussion of the dopamine transporter variant.  Here are links to her lab, the blog post and the podcast.

Thanks very much to Dr. Vaidya for sharing her thoughts with us!

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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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