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Posts Tagged ‘Genetic testing’

kermmarb

[link to research article on loss-of-function variants in the human genome]

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… but not like this.  Try openSNP.

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when you realize that the genetic risk of that allele you carry was calculated using a small population from south-western-upper-middle-eurasia-stan … and doesn’t really apply to your individual situation.

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Perhaps just a little bit.  One Law Professor’s experience.

“As it happens, … It turned out that I had a genetic variant that implied a moderately increased risk of meningioma, the second most common type of brain tumor.

The information came a little late to be useful. Last summer, … found me half conscious on the floor. The diagnosis at the local hospital was meningioma, a benign (i.e. non-cancerous) tumor inside my skull but fortunately outside my brain.”

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Having some fun here learning to visualize data using Processing.  Here is a map showing the relative number of genetic testing laboratories.  California is listed with the most (35 labs).  *Note, these are genetic testing laboratories which may service a wide range of health care providers and clinics.

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Thinking of bragging about the large size of your brain-function genes?

Brain-function genes can be very large.  Genetic variation – specifically, copy number variation (CNV) – is often found in brain-function genes in populations with mental disability … but … not much more often than in healthy populations.

To demonstrate the potential impact of confounders, we genotyped rare CNV events in 2,415 unaffected controls with Affymetrix 6.0; we then applied standard pathway analyses using four sets of brain-function genes and observed an apparently highly significant enrichment for each set. The enrichment is simply driven by the large size of brain-function genes.

The full story and a new statistical test – that aims to control for this confounding effect of large brain-function genes.  More on chromosomal structural variation and schizophrenia here.

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THE ultimate guide to your genome … ‘nuf said.

The mission of the Encyclopedia of DNA Elements (ENCODE) Project is to enable the scientific and medical communities to interpret the human genome sequence and apply it to understand human biology and improve health. The ENCODE Consortium is integrating multiple technologies and approaches in a collective effort to discover and define the functional elements encoded in the human genome, including genes, transcripts, and transcriptional regulatory regions, together with their attendant chromatin states and DNA methylation patterns. In the process, standards to ensure high-quality data have been implemented, and novel algorithms have been developed to facilitate analysis. Data and derived results are made available through a freely accessible database. Here we provide an overview of the project and the resources it is generating and illustrate the application of ENCODE data to interpret the human genome.

 

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I mean, how many people are really needed to run a sufficiently powered genome-wide association study?  Are there enough people on the planet?  Heather J. Cordell’s review, Detecting gene-gene interactions that underlie human diseases, seems optimistic, but, at this point, it seems a valid question … at least if you want to detect gene-gene interactions.

“The historical lack of success in genetic studies of complex disease can largely be attributed, not to ignored biological interactions, but rather to under-powered studies that surveyed only a fraction of genetic variation …”

thanks for the pic heckyeahart

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A LOT of genetic data is out there … and more coming all the time … easy to get excited about, but hard to make sense of.  Here’s an epic story of just one SNP.

One of the best research teams in the business performed a genomewide association study (GWAS) of neuroticism in 1,227 US Caucasion participants and found associations (P values of 10−5 to 10−6) with several markers – including rs7151262 in the MAMDC1 gene.  Later they replicated the finding in a German sample of 1,880 (P values in the same directions 0.006–0.025).

Very exciting to ponder the ways in which this SNP might relate to the development of brain systems that process emotional information!

More recently, they attempted another replication of the MAMDC1 gene for association with neuroticism in 2,722 US Caucasion participants.  This time they report, “the current analysis failed to detect a significant association signal“.

Some 5,829 people were involved in the research and the data suggest that rs7151262 may or may not contribute to one’s neurotic tendencies.  If you knew your rs7151262 genotype would it change the way you think about yourself?

I don’t know … the confusion over the (+) vs. (-) association data would make me … well, neurotic.

thanks for the photo jinxmesomethingcrazy.

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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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I probably deserve a punch in the head (see video). I will try harder to emphasize that this blog is NOT about “genes cause this” and “genes cause that”, but rather about the way we can use our genetic information as a tool – just one of many – to explore our relationships with each other, our past, other species and the environment. Still, you are welcome to punch me in the head (see video) if you like.

 

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Great commentary by neuroscientist Dorothy Bishop on the limits of personal genomics …

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View of Capitol Hill from the U.S. Supreme Court
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Pointer to Daniel MacArthur’s (Genomes Unzipped) post on the recent political grandstanding in consumer genetics.

This blog is more genomes, brains, social entrepreneurship and health 2.0 – than politics.   Hopefully the political phase will soon pass and some sensible regulations will preserve the right of consumers to access their genomes, while protecting consumers from scammers.

The one thing I hope does not happen is that the regulatory agencies (they work for us right?) “punt” on the issue and turn the whole consumer genetics ball of wax over to medical doctors and the medical insurance complex.  Like many, I am inspired by open-source, open-access, crowd-sourcing, bioinformatic and other open, web-based tools that allow consumers to by-pass the so-called “experts” in news media, finance, health and so many other industries that are being transformed by information technology.   The economic benefits for consumers are well documented, and so,  a country like the U.S. – economically sinking in a healthcare affordability crisis – might benefit (in the longer run) if it nurtured industries that helped consumers freely and openly ascertain their risks for illness without having to go through the economic choke point of an establishment of medical “experts”.

See health 2.0,  Regina Herzlinger’s “Who Killed Health Care?“,  Michael E. Porter and Elizabeth Olmsted Teisberg’s “Redefining Health Care: Creating Value-Based Competition on Results“,  Andy Kessler’s “The End of Medicine: How Silicon Valley (and Naked Mice) Will Reboot Your Doctor”  and Nobel Prize-winning economist Kenneth Arrow’s classic 1963 essay “Uncertainty and the Welfare Economics of Medical Care”  for some more on this.

Update:  The comment stream on Daniel MacArthur’s (Genomes Unzipped) post are chilling.  Many of the responders seem to have experience in the direct-to-consumer genetics business, and they don’t sound as optimistic as my (naive) self.  Part of one comment:

Seriously, you don’t understand. The DTC testing industry is ALREADY DEAD. In the Wall Street Journal, Shuren declared DTC subject to PMA approval, which costs tens of million of dollars! People are quitting the companies by the droves. 23andMe’s former director of regulatory affairs left for NextBio. VCs have refused to re-up. There will be no Series X+1 financing for an industry with no growth potential.

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The structure of part of a DNA double helix
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just a pointer to: Genetic Future’s pointer to the recent article, “Family become first to have DNA sequenced for non-medical reasons“.    The father suggests, “it will be ethically improper if you don’t have your children sequenced“.

Early days.

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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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wotd044
Image by theloushe via Flickr

** PODCAST accompanies this post**

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

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

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

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

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

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

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

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

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

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

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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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***PODCAST ACCOMPANIES THIS POST***

In his undergraduate writings while a student at Harvard in the early 1900’s E. E. Cummings quipped that, “Japanese poetry is different from Western poetry in the same way as silence is different from a voice”.  Isabelle Alfandary explores this theme in Cummings’ poetry in her essay, “Voice and Silence in E. E. Cummings’ Poetry“,  giving some context to how the poet explored the meanings and consequences of voice and silence.  Take for example, his poem “silence”

silence

.is
a
looking

bird:the

turn
ing;edge, of
life

(inquiry before snow

e.e. cummings

Lately, it seems that the brain imaging community is similarly beginning to explore the meanings and consequences of the brain when it speaks (activations whilst performing certain tasks) and when it rests quietly.  As Cummings beautifully intuits the profoundness of silence and rest,  I suppose he might have been intrigued by just how very much the human brain is doing when we are not speaking, reading, or engaged in a task. Indeed, a community of brain imagers seem to be finding that the brain at rest has quite a lot to say – moreso in people who carry certain forms of genetic variation (related posts here & here).

A paper by Perrson and colleagues “Altered deactivation in individuals with genetic risk for Alzheimer’s disease” [doi:10.1016/j.neuropsychologia.2008.01.026] asked individuals to do something rather ordinary – to pay attention to words – and later to then respond to the meaning of these words (a semantic categorization task). This simple endeavor, which, in many ways uses the very same thought processes as used when reading poetry, turns out to activate regions of the temporal lobe such as the hippocampus and other connected structures such as the posterior cingulate cortex.  These brain regions are known to lose function over the course of life in some individuals and underlie their age-related difficulties in remembering names and recalling words, etc.  Indeed, some have described Alzheimer’s disease as a tragic descent into a world of silence.

In their recordings of brain activity of subjects (60 healthy participants aged 49-79), the team noticed something extraordinary.  They found that there were differences not in how much the brain activates during the task – but rather in how much the brain de-activates – when participants simply stare into a blank screen at a small point of visual fixation.  The team reports that individuals who carry at least one copy of epsilon-4 alleles of the APOE gene showed less de-activation of their their brain (in at least 6 regions of the so-called default mode network) compared to individuals who do not carry genetic risk for Alzheimer’s disease.  Thus the ability of the brain to rest – or transition in and out of the so-called default mode network – seems impaired in individuals who carry higher genetic risk.

So, I shall embrace the poetic wisdom of E. E. Cummings and focus on the gaps, empty spaces, the vastness around me, the silences, and learn to bring my brain to rest.  And in so doing, perhaps avoid an elderly descent into silence.

***PODCAST ACCOMPANIES THIS POST***

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

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

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

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

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

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