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Posts Tagged ‘Genetic testing’

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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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The recent paper, “Comparative genomics of autism and schizophrenia” by Bernard Crespi and colleagues provides a very exciting take on how genetic data can be mined to understand cognitive development and mental illness.  Looking at genetic association data for autism and schizophrenia, the authors point out that 4 loci are associated with both schizophrenia and autism – however, with a particular twist.  In the case of 1q21.1 and 22q11.21 it seems that genetic deletions are associated with schizophrenia while duplications at this locus are associated with autism.  At 16p11.2 and 22q13.3  it seems that duplications are associated with schizophrenia and deletions are associated with autism.  Thus both loci contain genes that regulate brain development such that too much (duplication) or too little (deletion) of these genes can cause brain development to go awry.  The authors point to genes involved in cellular and synaptic growth for which loss-of-function in growth inhibition genes (which would cause overgrowth) have been associated with autism while loss-of-function in growth promoting genes (which would cause undergrowth) have been associated with schizophrenia.  Certainly there is much evidence for overproduction of synapses in the autism-spectrum disorders and loss of synapses in schizophrenia.  Crespi et al., [doi:10.1073/pnas.0906080106]

Other research covered (here, here) demonstrates the importance of the proper balance of excitatory and inhibitory signalling during cortical development.

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Where da rodents kick it
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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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LARRY DAVID AT TRIBECA FILM FESTIVAL WIKIPEDIA
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pointer to: Eye-on-DNA’s post of last nights episode of “Lopez Tonight” where Larry David shared the unveiling of his “Ancestry-by-DNA” results.  He was good sport and it was great to see science as FUNHis results made me wonder if such ancestry tests are reliable though.

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The neuregulin-1 (NRG1) gene is widely known as one of the most well-replicated genetic risk factors for schizophrenia.  Converging evidence shows that it is associated with schizophrenia at the gene expression and mouse model levels which are consistent with its molecular functions in neural development.   However, in several recent genome-wide association studies (GWAS), there appeared nary a blip of association at the 8p12 locus where NRG1 resides.  What gives?

While there are many possibilities for this phenomenon (some discussed here), the recent paper, “Support for NRG1 as a Susceptibility Factor for Schizophrenia in a Northern Swedish Isolated Population” by Maaike Alaerts and colleagues, suggest that the typical GWAS study may not adequately probe genetic variation at a fine enough scale – or, if you will, use a netting with sufficiently small holes.  By holes, I mean both the physical distance between genetic markers and the frequency with which they occur in populations.  While GWAS studies may use upwards of 500,000 markers – that’s a pretty fine scale net for a 3,000,000,000bp genome (about 6,000bp apart) – Alaerts and colleagues set forth with slightly finer-scale netting.  They focus on a 157kb region that is about 60kb upstream from the start of the NRG1 gene and construct a net consisting of 37 variants between the markers rs4268087 and rs17601950 (average spacing about 5kb).  They used the tagger program to select markers that account for all haplotypes whose frequency is higher than 1.5%.  Thus – even though there are still more than 500 possible snps in the region Alaerts and colleagues are exploring, they are using a slightly finer netting than a typical GWAS.

The results of their analysis (using GENEPOP) of 486 patients and 514 ethnically matched control participants from northern Sweden did reveal significant associations in an area slightly downstream (about 50kb closer to the start point of the NRG1 gene) than the location of the “previously often replicated variants”, suggesting that the region does confer some risk for schizophrenia, but, that diagnostic markers for such risk will be different for different populations.  More telling however are the very weak effects of the haplotypes that show significant association.  Those haplotypes with the most significance show meager differences in how often they are observed in patients vs. controls.  For example, one haplotype was observed in 5% of patients vs. 3% of controls. Others examples were, 11 vs. 9, 25 vs. 22 and 40% vs. 35% – revealing the very modest (krill sized) effects that single genetic variants can have in conferring risk toward mental illness.

However, there are potentially lots of krill in the genomic sea!

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Daniel R. Weinberger, M.D., Chief of the Clinical Brain Disorders Branch and Director of the Genes, Cognition and Psychosis Program, National Institute of Mental Health  discusses the background, findings and general issues of genes and mental illness in this brief interview on his paper, “A primate-specific, brain isoform of KCNH2 affects cortical physiology, cognition, neuronal repolarization and risk of schizophrenia”.  Click  HERE for the podcast and HERE for the original post.

Thanks again to Dr. Weinberger for his generous participation!

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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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rsrtlogoIt was a delight today to chat with Monica Coenraads, Executive Director of the Rett Syndrome Research Trust.  The RSRT has teamed up with a deeply focused world-class team of research scientists to translate the fruits of basic research on Rett syndrome into viable cures.   Whether you are a scientist, student or concerned family member, you will learn a lot from exploring the RSRT website, blog as well as this short video lectureJust by a strange, unanticipated coincidence, today marks the 10-year annivesary of the identification of MeCP2 as the underlying gene for Rett syndrome. Click here for prior blog posts on Rett syndrome.  (click here for podcast)

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pointer to: Razib Khan’s results (600+ respondents!) survey on genetic testing and psychiatric illness.  Very informative!

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BUY MY GENETIC TEST KIT!

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pointers to: “Personalized Genetics: DTC Genetic Tests Are Hype” and “The World of Genetic Genealogy and DTC Genetic Testing Never Sleeps…

Even though the data collection technology still outpaces the deeper understanding of the data, we’re learning more and more all the time.

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Family history web imagepointer to next week’s conference in Bethesda NIH State-of-the-Science Conference: Family History and Improving Health.  From the website, “Family history is also critical to determining who will benefit from genetic testing for both common and rare conditions, and can facilitate interpretation of genetic test results.”  You can watch live or later via an archived webcast!

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Last summer I took a day to drive to Camden, NJ to attend a free lecture & spit event at the Coriell Institute.  Today, I was pleased to find that the data are flowing through their user-friendly web portal.  After about 40 minutes of standardized online family, lifestyle & medical history questionnaires, I was able to view my data:

Iron Overload Genetic Variant #1 (HFE rs1800562)
GG – low risk
Type 2 Diabetes – Variant #1 (rs7754840)
CG – medium risk
Prostate Cancer – Variant #1 (rs16901979)
CC – low risk
Coronary Artery Disease – Variant #1 (rs1333049)
GC  – low risk
Melanoma Genetic Variant #1 (rs910873)
CC  – low risk

These data match my 23andMe results (except for Melanoma Genetic Variant #1 (rs910873) which is not covered by 23andMe) and the online medical education resources for each genetic test are extensive.  According to the site, more data and related medical education will be flowing soon.

Glad to have this free, albeit minimal,  access to my genome information!

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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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1/365 [dazed & confused]
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pointer to: Daniel MacArthur and Neil Walker’s (@ Genetic Future bog) in-depth coverage of various critiques on the recent back-to-back-to-back Nature magazine trifecta (covered here) on GWAS results for schizophrenia.  Rough going for the global corsortia and a major f**king bummer for folks like myself who have been hoping that these vast studies would provide a solid basis for genome-based cognitive intervention strategies in the future.  Some of the discussion in the comments section points to the weakness in the diagnostic criteria, which is a topic also covered here recently.

Perhaps there is hope in the brain systems / imaging-based approaches that are taking off as genome technology spreads into cognitive and imaging science. Tough to scan 10’s of thousands of people however. Double F**K!

I guess DSM-based psychiatric genetics is just about dead for the time being.  The announcement of the soon to shutter deCODE Genetics and its 5-year stock price captures the failure of this endeavor.

decode1

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Hat tip to Daniel MacArthur who points to this story from CNN. “About 30 children aged 3 to 12 years old and their parents are participating in a new program that uses DNA testing to identify genetic gifts and predict the future”  “For about $880, Chinese parents can sign their kids up for the test and five days of summer camp in Chongqing, where the children will be evaluated in various settings from sports to art. The scientific results, combined with observations by experts throughout the week, will be used to make recommendations to parents about what their child should pursue.

What’s the chinese word for SCAM?

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A recent summary statement from the Cross-Disorder Phenotype Group of the Psychiatric GWAS Consortium [doi 10.1192/bjp.bp.108.063156] highlights the recent convergence of GWAS findings in bipolar disorder (ANK3 & CACNA1C) and schizophrenia (ZNF804A).  They also suggest that, “the most useful biological categories and/or dimensional definitions and measures are still unknown” and that “there may be overlap in the genetic susceptibility across disorders” and furthermore, “The notion that there is a gene for one of more psychiatric disorders is inappropriate and unhelpful“.

As someone whose been covering the more granular details of genes and brain function, it is reassuring to hear that the genome experts at 10,000 feet find that the evidence suggests that DSM-based diagnostics do not always jibe with basic brain biology.

How to interpret past psychiatric genetic data and how to move forward to make sense of the waves of new data (the PGC will have more than 80,000 participants each with more than 500,000 genotypes on record by end of 2009)?   Jeebus help us!

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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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RICHMOND, CANADA - FEBRUARY 12:  Simon Whitfie...
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While often the object of scorn from its capitalistic southern neighbor, the Canada Foundation for Innovation has just awarded Dr. David Kennedy a large research grant to deploy both neuroimaging and genetic markers in the development of personalised treatment for schizophrenia – through a program dubbed “neuroIMAGENE“.  Dr. Kennedy suggests that this technological strategy may actually save money in the long run by helping physicians select the proper medication and dosage.

Capitalistic scorn huh? This news comes as the U.S. healthcare flagship GE healthcare flushes its own personalized medicine effort all the while nary a Canadian bank requires bailout largesse.  Indeed.

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pointer to Mark Henderson’s coverage of how the British NHS may adapt to the rise of direct-to-consumer genetic testing.  Among the complexities mentioned were its ubiquity, potential (yet mostly future) benefits and costs of retraining and implementing.  Also, tighter regulatory standards for DTC vendors.

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