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Archive for the ‘Chromosome structural variants’ Category

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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“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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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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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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By Richard Wheeler (Zephyris) 2007. The three ...
Image via Wikipedia

File this story under “the more you know, the more you don’t know” or simply under “WTF!”  The new paper, “Microduplications of 16p11.2 are associated with schizophrenia” [doi:10.1038/ng.474] reveals that a short stretch of DNA on chromosome 16p11.2 is – very rarely – duplicated and – more rarely – deleted.  In an analysis of 8,590 individuals with schizophrenia, 2,172 with developmental delay or autism, 4,822 with bipolar disorder and 30,492 controls, the the microduplication of 16p11.2 was strongly associated with schizophrenia, bipolar and autism while the reciprocal microdeletion was strongly associated with developmental delay or autism – but not associated with schizophrenia or bipolar disorder.

OK, so the title of my post is misleading (hey, its a blog) since there are clearly many additional factors that contribute to the developmental outcome of autism vs. schizophrenia, but this stretch of DNA seems to hold clues about early development of brain systems that go awry in both disorders.  Here is a list of the brain expressed genes in this 600 kbp region (in order from telomere-side to centromere-side): SPN, QPRT, C16orf54, MAZ, PRRT2, C16orf53, MVP, CDIPT, SEZ6L2, ASPHD1, KCTD13, TMEM219, TAOK2, HIRIP3, INO80E, DOC2A, FLJ25404, FAM57B, ALDOA, PPP4C, TBX6, YPEL3, GDPD3, MAPK3, CORO1A.

Any guess as to which one(s) are the culprits?  I’ll go with HIRIP3 given its role in chromatin structure regulation – and the consequent regulation of under- (schiz?)/over- (autism) growth of synapses. What an amazing mystery to pursue.

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Karyogram of a human maleImage via Wikipedia Doctor David Ledbetter gives an eloquent editorial overview in his piece, “Cytogenetic Technology: Genotype and Phenotype” [doi: 10.1056/NEJMe0806570] on the renaissance underway in the field of medical cytogenetics. The use of high density arrays for genome-wide copy number variation has identified a slew of new sites showing recurrent microdeletion that are reliably found in patients with mental developmental disabilities (autism, mental retardation, schizophrenia to name a few). Ledbetter suggests that the ‘genotype first’ process of diagnosis is now much more effective with the help of the new arrays. He notes, “a pediatrician has the option of ordering this test as an adjunct to or replacement of a standard karyotype and can expect a much higher yield of clinically significant results”. This is an exciting realization of the long-awaited promise of genetics in medicine.

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Gene duplication illustration
Image by Colin Purrington via Flickr

A pair of Nature papers (PubMedIDs: 18668039, 18668038) find that mapping the risk of schizophrenia to the genome is more readily achieved when examining structural variation (insertions, deletions, duplications etc.). This is welcome news given the sparse success of SNP screening, although it would be reasonable to assume that SNPs can modify such structural variants (here for the most recent schizophrenia SNP association study). The pair of papers found similar sites, which is pretty amazing given that many structural variants are rare (see the 2006 survey report). The Copy Number Variation Project provides more details on this important class of variation.

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Walther Flemming's 1882 diagram of eukaryotic ...Image via Wikipedia Amidst all the genome-wide ‘snp-ing’ going on of late (my 23-and-me data should arrive in a couple of weeks), Walsh and colleagues provide an incredible trove of structural variation (deletions/insertions in the size range of more than 100kbp but less than 100Mbp) that is 3- to 4-fold enriched in patients with adult onset and childhood onset schizophrenia. Their paper, “Rare Structural Variants Disrupt Multiple Genes in Neurodevelopmental Pathways in Schizophrenia” (DOI 10.1126/science.1155174) uses a variety of genome hybriziation techniques to map novel variants and finds, amazingly, that many of the hits are within genes that function in common pathways of brain development and synaptic function. The authors admit that it is hard to ascribe a population risk value to any one of these variants, but the biochemical pathways suggest that the genes that were identified by this method deserve a great deal of attention in the basic and clinical genetic research community.

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