Posted in Frontal cortex, Lateral ventricle, Temporal lobe, White matter, tagged 23andMe, Add new tag, Brain, brain structure, Development, Frontal lobe, Genetics, Genome-wide association study, GWAS, Neuroimaging, Statistical hypothesis testing, Statistics, Temporal lobe, White matter on March 12, 2010 |
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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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Posted in Cingulate cortex, Hippocampus, Temporal lobe, tagged aging, Alzheimer's disease, Brain, Cognition, default mode network, default network, dementia, E. E. Cummings, Frontal lobe, Functional magnetic resonance imaging, Genetic testing, Health, Hippocampus, Human brain, Japanese poetry, Poetry, Temporal lobe on January 22, 2010 |
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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”
(inquiry before snow
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.
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A recent analysis of brain structure in healthy individuals who carry a common 2,445-bp deletion in intron 2 of the doublecortin domain containing 2 (DCDC2) gene found that heterozygotes for the deletion showed higher grey matter volumes for several brain areas known to be involved in the processing of written and spoken language (superior, medial and inferior temporal cortex, fusiform, hippocampal / parahippocampal, inferior occipito-parietal, inferior and middle frontal gyri, especially in the left hemisphere) [doi:10.1007/s11682-007-9012-1]. The DCDC2 gene sits within a well known locus frequently found to be associated with developmental dyslexia, and associations of reading disability with DCDC2 have been confirmed in population-based studies. Further work on DCDC2 (open access) shows that the DNA that is deleted in the 2,445-bp deletion in intron 2 carries a number of repeating sequences to which developmental transcription factors bind and that inhibition of DCDC2 results in altered neuronal migration (the right-hand panel shows altered radial migration when DCDC2 is inhibited). Perhaps the greater grey matter volumes are related to this type of neuronal migration finding? Will be interesting to follow this story further!
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