Archive for the ‘imaging genetics’ Category

Genetics is increasingly making itself felt in the word of neuroscience. Labs all over the world are trying to understand the role played the the genome in the development of the brain, and impressive results are published each month highlighting how genes are expressed in the working brain, influencing learning and behaviour.

The holy grail of this neurogenomic research is, of course, the establishment of a bridge between the genome, the cell biology of neurons and synapses, the neurobiology of cognitive mechanisms, and behaviour – i.e., the four major aspects of the human mind. So far, not many behavioural traits – if any – can be explained fully in terms of the neurobiological mechanisms causing it, the molecular processes involved in said mechanisms, and the genomics underlying it all, but tintalizing results are emerging all the time that hint at what will come. The Hariri experiments Thomas and I have posted about here on the blog constitute one example. The tracing of how gene expression correlates with the learning of songs in song birds is another. [Check out these two sites.]

In lieu of all this, Cognition has decided to put together a special issue reviewing the progress made in genetics relating to the understanding of human cognition. The issue is still in press, but it is already possible to read some of the papers on the journal's webpage. As far as I can tell from the editorial introduction, written by Franck Ramus [available here], the special issue will contain contributions by Simon Fisher, Evan Balaban, Karin Stromswold, Bruce Pennington, James Blair, and Gary Marcus. Of these, Fisher's paper ["Tangled webs: Tracing the connections between genes and cognition"], Balaban's ["Cognitive developmental biology: History, process and fortune's wheel"], and Marcus' ["Cognitive architecture and descent with modification"] are on-line as I write this. I have glanced quickly at the available articles, and from what I can gather they look especially relevant to researchers working within the cognitive neurosciences who are interested in knowing more about how neurogenomics will impact their work.

Naturally, any attempts to root cognition in genetics will stir up controversies, and raise numerous hard questions. I will return to some of these issues in the coming weeks, as I read my way through the paper. Teaser: You are definitly going to hear more about modularity in the coming days!


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As we age, genes are expressed differently throughout our body. The most obvious examples are the hormonal changes seen in adolescence and in the menopause. In many models of how genes are expressed during older age, one of the prevalent models – the programmed ageing model – claims that ageing is caused by genetically programmed cell death. In other words, ageing is programmed into our cells – little blame is normally to be put on random or environmental factors.

Opposed to this model we have the normally less favoured stochastic model, which claims that random biological events play a significant role in ageing. In a recent report (PDF) (see also more extensive material here (PDF)) in Current Biology a team of researchers from the Max Planck Institute for Evolutionary Anthropology, headed by Mehmet Somel, present evidence supporting this model. Using an in-house method (called "age-correlated heterogeneity of expression", or ACHE) to assess heterogeneity of gene expression, they found that the expression becomes more heterogeneous as we age. And this goes not only for humans. Rats show the same pattern, too. They find that their results "are compatible with ACHE being an outcome of the accumulation of stochastic effects at the cellular level". In other words, something that is not programmed but due to other biological factors.

You can see this in the following figure from the article:


Explanation: "An example from the human brain data set B, the log-expression versus age plot for a probe set detecting the gene PIM-1, for which the ACHE test p-value was calculated as0.0002."
Looks like heterogeneity to me … although I'd like to see some more data, maybe on 100-200 subjects.

Note also from that article that the heterogeneity is different depending on where in the body we take the sample. What I find interesting is that the brain seems to be one of the organs where genes become most heterogeneous during ageing (see bar 2-5). This also goes for the rat hippocampus. Click the image to see a larger version:

Explanation: The heights of the bars indicate observed to expected ratios of the number of probe sets at different cutoffs within the ACHE test p-value distribution

But what is ACHE really a measure of? Here's the answer from Somel et al.:

Our results indicate that ACHE is a general — but weak — effect in the transcriptome.This is compatible with ACHE being the outcome of accumulating stochastic effects in the soma, such as cellular damage and mutations. These effects will influence each cell in a unique way so that expression variation among aging cells will be equalized at the tissue level. If somatic mutations mostly cause decreases in expression level, the overlap between ACHE and age- related decrease in expression levels can also be explained within this framework. ACHE supports the stochastic nature attributed to the aging process. It implies a weakening of expression regulation with age, contrary to previous observations and hypotheses based on measurements on a small number of gene.

While browsing around for links to this post, I found a great forthcoming publication (PDF) in Trends in Ecology and Evolution by Partridge and Gems. See also this nice yet brief post at Wikipedia about the ageing brain.


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Gene-hyped as we are here at BrainEthics, I'm mentioning a few articles that are highlighting the relationship between genes, brain and mind. As neuroscience deals with the wet matter of the mind – the fatty, information-processing and massively energy consuming body part we call the brain – we must also realize that the basic building block of the brain is the genome.

This is not as simple as it may sound. Genes simply do not merely encode how a cell is to look like or function. Genes only react to the environment in which they are situated. The development of, say, a hippocampal cell is not encoded in the genome per se; it stems from the influence of the local environment of that part of the brain, and how the brain cell (at the developmental stage actually more like a stem cell) migrates and connects to the network that will develop into the hippocampus. Neuroscience is certainly sorting out the nitty-gritty details on this, with the fantastic work by people such as Pasco Rakic. IMHO, even neuroimaging cannot escape this turn: we must move from the "blobology" of fMRI, PET and all other neuroimaging methods (this even applies to the clever diffusion fMRI, as described recently), and towards a better understanding of what goes on within these blobs. Just as I briefly mentioned in my post about Nikos Logothetis.

So here's a few additions in the story about imaging genetics, the study where neuroimaging is informed by genetic variations:

What is the hidden structure of the genome? The human genome is much more diverse and dynamic than what one could get the impression of through normal genotyping studies. Variations abound, and in a number beyond what we normally think. These are not just curiosities; they play important roles in the way that the body (and brain) develops and functions. In a news article in Nature, Andrew Sharp briefly presents two ways to study the genome, and how the new insight about variability influences current research. From the article: "The genetics community is only just beginning to appreciate the extent of structural variation present in the human genome and its role in human disease. Although we now have a finished human genome sequence in hand, geneticists have begun to appreciate that this is in fact a highly dynamic structure. The realization that the long-awaited reference sequence represents only one version of the human genome, which has significant large-scale variation between any two individuals, means that techniques such as these for investigating genome structure will be in high demand."

What is a gene? In another Nature news article, Helen Pearson discusses how RNA is becoming the new field of studying how genetic information is implemented in the organism. From the article: "In classical genetics, a gene was an abstract concept – a unit of inheritance that ferried a characteristic from parent to child. As biochemistry came into its own, those characteristics were associated with enzymes or proteins, one for each gene. And with the advent of molecular biology, genes became real, physical things – sequences of DNA which when converted into strands of so-called messenger RNA could be used as the basis for building their associated protein piece by piece. The great coiled DNA molecules of the chromosomes were seen as long strings on which gene sequences sat like discrete beads. This picture is still the working model for many scientists. But those at the forefront of genetic research see it as increasingly old-fashioned – a crude approximation that, at best, hides fascinating new complexities and, at worst, blinds its users to useful new paths of enquiry."

How heritable is Alzheimer's Disease? According to a study by Margaret Gatz and colleagues, the influence of genetics is very high, and higher than often thought. For a best-fit model estimation, genes are though to be responsible for 79%. Environmental risk factors do indeed play a role, but not as high as we might think from previous reports.

How to read the genome and its functional implications? Simon Fisher and Clyde Francks have a nice review in Trends in Cognitive Science on the genetic influence of dyslexia. Dyslexia is being used here as a model to explain how to use genotyping in a meaningful way to study the genetic influence on cognitive function and dysfunction.

These are just to mention a few important articles from this burgeoning scientific field. More are bound to follow, and we'll cover them the best we can here at BrainEthics.

(BTW, the image used here is from the Rakic Lab, illustrating the migration of brain cells during development. At the Human Brain Mapping conference in Toronto last year, Rakic held a superb talk showing movies of migrating cells. It was a true eye-opener to those of us who had not realized how much actually goes on during development. I can see that they are setting up a page for a media gallery, hopefully that will cover some of these excellent movies. I'll be watching that page closely.)


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In a thorough and very good review in PLoS Genetics, James Sikela writes about the comparative genetics between the chimp and the human genome. From the article:

It has been pointed out that the primary molecular mechanisms underlying genome evolution are 1) single nucleotide polymorphisms, 2) gene/segmental duplications, and 3) genome rearrangement. In addition, a “less-is-more” hypothesis has been proposed that argues loss of genetic material may also be a source of evolutionary change. Given these factors, what are we learning about their respective roles now that we can compare multiple primate genome sequences?

As we have pointed out repeatedly in this blog, the study of genetic influence on the brain is going to change our understanding of what a human is, how and why our thoughts are formed (and restricted) the way they are. This review surely puts the finger on the pulse and notes:

One of the most important findings to emerge from the latest human and primate genome-wide studies is that a fundamental assumption underlying this model has changed: the interspecies genomic changes are numerous and diverse, and, as a result, there appear to be many additional types of genomic mechanisms and features that could also be important to the evolution of lineage-specific traits. Given this new perspective, we now know that the degree of difference between our genome and that of the chimp depends on where, and how comprehensively, we look. The multitude of genomic differences that we now know exists should provide an abundance of fertile genomic ground from which important lineage-specific phenotypes, such as enhanced cognition, could have emerged. 

Here is the abstract:

The jewels of our genome: the search for the genomic changes underlying the evolutionary unique capacities of the human brain

James M. Sikela

The recent publication of the initial sequence and analysis of the chimp genome allows us, for the first time, to compare our genome with that of our closest living evolutionary relative. With more primate genome sequences being pursued, and with other genome-wide, cross-species comparative techniques emerging, we are entering an era in which we will be able to carry out genomic comparisons of unprecedented scope and detail. These studies should yield a bounty of new insights about the genes and genomic features that are unique to our species as well as those that are unique to other primate lineages, and may begin to causally link some of these to lineage-specific phenotypic characteristics. The most intriguing potential of these new approaches will be in the area of evolutionary neurogenomics and in the possibility that the key human lineage–specific (HLS) genomic changes that underlie the evolution of the human brain will be identified. Such new knowledge should provide fresh insights into neuronal development and higher cognitive function and dysfunction, and may possibly uncover biological mechanisms for information storage, analysis, and retrieval never previously seen.



John Hawks has a very good discussion about this article. 

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Several studies today are looking at different changes in the brain structures in healthy vs. non-healthy development, and other brain diseases. In a study just published in the Journal of Neuroscience, David van Essen and colleagues studied the brains of people suffering from Williams syndrome, a rare genetic developmental order that is characterised by "a distinctive, "elfin" facial appearance, an unusually cheerful demeanor, ease with strangers, mental retardation coupled with an unusual facility with language, a love for music, cardiovascular problems such as supravalvular aortic stenosis, and transient hypercalcemia."

In this study, van Essen found that the brains of these people were different in 33 areas, and that there was a surprising bilateral symmetry to the differences from the control group. 16 changes in the left hemisphere was mirrored by 16 changes in the right hemisphere. In addition, hemispheric asymmetry of the temporal lobe was generally smaller in this group compared to controls.

Since Williams syndrome is caused by a deletion of material in region q11.2 of chromosome 7, we can speculate that these functions normally subserve both the development and function of these brain regions, in addition to an effect of strength of hemispheric specialization and lateralization. One interesting point is that the genes affected here produce diverse changes in the brain, not strictly following traditional cognitive-functional borders. Williams syndrome is not a brain-only disease, also affecting other somatic functions such as the cardiac system. One can only speculate at this point how many regions of chromosome 7 affects the brain, how many the cardiac system, and to what extent there is an overlap between gene-brain-body mapping.

Here is the abstract:

Van Essen D, Dierker D, Snyder A, Raichle ME, Reiss A, Korenberg J. Symmetry of cortical folding abnormalities in Williams syndrome revealed by surface-based analyses. The Journal of Neuroscience, May 17, 2006.

We analyzed folding abnormalities in the cerebral cortex of subjects with Williams syndrome (WS), a genetically based developmental disorder, using surface-based analyses applied to structural magnetic resonance imaging data. Surfaces generated from each individual hemisphere were registered to a common atlas target (the PALS-B12 atlas). Maps of sulcal depth (distance from the cerebral hull) were combined across individuals to generate maps of average sulcal depth for WS and control subjects, along with depth-difference maps and t-statistic maps that accounted for within-group variability. Significant structural abnormalities were identified in 33 locations, arranged as 16 bilaterally symmetric pairs plus a lateral temporal region in the right hemisphere. Discrete WS folding abnormalities extended across a broad swath from dorsoposterior to ventroanterior regions of each hemisphere, in cortical areas associated with multiple sensory modalities as well as regions implicated in cognitive and emotional behavior. Hemispheric asymmetry in the temporal cortex is reduced in WS compared with control subjects. These findings provide insights regarding possible developmental mechanisms that give rise to folding abnormalities and to the spectrum of behavioral characteristics associated with WS.

While discussing Williams syndrome, it is important to mention the work of Andreas Meyer-Lindenberg, who is doing an impressive amount of work on this rare disease, and reporting dazzling findings on the relationship between genes, brain and (social) behaviour.


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(This is a follow-up on Martins and my brief review)

In the latest issue of Trends in Cognitive Sciences, Kovas and Plomin has an article about the implications of "generalist genes", should the theory be correct. The "generalist genes hypothesis" states that the same genes affect most cognitive abilities and disabilities. That is, our diverse cognitive apparatus — from language, to working memory, to visual attention — is affected by a few genes alone. This thought runs straight counter to the idea that genes can be responsible for one cognitive function alone.

Kovas and Plomin speculate about the meaning of generalist genes for our theories of how the brain works. From the article:

One possibility is that a generalist gene affects a single brain area or function that in turn influences several cognitive processes. The effect of such a gene would be general at the cognitive level, but specific at the level of localization in the brain. In other words, the structures and functions of the brain are uncorrelated genetically because they are influenced by different genes. We consider that this possibility is unlikely because pleiotropy suggests that any gene is likely to be expressed in more than one structure or function.

A second possibility is that cognition-related generalist genes pleiotropically affect multiple brain structures and functions, but each of these structures and functions affects a specific cognitive process. In other words, the structure and function of these specialized areas are correlated genetically because the same genetic polymorphism affects these different regions. Even though each brain structure and function is associated with one specific cognitive process, these cognitive processes are correlated genetically because the brain processes are correlated genetically.

The most likely possibility in our opinion is that generalist genes affect multiple brain structures and functions, each of which affects multiple cognitive processes. This mechanism would lead to genetic correlations both in the brain and in the mind.

I assume that generalist genes is initially incompatible with the thought of massive modularity as we see in evolutionary psychology. That does not rule out, however, the possibility of incorporating generalist gene'ism with EP. Yes, we can say that cognitive functions have evolved separately, but they might still be built out of the same genetic foundation. No need for logical inconsistency, as far as I can see.


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As the community — and thought — about imaging genetics grows, new studies are emerging. These studies focus on the way that genes are found to play a role in different cognitive functions. In a recent special issue of Behavior Genetics, the focus is on the progress in the linkage between the genetic map and behavioural traits. There are a lot of interesting articles in this special issue, altough I find a few especially intriguing.

In a nice review, Steven Buyske reviews different findings that map cognitive functions and the gene map. Here's the abstract:

Cognitive Traits Link to Human Chromosomal Regions

Human cognition in normal and disease states is both environmentally and genetically mediated. Except for measures of language-specific abilities, however, few cognitive measures have been associated with specific genes or chromosomal regions. We performed genome-wide linkage analysis of five neuropsychological tests in the Collaborative Study on Genetics of Alcoholism sample. The sample included 1579 individuals (53% female, 76% White Non-Hispanic) in 217 families. There were 390 markers with mean intermarker distance of 9.6 cM. Performance on the Digit Symbol Substitution Test, a component of the Wechsler Adult Intelligence Scale-R, showed significant linkage to 14q11.2 and suggestive linkage to 14q24.2. This test of sustained visual attention also involves visual-motor coordination and executive functions. Performance on the WAIS-R Digit Span Test of immediate memory and mental flexibility showed suggestive linkage to 11q25. Although the validity of these results beyond populations with a susceptibility for alcohol dependence is unclear, these results are among the first linkage results for non-language components of cognition.

But hey, there's more. There are studies on the association of genes and anxiety and neuroticism; gene association of feelings of loneliness; gene association to age at first cigarette; genes on academic skills; and genes on IQ (of course).

The question is: where will it end? Of course, genes are abundantly represented in the body. They are, after all, the receipt to every cell and how they should work. But what level of description and explanation should we apply in this gene-to-cognition mapping? I fear that at least in some studies, old "folk-psychological" concepts about cognitive traits are compared to high-detailed analysis and knowledge about the genes. In order to understand how genes get expressed in a way that they shape behaviour, we need to work out the intermediate stages. We need to know how genes influence neurons, transmitters, plasticity on one level; how they shape interacting neurons and neural assemblies; and finally how this cumulates into one or the other kinds of behaviour. The leap from gene to behaviour is, IMHO, too wide. The solution is in the nitty-gritty details.

Way to go CIMBI!


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