Donald Doherty's blog

Category: Brain Science

Autism, the Brain’s Frontal Lobes, and the CNTNAP2 Gene

Recent studies on the genetics of childhood psychiatric diseases have resulted in a long list of candidate genes that may contribute to the risk of autism spectrum disorders (see my earlier blog post “Genetics of Autism: Challenging Psychiatric Classifications“). A common genetic variation in the contactin-associated protein-like 2 (CNTNAP2) gene is a strong candidate for risk of autism and other disorders including Tourette syndrome, obsessive compulsive disorder, and epilepsy. CNTNAP2 has been shown to affect language ability and is associated in autism with specific language impairment.

Anatomical studies have shown that CNTNAP2 messenger RNA (mRNA) is significantly enriched in the frontal and temporal lobes of the developing human brain. CNTNAP2 is involved in clustering voltage-gated potassium channels (Kv1.1) at the nodes of Ranvier. During development, Caspr2, the protein encoded by CNTNAP2, is thought to assist in interactions important for cellular migration and subsequent laminar organization, indicating a role for CNTNAP2 in the construction of neural circuits.

The authors of the new paper “Altered Functional Connectivity in Frontal Lobe Circuits Is Associated with Variation in the Autism Risk Gene CNTNAP2” published November 3, 2010 in Science Translational Medicine set out to test if a variation at the CNTNAP2 gene would predispose a person to cognitive dysfunction due to changes in typical frontal lobe neural activity and functional connectivity.

The research team scanned the brains of 32 children using functional magnetic resonance imaging (fMRI). Half of the participants were diagnosed with autism and the other half had no known psychiatric disorders. The participants performed a learning task during the brain scans.

The researchers investigated the brain areas and connections affected by the rs2710102 allele (in the CNTNAP2 gene), which is known to confer the risk of autism on carriers. Interestingly, the frequency of the risk genotype was similar between the typically developing and the autism groups so they collapsed the data across groups and investigated the appearance of the risk variant and associated differences in brain function.

Those without the risk allele showed stronger long-range anterior-posterior connectivity between the medial prefrontal cortex and the medial occipital and ventral temporal cortices. Brain imaging studies have shown that robust short range functional connections in the maturing human brain get progressively weaker and the sparser long range functional connections get progressively stronger (see my earlier blog post “Predicting Individual Brain Maturity from Functional Imaging“). These data suggest that those carrying the risk allele retain a more immature functional connectivity in certain areas of the cerebral cortex associated with language, sociability, and other cognitive skills.

The team also showed significantly reduced activity in the medial prefrontal cortex during the learning task in the group not carrying the risk allele. The medial prefrontal cortex is typically more active during rest than during externally directed attention. The team’s findings suggest that those carrying the risk allele process externally directed attention differently than those without the allele.

Other related blog posts:

Genetics of Autism: Challenging Psychiatric Classifications

Predicting Individual Brain Maturity from Functional Imaging

November 5, 2010
How the Brain Works, Flies, and the FlyBase Online Data Repository

Fruit flies have a complex enough nervous system, with brains composed of about 100,000 neurons, to support some behaviors found in humans and other mammals. Contrast that with the human brain that has somewhere in the neighborhood of one hundred billion neurons and add the fact that the fruit fly is one of the most studied organisms in genetics and development and you can see why our little insect friend is an excellent candidate for clarifying principles governing how the brain works.

A new paper published in Science describes research that uses a combination of sophisticated genetic, anatomical, and physiological techniques to discover a pair of neurons that control a fundamental fly behavior. It seemed the perfect opportunity for me to take a peek at the latest in fly neuroscience. Also, I wanted to see if I could find tools based on Semantic Web technologies that would leverage my knowledge of mammalian brains to help me understand the fly nervous system.

As it turns out the paper “Two Pairs of Neurons in the Central Brain Control Drosophila Innate Light Preference” (published October 22, 2010 in Science) is a veritable alphabet soup of fly jargon. “…TeTxLC expression driven by NP394-Gal4 was excluded from the NP394-neurons…” Perfect!

The first step described in the paper was to screen a large number of fly larva with a genetic manipulation that, when expressed at a connection between nerve cells, would turn off communication from one neuron to the next (turn off the synaptic release of neurotransmitter). Normally fly larvae avoid light. Most of the genetically manipulated larvae continued to avoid light but some lost any light preference and a few actually preferred light.

The team focused on the larvae that preferred light and used labeling techniques to highlight the cells responsible for the switch from light avoiding to light loving fly larvae. They narrowed the cells responsible to two pairs of neurons in the supraesophageal ganglion. At this point I was ready for a quick, preferably visual, orientation to the fly nervous system and how the supraesophageal ganglion fits in.

I was aware that FlyBase, an online data repository of fly genes and genomes, was instrumental in developing a fly (Drosophila melanogaster) gross anatomy ontology so I took a look at their website (see Figure 1)

Note: The FlyBase Anatomy (FBbt) ontology is hosted on the Open Biological and Biomedical Ontologies [OBO] website and is available in Web Ontology Language [OWL] in addition to OBO format.

Figure 1. The FlyBase website includes a QuickSearch area.

I was able to search for and find the supraesophageal ganglion on the FlyBase website. To try it yourself go to FlyBase and, in the QuickSearch area, open the drop-down menu next to the “Data Class” label by clicking on the up-down arrows. Scroll down and select “controlled vocabularies” and then enter “supraesophageal ganglion” into the “Enter text” box. The page should look something like in Figure 2.

Figure 2. Search the FlyBase control vocabularies for supraesophageal ganglion.

Note: If you open the drop-down menu for “CV Hierarchy” in the QuickSearch area you’ll see at least 5 ontologies listed. The search for the supraesophageal ganglion will use the FlyBase Anatomy ontology.

Click the Search button and you should see a page returned that looks something like in Figure 3.

Figure 3. The results from a search for the supraesophageal ganglion.

Click on the term “supraesophageal ganglion” and information about the term is displayed like in Figure 4.

Figure 4. A description in addition to other information displayed after clicking on supraesophageal ganglion.

The page describes the supraesophageal ganglion but this is probably most helpful to a fly specialist. I’ll need to take some time and find diagrams. Nevertheless, I’ve found the FlyBase site to be useful even at the anatomical level. I entered “pdf” into the QuickSearch area and FlyBase returned a list of terms that included “Pdf neuron.” Pdf is a factor associated with specific neurons in the fly larva known to receive input from photoreceptors. The pair of neurons that the research team found (NP394-neurons) are adjacent to Pdf neurons in the supraesophageal ganglion and are involved in light preference behavior.

FlyBase doesn’t claim to be an anatomical atlas. It’s a repository for genes and genomes and there are useful links with anatomical terms within this context. However, I’d love to be able to use a virtual fly nervous system similar to the virtual mouse brain in the Whole Brain Catalog. I haven’t found anything like that. Have you?

Other related blog posts:

NeuronBank: Neuronal Circuit Online Data Repository

Whole Brain Catalog: the Google Earth for the Brain

Whole Brain Catalog: Brain Cells and Molecules

Bio-Commons a Global Challenge

Whole Brain Catalog: Visualizing Neural Network Activity

November 4, 2010
Mental Activity Influences Brain Biochemistry

You’re going to a house that you’ve never been to before. At a stoplight you glance at the address and then, when the light turns green, you look for the number. You’re using what is technically called working memory to maintain mental access to the house number.

Many studies have shown that working memory may be improved through intensive training, which is encouraging since aging reduces working memory capacity. There are also neurological and psychiatric disorders that impact working memory.

The neurotransmitter dopamine is known to play a central role in working memory. Researchers asked if intensive mental activity due to training could affect dopamine. Specifically they looked at the concentration of two types of dopamine receptors in the brain. They looked to see if there may be a change in the number of D1 receptors in the cerebral cortex or D2 receptors in subcortical brain regions.

The paper titled “Changes in Cortical Dopamine D1 Receptor Binding Associated with Cognitive Training” was published February 6, 2009 in Science.

Volunteers went through 14 hours of training to improve working memory over a 5 week period. Using brain imaging techniques (functional magnetic resonance imaging) the research team showed that improved working memory was associated with a decrease in the number of available D1 receptors.

November 3, 2010