Guilt by association: SCN1A in Temporal Lobe Epilepsy

GWAS. Genome-wide association studies investigate the association of common genetic variants with disease in large patient samples. While this approach has been very successful in many other diseases, the results in epilepsy research have been less convincing. Given the complexity of epilepsy phenotypes, selection of the right epilepsy phenotype has been an ongoing debate. Now, a recent study in Brain finds an intronic variant of the SCN1A gene that is associated with Temporal Lobe Epilepsy (TLE), the most common epilepsy in man. Interestingly, the association with SCN1A seems to be specific for only a particular subtype of focal epilepsies. Continue reading

The genetics of emergent phenotypes

This article was written Kevin Mitchell and first published on his blog “Wiring The Brain” and appears here with his consent.

Why are some brain disorders so common? Schizophrenia, autism and epilepsy each affect about 1% of the world’s population, over their lifetimes. Why are the specific phenotypes associated with those conditions so frequent? More generally, why do particular phenotypes exist at all? What constrains or determines the types of phenotypes we observe, out of all the variations we could conceive of? Why does a system like the brain fail in particular ways when the genetic program is messed with? Here, I consider how the difference between “concrete” and “emergent” properties of the brain may provide an explanation, or at least a useful conceptual framework. Continue reading

Exome sequencing in epileptic encephalopathies – the powers that be

The power, over and over again. I must admit that I am thoroughly confused by power calculations for rare genetic variants, particularly for de novo variants that are identified through trio exome sequencing. Carolien has recently written a post about the results we can expect from exome sequencing studies. For a current grant proposal, I have now tried to estimate the rate of de novos using a small simulation experiment. And I have realized that we need to re-think the concept of power. Continue reading

The exome fallacy

Are you fully covered? My experience with a phenomenon I shall call exome fallacy began in 2011. While browsing the exomes of a few patients with epileptic encephalopathies, we wanted to have a quick look at whether we could exclude mutations in the epilepsy gene SCN1A in our patients through exome data. As some of you might already guess, the words “exome” and “exclude” don’t go well together and we learned the hard way that each individual exome covers certain parts of the gene quite well. However, if you expect your exome data to have sufficient quality to cover an entire gene in several individuals, you end up disappointed. But there is even more to the exome fallacy than you might think… Continue reading

Why CNS disorders are more likely to be monogenic

Once again, the flood of rare variants. Deep sequencing studies have revealed an unexpected plethora of rare variants, i.e. genetic variants that can only be found in few or even single individuals. While the genetic architecture of more common genetic variants, so-called Single Nucleotide Polymorphisms (SNPs) is well known through the HapMap project, the role of rare variants identified with recent sequencing studies is difficult to interpret. Basically, for an individual variant it is difficult to establish whether this variant is disease-causing or disease-related based on the frequency in cases. Establishing association at the same level of statistical significance as required for SNPs is difficult given that much larger samples are needed. Furthermore, protein prediction algorithms have their limitations and might not be able to discriminate an accidental from a causal variant, given that every individual might be homozygous or compound homozygous for gene-disrupting variants in at least three genes. We are drowning in a flood of rare variants and cannot distinguish pathological from benign variants very well yet. Continue reading