The need for re-contact. Genotype-driven research recruitment refers to the inclusion of research participants in future genetic studies based on the findings from previous studies. For example, deep sequencing efforts within the EuroEPINOMICS Consortium may generate potentially interesting novel variants that warrant further investigation. In some cases, it might be necessary to obtain more phenotypic information, in other cases, segregation in the family might be of interest. Since many variants are rare in the general population, genotype-driven approaches are particularly attractive, i.e. research participants are selected based on genetic findings. This so-called “bottom up” approach allows for targeted studies without the time-consuming and expensive step of re-screening large patient cohorts. In the future, genotype-driven research efforts will likely become increasingly common, since it is unlikely that large-scale genomic studies alone will be able to sufficiently characterize rare genetic variants. However, approaching patients based on genetic research data raises important questions. Continue reading
Exomes on Twitter. Two different trains of thoughts eventually prompted me to write this post. First, a report of a father identifying the mutation responsible for his son’s disease pretty much dominated the exome-related twittersphere. In Hunting down my son’s killer, Matt Might describes his family’s journey that finally led to the identification of the gene coding for N-Glycanase 1 as the cause of his son’s disease, West Syndrome with associated features such as liver problems. The exome sequencing that finally led to the discovery was part of a larger program on identifying the genetic basis of unknown, putatively genetic disorders reported in a paper by Anna Need and colleagues, which is available through open access. This paper is an interesting proof-of-principle study that exome sequencing is ready for prime time. Need and colleagues suggest exome sequencing can find causal mutations in up to 50% of patients. By the way, a gene also that turned up again was SCN2A in a patient with severe intellectual disability, developmental delay, infantile spasms, hypotonia and minor dysmorphisms. This represents a novel SCN2A-related phenotype, expanding the spectrum to severe epileptic encephalopathies.
The exome consult. My second experience last week was my first “exome consult”. A colleague asked me to look at a gene list of a patient to see whether any of the genes identified (there were 300+ genes) might be related to the patient’s epilepsy phenotype. Since I wasn’t sure how to best handle this, I tried to run an automated PubMed search for combination of 20 search terms with a small R script I wrote. Nothing really convincing came up except the realisation that this will be an issue that we will be increasingly faced in the future: working our way through exome dataset after the first “flush” of data analysis did not reveal convincing results. Two terms that came to my mind were bioinformatic literacy as something that we need to improve and Program or be Programmed, a book by Douglas Rushkoff on the “Ten commands of the Digital Age”. In his book, he basically points out that in the future, understanding rather than simply using IT will be crucial.
The cost of interpretation is rising. The Genome Center in Nijmegen suggests on their homepage that by the year 2020, whole-genome sequencing will be a standard tool in medical research. What this webpage does not say is that by 2020, 95% of the effort will not go into the technical aspects of data generation, but into data interpretation. For biotechnology, interpretation will be the largest marketing sector.
So, what about epilepsy? ”50% of cases to be identified” sounds good for any grant proposal that I would write, but this might be a clear overestimate. Need and colleagues used a highly selected patient population and even in the variants they identified, causality is sometimes difficult to assess. We are maybe much further away from clinical exome sequencing in the epilepsies than we would like to admit. The only reference point we have for seizure disorders to date is large datasets for patients with autism and intellectual disability. While some genes with overlapping phenotypes can be identified, we would virtually be drowning in exome data without being capable of making sense of this.
10,000 exomes now. I would like to predict that after having identified some low-hanging fruits with monogenic disorders, 10,000 or more “epilepsy exomes” would have to be collected before making significant progress. It is, therefore, crucial not to be tempted by wishful thinking that particular epilepsy subtypes necessarily have to be monogenic, as in the case of epileptic encephalopathies or other severe epilepsies. Much of the genetic architecture of the epilepsies might be more complex than anticipated, requiring larger cohorts and unanticipated perseverance.
Remember Guthrie cards and the heel stick for newborn screening? It will be a thing of the past in 10 years replaced by methods performed through Next Generation Sequencing (NGS). NHGRI and NICHD have already committed to a $25M program for Next Generation Sequencing in Newborn Screening and first reports appear describing the value of exome sequencing in solving undiagnosed cases. However, these reports all leave clinicians working in the epilepsy clinic scratching their heads – this all sounds very good, but what can you offer your patients already, not just in 2-3 years?
265 genes at once. A team led by the EuroEPINOMICS researchers Johannes Lemke and Saskia Biskup has now evaluated the feasibility of targeted Next Generation Sequencing of a panel of epilepsy genes and the results published in Epilepsia last week are quite impressive. With their panel of 265 genes, they identified mutations in 16/33 patients with unclassified, presumably genetic epilepsy. While the overall yield of this candidate panel is probably lower than the impressive 50% in their pioneer study, these results clearly show that the general workflow in the epilepsy clinic is ready to shift from candidate gene screening to Next Gen panel analysis.
New and old genes identified. The list of genes identified in their screening is a mixed bag of epilepsy genes, many of which were identified in syndromes with a high degree of clinical suspicion including mutations in SCN1A, SCN2A and KCNQ3. Interestingly, some unlikely candidates also popped up. One patient with a clinical picture of Dravet Syndrome (DS) had a mutation in TPP1, the gene causative for Neuronal Ceroid Lipofuscinosis Type 2. This unexpected finding highlights another important “side-effect” of NGS: we will probably discover many unusual phenotypes for known disorders.
You wouldn’t think so, but panels are sometimes more thorough. Lemke and coworkers identify mutations in SCN1A in three patients with DS. This alone would not be all that remarkable. However, these three patients were previously reported to be negative for SCN1A by Sanger sequencing. This phenomenon is not new. In addition to identifying GABRA1 in SCN1A-negative DS, Mefford and colleagues also identified a mutation in SCN1A by exome in a patient with DS that was missed by conventional sequencing. While it is difficult to compare exome and conventional sequencing, these two anectodes at least suggest that NGS is not fairing any worse than conventional methods.
Targeted sequencing vs. exome. In the upcoming 12-24 months, we expect an intense debate on whether targeted sequencing is actually necessary or whether you could directly apply diagnostic exome sequencing. Targeted technologies – for now – have the advantage of the higher coverage, i.e. the eventual quality and completeness of candidate gene sequences higher than in exome studies. However, the field is evolving and the next, better technology might already be around the corner.