Category Archives: Publications

FAME – when phenotypes cross over but chromosomes don’t

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Crompton and colleagues recently published the clinical and genetic description of a large family with Familial Adult Myoclonic Epilepsy (FAME).  This phenotype is particularly interesting since it provides some insight into how neurologists conceptualize twitches and jerks.  It is also a good example that large families do not necessarily result in a narrow linkage region, particularly when centromeric regions are involved.

What is myoclonus?  Despite usually mentioned in the context of epilepsy, most people are inherently familiar with myoclonus. Most of us “twitch” when we fall asleep and sometimes experience this twitch as part of a dream.  These episodes are entirely normal and are called hypnic jerks, but they give people a good idea of what a sudden, brief, shocklike, involuntary movement caused by muscular contraction or inhibition would feel like.  Myoclonus in the setting of epilepsy is usually mentioned as part of a Juvenile Myoclonic Epilepsy (JME) or Progressive Myoclonus Epilepsy (PME).  Please note that both epilepsies use different endings to describe the twitch (“-us” vs. “–ic”).  This is mainly convention.  Basically, myoclonus is a brief shock-like twitch, which can affect almost every part of the body and can be due to dysfunctions in various regions in the Central Nervous System.

The neuroanatomy of twitching.  A motor command from the cerebral cortex has to pass through several steps prior to execution.  For example, the simple command of tapping a finger on the table surface is prepared by the cortex through several loops before being sent down your spine.  Accordingly, myoclonus can arise from different parts in the brain.  (1) The cortical myoclonus is due to a purely cortical source and can be seen in many forms of symptomatic myoclonus.  (2) The cortico-subcortical myoclonus is due to feedback from the cortex to other brain areas. This is the myoclonus we see in patients with JME.  Both variants may be seen on EEG since the cortex is involved.  (3) The subcortical-supraspinal myoclonus is generated in the brain stem or below and is responsible for phenomena such as hyperekplexia or startle disease.   Some forms of hyperekplexia, literally “exaggerated surprise”, are due to mutations in genes involved in glycinergic transmission and can be found in some isolated communities such as the Jumping Frenchmen of Maine.  (4) Finally, there is also spinal and peripheral myoclonus.

FAME – epilepsy or movement disorder?  Familial Adult Myoclonic Epilepsy (FAME) is an enigmatic familial disorder with the triad of myoclonus, tremor and seizures.  Several families have been described and two loci on 8q23.3-8q24.11 and 2p11.1-q212.2 for FAME have been established.  The underlying genes are still unknown.  Crompton and colleagues no describe a large six-generation family with FAME in Australia/New Zealand.  The familial disease usually starts with tremor in early adulthood in the affected family members, even though a wide range of age of onset is observed. Interestingly, only a quarter of all affected family members had seizures, which is in contrast to previous studies.  Therefore, FAME may actually be better characterized as a movement disorder with concomitant seizures rather than a familial epilepsy syndrome.  The authors also point out the difficulties distinguishing FAME from the much more common essential tremor (ET).  In particular, the well-described response to β-blockers seen in patients with ET can also be observed in some family members.

Figure 1. The candidate gene landscape of the chr2 FAME region. All genes were searched for the number of hits in PubMed for the listed search terms in an automated fashion. As usual in large linkage intervals, only few genes are known in the context of neurological disorders, while most genes are unknown.

The genetics of FAME.  Crossovers during meiosis usually lead to a progressive narrowing of the linkage interval in familial disorders.  However, the lack of crossover events leads to very large linkage intervals even in very extended families.  The family described by Crompton et al. links to the pericentromeric region of chromosome 2.  Pericentromeric regions usually have a low frequency of crossover events, and this phenomenon has also delayed the identification of other familial epilepsies such as Benign Familial Infantile Seizures with mutations in PRRT2.  The linkage region contains almost 100 genes and Figure 1 shows the “candidate gene landscape” in this region.  While some genes clearly classify as top candidate genes, the majority of the genes in this region are unknown in the context of epilepsy. Therefore, identification of the FAME gene will be exciting and provide us with novel insight on how genetic alterations may produce combined neurological phenotypes.

Be literate when the exome goes clinical

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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.

By 2020, probably more than 10 million genomes will have been sequenced. Data interpretation rather than data generation will represent the most pressing issue.

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.

Next Generation Sequencing as a diagnostic tool in the epilepsy clinic

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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.

Study by Lemke et al. demonstrating the usefulness of targeted NGS in patients with epilepsy. Unlike few other genetic technologies, targeted NGS is very likely to alter your work flow in clinic at short term.

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.

The surprising truth of your motivation for epilepsy genetics

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Why are we doing what we are doing? Academic research appears to be a rat race of high-strung egomaniacs fighting for grant money, impact factors and ultimately their scientific legacy. In this constant struggle you either make it or you don’t, you publish or perish, depending on how good you can elbow your way through. And finally, make no mistake, it’s all about the money. Unfortunately, many young researchers are given this dire, coldhearted perspective by senior scientists and supervisors. Your PhD either results in a Nature or Science paper or you’re gone. Family? Not my problem. Holidays? Why are you even asking. This blog post is about the hidden secrets of human motivation, trying to point out some basic fallacies in these arguments. My brief answer to this is: “This is so 1995…”

Party like it’s 1995. Just imagine we are back in 1995 and we were asked the following question. “I would like you to tell me our opinion about the possible success of two different online encyclopedias. Type A is financed by the world’s largest software company, which has dedicated a generous budget to this project that pays both a highly qualified staff of writers and an experienced management team. Type B is a voluntary encyclopedia with no budget, established through people dedicating their spare time. In 15 years from now, which online encyclopedia will still exist?” In 1995, there was probably not a single person who would have put his or her money on Encyclopedia B based on this description. However, Encyclopedia B has evolved into one of the world’s largest online knowledge repositories, while Encyclopedia A closed its doors for good in 2009.

Wikipedia vs. Encarta. If I tell you that Encyclopedia B is Wikipedia and Encyclopedia A is Microsoft’s Encarta, this story makes sense to you. Daniel Pink provides this example in his book “Drive”, which tries to explain the secrets of human motivation. In brief, in contrast to the prevalent belief that strong incentives such as money or titles are the main drivers of human motivation, this “carrot and stick” method only gets you so far and will produce people being productive for the reward, and not for the issue itself. Pink identifies three elements that are the main drivers of motivation, namely Autonomy, Mastery and Purpose. In brief, Wikipedia became what is today by enabling people to work autonomously, to engage their expertise and to feel a sense of purpose through a shared experience and feedback, something that millions of dollars by Microsoft could not buy.

Motivational theory. Pink’s arguments are nothing new. They are based on scientific investigations by Deci and Ryan in the 1970s, who conducted sophisticated psychological experiments to analyse human motivation and who identified these three elements as part of their self-determination theory of motivation.

Application to research. Uri Alon from the Weizman Institute has re-interpreted these results for the field of science in a freely available comment in Molecular Cell, identifying Competence, Autonomy and Social connectedness as the three elements that apply to science. Competence basically relates to working in an environment that is neither too boring nor too challenging. In research, we are mainly faced with leaving people with a task that is too challenging for their current knowledge level. For example, suggesting that a Young Researcher design a sophisticated genome-wide association study on pediatric pharmacology without any prior knowledge of biostatistics is too challenging, eventually decreasing motivation. Altering the project to a candidate gene screening will eventually  increase the researcher’s motivation, despite the possible lack of scientific ingenuity. However, in the end, the second option will be more productive for the team as the young investigator is capable of working at her or his level of competence. Autonomy refers to a related issue. You can only be motivated in science when you perceive a sense of independence and an intermediate level of structure. Not too structured and not too independent. The third strand of motivation in science is Social Connectedness. It’s the proverbial water cooler discussion, the environment that gives you a sense of belonging, the interesting paper that was pointed out by that guy next in the lab next door, the senior postdoc who has nothing to do with your project, but  who is happy to have a look at why your PCR isn’t working. Networks have been the main driver of scientific innovations over the past centuries, which is “Where good ideas come from”, as authors Steven Johnson puts it. Naturally, the science network arising from research consortia such as EPICURE or EuroEPINOMICS is much more than just a collection of scientists. These networks are organic entities and the ideal breeding ground for scientific innovation in the field.

The hidden secrets of motivation. How motivation works in science and how to choose projects that are ideally suited for you in epilepsy genetics.

When scientific projects are really well suited for you. Uri Alon goes on to re-interpret these three elements in the context of scientific projects, suggesting a so-called TOP model (Figure). Projects are particularly well suited for you if they manage to completely engage you, drawing on your talents, your passions and your goals. Epilepsy genetics of the future will be multifaceted with many different niches and subfields that might allow a broad range of scientists with different backgrounds and motivations to contribute. Touching upon diverse fields such as genetics, neuroscience, social sciences, public health, etc., researchers with “cross-over skill sets” will be crucial. The age of the lonely genius researcher hiding out in his secret lab to eventually emerge with a Nobel-prize winning flash of inspiration is over, if it has ever existed. The science of the future will be network science and “chance favors the connected mind”.

Balanced translocations in neurodevelopmental disorders

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Major genomic rearrangements without loss of genetic material — balanced translocations — are infrequently found in patients with neurodevelopmental disorders but also in unaffected individuals. Genome sequencing and break point analysis of 38 patients now show a fine-grained view of the implication of such chromosomal abnormalities in neurodevelopmental disorders.

Most balanced translocations in patients with autism or ID are non-recurrent and leave the geneticists who want to understand cause and effect scratching their heads as the overall genomic content appears normal as all genes are present at first glance.

Study design of the recent study by Talkowski et al. on break point sequencing in balanced translocations in neurodevelopmental disorders

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Probing autism for hidden autosomal recessive mutations using exome sequencing

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Study design applied by Chahrour et al., PLOS Genetics 2012 to identify autosomal recessive genes in non-syndromic autism.

Autosomal recessive neurological disorders are usually distinct and severe diseases that result from the combination of two recessive alleles transmitted by parents. Autosomal recessive disorders are rare, but collectively account for a significant fraction of the genetic morbidity.  With respect to neurodevelopmental disorders including epilepsy, neurometabolic disorders and storage disorders frequently result in complex phenotypes that also comprise intellectual disability, behavioural issues and seizures. Particularly in populations with a high degree of consanguinity such as certain Arab populations, recessive disorders represent a major challenge.

Is autism a recessive disorder? Some recessive disorders might present with atypical phenotypes and are “hypomorphic“. Given that recessive disorders may appear sporadic, i.e. only a single child is affected, it is virtually impossible to distinguish the inheritance pattern in a single individual, particularly in small families. Accordingly, the question frequently arises, if and to what extent neurodevelopmental disorders may either be atypical presentations of known recessive disorders or may be due to novel, as yet unknown recessive mutations. Continue reading →

Exome sequencing in autism – the big picture and implications for epilepsy genetics

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The recent weeks have produced several large studies on exome sequencing in autism and we have previously commented on three publications which appeared back-to-back in Nature. Here I summarize these findings, which advanced our understanding of the genetic architecture of autism  in the light of a recent, equally comprehensive study by Iossifov et al. published in Neuron. The enormous amount of genetic variation and de novo mutations in the human genome reported demonstrate the possibilities and difficulties of exome sequencing studies and require new study design.  Up to 10% of cases of autism appear due to de novo mutations, indicating a significant, but modest contribution comparable to the effect of copy number variations.

Study by Iossifov et al., 2012. The authors performed exome sequencing in families with an affected proband and at least one unaffected sibling (quads).  After stringent filtering they estimate the burden of de novo mutations and indels, finding an elevated rate of likely gene disrupting mutations in probands (17%) compared to unaffected siblings (8%). The rate of all missense mutations in contrast to the gene-disrupting mutations was comparable in probands and siblings. De novo mutations are common in affected and unaffected individuals and additional criteria are required to distinguish causal from benign de novo mutations.  Nevertheless, the rate of gene-disrupting mutations in probands with autism is two-fold higher compared to unaffected siblings, suggesting a modest contribution of these mutations to the overall pathogenesis of autism. The authors further analyze molecular pathways that these genes are implicated in and suggest that many products of genes implicated in autism are functionally associated with the Fragile-X-Mental-Retardation Protein (FMRP).  In line with previous studies, they estimate 300-400 autism susceptibility genes.

Five novel candidate genes. In conjunction with the study by Neale et al., O’Roak et al. and Sanders et al., recurrent gene-disrupting mutations have been identified in 5 genes, namely, SCN2A, CHD8, KATNAL2, DYRK1A and POGZ. Among these five genes, only SCN2A and DYRK1A have previously been implicated in neurodevelopmental disorders.  SCN2A is well known to the epilepsy community and codes for the alpha-2 subunit of the voltage-gated sodium channel. SCN2A is known to cause Benign Familial Neonatal-Infantile Seizures (BFNIS). It should be pointed out that none of the two probands with autism carrying mutations in SCN2A had seizures and the connection between axon initial segment dysfunction and autism in not clear. DYRK1A codes for the dual-specificity tyrosine-(Y)-phosphorylation regulated kinase 1A and represents the main candidate gene for intellectual disability in Trisomy 21. The role of the other three genes is not clear. CHD8 codes for chromodomain helicase DNA binding protein 8 involved in chromatin remodeling. POGZ codes for the pogo transposable element with ZNF domain involved in transcriptional regulation. The role of KATNAL2 coding for the katanin p60 subunit A-like 2 is unknown.  In summary, given the candidate genes from CNV studies in autism including many genes involved in synapse functions, these are not the candidate genes you would expect.  The authors point this out, indicating the lack of overlap in candidate genes from CNV and exome studies in autism.

Common findings in all four studies on exome sequencing in autism. Iossifov et al. summarize that the frequency of de novo mutations is elevated in children with older parents, that de novo gene disrupting mutations are twice as frequent in probands compared to siblings and that the role of all missense mutations in general irrespective of their putative functional role is not significant or marginal.  In summary, the role of de novo mutations in autism can be compared to the role of large Copy Number Variations (up to 10% of cases).  Given the vast expectations put into exome sequencing studies, these results are disappointing. Theoretical predictions suggest a higher rate of de novo mutations in autism and the reasons for this gap are as yet unknown. In addition, these studies highlight the difficulties to distinguish pathogenic from accidental variation, an issue that will be central to the upcoming studies in epilepsy research.

Implication for epilepsy genetics and EuroEPINOMICS. The autism studies provide a template for the EuroEPINOMICS projects, particularly the studies, which sequence probands and parents (trios). In contrast to the “naive” assumption that a causative mutation can be identified in every patient, it will be difficult to tell the pathogenic mutation from benign variation. Assuming that the genetics of various epilepsies is comparable to the genetic architecture of autism, the pathogenic role of identified variants would need to be shown through (a) identification of genes already implicated in neurological disorders, (b) functional studies or (c) statistical evidence. Functional studies will be difficult to implement unless the identified genes fall within pathways for which functional assays are established (e.g. ion channels) and statistical evidence, demonstrating that de novo mutations in a given gene are associated with epilepsy will require large cohorts. From the autism studies, we can expect that using a trio-based design, we will identify likely pathogenic de novo mutations in 10% of probands with epilepsy. Exome sequencing is not the final genetic study that will identify the genetic basis of the majority of patients, but only the beginning for upcoming genome-wide sequencing methods with increasing coverage of the genome that can be interpreted in the presence of a growing body of exome data for neurodevelopmental disorders including autism and intellectual disability. The pick-up rate for other study designs including sequencing of families and sibling pairs is difficult to estimate. However, exome sequencing studies have been particularly successful in this field of genetics.

Some may argue that the outlook for epilepsy studies is rather bleak given the low expected frequency. We don’t. If some similarities between autism, ID and epilepsy are present, exome sequencing studies using a trio-based design have the unique possibility to detect causative mutations in up to 10% of patients and significantly enhance our understanding of various epilepsy syndromes. The prerequisite for these studies, however, is careful phenotyping and biobanking for follow-up studies and further increase in the sequence data generation and processing.

Exome sequencing for neurological syndromes

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Model of SCN2A protein from Modbase. Its lower half is the membrane region, which can be seen in the distribution of carbon (white).

SNC2A plays a significant role in autism reported one of three recent exome sequencing studies [1].  We were enthusiastic but others – Mike Eisen in particularly – were critical about the claim. Statistically, his analysis is correct but there is context around SCN2A that should be considered. First, it was already shown to be implicated as early as 2003[2]. The new study reconfirms the finding and provides new evidence corroborating the previous results. Soft factors, particular its known expression in the brain and its role in epilepsy would possibly make it an interesting finding even if it would have been detected in a single case.

Ben Neale, the first author of one of the studies summarized the findings in a recommended blog post. Complex diseases are complex. If years and years of research found a syndrome to be influenced by many factors, is hard to characterize, no sequencing effort no matter how deep find a simple mutation explaining most of the cases – or even a sizable part.

Some of the experiments performed in the EuroEPINOMICS consortium are close in design to the three autism studies. They should provide us with expectations and update us on experimental standards and statistical standards. And teach us some modesty.