University of Groningen Genotyping and phenotyping epilepsies of childhood Vlaskamp, Danique

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Genotyping and phenotyping epilepsies of childhood

Vlaskamp, Danique

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525699-L-sub01-bw-Vlaskamp 525699-L-sub01-bw-Vlaskamp 525699-L-sub01-bw-Vlaskamp 525699-L-sub01-bw-Vlaskamp Processed on: 29-10-2018 Processed on: 29-10-2018 Processed on: 29-10-2018

Processed on: 29-10-2018 PDF page: 1PDF page: 1PDF page: 1PDF page: 1

Genotyping and phenotyping

epilepsies of childhood

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Printed by Ipskamp Printing, Enschede, the Netherlands

ISBN 978-94-034-1144-6 (printed version)

978-94-034-1143-9 (e-book)

This research was funded by the Junior Scientiﬁ c Masterclass.

Unrestricted travel grants were received from the Dutch Society of Child Neurology, Jo Kolk Foundation (VVAO), the Research School of Behavioural and Cognitive Neurosciences (BCN). Conference attendances were ﬁ nancially supported by the BCN.

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Genotyping and phenotyping

epilepsies of childhood

Proefschrift

ter verkrijging van de graad van doctor aan de Rijksuniversiteit Groningen

op gezag van de

rector magniﬁcus prof. dr. E. Sterken en volgens besluit van het College voor Promoties.

De openbare verdediging zal plaatsvinden op woensdag 05 december 2018 om 14.30 uur

door

Danique Rienke Maria Vlaskamp

geboren op 15 mei 1991

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Prof. dr. O.F. Brouwer Copromotores Dr. P.M.C. Callenbach Dr. P. Rump

Beoordelingscommissie Prof. dr. V.V.A.M. Knoers Prof. dr. H.P.H. Kremer Prof. dr. K.P.J. Braun

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COVER

The tree on the cover of this thesis symbolizes the relationship between the genotype and the phenotype

of epilepsies of childhood.

The beautiful tree has deeply anchored, widely spreading roots (genotype) that grow a new ﬂowering tree with a unique pattern of branches,

leaves and blossoms (phenotype).

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Paranimfen

Nienke te Grootenhuis Wieke Eggink

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7

Chapter 1

Introduction

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Processed on: 29-10-2018 PDF page: 10PDF page: 10PDF page: 10PDF page: 10 I am about to discuss the disease called “sacred.” It is not, in my opinion, any more divine or more sacred

than any other diseases, but has a natural cause…

Its origin, like that of other diseases, lies in heredity... The fact is that the cause of this aﬀection is... the brain...

My own view is that those who ﬁrst attributed a sacred character to this malady were like the magicians, puriﬁers, charlatans, and quacks of our own day... So that there is no need to put the disease in a special class and to consider it more divine than the others...

Each has a nature and a power of its own; none is hopeless or incapable of treatment.1

Hippocrates, 460–370 BC, on epilepsy

Hippocrates was revolutionary for his time in arguing that the origin of epilepsy lies in ‘heredity’. Although hereditary does not always equal genetic, we now have robust evidence that genetic variants can cause or contribute to epilepsy. However, we still have a long way to go to fully understand the intriguing role of genetics in epilepsy.

To comprehend the current challenges in epilepsy genetics addressed in this thesis, it is helpful to learn more about epilepsy phenotyping and genotyping. Whereas epilepsy phenotyping concentrates on describing the clinical presentation, epilepsy genotyping focuses on identifying the underlying genetic cause. Integration of information on epilepsy phenotype and genotype is important in clinical practice and research settings in order to ﬁnd new genes and risk factors for epilepsy, to better understand the disease and its presentation and to improve its management and outcome.

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11

EPILEPSY PHENOTYPING

An epileptic seizure is deﬁned as a transient occurrence of signs and/or symptoms due to abnormal

excessive or synchronous neuronal activity in the brain.2_{Seizures can be provoked by acute}

disturbances in the body, such as hypoglycemia or acute infection, or can occur unprovoked. Patients are diagnosed with epilepsy if they present with any of the following three conditions: 1. at least two unprovoked seizures occurring >24 hours apart, 2. one unprovoked (or reﬂex) seizure and a probability of further seizures in the next 10 years similar to the general recurrence risk after two

unprovoked seizures (at least 60%), or 3. a diagnosis of an epilepsy syndrome.3_{Epilepsy is diagnosed}

in 41-87 children per 100,000 children each year.4

Epilepsy is not a single disease entity, but should be considered as a group of disorders. Its presentation, etiology, management and prognosis can vary significantly for the different epilepsies. Epilepsy therefore warrants further classification for clinical and research purposes. The International

League Against Epilepsy (ILAE) has made several classiﬁcation guidelines.5–11_{In the most recent}

guideline from 2017, they recommended classifying epilepsy at three consecutive levels: 1. seizure

type, 2. epilepsy type, and 3. epilepsy syndrome.12_{The ﬂowchart in Figure 1 demonstrates how to}

classify epilepsies using this three-step method. Depending on the availability of clinical information, epilepsy can be classiﬁed up to level 1, 2 or 3.

1. Seizure type. Epileptic seizures should be classiﬁed based on their onset as focal, generalized

or unknown.12,13_{Epilepsy is a disorder involving neuronal networks and all seizures are}

hypothesized to occur somewhere within a network.14,15_{Focal seizures are limited to networks}

within one hemisphere, while generalized seizures rapidly engage bilaterally distributed

networks.16_{Both clinical and electroencephalogram (EEG) data can help to distinguish focal}

and generalized seizures. If more detailed clinical information on the seizures is available, they can be further classiﬁed based on the level of awareness (for focal seizures only) and

by describing their ﬁrst feature.12,13_{Focal seizures can evolve to bilateral tonic-clonic seizures}

(previously called ‘secondary generalized seizures’).12,13,17

2. Epilepsy type. Since individuals can have both focal and generalized seizures, a second level of classiﬁcation has been introduced: epilepsy type. Epilepsy type can be focal, generalized or

combined generalized and focal.12

3. Epilepsy syndrome. To diagnose the epilepsy syndrome, one should also consider the setting in which seizures occur. This setting includes the patient’s gender, age at seizure onset, developmental course, family history, and results from additional investigations such as EEG and imaging. Recognition of a distinctive clinical and EEG pattern allows a syndrome

diagnosis.12

INTRODUCTION

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>t z ^/ E d/ &z d, W /> W ^z d /K >K ' z ^d Z h dh Z > ' E d / /E & d/ K h ^ D d K >/ /D D h E h E <E K t E ϭ ͘ ^ / h Z d zW Ϯ ͘ W /> W ^z d zW &K > KŶůǇ ĨŽĐĂů ƐĞŝǌ Ƶ ƌĞƐ h E <E K t E ' E Z >/ KŶůǇ ŐĞŶĞƌĂůŝǌ ĞĚ ƐĞŝǌ ƵƌĞƐ ' E Z >/ E & K > ŽƚŚ ĨŽĐĂů ĂŶĚ ŐĞŶĞƌĂůŝǌĞĚ ƐĞŝǌƵƌĞƐ ϯ ͘ W /> W ^z ^ zE Z K D K E d yd 'ĞŶĚĞƌ ͕Ă ŐĞ Ăƚ ƐĞŝǌƵƌ Ğ ŽŶƐ Ğƚ͕ ĚĞǀĞůŽƉŵĞŶƚ͕ ŝŶƚĞůůĞĐƚ͕ ĐŽŵŽƌ ďŝĚŝƚŝĞƐ͕ ĨĂŵŝůǇ ŚŝƐƚŽƌ Ǉ K d, Z & /E /E ' ^ ZĞƐƵůƚƐ Ĩƌ Žŵ ŝŶǀĞƐƚŝŐĂƚŝŽŶƐ ;ŝŵĂŐŝŶŐ͕ĞůĞĐƚƌ ŽĞŶĐĞƉŚĂůŽŐƌ ĂŵͿ W /> W ^z ^z E Z K D / ' E K ^/ ^ &K >^ / h Z ^ĞŝǌƵƌ Ğ ǁ ŝƚŚ ŝŶǀŽůǀĞŵĞŶƚ Ž Ĩ ŶĞƚǁŽƌ ŬƐ ŝŶ Ž ŶĞ ŚĞŵŝƐƉŚĞƌ Ğ ' E Z >/ ^ / h Z ^ĞŝǌƵƌ Ğ ǁ ŝƚŚ ŝŶǀŽůǀĞŵĞŶƚ ŽĨ ŶĞƚǁŽƌ ŬƐ ŝŶ ďŽƚŚ ŚĞŵŝƐƉŚĞƌ ĞƐ h E <E K t E hŶŬŶŽǁŶ Ž ƌ ƵŶĐůĂƐƐŝĨŝĂďůĞ ƐĞŝǌƵƌ Ğ K Ŷ ƐĞ ƚ t Z E K d t Z D K dK Z ƵƚŽŵ ĂƚŝƐŵ ͬ ĂƚŽŶŝĐ ͬ ĐůŽ Ŷ ŝĐ ͬ ƐƉ ĂƐ ŵƐ ͬ ŚǇƉĞ ƌŬŝŶĞ ƚŝĐ ͬ ŵ ǇŽĐ ůŽ Ŷŝ Đ ͬ ƚŽŶŝ Đ E K E ͲD K dK Z ƵƚŽŶŽŵ ŝĐ ͬ ďĞ ŚĂǀ ŝŽƌ ĂƌƌĞ Ɛƚ ͬ ĐŽ ŐŶŝƚŝǀĞ ͬĞ ŵŽ ƚŝŽ Ŷ Ăů ͬ ƐĞ ŶƐŽƌǇ ǁ Ăƌ ĞŶ ĞƐ Ɛ &ŝ ƌƐ ƚĨ ĞĂ ƚƵ ƌĞ D K dK Z dŽ Ŷ ŝĐ ͬ ĐůŽ Ŷ ŝĐ ͬ ƚŽ Ŷ ŝĐͲĐůŽ Ŷ ŝĐ ͬ ŵ ǇŽĐ ůŽ Ŷŝ Đ ͬŵ ǇŽ Đů ŽŶŝ ĐͲ ƚŽŶŝ ĐͲ Đů ŽŶŝ Đ ͬŵ ǇŽĐ ůŽ Ŷŝ ĐͲ ĂƚŽ Ŷ ŝĐ ͬ ĂƚŽ Ŷ ŝĐ ͬ Ğ Ɖ ŝůĞ Ɖ ƚŝĐ ƐƉĂƐŵ E K E ͲD K dK Z dǇƉ ŝĐĂů Ž ƌ Ăƚ ǇƉ ŝĐĂů ĂďƐĞ ŶĐĞ ͬ ŵǇŽ ĐůŽ Ŷ ŝĐ ͬ ĞǇĞ ůŝĚ ŵǇŽ ĐůŽ Ŷ ŝĂ D K dK Z dŽ Ŷ ŝĐͲĐůŽ Ŷ ŝĐ ͬ ĞƉ ŝůĞƉ ƚŝ Đ ƐƉĂƐŵ Ɛ E K E ͲD K dK Z Ğ ŚĂ ǀŝ ŽƌĂ ů ƌƌĞ Ɛƚ >t z^ / E d/& z KD KZ / /dz &Ž ĐĂ ůƚ Ž ď ŝůĂ ƚĞ ƌĂ ůƚ Ž Ŷ ŝĐ ͲĐ ůŽ Ŷ ŝĐ ƐĞ ŝǌ Ƶ ƌĞ Ž Ƶ ƌƐ Ğ W /> W ^z dz W F igur e 1: Flow char t f

or the classiﬁcation of epilepsies f

ollowing a thr ee st ep method . M odiﬁed af ter F isher et al . 2017 & Scheﬀ er et al . 2017. 12,13

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13

Comorbidities

In parallel with classifying the epilepsy from seizure type to epilepsy syndrome, it is important to identify comorbidities. Examples of comorbidities include intellectual disability, movement disorders, autism spectrum disorders and other psychiatric and behavioral disorders. Pro-active screening for the presence of comorbidities is vital because it not only helps in epilepsy syndrome and etiology diagnosis, it also enables appropriate management of comorbidities that can improve quality of life of patients and their families.

Etiology

During the whole process of phenotyping epilepsies, it is also essential to try to identify the etiology. Understanding etiology can prevent unnecessary further diagnostic investigations and may lead to better counseling, management and, possibly, outcome. Six epilepsy etiology groups have been

proposed: genetic, structural, infectious, metabolic, immune and unknown.12_{For some epilepsies,}

etiology can be classiﬁed into more than one etiology category. For example, pyridoxine-dependent epilepsy due to a pathogenic ALDH7A1 variant has a metabolic and genetic etiology while DEPDC5-gene-related epilepsy with a cortical malformation has a genetic and structural etiology. For the genetic etiology, epilepsies can be considered genetic based on the presenting phenotype or

family history even when the variant itself has not yet been identiﬁed.12

Developmental and epileptic encephalopathy

In some epilepsies, “the epileptic activity itself may contribute to severe cognitive and behavioral

impairments that is beyond what might be expected from the underlying pathology alone”11_,

deﬁned as an epileptic encephalopathy (EE). There are many diﬀerent EEs that can occur in infancy

and childhood, and these are often genetic.18_{However, developmental slowing and regression}

often precede seizure onset and cognitive deﬁcits can persist after seizure remission. Therefore, the term developmental and epileptic encephalopathy (DEE) was introduced to describe the encephalopathies where the underlying genetic condition and the seizure activity together lead

to developmental plateauing or regression.12_{An example of a DEE is SYNGAP1-encephalopathy,}

which is studied in this thesis.

EPILEPSY GENOTYPING

Although the role of genetics in epilepsies has been appreciated since antiquity, research on this role only started the last century and the growth in knowledge since then has been revolutionary. What follows is a historical overview of the diﬀerent consecutive study types that have led to our current understanding of the complex role of genetics in epilepsies.

INTRODUCTION

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Family studies

The ﬁrst evidence for epilepsy as a hereditary disease came from clinical family studies performed in the end of the last century. Family aggregation studies showed a 3-7 times higher incidence of

epilepsy in siblings and oﬀspring of patients with epilepsy than expected by chance.19–21_{Of patients}

with epilepsy, 5-21% have at least one ﬁrst-degree relative sharing a diagnosis of epilepsy.22–25

Furthermore, twin studies revealed a higher concordance for epilepsy among monozygotic versus

dizygotic twins.26–28_{These studies together indicated that epilepsy has a genetic basis, but its}

nature and extent are unknown. Nowadays, family studies are mainly performed to evaluate the phenotypic spectrum of familial epilepsy syndromes, e.g. genetic epilepsy with febrile seizures

plus29_{, or to identify new familial syndromes, e.g. familial posterior quadrant epilepsies.}30

Searching for epilepsy candidate genes

Following these family studies, diﬀerent approaches were used to identify the epilepsy candidate genes and their position within the human genome (called locus). Two important study types, linkage analysis and association studies, have been performed since the eighties and nineties of the last century, respectively.

Linkage studies.

Linkage analysis can be used in families to evaluate the segregation of epilepsy with genetic markers with a known position in the genome. This technique is based on the principle that genes that reside closely together are linked during meiosis. By identifying the genetic marker that is carried by affected relatives but not by non-affected relatives, the linked gene or locus for epilepsy can be identified. The first locus for epilepsy (juvenile myoclonus epilepsy on chromosome 6) was identified in 1989, and this was followed by the discovery of many other loci for this and other

epilepsy syndromes.31,32_{Linkage analysis is still used to identify new loci for epilepsy.}32

Association studies.

Association studies aim at identifying alleles that increase the risk for developing epilepsy, called ‘susceptibility alleles’. In these studies, the statistical association between a specific allele and an epilepsy syndrome is calculated by comparing the presence of this allele in large numbers of patients versus controls. Alleles found significantly more often in patients are considered susceptibility alleles. The many association studies performed to date have consistently identified a few susceptibility loci for different generalized epilepsies (1q43, 2p16.1, 2q22.3 and 17q21.32), focal and generalized epilepsy and febrile seizures (2q24.3 including SCN1A), febrile seizures (2q24.3, 11p14.2 and 12q21.33)

or focal and generalized epilepsy (4p15.1).33_{Focusing on epilepsy treatment, an HLA-B*1502 allele}

has been associated with the occurrence of carbamazepine-induced Stevens-Johnson syndrome.34

Unfortunately, many other ﬁndings from association studies could not be replicated, mainly due to low statistical power. Future collaboration between epilepsy research groups is necessary to increase the number of participants and thereby increase the statistical power to identify new loci

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Molecular genetic studies

Advances in molecular genetic techniques that disentangle the human genome in greater detail together with more adequate epilepsy phenotyping have resulted in the identiﬁcation of many new genes for epilepsy. Table 1 gives an overview of the diﬀerent molecular techniques that are currently available to detect genetic variants at all levels of the human genome. Here, we will discuss the three most important techniques in terms of identifying new genes and loci for epilepsy.

Sanger sequencing.

In 1995, the first disease-causing gene variant for epilepsy (previously called a mutation) was identified using Sanger sequencing in a locus identified by linkage analysis. A missense mutation in the CHolinergic Receptor Nicotinic Alpha 4 Subunit gene (CHRNA4) was found in a large Australian

family with autosomal dominant nocturnal frontal lobe epilepsy.37_{Sanger sequencing, invented}

in 1977, has dominated genetic diagnostics for decades.38_{Many disease-causing variants in}

other genes (SCN1B39, KCNQ240, KCNQ341, SLC2A142, SCN1A43, GABRA144, and GABRG245) for other dominantly inherited epilepsies have been found following identification of their loci using linkage analysis. Currently, Sanger sequencing is mainly used to sequence a single gene selected based on a family history with variants in this gene or on an urgent need for specific treatment (such as SCL2A1 for glut1 deficiency requiring treatment with a ketogenic diet).

Microarray.

Microarray analysis has been a widely available technique since the early 2000’s. Microarray analysis

detects losses (deletions) or gains (duplications) of relatively small parts of the chromosomes.46

These deletions and duplications are called copy number variants (CNVs). There are two types of CNVs that can underlie epilepsy: recurrent and non-recurrent CNVs.

Recurrent CNVs occur at speciﬁc sites of the genome due to the recombination of DNA between highly homologous chromosomal regions (non-allelic homologous recombination). During meiosis, these highly homologous regions can misalign and an unequal crossover can occur, resulting in deletions

or duplications of the DNA. These deletions and duplications can include single or multiple genes.47

Recurrent CNVs are associated with diﬀerent syndromes. For example, a 15q11.2-q13 microdeletion is associated with Angelman and Prader-Willi syndrome (OMIM 105830 and 176270, respectively) and a 22q13.33 microdeletion with Phelan-McDermid Syndrome (OMIM 606232). Epilepsy might occur in the context of these microdeletion or microduplication syndromes.

Non-recurrent CNVs are unique for every individual. These CNVs occur due to unequal crossover of DNA during meiotic (or less frequently mitotic) DNA repair processes with inconsistent breakpoints

throughout the genome in regions with limited homology.47_{Identifying a critical region of overlap}

(CRO) between such non-recurrent CNVs of patients with similar phenotypes can elucidate new genes for epilepsy. For example, GRIN2A was identiﬁed as a candidate gene for epilepsy based on

the identiﬁcation of a CRO betewen 16p13.2 deletions in three patients with similar phenotypes.48

INTRODUCTION

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Processed on: 29-10-2018 PDF page: 16PDF page: 16PDF page: 16PDF page: 16 Subsequently, disease-causing variants in GRIN2A were identiﬁed in patients with epilepsy within

the epilepsy-aphasia-spectrum.49–51

Several studies have shown that causal CNVs are present in ~5% of patients from diﬀerent cohorts

with generalized epilepsy, focal epilepsy or epileptic encephalopathy.52–55_{In addition, a few recurrent}

CNVs have been found signiﬁcantly more often in patients with epilepsy compared to controls, and these are now referred to as susceptibility CNVs because they can increase the risk of developing epilepsy. Deletions on chromosomes 1q21.1, 15q11.2, 15q13.3, 16p11.2 and 16p13.11 and duplications

on chromosome 16p11.2 are well-known examples of susceptibility CNVs.52,55–57

Next generation sequencing.

With the introduction of Next Generation Sequencing (NGS) in 2008-2009, we entered a new, very exciting era in epilepsy genetics research and diagnostics. NGS enables sequencing of multiple genes, of the whole exome or of the whole genome in a single test run. This has enabled two major advances. First, variants can be identiﬁed in genes that would otherwise not have been selected for genetic testing. NGS may therefore identify many novel candidate genes for epilepsy and, indeed,

the list of epilepsy candidate genes has grown tremendously since its introduction.58–60_Second,

gene-related phenotypic spectra can be expanded when gene variants are found in patients with phenotypes that were not yet associated with this gene. For example, SYNGAP1 was identiﬁed as a

gene for an epileptic encephalopathy after it was ﬁrst identiﬁed as a gene for intellectual disability.61,62

GENETIC DATA INTERPRETATION

The genome of each individual, affected or non-affected, differs at 4-5 million sites from the

reference human genome and harbors 2,100 to 2,500 structural genetic variants.63_{Not surprisingly,}

the genome-wide genetic techniques discussed above also identify numerous variants that are not associated with disease. Therefore, our challenge is to interpret these variants and pinpoint the disease-causing variant in our patients. International guidelines have been established to classify variants based on their pathogenicity as benign, likely benign, of unknown signiﬁcance,

likely pathogenic or definitely pathogenic.64_{Variants are first filtered based on their prevalence in}

national and international population databases such as the genome of the Netherlands (GoNL)65_,

genome Aggregation Database (gnomAD)66_{, 1000 Genomes}63_{, dbSNP}67_{and the database for}

genomic variants (DGV)68_{. A variants is considered likely benign if it is present in more than 1% of}

the population.64_{For the variants that are not considered likely benign, the variant’s inheritance,}

location, in silico predicted or functionally tested eﬀects, presence in other patients with similar

phenotypes are evaluated to determine its pathogenicity.64_{With the introduction of whole exome}

sequencing, and possibly whole genome sequencing in the near future, the interpretation of genetic testing is becoming more diﬃcult and time-consuming as ever more variants are being identiﬁed.

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17

T

able 1:

Genetic t

echniques and their indications

, advantages , disadvantages Human genome le v e l for detec ting var ian ts Te st Va ri a ti o n s dete ct e d Ty pical indicat ion A dvan tages Disadvan tages Ka ry o ty p in g La rg e chr o m os o mal re ar ra nge me n ts Su spicion of a chr o m os o mal di so rd er - Ab le t o det ec t r ing chr o m o so m es an d b alanc ed re ar ra nge me n ts - L o w r es o lution c o ver age of genom e - Po ss ibilit y of inciden tal fi n d ing s for di se as es o th er than epileps y Micr o ar ra y C N Vs , r egion s of homo zy go si ty , unip ar en tal is o d is o m y Ep ileps y “ p lu s” (d evelopm en tal dela y, b eh aviora l pr oble m s o r d ysm o rp h isms ) - High r es o lution co ve rage of ge nome - Mi ss es b alanc ed chr o m o so mal re ar ra nge me n ts - Po ss ibilit y of inciden tal fi n d ing s for di se as es o th er than epileps y Sa nger se q u en ci ng Se qu en ce v ar ian ts in s ingle or up t o a few gen es Ep ile p sy sy n d ro m e kn ow n t o b e c au se d by a s ingle gen e va ria n t - N o p o ss ibilit y of in ci de n ta l fi nd in g s due t o c ar ef u l se le ct ion of gen es - Pr e-se le ct ion of gen e b as ed on clinic al pr es en ta tion i s n ec ess ar y - Ti m e- an d c o st -e xp en si ve t o s equenc e g en es in di vi duall y - N o t p o ss ib le t o det ec t in tr ag enic C N Vs Ep ile p sy gen e p an el Se qu en ce v ar ian ts within a s u bs et of ge nes G en etic epileps y - Lo w p o ss ibilit y of in ci de n ta l fi nd in g s due t o c ar ef u l se le ct ion of gen es - G en e p an el s n ee d t o b e up da te d fr eq uen tl y - So m e lab o ra to ri es : no t p o ss ib le t o det ec t i n trage n ic C N Vs Whol e ex o m e se q u en ci ng with epileps y fi lt er Se qu en ce v ar ian ts in th e e xom es, but on ly a n al yz es of subs et o f g en es G en etic epileps y - Lo w p o ss ibilit y of in ci de n ta l fi nd in g s due t o c ar ef u l se le ct ion of gen es, which c an b e ex te nde d e as ily - So m e lab o ra to ri es : no t p o ss ib le t o det ec t i n trage n ic C N Vs Whol e ex o m e se q u en ci ng Se qu en ce v ar ian ts within in th e ex o m es G en etic epileps y without a gen e va rian t iden tifi e d u sing a gen e p an el - N o n ee d for s ele ct ion of gen es if no clinic al clu e Whol e ge nome se q u en ci ng Se qu en ce v ar ian ts an d C N Vs in th e whole ge nome (int ro ns + e xo n s) C u rr en tl y onl y app lie d in re se ar ch se tt in g s - N o n ee d for s ele ct ion of gen es if no clinic al clu e - Da ta a vailab le t o det ec t i n tr on ic var ian ts an d e xo n ic co py numb er v ar ian ts - N o t yet p oss ib le t o re liab ly in te rp ret th e re lev anc e of in tr onic v ar ian ts - Po ss ibilit y of inciden tal fi n d ing s for di se as es o th er than epileps y INTRODUCTION

1

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CONCEPTUALIZING EPILEPSY GENETICS

Over the last few decades our understanding of the genetic basis of epilepsies has increased tremendously and this knowledge can be summarized in three important concepts.

Epilepsy gene products are part of different pathways

When the ﬁrst ion-channel-coding genes for epilepsies were discovered, the idea was raised that

epilepsy could be channelopathy.60_{This concept has however been overturned by the discovery}

in 2002 of LGI1, a non-ion-channel-coding gene for autosomal dominant lateral temporal lobe

epilepsy.69_{Following the identiﬁcation of many non-ion-coding-channel genes for epilepsy, we}

realized that epilepsy gene products can be part of different pathways and thereby affect neuronal function differently. These pathways include DNA repair, transcriptional regulation, axon myelination, metabolite and ion transport, peroxisomal function, cell-cell adhesion, neurite formation,

interneuron migration, apoptosis and blood-brain barrier transport.70_{Notably, gene products}

within the same pathway can often result in a similar epilepsy phenotype. The identiﬁcation of DEPDC5 as the causal gene for focal epilepsy and cortical brain malformations in the mammalian target of rapamycin (mTOR) pathway, known to be involved in tuberous sclerosis, nicely illustrates

this.71,72_{Even more striking, sequencing of other genes in the mTOR pathway identiﬁed variants in}

NPRL2 and NPRL3, both associated with a similar phenotype.73

Epilepsy encompasses different modes of inheritance

We have learned that epilepsy can be inherited following diﬀerent modes of inheritance. Although some epilepsies are caused by a single gene variant (monogenic inheritance), the majority of epilepsies follow a complex inheritance where many genes (polygenic inheritance) or a combination of genes

and environmental factors (multifactorial inheritance) increase the risk of developing epilepsy.74_In

monogenic epilepsies, the disease-causing gene variant does not necessarily lead to disease in all relatives carrying this variant, a phenomenon called incomplete penetrance. Alternatively, a relative might be aﬀected yet not carry the disease-causing variant, a condition referred to as a phenocopy.

Phenotypic and genetic heterogeneity play a key role in epilepsy

Phenotypic heterogeneity (also called pleiotropy) refers to a single genetic disorder leading to diﬀerent epilepsy syndromes: e.g. mutations in KCNQ2 can cause benign neonatal and infantile epilepsy

as well as severe neonatal epileptic encephalopathy.75,76_{Genetic heterogeneity means that a single}

epilepsy syndrome can be caused by pathogenic variants in diﬀerent genes. For example, benign

infantile epilepsy can by caused by variants in KCNQ2, KCNQ3, SCN2A or PRRT2.75_{For some genes,}

such as SCN1A, clear genotype-phenotype correlations have been identiﬁed that explain the SCN1A phenotypic heterogeneity by focusing on the mutation type and location of SCN1A variants in

relation to the phenotype.77_{For other genes, such as SYNGAP1 and GRIN2A, we still lack a clear}

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ADVANCES AND CHALLENGES IN EPILEPSY GENETICS IN

CURRENT CLINICAL PRACTICE

The yield of genetic testing

Not long ago it was unimaginable that we would now know of 700 genes related to epilepsy.58

Even so, we still cannot identify the genetic cause in a signiﬁcant number of epilepsy cases that are suspected to be genetic. Only one large and two very small studies addressed the yield of microarray in clinical hospital cohorts of patients with all types of epilepsies: the yield varied between 9% and 40%.55,80,81_{In one of these studies, new loci of interest for epilepsy were identiﬁed.}55_{In chapter 2,} we describe the diagnostic yield of microarray in a large clinical hospital cohort of children with epilepsy in the Netherlands and the possible novel CNVs for epilepsy.

With our increasing ability to identify the underlying genetic causes of epilepsy, genetic testing is oﬀered more and more in clinical practice. Using these techniques, we hope not only to improve epilepsy care but also to provide answers to longstanding questions from patients and parents about the epilepsy cause and prognosis. However, the impact on patients and their parents of genetic

counseling and receiving a genetic diagnosis has not yet been studied.82,83_{In chapter 3, we present}

the results of a study evaluating empowerment and anxiety during a genetic counseling trajectory in patients with epilepsy or their parents in whom genetic causes were and were not identiﬁed.

Genotype-phenotype studies

With the introduction of NGS, many new genes for epilepsy have been identiﬁed in diﬀerent cohorts of patients selected based on their phenotype. Due to this ascertainment, the clinical features associated with these genes is often biased in the original papers. To unravel the full gene-related phenotypic spectrum and the genotype-phenotype correlations, patients should be selected based on their genotype and subsequently be phenotyped (a process called reverse phenotyping). In chapter 4 and chapter 5, we report the phenotypic spectra and genotype-phenotype correlations for SYNGAP1 and GRIN2A, respectively. In chapter 6, we show that psychotic disorders are a new, later-onset manifestation of PCDH19 Girls Clustering Epilepsy. Chapter 7 describes a case report of a boy with a deletion of the STX1B gene and a new phenotype: epilepsy with myoclonic-atonic seizures (previously called myoclonic astatic epilepsy).

In Chapter 8, we evaluate the presence of PRRT2-related phenotypes in patients with 16p11.2 microdeletions including PRRT2 and the 16p11.2 microdeletion syndrome.

All eﬀorts to identify genes for epilepsy are driven by the hope of improving epilepsy care. For now, however, the identiﬁcation of new epilepsy genes has been translated into better management of seizures in only a few cases. Currently, ‘personalized’ medicine for epilepsy has been established in only two scenarios: a ketogenic diet for patients with SLC2A1 variants and treatment with pyridoxine

for patients with ALDH7A1 variants.84_{In chapter 9, we report the eﬃcacy of carbamazepine as a}

INTRODUCTION

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Processed on: 29-10-2018 PDF page: 20PDF page: 20PDF page: 20PDF page: 20 sodium-channel blocker in the case of a girl with infantile epilepsy due to a SCN2A sequence variant

and. This case report is an example of precision medicine.

In chapter 10 we discuss our results in a general perspective and we propose a diagnostic algorithm for genetic testing for epilepsy in clinical practice.

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INTRODUCTION

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PART I

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Chapter 2

Copy number variation in

a hospital-based cohort of

children with epilepsy

Published as: DRM Vlaskamp, PMC Callenbach, P Rump, et al. Copy number variation in a hospital-based cohort of children with epilepsy. Epilepsia Open, 2017; 2: 244–254.

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Danique RM Vlaskamp1,2_{, Petra MC Callenbach}1*_{, Patrick Rump}2*_{, Lucia AA Giannini}2_{, Trijnie}

Dijkhuizen2_{, Oebele F Brouwer}1_{, Conny MA van Ravenswaaij-Arts}2

1_{University of Groningen, University Medical Center Groningen, Department of Neurology,}

Groningen the Netherlands. 2_{University of Groningen, University Medical Center Groningen,}

Department of Genetics, Groningen, the Netherlands. * These authors contributed equally to this work

Acknowledgements. P.M.C. Callenbach received an unrestricted research grant from UCB Pharma BV, the Netherlands. UCB Pharma BV had no role in the study design, data collection, and analysis, decision to publish, or preparation of the manuscript. We thank K. McIntyre for editing the manuscript and J. Anderson for helping identifying CNVs for epilepsy reported in the literature.

Disclosures. None of the authors has any conflicts of interest to disclose. We confirm that we have read the Journal’s position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.

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ABSTRACT

Objective. To evaluate the diagnostic yield of microarray analysis in a hospital-based cohort of children with seizures and to identify novel candidate genes and susceptibility loci for epilepsy. Methods. Of all children who presented with their ﬁrst seizure in the University Medical Center Groningen (January 2000 through May 2013) (n = 1,368), we included 226 (17%) children who underwent microarray analysis before June 2014. All 226 children had a deﬁnite diagnosis of epilepsy. All their CNVs on chromosomes 1-22 and X that contain protein-coding genes and have a prevalence of <1% in healthy controls were evaluated for their pathogenicity.

Results. Children selected for microarray analysis more often had developmental problems (82% vs 25%, p < 0.001), facial dysmorphisms (49% vs 8%, p < 0.001) or behavioral problems (41% vs 13%, p < 0.001) than children who were not selected. We found known clinically relevant CNVs for epilepsy in 24 of the 226 children (11%). Seventeen of these 24 children had been diagnosed with symptomatic focal epilepsy not otherwise specified (71%) and five with West syndrome (21%). Of these 24 children, many had developmental problems (100%), behavioral problems (54%) or facial dysmorphisms (46%). We further identified five novel CNVs comprising four potential candidate genes for epilepsy: MYT1L, UNC5D, SCN4B and NRXN3.

Significance. The 11% yield in our hospital-based cohort underscores the importance of microarray analysis in diagnostic evaluation of children with epilepsy.

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INTRODUCTION

Genetic factors play an important role in the etiology of epilepsy,1_{as demonstrated by the large}

number of genes and regions that cause or predispose to epilepsy newly identiﬁed by various

genome-wide technologies.2_{Chromosomal microarray analysis, in particular, enables the}

identiﬁcation of chromosomal deletions (losses) or duplications (gains), called Copy Number Variants

(CNVs).3_{CNVs may contribute to epilepsy in two ways. First, CNVs that comprise epilepsy-related}

genes could lead to epilepsy following a Mendelian inheritance. For example, both KCNQ2 sequence

variants and whole gene deletions can cause benign familial neonatal seizures.4,5_{Second, CNVs}

that occur more frequently in patients compared to healthy controls may increase an individual’s susceptibility to developing epilepsy, with the responsible haploinsuﬃcient gene(s) often being unknown. Large cohort studies have identiﬁed such susceptibility CNVs in several chromosomal

regions, including well-known CNVs located at 15q11.2 (BP1-BP2), 15q13.3 and 16p13.11.6-8

Studies using microarray analysis have most often been performed in research cohorts of children who were selected based on their epilepsy diagnosis, e.g. idiopathic generalized epilepsies, focal

epilepsies and/or fever-associated epilepsies.6-8_{Only a few studies have addressed the yield of}

microarray analysis in clinical cohorts of all children presenting with any type of seizures in a clinical

setting.9-11_{We therefore aimed to evaluate the diagnostic yield of microarray analysis in a}

hospital-based cohort of children with epilepsy for whom detailed phenotypic information was available, with the further goal of identifying novel candidate genes or susceptibility loci for epilepsy.

MATERIAL AND METHODS

Study cohort

The study cohort was derived from the childhood seizure database of the University Medical Center Groningen (UMCG), a regional referral center for children with epilepsy. In this database, we retrospectively included all children who presented with their ﬁrst febrile or afebrile seizure before the age of 18 years between January 2000 and June 2013, and who were seen and/or treated by a child neurologist of the UMCG (n = 1,368). Epilepsy was diagnosed in 91% of these children using the current International League Against Epilepsy (ILAE) practical clinical deﬁnition

of epilepsy.12_{Of the remaining children (9%), 7% had febrile seizures only and 2% had only one}

afebrile seizure. The UMCG database contains phenotype information and was independently completed by two researchers (DRMV and PMCC). Phenotypic inconsistencies and epilepsy classiﬁcation were discussed until agreement was reached using the information in the database as well as in the original medical records (PMCC and OFB). Epilepsy syndromes and seizure types

were classiﬁed according to the 2006 ILAE classiﬁcation.13_{Children were included in this study if}

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Formal independent review board evaluation was waived by the Institutional Medical Ethical Committee of the UMCG because of the retrospective and observational character of this study.

Chromosomal microarray analysis and data interpretation

Microarray analyses were performed using an oligonucleotide array (Agilent 105K or 180K custom HD-DGH microarray; Agilent Technologies, Santa Clara, USA) or a single nucleotide polymorphism (SNP) array (Illumina Omni Express 12-V1.0; Illumina, San Diego, USA). Cartagenia Bench Lab CNV software was used for storage, analysis and reporting of the structural genomic data (Cartagenia, Leuven, Belgium; part of Agilent Technologies, Santa Clara, USA). The chromosomal coordinates of CNVs were reported relative to the Genome Reference Consortium Human Reference genome version 37 (GRCh37/hg19).

CNVs on chromosome 1-22 or X identiﬁed by at least three (SNP microarray) or four (oligonucleotide microarray) consecutive probes were evaluated for their pathogenicity (Figure 1). CNVs were excluded from further analysis when they did not contain (protein-coding) genes or had ≥90% overlap with CNVs seen in ≥1% of healthy controls. The prevalence of CNVs in healthy controls was calculated using the International Database of Genomic Variance (n =

14,316, last updated February 2013),14_{the Low Lands Consortium database of oligonucleotides (n}

= 2,402, last updated December 2012) and SNP microarray results of healthy parents of children who underwent microarray analysis in ﬁve Dutch genetic centers (n = 749, last updated October 2014). Remaining CNVs were categorized into two groups: (1) CNVs with <90% overlap with CNVs observed in healthy controls and (2) CNVs with ≥90% overlap with CNVs observed in <1% of the healthy controls (Figure 1). CNVs in both groups were marked as potentially clinically relevant if they had overlap with genetic regions previously associated with epilepsy. These regions were identiﬁed by performing a literature search using PubMed, complemented with information from the Decipher database and Cartagenia Bench Lab CNV software. The remaining CNVs in both groups were evaluated for novel candidate genes or susceptibility loci for epilepsy. CNVs with <90% overlap with CNVs of healthy controls were of interest if they contained a gene with an expression or function in the brain or a gene associated with an autosomal dominant or X-linked neuropsychiatric disease, and if they occurred in at least one (for deletions) or two (for duplications) unrelated children in our cohort. In the group of CNVs with ≥90% overlap with CNVs observed in <1% of the healthy controls, overlapping regions between CNVs in at least two unrelated children were of interest if these regions contained protein-coding genes and were 10 times more prevalent in our cohort compared to healthy controls.

Statistical analyses

SPSS Statistics Version 22.0 (IBM Corporation, NY, USA) was used to perform descriptive and comparative statistics. Diﬀerences in categorical and ordinal phenotypic data between children were analyzed using Fisher’s exact and Mann-Whitney U tests, respectively.

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RESULTS

Characteristics of the study cohort

In 226 (17%) children, microarray analysis was performed in the context of their diagnostic work-up. Their phenotypic characteristics are summarized in Table 1. All children had a deﬁnite diagnosis of epilepsy, except for one who had a single febrile status epilepticus.

Children with epilepsy who underwent microarray analysis had significantly more developmental problems (82% vs 25%, p < 0.001), facial dysmorphisms (49% vs 8%, p < 0.001) or behavioral problems (41% vs 13%, p < 0.001) when compared to children in our database who did not undergo microarray analysis. To reduce bias, our comparisons were limited to children with epilepsy onset after December 31, 2005, when microarray analysis was introduced in our center (n = 158 for children with array; n = 271 for children without array or another identified genetic cause). The presence of a positive family history for epilepsy, known in 141/158 children who did and in 206/271 children who did not undergo microarray, did not differ significantly (33% vs 30%, p = 0.56) between the two groups.

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Figure 1: Flowchart for evaluating Copy Number Variants (CNVs) in our hospital-based cohort of

University of Groningen Genotyping and phenotyping epilepsies of childhood Vlaskamp, Danique

Genotyping and phenotyping epilepsies of childhood

Vlaskamp, Danique

Genotyping and phenotyping

epilepsies of childhood

Genotyping and phenotyping

epilepsies of childhood

Proefschrift

Danique Rienke Maria Vlaskamp

COVER

CONTENTS

Chapter 1

Introduction

EPILEPSY PHENOTYPING

EPILEPSY GENOTYPING

GENETIC DATA INTERPRETATION

1

CONCEPTUALIZING EPILEPSY GENETICS

ADVANCES AND CHALLENGES IN EPILEPSY GENETICS IN

CURRENT CLINICAL PRACTICE

REFERENCES

PART I

Chapter 2

Copy number variation in

a hospital-based cohort of

children with epilepsy

ABSTRACT

INTRODUCTION

MATERIAL AND METHODS

RESULTS