NCOR2 is a novel candidate gene for migraine-epilepsy phenotype

Hypothesis To identify genetic factors predisposing to migraine-epilepsy phenotype utilizing a multi-generational family with known linkage to chr12q24.2-q24.3. Methods We used single nucleotide polymorphism (SNP) genotyping and next-generation sequencing technologies to perform linkage, haplotype, and variant analyses in an extended Finnish migraine-epilepsy family (n = 120). In addition, we used a large genome-wide association study (GWAS) dataset of migraine and two biobank studies, UK Biobank and FinnGen, to test whether variants within the susceptibility region associate with migraine or epilepsy related phenotypes in a population setting. Results The family showed the highest evidence of linkage (LOD 3.42) between rs7966411 and epilepsy. The haplotype shared among 12 out of 13 epilepsy patients in the family covers almost the entire NCOR2 and co-localizes with one of the risk loci of the recent GWAS on migraine. The haplotype harbors nine low-frequency variants with potential regulatory functions. Three of them, in addition to two common variants, show nominal associations with neurological disorders in either UK Biobank or FinnGen. Conclusion We provide several independent lines of evidence supporting association between migraine-epilepsy phenotype and NCOR2. Our study suggests that NCOR2 may have a role in both migraine and epilepsy and thus would provide evidence for shared pathophysiology underlying these two diseases.Peer reviewe

Kopfschmerz bei Parietal- und Okzipitallappenepilepsien

Epilepsiepatienten leiden überdurchschnittlich häufig unter Kopfschmerzen. Dies gilt insbesondere für Patienten mit idiopathisch generalisierten und parietookzipitalen Epilepsien. Die Häufigkeit des gemeinsamen Auftretens von Kopfschmerzen und Epilepsie überschreitet dabei die rechnerische Koinzidenz, sodass von einer Komorbidität beider Syndrome auszugehen ist. Bestärkt wird diese Hypothese durch überlappende genetische Veränderungen sowie gemeinsame pathophysiologische Mechanismen. Bis zu 62 % der Patienten mit z. B. Parietal- und Okzipitallappenepilepsie (POLE) geben Kopfschmerzen an. Diese treten v. a. nach dem Anfall (postiktal) auf und manifestieren sich am häufigsten als Migräne-ähnlicher Kopfschmerz oder Spannungskopfschmerz. Seltener kommt es zu Kopfschmerzen vor (periiktal), während (iktal) oder zwischen (interiktal) epileptischen Anfällen. Bei transienten neurologischen Ausfallsymptomen mit begleitenden Kopfschmerzen ist differenzialdiagnostisch neben der Migräne an vaskuläre Ereignisse wie Synkopen oder eine transiente ischämische Attacke zu denken.The prevalence of headache in epilepsy patients is above average compared to the general population. This is especially true for patients with idiopathic generalized and parieto-occipital epilepsies. Comorbidity of both syndromes is suspected as the frequency of the joint occurrence of headache and epilepsy exceeds the statistical coincidence rate. This hypothesis is supported by data on shared genetic variants as well as overlapping pathophysiological mechanisms. Up to 62% of patients with parietal and occipital lobe epilepsy (POLE) report headaches. These occur especially following seizures (postictally) and with migraine-like or tension-type characteristics. Less frequently, headache manifests before (preictal), during (ictal) or between (interictal) epileptic seizures. The most relevant differential diagnoses for paroxysmal events with neurological deficits and accompanying headache are migraine and vascular events, such as syncope and transient ischemic attacks

Aurallinen migreeni – geneettiset alttiusvariantit

Migraine is a complex headache disorder affecting approximately 15% of the adult population worldwide. It has a great impact on both individual patients and society. According to the Global Burden of Disease Study, migraine is one of the most costly and disabling neurological diseases. There are two main subtypes of migraine: migraine without aura and migraine with aura. Migraine without aura is the most common subtype of migraine. However, one-third of migraine patients experience neurological aura symptoms. In most cases, aura is visual, including scintillating scotoma and loss of vision type symptoms, but it can also be sensory, motor or result in speech disturbance. In hemiplegic migraine, a rare form of migraine with aura, the aura is characterized by motor weakness. The exact pathophysiological mechanisms underlying migraine are still unknown. Both family and twin studies have shown that migraine is hereditary. Recent genome-wide association studies (GWAS) have revealed the polygenic nature of common forms of migraine, while high-impact mutations have been found mainly in familial hemiplegic migraine (FHM). FHM is suggested to be a monogenic disorder with three major causative genes: CACNA1A, ATP1A2 and SCN1A. Genetic variants in these ion-transport/channel genes have also been associated with rare monogenic forms of epilepsy. The aim of this doctoral thesis was to identify genetic susceptibility factors for migraine with aura and migraine-epilepsy phenotype. We applied targeted and genome-wide approaches in a large and well-characterized Finnish migraine family sample (1,967 families with 8,937 family members). The first part of the thesis defined hemiplegic migraine as a clinically and genetically heterogeneous disease. In terms of headache characteristics and neurological aura symptoms, hemiplegic migraine patients appeared at the extreme end of the migraine with aura symptom spectrum. Our study also showed that mutations in CACNA1A, ATP1A2 and SCN1A are not the major cause of hemiplegic migraine in Finnish patients, as only 9% (4/45) of the studied FHM families and none of the sporadic cases (n=201) carried pathogenic exonic variants in these genes. These data suggest that there are additional genetic factors contributing to the hemiplegic migraine phenotype. In the second part of this thesis, we utilized data obtained from a previously published migraine GWAS to calculate polygenic risk scores (PRS) for 8,319 participants from the Finnish migraine family collection and 14,470 FINRISK population-based samples. Results showed that common polygenic variation significantly contributes to the familial aggregation of migraine. The polygenic burden was higher in familial migraine cases than in population cases. Furthermore, the polygenic burden was increased across all of the studied migraine with aura and migraine without aura subtypes in the family dataset compared with the population controls. Patients with typical migraine aura or hemiplegic migraine carried a higher load compared with patients having migraine without aura. Our findings are especially interesting considering that FHM has been suggested to be a monogenic disorder primarily driven by rare, high-impact variants. The third part of this thesis focused on a previously identified migraine-epilepsy susceptibility locus on chromosome 12q24.2-q24.3 identified in a large multi-generational Finnish migraine-epilepsy family including 120 individuals. We defined a 450 kbp haplotype that was shared among 12 out of 13 epilepsy patients. This segment covers almost the entire NCOR2 gene, which plays an important regulatory role during brain development. Interestingly, one of the 123 migraine risk loci recently reported by the International Headache Genetics Consortium also co-localized with this region. Our results suggest that NCOR2 could potentially have a role in both migraine and epilepsy and could thus contribute to the susceptibility of both of these paroxysmal brain diseases. However, further studies are needed to identify the actual causal variants. Overall, the results of this doctoral thesis highlight migraine as a clinically and genetically heterogeneous disease. Our results suggest that migraine with typical aura and hemiplegic migraine share a similar genetic background with a high polygenic load. Even FHM may not be a true monogenic disease, but rather a disease in which common risk variants, together with rare pathogenic variants and environmental risk factors, contribute to the disease outcome. Furthermore, our results provide genetic evidence from a large multi-generational Finnish family for potentially shared pathophysiology underlying both epilepsy and migraine.Migreeni on yleinen kohtauksellinen päänsärkysairaus. Kolmasosalla migreenipotilaista kohtauksiin liittyy auraoire, joka voi olla näkö-, puhe- tai tuntohäiriö. Harvinaisessa hemiplegisessä migreenissä aura esiintyy toisella puolella kehoa puutumista ja voimattomuutta aiheuttavana oireena. Migreenin patofysiologiaa ei vielä täysin tunneta. Laajat geenitutkimukset ovat tunnistaneet yli sata migreeniriskiä hieman lisäävää perimän vaihtelevaa kohtaa (geenivarianttia). Sairastumisriskiin merkittävästi yksinään vaikuttavia variantteja on tunnistettu vain monogeenisenä sairautena pidetylle hemiplegiselle migreenille. Tässä väitöskirjatutkimuksessa selvitettiin aurallisen migreenin sekä migreenin ja epilepsian yhteisesiintymisen geneettistä taustaa hyödyntämällä suurta suomalaista migreeniperheaineistoa (1967 perhettä, 8937 henkilöä). Tutkimuksen ensimmäisen osatyön tulokset osoittivat, että hemipleginen migreeni on osa aurallisen migreenin oirejatkumoa, vaikkakin hemiplegistä migreeniä sairastavien oireet ovat keskimäärin vakavampia kuin tyypillistä aurallista migreeniä sairastavilla. Tulokset osoittivat myös, että kolme tunnettua hemiplegisen migreenin alttiusgeeniä (CACNA1A, ATP1A2 ja SCN1A) eivät yksinään riitä selittämään hemiplegisen migreenin esiintymistä suomalaisissa perheissä. Ainoastaan 9 %:lta tutkituista perheistä (4/45) löydettiin todennäköinen sairausvariantti kyseisistä geeneistä. Tutkimuksen toisen osatyön tulokset osoittivat, että monien geneettisten riskitekijöiden yhteisvaikutus selittää migreenin esiintymistä suvuissa. Tutkimuksessa havaittiin myös eroja eri migreenityyppien välillä. Yleisten geneettisten riskitekijöiden muodostama taakka oli suurempi aurallisessa migreenissä, mukaan lukien hemiplegistä migreeniä sairastavat henkilöt, kuin aurattomassa migreenissä. Aiemmin hemiplegisen migreenin on ajateltu aiheutuvan pelkästään harvinaisista varianteista. Tutkimuksen viimeisessä osatyössä keskityttiin yhteen suureen perheeseen ja siinä tunnistettuun migreenille ja epilepsialle altistavaan 12q24.31 kromosomialueeseen. Jatkotutkimukset osoittivat aivojen kehitykseen vaikuttavan NCOR2-geenin todennäköisimmäksi epilepsian alttiusgeeniksi kyseisessä perheessä. Yksi migreenin riskialueista sijaitsee samalla genomialueella, mikä tukee alueen merkitystä myös migreenin taustalla. Kokonaisuudessaan tämän väitöstutkimuksen tulokset viittaavat siihen, että migreeni on kliinisesti ja geneettisesti heterogeeninen sairaus, jonka kehittymiseen vaikuttavat useat geenivariantit yhdessä ulkoisten tekijöiden kanssa. Aurallisen migreenin kliiniset oireet muodostavat jatkumon, jossa hemiplegisen migreenin oireet ovat kestoltaan, määrältään ja tyypiltään kaikkein vakavimpia. Yllättäen myös geneettisten riskitekijöiden yhteisvaikutus on aurallisilla ja hemiplegisillä migreenipotilailla kaikkein suurin

Kromosomin 14q12-q23 tarkempi analysointi suomalaisessa migreeni-epilepsiasuvussa

Tutkimuksen tavoitteena oli löytää migreenille ja epilepsialle altistavia geneettisiä variantteja eksomisekvensoinnin avulla kromosomista 14q12-q23. Aineistona toimi kumpaakin sairautta ilmentävä suomalainen suku. Migreenidiagnoosit asetettiin kyselylomakkeen pohjalta, johon vastasi 111 henkilöä. Lomakkeen avulla karakterisoitiin tarkemmin suvun fenotyyppi migreenin suhteen. Aineistosta 61,3 % kärsi migreenistä ja 13,5 % epilepsiasta. Epilepsia assosioitui selkeästi aurattomaan migreeniin: epileptikoista 73,3 % sairasti auratonta migreeniä ja aurallista vain 20 %. Samanaikainen epilepsia lisäsi migreenioireiden vakavuutta. Epilepsiasta kärsivien migreeni alkoi keskimäärin nuorempana, oli oirekuvaltaan vaikeampaa ja kohtausten lukumäärä oli suurempi kuin vertailuryhmällä, joka kärsi pelkästä migreenistä. Eksomisekvensointia varten valittiin 8 henkilöä, joilta etsittiin harvinaisia variantteja, jotka segregoivat sairauden mukana ja aiheuttavat toiminnallisesti kiinnostavan muutoksen. 13 varianttia pääsi lopulliseen tarkasteluun. Näistä kaksi sijaitsi SYNE2-geenissä, joka osallistuu neurogeneesin säätelyyn. Jompikumpi varianteista esiintyi viidellä eksomisekvensoidulla henkilöllä, kaikilla heterotsygoottisina. Ne eivät kuitenkaan esiintyneet aineistossa siten, että niitä voitaisiin pitää migreenille ja epilepsialle altistavina variantteina. Lisäksi määritettiin kandidaattigeeneiksi SYNE2 ja NPAS3, joista seulottiin ei-eksonisia variantteja ilman vakuuttavia löydöksiä

Benchmarking of univariate pleiotropy detection methods, with an application to epilepsy phenotypes

Over the past decades, various methods have been used to scan the human genome to identify genetic variations associated with diseases, in particular with common, complex disorders. One of such approaches is the genome-wide association study (GWAS), which compares genetic variation between affected and healthy individuals to find genomic variants in the DNA sequence associated with a trait. GWAS are usually conducted separately for individual traits, and the same single nucleotide polymorphisms (SNP)/loci are associated with different traits in independent studies 7-10. These findings buttress the knowledge that most complex traits are correlated and have shared genetic architecture, therefore, sharing the same heritable risk factors11. Knowledge of the genetic risk factors can directly or indirectly contribute to improvements in risk assessment, drug target development, and ultimately in providing effective therapies to the affected individuals. Pleiotropy is the phenomenon of a hereditary unit affecting more than one trait, and the earliest reported evidence was provided by Mendel when he noted that some set of features were always observed together in a plant. Although this example could have been purely due to linkage and could be regarded as spurious pleiotropy in recent times, it opened up more discussion and research into pleiotropy, which has since been an active area of research12. In this work, I focused on complex epilepsies and the overlap in the genetic factors impacting their phenotypes. Epilepsy is a brain disorder comprising monogenic and common/complex forms characterized by recurrent partial or generalized seizures. However, the extent to which genetic variants contribute to the disorder and how much of the genetic contribution is shared between the different phenotypes is not yet fully understood. This motivated this project, where I benchmarked available pleiotropy detection approaches to select the best performing method in terms of power and false-positive rate to detect true pleiotropy. Then, I applied the selected method to summary statistics of focal epilepsy (FE) and genetic generalized epilepsy (GGE), provided by the International League Against Epilepsy Consortium (ILAE) on complex epilepsies and the EPI25 collaborative, to identify shared genetic factors in both phenotypes of epilepsy. Identifying pleiotropic SNPs or genes is an active area of research with multiple proposed approaches, broadly categorized into univariate and multivariate methods. Multivariate approaches have the limitation that they require all phenotypes to be measured in the same individual and their corresponding genotype data provided, which is often not the case since GWAS are usually performed per specific trait. However, various consortia studying complex traits readily share the summary statistics (effect sizes and p-values) from genome-wide association studies, making it easier to apply univariate pleiotropy detection approaches that combine these statistics to identify SNPs or loci with a concordant or discordant direction of effects. Therefore, in this project, I first compared the relative power and false-positive rate (FPR) performance of five univariate pleiotropy detection approaches, classic meta-analysis, cFDR, PLACO, ASSET, and CPBayes (see section 6.1), through simulation studies. After that, I applied the best-performing method to the analysis of phenotypes of epilepsy using actual data. The data simulation procedure was performed in 3 steps. First, a population of 1 million individuals of European ancestry was simulated via resampling using the HAPGEN2 software13 and haplotypes of central Europeans from the 1000 genomes project14. In the second phase of the simulation, disease SNPs were randomly selected and used for the additive liability threshold model (ALTM)15 to simulate multifactorial disease phenotypes from the simulated genetic data. As expected, the performance of the methods varied in terms of power and false positive rate (FPR). The variability between the methods is higher for FPR, while most methods are comparable in terms of power, especially for larger sample sizes and RR. Although the classical meta-analysis is very powerful, it is also riddled with a very high false-positive rate, making it less suitable for identifying pleiotropic loci. While all the methods performed well in terms of power, the ASSET method gave a better trade-off between power and FPR for the different simulation approaches. Applying ASSET to the two phenotypes of epilepsy, GGE and FE, resulted in identifying a new putative locus 17q21.32 while replicating locus 2q24.3, previously reported by the ILAE consortium 16. Further, applying the ASSET method to summary statistics of larger samples of epilepsy phenotypes resulted in the identification of loci 2q24.3 and 9q21.13. These findings corroborate the result obtained by the ILAE consortium through mega and meta-analysis. Classical meta-analysis (MA) is not recommended for pleiotropy detection, based on the simulation study results. Though MA demonstrated good power to detect pleiotropy, it also recorded high FPR across all simulation scenarios. However, the ASSET method is highly recommended as it kept the FPR low while demonstrating good power to detect pleiotropy. This study also contributed three new pleiotropic loci (2q24.3, 17q21.32, and 9q21.13) to understanding the relationship of genetic variation with epilepsy phenotypes and the inter-relationship between these phenotypes. Although the locus 17q21.32 could not be replicated in the larger sample set, it is not necessarily a false positive discovery. The locus was genome-wide significant for GGE but marginally significant for FE, which confirmed the trend observed in the FE cases in the EPI25 collaborative dataset, where no genome-wide significance result was found. Therefore, replication in an independent sample is desirable. One limitation of using the univariate pleiotropy detection approaches as seen with the classical MA is that one trait with a very low P-value could drive the observed pleiotropic association. Also, methods like cFDR and PLACO could only accommodate two traits, though this was not a challenge in this project. Despite these limitations, the presented work established a benchmark of the relative performance of the assessed methods and could also guide researchers in related fields in their future work. This study also contributed to understanding the shared genetic factors between GGE and FE with the expectation that larger sample sizes will lead to more discoveries

Shared Genetic Etiology for Migraine and Epilepsy

Shared loci for migraine and epilepsy were found on chromosomes 14q12-q23 and 12q24.2-q24.3 in a linkage analysis study of a Finish family with a complex phenotype, in a report from Folkhalsan Institute and other centers in Helsinki and Oulu, Finland; University of California, Los Angeles; and Wellcome Trust Sanger Institute, Cambridge, UK

Somatic co‐morbidities in epilepsy

People with epilepsy seem to have more concomitant medical conditions than the general population. The burden of somatic co‐morbidities plays an important role in the premature mortality in epilepsy. I sought to explore the relation between somatic co‐morbidities and epilepsy, attempting to avoid biases in previous studies. In a first study, I collected clinical, demographic and somatic co‐morbidity data in 2016 consecutive people with epilepsy referred for assessment at a tertiary centre and in 1297 people with epilepsy in the community. In a second study, I analysed the lifelong course of epilepsy of an historical cohort of 235 people who were in residential care at the Chalfont Centre for Epilepsy: 122 had comprehensive post‐mortem examination. Confounders (causes or consequences of epilepsy/ its treatment) were distinguished from co‐morbidities. In the first study, somatic co‐morbidities were significantly more frequent in the referral centre than in the community (49% vs 37%). Consistent risk factors were found in both cohorts. When adjusting for age, epilepsy duration, and absence of underlying brain lesion were independently associated with an increased burden of somatic conditions. In the second study, age at death showed an early peak of mortality between 45‐50 years old. High seizure frequency was an independent predictor of early death due to co‐morbidities. Those who survived increasingly went into spontaneous remission lasting until death; older age and presence of neuropathologically‐confirmed degenerative changes were independent predictors of terminal remission. Somatic co‐morbidities do not occur randomly in relation with epilepsy. Greater epilepsy severity seems to be a risk factor; several other consistent predictors were identified. Epilepsy may cause premature death indirectly through co‐morbid conditions. Ageing and degenerative changes could improve epilepsy drug responsiveness