Towards an understanding of genetic predisposition to migraine

Plausible genome-wide associations for episodic neurological diseases (such as migraine, epilepsy and ataxias) have been slow to emerge. The first such association was reported in a recent genome-wide association study of migraine, with quantitative expression analysis linking the variant to a nearby regulatory gene, MTDH/AEG-1. This putative mechanism, regulating the expression of the primary glutamate transporter in the brain, EAAT2/GLT-1, has interesting implications bridging the gap between Mendelian and common forms in this key group of disorders

High-resolution population-specific recombination rates and their effect on phasing and genotype imputation

Previous research has shown that using population-specific reference panels has a significant effect on downstream population genomic analyses like haplotype phasing, genotype imputation, and association, especially in the context of population isolates. Here, we developed a high-resolution recombination rate mapping at 10 and 50 kb scale using high-coverage (20-30x) whole-genome sequenced data of 55 family trios from Finland and compared it to recombination rates of non-Finnish Europeans (NFE). We tested the downstream effects of the population-specific recombination rates in statistical phasing and genotype imputation in Finns as compared to the same analyses performed by using the NFE-based recombination rates. We found that Finnish recombination rates have a moderately high correlation (Spearman's rho = 0.67-0.79) with NFE, although on average (across all autosomal chromosomes), Finnish rates (2.268 +/- 0.4209 cM/Mb) are 12-14% lower than NFE (2.641 +/- 0.5032 cM/Mb). Finnish recombination map was found to have no significant effect in haplotype phasing accuracy (switch error rates similar to 2%) and average imputation concordance rates (97-98% for common, 92-96% for low frequency and 78-90% for rare variants). Our results suggest that haplotype phasing and genotype imputation mostly depend on population-specific contexts like appropriate reference panels and their sample size, but not on population-specific recombination maps. Even though recombination rate estimates had some differences between the Finnish and NFE populations, haplotyping and imputation had not been noticeably affected by the recombination map used. Therefore, the currently available HapMap recombination maps seem robust for population-specific phasing and imputation pipelines, even in the context of relatively isolated populations like Finland.Peer reviewe

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

Premonitory symptoms in migraine : A cross-sectional study in 2714 persons

Aim To describe the frequency and number of premonitory symptoms (PS) in migraine, the co-occurrence of different PS, and their association with migraine-related factors. Methods In this cross-sectional study, a validated questionnaire was sent to Finnish migraine families between 2002 and 2013 to obtain data on 14 predefined PS, migraine diagnoses, demographic factors, and migraine characteristics. The estimated response rate was 80%. Results Out of 2714 persons, 2223 were diagnosed with migraine. Among these, 77% reported PS, with a mean number of 3.0 symptoms compared to 30% (p Conclusion PS are experienced by a majority of migraineurs. More severe migraine is associated with a higher burden of PS. Since the material was not entirely representative of the general population of migraineurs, caution should be exercised in generalizing the results.Peer reviewe

Migreenin geneettinen tausta on monitekijäinen

Vertaisarvioitu.Migreeni on yleinen neurovaskulaarinen aivosairaus, jolla on vahva geneettinen tausta. Migreenin molekyyligeneettiset tutkimukset 1990-luvulla kohdistuivat harvinaiseen hemiplegiseen migreeniin, joka osoittautui ionikanavataudiksi. Yleisten migreenimuotojen geneettinen tausta alkoi hahmottua 2010-luvulla genominlaajuisten assosiaatiotutkimusten (GWAS) avulla. Tutkimukset ovat paljastaneet kymmeniä yleisiä, vaikutukseltaan vähäisiä migreenin geneettisiä riskivariantteja, erityisesti vaskulaarisissa kudoksissa ilmenevistä geeneistä. On selvinnyt, että aurallisen, aurattoman ja hemiplegisen migreenin riskivariantit ovat osittain samoja. Yleisten riskivarianttien yhteisvaikutus taas selittää migreenin kertymistä perheisiin. Mielenkiintoista on myös se, että migreenillä on yhteisiä geneettisiä riskitekijöitä psyykkisten sairauksien, erityisesti ADHD:n, vakavan masennuksen ja Touretten oireyhtymän kanssa. Riskivarianttien todellinen merkitys migreenin patofysiologiaan selviää vasta toiminnallisten tutkimusten avulla.Peer reviewe

Polygenic risk provides biological validity for the ICHD-3 criteria among Finnish migraine families

Background Migraine is diagnosed using the extensively field-tested International Classification of Headache Disorders (ICHD-3) consensus criteria derived by the International Headache Society. To evaluate the criteria in respect to a measurable biomarker, we studied the relationship between the main ICHD-3 criteria and the polygenic risk score, a measure of common variant burden in migraine. Methods We used linear mixed models to study the correlation of ICHD-3 diagnostic criteria, underlying symptoms, and main diagnoses with the polygenic risk score of migraine in a cohort of 8602 individuals from the Finnish Migraine Genome Project. Results Main diagnostic categories and all underlying diagnostic criteria formed a consistent continuum along the increasing polygenic burden. Polygenic risk was associated with the heterogeneous clinical picture starting from the non-migraine headache (mean 0.07; 95% CI 0.02-0.12; p = 0.008 compared to the non-headache group), to probable migraine (mean 0.13; 95% CI 0.08-0.18; p < 0.001), migraine headache (mean 0.17; 95% CI 0.14-0.21; p < 0.001) and migraine with typical visual aura (mean 0.29; 95% CI 0.26-0.33; p < 0.001), all the way to the hemiplegic aura (mean 0.37; 95% CI 0.31-0.43; p < 0.001). All individual ICHD-3 symptoms and the total number of reported symptoms, a surrogate of migraine complexity, demonstrated a clear inclination with an increasing polygenic risk. Conclusions The complex migraine phenotype progressively follows the polygenic burden from individuals with no headache to non-migrainous headache and up to patients with attacks manifesting all the features of the ICHD-3 headache and aura. Results provide further biological support for the ICHD-3 diagnostic criteria.Peer reviewe

A structural variation reference for medical and population genetics

Structural variants (SVs) rearrange large segments of DNA(1) and can have profound consequences in evolution and human disease(2,3). As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD)(4) have become integral in the interpretation of single-nucleotide variants (SNVs)(5). However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across diverse global populations (54% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25-29% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage(6). We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than all noncoding effects. Finally, we identified very large (over one megabase), rare SVs in 3.9% of samples, and estimate that 0.13% of individuals may carry an SV that meets the existing criteria for clinically important incidental findings(7). This SV resource is freely distributed via the gnomAD browser(8) and will have broad utility in population genetics, disease-association studies, and diagnostic screening.Peer reviewe

Evaluating drug targets through human loss-of-function genetic variation

Naturally occurring human genetic variants that are predicted to inactivate protein-coding genes provide an in vivo model of human gene inactivation that complements knockout studies in cells and model organisms. Here we report three key findings regarding the assessment of candidate drug targets using human loss-of-function variants. First, even essential genes, in which loss-of-function variants are not tolerated, can be highly successful as targets of inhibitory drugs. Second, in most genes, loss-of-function variants are sufficiently rare that genotype-based ascertainment of homozygous or compound heterozygous 'knockout' humans will await sample sizes that are approximately 1,000 times those presently available, unless recruitment focuses on consanguineous individuals. Third, automated variant annotation and filtering are powerful, but manual curation remains crucial for removing artefacts, and is a prerequisite for recall-by-genotype efforts. Our results provide a roadmap for human knockout studies and should guide the interpretation of loss-of-function variants in drug development.Peer reviewe

Landscape of multi-nucleotide variants in 125,748 human exomes and 15,708 genomes

Multi-nucleotide variants (MNVs), defined as two or more nearby variants existing on the same haplotype in an individual, are a clinically and biologically important class of genetic variation. However, existing tools typically do not accurately classify MNVs, and understanding of their mutational origins remains limited. Here, we systematically survey MNVs in 125,748 whole exomes and 15,708 whole genomes from the Genome Aggregation Database (gnomAD). We identify 1,792,248 MNVs across the genome with constituent variants falling within 2bp distance of one another, including 18,756 variants with a novel combined effect on protein sequence. Finally, we estimate the relative impact of known mutational mechanisms - CpG deamination, replication error by polymerase zeta, and polymerase slippage at repeat junctions - on the generation of MNVs. Our results demonstrate the value of haplotype-aware variant annotation, and refine our understanding of genome-wide mutational mechanisms of MNVs. Multi-nucleotide variants (MNV) are genetic variants in close proximity of each other on the same haplotype whose functional impact is difficult to predict if they reside in the same codon. Here, Wang et al. use the gnomAD dataset to assemble a catalogue of MNVs and estimate their global mutation rate.Peer reviewe