Correction: Large-scale genome-wide meta-analysis of polycystic ovary syndrome suggests shared genetic architecture for different diagnosis criteria.

[This corrects the article DOI: 10.1371/journal.pgen.1007813.].

Left ventricular hypertrophy and other cardiac risk factors in migraineurs.

BACKGROUND: The influence of cardiovascular risk factors on the probability of cardiovascular diseases in migraineurs is still being discussed. AIMS OF THE STUDY: To further elucidate the mechanisms of these relationships, we assessed the associations between migraine and cardiovascular risk factors, including those that have been recently shown to improve the prediction of cardiovascular events. METHODS: We used the data of the Finnish Health 2000 Survey (BRIF8901), consisting of 5737 subjects aged 30 years or older. In total, 488 participants reported migraine. In addition to conventional cardiovascular risk factors, educational attainment, presence of electrocardiographic signs of left ventricular hypertrophy and hemoglobin A1c were also included in the logistic regression analyses. RESULTS: Migraine was found to be associated with female sex (Odds ratio (OR) = 3.75, p < .001), lower age (B = 0.99, p < .001), lower high-density lipoprotein cholesterol (OR = 1.23, p < .05), higher diastolic blood pressure (OR = 1.31, p < .05), and left ventricular hypertrophy (OR = 1.32, p < .05), the probability of the last one increasing with migraine attack frequency. CONCLUSIONS: Left ventricular hypertrophy, most probably as a consequence of migraine-related arterial hypertension and dyslipidemia, may play a role in the relationship between migraine and cardiovascular events. The nature of this finding calls for further studies.

Electrocardiographic findings in migraineurs: results of the Finnish Health 2000 survey.

BACKGROUND: The precise relation between migraine and cardiovascular diseases remains unknown, but cardiac autonomic regulation as reflected by electrocardiography is poorly studied in migraineurs. AIMS OF THE STUDY: To search whether electrocardiographic findings may elucidate the mechanisms linking migraine with cardiovascular diseases. METHODS: We compared electrocardiographic findings in headache-free subjects (n=5,317) and people with migraine (n=490) in a Finnish population cohort. RESULTS: The frequency of cardiac rhythm and conduction disorders did not differ between the groups but left ventricular hypertrophy was more often seen in migraineurs than in non-migraineurs (odds ratio (OR)=1.32, 95% confidence interval (CI) 1.0; 1.74, p<0.05). In migraineurs reporting frequent attacks, cardiovascular diseases were associated with longer QTc intervals (p<0.05). After excluding confounders, migraineurs had longer PR intervals (160.3 vs 159.8 ms, mean difference (MD)=3.14, 95% CI 0.65; 5.62, p<0.05) than non-migraineurs. PR intervals (MD=6.6, CI 1.51; 11.68, p<0.05) and the probability of left ventricular hypertrophy (OR=1.98, CI 1.2; 3.26, p<0.05) were different in males with and without migraine, especially in patients with frequent attacks, but not in females. CONCLUSIONS: Our findings support the notion that there are interactions between migraine and cardiovascular disorders and suggest that electrocardiographic screening in migraineurs should be considered during clinical work-up.

Large-scale genome-wide meta-analysis of polycystic ovary syndrome suggests shared genetic architecture for different diagnosis criteria.

Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed based on the two criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a fixed-effect, inverse-weighted-variance meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related traits. We identified 3 novel loci (near PLGRKT, ZBTB16 and MAPRE1), and provide replication of 11 previously reported loci. Only one locus differed significantly in its association by diagnostic criteria; otherwise the genetic architecture was similar between PCOS diagnosed by self-report and PCOS diagnosed by NIH or non-NIH Rotterdam criteria across common variants at 13 loci. Identified variants were associated with hyperandrogenism, gonadotropin regulation and testosterone levels in affected women. Linkage disequilibrium score regression analysis revealed genetic correlations with obesity, fasting insulin, type 2 diabetes, lipid levels and coronary artery disease, indicating shared genetic architecture between metabolic traits and PCOS. Mendelian randomization analyses suggested variants associated with body mass index, fasting insulin, menopause timing, depression and male-pattern balding play a causal role in PCOS. The data thus demonstrate 3 novel loci associated with PCOS and similar genetic architecture for all diagnostic criteria. The data also provide the first genetic evidence for a male phenotype for PCOS and a causal link to depression, a previously hypothesized comorbid disease. Thus, the genetics provide a comprehensive view of PCOS that encompasses multiple diagnostic criteria, gender, reproductive potential and mental health.

Serum calcium and risk of migraine: a Mendelian randomization study.

Migraine affects ∼14% of the world's population, though not all predisposing causal risk factors are known. We used electronic health records, genetic co-heritability analysis, and a two-sample Mendelian Randomization (MR) design to determine if elevated serum calcium levels were associated with risk of migraine headache. Co-morbidity was evaluated using electronic health records obtained from the PennOmics database comprising >1 million patient entries. Genetic co-heritability and causality via MR was assessed using data from the International Headache Consortium (23,285 cases, 95,425 controls) and circulating serum calcium levels (39,400 subjects). We observed co-occurrence of migraine and hypercalcaemia ICD-9 diagnoses (OR = 1.58, P = 4 × 10-13), even after inclusion of additional risk factors for migraine (OR = 1.23, P = 2 × 10-3). Second, we observed co-heritability (rg = 0.191, P = 0.03) between serum calcium and migraine headache, indicating that these traits have a genetic basis in common. Finally, we found that elevation of serum calcium levels by 1 mg/dl resulting from our genetic score was associated with an increase in risk of migraine (OR = 1.80, 95% CI: 1.31-2.46, P = 2.5 × 10-4), evidence supporting a causal hypothesis. We also present multiple MR sensitivity analyses in support of this central finding. Our results provide evidence that hypercalcaemia is comorbid with migraine headache diagnoses, and that genetically elevated serum calcium over lifetime appears to increase risk for migraine. Further studies will be required to understand the biological mechanism, pathways, and clinical implication for risk management.

Novel hypotheses emerging from GWAS in migraine?

Recent technical advances in genetics made large-scale genome-wide association studies (GWAS) in migraine feasible and have identified over 40 common DNA sequence variants that affect risk for migraine types. Most of the variants, which are all single nucleotide polymorphisms (SNPs), show robust association with migraine as evidenced by the fact that the vast majority replicate in subsequent independent studies. However, despite thorough bioinformatic efforts aimed at linking the migraine risk SNPs with genes and their molecular pathways, there remains quite some discussion as to how successful this endeavour has been, and their current practical use for the diagnosis and treatment of migraine patients. Although existing genetic information seems to favour involvement of vascular mechanisms, but also neuronal and other mechanisms such as metal ion homeostasis and neuronal migration, the complexity of the underlying genetic pathophysiology presents challenges to advancing genetic knowledge to clinical use. A major issue is to what extent one can rely on bioinformatics to pinpoint the actual disease genes, and from this the linked pathways. In this Commentary, we will provide an overview of findings from GWAS in migraine, current hypotheses of the disease pathways that emerged from these findings, and some of the major drawbacks of the approaches used to identify the genes and pathways. We argue that more functional research is urgently needed to turn the hypotheses that emerge from GWAS in migraine to clinically useful information.

LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis.

MOTIVATION: LD score regression is a reliable and efficient method of using genome-wide association study (GWAS) summary-level results data to estimate the SNP heritability of complex traits and diseases, partition this heritability into functional categories, and estimate the genetic correlation between different phenotypes. Because the method relies on summary level results data, LD score regression is computationally tractable even for very large sample sizes. However, publicly available GWAS summary-level data are typically stored in different databases and have different formats, making it difficult to apply LD score regression to estimate genetic correlations across many different traits simultaneously. RESULTS: In this manuscript, we describe LD Hub - a centralized database of summary-level GWAS results for 173 diseases/traits from different publicly available resources/consortia and a web interface that automates the LD score regression analysis pipeline. To demonstrate functionality and validate our software, we replicated previously reported LD score regression analyses of 49 traits/diseases using LD Hub; and estimated SNP heritability and the genetic correlation across the different phenotypes. We also present new results obtained by uploading a recent atopic dermatitis GWAS meta-analysis to examine the genetic correlation between the condition and other potentially related traits. In response to the growing availability of publicly accessible GWAS summary-level results data, our database and the accompanying web interface will ensure maximal uptake of the LD score regression methodology, provide a useful database for the public dissemination of GWAS results, and provide a method for easily screening hundreds of traits for overlapping genetic aetiologies. AVAILABILITY AND IMPLEMENTATION: The web interface and instructions for using LD Hub are available at http://ldsc.broadinstitute.org/ CONTACT: jie.zheng@bristol.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online.

IFITM3 restricts the morbidity and mortality associated with influenza.

The 2009 H1N1 influenza pandemic showed the speed with which a novel respiratory virus can spread and the ability of a generally mild infection to induce severe morbidity and mortality in a subset of the population. Recent in vitro studies show that the interferon-inducible transmembrane (IFITM) protein family members potently restrict the replication of multiple pathogenic viruses. Both the magnitude and breadth of the IFITM proteins' in vitro effects suggest that they are critical for intrinsic resistance to such viruses, including influenza viruses. Using a knockout mouse model, we now test this hypothesis directly and find that IFITM3 is essential for defending the host against influenza A virus in vivo. Mice lacking Ifitm3 display fulminant viral pneumonia when challenged with a normally low-pathogenicity influenza virus, mirroring the destruction inflicted by the highly pathogenic 1918 'Spanish' influenza. Similar increased viral replication is seen in vitro, with protection rescued by the re-introduction of Ifitm3. To test the role of IFITM3 in human influenza virus infection, we assessed the IFITM3 alleles of individuals hospitalized with seasonal or pandemic influenza H1N1/09 viruses. We find that a statistically significant number of hospitalized subjects show enrichment for a minor IFITM3 allele (SNP rs12252-C) that alters a splice acceptor site, and functional assays show the minor CC genotype IFITM3 has reduced influenza virus restriction in vitro. Together these data reveal that the action of a single intrinsic immune effector, IFITM3, profoundly alters the course of influenza virus infection in mouse and humans.

Heterogeneous contribution of microdeletions in the development of common generalised and focal epilepsies.

BACKGROUND: Microdeletions are known to confer risk to epilepsy, particularly at genomic rearrangement 'hotspot' loci. However, microdeletion burden not overlapping these regions or within different epilepsy subtypes has not been ascertained. OBJECTIVE: To decipher the role of microdeletions outside hotspots loci and risk assessment by epilepsy subtype. METHODS: We assessed the burden, frequency and genomic content of rare, large microdeletions found in a previously published cohort of 1366 patients with genetic generalised epilepsy (GGE) in addition to two sets of additional unpublished genome-wide microdeletions found in 281 patients with rolandic epilepsy (RE) and 807 patients with adult focal epilepsy (AFE), totalling 2454 cases. Microdeletions were assessed in a combined and subtype-specific approaches against 6746 controls. RESULTS: When hotspots are considered, we detected an enrichment of microdeletions in the combined epilepsy analysis (adjusted p=1.06×10-6,OR 1.89, 95% CI 1.51 to 2.35). Epilepsy subtype-specific analyses showed that hotspot microdeletions in the GGE subgroup contribute most of the overall signal (adjusted p=9.79×10-12, OR 7.45, 95% CI 4.20-13.5). Outside hotspots , microdeletions were enriched in the GGE cohort for neurodevelopmental genes (adjusted p=9.13×10-3,OR 2.85, 95% CI 1.62-4.94). No additional signal was observed for RE and AFE. Still, gene-content analysis identified known (NRXN1, RBFOX1 and PCDH7) and novel (LOC102723362) candidate genes across epilepsy subtypes that were not deleted in controls. CONCLUSIONS: Our results show a heterogeneous effect of recurrent and non-recurrent microdeletions as part of the genetic architecture of GGE and a minor contribution in the aetiology of RE and AFE.

Selectivity in genetic association with sub-classified migraine in women.

Migraine can be sub-classified not only according to presence of migraine aura (MA) or absence of migraine aura (MO), but also by additional features accompanying migraine attacks, e.g. photophobia, phonophobia, nausea, etc. all of which are formally recognized by the International Classification of Headache Disorders. It remains unclear how aura status and the other migraine features may be related to underlying migraine pathophysiology. Recent genome-wide association studies (GWAS) have identified 12 independent loci at which single nucleotide polymorphisms (SNPs) are associated with migraine. Using a likelihood framework, we explored the selective association of these SNPs with migraine, sub-classified according to aura status and the other features in a large population-based cohort of women including 3,003 active migraineurs and 18,108 free of migraine. Five loci met stringent significance for association with migraine, among which four were selective for sub-classified migraine, including rs11172113 (LRP1) for MO. The number of loci associated with migraine increased to 11 at suggestive significance thresholds, including five additional selective associations for MO but none for MA. No two SNPs showed similar patterns of selective association with migraine characteristics. At one extreme, SNPs rs6790925 (near TGFBR2) and rs2274316 (MEF2D) were not associated with migraine overall, MA, or MO but were selective for migraine sub-classified by the presence of one or more of the additional migraine features. In contrast, SNP rs7577262 (TRPM8) was associated with migraine overall and showed little or no selectivity for any of the migraine characteristics. The results emphasize the multivalent nature of migraine pathophysiology and suggest that a complete understanding of the genetic influence on migraine may benefit from analyses that stratify migraine according to both aura status and the additional diagnostic features used for clinical characterization of migraine.

High risk population isolate reveals low frequency variants predisposing to intracranial aneurysms.

3% of the population develops saccular intracranial aneurysms (sIAs), a complex trait, with a sporadic and a familial form. Subarachnoid hemorrhage from sIA (sIA-SAH) is a devastating form of stroke. Certain rare genetic variants are enriched in the Finns, a population isolate with a small founder population and bottleneck events. As the sIA-SAH incidence in Finland is >2× increased, such variants may associate with sIA in the Finnish population. We tested 9.4 million variants for association in 760 Finnish sIA patients (enriched for familial sIA), and in 2,513 matched controls with case-control status and with the number of sIAs. The most promising loci (p<5E-6) were replicated in 858 Finnish sIA patients and 4,048 controls. The frequencies and effect sizes of the replicated variants were compared to a continental European population using 717 Dutch cases and 3,004 controls. We discovered four new high-risk loci with low frequency lead variants. Three were associated with the case-control status: 2q23.3 (MAF 2.1%, OR 1.89, p 1.42×10-9); 5q31.3 (MAF 2.7%, OR 1.66, p 3.17×10-8); 6q24.2 (MAF 2.6%, OR 1.87, p 1.87×10-11) and one with the number of sIAs: 7p22.1 (MAF 3.3%, RR 1.59, p 6.08×-9). Two of the associations (5q31.3, 6q24.2) replicated in the Dutch sample. The 7p22.1 locus was strongly differentiated; the lead variant was more frequent in Finland (4.6%) than in the Netherlands (0.3%). Additionally, we replicated a previously inconclusive locus on 2q33.1 in all samples tested (OR 1.27, p 1.87×10-12). The five loci explain 2.1% of the sIA heritability in Finland, and may relate to, but not explain, the increased incidence of sIA-SAH in Finland. This study illustrates the utility of population isolates, familial enrichment, dense genotype imputation and alternate phenotyping in search for variants associated with complex diseases.

Gene co-expression analysis identifies brain regions and cell types involved in migraine pathophysiology: a GWAS-based study using the Allen Human Brain Atlas.

Migraine is a common disabling neurovascular brain disorder typically characterised by attacks of severe headache and associated with autonomic and neurological symptoms. Migraine is caused by an interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified over a dozen genetic loci associated with migraine. Here, we integrated migraine GWAS data with high-resolution spatial gene expression data of normal adult brains from the Allen Human Brain Atlas to identify specific brain regions and molecular pathways that are possibly involved in migraine pathophysiology. To this end, we used two complementary methods. In GWAS data from 23,285 migraine cases and 95,425 controls, we first studied modules of co-expressed genes that were calculated based on human brain expression data for enrichment of genes that showed association with migraine. Enrichment of a migraine GWAS signal was found for five modules that suggest involvement in migraine pathophysiology of: (i) neurotransmission, protein catabolism and mitochondria in the cortex; (ii) transcription regulation in the cortex and cerebellum; and (iii) oligodendrocytes and mitochondria in subcortical areas. Second, we used the high-confidence genes from the migraine GWAS as a basis to construct local migraine-related co-expression gene networks. Signatures of all brain regions and pathways that were prominent in the first method also surfaced in the second method, thus providing support that these brain regions and pathways are indeed involved in migraine pathophysiology.

In silico phenotyping via co-training for improved phenotype prediction from genotype.

MOTIVATION: Predicting disease phenotypes from genotypes is a key challenge in medical applications in the postgenomic era. Large training datasets of patients that have been both genotyped and phenotyped are the key requisite when aiming for high prediction accuracy. With current genotyping projects producing genetic data for hundreds of thousands of patients, large-scale phenotyping has become the bottleneck in disease phenotype prediction. RESULTS: Here we present an approach for imputing missing disease phenotypes given the genotype of a patient. Our approach is based on co-training, which predicts the phenotype of unlabeled patients based on a second class of information, e.g. clinical health record information. Augmenting training datasets by this type of in silico phenotyping can lead to significant improvements in prediction accuracy. We demonstrate this on a dataset of patients with two diagnostic types of migraine, termed migraine with aura and migraine without aura, from the International Headache Genetics Consortium. CONCLUSIONS: Imputing missing disease phenotypes for patients via co-training leads to larger training datasets and improved prediction accuracy in phenotype prediction. AVAILABILITY AND IMPLEMENTATION: The code can be obtained at: http://www.bsse.ethz.ch/mlcb/research/bioinformatics-and-computational-biology/co-training.html

Involvement of astrocyte and oligodendrocyte gene sets in migraine.

BACKGROUND: Migraine is a common episodic brain disorder characterized by recurrent attacks of severe unilateral headache and additional neurological symptoms. Two main migraine types can be distinguished based on the presence of aura symptoms that can accompany the headache: migraine with aura and migraine without aura. Multiple genetic and environmental factors confer disease susceptibility. Recent genome-wide association studies (GWAS) indicate that migraine susceptibility genes are involved in various pathways, including neurotransmission, which have already been implicated in genetic studies of monogenic familial hemiplegic migraine, a subtype of migraine with aura. METHODS: To further explore the genetic background of migraine, we performed a gene set analysis of migraine GWAS data of 4954 clinic-based patients with migraine, as well as 13,390 controls. Curated sets of synaptic genes and sets of genes predominantly expressed in three glial cell types (astrocytes, microglia and oligodendrocytes) were investigated. DISCUSSION: Our results show that gene sets containing astrocyte- and oligodendrocyte-related genes are associated with migraine, which is especially true for gene sets involved in protein modification and signal transduction. Observed differences between migraine with aura and migraine without aura indicate that both migraine types, at least in part, seem to have a different genetic background.

Systematic re-evaluation of genes from candidate gene association studies in migraine using a large genome-wide association data set.

BACKGROUND: Before the genome-wide association (GWA) era, many hypothesis-driven candidate gene association studies were performed that tested whether DNA variants in genes that had been selected based on prior knowledge about migraine pathophysiology were associated with migraine. Most studies involved small sample sets without robust replication, thereby making the risk of false-positive findings high. Genome-wide marker data of thousands of migraine patients and controls from the International Headache Genetics Consortium provide a unique opportunity to re-evaluate key findings from candidate gene association studies (and other non-GWA genetic studies) in a much larger data set. METHODS: We selected 21 genes from published candidate gene association studies and six additional genes from other non-GWA genetic studies in migraine. Single nucleotide polymorphisms (SNPs) in these genes, as well as in the regions 500 kb up- and downstream, were inspected in IHGC GWAS data from 5175 clinic-based migraine patients with and without aura and 13,972 controls. RESULTS: None of the SNPs in or near the 27 genes, including the SNPs that were previously found to be associated with migraine, reached the Bonferroni-corrected significance threshold; neither when analyzing all migraine patients together, nor when analyzing the migraine with and without aura patients or males and females separately. CONCLUSION: The available migraine GWAS data provide no clear evidence for involvement of the previously reported most promising candidate genes in migraine.

Gene-based pleiotropy across migraine with aura and migraine without aura patient groups.

INTRODUCTION: It is unclear whether patients diagnosed according to International Classification of Headache Disorders criteria for migraine with aura (MA) and migraine without aura (MO) experience distinct disorders or whether their migraine subtypes are genetically related. AIM: Using a novel gene-based (statistical) approach, we aimed to identify individual genes and pathways associated both with MA and MO. METHODS: Gene-based tests were performed using genome-wide association summary statistic results from the most recent International Headache Genetics Consortium study comparing 4505 MA cases with 34,813 controls and 4038 MO cases with 40,294 controls. After accounting for non-independence of gene-based test results, we examined the significance of the proportion of shared genes associated with MA and MO. RESULTS: We found a significant overlap in genes associated with MA and MO. Of the total 1514 genes with a nominally significant gene-based p value (pgene-based ≤ 0.05) in the MA subgroup, 107 also produced pgene-based ≤ 0.05 in the MO subgroup. The proportion of overlapping genes is almost double the empirically derived null expectation, producing significant evidence of gene-based overlap (pleiotropy) (pbinomial-test = 1.5 × 10(-4)). Combining results across MA and MO, six genes produced genome-wide significant gene-based p values. Four of these genes (TRPM8, UFL1, FHL5 and LRP1) were located in close proximity to previously reported genome-wide significant SNPs for migraine, while two genes, TARBP2 and NPFF separated by just 259 bp on chromosome 12q13.13, represent a novel risk locus. The genes overlapping in both migraine types were enriched for functions related to inflammation, the cardiovascular system and connective tissue. CONCLUSIONS: Our results provide novel insight into the likely genes and biological mechanisms that underlie both MA and MO, and when combined with previous data, highlight the neuropeptide FF-amide peptide encoding gene (NPFF) as a novel candidate risk gene for both types of migraine.

Genome-wide association and longitudinal analyses reveal genetic loci linking pubertal height growth, pubertal timing and childhood adiposity.

The pubertal height growth spurt is a distinctive feature of childhood growth reflecting both the central onset of puberty and local growth factors. Although little is known about the underlying genetics, growth variability during puberty correlates with adult risks for hormone-dependent cancer and adverse cardiometabolic health. The only gene so far associated with pubertal height growth, LIN28B, pleiotropically influences childhood growth, puberty and cancer progression, pointing to shared underlying mechanisms. To discover genetic loci influencing pubertal height and growth and to place them in context of overall growth and maturation, we performed genome-wide association meta-analyses in 18 737 European samples utilizing longitudinally collected height measurements. We found significant associations (P < 1.67 × 10(-8)) at 10 loci, including LIN28B. Five loci associated with pubertal timing, all impacting multiple aspects of growth. In particular, a novel variant correlated with expression of MAPK3, and associated both with increased prepubertal growth and earlier menarche. Another variant near ADCY3-POMC associated with increased body mass index, reduced pubertal growth and earlier puberty. Whereas epidemiological correlations suggest that early puberty marks a pathway from rapid prepubertal growth to reduced final height and adult obesity, our study shows that individual loci associating with pubertal growth have variable longitudinal growth patterns that may differ from epidemiological observations. Overall, this study uncovers part of the complex genetic architecture linking pubertal height growth, the timing of puberty and childhood obesity and provides new information to pinpoint processes linking these traits.

Concordance of genetic risk across migraine subgroups: Impact on current and future genetic association studies.

BACKGROUND: There has been intensive debate whether migraine with aura (MA) and migraine without aura (MO) should be considered distinct subtypes or part of the same disease spectrum. There is also discussion to what extent migraine cases collected in specialised headache clinics differ from cases from population cohorts, and how female cases differ from male cases with respect to their migraine. To assess the genetic overlap between these migraine subgroups, we examined genome-wide association (GWA) results from analysis of 23,285 migraine cases and 95,425 population-matched controls. METHODS: Detailed heterogeneity analysis of single-nucleotide polymorphism (SNP) effects (odds ratios) between migraine subgroups was performed for the 12 independent SNP loci significantly associated (p < 5 × 10(-8); thus surpassing the threshold for genome-wide significance) with migraine susceptibility. Overall genetic overlap was assessed using SNP effect concordance analysis (SECA) at over 23,000 independent SNPs. RESULTS: Significant heterogeneity of SNP effects (p het < 1.4 × 10(-3)) was observed between the MA and MO subgroups (for SNP rs9349379), and between the clinic- and population-based subgroups (for SNPs rs10915437, rs6790925 and rs6478241). However, for all 12 SNPs the risk-increasing allele was the same, and SECA found the majority of genome-wide SNP effects to be in the same direction across the subgroups. CONCLUSIONS: Any differences in common genetic risk across these subgroups are outweighed by the similarities. Meta-analysis of additional migraine GWA datasets, regardless of their major subgroup composition, will identify new susceptibility loci for migraine.

Founder population-specific HapMap panel increases power in GWA studies through improved imputation accuracy and CNV tagging.

The combining of genome-wide association (GWA) data across populations represents a major challenge for massive global meta-analyses. Genotype imputation using densely genotyped reference samples facilitates the combination of data across different genotyping platforms. HapMap data is typically used as a reference for single nucleotide polymorphism (SNP) imputation and tagging copy number polymorphisms (CNPs). However, the advantage of having population-specific reference panels for founder populations has not been evaluated. We looked at the properties and impact of adding 81 individuals from a founder population to HapMap3 reference data on imputation quality, CNP tagging, and power to detect association in simulations and in an independent cohort of 2138 individuals. The gain in SNP imputation accuracy was highest among low-frequency markers (minor allele frequency [MAF] < 5%), for which adding the population-specific samples to the reference set increased the median R(2) between imputed and genotyped SNPs from 0.90 to 0.94. Accuracy also increased in regions with high recombination rates. Similarly, a reference set with population-specific extension facilitated the identification of better tag-SNPs for a subset of CNPs; for 4% of CNPs the R(2) between SNP genotypes and CNP intensity in the independent population cohort was at least twice as high as without the extension. We conclude that even a relatively small population-specific reference set yields considerable benefits in SNP imputation, CNP tagging accuracy, and the power to detect associations in founder populations and population isolates in particular.

Novel mutations consolidate KCTD7 as a progressive myoclonus epilepsy gene.

BACKGROUND: The progressive myoclonus epilepsies (PMEs) comprise a group of clinically and genetically heterogeneous disorders characterised by myoclonus, epilepsy, and neurological deterioration. This study aimed to identify the underlying gene(s) in childhood onset PME patients with unknown molecular genetic background. METHODS: Homozygosity mapping was applied on genome-wide single nucleotide polymorphism data of 18 Turkish patients. The potassium channel tetramerisation domain-containing 7 (KCTD7) gene, previously associated with PME in a single inbred family, was screened for mutations. The spatiotemporal expression of KCTD7 was assessed in cellular cultures and mouse brain tissue. RESULTS: Overlapping homozygosity in 8/18 patients defined a 1.5 Mb segment on 7q11.21 as the major candidate locus. Screening of the positional candidate gene KCTD7 revealed homozygous missense mutations in two of the eight cases. Screening of KCTD7 in a further 132 PME patients revealed four additional mutations (two missense, one in-frame deletion, and one frameshift-causing) in five families. Eight patients presented with myoclonus and epilepsy and one with ataxia, the mean age of onset being 19 months. Within 2 years after onset, progressive loss of mental and motor skills ensued leading to severe dementia and motor handicap. KCTD7 showed cytosolic localisation and predominant neuronal expression, with widespread expression throughout the brain. None of three polypeptides carrying patient missense mutations affected the subcellular distribution of KCTD7. DISCUSSION: These data confirm the causality of KCTD7 defects in PME, and imply that KCTD7 mutation screening should be considered in PME patients with onset around 2 years of age followed by rapid mental and motor deterioration.