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.

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.

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.].

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.

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.

Analysis of shared heritability in common disorders of the brain.

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

Common Variant Burden Contributes to the Familial Aggregation of Migraine in 1,589 Families.

Complex traits, including migraine, often aggregate in families, but the underlying genetic architecture behind this is not well understood. The aggregation could be explained by rare, penetrant variants that segregate according to Mendelian inheritance or by the sufficient polygenic accumulation of common variants, each with an individually small effect, or a combination of the two hypotheses. In 8,319 individuals across 1,589 migraine families, we calculated migraine polygenic risk scores (PRS) and found a significantly higher common variant burden in familial cases (n = 5,317, OR = 1.76, 95% CI = 1.71-1.81, p = 1.7 × 10-109) compared to population cases from the FINRISK cohort (n = 1,101, OR = 1.32, 95% CI = 1.25-1.38, p = 7.2 × 10-17). The PRS explained 1.6% of the phenotypic variance in the population cases and 3.5% in the familial cases (including 2.9% for migraine without aura, 5.5% for migraine with typical aura, and 8.2% for hemiplegic migraine). The results demonstrate a significant contribution of common polygenic variation to the familial aggregation of migraine.

Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types.

We introduce an approach to identify disease-relevant tissues and cell types by analyzing gene expression data together with genome-wide association study (GWAS) summary statistics. Our approach uses stratified linkage disequilibrium (LD) score regression to test whether disease heritability is enriched in regions surrounding genes with the highest specific expression in a given tissue. We applied our approach to gene expression data from several sources together with GWAS summary statistics for 48 diseases and traits (average N = 169,331) and found significant tissue-specific enrichments (false discovery rate (FDR) < 5%) for 34 traits. In our analysis of multiple tissues, we detected a broad range of enrichments that recapitulated known biology. In our brain-specific analysis, significant enrichments included an enrichment of inhibitory over excitatory neurons for bipolar disorder, and excitatory over inhibitory neurons for schizophrenia and body mass index. Our results demonstrate that our polygenic approach is a powerful way to leverage gene expression data for interpreting GWAS signals.

Statistical power and utility of meta-analysis methods for cross-phenotype genome-wide association studies.

Advances in recent genome wide association studies (GWAS) suggest that pleiotropic effects on human complex traits are widespread. A number of classic and recent meta-analysis methods have been used to identify genetic loci with pleiotropic effects, but the overall performance of these methods is not well understood. In this work, we use extensive simulations and case studies of GWAS datasets to investigate the power and type-I error rates of ten meta-analysis methods. We specifically focus on three conditions commonly encountered in the studies of multiple traits: (1) extensive heterogeneity of genetic effects; (2) characterization of trait-specific association; and (3) inflated correlation of GWAS due to overlapping samples. Although the statistical power is highly variable under distinct study conditions, we found the superior power of several methods under diverse heterogeneity. In particular, classic fixed-effects model showed surprisingly good performance when a variant is associated with more than a half of study traits. As the number of traits with null effects increases, ASSET performed the best along with competitive specificity and sensitivity. With opposite directional effects, CPASSOC featured the first-rate power. However, caution is advised when using CPASSOC for studying genetically correlated traits with overlapping samples. We conclude with a discussion of unresolved issues and directions for future research.

Genetics of migraine.

Genetics of migraine has recently undergone a major shift, moving in the space of a few years from having only a few known genes for rare Mendelian forms to 47 known common variant loci affecting the susceptibility of the common forms of migraine. This has largely been achieved by rapidly increasing sample sizes for genomewide association studies (GWAS), soon to be followed by the first wave of large-scale exome-sequencing studies. The large number of detected loci, chief among them TRPM8, PRDM16, and LRP1, have enabled a number of in silico analyses, which have shed light on the functional and tissue-level aspects of the common risk variants for migraine, including evidence for involvement of both vascular and neuronal mechanisms. Polygenic risk scores and other measures of genetic variance based on GWAS information are further opening the door to dissecting pharmacogenetics, functional etiology, and comorbidity. Heritability-based analyses are demonstrating strong links between migraine and other neuropsychiatric disorders and brain phenotypes, highlighting genetic links between migraine and major depressive disorder and attention-deficit hyperactivity disorder, among others. These recent successes in migraine genetics are starting to be mature enough to provide robust evidence of specific quantifiable genetic factors in common migraine.

Shared genetic risk between migraine and coronary artery disease: A genome-wide analysis of common variants.

Migraine is a recurrent pain condition traditionally viewed as a neurovascular disorder, but little is known of its vascular basis. In epidemiological studies migraine is associated with an increased risk of cardiovascular disease, including coronary artery disease (CAD), suggesting shared pathogenic mechanisms. This study aimed to determine the genetic overlap between migraine and CAD, and to identify shared genetic risk loci, utilizing a conditional false discovery rate approach and data from two large-scale genome-wide association studies (GWAS) of CAD (C4D, 15,420 cases, 15,062 controls; CARDIoGRAM, 22,233 cases, 64,762 controls) and one of migraine (22,120 cases, 91,284 controls). We found significant enrichment of genetic variants associated with CAD as a function of their association with migraine, which was replicated across two independent CAD GWAS studies. One shared risk locus in the PHACTR1 gene (conjunctional false discovery rate for index SNP rs9349379 < 3.90 x 10-5), which was also identified in previous studies, explained much of the enrichment. Two further loci (in KCNK5 and AS3MT) showed evidence for shared risk (conjunctional false discovery rate < 0.05). The index SNPs at two of the three loci had opposite effect directions in migraine and CAD. Our results confirm previous reports that migraine and CAD share genetic risk loci in excess of what would be expected by chance, and highlight one shared risk locus in PHACTR1. Understanding the biological mechanisms underpinning this shared risk is likely to improve our understanding of both disorders.

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.

SNP Variants in Major Histocompatibility Complex Are Associated with Sarcoidosis Susceptibility-A Joint Analysis in Four European Populations.

Sarcoidosis is a multiorgan inflammatory disorder with heritability estimates up to 66%. Previous studies have shown the major histocompatibility complex (MHC) region to be associated with sarcoidosis, suggesting a functional role for antigen-presenting molecules and immune mediators in the disease pathogenesis. To detect variants predisposing to sarcoidosis and to identify genetic differences between patient subgroups, we studied four genes in the MHC Class III region (LTA, TNF, AGER, BTNL2) and HLA-DRA with tag-SNPs and their relation to HLA-DRB1 alleles. We present results from a joint analysis of four study populations (Finnish, Swedish, Dutch, and Czech). Patients with sarcoidosis (n = 805) were further subdivided based on the disease activity and the presence of Löfgren's syndrome. In a joint analysis, seven SNPs were associated with non-Löfgren sarcoidosis (NL; the strongest association with rs3177928, P = 1.79E-07, OR = 1.9) and eight with Löfgren's syndrome [Löfgren syndrome (LS); the strongest association with rs3129843, P = 3.44E-12, OR = 3.4] when compared with healthy controls (n = 870). Five SNPs were associated with sarcoidosis disease course (the strongest association with rs3177928, P = 0.003, OR = 1.9). The high linkage disequilibrium (LD) between SNPs and an HLA-DRB1 challenged the result interpretation. When the SNPs and HLA-DRB1 alleles were analyzed together, independent association was observed for four SNPs in the HLA-DRA/BTNL2 region: rs3135365 (NL; P = 0.015), rs3177928 (NL; P < 0.001), rs6937545 (LS; P = 0.012), and rs5007259 (disease activity; P = 0.002). These SNPs act as expression quantitative trait loci (eQTL) for HLA-DRB1 and/or HLA-DRB5. In conclusion, we found novel SNPs in BTNL2 and HLA-DRA regions associating with sarcoidosis. Our finding further establishes that polymorphisms in the HLA-DRA and BTNL2 have a role in sarcoidosis susceptibility. This multi-population study demonstrates that at least a part of these associations are HLA-DRB1 independent (e.g., not due to LD) and shared across ancestral origins. The variants that were independent of HLA-DRB1 associations acted as eQTL for HLA-DRB1 and/or -DRB5, suggesting a role in regulating gene expression.

Significant Locus and Metabolic Genetic Correlations Revealed in Genome-Wide Association Study of Anorexia Nervosa.

OBJECTIVE: The authors conducted a genome-wide association study of anorexia nervosa and calculated genetic correlations with a series of psychiatric, educational, and metabolic phenotypes. METHOD: Following uniform quality control and imputation procedures using the 1000 Genomes Project (phase 3) in 12 case-control cohorts comprising 3,495 anorexia nervosa cases and 10,982 controls, the authors performed standard association analysis followed by a meta-analysis across cohorts. Linkage disequilibrium score regression was used to calculate genome-wide common variant heritability (single-nucleotide polymorphism [SNP]-based heritability [h2SNP]), partitioned heritability, and genetic correlations (rg) between anorexia nervosa and 159 other phenotypes. RESULTS: Results were obtained for 10,641,224 SNPs and insertion-deletion variants with minor allele frequencies >1% and imputation quality scores >0.6. The h2SNP of anorexia nervosa was 0.20 (SE=0.02), suggesting that a substantial fraction of the twin-based heritability arises from common genetic variation. The authors identified one genome-wide significant locus on chromosome 12 (rs4622308) in a region harboring a previously reported type 1 diabetes and autoimmune disorder locus. Significant positive genetic correlations were observed between anorexia nervosa and schizophrenia, neuroticism, educational attainment, and high-density lipoprotein cholesterol, and significant negative genetic correlations were observed between anorexia nervosa and body mass index, insulin, glucose, and lipid phenotypes. CONCLUSIONS: Anorexia nervosa is a complex heritable phenotype for which this study has uncovered the first genome-wide significant locus. Anorexia nervosa also has large and significant genetic correlations with both psychiatric phenotypes and metabolic traits. The study results encourage a reconceptualization of this frequently lethal disorder as one with both psychiatric and metabolic etiology.

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.

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.

Genome-Wide Meta-Analysis of Sciatica in Finnish Population.

Sciatica or the sciatic syndrome is a common and often disabling low back disorder in the working-age population. It has a relatively high heritability but poorly understood molecular mechanisms. The Finnish population is a genetic isolate where small founder population and bottleneck events have led to enrichment of certain rare and low frequency variants. We performed here the first genome-wide association (GWAS) and meta-analysis of sciatica. The meta-analysis was conducted across two GWAS covering 291 Finnish sciatica cases and 3671 controls genotyped and imputed at 7.7 million autosomal variants. The most promising loci (p<1x10-6) were replicated in 776 Finnish sciatica patients and 18,489 controls. We identified five intragenic variants, with relatively low frequencies, at two novel loci associated with sciatica at genome-wide significance. These included chr9:14344410:I (rs71321981) at 9p22.3 (NFIB gene; p = 1.30x10-8, MAF = 0.08) and four variants at 15q21.2: rs145901849, rs80035109, rs190200374 and rs117458827 (MYO5A; p = 1.34x10-8, MAF = 0.06; p = 2.32x10-8, MAF = 0.07; p = 3.85x10-8, MAF = 0.06; p = 4.78x10-8, MAF = 0.07, respectively). The most significant association in the meta-analysis, a single base insertion rs71321981 within the regulatory region of the transcription factor NFIB, replicated in an independent Finnish population sample (p = 0.04). Despite identifying 15q21.2 as a promising locus, we were not able to replicate it. It was differentiated; the lead variants within 15q21.2 were more frequent in Finland (6-7%) than in other European populations (1-2%). Imputation accuracies of the three significantly associated variants (chr9:14344410:I, rs190200374, and rs80035109) were validated by genotyping. In summary, our results suggest a novel locus, 9p22.3 (NFIB), which may be involved in susceptibility to sciatica. In addition, another locus, 15q21.2, emerged as a promising one, but failed to replicate.

Meta-analysis of 375,000 individuals identifies 38 susceptibility loci for migraine.

Migraine is a debilitating neurological disorder affecting around one in seven people worldwide, but its molecular mechanisms remain poorly understood. There is some debate about whether migraine is a disease of vascular dysfunction or a result of neuronal dysfunction with secondary vascular changes. Genome-wide association (GWA) studies have thus far identified 13 independent loci associated with migraine. To identify new susceptibility loci, we carried out a genetic study of migraine on 59,674 affected subjects and 316,078 controls from 22 GWA studies. We identified 44 independent single-nucleotide polymorphisms (SNPs) significantly associated with migraine risk (P < 5 × 10(-8)) that mapped to 38 distinct genomic loci, including 28 loci not previously reported and a locus that to our knowledge is the first to be identified on chromosome X. In subsequent computational analyses, the identified loci showed enrichment for genes expressed in vascular and smooth muscle tissues, consistent with a predominant theory of migraine that highlights vascular etiologies.