Genetic overlap and causality between blood metabolites and migraine.

The availability of genome-wide association studies (GWASs) for human blood metabolome provides an excellent opportunity for studying metabolism in a heritable disease such as migraine. Utilizing GWAS summary statistics, we conduct comprehensive pairwise genetic analyses to estimate polygenic genetic overlap and causality between 316 unique blood metabolite levels and migraine risk. We find significant genome-wide genetic overlap between migraine and 44 metabolites, mostly lipid and organic acid metabolic traits (FDR < 0.05). We also identify 36 metabolites, mostly related to lipoproteins, that have shared genetic influences with migraine at eight independent genomic loci (posterior probability > 0.9) across chromosomes 3, 5, 6, 9, and 16. The observed relationships between genetic factors influencing blood metabolite levels and genetic risk for migraine suggest an alteration of metabolite levels in individuals with migraine. Our analyses suggest higher levels of fatty acids, except docosahexaenoic acid (DHA), a very long-chain omega-3, in individuals with migraine. Consistently, we found a causally protective role for a longer length of fatty acids against migraine. We also identified a causal effect for a higher level of a lysophosphatidylethanolamine, LPE(20:4), on migraine, thus introducing LPE(20:4) as a potential therapeutic target for migraine.

Cross-trait analyses identify shared genetics between migraine, headache, and glycemic traits, and a causal relationship with fasting proinsulin.

The co-occurrence of migraine and glycemic traits has long been reported in observational epidemiological studies, but it has remained unknown how they are linked genetically. We used large-scale GWAS summary statistics on migraine, headache, and nine glycemic traits in European populations to perform cross-trait analyses to estimate genetic correlation, identify shared genomic regions, loci, genes, and pathways, and test for causal relationships. Out of the nine glycemic traits, significant genetic correlation was observed for fasting insulin (FI) and glycated haemoglobin (HbA1c) with both migraine and headache, while 2-h glucose was genetically correlated only with migraine. Among 1703 linkage disequilibrium (LD) independent regions of the genome, we found pleiotropic regions between migraine and FI, fasting glucose (FG), and HbA1c, and pleiotropic regions between headache and glucose, FI, HbA1c, and fasting proinsulin. Cross-trait GWAS meta-analysis with glycemic traits, identified six novel genome-wide significant lead SNPs with migraine, and six novel lead SNPs with headache (Pmeta < 5.0 × 10-8 and Psingle-trait < 1 × 10-4), all of which were LD-independent. Genes with a nominal gene-based association (Pgene ≤ 0.05) were significantly enriched (overlapping) across the migraine, headache, and glycemic traits. Mendelian randomisation analyses produced intriguing, but inconsistent, evidence for a causal relationship between migraine and headache with multiple glycemic traits; and consistent evidence suggesting increased fasting proinsulin levels may causally decrease the risk of headache. Our findings indicate that migraine, headache, and glycemic traits share a common genetic etiology and provide genetic insights into the molecular mechanisms contributing to their comorbid relationship.

Integrating eQTL and GWAS data characterises established and identifies novel migraine risk loci.

Migraine-a painful, throbbing headache disorder-is the most common complex brain disorder, yet its molecular mechanisms remain unclear. Genome-wide association studies (GWAS) have proven successful in identifying migraine risk loci; however, much work remains to identify the causal variants and genes. In this paper, we compared three transcriptome-wide association study (TWAS) imputation models-MASHR, elastic net, and SMultiXcan-to characterise established genome-wide significant (GWS) migraine GWAS risk loci, and to identify putative novel migraine risk gene loci. We compared the standard TWAS approach of analysing 49 GTEx tissues with Bonferroni correction for testing all genes present across all tissues (Bonferroni), to TWAS in five tissues estimated to be relevant to migraine, and TWAS with Bonferroni correction that took into account the correlation between eQTLs within each tissue (Bonferroni-matSpD). Elastic net models performed in all 49 GTEx tissues using Bonferroni-matSpD characterised the highest number of established migraine GWAS risk loci (n = 20) with GWS TWAS genes having colocalisation (PP4 > 0.5) with an eQTL. SMultiXcan in all 49 GTEx tissues identified the highest number of putative novel migraine risk genes (n = 28) with GWS differential expression at 20 non-GWS GWAS loci. Nine of these putative novel migraine risk genes were later found to be at and in linkage disequilibrium with true (GWS) migraine risk loci in a recent, more powerful migraine GWAS. Across all TWAS approaches, a total of 62 putative novel migraine risk genes were identified at 32 independent genomic loci. Of these 32 loci, 21 were true risk loci in the recent, more powerful migraine GWAS. Our results provide important guidance on the selection, use, and utility of imputation-based TWAS approaches to characterise established GWAS risk loci and identify novel risk gene loci.

Genome-wide Association Analysis in Humans Links Nucleotide Metabolism to Leukocyte Telomere Length.

Leukocyte telomere length (LTL) is a heritable biomarker of genomic aging. In this study, we perform a genome-wide meta-analysis of LTL by pooling densely genotyped and imputed association results across large-scale European-descent studies including up to 78,592 individuals. We identify 49 genomic regions at a false dicovery rate (FDR) < 0.05 threshold and prioritize genes at 31, with five highlighting nucleotide metabolism as an important regulator of LTL. We report six genome-wide significant loci in or near SENP7, MOB1B, CARMIL1, PRRC2A, TERF2, and RFWD3, and our results support recently identified PARP1, POT1, ATM, and MPHOSPH6 loci. Phenome-wide analyses in >350,000 UK Biobank participants suggest that genetically shorter telomere length increases the risk of hypothyroidism and decreases the risk of thyroid cancer, lymphoma, and a range of proliferative conditions. Our results replicate previously reported associations with increased risk of coronary artery disease and lower risk for multiple cancer types. Our findings substantially expand current knowledge on genes that regulate LTL and their impact on human health and disease.

Shared genetics and causal relationships between migraine and thyroid function traits.

BACKGROUND: Epidemiological studies have reported a comorbid relationship between migraine and thyroid dysfunction. METHODS: We investigated the genetic relationship between migraine and thyroid function traits using genome-wide association study (GWAS) data. RESULTS: We found a significant genetic correlation (rg) with migraine for hypothyroidism (rg = 0.0608), secondary hypothyroidism (rg = 0.195), free thyroxine (fT4) (rg = 0.0772), and hyperthyroidism (rg = -0.1046), but not thyroid stimulating hormone (TSH). Pairwise GWAS analysis revealed two shared loci with TSH and 11 shared loci with fT4. Cross-trait GWAS meta-analysis of migraine identified novel genome-wide significant loci: 17 with hypothyroidism, one with hyperthyroidism, five with secondary hypothyroidism, eight with TSH, and 15 with fT4. Of the genes at these loci, six (RERE, TGFB2, APLF, SLC9B1, SGTB, BTBD16; migraine + hypothyroidism), three (GADD45A, PFDN1, RSPH6A; migraine + TSH), and three (SSBP3, BRD3, TEF; migraine + fT4) were significant in our gene-based analysis (pFisher's combined P-value < 2.04 × 10-6). In addition, causal analyses suggested a negative causal relationship between migraine and hyperthyroidism (p = 8.90 × 10-3) and a positive causal relationship between migraine and secondary hypothyroidism (p = 1.30 × 10-3). CONCLUSION: These findings provide strong evidence for genetic correlation and suggest complex causal relationships between migraine and thyroid traits.

Migraine genetics: Status and road forward.

BACKGROUND: Migraine is considered a multifactorial genetic disorder. Different platforms and methods are used to unravel the genetic basis of migraine. Initially, linkage analysis in multigenerational families followed by Sanger sequencing of protein-coding parts (exons) of genes in the genomic region shared by affected family members identified high-effect risk DNA mutations for rare Mendelian forms of migraine, foremost hemiplegic migraine. More recently, genome-wide association studies testing millions of DNA variants in large groups of patients and controls have proven successful in identifying many dozens of low-effect risk DNA variants for the more common forms of migraine with the number of associated DNA variants increasing steadily with larger sample sizes. Currently, next-generation sequencing, utilising whole exome and whole genome sequence data, and other omics data are being used to facilitate their functional interpretation and the discovery of additional risk factors. Various methods and analysis tools, such as genetic correlation and causality analysis, are used to further characterise genetic risk factors. FINDINGS: We describe recent findings in genome-wide association studies and next-generation sequencing analysis in migraine. We show that the combined results of the two most recent and most powerful migraine genome-wide association studies have identified a total of 178 LD-independent (r2 < 0.1) genome-wide significant single nucleotide polymorphisms (SNPs), of which 99 were unique to Hautakangas et al., 11 were unique to Choquet et al., and 68 were identified by both studies. When considering that Choquet et al. also identified three SNPs in a female-specific genome-wide association studies then these two recent studies identified 181 independent SNPs robustly associated with migraine. Cross-trait and causal analyses are beginning to identify and characterise specific biological factors that contribute to migraine risk and its comorbid conditions. CONCLUSION: This review provides a timely update and overview of recent genetic findings in migraine.

Migraine and thyroid dysfunction: Co-occurrence, shared genes and biological mechanisms.

BACKGROUND AND PURPOSE: Migraine and thyroid dysfunction, particularly hypothyroidism, are common medical conditions and are known to have high heritability. Thyroid function measures, thyroid stimulating hormone (TSH) and free thyroxine (fT4), are also known to be genetically influenced. Although observational epidemiological studies report an increased co-occurrence of migraine and thyroid dysfunction, a clear and combined interpretation of the findings is currently lacking. A narrative review is provided of the epidemiological and genetic association evidence linking migraine, hypothyroidism, hyperthyroidism and thyroid hormones TSH and fT4. METHODS: An extensive literature search was conducted in the PubMed database for epidemiological, candidate gene and genome-wide association studies using the terms migraine, headache, thyroid hormones, TSH, fT4, thyroid function, hypothyroidism and hyperthyroidism. RESULTS: Epidemiological studies suggest a bidirectional relationship between migraine and thyroid dysfunction. However, the nature of the relationship remains unclear, with some studies suggesting migraine increases the risk for thyroid dysfunction whilst other studies suggest the reverse. Early candidate gene studies have provided nominal evidence for MTHFR and APOE, whilst more recently genome-wide association studies have provided robust evidence for THADA and ITPK1 being associated with both migraine and thyroid dysfunction. CONCLUSIONS: These genetic associations improve our understanding of the genetic relationship between migraine and thyroid dysfunction, provide an opportunity to develop biomarkers to identify migraine patients most likely to benefit from thyroid hormone therapy, and indicate that further cross-trait genetic studies have excellent potential to provide biological insight into their relationship and inform clinical interventions.

Elucidating the relationship between migraine risk and brain structure using genetic data.

Migraine is a highly common and debilitating disorder that often affects individuals in their most productive years of life. Previous studies have identified both genetic variants and brain morphometry differences associated with migraine risk. However, the relationship between migraine and brain morphometry has not been examined on a genetic level, and the causal nature of the association between brain structure and migraine risk has not been determined. Using the largest available genome-wide association studies to date, we examined the genome-wide genetic overlap between migraine and intracranial volume, as well as the regional volumes of nine subcortical brain structures. We further focused the identification and biological annotation of genetic overlap between migraine and each brain structure on specific regions of the genome shared between migraine and brain structure. Finally, we examined whether the size of any of the examined brain regions causally increased migraine risk using a Mendelian randomization approach. We observed a significant genome-wide negative genetic correlation between migraine risk and intracranial volume (rG = -0.11, P = 1 × 10-3) but not with any subcortical region. However, we identified jointly associated regional genomic overlap between migraine and every brain structure. Gene enrichment in these shared genomic regions pointed to possible links with neuronal signalling and vascular regulation. Finally, we provide evidence of a possible causal relationship between smaller total brain, hippocampal and ventral diencephalon volume and increased migraine risk, as well as a causal relationship between increased risk of migraine and a larger volume of the amygdala. We leveraged the power of large genome-wide association studies to show evidence of shared genetic pathways that jointly influence migraine risk and several brain structures, suggesting that altered brain morphometry in individuals with high migraine risk may be genetically mediated. Further interrogation of these results showed support for the neurovascular hypothesis of migraine aetiology and shed light on potentially viable therapeutic targets.

A comparative study of multi-omics integration tools for cancer driver gene identification and tumour subtyping.

Oncogenesis and cancer can arise as a consequence of a wide range of genomic aberrations including mutations, copy number alterations, expression changes and epigenetic modifications encompassing multiple omics layers. Integrating genomic, transcriptomic, proteomic and epigenomic datasets via multi-omics analysis provides the opportunity to derive a deeper and holistic understanding of the development and progression of cancer. There are two primary approaches to integrating multi-omics data: multi-staged (focused on identifying genes driving cancer) and meta-dimensional (focused on establishing clinically relevant tumour or sample classifications). A number of ready-to-use bioinformatics tools are available to perform both multi-staged and meta-dimensional integration of multi-omics data. In this study, we compared nine different integration tools using real and simulated cancer datasets. The performance of the multi-staged integration tools were assessed at the gene, function and pathway levels, while meta-dimensional integration tools were assessed based on the sample classification performance. Additionally, we discuss the influence of factors such as data representation, sample size, signal and noise on multi-omics data integration. Our results provide current and much needed guidance regarding selection and use of the most appropriate and best performing multi-omics integration tools.

Genome-wide associations for birth weight and correlations with adult disease.

Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P < 5 × 10-8). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (Rg = -0.22, P = 5.5 × 10-13), T2D (Rg = -0.27, P = 1.1 × 10-6) and coronary artery disease (Rg = -0.30, P = 6.5 × 10-9). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P = 1.9 × 10-4). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated.

Genetic analyses of gynecological disease identify genetic relationships between uterine fibroids and endometrial cancer, and a novel endometrial cancer genetic risk region at the WNT4 1p36.12 locus.

Endometriosis, polycystic ovary syndrome (PCOS) and uterine fibroids have been proposed as endometrial cancer risk factors; however, disentangling their relationships with endometrial cancer is complicated due to shared risk factors and comorbidities. Using genome-wide association study (GWAS) data, we explored the relationships between these non-cancerous gynecological diseases and endometrial cancer risk by assessing genetic correlation, causal relationships and shared risk loci. We found significant genetic correlation between endometrial cancer and PCOS, and uterine fibroids. Adjustment for genetically predicted body mass index (a risk factor for PCOS, uterine fibroids and endometrial cancer) substantially attenuated the genetic correlation between endometrial cancer and PCOS but did not affect the correlation with uterine fibroids. Mendelian randomization analyses suggested a causal relationship between only uterine fibroids and endometrial cancer. Gene-based analyses revealed risk regions shared between endometrial cancer and endometriosis, and uterine fibroids. Multi-trait GWAS analysis of endometrial cancer and the genetically correlated gynecological diseases identified a novel genome-wide significant endometrial cancer risk locus at 1p36.12, which replicated in an independent endometrial cancer dataset. Interrogation of functional genomic data at 1p36.12 revealed biologically relevant genes, including WNT4 which is necessary for the development of the female reproductive system. In summary, our study provides genetic evidence for a causal relationship between uterine fibroids and endometrial cancer. It further provides evidence that the comorbidity of endometrial cancer, PCOS and uterine fibroids may partly be due to shared genetic architecture. Notably, this shared architecture has revealed a novel genome-wide risk locus for endometrial cancer.

Genetic analysis of endometriosis and depression identifies shared loci and implicates causal links with gastric mucosa abnormality.

Evidence from observational studies indicates that endometriosis and depression often co-occur. However, conflicting evidence exists, and the etiology as well as biological mechanisms underlying their comorbidity remain unknown. Utilizing genome-wide association study (GWAS) data, we comprehensively assessed the relationship between endometriosis and depression. Single nucleotide polymorphism effect concordance analysis (SECA) found a significant genetic overlap between endometriosis and depression (PFsig-permuted = 9.99 × 10-4). Linkage disequilibrium score regression (LDSC) analysis estimated a positive and highly significant genetic correlation between the two traits (rG = 0.27, P = 8.85 × 10-27). A meta-analysis of endometriosis and depression GWAS (sample size = 709,111), identified 20 independent genome-wide significant loci (P < 5 × 10-8), of which eight are novel. Mendelian randomization analysis (MR) suggests a causal effect of depression on endometriosis. Combining gene-based association results across endometriosis and depression GWAS, we identified 22 genes with a genome-wide significant Fisher's combined P value (FCPgene < 2.75 × 10-6). Genes with a nominal gene-based association (Pgene < 0.05) were significantly enriched across endometriosis and depression (Pbinomial-test = 2.90 × 10-4). Also, genes overlapping the two traits at Pgene < 0.1 (Pbinomial-test = 1.31 × 10-5) were significantly enriched for the biological pathways 'cell-cell adhesion', 'inositol phosphate metabolism', 'Hippo-Merlin signaling dysregulation' and 'gastric mucosa abnormality'. These results reveal a shared genetic etiology for endometriosis and depression. Indeed, additional analyses found evidence of a causal association between each of endometriosis and depression and at least one abnormal condition of gastric mucosa. Our study confirms the comorbidity of endometriosis and depression, implicates links with gastric mucosa abnormalities in their causal pathways and reveals potential therapeutic targets for further investigation.

Association and genetic overlap between clinical chemistry tests and migraine.

INTRODUCTION: In this paper, we studied several serum clinical chemistry tests of cardiovascular disease (CVD), iron deficiency anemia, liver and kidney disorders in migraine. METHODS: We first explored the association of 22 clinical chemistry tests with migraine risk in 697 migraine patients and 2722 controls. To validate and interpret association findings, cross-trait genetic analyses were conducted utilising genome-wide association study (GWAS) data comprising 23,986 to 452,264 individuals. RESULTS: Significant associations with migraine risk were identified for biomarkers of CVD risk, iron deficiency and liver dysfunction (odds ratios = 0.86-1.21; 1 × 10-4 < p < 3 × 10-2). Results from cross-trait genetic analyses corroborate the significant biomarker associations and indicate their relationship with migraine is more consistent with biological pleiotropy than causality. For example, association and genetic overlap between a lower level of HDL-C and increased migraine risk are due to shared biology rather than a causal relationship. Furthermore, additional genetic analyses revealed shared genetics among migraine, the clinical chemistry tests, and heart problems and iron deficiency anemia, but not liver disease. CONCLUSIONS: These findings highlight common biological mechanisms underlying migraine, heart problems and iron deficiency anemia and provide support for their investigation in the development of novel therapeutic and dietary interventions.

Recognition and clinical implications of high prevalence of migraine in patients with Brugada syndrome and drug-induced type 1 Brugada pattern.

INTRODUCTION: We have previously reported high 1-year prevalence of migraine in patients with atrial arrhythmias associated with DI-type 1 BrP. The present study was designed to determine the lifetime prevalence of migraine in patients with Brugada syndrome (BrS) or drug-induced type 1 Brugada pattern (DI-type 1 BrP) and control group, to investigate the demographic and clinical characteristics, and to identify clinical variables to predict underlying BrS/DI-type 1 BrP among migraineurs. METHODS AND RESULTS: Lifetime prevalence of migraine and migraine characteristics were compared between probands with BrS/DI-type 1 BrP (n = 257) and control group (n = 370). Lifetime prevalence of migraine was 60.7% in patients with BrS/DI-type 1 BrP and 30.3% in control group (p = 3.6 × 10-14 ). On stepwise regression analysis, familial migraine (odds ratio [OR] of 4.4; 95% confidence interval [CI]: 2.0-9.8; p = 1.3 × 10-4 ), vestibular migraine (OR of 5.4; 95% CI: 1.4-21.0); p = .013), migraine with visual aura (OR of 1.8; 95% CI: 1.0-3.4); p = .04) and younger age-at-onset of migraine (OR of 0.95; 95% CI: 0.93-0.98); p = .004) were predictors of underlying BrS/DI-type 1 BrP among migraineurs. Use of anti-migraine drugs classified as "to be avoided" or "preferably avoided" in patients with BrS and several other anti-migraine drugs with potential cardiac INa /ICa channel blocking properties was present in 25.6% and 26.9% of migraineurs with BrS/DI-type 1 BrP, respectively. CONCLUSION: Migraine comorbidity is common in patients with BrS/DI-type 1 BrP. We identify several clinical variables that point to an underlying type-1 BrP among migraineurs, necessitating cautious use of certain anti-migraine drugs.

Mitochondrial genome-wide association study of migraine - the HUNT Study.

BACKGROUND: Variation in mitochondrial DNA (mtDNA) has been indicated in migraine pathogenesis, but genetic studies to date have focused on candidate variants, with sparse findings. We aimed to perform the first mitochondrial genome-wide association study of migraine, examining both single variants and mitochondrial haplogroups. METHODS: In total, 71,860 participants from the population-based Nord-Trøndelag Health Study were genotyped. We excluded samples not passing quality control for nuclear genotypes, in addition to samples with low call rate and closely maternally related. We analysed 775 mitochondrial DNA variants in 4021 migraine cases and 14,288 headache-free controls, using logistic regression. In addition, we analysed 3831 cases and 13,584 controls who could be reliably assigned to a mitochondrial haplogroup. Lastly, we attempted to replicate previously reported mitochondrial DNA candidate variants. RESULTS: Neither of the mitochondrial variants or haplogroups were associated with migraine. In addition, none of the previously reported mtDNA candidate variants replicated in our data. CONCLUSIONS: Our findings do not support a major role of mitochondrial genetic variation in migraine pathophysiology, but a larger sample is needed to detect rare variants and future studies should also examine heteroplasmic variation, epigenetic changes and copy-number variation.

Migraine, Human Genetics and a Passion for Science.

This note reflects on my collaborations with Nick Martin and the GenEpi group over the past 20 years. Over the past two decades, our work together has focused on gene mapping and understanding the genetic architecture of a wide range of traits with particular foci on migraine and common baldness. Our migraine research has included latent class and twin analyses cumulating in genome-wide association analyses which had identified 44 (34 new) risk variants for migraine. Leveraging these results through polygenic risk score analyses identified subgroups of patients likely to respond to triptans (an acute migraine drug), providing the first step toward precision medicine in migraine [Kogelman et al. (2019) Neurology Genetics, 5, e364].

Identification of Common Genetic Variants Influencing Spontaneous Dizygotic Twinning and Female Fertility.

Spontaneous dizygotic (DZ) twinning occurs in 1%-4% of women, with familial clustering and unknown physiological pathways and genetic origin. DZ twinning might index increased fertility and has distinct health implications for mother and child. We performed a GWAS in 1,980 mothers of spontaneous DZ twins and 12,953 control subjects. Findings were replicated in a large Icelandic cohort and tested for association across a broad range of fertility traits in women. Two SNPs were identified (rs11031006 near FSHB, p = 1.54 × 10(-9), and rs17293443 in SMAD3, p = 1.57 × 10(-8)) and replicated (p = 3 × 10(-3) and p = 1.44 × 10(-4), respectively). Based on ∼90,000 births in Iceland, the risk of a mother delivering twins increased by 18% for each copy of allele rs11031006-G and 9% for rs17293443-C. A higher polygenic risk score (PRS) for DZ twinning, calculated based on the results of the DZ twinning GWAS, was significantly associated with DZ twinning in Iceland (p = 0.001). A higher PRS was also associated with having children (p = 0.01), greater lifetime parity (p = 0.03), and earlier age at first child (p = 0.02). Allele rs11031006-G was associated with higher serum FSH levels, earlier age at menarche, earlier age at first child, higher lifetime parity, lower PCOS risk, and earlier age at menopause. Conversely, rs17293443-C was associated with later age at last child. We identified robust genetic risk variants for DZ twinning: one near FSHB and a second within SMAD3, the product of which plays an important role in gonadal responsiveness to FSH. These loci contribute to crucial aspects of reproductive capacity and health.

Linking migraine frequency with family history of migraine.

BACKGROUND: Migraine is a complex genetic disorder that is brought about by multiple genetic and environmental factors. We aimed to assess whether migraine frequency is associated with genetic susceptibility. METHODS: We investigated in 2829 migraine patients (14% males) whether 'migraine frequency' (measured as the number of migraine days per month) was related to 'genetic load' (measured as the number of parents affected with migraine) using a validated web-based questionnaire. In addition, we investigated associations with age-at-onset, migraine subtype, use of acute headache medication, and comorbid depression. RESULTS: We found an association between the number of migraine days per month and family history of migraine for males ( p = 0.03), but not for females ( p = 0.97). This association was confirmed in a linear regression analysis. Also, a lower age-at-onset ( p < 0.001), having migraine with aura ( p = 0.03), and a high number of medication days ( p = 0.006) were associated with a stronger family history of migraine, whereas lifetime depression ( p = 0.13) was not. DISCUSSION: Migraine frequency, as measured by the number of migraine days per month, seems associated with a genetic predisposition only in males. A stronger family history of migraine was also associated with a lower age-at-onset, a higher number of medication days, and migraine with aura. Our findings suggest that specific clinical features of migraine seem more determined by genetic factors.

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.

Genome-wide DNA methylation profiling in whole blood reveals epigenetic signatures associated with migraine.

BACKGROUND: Migraine is a common heritable neurovascular disorder typically characterised by episodic attacks of severe pulsating headache and nausea, often accompanied by visual, auditory or other sensory symptoms. Although genome-wide association studies have identified over 40 single nucleotide polymorphisms associated with migraine, there remains uncertainty about the casual genes involved in disease pathogenesis and how their function is regulated. RESULTS: We performed an epigenome-wide association study, quantifying genome-wide patterns of DNA methylation in 67 migraine cases and 67 controls with a matching age and sex distribution. Association analyses between migraine and methylation probe expression, after adjustment for cell type proportions, indicated an excess of small P values, but there was no significant single-probe association after correction for multiple testing (P < 1.09 × 10- 7). However, utilising a 1 kb sliding window approach to combine adjacent migraine-methylation association P values, we identified 62 independent differentially methylated regions (DMRs) underlying migraine (false discovery rate < 0.05). Migraine association signals were subtle but consistent in effect direction across the length of each DMR. Subsequent analyses showed that the migraine-associated DMRs were enriched in regulatory elements of the genome and were in close proximity to genes involved in solute transportation and haemostasis. CONCLUSIONS: This study represents the first genome-wide analysis of DNA methylation in migraine. We have identified DNA methylation in the whole blood of subjects associated with migraine, highlighting novel loci that provide insight into the biological pathways and mechanisms underlying migraine pathogenesis.