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Abstract Statins are thought to have positive effects on migraine but existing data are inconclusive. We aimed to evaluate the causal effect of such drugs on migraines using Mendelian randomization. We used four types of genetic instruments as proxies for HMG-CoA reductase inhibition. We included the expression quantitative trait loci of the HMG-CoA reductase gene and genetic variation within or near the HMG-CoA reductase gene region. Variants were associated with low-density lipoprotein cholesterol, apolipoprotein B, and total cholesterol. Genome-wide association study summary data for the three lipids were obtained from the UK Biobank. Comparable data for migraine were obtained from the International Headache Genetic Consortium and the FinnGen Consortium. Inverse variance weighting method was used for the primary analysis. Additional analyses included pleiotropic robust methods, colocalization, and meta-analysis. Genetically determined high expression of HMG-CoA reductase was associated with an increased risk of migraines (OR = 1.55, 95% CI 1.30–1.84, P = 6.87 × 10−7). Similarly, three genetically determined HMG-CoA reductase-mediated lipids were associated with an increased risk of migraine. These conclusions were consistent across meta-analyses. We found no evidence of bias caused by pleiotropy or genetic confounding factors. These findings support the hypothesis that statins can be used to treat migraine.

BackgroundMigraine has an increased prevalence in several immune disorders, but genetic cause-effect relationships remain unclear. Mendelian randomization (MR) was used in this study to explore whether immune diseases are causally associated with migraine and its subtypes.MethodsWe conducted a two-sample bidirectional multivariate Mendelian randomization study. Single-nucleotide polymorphisms (SNP) for six immune diseases, including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes mellitus (T1D), allergic rhinitis (AR), asthma and psoriasis, were used as genetic instrumental variables. Summary statistics for migraine were obtained from 3 databases: the International Headache Genetics Consortium (IHGC), UK Biobank, and FinnGen study. MR analyses were performed per outcome database for each exposure and subsequently meta-analyzed. Reverse MR analysis was performed to determine whether migraine were risk factors for immune diseases. In addition, we conducted a genetic correlation to identify shared genetic variants for these two associations.ResultsNo significant causal relationship was found between immune diseases and migraine and its subtypes. These results were robust with a series of sensitivity analyses. Using the linkage disequilibrium score regression method (LDSC), we detected no genetic correlation between migraine and immune diseases.ConclusionThe evidence from our study does not support a causal relationship between immune diseases and migraine. The mechanisms underlying the frequent comorbidity of migraine and several immune diseases need to be further elucidated.

Abstract Background Migraine is a disabling neurological disorder with the pathophysiology yet to be understood. The microstructural alteration in brain white matter (WM) has been suggested to be related to migraine in recent studies, but these evidence are observational essentially and cannot infer a causal relationship. The present study aims to reveal the causal relationship between migraine and microstructural WM using genetic data and Mendelian randomization (MR). Methods We collected the Genome-wide association study (GWAS) summary statistics of migraine (48,975 cases / 550,381 controls) and 360 WM imaging-derived phenotypes (IDPs) (31,356 samples) that were used to measure microstructural WM. Based on instrumental variables (IVs) selected from the GWAS summary statistics, we conducted bidirectional two-sample MR analyses to infer bidirectional causal associations between migraine and microstructural WM. In forward MR analysis, we inferred the causal effect of microstructural WM on migraine by reporting the odds ratio (OR) that quantified the risk change of migraine for per 1 standard deviation (SD) increase of IDPs. In reverse MR analysis, we inferred the causal effect of migraine on microstructural WM by reporting the β value that represented SDs of changes in IDPs were caused by migraine. Results Three WM IDPs showed significant causal associations (p

Psychiatric disorders are often accompanied by alterations in BMI and body composition due to changes in eating behaviour and physical activity. Here, Hübel et al. study the genetic overlap between these traits and find that genetic correlations between psychiatric disorders and body composition are sex-specific and evident only in adulthood.

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.

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.

Abstract Background The causal association between the gut microbiome and the development of migraine and its subtypes remains unclear. Methods The single nucleotide polymorphisms concerning gut microbiome were retrieved from the gene-wide association study (GWAS) of the MiBioGen consortium. The summary statistics datasets of migraine, migraine with aura (MA), and migraine without aura (MO) were obtained from the GWAS meta-analysis of the International Headache Genetics Consortium (IHGC) and FinnGen consortium. Inverse variance weighting (IVW) was used as the primary method, complemented by sensitivity analyses for pleiotropy and increasing robustness. Results In IHGC datasets, ten, five, and nine bacterial taxa were found to have a causal association with migraine, MA, and MO, respectively, (IVW, all P

Understanding of the causes and treatment of migraine is incomplete. Here, the authors detect pleiotropic genetic effects and causal relationships between migraine and 58 proteins that are largely distinct from migraine-associated loci identified by GWAS.

The association between blood pressure (BP) and migraine is poorly understood. Here, the authors explore this relationship using summary-level GWAS data for BP and migraine. Cross-trait meta-analysis reveals shared loci between BP and migraine, while Mendelian randomization suggests that diastolic BP specifically plays a key role in migraine susceptibility.