Phenotypic and Genotypic Associations Between Migraine and Lipoprotein Subfractions

Conventional and genetic association between migraine and stroke with druggable genome-wide Mendelian randomization

The genetic relationship between migraine and stroke remains underexplored, particularly in the context of druggable targets. Previous studies have been limited by small sample sizes and a lack of focus on genetic-targeted therapies for these conditions. We analyzed the association and causality between migraine and stroke using multivariable logistic regression in the UK Biobank cohort and Mendelian randomization (MR) analyses based on genome-wide association study (GWAS) data. Integrating expression quantitative trait loci (eQTLs) data from blood and brain regions, we explored the phenotypic and genetic links between migraine medications, drug target, and stroke. Additionally, we explored novel druggable genes for migraine and evaluated their effects on migraine signaling molecules and stroke risk. Migraine was significantly associated with stroke, particularly ischemic stroke (IS) and intracerebral hemorrhage (ICH), with MR analysis confirming a causal link to ICH. HTR1A emerged as a potential link between antidepressants (preventive medications for migraine) and stroke. We identified 17 migraine-related druggable genes, with 5 genes (HMGCR, TGFB1, TGFB3, KCNK5, IMPDH2) associated with nine existing drugs. Further MR analysis identified correlation of CELSR3 and IMPDH2 with cGMP pathway marker PRKG1, and identified KCNK5, PLXNB1, and MDK as novel migraine-associated druggable genes significantly linked to the stroke risks. These findings established the phenotypic and genetic link between migraine, its medication and stroke, identifying potential targets for single and dual-purpose therapies for migraine and stoke, and emphasized the need for further research to validate these associations.

Mendelian randomization analysis reveals causal effects of migraine and its subtypes on early-onset ischemic stroke risk

Previous observational studies have suggested at a potential link between migraine, particularly migraine with aura, and the susceptibility to early-onset ischemic stroke. We aimed to investigate the causal effects of genetically determined migraine and its subtypes on the risk of early-onset ischemic stroke using the two-sample Mendelian randomization method. Genetic instrumental variables associated with migraine and its subtypes were acquired from two sources with the largest sample sizes available. Summary data for early-onset ischemic stroke was acquired from a study encompassing individuals aged 18-59 years, comprising 16,730 cases and 599,237 non-stroke controls. The random-effects inverse variance weighted method was used as the primary analysis approach. Additionally, linkage disequilibrium score regression analysis was used to evaluate the genetic correlation. The Mendelian randomization analysis revealed no association between overall migraine and migraine without aura with the risk of early-onset ischemic stroke. However, migraine with aura showed a suggestive association with an elevated risk of early-onset ischemic stroke, with odds ratios of 1.114 (95% confidence interval = 1.005 to 1.236, p-value = 0.040) and 1.062 (95% confidence interval = 1.002 to 1.126, p-value = 0.042) based on instruments from two independent sources. The odds ratio was 1.074 (95% confidence interval = 1.022 to 1.130, p-value = 0.005) based on instruments from both two sources. No evidence of heterogeneity or horizontal pleiotropy was found. By contrast, migraine with aura was not related to ischemic stroke in all adults. Furthermore, a significant positive genetic correlation was found between migraine with aura and early-onset ischemic stroke (genetic correlation = 0.208, 95% confidence interval = 0.038 to 0.377, p-value = 0.016). This study provides evidence of a causal relationship between migraine with aura and the risk of early-onset ischemic stroke, as well as a positive genetic correlation between them.

Association between severe headache or migraine and lipid accumulation product and visceral adiposity index in adults: a cross-sectional study from NHANES

BACKGROUND

Existing literature on the impact of lipid accumulation product (LAP) and visceral adiposity index (VAI) on severe headache or migraine is limited. This study aims to elucidate the association between LAP and VAI and the prevalence of migraine.

METHODS

Data for this study were sourced from the 1999-2004 National Health and Nutrition Examination Survey (NHANES). A database-self-administered questionnaire was used to assess severe headache or migraine. A weighted logistic regression model was employed to assess the relationship between LAP and VAI with migraine prevalence. Complementary analytical approaches included subgroup analysis, restricted cubic spline (RCS), and threshold effect analysis to validate the findings.

RESULTS

In the end, 4572 people were recruited for the research, including 880 with migraine and 3692 without migraine. Following adjustment for the relevant covariables, weighted logistic regression analysis (OR = 1.409, 95% CI: 1.054, 1.883, P = 0.022; OR = 1.288, 95% CI: 1.010, 1.642, P = 0.042) revealed significantly elevated odds of migraine prevalence in participants within the highest tertile (T3) of LAP and VAI than those in the lowest tertile (T1). The nonlinear association between migraine prevalence and both VAI and LAP was further elucidated through a restricted cubic spline. The threshold analysis pinpointed 2.142 (log-likelihood ratio = 0.016) as the critical inflection point for VAI. Subgroup analysis and interaction testing revealed the significant association was independent in different subgroup factors.

CONCLUSIONS

The data indicate a robust association between higher levels of LAP and VAI and an increased prevalence of migraine.

Identification of genetic susceptibility for Chinese migraine with depression using machine learning

Background

Migraine is a common primary headache that has a significant impact on patients' quality of life. The co-occurrence of migraine and depression is frequent, resulting in more complex symptoms and a poorer prognosis. The evidence suggests that depression and migraine comorbidity share a polygenic genetic background.

Objective

The aim of this study is to identify related genetic variants that contribute to genetic susceptibility to migraine with and without depression in a Chinese cohort.

Methods

In this case-control study, 263 individuals with migraines and 223 race-matched controls were included. Eight genetic polymorphism loci selected from the GWAS were genotyped using Sequenom's MALDI-TOF iPLEX platform.

Results

In univariate analysis, ANKDD1B rs904743 showed significant differences in genotype and allele distribution between migraineurs and controls. Furthermore, a machine learning approach was used to perform multivariate analysis. The results of the Random Forest algorithm indicated that ANKDD1B rs904743 was a significant risk factor for migraine susceptibility in China. Additionally, subgroup analysis by the Boruta algorithm showed a significant association between this SNP and migraine comorbid depression. Migraineurs with depression have been observed to have worse scores on the Beck Anxiety Inventory (BAI) and the Migraine Disability Assessment Scale (MIDAS).

Conclusion

The study indicates that there is an association between ANKDD1B rs904743 and susceptibility to migraine with and without depression in Chinese patients.

Identifying therapeutic target genes for migraine by systematic druggable genome-wide Mendelian randomization

BACKGROUND

Currently, the treatment and prevention of migraine remain highly challenging. Mendelian randomization (MR) has been widely used to explore novel therapeutic targets. Therefore, we performed a systematic druggable genome-wide MR to explore the potential therapeutic targets for migraine.

METHODS

We obtained data on druggable genes and screened for genes within brain expression quantitative trait locis (eQTLs) and blood eQTLs, which were then subjected to two-sample MR analysis and colocalization analysis with migraine genome-wide association studies data to identify genes highly associated with migraine. In addition, phenome-wide research, enrichment analysis, protein network construction, drug prediction, and molecular docking were performed to provide valuable guidance for the development of more effective and targeted therapeutic drugs.

RESULTS

We identified 21 druggable genes significantly associated with migraine (BRPF3, CBFB, CDK4, CHD4, DDIT4, EP300, EPHA5, FGFRL1, FXN, HMGCR, HVCN1, KCNK5, MRGPRE, NLGN2, NR1D1, PLXNB1, TGFB1, TGFB3, THRA, TLN1 and TP53), two of which were significant in both blood and brain (HMGCR and TGFB3). The results of phenome-wide research showed that HMGCR was highly correlated with low-density lipoprotein, and TGFB3 was primarily associated with insulin-like growth factor 1 levels.

CONCLUSIONS

This study utilized MR and colocalization analysis to identify 21 potential drug targets for migraine, two of which were significant in both blood and brain. These findings provide promising leads for more effective migraine treatments, potentially reducing drug development costs.

HMG-CoA reductase is a potential therapeutic target for migraine: a mendelian randomization study

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.

Cis-eQTLs in seven duck tissues identify novel candidate genes for growth and carcass traits

BACKGROUND

Expression quantitative trait loci (eQTL) studies aim to understand the influence of genetic variants on gene expression. The colocalization of eQTL mapping and GWAS strategy could help identify essential candidate genes and causal DNA variants vital to complex traits in human and many farm animals. However, eQTL mapping has not been conducted in ducks. It is desirable to know whether eQTLs within GWAS signals contributed to duck economic traits.

RESULTS

In this study, we conducted an eQTL analysis using publicly available RNA sequencing data from 820 samples, focusing on liver, muscle, blood, adipose, ovary, spleen, and lung tissues. We identified 113,374 cis-eQTLs for 12,266 genes, a substantial fraction 39.1% of which were discovered in at least two tissues. The cis-eQTLs of blood were less conserved across tissues, while cis-eQTLs from any tissue exhibit a strong sharing pattern to liver tissue. Colocalization between cis-eQTLs and genome-wide association studies (GWAS) of 50 traits uncovered new associations between gene expression and potential loci influencing growth and carcass traits. SRSF4, GSS, and IGF2BP1 in liver, NDUFC2 in muscle, ELF3 in adipose, and RUNDC1 in blood could serve as the candidate genes for duck growth and carcass traits.

CONCLUSIONS

Our findings highlight substantial differences in genetic regulation of gene expression across duck primary tissues, shedding light on potential mechanisms through which candidate genes may impact growth and carcass traits. Furthermore, this availability of eQTL data offers a valuable resource for deciphering further genetic association signals that may arise from ongoing extensive endeavors aimed at enhancing duck production traits.

Genetics of migraine: complexity, implications, and potential clinical applications

Migraine is a common neurological disorder with large burden in terms of disability for individuals and costs for society. Accurate diagnosis and effective treatments remain priorities. Understanding the genetic factors that contribute to migraine risk and symptom manifestation could improve individual management. Migraine has a strong genetic basis that includes both monogenic and polygenic forms. Some distinct, rare, familial migraine subtypes are caused by pathogenic variants in genes involved in ion transport and neurotransmitter release, suggesting an underlying vulnerability of the excitatory-inhibitory balance in the brain, which might be exacerbated by disruption of homoeostasis and lead to migraine. For more prevalent migraine subtypes, genetic studies have identified many susceptibility loci, implicating genes involved in both neuronal and vascular pathways. Genetic factors can also reveal the nature of relationships between migraine and its associated biomarkers and comorbidities and could potentially be used to identify new therapeutic targets and predict treatment response.

Comprehensive analysis of genetic associations and single-cell expression profiles reveals potential links between migraine and multiple diseases: a phenome-wide association study

Migraine is a common neurological disorder that affects more than one billion people worldwide. Recent genome-wide association studies have identified 123 genetic loci associated with migraine risk. However, the biological mechanisms underlying migraine and its relationships with other complex diseases remain unclear. We performed a phenome-wide association study (PheWAS) using UK Biobank data to investigate associations between migraine and 416 phenotypes. Mendelian randomization was employed using the IVW method. For loci associated with multiple diseases, pleiotropy was tested using MR-Egger. Single-cell RNA sequencing data was analyzed to profile the expression of 73 migraine susceptibility genes across brain cell types. qPCR was used to validate the expression of selected genes in microglia. PheWAS identified 15 disorders significantly associated with migraine, with one association detecting potential pleiotropy. Single-cell analysis revealed elevated expression of seven susceptibility genes (including ZEB2, RUNX1, SLC24A3, ANKDD1B, etc.) in brain glial cells. And qPCR confirmed the upregulation of these genes in LPS-treated microglia. This multimodal analysis provides novel insights into the link between migraine and other diseases. The single-cell profiling suggests the involvement of specific brain cells and molecular pathways. Validation of gene expression in microglia supports their potential role in migraine pathology. Overall, this study uncovers pleiotropic relationships and the biological underpinnings of migraine susceptibility.

Lipids, lipid-modifying drug target genes and migraine: a Mendelian randomization study

INTRODUCTION

Migraine, a prevalent headache disorder with unclear mechanisms and limited treatments, may be influenced by dyslipidemia and genetic factors. Statins and emerging lipid-modifying agents show potential but lack evidence for migraine management. Mendelian Randomization analysis offers insights into causal relationships and therapeutic targets. This study aims to explore genetically predicted lipid traits, drug targets, and their association with migraine risk.

METHOD

We conducted Mendelian randomization (MR) analyses utilizing genetic variants associated with lipid traits and variants in genes encoding the protein targets of various classes of lipid-lowering drugs. The specific drug classes investigated included HMGCR, PCSK9, NPC1L1, ABCG5/ABCG8, LDLR, LPL, ANGPTL3, APOB, CETP, and APOC3. To determine the effects on migraine risk, we meta-analyzed MR estimates for regional variants using data from two large sample sets. The genetic variants were weighted based on their associations with specific lipid traits, such as low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), Apolipoprotein A1, and Apolipoprotein B. To obtain association weights, we utilized data from lipid genetics consortia. For lipid-modifying drug targets that exhibited suggestive significance, we further employed expression quantitative trait locus (eQTL) data. Additionally, we performed colocalization analysis to assess genetic confounding.

RESULT

The use of genetic proxies for HMGCR inhibition demonstrated a significant association with a decreased risk of migraine in the FinnGen dataset (OR = 0.64, 95% CI: 0.46-0.88, p = 0.0006) and a nearly significant association in the Choquet dataset (OR = 0.78, 95% CI: 0.60-1.01, p = 0.06). When pooling the estimates, the overall effect size showed a reduced risk of migraine (OR = 0.73, 95% CI: 0.60-0.89, p = 0.0016). Similarly, genetic mimicry of LPL enhancement was associated with a lower risk of migraine in the FinnGen dataset (OR = 0.82, 95% CI: 0.69-0.96, p = 0.01) and the Choquet dataset (OR = 0.91, 95% CI: 0.83-0.99, p = 0.03). Pooling the estimates showed a consistent effect size (OR = 0.89, 95% CI: 0.83-0.96, p = 0.002). Sensitivity analyses yielded no statistically significant evidence of bias arising from pleiotropy or genetic confounding.

CONCLUSION

In the study, it was observed that among the 10 lipid-lowering drug targets investigated, LPL and HMGCR showed significant associations with migraine risk. These findings indicate that LPL and HMGCR have the potential to serve as candidate drug targets for the treatment or prevention of migraines.

A sex- and site-specific relationship between body mass index and osteoarthritis: evidence from observational and genetic analyses

OBJECTIVE

We primarily aimed to investigate whether there are phenotypic and genetic links underlying body mass index (BMI) and overall osteoarthritis (OA). We then intended to explore whether the relationships differ across sexes and sites.

METHOD

We first evaluated the phenotypic association between BMI and overall OA using data from the UK Biobank. We then investigated the genetic relationship leveraging summary statistics of the hitherto largest genome-wide association studies performed for BMI and overall OA. Finally, we repeated all analyses in a sex- (female, male) and site- (knee, hip, spine) specific manner.

RESULTS

Observational analysis suggested an increased hazard of diagnosed OA per 5 kg/m² increment in BMI (hazard ratio = 1.38, 95% confidence interval (CI) = 1.37-1.39). A positive overall genetic correlation was observed for BMI and OA (r_g = 0.43, P = 4.72 × 10^-133), corroborated by 11 significant local signals. Cross-trait meta-analysis identified 34 pleiotropic loci shared between BMI and OA, of which seven were novel. Transcriptome-wide association study revealed 29 shared gene-tissue pairs, targeting nervous, digestive, and exo/endocrine systems. Mendelian randomization demonstrated a robust BMI-OA causal relationship (odds ratio = 1.47, 95% CI = 1.42-1.52). A similar pattern of effects was observed in sex- and site-specific analyses, with BMI affecting OA comparably in both sexes and most strongly in the knee.

CONCLUSION

Our work demonstrates an intrinsic relationship underlying BMI and overall OA, reflected by a pronounced phenotypic association, significant biological pleiotropy, and a putative causal link. Stratified analysis further reveals that the effects are distinct across sites and comparable across sexes.

Genetics of migraine: where are we now?

Migraine is a complex brain disorder explained by the interaction of genetic and environmental factors. In monogenic migraines, including familial hemiplegic migraine and migraine with aura associated with hereditary small-vessel disorders, the identified genes code for proteins expressed in neurons, glial cells, or vessels, all of which increase susceptibility to cortical spreading depression. The study of monogenic migraines has shown that the neurovascular unit plays a prominent role in migraine. Genome-wide association studies have identified numerous susceptibility variants that each result in only a small increase in overall migraine risk. The more than 180 known variants belong to several complex networks of "pro-migraine" molecular abnormalities, which are mainly neuronal or vascular. Genetics has also highlighted the importance of shared genetic factors between migraine and its major co-morbidities, including depression and high blood pressure. Further studies are still needed to map all of the susceptibility loci for migraine and then to understand how these genomic variants lead to migraine cell phenotypes.

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.

Personal view: Modelling pain mechanisms of migraine without aura

INTRODUCTION

This review aims to model migraine nociception.

METHODS

Personal experience and litterature.

RESULTS

Genetic and environmental factors in combination decide whether a person suffers from migraine. Endogenous and/or exogenous factors precipitate the individual attacks. Nociception takes place around blood vessels. There is a growing understanding of the molecular pathophysiological mechanisms of migraine from human provocation studies. Rodent models of migraine are necessary to understand the complex interrelation between the many putatively involved molecules and tissues but their relevance for human migraine is uncertain. The crucial element in migraine nociception is a unit consisting of endothelial cells, vascular smooth muscle cells, perivascular nerve fibers (trigeminal, parasympathetic and sympathetic) and mast cells. Attacks may start outside the brain by humoral or neurogenic activity releasing nociceptive substances around blood vessels. They may also (perhaps more often) start by the brain generating efferent activity in autonomic and somatic nerves.

CONCLUSION

Human and rodent studies can quickly uncover the "mystery of migraine".