Migraine and Ischemic Stroke: A Mendelian Randomization Study

Shu, Mei-Jun; Li, J.; Zhu, Yi-Cheng; Shen, Hang

doi:10.1007/s40120-021-00310-y

Cited by 43 publications

(40 citation statements)

References 27 publications

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“…Third, we excluded SNPs associated with the outcome (DVT) ( P < 1 × 10 ––5 ). Fourth, the PhenoScanner database 2 was used to assess whether the selected SNPs were associated with confounders ( 41 ). We considered the risk factors and potential confounders of DVT (obesity, age, sex, smoking, physical activity, use of lipid-lowering therapy, Factor V Leiden, cancer, recent major surgery and study, and for women only the use of oral contraceptives, use of hormone-replacement therapy, and menopausal status) ( 42 ).…”

Section: Methodsmentioning

confidence: 99%

“…We used Cochran’s Q statistic for MR-IVW analyses and Rucker’s Q statistic for MR Egger analyses to detect heterogeneity, and P -value > 0.05 was considered to indicate no heterogeneity ( 43 ). We used the MR Egger method to assess the extent to which directional pleiotropy may affect risk estimates by intercept tests, and P -value > 0.05 was considered to indicate no horizontal pleiotropy ( 41 ). Because MR Egger may show lower accuracy in some cases, the MR pleiotropy residual sum and outlier (MR-PRESSO) method was also used to assess outlier SNPs and potential horizontal pleiotropy ( 41 ).…”

Section: Methodsmentioning

confidence: 99%

“…We used the MR Egger method to assess the extent to which directional pleiotropy may affect risk estimates by intercept tests, and P -value > 0.05 was considered to indicate no horizontal pleiotropy ( 41 ). Because MR Egger may show lower accuracy in some cases, the MR pleiotropy residual sum and outlier (MR-PRESSO) method was also used to assess outlier SNPs and potential horizontal pleiotropy ( 41 ). The distortion test embedded in the MR-PRESSO analysis can detect outliers present in the MR analysis.…”

Section: Methodsmentioning

confidence: 99%

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Large-scale correlation analysis of deep venous thrombosis and gut microbiota

Yang

Luo

Zhang

et al. 2022

Front. Cardiovasc. Med.

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ObjectiveAlthough previous studies have shown that gut microbiota may be involved in the occurrence of deep venous thrombosis (DVT), the specific link between the two remains unclear. The present study aimed to explore this question from a genetic perspective.Materials and methodsGenome-wide association study (GWAS) summary data of DVT were obtained from the UK Biobank (N = 9,059). GWAS summary data of the gut microbiota were obtained from the Flemish Gut Flora Project (N = 2,223) and two German cohorts (FoCus, N = 950; PopGen, N = 717). All the participants were of European ancestry. Linkage disequilibrium score (LDSC) regression has great potential for analyzing the heritability of disease or character traits. LDSC regression was used to analyze the genetic correlation between DVT and the gut microbiota based on the GWAS summary data obtained from previous studies. Mendelian randomization (MR) was used to analyze the genetic causal relationship between DVT and the gut microbiota. We used the random effects inverse variance weighted, MR Egger, weighted median, simple mode, and weighted mode to perform MR analysis. We performed a sensitivity analysis of the MR analysis results by examining heterogeneity and horizontal pleiotropy.ResultsLinkage disequilibrium score analysis showed that Streptococcaceae (correlation coefficient = −0.542, SE = 0.237, P = 0.022), Dialister (correlation coefficient = −0.623, SE = 0.316, P = 0.049), Streptococcus (correlation coefficient = −0.576, SE = 0.264, P = 0.029), and Lactobacillales (correlation coefficient = −0.484, SE = 0.237, P = 0.042) had suggestive genetic correlation with DVT. In addition, the MR analysis showed that Streptococcaceae had a positive genetic causal relationship with DVT (P = 0.027, OR = 1.005). There was no heterogeneity or horizontal pleiotropy in the MR analysis (P > 0.05).ConclusionIn this study, four gut microbes (Streptococcaceae, Dialister Streptococcus, Lactobacillales) had suggestive genetic correlations with DVT, and Streptococcaceae had a positive causal relationship with DVT. Our findings provide a new research direction for the further study of and prevention of DVT.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Large-scale correlation analysis of deep venous thrombosis and gut microbiota

Yang

Luo

Zhang

et al. 2022

Front. Cardiovasc. Med.

View full text Add to dashboard Cite

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“…Of the many published MR studies that examine the relationship between migraine and a given disorder/trait, only some are discussed below. First, the causality between migraine and stroke has been investigated in three studies, two of which do not support a causal relationship between migraine and stroke (95–97), whereas one found a protective influence of large artery stroke (OR [95% CI] = 0.86 [0.76–0.96], P = 0.0067) on migraine, but no relation with stroke subtypes (97). Second, several other cardiovascular traits/risk factors and their possible causal relationship with migraine have been investigated, one showing that an increase in blood pressure directly contributes to migraine risk (84).…”

Section: Causality In Migrainementioning

confidence: 99%

Migraine genetics: Status and road forward

et al. 2023

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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.

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“…As far as other diseases are concerned, there is no evidence of a causal association between depression and risk of IS [ 100 , 101 ], whereas one study has observed an association with increased risk of small vessel stroke (SVS) [ 100 ]. No causal associations were identified between migraine and AIS or stroke subtypes [ 102 ]. Impaired renal function is causally associated with an increased risk of LAS, but not other subtypes [ 110 ].…”

Section: Mendelian Randomization In Strokementioning

confidence: 99%

Genome-Wide Studies in Ischaemic Stroke: Are Genetics Only Useful for Finding Genes?

Gallego-Fábrega

Muiño

Cárcel‐Márquez

et al. 2022

IJMS

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Ischaemic stroke is a complex disease with some degree of heritability. This means that heritability factors, such as genetics, could be risk factors for ischaemic stroke. The era of genome-wide studies has revealed some of these heritable risk factors, although the data generated by these studies may also be useful in other disciplines. Analysis of these data can be used to understand the biological mechanisms associated with stroke risk and stroke outcome, to determine the causality between stroke and other diseases without the need for expensive clinical trials, or to find potential drug targets with higher success rates than other strategies. In this review we will discuss several of the most relevant studies regarding the genetics of ischaemic stroke and the potential use of the data generated.

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Migraine and Ischemic Stroke: A Mendelian Randomization Study

Cited by 43 publications

References 27 publications

Large-scale correlation analysis of deep venous thrombosis and gut microbiota

Large-scale correlation analysis of deep venous thrombosis and gut microbiota

Migraine genetics: Status and road forward

Genome-Wide Studies in Ischaemic Stroke: Are Genetics Only Useful for Finding Genes?

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