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

IF 3.8 2区 生物学 Q2 GENETICS & HEREDITY
Xiaoyu Wang, Wendu Pang, Xin Hu, Tao Shu, Yaxin Luo, Junhong Li, Lan Feng, Ke Qiu, Yufang Rao, Yao Song, Minzi Mao, Yuyang Zhang, Jianjun Ren, Yu Zhao
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引用次数: 0

Abstract

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.

偏头痛和中风与可用药全基因组孟德尔随机化之间的传统和遗传关联。
偏头痛和中风之间的遗传关系仍未得到充分探讨,特别是在可药物靶点的背景下。以前的研究受到样本量小和缺乏对这些疾病的基因靶向治疗的关注的限制。我们在英国生物银行队列中使用多变量逻辑回归分析偏头痛和中风之间的关联和因果关系,并基于全基因组关联研究(GWAS)数据进行孟德尔随机化(MR)分析。整合来自血液和大脑区域的表达数量性状位点(eqtl)数据,我们探索了偏头痛药物、药物靶点和中风之间的表型和遗传联系。此外,我们探索了新的偏头痛药物基因,并评估了它们对偏头痛信号分子和中风风险的影响。偏头痛与中风,特别是缺血性中风(IS)和脑出血(ICH)显著相关,磁共振分析证实了与ICH的因果关系。HTR1A被认为是抗抑郁药(偏头痛的预防药物)和中风之间的潜在联系。我们鉴定了17个偏头痛相关的可药物基因,其中5个基因(HMGCR、TGFB1、TGFB3、KCNK5、IMPDH2)与9种现有药物相关。进一步的MR分析发现CELSR3和IMPDH2与cGMP通路标记物PRKG1相关,并发现KCNK5、PLXNB1和MDK是与卒中风险显著相关的新型偏头痛相关药物基因。这些发现建立了偏头痛及其药物与中风之间的表型和遗传联系,确定了偏头痛和中风的单一和双重目的治疗的潜在靶点,并强调需要进一步研究来验证这些关联。
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来源期刊
Human Genetics
Human Genetics 生物-遗传学
CiteScore
10.80
自引率
3.80%
发文量
94
审稿时长
1 months
期刊介绍: Human Genetics is a monthly journal publishing original and timely articles on all aspects of human genetics. The Journal particularly welcomes articles in the areas of Behavioral genetics, Bioinformatics, Cancer genetics and genomics, Cytogenetics, Developmental genetics, Disease association studies, Dysmorphology, ELSI (ethical, legal and social issues), Evolutionary genetics, Gene expression, Gene structure and organization, Genetics of complex diseases and epistatic interactions, Genetic epidemiology, Genome biology, Genome structure and organization, Genotype-phenotype relationships, Human Genomics, Immunogenetics and genomics, Linkage analysis and genetic mapping, Methods in Statistical Genetics, Molecular diagnostics, Mutation detection and analysis, Neurogenetics, Physical mapping and Population Genetics. Articles reporting animal models relevant to human biology or disease are also welcome. Preference will be given to those articles which address clinically relevant questions or which provide new insights into human biology. Unless reporting entirely novel and unusual aspects of a topic, clinical case reports, cytogenetic case reports, papers on descriptive population genetics, articles dealing with the frequency of polymorphisms or additional mutations within genes in which numerous lesions have already been described, and papers that report meta-analyses of previously published datasets will normally not be accepted. The Journal typically will not consider for publication manuscripts that report merely the isolation, map position, structure, and tissue expression profile of a gene of unknown function unless the gene is of particular interest or is a candidate gene involved in a human trait or disorder.
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