脑成像表型、脑和脑脊液代谢物以及脑基因对偏头痛亚型的遗传影响：一项孟德尔随机化和多组学研究。
Genetic influence of the brain imaging phenotypes, brain and cerebrospinal fluid metabolites and brain genes on migraine subtypes: a Mendelian randomization and multi-omics study.
作者信息
Zhang Ping-An, Wang Jie-Lin, Dong Mei-Hua, Huang Xiang-Chun, Li Nai-Jian, Qin Run-Dong, Li Jing
机构信息
Department of Allergy and Clinical Immunology, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, No.151, Yanjiangxi Road, Yuexiu District, Guangzhou, Guangdong, 510120, China.
Department of Obstetrics and Gynecology, Department of Gynecologic Oncology Research Office, Guangzhou Key Laboratory of Targeted Therapy for Gynecologic Oncology, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, Guangdong-Hong Kong-Macao Greater Bay Area Higher Education Joint Laboratory of Maternal-Fetal Medicine, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, China.
出版信息
J Headache Pain. 2025 May 20;26(1):124. doi: 10.1186/s10194-025-02063-7.
BACKGROUND
Migraine is a complex neurological disorder with high prevalence but unclear pathogenesis. Numerous studies have suggested that migraine is associated with alterations in brain imaging phenotypes (BIPs) and dysregulation of cerebrospinal fluid (CSF) and brain metabolism; however, causal evidence remains limited. Mendelian randomization (MR) offers a powerful approach for inferring causality using genetic instruments.
METHODS
Firstly, we conducted linkage disequilibrium score regression (LDSC) to evaluate genetic correlations between migraine, including the migraine with aura (MA) and migraine without aura (MO) subtypes, and BIPs, CSF, and brain metabolites. Traits that showed genetic correlations with migraine, MA, or MO were retained for subsequent MR analysis with the corresponding migraine phenotype. Traits showing significant correlations were analyzed using bidirectional two-sample MR (TSMR), followed by two-step TSMR to identify cross-omics mediation effects. Additionally, We also applied summary-data-based MR (SMR) to detect brain-region-specific genes with potential causal effects. Enrichment analyses (KEGG, GO, PPI, transcription factor, and miRNA networks) were conducted to further explore underlying mechanisms.
RESULTS
LDSC identified significant genetic correlations with 73 BIPs and 40 metabolites for overall migraine, 71 BIPs and 37 metabolites for MA, and 49 BIPs and 62 metabolites for MO. Enrichment analysis revealed that genetically associated metabolites were predominantly involved in amino acid metabolic pathways. TSMR identified 6 BIPs and 2 metabolites causally linked to overall migraine, 3 BIPs and 3 metabolites to MA, and 2 BIPs and 5 metabolites to MO. Most migraine-related BIPs mapped to the parietal lobe. Reverse MR analysis showed that overall migraine causally influenced 4 BIPs and 3 metabolites, while MA and MO affected 1 BIP and 1 metabolite, and 3 BIPs and 1 metabolite, respectively. Mediation analysis revealed five significant mediation pathways were identified. SMR analysis identified FAM83B and CIB2 consistently showing inhibitory effects across most regions. Enrichment analysis showed that these genes were predominantly involved in immune activation and cell adhesion.
CONCLUSIONS
Our study integrates cross-omics analyses to investigate the causal links between brain structure, metabolic alterations, gene expression, and migraine including its MA and MO subtypes. These findings provide novel insights into the pathophysiological mechanisms and potential targets for intervention across migraine subtypes.
背景
偏头痛是一种复杂的神经系统疾病，患病率高但发病机制尚不清楚。大量研究表明，偏头痛与脑成像表型（BIPs）改变、脑脊液（CSF）和脑代谢失调有关；然而，因果证据仍然有限。孟德尔随机化（MR）提供了一种使用遗传工具推断因果关系的有力方法。
方法
首先，我们进行连锁不平衡评分回归（LDSC），以评估偏头痛（包括有先兆偏头痛（MA）和无先兆偏头痛（MO）亚型）与BIPs、CSF和脑代谢物之间的遗传相关性。与偏头痛、MA或MO显示遗传相关性的性状被保留用于随后与相应偏头痛表型的MR分析。使用双向双样本MR（TSMR）分析显示出显著相关性的性状，随后进行两步TSMR以识别跨组学中介效应。此外，我们还应用基于汇总数据的MR（SMR）来检测具有潜在因果效应的脑区特异性基因。进行富集分析（KEGG、GO、PPI、转录因子和miRNA网络）以进一步探索潜在机制。
结果
LDSC确定总体偏头痛与73个BIPs和40种代谢物、MA与71个BIPs和37种代谢物、MO与49个BIPs和62种代谢物存在显著遗传相关性。富集分析表明，遗传相关的代谢物主要参与氨基酸代谢途径。TSMR确定6个BIPs和2种代谢物与总体偏头痛存在因果联系，3个BIPs和3种代谢物与MA存在因果联系，2个BIPs和5种代谢物与MO存在因果联系。大多数与偏头痛相关的BIPs定位于顶叶。反向MR分析表明，总体偏头痛对4个BIPs和3种代谢物有因果影响，而MA和MO分别影响1个BIP和1种代谢物、3个BIPs和1种代谢物。中介分析确定了五条显著的中介途径。SMR分析确定FAM83B和CIB2在大多数区域持续显示抑制作用。富集分析表明，这些基因主要参与免疫激活和细胞粘附。
结论
我们的研究整合了跨组学分析，以研究脑结构、代谢改变、基因表达与偏头痛（包括其MA和MO亚型）之间的因果联系。这些发现为偏头痛亚型的病理生理机制和潜在干预靶点提供了新的见解。
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