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

Abstract

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.

Keywords: Brain and cerebrospinal fluid metabolites; Brain imaging phenotypes; Genome-wide association; Mendelian randomization; Migraine; Multi-omics.

Fig. 1

Overall study design of the article

Fig. 2

Genetic correlations between BIPs, CSF and brain metabolite, and migraine. (A) Manhattan plot of LDSC results for BIPs and CSF/brain metabolites across migraine phenotypes. (B)Venn diagram illustrating the genetic correlation of BIPs with Migraine, MA, and MO. Numbers represent unique and shared metabolites among the groups. (C).Venn diagram illustrating the genetic correlation of metabolites with Migraine, MA, and MO. Numbers represent unique and shared metabolites among the groups. (D) Stacked bar plot showing the classification of metabolites with significant genetic correlations to migraine phenotypes. (E–G) KEGG pathway enrichment analyses of migraine-related metabolites for overall migraine (E), MA (F), and MO (G)

Fig. 3

Bidirectional Mendelian randomization analysis of causal relationships between BIPs, metabolites, and migraine subtypes. (A) Forest plot showing the causal effects of BIPs on overall migraine, MA, and MO identified through forward MR analysis. (B) Forest plot illustrating the causal effects of CSF and brain metabolites on migraine phenotypes based on forward MR analysis. (C) Forest plot of reverse MR results showing the causal effects of migraine and its subtypes on BIPs. (D) Forest plot of reverse MR results displaying the causal effects of migraine and its subtypes on CSF and brain metabolites

Fig. 4

Mediation analysis reveals cross-omics causal pathways linking brain imaging phenotypes, metabolites, and migraine. (A) Forest plot from the second step of two-step MR, assessing causal links between BIPs and metabolites that both demonstrated causal associations with migraine in the first step. (B) Schematic summary of five significant mediation pathways identified from two-step MR

Fig. 5

The causal effect of gene expression in Cerebellar Hemisphere region on migraine. Venn diagram illustrating gene expression in the brain cerebellar hemisphere with significant causal effects on Migraine, MA, and MO. Numbers indicate unique and shared metabolites among the groups (A). GO (B) and KEGG (C) pathways enriched by genes expressed in the brain cerebellar hemisphere region, exhibiting significant causal effects on Migraine, as well as MA and MO subtypes; the PPI network of screened genes showing the significant causal impact on Migraine, as well as MA and MO subtypes (D). The potential translational factors interacted with screened genes, significantly affecting migraine and MA and MO subtypes (E). The potential miRNA interacted with screened genes, significantly affecting migraine and MA and MO subtypes (F). Forest plot depicting the causal associations between genes and overall migraine (G), MA (H), and MO (I)