Uncovering drug targets for cluster headache through proteome-wide Mendelian randomization analysis

Abstract

Background: Cluster headache (CH) is a highly disabling primary headache disorder with a complex underlying mechanism. However, there are currently no effective targeted therapeutic drugs available. Existing medications often have limited efficacy and numerous side effects, which frequently fail to meet clinical needs. This study aims to identify potential new therapeutic targets for CH through proteome-wide mendelian randomization (PWMR).

Methods: We used PWMR to estimate the causal effects of plasma proteins on CH. This analysis integrated plasma protein quantitative trait loci (pQTL) data with genome-wide association study (GWAS) results of CH phenotypes. In addition, we conducted various sensitivity analyses, enrichment analyses, phenome-wide MR assessments, protein-protein interaction network construction, and mediation MR analyses to further validate the drug potential of the identified protein targets.

Results: We identified 11 protein targets for CH (p < 2.41 × 10^-5), with high-priority candidates exhibiting minimal side effects. Phenome-wide MR revealed novel targets-PXDNL, CCN4, PKD1, LGALS9, and MRC1-that show no significant disease-related adverse effects and interact with established preventive CH drug targets. Notably, PXDNL interacts with both acute and preventive CH drug targets. Furthermore, the causal effect of plasma proteins on CH is partially mediated by cortical surface area, with mediation proportions ranging from 3.2% to 10.0%.

Conclusions: We identified a set of potential protein targets for CH, characterized by rare side effects and a strong association with the biological mechanisms underlying the disorder. These findings offer valuable insights for the development of targeted drug therapies in the treatment of CH.

Keywords: Cluster headache; Drug targets; Mendelian randomization; Proteomics.

Fig. 1

Study design for identification of plasma proteins causally associated with CH

Fig. 2

MR results for plasma proteins and the risk of CH. The forest plot of the MR results for 2073 plasma proteins on the risk of CH. Each box represents the effect (i.e., OR change) per 1 SD change in the respective plasma proteins on CH and the error bars represent 95% CI. Arrows indicate that 95% CI exceeds the x axis. Bonfferoni corrected P = 2.41E-05 (0.05/2073). Abbreviations: OR, odds ratio; CI, confidence interval

Fig. 3

Results of enrichment analysis and phenome-wide MR analysis. A Networks and functions of identified proteins associated with CH. The colors of the line represent different networks. The network and function prediction was based on an online tool: GeneMANIA (http://www.genemania.org). B Heatmap of phenome-wide MR results. Heat map of phenome-wide MR Results between CH related proteins and the Finngen disease database. Red squares indicate that the protein is associated with the disease. Bonferroni correction p < 3.20 × 10^–6 (0.05/1421 diseases/11 total proteins)

Fig. 4

Interaction between commonly used acute and preventive CH medications targets and identified potential drug targets. The CH-associated proteins, including PXDNL, CCN4, PKD1, LGALS9, and MRC1 were linked to preventive CH drugs. PXDNL is also associated with acute CH drugs

Fig. 5

Mediation analyses to quantify the effects of proteins with PPI on CH via cortical structure. PXDNL effect on CH mediated by supramarginal surface area. β_EM effects of exposure on mediator, β_MO effects of mediator on outcome, β_EO effects of exposure on outcome