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DOI 10.1016/j.virusres.2026.199708

Медицинская библиотека · Virus research · 2026

Shared genetic structure between COVID-19 and migraine: insights from large-scale genome-wide cross-trait analysis.

Wang Xiangyu, Guo Jinniu, Liu Jinfeng, Jiang Jinzhao, Long Yu, Sun Ruohan

СтатьяПеревод пока не подготовлен

Аннотация

PURPOSE: This study assessed the genetic correlation and causal relationship between COVID-19 phenotypes and migraine.

METHODS

Genome-Wide Association Study‌ (GWAS) data of 13,465 migraine cases and 264,662 controls were obtained from FinnGen consortium. Four phenotypes from COVID-19 HGI were analyzed. Linkage disequilibrium score regression (LDSC) assessed genetic correlations. Pleiotropy analysis under composite null hypothesis (PLACO) identified pleiotropic genes/SNPs. MsigDB v6.2 was used for gene annotation, and multi-marker Analysis of GenoMic Annotation (MAGMA) analyzed pathway enrichment. Tissue-specific expression and immune cell-type heritability were examined. Bidirectional mendelian randomization (MR) tested causality.

RESULTS

Moderate genetic correlations were detected between COVID-19 phenotypes and migraine. Local heritability correlations were found between three COVID-19 phenotypes and migraine. PLACO detected 13 pleiotropic SNPs and 6 pleiotropic genes, enriched in mTOR and beta catenin pathways. Tissue and cell-type specific analyses indicated high expression in lung and cerebral cortex tissues, along with specific immune cells. MR detected no robust causal effects between COVID-19 phenotypes and migraine.

CONCLUSIONS

COVID-19 phenotypes and migraine shared genetic structures, though no causality was detected. Pleiotropic genes play key roles in the mTOR and beta catenin pathways, with tissue enrichment in lung, cerebral cortex, and specific immune cells, suggesting a potential mechanism for shared susceptibility.

Для цитирования: Wang Xiangyu, Guo Jinniu, Liu Jinfeng, Jiang Jinzhao, Long Yu, Sun Ruohan. Shared genetic structure between COVID-19 and migraine: insights from large-scale genome-wide cross-trait analysis.. Virus research. 2026. DOI: 10.1016/j.virusres.2026.199708.

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