Association and genetic overlap between clinical chemistry tests and migraine

Research output: Contribution to journalJournal articleResearchpeer-review

  • Hamzeh M. Tanha
  • The International Headache Genetics Consortium (IHGC)

Introduction: In this paper, we studied several serum clinical chemistry tests of cardiovascular disease (CVD), iron deficiency anemia, liver and kidney disorders in migraine. Methods: We first explored the association of 22 clinical chemistry tests with migraine risk in 697 migraine patients and 2722 controls. To validate and interpret association findings, cross-trait genetic analyses were conducted utilising genome-wide association study (GWAS) data comprising 23,986 to 452,264 individuals. Results: Significant associations with migraine risk were identified for biomarkers of CVD risk, iron deficiency and liver dysfunction (odds ratios = 0.86–1.21; 1 × 10−4 < p < 3 × 10−2). Results from cross-trait genetic analyses corroborate the significant biomarker associations and indicate their relationship with migraine is more consistent with biological pleiotropy than causality. For example, association and genetic overlap between a lower level of HDL-C and increased migraine risk are due to shared biology rather than a causal relationship. Furthermore, additional genetic analyses revealed shared genetics among migraine, the clinical chemistry tests, and heart problems and iron deficiency anemia, but not liver disease. Conclusions: These findings highlight common biological mechanisms underlying migraine, heart problems and iron deficiency anemia and provide support for their investigation in the development of novel therapeutic and dietary interventions.

Original languageEnglish
JournalCephalalgia
Volume41
Issue number11-12
Pages (from-to)1208-1221
Number of pages14
ISSN0333-1024
DOIs
Publication statusPublished - 2021

Bibliographical note

Publisher Copyright:
© International Headache Society 2021.

    Research areas

  • Biochemistry tests, gene-based genetic overlap, genetic correlation, Mendelian randomisation, SNP-based genetic overlap

ID: 283003305