| Title: | A Meta-Analysis of the Genome-Wide Association Studies on Two Genetically Correlated Phenotypes Suggests Four New Risk Loci for Headaches |
| Journal: | Phenomics |
| Published: | 18 Nov 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/36939796/ |
| DOI: | https://doi.org/10.1007/s43657-022-00078-7 |
| URL: | https://link.springer.com/content/pdf/10.1007/s43657-022-00078-7.pdf |
| Citations: | 5 (5 in last 2 years) as of 8 Aug 2024 |
Publication 10700
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Abstract
Headache is one of the commonest complaints that doctors need to address in clinical settings. The genetic mechanisms of different types of headache are not well understood while it has been suggested that self-reported headache and self-reported migraine were genetically correlated. In this study, we performed a meta-analysis of genome-wide association studies (GWAS) on the self-reported headache phenotype from the UK Biobank and the self-reported migraine phenotype from the 23andMe using the Unified Score-based Association Test (metaUSAT) software for genetically correlated phenotypes (N = 397,385). We identified 38 loci for headaches, of which 34 loci have been reported before and four loci were newly suggested. The LDL receptor related protein 1 (LRP1) - Signal Transducer and Activator of Transcription 6 (STAT6) - Short chainDehydrogenase/Reductase family 9C member 7 (SDR9C7) region in chromosome 12 was the most significantly associated locus with a leading p value of 1.24 × 10-62 of rs11172113. The One Cut homeobox 2 (ONECUT2) gene locus in chromosome 18 was the strongest signal among the four new loci with a p value of 1.29 × 10-9 of rs673939. Our study demonstrated that the genetically correlated phenotypes of self-reported headache and self-reported migraine can be meta-analysed together in theory and in practice to boost study power to identify more variants for headaches. This study has paved way for a large GWAS meta-analysis involving cohorts of different while genetically correlated headache phenotypes.</p>
14 Authors
- Weihua Meng
- Parminder S. Reel
- Charvi Nangia
- Aravind Lathika Rajendrakumar
- Harry L. Hebert
- Qian Guo
- Mark J. Adams
- Hua Zheng
- Zen Haut Lu
- Debashree Ray
- Lesley A. Colvin
- Colin N. A. Palmer
- Andrew M. McIntosh
- Blair H. Smith
1 Application
| Application ID | Title |
|---|---|
| 4844 | STratifying Resilience and Depression Longitudinally (STRADL) |
Enabling scientific discoveries that improve human health