H MAGMA

I applied H-MAGMA¹ to the summary statistics from Johnston et al.²'s GWAS of multisite pain.

Results

I used the 6 standard variant-to-gene assignment maps provided by the authors of H-MAGMA. Like in the other MAGMA analyses, I used the European 1000-genomes linkage disequilibrium reference. The Manhattan plots below illustrate the gene-level MAGMA results.

Adult Brain

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Fetal Brain

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Cortical Neuron

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Midbrain

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IPSC-derived Astrocyte

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IPSC-derived Neuron

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1. Nancy YA Sey, Benxia Hu, Won Mah, Harper Fauni, Jessica Caitlin McAfee, Prashanth Rajarajan, Kristen J Brennand, Schahram Akbarian, and Hyejung Won. A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles. Nature Neuroscience, 23(4):583–593, 2020. URL: https://pmc.ncbi.nlm.nih.gov/articles/PMC7131892/. ↩

2. Keira JA Johnston, Mark J Adams, Barbara I Nicholl, Joey Ward, Rona J Strawbridge, Amy Ferguson, Andrew M McIntosh, Mark ES Bailey, and Daniel J Smith. Genome-wide association study of multisite chronic pain in UK Biobank. PLoS Genetics, 15(6):e1008164, 2019. URL: https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1008164. ↩