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MAGMA HBA (Kerrebijin et al, Fibromyalgia)

I applied MAGMA to the Kerrebijin et al.'s GWAS of Fibromyalgia2 using scRNAseq data from the Human Brain Atlas3 (HBA). As in my other MAGMA analyses, I sourced linkage disequilibrium reference data from the European subset of the 1000-genomes project. I used a MAGMA gene/cell specificity matrix (i.e. the \(E\) matrix in my notes on MAGMA ) prepared as described1 in Duncan et al.4

Results

The results are plotted below, first as a static image, then as an interactive plot:

hba-magma-plot-for-fibromyalgia

The x-axis corresponds to HBA cluster number3, while the y-axis corresponds to the \(-\log_{10}(p)\) score generated by MAGMA. Clusters are colored according to their HBA supercluster. The dotted line denotes the Bonferroni significance threshold. I used a conditional analysis approach based on the one described in Wanatabe et al.5 to identify independent clusters.

It is interesting to compare these results to those from the HBA-MAGMA analysis of DecodeME. Despite the high CT-LDSC-measured high genetic correlation between fibromyalgia and DecodeME ME/CFS, the significant brain cells types of the two phenotypes are quite different.

  1. Duncan et al.4 first log-transform the raw RNAseq matrix, and then row-normalize it. Note that this differs from the FUMA approach. See the Section "Gene expression data" from their paper. See also their GitHub repo. ↩

  2. Isabel Kerrebijn, Gyda Bjornsdottir, Keon Arbabi, Lea Urpa, Hele Haapaniemi, Gudmar Thorleifsson, Lilja Stefansdottir, Stephan Frangakis, Jesse Valliere, Lovemore Kunorozva, and others. The genetic architecture of fibromyalgia across 2.5 million individuals. Nature Medicine, pages 1–11, 2026. URL: https://www.nature.com/articles/s41591-026-04492-6.pdf. ↩

  3. Kimberly Siletti, Rebecca Hodge, Alejandro Mossi Albiach, Ka Wai Lee, Song-Lin Ding, Lijuan Hu, Peter Lönnerberg, Trygve Bakken, Tamara Casper, Michael Clark, and others. Transcriptomic diversity of cell types across the adult human brain. Science, 382(6667):eadd7046, 2023. URL: https://www.science.org/doi/abs/10.1126/science.add7046. ↩↩

  4. Laramie E Duncan, Tayden Li, Madeleine Salem, Will Li, Leili Mortazavi, Hazal Senturk, Naghmeh Shahverdizadeh, Sam Vesuna, Hanyang Shen, Jong Yoon, and others. Mapping the cellular etiology of schizophrenia and complex brain phenotypes. Nature Neuroscience, 28(2):248–258, 2025. URL: https://www.nature.com/articles/s41593-024-01834-w. ↩↩

  5. Kyoko Watanabe, Maša Umićević Mirkov, Christiaan A de Leeuw, Martijn P van den Heuvel, and Danielle Posthuma. Genetic mapping of cell type specificity for complex traits. Nature Communications, 10(1):3222, 2019. URL: https://www.nature.com/articles/s41467-019-11181-1. ↩