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MAGMA HBA Analysis

I applied MAGMA1 to Nyeo et al.'s GWAS of Epstein-Barr Virus (EBV) DNA2 using scRNAseq data from the Human Brain Atlas3 (HBA) as a reference.

The results are plotted below:

Result of HBA MAGMA applied to Nyeo et al.'s EBV DNA GWAS. The x-axis corresponds to HBA cluster number, while the y-axis corresponds to the negative log p value generated by MAGMA. Clusters are colored according to their HBA supercluster. The dotted line denotes the Bonferroni significance threshold.

I also used a conditional analysis approach based on the one described in Watanabe et al.4 to identify independent clusters. The one independent cluster found is listed in the table below.

Retained_clusters P Supercluster Class auto-annotation Neurotransmitter auto-annotation Neuropeptide auto-annotation Subtype auto-annotation Transferred MTG Label Top three regions Top Enriched Genes
Cluster1 4.9983e-11 Miscellaneous TCELL 0 0 0 Midbrain: 15.0%, Basal forebrain: 14.0%, Pons: 13.2% CD2, IL7R, PTPRC, SLFN12L, IL32, CCL5, GRAP2, RUNX3, CD69, CD3E

Since an overwhelming majority of people are infected by EBV, the level of EBV DNA in a person's blood is primarily a function of how well that person's adaptive immune system is able to keep their infection under control and in a dormant state. It thus makes sense that MAGMA analysis should point to T lymphocytes, which are central cells of the adaptive immune system, as key determinants of EBV DNA levels.

  1. Christiaan A De Leeuw, Joris M Mooij, Tom Heskes, and Danielle Posthuma. MAGMA: generalized gene-set analysis of GWAS data. PLoS Computational Biology, 11(4):e1004219, 2015. URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004219. ↩

  2. Sherry S Nyeo, Erin M Cumming, Oliver S Burren, Meghana S Pagadala, Jacob C Gutierrez, Thahmina A Ali, Laura C Kida, Yifan Chen, Hoyin Chu, Fengyuan Hu, and others. Population-scale sequencing resolves determinants of persistent ebv dna. Nature, pages 1–9, 2026. URL: https://www.nature.com/articles/s41586-025-10020-2. ↩

  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. 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. ↩