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MAGMA IBD Analysis

After applying MAGMA to the DecodeME summary statistics, I decided to apply it to summary statistics of a number of other conditions whose biology is better understood. The aim here was to assess the reliability of MAGMA. If MAGMA recapitulates known aspects of the pathophysiology of other diseases, this increases our confidence in the results of applying MAGMA to ME/CFS.

Data

I decided to start with Inflammatory bowel disease (IBD).

I used summary statistics from Liu et al.'s 2023 cross-ancestry meta-GWAS of inflammatory bowel disease1. Because my reference data is from the European population, I extracted only the summary statistics corresponding to non-Finish Europeans, excluding those summary statistics from other populations. I passed these summary statistics through the same MAGMA pipeline I applied to DecodeME.

Results

As before, I ran the gene analysis set, followed by the gene-set analysis step. In the gene property analysis step, I used tissue-specific RNAseq data from GTEx2 to try to link genes associated with IBD to specific tissues. The results are shown in the bar plot below:

bar_plot

Of note, the associations with colon and intestinal tissue make sense. These findings increase my confidence in MAGMA.

The association with whole blood may be a consequence of genes expressed in leukocytes, and may reflect the autoimmune nature of IBD. Finucane et al.3 hypothesized that the lungs of post-mortem donors from which the GTEx is derived may have contained a significant quantity of blood. If this hypothesis is correct, it would also explain the significant association of IBD with lung tissue observed here.

Reproducing

To reproduce the above, run the IBD GWAS Analysis Script.

  1. Zhanju Liu, Ruize Liu, Han Gao, Seulgi Jung, Xiang Gao, Ruicong Sun, Xiaoming Liu, Yongjae Kim, Ho-Su Lee, Yosuke Kawai, and others. Genetic architecture of the inflammatory bowel diseases across East Asian and European ancestries. Nature Genetics, 55(5):796–806, 2023. URL: https://www.nature.com/articles/s41588-023-01384-0. ↩

  2. GTEx Consortium. The GTEx consortium atlas of genetic regulatory effects across human tissues. Science, 369(6509):1318–1330, 2020. URL: https://www.science.org/doi/full/10.1126/science.aaz1776. ↩

  3. Hilary K Finucane, Yakir A Reshef, Verneri Anttila, Kamil Slowikowski, Alexander Gusev, Andrea Byrnes, Steven Gazal, Po-Ru Loh, Caleb Lareau, Noam Shoresh, and others. Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types. Nature Genetics, 50(4):621–629, 2018. URL: https://pmc.ncbi.nlm.nih.gov/articles/PMC5896795/. ↩