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MAGMA

I applied the MAGMA2 pipeline to summary statistics from a GWAS of LDL from WIller at el.3.

In the gene set analysis step, I incorporated tissue-specific RNAseq data from GTEx4 to try to link genes associated with LDL to specific tissues.

The results are shown below:

Result of MAGMA GTEx applied to Willer et al.'s LDL GWAS. The x axis corresponds to tissue type, while the y axis measures MAGMA significance level.

The 4 most-significant tissues found by MAGMA are all in liver. This is very consistent with the known biology of LDL1 which is both synthesized and disposed of by liver cells.

  1. See for instance Chapters 4 and 5 of Steinberg's book5. ↩

  2. 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. ↩

  3. Global Lipids Genetics Consortium. Discovery and refinement of loci associated with lipid levels. Nature Genetics, 45(11):1274–1283, 2013. URL: https://pmc.ncbi.nlm.nih.gov/articles/PMC3838666/. ↩

  4. 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. ↩

  5. Daniel Steinberg. The cholesterol wars: the skeptics vs the preponderance of evidence. Elsevier, 2011. URL: https://www.amazon.com/dp/B0085TMWZ4. ↩