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PPP CT-LDSC (DecodeME, ME/CFS)

I applied Cross Trait Linkage Disequilibrium Score Regression (CT-LDSC)1 to estimate genetic correlation between the DecodeME GWAS of ME/CFS and the Olink proteomic 2 GWAS of the European discovery cohort of the UK Biobank Pharma Proteomics Project (UKBB PPP)3.

Results

As is standard for LDSC analysis, I restricted the summary statistics to Hapmap 3 variants, and excluded the MHC region. I used the standard thousand genomes linkage disequilibrium scores provided by the authors of LDSC. To focus on trans effects, I excluded the cis regions from the proteomic GWAS.

The results are below:

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Columns: oid: Olink assay ID; gene: name of gene/protein under study; rg: CT-LDSC genetic correlation estimate; rg_se: jackknife standard error of CT-LDSC genetic correlation estimate; rg_p: p value of test that rg is not zero; gcov: estimated genetic covariance; inter: intercept term in CT-LDSC regression; h2_trait: trait heritability estimate; h2_prot: protein heritability estimate; n_snps: number of hapmap3 variants included; spr: for cases in which multiple rows corresponding to distinct Olink assays of the same protein have been merged into a single row, this gives the maximum spread between the rg values of the merged rows; s_bh: True if the null hypothesis is rejected under the Benjamini-Hochberg procedure at an FDR of 0.05; s_bon: True if the null hypothesis is rejected under the Bonferroni correction at a significance level of 0.05.

Interpretation

There are no significant genetic correlations. Thoughts:

  • This could simply be a power issue. In the future, when we have ME/CFS GWAS with large sample sizes, we may be able to detect genetic correlations with plasma proteins.
  • Our MAGMA and S-LDSC analyses suggest that ME/CFS heritability is enriched in neural tissue. Thus, instead of studying genetic correlations between ME/CFS and plasma protein levels, it could be more fruitful to look for genetic correlations between ME/CFS and cerebro-spinal fluid (CSF) protein levels. Public summary statistics of CSF proteomic GWAS are available4.
  • CT-LDSC is a robust but generic technique. It could be productive to apply a technique specifically designed to detect genetic associations between diseases traits and proteomic traits. PolyPWAS5 is an example of such a technique.

How to reproduce this

To reproduce these results, run this script.

  1. Brendan Bulik-Sullivan, Hilary K Finucane, Verneri Anttila, Alexander Gusev, Felix R Day, Po-Ru Loh, ReproGen Consortium, Psychiatric Genomics Consortium, Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control Consortium 3, Laramie Duncan, and others. An atlas of genetic correlations across human diseases and traits. Nature Genetics, 47(11):1236–1241, 2015. URL: https://pmc.ncbi.nlm.nih.gov/articles/PMC4797329/. ↩

  2. Lotta Wik, Niklas Nordberg, John Broberg, Johan Björkesten, Erika Assarsson, Sara Henriksson, Ida Grundberg, Erik Pettersson, Christina Westerberg, Elin Liljeroth, and others. Proximity extension assay in combination with next-generation sequencing for high-throughput proteome-wide analysis. Molecular & Cellular Proteomics, 20:100168, 2021. URL: https://www.sciencedirect.com/science/article/pii/S1535947621001407. ↩

  3. Benjamin B Sun, Joshua Chiou, Matthew Traylor, Christian Benner, Yi-Hsiang Hsu, Tom G Richardson, Praveen Surendran, Anubha Mahajan, Chloe Robins, Steven G Vasquez-Grinnell, and others. Plasma proteomic associations with genetics and health in the UK Biobank. Nature, 622(7982):329–338, 2023. URL: https://www.nature.com/articles/s41586-023-06592-6. ↩

  4. Daniel Western, Jigyasha Timsina, Lihua Wang, Ciyang Wang, Chengran Yang, Bridget Phillips, Yueyao Wang, Menghan Liu, Muhammad Ali, Aleksandra Beric, and others. Proteogenomic analysis of human cerebrospinal fluid identifies neurologically relevant regulation and implicates causal proteins for alzheimer’s disease. Nature genetics, 56(12):2672–2684, 2024. URL: https://pmc.ncbi.nlm.nih.gov/articles/PMC11831731/. ↩

  5. Kangcheng Hou, Ali Pazokitoroudi, Benjamin Strober, Xilin Jiang, and Alkes L Price. Functionally informed cis and trans proteome-wide association studies prioritize disease-critical genes. Research Square, pages rs–3, 2026. ↩