Human Molecular GeneticsGeneticsPeer-reviewed journal article
Integrating Mendelian randomization and multiple-trait colocalization to uncover cell-specific inflammatory drivers of autoimmune and atopic disease
Lucy M. McGowaniD, George Davey SmithiD, Tom R. GauntiD, Tom G. RichardsoniD
Abstract
Immune mediated diseases (IMDs) arise from a lack of immune tolerance, causing chronic inflammation. Despite their growing prevalence, targeted therapies to treat IMDs are lacking. Cytokines and their receptors, which mediate inflammation, have been associated with IMD susceptibility. However, the complex signalling networks and multiple cell-types required to orchestrate inflammatory responses have made it difficult to pinpoint specific cytokines and immune cell-types which drive IMDs.\n\nIn this study, we developed an analytical framework which integrates Mendelian randomisation (MR) and multiple-trait colocalization (moloc) analyses to determine putative cell-specific drivers of IMDs. We used MR to determine the likelihood of causal associations between the levels of 10 circulating cytokines/cytokine receptors and 9 IMDs within human populations of European descent. Conservative (single SNP) and liberal (multiple SNP) MR analysis supported a causal role for IL-18 in inflammatory bowel disease (P = 1.17 x 10-4) and eczema/dermatitis (P = 2.81 x 10-3), as well as roles for IL-2r and IL-6R in several IMDs.\n\nWhere associations between cytokines/cytokine receptors and IMDs were discovered using MR, we undertook moloc analyses. This was to assess the likelihood that cytokine/cytokine receptor protein quantitative trait loci (pQTL) and IMD-associated loci share a causal genetic variant along with expression QTL (eQTL) using data from 3 immune cell-types: monocytes, neutrophils and T cells. We found a monocyte and neutrophil-driven role for IL-18 in IBD pathogenesis, amongst evidence supporting several other cell-specific inflammatory drivers of IMDs. Our study helps to elucidate causal pathways for the pathogeneses of IMDs which, together with other studies, highlights possible therapeutic targets for their treatment.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- approach: Bayesian inference
- Citations
- 39
- FWCI
- 3.00
- Field percentile
- top 8%
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