eQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs.

The eQTL Catalogue is an open database of uniformly processed human molecular quantitative trait loci (QTLs). We are continuously updating the resource to further increase its utility for interpreting genetic associations with complex traits. Over the past two years, we have increased the number of uniformly processed studies from 21 to 31 and added X chromosome QTLs for 19 compatible studies. We have also implemented Leafcutter to directly identify splice-junction usage QTLs in all RNA sequencing datasets. Finally, to improve the interpretability of transcript-level QTLs, we have developed static QTL coverage plots that visualise the association between the genotype and average RNA sequencing read coverage in the region for all 1.7 million fine mapped associations. To illustrate the utility of these updates to the eQTL Catalogue, we performed colocalisation analysis between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. Although most GWAS loci colocalised both with eQTLs and transcript-level QTLs, we found that visual inspection could sometimes be used to distinguish primary splicing QTLs from those that appear to be secondary consequences of large-effect gene expression QTLs. While these visually confirmed primary splicing QTLs explain just 6/53 of the colocalising signals, they are significantly less pleiotropic than eQTLs and identify a prioritised causal gene in 4/6 cases.

Skin Colonization with S. aureus Can Lead to Increased NLRP1 Inflammasome Activation in Patients with Atopic Dermatitis.

The role of NLRP1 inflammasome activation and subsequent production of IL-1 family cytokines in the development of atopic dermatitis (AD) is not clearly understood. Staphylococcus aureus is known to be associated with increased mRNA levels of IL1 family cytokines in the skin and more severe AD. In this study, the altered expression of IL-1 family cytokines and inflammasome-related genes was confirmed, and a positive relationship between mRNA levels of inflammasome sensor NLRP1 and IL1B or IL18 was determined. Enhanced expression of the NLRP1 and PYCARD proteins and increased caspase-1 activity were detected in the skin of patients with AD. The genetic association of IL18R1 and IL18RAP with AD was confirmed, and the involvement of various immune cell types was predicted using published GWAS and expression quantitative trait loci datasets. In keratinocytes, the inoculation with S. aureus led to the increased secretion of IL-1ß and IL-18, whereas small interfering RNA silencing of NLRP1 inhibited the production of these cytokines. Our results suggest that skin colonization with S. aureus may cause the activation of the NLRP1 inflammasome in keratinocytes, which leads to the secretion of IL-1ß and IL-18 and thereby may contribute to the pathogenesis of AD, particularly in the presence of genetic variations in the IL-18 pathway.

Systematic visualisation of molecular QTLs reveals variant mechanisms at GWAS loci.

Splicing quantitative trait loci (QTLs) have been implicated as a common mechanism underlying complex trait associations. However, utilising splicing QTLs in target discovery and prioritisation has been challenging due to extensive data normalisation which often renders the direction of the genetic effect as well as its magnitude difficult to interpret. This is further complicated by the fact that strong expression QTLs often manifest as weak splicing QTLs and vice versa, making it difficult to uniquely identify the underlying molecular mechanism at each locus. We find that these ambiguities can be mitigated by visualising the association between the genotype and average RNA sequencing read coverage in the region. Here, we generate these QTL coverage plots for 1.7 million molecular QTL associations in the eQTL Catalogue identified with five quantification methods. We illustrate the utility of these QTL coverage plots by performing colocalisation between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. We find that while visually confirmed splicing QTLs explain just 6/53 of the colocalising signals, they are significantly less pleiotropic than eQTLs and identify a prioritised causal gene in 4/6 cases. All our association summary statistics and QTL coverage plots are freely available at https://www.ebi.ac.uk/eqtl/.