Mendelian pathway analysis of laboratory traits reveals distinct roles for ciliary subcompartments in common disease pathogenesis

Abstract

SummaryRare monogenic disorders of the primary cilium, termed ciliopathies, are characterized by extreme presentations of otherwise-common diseases, such as diabetes, hepatic fibrosis, and kidney failure. However, despite a revolution in our understanding of the cilium’s role in rare disease pathogenesis, the organelle’s contribution to common disease remains largely unknown. We hypothesized that common genetic variants affecting Mendelian ciliopathy genes might also contribute to common complex diseases pathogenesis more generally. To address this question, we performed association studies of 16,875 common genetic variants across 122 well-characterized ciliary genes with 12 quantitative laboratory traits characteristic of ciliopathy syndromes in 378,213 European-ancestry individuals in the UK BioBank. We incorporated tissue-specific gene expression analysis, expression quantitative trait loci (eQTL) and Mendelian disease information into our analysis, and replicated findings in meta-analysis to increase our confidence in observed associations between ciliary genes and human phenotypes. 73 statistically-significant gene-trait associations were identified across 34 of the 122 ciliary genes that we examined (including 8 novel, replicating associations). With few exceptions, these ciliary genes were found to be widely expressed in human tissues relevant to the phenotypes being studied, and our eQTL analysis revealed strong evidence for correlation between ciliary gene expression levels and patient phenotypes. Perhaps most interestingly our analysis identified different ciliary subcompartments as being specifically associated with distinct sets of patient phenotypes, offering a number of testable hypotheses regarding the cilium’s role in common complex disease. Taken together, our data demonstrate the utility of a Mendelian pathway-based approach to genomic association studies, and challenge the widely-held belief that the cilium is an organelle important mainly in development and in rare syndromic disease pathogenesis. The continued application of techniques similar to those described here to other phenotypes/Mendelian diseases is likely to yield many additional fascinating associations that will begin to integrate the fields of common and rare disease genetics, and provide insight into the pathophysiology of human diseases of immense public health burden.Contacttheodore.drivas@gmail.com

eQTpLot: a user-friendly R package for the visualization and colocalization of eQTL and GWAS signals

“…What follows is a description of the process used to generate each of the plots produced by eQTpLot, along with a series of use examples to both demonstrate the utility of eQTpLot, and to highlight some of the many options that can be combined to generate different outputs. For these examples we have analyzed a subset of data from our recently-published analysis of quantitative laboratory traits in the UK Biobank (22) – these summary statistics are available in full at https://ritchielab.org/publications/supplementary-data/ajhg-cilium, and the subset of summary data used for our example analyses can be downloaded from the eQTpLot GitHub page such that the reader may experiment with eQTpLot with the pre-supplied data.…”

eQTpLot: a user-friendly R package for the visualization of colocalization between eQTL and GWAS signals

“…What follows is a description of the process used to generate each of the plots produced by eQTpLot, along with a series of use examples to both demonstrate the utility of eQTpLot, and to highlight some of the many options that can be combined to generate different outputs. For these examples we have analyzed a subset of data from our recently-published analysis of quantitative laboratory traits in the UK Biobank [24] these summary statistics are available in full at https://ritchielab.org/publications/ supplementary-data/ajhg-cilium, and the subset of summary data used for our example analyses can be downloaded from the eQTpLot GitHub page such that the reader may experiment with eQTpLot with the pre-supplied data.…”

“…The eQTL data used to generate the eQTL.df file were generated previously, and are freely available through the GTEx Portal [11]. The GWAS summary statistics used to generate the GWAS.df file used in this manuscript are available at https://ritchielab.org/publications/supplementary-data/ajhg-cilium and are based on a study utilizing data available through the UK Biobank (UKBB) [24,25]. As a part of our agreement to use the data contained within UKBB, we are not allowed to share the raw data ourselves, but individuals who are interested can request access.…”

“…No new data involving human participants was generated or analyzed in this manuscript. Data used to generate the four example figures was obtained from previously-published summary statistics [24].…”