Joint analysis reveals shared autoimmune disease associations and identifies common mechanisms

Lincoln, Matthew R.; Connally, Neeta P.; Axisa, Pierre-Paul; Gasperi, Christiane; Mitrovič, Mitja; Dv, Heel; Wijmenga, Cisca; Withoff, Sebo; Ih, Jonkers; Padyukov, Leonid; Rich, Stephen S.; Rr, Graham; Pm, Gaffney; Cd, Langefeld; Da, Hafler; Chun, Sung; Sunayev,; Cotsapas, Chris

doi:10.1101/2021.05.13.21257044

Cited by 10 publications

(11 citation statements)

References 34 publications

(31 reference statements)

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“…Using these and related statistical techniques, highly significant genetic covariances were estimated among various autoimmune diseases and among various psychiatric diseases and related phenotypes ( Cotsapas et al, 2011 ; Lee et al, 2013 ; Watanabe et al, 2019 ; Lincoln et al, 2021 ). The analysis of genetic covariances between two traits has some limitations.…”

Section: Empirical Demonstrations Of the Existence And Nature Of Pleiotropymentioning

confidence: 99%

“…Multiple examples of local genetic correlations and individually colocalized loci have been described ( van Rheenen et al, 2019 ; Aguet et al, 2020 ; Vuckovic et al, 2020 ). However, some QTLs involved in genetically correlated traits do not show obvious signals of colocalization, suggesting that genetic correlation does not necessarily imply pleiotropic effects of all variants ( Lincoln et al, 2021 ).…”

Section: Empirical Demonstrations Of the Existence And Nature Of Pleiotropymentioning

confidence: 99%

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Maintenance of Complex Trait Variation: Classic Theory and Modern Data

Koch

Sunyaev

2021

Front. Genet.

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Numerous studies have found evidence that GWAS loci experience negative selection, which increases in intensity with the effect size of identified variants. However, there is also accumulating evidence that this selection is not entirely mediated by the focal trait and contains a substantial pleiotropic component. Understanding how selective constraint shapes phenotypic variation requires advancing models capable of balancing these and other components of selection, as well as empirical analyses capable of inferring this balance and how it is generated by the underlying biology. We first review the classic theory connecting phenotypic selection to selection at individual loci as well as approaches and findings from recent analyses of negative selection in GWAS data. We then discuss geometric theories of pleiotropic selection with the potential to guide future modeling efforts. Recent findings revealing the nature of pleiotropic genetic variation provide clues to which genetic relationships are important and should be incorporated into analyses of selection, while findings that effect sizes vary between populations indicate that GWAS measurements could be misleading if effect sizes have also changed throughout human history.

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Section: Empirical Demonstrations Of the Existence And Nature Of Pleiotropymentioning

confidence: 99%

Section: Empirical Demonstrations Of the Existence And Nature Of Pleiotropymentioning

confidence: 99%

Maintenance of Complex Trait Variation: Classic Theory and Modern Data

Koch

Sunyaev

2021

Front. Genet.

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“…Beside HLA, other genetic loci are shared between autoimmune diseases, with first investigations finding 47/107 (44%) immune-mediated disease risk variants associated with multiple, but not all such diseases (3), and later work identifying 244 shared disease loci (4). Accordingly, efforts are ongoing to unravel shared disease mechanisms based on shared genetic profiles (5,6). Such genetics-driven systems approaches to autoimmune disease can largely benefit from public resources of genome and phenotype data as well as derived information.…”

Section: Introductionmentioning

confidence: 99%

A survey of genome-wide association studies, polygenic scores and UK Biobank highlights resources for autoimmune disease genetics

Saurabh

Fouodo²,

König³

et al. 2022

Front. Immunol.

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Autoimmune diseases share a general mechanism of auto-antigens harming tissues. Still. they are phenotypically diverse, with genetic as well as environmental factors contributing to their etiology at varying degrees. Associated genomic loci and variants have been identified in numerous genome-wide association studies (GWAS), whose results are increasingly used for polygenic scores (PGS) that are used to predict disease risk. At the same time, a technological shift from genotyping arrays to next generation sequencing (NGS) is ongoing. NGS allows the identification of virtually all - including rare - genetic variants, which in combination with methodological developments promises to improve the prediction of disease risk and elucidate molecular mechanisms underlying disease. Here we review current, publicly available autoimmune disease GWAS and PGS data based on information from the GWAS and PGS catalog, respectively. We summarize autoimmune diseases investigated, respective studies conducted and their results. Further, we review genetic data and autoimmune disease patients in the UK Biobank (UKB), the largest resource for genetic and phenotypic data available for academic research. We find that only comparably prevalent autoimmune diseases are covered by the UKB and at the same time assessed by both GWAS and PGS catalogs. These are systemic (systemic lupus erythematosus) as well as organ-specific, affecting the gastrointestinal tract (inflammatory bowel disease as well as specifically Crohn’s disease and ulcerative colitis), joints (juvenile ideopathic arthritis, psoriatic arthritis, rheumatoid arthritis, ankylosing spondylitis), glands (Sjögren syndrome), the nervous system (multiple sclerosis), and the skin (vitiligo).

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“…A cross-disorder genomic analysis could identify shared mechanisms and potential targets for drug repurposing. By combining cases and controls across immune diseases, recent work identified 224 shared associations, improved fine-mapping and revealed shared disease genes such as RGS1 13 . Similarly, a study using local genetic correlation showed widespread sharing across traits 14 .…”

Section: Introductionmentioning

confidence: 99%

Cross-disorder genetic analysis of immune diseases reveals distinct disease groups and associated genes that converge on common pathogenic pathways

Demela

Pirastu

Soskic

2022

Preprint

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Genome-wide association studies (GWAS) have mapped thousands of susceptibility loci associated with immune-mediated diseases, many of which are shared across multiple diseases. To assess the extent of the genetic sharing across nine immune-mediated diseases we applied genomic structural equation modelling (genomic SEM) to GWAS data. By modelling the genetic covariance between these diseases, we identified three distinct groups: gastrointestinal tract diseases, rheumatic and systemic diseases, and allergic diseases. We identified 92, 103 and 91 genetic loci that predispose to each of these disease groups, with only 12 of them being shared across groups. Although loci associated with each of these disease groups were highly specific, they converged on perturbing the same pathways, primarily T cell activation and cytokine signalling. Finally, to assess whether variants associated with each disease group modulate gene expression in immune cells, we tested for colocalization between loci and single-cell eQTLs derived from peripheral blood mononuclear cells. We identified the causal route by which 47 loci contribute to predisposition to these three disease groups. In addition, given that the assessed variants are pleiotropic, we found evidence for eight of these genes being strong candidates for drug repurposing. Taken together, our data suggest that different constellations of diseases have distinct patterns of genetic association, but that associated loci converge on perturbing different nodes in a common set of T cell activation and signalling pathways.

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Joint analysis reveals shared autoimmune disease associations and identifies common mechanisms

Cited by 10 publications

References 34 publications

Maintenance of Complex Trait Variation: Classic Theory and Modern Data

Maintenance of Complex Trait Variation: Classic Theory and Modern Data

A survey of genome-wide association studies, polygenic scores and UK Biobank highlights resources for autoimmune disease genetics

Cross-disorder genetic analysis of immune diseases reveals distinct disease groups and associated genes that converge on common pathogenic pathways

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