SynthesisFrontiers in immunology2023
PheWAS and cross-disorder analysis reveal genetic architecture, pleiotropic loci and phenotypic correlations across 11 autoimmune disorders.
Synthesis in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 11 citations in OpenAlex.
- AI-based multimodal integration of genomics and electronic health records.Nature reviews. Genetics · 2026Review
- Genetic evidence for causal links between type 1 diabetes and autoimmune liver diseases.Diabetology & metabolic syndrome · 2025Article
- Examining the genetic links between clusters of immune-mediated diseases and psychiatric disorders.Translational psychiatry · 2025Article
- Integrating transcriptomic and polygenic risk scores to enhance predictive accuracy for ischemic stroke subtypes.Human genetics · 2025Article
- Mapping the genetic landscape of immune-mediated disorders: potential implications for classification and therapeutic strategies.Frontiers in immunology · 2025Article
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Authors and funding
15 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Autoimmune disorders (ADs) are a group of about 80 disorders that occur when self-attacking autoantibodies are produced due to failure in the self-tolerance mechanisms. ADs are polygenic disorders and associations with genes both in the human leukocyte antigen (HLA) region and outside of it have been described. Previous studies have shown that they are highly comorbid with shared genetic risk factors, while epidemiological studies revealed associations between various lifestyle and health-related phenotypes and ADs. Methods: Here, for the first time, we performed a comparative polygenic risk score (PRS) - Phenome Wide Association Study (PheWAS) for 11 different ADs (Juvenile Idiopathic Arthritis, Primary Sclerosing Cholangitis, Celiac Disease, Multiple Sclerosis, Rheumatoid Arthritis, Psoriasis, Myasthenia Gravis, Type 1 Diabetes, Systemic Lupus Erythematosus, Vitiligo Late Onset, Vitiligo Early Onset) and 3,254 phenotypes available in the UK Biobank that include a wide range of socio-demographic, lifestyle and health-related outcomes. Additionally, we investigated the genetic relationships of the studied ADs, calculating their genetic correlation and conducting cross-disorder GWAS meta-analyses for the observed AD clusters. Results: In total, we identified 508 phenotypes significantly associated with at least one AD PRS. 272 phenotypes were significantly associated after excluding variants in the HLA region from the PRS estimation. Through genetic correlation and genetic factor analyses, we identified four genetic factors that run across studied ADs. Cross-trait meta-analyses within each factor revealed pleiotropic genome-wide significant loci. Discussion: Overall, our study confirms the association of different factors with genetic susceptibility for ADs and reveals novel observations that need to be further explored.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.