Genome-wide classification of epigenetic activity reveals regions of enriched heritability in immune-related traits.

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  • Additional Information
    • Source:
      Publisher: Elsevier, Inc Country of Publication: United States NLM ID: 9918284260106676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2666-979X (Electronic) Linking ISSN: 2666979X NLM ISO Abbreviation: Cell Genom Subsets: MEDLINE
    • Publication Information:
      Original Publication: [New York] : Elsevier, Inc., [2021]-
    • Subject Terms:
      Quantitative Trait Loci* ; Genomics*; Phenotype ; Linkage Disequilibrium/genetics ; Epigenesis, Genetic/genetics
    • Abstract:
      Epigenetics underpins the regulation of genes known to play a key role in the adaptive and innate immune system (AIIS). We developed a method, EpiNN, that leverages epigenetic data to detect AIIS-relevant genomic regions and used it to detect 2,765 putative AIIS loci. Experimental validation of one of these loci, DNMT1, provided evidence for a novel AIIS-specific transcription start site. We built a genome-wide AIIS annotation and used linkage disequilibrium (LD) score regression to test whether it predicts regional heritability using association statistics for 176 traits. We detected significant heritability effects (average |τ ∗ |=1.65) for 20 out of 26 immune-relevant traits. In a meta-analysis, immune-relevant traits and diseases were 4.45× more enriched for heritability than other traits. The EpiNN annotation was also depleted of trans-ancestry genetic correlation, indicating ancestry-specific effects. These results underscore the effectiveness of leveraging supervised learning algorithms and epigenetic data to detect loci implicated in specific classes of traits and diseases.
      Competing Interests: Declaration of interests S.N. is an employee of Roche. W.-Y.C. is an employee of Regeneron and a former employee of Roche.
      (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)
    • Comments:
      Erratum in: Cell Genom. 2024 Mar 13;4(3):100508. (PMID: 38484703)
    • Grant Information:
      United Kingdom WT_ Wellcome Trust
    • Contributed Indexing:
      Keywords: epigenetics; heritability; immune system; machine learning
    • Publication Date:
      Date Created: 20240108 Date Completed: 20240214 Latest Revision: 20240314
    • Publication Date:
      20240315
    • Accession Number:
      PMC10794845
    • Accession Number:
      10.1016/j.xgen.2023.100469
    • Accession Number:
      38190103