Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Jan 12;12(1):e0169918.
doi: 10.1371/journal.pone.0169918. eCollection 2017.

Collective Genetic Interaction Effects and the Role of Antigen-Presenting Cells in Autoimmune Diseases

Free PMC article

Collective Genetic Interaction Effects and the Role of Antigen-Presenting Cells in Autoimmune Diseases

Hyung Jun Woo et al. PLoS One. .
Free PMC article


Autoimmune diseases occur when immune cells fail to develop or lose their tolerance toward self and destroy body's own tissues. Both insufficient negative selection of self-reactive T cells and impaired development of regulatory T cells preventing effector cell activation are believed to contribute to autoimmunity. Genetic predispositions center around the major histocompatibility complex (MHC) class II loci involved in antigen presentation, the key determinant of CD4+ T cell activation. Recent studies suggested that variants in the MHC region also exhibit significant non-additive interaction effects. However, collective interactions involving large numbers of single nucleotide polymorphisms (SNPs) contributing to such effects are yet to be characterized. In addition, relatively little is known about the cell-type-specificity of such interactions in the context of cellular pathways. Here, we analyzed type 1 diabetes (T1D) and rheumatoid arthritis (RA) genome-wide association data sets via large-scale, high-performance computations and inferred collective interaction effects involving MHC SNPs using the discrete discriminant analysis. Despite considerable differences in the details of SNP interactions in T1D and RA data, the enrichment pattern of interacting pairs in reference epigenomes was remarkably similar: statistically significant interactions were epigenetically active in cell-type combinations connecting B cells to T cells and intestinal epithelial cells, with both helper and regulatory T cells showing strong disease-associated interactions with B cells. Our results provide direct genetic evidence pointing to the important roles B cells play as antigen-presenting cells toward CD4+ T cells in the context of central and peripheral tolerance. In addition, they are consistent with recent experimental studies suggesting that the repertoire of B cell-specific self-antigens in the thymus are critical to the effective control of corresponding autoimmune activation in peripheral tissues.

Conflict of interest statement

The authors have declared that no competing interests exist.


Fig 1
Fig 1. Genome-wide association of type 1 diabetes (T1D) and rheumatoid arthritis (RA) single-nucleotide polymorphisms (SNPs) under independent-SNP and collective inferences.
(A) Independent-SNP p-value profiles based on genotypic model. Note that the p-values are in “double logarithmic” scale for clarity. (B-C) Optimization of collective inference model parameters with cross-validation area under the curve (AUC) as a function of model sizes (mean number of SNPs selected) and inverse of penalizer 1/λ. The small and large-1/λ limits correspond to non-interacting and strongly interacting limits, respectively. Vertical bars are 95% c.i. (D-E) Statistical significance of the rise in AUC from interaction effects (ΔAUC; defined as the difference between the maximum AUC and the non-interacting limit). For T1D (D) and RA (E), the first m SNPs were selected from the sorted list with increasing order of single-SNP p-value pi, and the null distribution of ΔAUC was sampled by permutation of the phenotypic label to estimate the p-value (bottom; horizontal line represents p = 0.05) for the significance of the actual ΔAUC observed (top).
Fig 2
Fig 2. T1D collective inference p-values and epigenetic activity distribution.
SNPs (“proxies”) were selected based on their independent-SNP pi values (middle, open bars). The top (triangular) and middle (bar graph) panels show the interaction and (additive) single-SNP contributions, respectively. Bottom panel shows the mean frequencies (averaged over groups of all known SNPs in high LD to each proxy) of epigenetically active states within the 111 Roadmap reference epigenomes.
Fig 3
Fig 3. RA collective inference p-values and epigenetic activity distribution.
m = 70 proxy SNPs were selected based on pi values (middle, open bars) combined with clustering to reduce LD. The top (triangular) and middle (bar graph) panels show the interaction and (additive) single-SNP contributions, respectively. Bottom panel shows the mean frequencies of epigenetically active states as in Fig 2.
Fig 4
Fig 4. Cell type-specific enrichment of SNPs and their interactions.
(A) Single-SNP enrichment (over-representation p-values) of T1D and RA-associated proxy SNPs (Fig 2) in reference epigenomes. (B) Enrichment of statistically significant interaction pairs active in cell type combinations. Combinations with negligible enrichment are not shown for clarity. Note the dominance of B cells in their interaction to T cells, monocytes, and intestinal epithelial cells. See S5 Fig for the full epigenome names. (C) Interrelationships of genetic factors associated with autoimmunity in the context of antigen presenting cell (APC) versus T cell interaction. Thymic APCs are stimulated by the epidermal growth factor receptor (EGFR) and interferon (IFN)-γ signaling pathways to express major histocompatibility (MHC) class II molecules, which are assembled in the endoplasmic reticulum (ER) and loaded by AIRE-induced self-peptides in the endosomal MHC class II compartment (MIIC). The peptide-MHC complex is recognized by the T cell receptor (TCR), initiating its downstream signaling leading to the activation of NF-κB, which enters the nucleus and up-regulates FOXP3 (in Tregs), interleukin (IL)-2 receptors, and IL-2 (in conventional CD4+ T cells). IL-2 signaling is crucial to both conventional T cell proliferation and Treg cell activation. Genes shown in red are those implicated by the top-ranked pathways (Fig 6).
Fig 5
Fig 5. Sequence of relative importance of APC repertoire in T cell selection based on epigenomic enrichment.
The p-values indicated (Table 1) refer to those of interactions with Th naive for fetal thymus, monocytes, B cells (cord blood), and B cells (peripheral blood), respectively.
Fig 6
Fig 6. Spatial distribution of tissue-specific SNP-interactions for T1D.
The overall enrichment profiles of cell type combinations in Fig 4B were resolved into contributions from genetic regions within the MHC locus. (A) B cell:B cell, (B) B cell:T cell, and (C) Duodenum mucosa:Treg cell combinations. The left and right columns show the effective number of active SNP pairs (in a 20-kb grid) and the relative enrichment of this number within the given cell type combination against the total (in a 100-kb grid), respectively.
Fig 7
Fig 7. Immune system pathways scored by collective inference.
The pathways belonging to the Immune system pathway in Reactome hierarchy in association with (A) T1D with AUC > 0.65 and (B) RA with AUC > 0.57 are shown. The dendrograms below the bars represent the relative hierarchical relationships. Error bars are 95% c.i. Adv., advanced; DAP12, DNAX activation protein of 12kDa; DHX, aspartate-glutamate-any amino acid aspartate/histidine (DExD/H) box helicase; ER, endoplasmic reticulum; exog. exogenous; immunoreg., immunoregulatory; IFN, interferon; inter., interation; PD-1, programmed cell death protein 1; present., presentation; RIP, receptor-interacting protein; sol., soluble; TCR, T cell receptor; ZBP1, Z-DNA binding protein 1.

Similar articles

See all similar articles

Cited by 3 articles


    1. Parkes M, Cortes A, van Heel DA, Brown MA. Genetic insights into common pathways and complex relationships among immune-mediated diseases. Nat Rev Genet. 2013;14(9):661–73. Epub 2013/08/07. 10.1038/nrg3502 - DOI - PubMed
    1. van Belle TL, Coppieters KT, von Herrath MG. Type 1 diabetes: etiology, immunology, and therapeutic strategies. Physiol Rev. 2011;91(1):79–118. Epub 2011/01/21. 10.1152/physrev.00003.2010 - DOI - PubMed
    1. Firestein GS. Evolving concepts of rheumatoid arthritis. Nature. 2003;423(6937):356–61. Epub 2003/05/16. 10.1038/nature01661 - DOI - PubMed
    1. Andlauer TF, Buck D, Antony G, Bayas A, Bechmann L, Berthele A, et al. Novel multiple sclerosis susceptibility loci implicated in epigenetic regulation. Sci Adv. 2016;2(6):e1501678 Epub 2016/07/08. 10.1126/sciadv.1501678 - DOI - PMC - PubMed
    1. Polychronakos C, Li Q. Understanding type 1 diabetes through genetics: advances and prospects. Nat Rev Genet. 2011;12(11):781–92. Epub 2011/10/19. 10.1038/nrg3069 - DOI - PubMed

MeSH terms