Heterozygous mutations in the C-terminal domain of COPA underlie a complex autoinflammatory syndrome
Selket Delafontaine, … , Jérôme Delon, Isabelle Meyts
Selket Delafontaine, … , Jérôme Delon, Isabelle Meyts
Published January 4, 2024
Citation Information: J Clin Invest. 2024;134(4):e163604. https://doi.org/10.1172/JCI163604.
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Research Article Immunology

Heterozygous mutations in the C-terminal domain of COPA underlie a complex autoinflammatory syndrome

Abstract

Mutations in the N-terminal WD40 domain of coatomer protein complex subunit α (COPA) cause a type I interferonopathy, typically characterized by alveolar hemorrhage, arthritis, and nephritis. We described 3 heterozygous mutations in the C-terminal domain (CTD) of COPA (p.C1013S, p.R1058C, and p.R1142X) in 6 children from 3 unrelated families with a similar syndrome of autoinflammation and autoimmunity. We showed that these CTD COPA mutations disrupt the integrity and the function of coat protein complex I (COPI). In COPAR1142X and COPAR1058C fibroblasts, we demonstrated that COPI dysfunction causes both an anterograde ER-to-Golgi and a retrograde Golgi-to-ER trafficking defect. The disturbed intracellular trafficking resulted in a cGAS/STING-dependent upregulation of the type I IFN signaling in patients and patient-derived cell lines, albeit through a distinct molecular mechanism in comparison with mutations in the WD40 domain of COPA. We showed that CTD COPA mutations induce an activation of ER stress and NF-κB signaling in patient-derived primary cell lines. These results demonstrate the importance of the integrity of the CTD of COPA for COPI function and homeostatic intracellular trafficking, essential to ER homeostasis. CTD COPA mutations result in disease by increased ER stress, disturbed intracellular transport, and increased proinflammatory signaling.

Authors

Selket Delafontaine, Alberto Iannuzzo, Tarin M. Bigley, Bram Mylemans, Ruchit Rana, Pieter Baatsen, Maria Cecilia Poli, Daisy Rymen, Katrien Jansen, Djalila Mekahli, Ingele Casteels, Catherine Cassiman, Philippe Demaerel, Alice Lepelley, Marie-Louise Frémond, Rik Schrijvers, Xavier Bossuyt, Katlijn Vints, Wim Huybrechts, Rachida Tacine, Karen Willekens, Anniek Corveleyn, Bram Boeckx, Marco Baggio, Lisa Ehlers, Sebastian Munck, Diether Lambrechts, Arnout Voet, Leen Moens, Giorgia Bucciol, Megan A. Cooper, Carla M. Davis, Jérôme Delon, Isabelle Meyts

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Figure 7

CTD COPA mutations cause activation of ER stress and proinflammatory signaling pathways such as the NF-κB pathway.

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CTD COPA mutations cause activation of ER stress and proinflammatory sign...
(A) Relative mRNA expression of HSPA5, ATF4, DDIT3, and COPA in EBV LCLs of 4 healthy controls, A.I.1, A.II.3, C.I.1, and C.II.1–4. LCLs were unstimulated (white, –) or treated for 6 hours with thapsigargin (black, +). Results were normalized to GAPDH (ΔCt) and to the control samples (ΔΔCt). (B) Representative images of immunofluorescent analysis of BiP intensity in fibroblasts of healthy controls, A.I.1, A.II.3, and B.II.1. Cells were stained for BiP, F-actin, and nucleus and stimulated with thapsigargin. Graphs represent quantification of MFI of BiP. (C) Representative images of immunofluorescent analysis of p65–NF-κB nuclear translocation in fibroblasts of healthy controls, A.I.1, A.II.3, and B.II.1. Cells were stimulated with LPS and stained for p65–NF-κB and nucleus. Nuclear translocation of p65 appears violet. Graphs represent quantification of nuclear translocation of NF-κB. Scale bars: 10 μm. In A–C, columns and bars represent mean ± SEM, representative of 2 (A) to 3 (B and C) independent experiments. Statistical analysis was performed using 1-way (A) or 2-way ANOVA (B and C) (*P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001). (D–F) Analysis of bulk RNA sequencing data of whole-blood RNA of 4 controls (black), 2 carriers (A.I.1 and C.I.1), 1 SAVI patient (green), and 5 patients (A.II.3, C.II.1–4). (D) Principal component analysis (PCA) plot of bulk RNA sequencing data, based on the 1,000 genes with the largest intersample variance (after a variance stabilizing transformation removing the variance dependence on the mean). (E) Top 10 differentially expressed pathways determined by IPA analysis of differential gene expression for patients A.II.3 (left) and C.II.4 (right) versus the group consisting of carriers (A.I.1, C.I.1), controls, SAVI patient, and C.II.1–3. (F) Heatmaps represent differential expression analysis for the eIF2 pathway, 24 autophagy genes, and a limited list of ISGs.