Chronic mucocutaneous candidiasis and connective tissue disorder in humans with impaired JNK1-dependent responses to IL-17A/F and TGF-β

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Science Immunology  29 Nov 2019:
Vol. 4, Issue 41, eaax7965
DOI: 10.1126/sciimmunol.aax7965

Putting JNK1 on the immunodeficiency map

Impaired TH17 immunity is the shared element among the group of inherited immunodeficiencies associated with chronic mucocutaneous candidiasis (CMC). Li et al. studied three patients from a single family who had CMC associated with an atypical form of connective tissue disorder with some features of Ehlers-Danlos syndrome. Whole-exome sequencing identified a previously unreported loss-of-function splice-site mutation in the MAPK8 gene encoding c-Jun N-terminal kinase 1 (JNK1) that causes JNK1 haploinsufficiency with autosomal dominant inheritance. The complex clinical phenotype in these patients results from defects in signaling downstream of both IL-17 and TGF-β cytokines. These findings demonstrate that JNK1-mediated signaling plays a critical role in maintaining normal immunity to Candida as well as supporting TGF-β–dependent homeostasis of connective tissues.


Genetic etiologies of chronic mucocutaneous candidiasis (CMC) disrupt human IL-17A/F–dependent immunity at mucosal surfaces, whereas those of connective tissue disorders (CTDs) often impair the TGF-β–dependent homeostasis of connective tissues. The signaling pathways involved are incompletely understood. We report a three-generation family with an autosomal dominant (AD) combination of CMC and a previously undescribed form of CTD that clinically overlaps with Ehlers-Danlos syndrome (EDS). The patients are heterozygous for a private splice-site variant of MAPK8, the gene encoding c-Jun N-terminal kinase 1 (JNK1), a component of the MAPK signaling pathway. This variant is loss-of-expression and loss-of-function in the patients’ fibroblasts, which display AD JNK1 deficiency by haploinsufficiency. These cells have impaired, but not abolished, responses to IL-17A and IL-17F. Moreover, the development of the patients’ TH17 cells was impaired ex vivo and in vitro, probably due to the involvement of JNK1 in the TGF-β–responsive pathway and further accounting for the patients’ CMC. Consistently, the patients’ fibroblasts displayed impaired JNK1- and c-Jun/ATF-2–dependent induction of key extracellular matrix (ECM) components and regulators, but not of EDS-causing gene products, in response to TGF-β. Furthermore, they displayed a transcriptional pattern in response to TGF-β different from that of fibroblasts from patients with Loeys-Dietz syndrome caused by mutations of TGFBR2 or SMAD3, further accounting for the patients’ complex and unusual CTD phenotype. This experiment of nature indicates that the integrity of the human JNK1-dependent MAPK signaling pathway is essential for IL-17A– and IL-17F–dependent mucocutaneous immunity to Candida and for the TGF-β–dependent homeostasis of connective tissues.


Chronic mucocutaneous candidiasis (CMC) is characterized by recurrent lesions of the skin, nails, oral, and genital mucosae caused by Candida albicans (1). Patients with profound and broad inherited T cell immunodeficiencies present with CMC as one of their many infections (2). Most patients heterozygous for dominant-negative STAT3 mutations (3) or gain-of-function STAT1 mutations (4), and most patients with autosomal recessive (AR) RORC (5) or ZNF341 deficiency (6, 7) have CMC among the infections suffered, the range of which is smaller than for patients with severe T cell deficiencies. Patients with these various forms of syndromic CMC (SCMC) share a paucity of circulating T helper 17 (TH17) cells (513). Patients with AR autoimmune regulator (AIRE) deficiency display not only autoimmunity but also CMC as their only infection due to the production of neutralizing autoantibodies against interleukin-17A (IL-17A) and/or IL-17F (14, 15). Last, isolated forms of CMC (ICMC), in which CMC is the predominant or only clinical manifestation in otherwise healthy individuals, can be due to autosomal dominant (AD) IL-17F deficiency, or inborn errors of the IL-17–responsive pathway, such as AR IL-17RA, IL-17RC, and ACT1 deficiencies (1620). Fibroblasts and keratinocytes derived from these patients display impaired (AD IL-17F deficiency) (16) or abolished (AR IL-17RA, IL-17RC, or ACT1 deficiency) responses to IL-17A and IL-17F (1619).

Patients with inherited ICMC do not, however, display any overt signs of connective tissue disorders (CTDs) as their skin, joints, bones, and blood vessels are unaffected. Conversely, patients with CTDs, such as Ehlers-Danlos syndrome (EDS), Loeys-Dietz syndrome (LDS), and Marfan syndrome (MS), do not suffer from CMC (21). Whereas the genetic basis of hypermobile EDS (hEDS) is unknown (22), the other 13 subtypes of EDS are caused by various inborn errors of genes, many of which encode collagen or collagen-modifying enzymes (e.g., COL1A1, COL1A2, COL3A1, COL5A1, COL5A2, ADAMTS2, and PLOD1) (22, 23). LDS is caused by inborn errors of the transforming growth factor–β (TGF-β) signaling pathway (TGFBR1, TGFBR2, SMAD2, SMAD3, TGFB2, and TGFB3) (24), and MS by inborn errors of FBN1, which encodes fibrillin-1 (25). In these disorders, the homeostasis and integrity of connective tissues are impaired by dysfunctional extracellular matrix (ECM) proteins, the production of which is controlled by TGF-β in fibroblasts (24, 26).


A private heterozygous MAPK8 variant in a kindred with AD CMC and CTD

We studied three patients (P1, P2, and P3) from three generations of a French family with AD CMC and a CTD overlapping with hEDS (Fig. 1A, fig. S1A, table S1, and the “Case reports” section in the Supplementary Materials). We performed whole-exome sequencing (WES) and found no rare nonsynonymous coding variants in any of the known CMC-, EDS-, LDS-, and MS-causing genes, all of which were well covered by WES (table S2). Under a complete penetrance model, we found 18 heterozygous nonsynonymous variants common to the three patients and private to this family, i.e., not previously reported in the 1000 Genomes Project, the Single-Nucleotide Polymorphism Database, the National Heart, Lung, and Blood Institute (NHLBI) GO Exome Sequencing Project, the Exome Aggregation Consortium Genome Aggregation Database, the NHLBI’s TOPMed program (Bravo), or our in-house database of more than 6000 exomes from patients with various infectious diseases (fig. S1B and table S3). The most plausible candidate was a splice-site mutation in the MAPK8 gene, for which the biological distance to six of eight known SCMC- and ICMC-causing genes other than AIRE (IL17F, IL17RA, ACT1, STAT1, STAT3, and RORC) was shortest in the human gene connectome, and the distance to the other two (IL17RC and ZNF341) ranked second shortest (27, 28). The familial segregation of this private mutant MAPK8 allele was consistent with a fully penetrant AD trait (Fig. 1, A and B). This nucleotide substitution (c.311+1G>A), 1 base pair (bp) downstream from exon IV (Fig. 1C), was predicted to affect splicing by altering the donor splice site (29). The c.311+1G>A mutation has a combined annotation-dependent depletion (CADD) score of 26 (30), which is above the mutation significance cutoff (MSC) threshold of 19.034 for MAPK8 (fig. S1C) (31). Moreover, three of four nonsense or frameshift mutations in MAPK8 present in public databases have a minor allele frequency (MAF) of <10−5, whereas the fourth, with a MAF of 0.0000114, has a CADD score below the MSC threshold (fig. S1C). Consistent with these findings, MAPK8 has a gene damage index of 0.32 (32), a neutrality index of 0.06 (33), and a SnIPRE f parameter of 0.329 (within the top 11% of genes within the genome subject to the greatest constraints) (fig. S1D) (34), indicating that this gene is highly conserved in human populations and has evolved under purifying selection. Last, MAPK8 has a probability of loss-of-function intolerance score of 0.98, which is greater than the threshold of 0.9, above which genes are considered to be extremely intolerant to loss-of-function variants (35). The MAPK8 mutation found in this kindred was therefore probably deleterious, with the potential to cause an AD disease.

Fig. 1 Identification of a heterozygous MAPK8 mutation in a kindred with AD CMC and CTD.

(A) Pedigree and segregation of the MAPK8 mutation. The patients, indicated with filled black symbols, are heterozygous for the mutation. “E?” indicates individuals whose genetic status could not be evaluated. (B) Electropherograms of partial sequences of MAPK8 corresponding to the mutation in a healthy control (C) and four members of the kindred (II.1, P1, P2, and P3). (C) Schematic illustration of the genomic locus and of the protein encoded by the MAPK8 gene extracted from the Ensembl database. It has 13 exons (I to XIII), 12 of which are coding exons (II to XIII), encoding four isoforms (JNK1α1, JNK1α2, JNK1β1, and JNK1β2), with alternative usage of exon VII or VIII and alternative splicing of exon XIII. The red arrow indicates the position of the mutation.

A loss-of-expression mutant MAPK8 allele

The MAPK8 gene encodes c-Jun N-terminal kinase 1 (JNK1), one of three members of the JNK family. This protein is a component of the mitogen-activated protein kinase (MAPK) pathway that converts extracellular stimuli into cellular responses (36, 37). JNK1 is phosphorylated by upstream MAPK kinases and, in turn, phosphorylates downstream activator protein-1 (AP-1) transcription factors, including c-Jun and ATF-2 (37). There are two long (JNK1α2 and JNK1β2, 54 kDa) and two short (JNK1α1 and JNK1β1, 46 kDa) isoforms, generated by alternative usage of exon VII or VIII and alternative splicing of exon XIII (Fig. 1C) (38). We amplified a complementary DNA (cDNA) fragment extending from exons III to V from Epstein-Barr virus (EBV)–transformed B cells and simian virus 40 (SV40)–transformed fibroblasts from the patients. In addition to the wild-type (WT) transcript (band 4), we detected four aberrant products (bands 1, 2, 3, and 5) (Fig. 2A). TA cloning and subsequent sequencing identified two aberrantly spliced transcripts: one in which intron IV was retained (band 2) and one in which exon IV was skipped (band 5) (Fig. 2A). Bands 1 and 3 were artifacts of heteroduplex formation (39). We then inserted a genomic fragment containing the WT or mutant intron IV together with the surrounding exons (IV and V) into an exon-trapping vector (Fig. 2B). The WT minigene was normally spliced, whereas the mutant minigene generated two aberrant splicing products: one in which exon IV was skipped and another in which intron IV was retained (Fig. 2B). This assay confirmed the direct impact of the c.311+1G>A mutation on MAPK8 mRNA splicing, with no detectable leakiness. Both aberrant mRNAs were predicted to result in the creation of premature stop codons (Fig. 2C). Consistent with this prediction, the levels of WT MAPK8 mRNA and JNK1 protein in the patients’ cells were about half those in control cells (Fig. 2, D and E). Moreover, no truncated proteins were detected in the patients’ cells (Fig. 2E) or in human embryonic kidney (HEK) 293T cells transfected with the corresponding mutant constructs, with or without the N-terminal Myc tag (Fig. 2F). The three patients were, therefore, heterozygous for a private loss-of-expression MAPK8 allele.

Fig. 2 The mutant MAPK8 allele is loss-of-expression.

(A) MAPK8 mRNA levels in EBV-B cells and SV40-fibroblasts from healthy controls (C1, C2, and C3) and patients (P1, P2, and P3). TA cloning and subsequent sequencing of the five bands generated by amplification from exon III to exon V identified three spliced transcripts: band 1 corresponding to the WT sequence together with intron IV retention and exon IV skipping; band 2 (376 bp) corresponding to intron IV retention; band 3 corresponding to the WT sequence together with exon IV skipping; band 4 (284 bp) corresponding to the WT sequence; band 5 (225 bp) corresponding to exon IV skipping. (B) Schematic diagram of the constructs used for exon trapping. pET01, exon-trapping vector; RSV, Rous sarcoma virus long terminal repeat promoter; pA, polyadenylation; E in black, exon of the pET01 vector; IV and V in blue, MAPK8 exons IV and V; in yellow, MAPK8 intron IV. The red arrow indicates the position of the mutation. Reverse transcription PCR and subsequent sequencing identified three spliced transcripts: band 1 corresponding to intron IV retention and exon IV skipping; band 2 (354 bp) corresponding to the WT sequence; band 3 (295 bp) corresponding to exon IV skipping. (C) Schematic illustration of the mutant proteins. JNK1ES (JNK1 exon skipping) represents exon IV skipping, whereas JNK1IR (JNK1 intron retention) denotes intron IV retention. Both transcripts are predicted to encode proteins of about 10 kDa in size. Red arrows indicate the positions of premature stop codons. (D) mRNA levels for MAPK8 isoforms in EBV-B cells (top) and SV40-fibroblasts (bottom) from healthy controls (C1, C2, and C3) and patients (P1, P2, and P3). Quantitative reverse transcription PCR was performed with primers specific for JNK1α1/JNK1α2 and JNK1β1/JNK1β2 mRNAs. α/β, total mRNA corresponding to JNK1α1, JNK1α2, JNK1β1, and JNK1β2; α, total mRNA corresponding to JNK1α1 and JNK1α2; β, total mRNA corresponding to JNK1β1 and JNK1β2. The values shown are the means ± SEM of three independent experiments. *P < 0.05, **P < 0.01, and ****P < 0.0001, unpaired t tests. (E and F) Immunoblot of JNK1 in EBV-B cells and SV40-fibroblasts from healthy controls (C1, C2, and C3) and patients (P1, P2, and P3) (E), and in HEK293T cells transfected with plasmids encoding four WT JNK1 isoforms (α1, α2, β1, and β2) and two mutants (ES and IR) inserted into the pTRIP-SFFV vector or the pCMV6-AN-Myc-DDK vector (F). Endogenous JNK1 was detected with an anti-JNK1 antibody recognizing the N terminus of JNK1. Myc-tagged JNK1 was detected with an anti-Myc antibody. EV, empty vector. The data shown are representative of three independent experiments (A, B, E, and F).

Impaired IL-17A/F signaling in patients’ fibroblasts

Human IL-17A, IL-17F, and IL-17A/F (referred to collectively as IL-17A/F) can activate JNK1 after binding to IL-17RA/IL-17RC, which is mostly expressed in various nonhematopoietic cells, thereby inducing the production of pro-inflammatory cytokines, chemokines, and antimicrobial peptides (40, 41). Upon stimulation with IL-17A/F, SV40-fibroblasts from the patients produced abnormally small amounts of growth-regulated oncogene-α (GRO-α) and IL-6, whereas SV40-fibroblasts from an IL-17RA–deficient patient did not respond at all (Fig. 3A). Similar results were obtained with primary fibroblasts (fig. S2A). The patients’ cells had subnormal-to-normal responses to tumor necrosis factor–α (TNF-α) and IL-1β (Fig. 3B and fig. S2B). Moreover, the activation of AP-1 (c-Jun/ATF-2), unlike that of extracellular signal–regulated kinase 1/2 (ERK1/2), p38, and nuclear factor κB (NF-κB), was impaired in the patients’ SV40-fibroblasts after stimulation with IL-17A, as shown by Western blotting (fig. S2C). By contrast, AP-1 was normally activated by TNF-α and IL-1β (fig. S2D). Fibroblasts and leukocytes from the patients also responded normally to lymphotoxin α1β2 (IL-8 production) and Toll-like receptor agonists (IL-6 and IL-8 production), respectively (fig. S2, E to G). Peripheral blood mononuclear cells (PBMCs) responded normally to IL-2 in combination with IL-17E (IL-5 production) (fig. S2H). Lentiviral transduction of the patients’ SV40-fibroblasts with cDNAs encoding WT JNK1 isoforms, JNK1α1 and JNK1β1 in particular, but not with any of the mutant isoforms, restored the response to IL-17A (Fig. 3C and fig. S2I). This finding is consistent with the predominant protein expression of JNK1α1 and JNK1β1 in control SV40-fibroblasts (Fig. 2E). Moreover, the induction of GRO-α and IL-6 in control SV40-fibroblasts was not affected by the overexpression of any mutant JNK1 isoform, suggesting that the mutant allele is not dominant negative (Fig. 3C and fig. S2I). This is consistent with the purifying selection exerted on the MAPK8 locus (fig. S1D) (34). By contrast, the RNA interference (RNAi)–mediated knockdown of MAPK8 impaired the response to IL-17A in control fibroblasts (Fig. 3D and fig. S2, J and K). Last, we performed RNA sequencing (RNA-Seq) to delineate the range of IL-17A–responsive genes in primary fibroblasts. The number of up-regulated or down-regulated genes in response to IL-17A was much lower in the patients (fig. S2L). Several IL-17A/F target genes, including CXCL1, CXCL2, IL6, IL8, C3, and ICAM1, were less induced in the patients’ cells (fig. S2M). About 60% of IL-17RA/IL-17RC–dependent genes were JNK1 dependent (fig. S2N). Collectively, these findings indicate that heterozygosity for the private MAPK8 c.311+1G>A loss-of-expression variant underlies a distinctive AD cellular phenotype, with impaired responses to IL-17A/F in fibroblasts, by haploinsufficiency. Moreover, impaired cellular responses to IL-17A/F in fibroblasts, and possibly in other cells, contribute to CMC (42, 43).

Fig. 3 The MAPK8 variant impairs fibroblast responses to IL-17A/F.

(A) Production of GRO-α (top) and IL-6 (bottom) by SV40-fibroblasts from healthy controls (C1 and C2), patients (P2 and P3), and an IL-17RA–deficient (IL17RA−/−) patient (16) stimulated with IL-17A, IL-17F, or IL-17A/F (10, 100, or 1000 ng/ml) for 24 hours. (B) Production of GRO-α (top) and IL-6 (bottom) by SV40-fibroblasts from healthy controls (C1 and C2), patients (P2 and P3), and a NEMO-deficient (NEMO−/−) patient (92) stimulated with TNF-α (20 ng/ml) or IL-1β (10 ng/ml) for 24 hours. (C) Production of GRO-α (top) and IL-6 (bottom) by SV40-fibroblasts from healthy controls (C1 and C2) and patients (P2 and P3) transfected with empty vector (EV) or plasmids encoding WT JNK1α1 (α1), JNK1α2 (α2), JNK1β1 (β1), JNK1β2 (β2), all four isoforms (α1/α2/β1/β2), JNK1ES (ES), or JNK1IR (IR) in the presence of IL-17A (100 ng/ml) for 24 hours. (D) Production of GRO-α (left) and IL-6 (right) by primary fibroblasts from healthy controls (C1, C2, and C3) transfected with control siRNA (50 nM) or MAPK8 siRNA (50 nM) for 24 hours and then stimulated with IL-17A (100 ng/ml) for an additional 24 hours. The values shown are the means ± SEM of three independent experiments (A to D). *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001, unpaired t tests (A to D).

Low proportions of ex vivo or in vitro differentiated TH17 cells

Given that mouse JNK1 is important for T cell activation and differentiation (4446), and that human TGF-β activates JNK1 (47) and is essential for TH17 differentiation in vitro (4850), we also investigated the development and function of T cells in the patients, testing the hypothesis that impaired TH17 development in the patients might also contribute to their CMC. The frequencies of naïve and CD45RA+ effector memory CD4+ and CD8+ T cells in the patients were slightly higher, whereas those of central and effector memory CD4+ and CD8+ T cells were correspondingly slightly lower than those in healthy controls (Fig. 4A). The patients had higher proportions of TH1 cells and lower proportions of TH17 cells than controls but normal proportions of the TH2, TH1*, TFH (T follicular helper), and (Treg) (T regulatory) subsets among circulating CD4+ T cells, as shown by flow cytometry (Fig. 4B) (51). Normal amounts of IL-17A and IL-22 were secreted by whole blood stimulated with phorbol 12-myristate 13-acetate (PMA) plus ionomycin (Fig. 4C). Ex vivo memory CD4+ T cells also expressed IL-17A and IL-17F, albeit in the lower part of the control range, and interferon-γ (IFN-γ) after stimulation with T cell activation and expansion (TAE) beads (anti-CD2/CD3/CD28 monoclonal antibody–conjugated beads) and PMA plus ionomycin (Fig. 4D). The patients’ naïve CD4+ T cells produced less IL-17A and IL-17F than control cells when cultured under TH17-polarizing conditions (Fig. 4, E and F). This difference was more pronounced when memory CD4+ T cells were tested under the same conditions (Fig. 4G). Last, the percentages of transitional, naïve, and memory B cells and of class-switched memory B cells were normal in these patients (fig. S3, A and B). The abilities of naïve and memory B cells to differentiate into antibody-secreting cells were also intact (fig. S3, C and D). Overall, the ability of T cells to produce IL-17A and IL-17F was 50% lower (ex vivo) and 75% lower (in vitro) in patients heterozygous for the MAPK8 mutation. The ex vivo development of Treg cells was largely unaffected, consistent with the absence of overt autoimmunity in the patients. The CMC in these patients is, thus, a combined consequence of lower proportions of TH17 cells and impaired cellular responses to IL-17A/F. Both human IL-17A/F– and IL-17RA/IL-17RC–dependent mucocutaneous immunity to C. albicans are, therefore, dependent on JNK1.

Fig. 4 Compromised T cell differentiation in the patients.

(A) Percentage of total, naïve (CCR7+CD45RA+), central memory (CM; CCR7+CD45RA), effector memory (EM; CCR7CD45RA), or CD45RA+ effector memory (EMRA; CCR7CD45RA+) CD4+ and CD8+ T cells from healthy controls (n = 40) and patients (P2 and P3). (B) Frequency of TH1 (CXCR5CXCR3+CCR6), TH2 (CXCR5CXCR3CCR6CCR4+), TH17 (CXCR5CXCR3CCR6+CCR4+), TH1* (CXCR5CXCR3+CCR6+CCR4+), TFH (CXCR5+), and Treg (CD25+FOXP3+) subsets among CD4+ T cells from healthy controls (TH1, TH2, TH17, TH1*, and TFH, n = 34; Treg, n = 17) and patients (P2 and P3). (C) Production of IL-17A and IL-22 by whole blood from healthy controls (n = 33) and patients (P2 and P3) after stimulation with PMA plus ionomycin for 24 hours. (D) Percentage of IL-17A+, IL-17F+, and IFN-γ+ cells among memory CD4+ T cells from healthy controls (n = 36) and patients (P2 and P3) activated by TAE beads or PMA plus ionomycin (P/I) for 12 hours. (E) Cytokine production by naïve CD4+ T cells from healthy controls (n = 8) and patients (P2 and P3) cultured under TH0-, TH17-, or TH1-polarizing conditions. (F and G) Frequency of IL-17A+ and IFN-γ+ cells among naïve (F) and memory (G) CD4+ T cells from healthy controls (n = 10) and patients (P2 and P3) cultured under TH0-, TH17-, or TH1-polarizing conditions. C, healthy controls; P, P2 and P3. Horizontal bars represent median values (A to G). *P < 0.05 and **P < 0.01, two-tailed Mann-Whitney tests (A to G).

Normal ECM organization but poor migratory capabilities of patients’ fibroblasts

We subsequently investigated the pathogenesis of the complex CTD phenotype of the patients. Previous studies have proposed an in vitro fibroblast phenotype common to most patients with EDS but apparently not observed in other inherited CTDs (5255). This phenotype is characterized by generalized fibronectin-ECM (FN-ECM) disarray, low levels of expression of the canonical integrin receptor α5β1, and the recruitment of αvβ3 integrin (52, 53, 56). EDS fibroblasts also seem to display little or no type III collagen deposition in the ECM (COLLIII-ECM) and a variable disorganization of type V collagen (COLLV-ECM) (52, 53, 56). A specific myofibroblast-like phenotype of hEDS has also been proposed, on the basis of the organization of α-smooth muscle actin (α-SMA), cadherin-11 (CAD-11) expression, and enhanced cell migration (56). Unlike cells from patients with EDS, the primary fibroblasts of P2 displayed no FN-ECM disarray, and α5β1 integrin was organized as in control fibroblasts (Fig. 5A). Despite the low levels of COLLIII-ECM and a barely detectable organization of COLLV-ECM, P2’s fibroblasts expressed the canonical collagen receptor, α2β1 integrin, normally, unlike EDS cells (Fig. 5A). The myofibroblast-specific markers α-SMA and CAD-11 were absent from the cells of P2, whereas they were present on hEDS fibroblasts (Fig. 5A). Consistent with this finding, the fibroblasts of P2 did not have the enhanced migratory capability reported for some hEDS fibroblasts, as shown by in vitro scratch and Transwell assays (Fig. 5, B and C). Instead, the fibroblasts of P2, like some classic EDS (cEDS) cells, migrated poorly (Fig. 5, B and C), probably accounting for the poor wound healing observed in the patients (see the “Case reports” section in the Supplementary Materials). Overall, these data suggest that, although the clinical presentation in these patients overlaps with EDS, and despite the 2017 EDS diagnostic criteria for hEDS being met (22), the in vitro fibroblast phenotype of these patients is apparently different from that proposed for EDS, in general, and for hEDS, in particular (52, 53, 56).

Fig. 5 Impaired response to TGF-β in the patients’ fibroblasts.

(A) Immunofluorescence of FN; type V collagen (COLLV); type III collagen (COLLIII); α2β1, α5β1, and αvβ3 integrins; α-SMA; and CAD-11 in primary fibroblasts from a healthy control (C), P2, a patient with hEDS (56), and a patient with cEDS (93). Scale bar, 10 μm. (B) In vitro scratch assay with primary fibroblasts from a healthy control (C), P2, a patient with hEDS (56), and a patient with cEDS (93). Images were captured at 0 and 48 hours after scratching. Scale bar, 100 μm. (C) Transwell assay with primary fibroblasts from a healthy control (C), P2, a patient with hEDS (56), and a patient with cEDS (93). (D) mRNA induction in primary fibroblasts from healthy controls (C1 and C2) and patients (P2 and P3) stimulated with TGF-β (10 ng/ml) for the indicated times. (E) Top 10 up-regulated or down-regulated genes in terms of absolute fold change, in primary fibroblasts from healthy controls (C1 and C2) stimulated with TGF-β (10 ng/ml) for 2, 6, and 24 hours, with a greater than 1.5-fold change relative to patients (P2 and P3) at each time point. (F and G) Expression of JNK1 protein (F) and production of FN (top) and IL-11 (bottom) (G) by primary fibroblasts from healthy controls (C1 and C2) transfected with control siRNA (50 nM) or MAPK8 siRNA (50 nM) for 48 hours and then stimulated with TGF-β (10 ng/ml) for an additional 24 hours. NS, nonstimulated conditions. The values shown are the means ± SEM of two (C) or three (D and G) independent experiments. *P < 0.05, ***P < 0.001, and ****P < 0.0001, unpaired t tests (D and G).

Impaired TGF-β signaling in patients’ fibroblasts

We tested the hypothesis that the patients’ CTD resulted from dysfunctional TGF-β signaling because this pathway controls the expression of key genes involved in the development and maintenance of the ECM (24). Upon TGF-β stimulation, the patients’ SV40-fibroblasts displayed impaired AP-1 (c-Jun/ATF-2) activation, whereas ERK1/2, p38, and SMAD2/3 were normally activated, as shown by Western blotting (fig. S4A). Previous reports have suggested that TGF-β induces the expression of FN in a JNK1-dependent manner (57, 58). Consistent with these findings, the induction of FN production by TGF-β was impaired at both the mRNA and protein levels in the patients’ fibroblasts (Fig. 5D and fig. S4, B and C). The patients did not display spondylometaphyseal dysplasia, which can be caused by heterozygous FN1 mutations (59), probably because their baseline FN-ECM organization levels were normal (Fig. 5A). By contrast, various SMAD2/3-dependent TGF-β target genes (58, 60), such as COL1A1, COL1A2, COL3A1, COL5A1, and COL5A2, encoding key components of the ECM and mutated in patients with cEDS and other forms of EDS (22), were normally induced by TGF-β in the patients’ cells (Fig. 5D and fig. S4, B and C). Last, we performed a transcriptomic analysis of the cellular response to TGF-β in primary fibroblasts. The genome-wide transcriptional response to TGF-β was impaired in the patients’ cells (fig. S4D). A number of TGF-β–responsive genes, including ELN, EDN1, IL11, and COMP, were not induced in the patients’ cells (Fig. 5E and fig. S4E). Consistently, their induction in control fibroblasts stimulated with TGF-β was impaired by the RNAi-mediated knockdown of MAPK8 (Fig. 5, F and G, and fig. S4F). These findings are consistent with previous reports of the presence of AP-1–binding motifs in the regulatory regions of COMP and ELN (61, 62) or of the AP-1-dependent induction of EDN1 and IL11 by TGF-β (63, 64). Mutations in these genes (59, 6568) or in those encoding the corresponding receptors (69, 70) have already been reported in patients with various CTDs other than EDS, LDS, and MS (table S4). The study of the patients’ fibroblasts thus delineated the transcriptomic impact of impaired JNK1-dependent, SMAD2/3-independent TGF-β signaling. Moreover, fibroblasts from patients with LDS, heterozygous for mutations in TGFBR2 or SMAD3, also showed impaired responses to TGF-β (fig. S4D), consistent with previous studies showing these mutations to be loss-of-function in vitro (7173). However, their impact differed from that of JNK1 haploinsufficiency, because about 40% of JNK1-dependent genes were TGFBR2/SMAD3 independent (fig. S4G). This is consistent with the clinical differences observed between our patient’s particular CTD (displaying some overlap with hEDS) and LDS. In addition, about 30% of TGFBR2-dependent genes were SMAD3 independent (fig. S4H), potentially accounting for some of the phenotypic differences between LDS patients with TGFBR2 and SMAD3 mutations. Our findings provide a molecular and cellular basis for the complex new form of CTD displayed by the patients, with an impairment of the TGF-β–dependent induction of key ECM components and regulators different from that of patients with another CTD, LDS, who are heterozygous for TGFBR2 or SMAD3 mutations.


We have found a heterozygous loss-of-expression and loss-of-function mutation of MAPK8 in a three-generation multiplex kindred with a rare combination of classic CMC and a previously undescribed form of CTD (Fig. 6). Human JNK1 haploinsufficiency impairs IL-17A/F immunity in two ways, by reducing the responses of fibroblasts to IL-17RA/IL-17RC ligation and by compromising the TGF-β–dependent development of TH17 cells, accounting for the impaired mucocutaneous immunity to C. albicans and subsequent development of CMC in these patients. These findings indicate that IL-17RA/IL-17RC–dependent protective mucocutaneous immunity to C. albicans is JNK1 dependent. We previously described CMC patients with biallelic mutations of ACT1 (19). The findings reported here identify JNK1 as a key component of this antifungal pathway acting downstream from ACT1. They also indicate that JNK1 haploinsufficiency has an impact on the development of TH17 cells, probably due to the involvement of JNK1 in the TGF-β pathway.

Fig. 6 JNK1-dependent IL-17 and TGF-β signaling.

The binding of IL-17A/F to the IL-17RA/IL-17RC receptor facilitates the recruitment of ACT1 to the receptor, which mediates the activation of JNK1, ERK, p38, and NF-κB (p65/p50) signaling, leading to the production of pro-inflammatory cytokines and chemokines (e.g., CXCL1 and IL6). Similarly, TGF-β binds to its receptor (TGFBR1/TGFBR2), leading to the activation of JNK1, ERK, p38, and SMAD (SMAD2/3/4) signaling. This pathway ultimately results in the production of ECM proteins and regulators (e.g., FN1 and IL11). The mutation (yellow star) in MAPK8 encoding JNK1 impairs the JNK1-dependent activation of downstream AP-1 (c-Jun/ATF-2), thereby reducing the JNK1-dependent cellular responses to IL-17 and TGF-β.

Our data also suggest that JNK1 haploinsufficiency impairs the c-Jun/ATF-2–dependent, and SMAD2/3-independent, TGF-β–responsive pathway in fibroblasts, a cellular phenotype that probably accounts for the patients’ complex and unusual CTD phenotype. The induction of collagen genes mutated in cEDS and other forms of EDS, such as COL1A1 and COL5A1, was intact, whereas that of other ECM proteins, such as COMP and ELN, mutated in patients with other types of CTD (65, 66), was impaired. The impaired induction of genes encoding ECM regulators, such as EDN1 and IL11, may also contribute to the patients’ CTD phenotype. It is also relevant that the impact of heterozygous mutations of MAPK8 differed from that of the TGFBR2 or SMAD3 of patients with LDS, in terms of the transcriptional response to TGF-β. Haploinsufficiency for JNK1 probably defines a previously undescribed CTD entity encompassing various clinical manifestations, some of which overlap with EDS, but not LDS.

Cellular responses to cytokines other than IL-17A/F and TGF-β were apparently intact in cells from the patients. JNK1-deficient mice have defects of innate and adaptive immunity to various infections (7476), but their connective tissues have not been studied. MAPK8-heterozygous mice have rarely been studied and seem to be normal (77). In conclusion, the integrity of the human JNK1 pathway is essential for IL-17A/F–dependent mucocutaneous immunity to Candida and for the TGF-β–dependent homeostasis of connective tissues.


Study design

We studied three patients from a kindred suffering from CMC and CTD. We analyzed this kindred by WES and found that the patients were heterozygous for a private splice-site mutation in MAPK8, the gene encoding JNK1. We evaluated the impact of this mutation in an overexpression system and in the patients’ cells. We assessed the cellular responses to IL-17A/F and TGF-β of the patients’ fibroblasts as well as the development and the differentiation properties of the patients’ T and B cells.

Human subjects

The patients (P1, P2, and P3) were followed in their country of residence, France. Another family member (II.1) also participated to the genetic study. Informed consent was obtained from each patient, in accordance with local regulations and a protocol for research on human subjects approved by the institutional review board (IRB) of Institut National de la Santé et de la Recherche Médicale (INSERM). Experiments were performed on samples from human subjects in the United States, France, Italy, and Australia, in accordance with local regulations and with the approval of the IRB of The Rockefeller University, the IRB of INSERM, the local ethical committee of Brescia, and the Sydney South West Area Health Service, respectively.

Whole-exome sequencing

Genomic DNA was extracted from whole blood and sheared with an S2 Focused-ultrasonicator (Covaris). An adaptor-ligated library was prepared with the TruSeq DNA Sample Prep Kit (Illumina). Exome capture was performed with the SureSelect Human All Exon V5 Kit (Agilent Technologies). Paired-end sequencing was performed on the HiSeq 2500 System (Illumina) generating 100-base reads. The sequences were aligned with the GRCh37 build of the human genome reference sequence, with the Burrows-Wheeler Aligner (78). Downstream processing and variant calling were performed with the Genome Analysis Toolkit (79), SAMtools (80), and Picard tools ( All variants were annotated with in-house annotation software.

Cell culture and transfection

Primary fibroblasts were obtained from skin biopsy specimens and cultured in Dulbecco’s modified Eagle’s medium (DMEM) (Gibco) supplemented with 10% fetal bovine serum (FBS) (Gibco). PBMCs were isolated from whole blood by density gradient centrifugation on Ficoll-Paque PLUS (GE Healthcare Life Sciences). Immortalized SV40-transformed fibroblasts (SV40-fibroblasts) and EBV-transformed B (EBV-B) cells were generated as previously described (81). HEK293T (American Type Culture Collection) and GP2-293 retroviral packaging cells (Clontech) were maintained in DMEM containing 10% FBS. HEK293T and GP2-293 cells were transiently transfected with the aid of X-tremeGENE 9 DNA Transfection Reagent (Roche). Primary fibroblasts were transfected with small interfering RNA (siRNA) in the presence of Lipofectamine RNAiMAX Transfection Reagent (Thermo Fisher Scientific), in accordance with the manufacturer’s instructions.

Molecular genetics

Genomic DNA was isolated from primary fibroblasts or EBV-B cells with the QIAamp DNA Mini Kit (QIAGEN). A fragment encompassing exon IV and intron IV of MAPK8 was amplified by polymerase chain reaction (PCR) with specific primers (table S5). The PCR products were analyzed by electrophoresis in 1% agarose gels and sequenced with the BigDye Terminator Cycle Sequencing Kit (Applied Biosystems). Sequencing products were purified by gel filtration on Sephadex G-50 Superfine columns (GE Healthcare Life Sciences), and sequences were analyzed using the ABI 3730 DNA Analyzer (Applied Biosystems).

Plasmids and siRNAs

JNK1α1 and JNK1α2 were amplified from pCDNA3 FLAG JNK1α1 (Addgene) and pCDNA3 FLAG JNK1α2 (Addgene), respectively. JNK1β1 and JNK1β2 were amplified from the cDNA derived from SV40-fibroblasts. The full-length WT isoforms and truncated mutants were inserted into pTRIP-SFFV (82) and the pCMV6-AN-Myc-DDK–tagged vector (OriGene), respectively. TA cloning and exon trapping were performed with the pCR4-TOPO vector (Thermo Fisher Scientific) and the pET01 vector (MoBiTec GmbH), respectively, according to the manufacturer’s instructions. Control siRNA (D-001810-10) and MAPK8 siRNA (L-003514-00) were obtained from Dharmacon.

Cell stimulation and cytokine production

SV40-fibroblasts and primary fibroblasts were plated on 24-well plates at a density of 6 × 104 cells per well in 0.5 ml of DMEM supplemented with 10% FBS. After 24 hours, cells were left unstimulated or were stimulated with recombinant human IL-17A (317-ILB; R&D Systems), recombinant human IL-17F (1335-IL; R&D Systems), recombinant human IL-17A/F (5194-IL; R&D Systems), recombinant human TNF-α (210-TA; R&D Systems), recombinant human IL-1β (201-LB; R&D Systems), recombinant human lymphotoxin α1/β2 (8884-LY; R&D Systems), lipoteichoic acid from Staphylococcus aureus (LTA-SA) (tlrl-slta; InvivoGen), Pam3CSK4 (tlrl-pms; InvivoGen), fibroblast-stimulating lipopeptide-1 (FSL-1) (tlrl-fsl; InvivoGen), Pam2CSK4 (tlrl-pm2s-1; InvivoGen), and lipopolysaccharide (LPS) (L9764; Sigma-Aldrich) for a further 24 hours. Enzyme-linked immunosorbent assay (ELISA) kits were used to determine the levels of GRO-α (DY275; R&D Systems), IL-6 (88-7066; Invitrogen), and IL-8 (M9318; Sanquin) in the supernatants. SV40-fibroblasts and primary fibroblasts were cultured in DMEM supplemented with 1% FBS for 24 hours and then stimulated with recombinant human TGF-β1 (240-B-002; R&D Systems) for various time periods. Protein levels were determined by ELISA for FN (DY1918-05; R&D Systems), procollagen I (α1) (DY6220-05; R&D Systems), and IL-11 (DY218; R&D Systems). Whole blood was stimulated with IL-1β, Pam3CSK4, heat-killed Staphylococcus aureus (tlrl-hksa; InvivoGen), FSL-1, Pam2CSK4, LPS, R848 (tlrl-r848; InvivoGen), and PMA (P1585; Sigma-Aldrich) plus ionomycin (I3909; Sigma-Aldrich) for 24 hours, and IL-6 production was measured by ELISA. PBMCs were cultured in X-VIVO 15 (Lonza) containing 5% human serum AB (Lonza) and recombinant human thymic stromal lymphopoietin (100 ng/ml) (1398-TS/CF; R&D Systems) for 24 hours. Cells were washed and plated on 48-well plates, at a density of 4 × 106 cells per well, in 0.5 ml of X-VIVO 15 supplemented with 5% human serum AB in the presence of recombinant human IL-2 (10 ng/ml) (202-IL; R&D Systems) and recombinant human IL-17E (10 ng/ml) (1258-IL; R&D Systems). After 72 hours, the amount of IL-5 present in each well was determined with an ELISA kit (DY205; R&D Systems).

Reverse transcription and PCR

Total RNA was extracted with the RNeasy Mini Kit (QIAGEN), according to the manufacturer’s instructions. Reverse transcription was carried out with the SuperScript III First-Strand Synthesis System (Invitrogen). Conventional PCR was performed with the Choice-Taq Blue DNA Polymerase (Denville Scientific), and the amplicons were analyzed by electrophoresis in 2% agarose gels. Quantitative PCR was performed with Fast SYBR Green Master Mix (Applied Biosystems) in the 7500 Fast Real-Time PCR System (Applied Biosystems). The primer pairs used for conventional and quantitative PCR are listed in table S5.

Western blotting

Whole-cell lysates were prepared in radioimmunoprecipitation assay buffer [50 mM tris-HCl (pH 7.5), 150 mM NaCl, 1% NP-40, 0.5% sodium deoxycholate, and 0.1% SDS] supplemented with cOmplete Protease Inhibitor Cocktail (Roche). Proteins were separated by electrophoresis in either 10% Criterion XT Bis-Tris Protein Gels (Bio-Rad) or 4 to 20% Mini-PROTEAN TGX Precast Protein Gels (Bio-Rad), and the resulting bands were transferred onto Immobilon-P PVDF Membrane (Millipore). All blots were incubated overnight with primary antibodies and developed with the Pierce ECL Western Blotting Substrate (Thermo Fisher Scientific). The antibodies used in this study included antibodies (from Cell Signaling Technology) against JNK1 (3708), pc-Jun (2361), c-Jun (9165), pATF-2 (9221), ATF-2 (9226), pIκBα (9246), pp65 (3033), pp38 (9211), p38 (9212), pERK1/2 (4370), ERK1/2 (4695), pSMAD2 (3101), SMAD2 (5339), pSMAD3 (9520), SMAD3 (9523), SMAD4 (38454), and Myc (2040), as well as IκBα (610690; BD Biosciences), p65 (sc-372; Santa Cruz Biotechnology), and β-actin (AM1829B; Abgent), and the following secondary antibodies: Amersham ECL Mouse Immunoglobulin G (IgG), horseradish peroxidase (HRP)–linked whole antibody (from sheep) (NA931; GE Healthcare Life Sciences), and Amersham ECL Rabbit IgG, HRP-linked whole antibody (from donkey) (NA934; GE Healthcare Life Sciences).

Ex vivo T cell activation

PBMCs were cultured in 48-well plates, at a density of 3 × 106 cells per milliliter, in RPMI 1640 medium (Gibco) containing 10% FBS with TAE beads (130-091-441; Miltenyi Biotec) or PMA plus ionomycin in the presence of a protein transport inhibitor (GolgiPlug; BD Biosciences). After 12 hours, the cells were collected and their expression of the indicated cytokines was assessed by flow cytometry, as previously described (17).

In vitro T cell differentiation

Naïve and memory CD4+ T cells were isolated and cultured under polarizing conditions, as previously described (6, 83). Briefly, cells were cultured with TAE beads alone (TH0) or under TH1 [IL-12 (20 ng/ml; R&D Systems)] or TH17 [TGF-β1 (2.5 ng/ml; PeproTech), IL-1β (20 ng/ml; PeproTech), IL-6 (50 ng/ml; PeproTech), IL-21 (50 ng/ml; PeproTech), and IL-23 (20 ng/ml; eBioscience)] polarizing conditions. After 5 days, the supernatants were harvested and the cells were restimulated with PMA/ionomycin for 6 hours. The levels of specific cytokines were determined by intracellular staining and flow cytometry. The secretion of the indicated cytokines was determined with a cytometric bead array (BD Biosciences).

In vitro B cell differentiation

Naïve and memory B cells were sorted and cultured in the presence of CD40L (200 ng/ml; R&D Systems), with or without IL-21 (50 ng/ml; PeproTech) for 7 days, as previously described (83). The production of IgA, IgG, and IgM was assessed by Ig heavy chain–specific ELISA (83).

Flow cytometry

Cells were surface-labeled with CD4-APC-Vio770 anti-human CD4 (clone M-T321; Miltenyi Biotec), Brilliant Violet 421 anti-human CD197 (CCR7) (clone G043H7; BioLegend), phycoerythrin (PE)–CF594 anti-human CD45RA (clone HI100; BD Biosciences), and LIVE/DEAD Fixable Aqua Dead Cell Stain Kit (L34957; Thermo Fisher Scientific). Intracellular staining was performed with the Fixation/Permeabilization Solution Kit (BD Biosciences) and antibodies including Alexa Fluor 488 anti–IL-17A (clone eBio64DEC17; eBioscience), PE anti–IL-17F (clone SHLR17; eBioscience), and Alexa Fluor 700 anti–IFN-γ (clone 4S.B3; eBioscience). Samples were analyzed with a Gallios flow cytometer (Beckman Coulter) and FlowJo software.

Immunofluorescence microscopy

Primary fibroblasts were fixed with ice-cold methanol and incubated with antibodies against FN (Sigma-Aldrich), type III collagen (Chemicon), and type V collagen (LifeSpan BioSciences) at a dilution of 1:100, and with anti–α-SMA antibody (A2547; Sigma-Aldrich) at a concentration of 2 μg/ml, as previously described (52, 56, 84). For analysis of the α2β1, α5β1, and αvβ3 integrins, cells were fixed with 3% paraformaldehyde (PFA)/60 mM sucrose and permeabilized with 0.5% Triton X-100, as previously reported (84). In particular, cells were incubated with anti-α5β1 (MAB1969; Chemicon), anti-αvβ3 (MAB1976; Chemicon), and anti-α2β1 (MAB1998; Chemicon) integrin antibodies at a concentration of 4 μg/ml for 1 hour. CAD-11 levels were investigated by fixing cells by incubation with 4% PFA/10 mM sucrose for 10 min, permeabilizing them by incubation with 0.1% Triton X-100 for 10 min, blocking them with by incubation with 2% bovine serum albumin in phosphate-buffered saline (PBS) for 1 hour, and then incubating them with anti-CDH11/cadherin OB antibody (Thermo Fisher Scientific) at a concentration of 2 μg/ml for 3 hours, as previously described (56). The cells were washed and then stained with Alexa Fluor 488 anti-rabbit and Alexa Fluor 594 anti-mouse antibodies (Thermo Fisher Scientific) or with rhodamine-conjugated anti-goat IgG antibody (Chemicon) for 1 hour. Immunofluorescence signals were acquired with a black-and-white charge-coupled device TV camera (SensiCam; PCO Computer Optics GmbH), mounted on a Zeiss Axiovert fluorescence microscope, and digitized with Image-Pro Plus software (Media Cybernetics).

In vitro scratch assay

Primary fibroblasts were plated on 35-mm petri dishes at a density of 3 × 104 cells per dish and grown to confluence. The cell monolayers were wounded with a rubber policeman to generate an acellular area, and dishes were marked to ensure the recording of the correct area. The monolayers were washed with PBS, rinsed in DMEM and 10% FBS, and photographed with an inverted microscope at 0 and 48 hours after scratching.

Transwell assay

Cell migration was evaluated in a Transwell assay with an 8-μm-pore filter (Corning Costar). Primary fibroblasts (5 × 104 cells) were resuspended in DMEM without FBS, placed in the upper chamber, and allowed to migrate for 6 hours through the polycarbonate membrane into the bottom well, which was filled with DMEM containing 10% FBS. The cells that did not migrate were removed from the upper surface with a cotton swab. The cells that had migrated were collected in the bottom chamber. They were fixed in methanol, stained with the Diff-Quik Staining Kit (Medion Diagnostic GmbH), and quantified in 10 nonoverlapping fields of 1 mm2 with a light microscope.

Microarray and RNA-Seq analyses

Total RNA was extracted with the RNeasy Plus Micro Kit (QIAGEN), according to the manufacturer’s instructions. Microarray analysis was performed with the GeneChip Human Gene 2.0 ST Array (Thermo Fisher Scientific). The raw expression data were normalized in R with the robust multi-array average method (85) and the affy R package (86), and processed as previously described (87). RNA-Seq analysis was performed with TruSeq Stranded mRNA (Illumina) and standard poly(A)-based methods for library preparation. Paired-end sequencing with a read length of 150 bp and ~19 million reads per sample was carried out with a HiSeq 4000 system (Illumina). Raw reads were aligned to the human genome assembly (hg38) with STAR aligner (88). The number of reads mapping to each gene feature was determined with HTSeq (89). Differential expression was analyzed with an in-house script in R with DESeq2 (90) and ComplexHeatmap (91). In brief, fold changes in expression between nonstimulated and stimulated conditions were calculated for each individual and time point separately, and genes were further filtered based on a minimal 1.5-fold change in expression (up-regulation or down-regulation). The residual responses of the patients were calculated on the basis of the number of responsive genes passing the above filter in both healthy controls [number of responsive genes in a subject/total number of responsive genes in healthy controls) × 100].

Statistical analysis

Unpaired t tests and two-tailed Mann-Whitney tests were used for comparisons of two groups. P < 0.05 was considered statistically significant in all tests performed with Prism software (GraphPad).


Case reports

Fig. S1. Identification of a private MAPK8 variant in the patients.

Fig. S2. Impaired IL-17A/F signaling in the patients’ fibroblasts.

Fig. S3. Normal B cell differentiation in the patients.

Fig. S4. Impaired TGF-β signaling in the patients’ fibroblasts.

Table S1. Immunological parameters of P1, P2, and P3.

Table S2. Careful WES analysis of rare (MAF < 1%) nonsynonymous coding variants in the known CMC-, EDS-, LDS-, and MS-causing genes.

Table S3. Heterozygous nonsynonymous variants common to P1, P2, and P3.

Table S4. Clinical presentations of disorders caused by mutations in JNK1-dependent TGF-β target genes or in genes encoding the corresponding receptors.

Table S5. Primers used for Sanger sequencing, reverse transcription PCR, and exon trapping.

Table S6. Raw data file (Excel spreadsheet).

References (94, 95)


Acknowledgments: We warmly thank the patients and their family for participating in the study. We also thank all the members of the Laboratory of Human Genetics of Infectious Diseases for fruitful discussions and the members of the genomics core facility at Sidra Medicine for their contributions to Illumina library preparation and RNA-Seq. Funding: This work was funded by the French National Research Agency (ANR) under the “Investments for the future” program (ANR-10-IAHU-01), the HGDIFD project (ANR-14-CE15-0006-01), the EURO-CMC project (ANR-14-RARE-0005-02), the Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence (ANR-10-LABX-62-IBEID), the INSERM, Paris Descartes University, the Cross-lab project of Imagine Institute, The Rockefeller University, Sidra Medicine, the Jeffrey Modell Foundation Translational Research Program, the Jeffrey Modell Centers Network, the St. Giles Foundation, the National Center for Research Resources of the NIH, the National Center for Advancing Translational Sciences of the NIH (UL1TR001866), and the National Institute of Allergy and Infectious Diseases of the NIH (R01AI127564). C.S.M. was supported by an Early-Mid Career Research Fellowship from the Office of Health and Medical Research of the New South Wales State Government. T.F. and L.G. were supported by the Ministry of Health of the Czech Republic (16-34414A). D.S. and F.M. were supported by the Research Foundation Flanders (FWO) of Belgium. S.G.T. was supported by the National Health and Medical Research Council of Australia. A.P. was supported by an AP-HP transversal research contract. Author contributions: J.L., M.R., C.S.M., G.R., S.C., L.G., R.L., V.B., K.P., D.T.A., M.M., and M. Chrabieh performed the experiments and analyzed the data. T.H., S. Bougarn, L.S., S. Boughorbel, A.G., F.R., and B. Bigio conducted WES, microarray, RNA-Seq, and computational analyses. E.C., M.M., and S. Boucherit provided clinical samples and analyzed clinical data. Y.I., B. Boisson, V.C.-D., D.S., F.M., N.Z., L.A., T.F., H.C.D., N.M., S.G.T., and M. Colombi provided expertise and feedback. J.L., J.-L.C., and A.P. designed the study and wrote the manuscript with the assistance of all coauthors. Competing interests: The authors declare that they have no competing interests. Data and materials availability: The WES data are available from the NCBI Sequence Read Archive via BioProject accession number PRJNA563623. The microarray and RNA-Seq data have been deposited to the Gene Expression Omnibus and are accessible under accession number GSE137110. All other data needed to evaluate the conclusions in the paper are present in the paper or the Supplementary Materials.
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