Journal of Immunology Research

Journal of Immunology Research / 2018 / Article

Research Article | Open Access

Volume 2018 |Article ID 9419204 | 26 pages | https://doi.org/10.1155/2018/9419204

Immune Response to Rotavirus and Gluten Sensitivity

Academic Editor: Peirong Jiao
Received31 Jul 2017
Revised18 Dec 2017
Accepted25 Dec 2017
Published15 Mar 2018

Abstract

Rotavirus is a double-stranded RNA virus belonging to the family of Reoviridae. The virus is transmitted by the faecal-oral route and infects intestinal cells causing gastroenteritis. Rotaviruses are the main cause of severe acute diarrhoea in children less than 5 years of age worldwide. In our previous work we have shown a link between rotavirus infection and celiac disease. Nonceliac gluten sensitivity (NCGS) is emerging as new clinical entity lacking specific diagnostic biomarkers which has been reported to occur in 6–10% of the population. Clinical manifestations include gastrointestinal and/or extraintestinal symptoms which recede with gluten withdrawal. The pathogenesis of the disease is still unknown. Aim of this work is to clarify some aspects of its pathogenesis using a gene array approach. Our results suggest that NCGS may have an autoimmune origin. This is based both on gene expression data (i.e., TH17-interferon signatures) and on the presence of TH17 cells and of serological markers of autoimmunity in NCGS. Our results also indicate a possible involvement of rotavirus infection in the pathogenesis of nonceliac gluten sensitivity similarly to what we have previously shown in celiac disease.

1. Introduction

Nonceliac gluten sensitivity (NCGS) can be defined as a nonallergic condition in which the consumption of gluten can lead to symptoms similar to those observed in celiac disease (CD). NCGS is characterized by the absence of celiac specific antibodies (against tissue transglutaminase, endomysium, and/or deamidated gliadin peptide) and absence of classical enteropathy (Marsh 0-1) although an increased density of CD3+ intraepithelial lymphocytes can be observed in duodenal biopsies. Patients with NCGS may have variable HLA status, and positivity for HLA-DQ2 and/or DQ8 has been found in roughly 50% of patients with NCGS. Serological analyses of NCGS patients revealed a high prevalence (40–50%) of first generation antigliadin IgG antibodies. NCGS is characterized by symptoms that usually occur soon after gluten ingestion and disappear or improve with gluten withdrawal but relapse following gluten challenge. The clinical presentation of NCGS may be a combination of gastrointestinal symptoms, including abdominal pain, bloating, bowel habit abnormalities (diarrhoea or constipation), and systemic manifestations, that is “foggy mind,” fatigue, muscle and joint pain, leg or arm numbness, eczema and skin rash, depression, and anemia. Similarly to patients with CD, subjects with clinical manifestations compatible with NCGS should start a gluten-free diet. Since it is still not clear whether NCGS is a permanent or transient condition, reintroduction of gluten after 1-2 years on a gluten-free diet can be considered [1, 2].

Rotavirus is a double-stranded RNA virus belonging to the family of Reoviridae.

The virus is transmitted by the faecal-oral route and infects intestinal cells causing gastroenteritis. Rotaviruses are the main cause of severe acute diarrhoea in children less than 5 years of age worldwide [3]. They are responsible for 453,000 deaths worldwide each year, which in most cases (85%) occur in developing countries [3]. The virus particle is composed of six viral proteins (VPs) called VP1, VP2, VP3, VP4, VP6, and VP7. Among these, the glycoprotein VP7 is located on the outer surface of the virus determining the specific G-type of the strain and plays a role in the development of immunity to infection [4].

We have previously described the presence, in active celiac disease (CD), of a subset of antitransglutaminase IgA antibodies that recognizes the viral protein VP-7 and is able to increase intestinal permeability and induce monocyte activation [5]. We then showed that the antirotavirus VP7 antibodies may be even detected before the CD onset and the detection of antitissue transglutaminase (tTG) and antiendomysium antibodies, showing a predictive role [6]. In addition, we observed that these antibodies were able to induce in human T84 intestinal cell line the modulation of genes involved in biological processes that represents typical features of CD [6]. Taken together, our data seem to provide a link between rotavirus infection and CD.

In this paper, we aim at clarifying some aspects of the pathogenesis of NCGS by a gene-array approach. In particular, we plan to verify the possibility of the involvement of an autoimmune mechanism in the disease. In addition, we also aim at investigating a possible involvement of rotavirus infection in the development of NCGS. For this purpose, we compared the global panel of modulated genes in NCGS to the dataset of human T84 intestinal cells treated with antirotavirus VP7 antibodies, described in our previous work [6], and to a dataset of acute phase of rotavirus infection, downloaded from the GEO (Gene Expression Omnibus) database, searching for transcriptional profiles that may be associated to viral infection.

2. Materials and Methods

2.1. Patients

We studied a cohort of 16 patients (6 males and 10 females, mean age: 27.3 years) affected by NCGS, attending the Unit of Autoimmune Diseases and the Immunology Unit and Child Neuropsychiatry Unit at the University Hospital of Verona, Italy.

All the enrolled subjects were recruited after informed consent. Main symptoms were headache, dermatitis, chronic urticaria, muscle and joint pain, bloating, abdominal pain, diarrhoea, alternating bowel movements, and fatigue in a variable combination.

Diagnosis of NCGS was established when all the following criteria were met: (1) exclusion of wheat allergy by clinical history and determination of specific IgE; (2) exclusion of celiac disease by absence of celiac-specific antibodies tissue transglutaminase (tTG), endomysium (EMA), and/or deamidated gliadin peptides (DGP); (3) duodenal biopsy with a histological damage grade 0 to 1, according to Marsh’s classification; (4) significant improvement of symptoms on strict gluten-free diet and relapse of symptoms after gluten reintroduction.

2.2. Detection of Anti-VP7 Peptide Antibodies

The ELISA test for antibody binding to the synthetic peptides has been carried out as already described elsewhere with minor modifications [7]. The synthetic peptides were used at a concentration of 20 μ/mL in PBS to coat polystyrene plates (Immulon 2HB, Thermo). For the detection of antirotavirus VP7 peptide IgA antibodies, only the sera whose OD readings were higher than the mean plus three standard deviations of each serum dilution of the control group were considered positive. OD values higher than 0.140 were considered positive.

2.3. Gene Array

Peripheral blood cells were collected for analysis of gene expression profiles on a gluten-containing diet. PAXgene Blood RNA tubes (PreAnalytiX, Hombrechtikon, Switzerland) were used for blood collection and total RNA was extracted according to the protocol supplied by the manufacturer. Preparation of cRNA hybridization and scanning of arrays for each samples were performed following the manufacturer instructions (Affymetrix, Santa Clara, CA, USA) by Cogentech Affymetrix microarray unit (Campus IFOM IEO, Milan, Italy) using the Human Genome U133A 2.0 GeneChip (Affymetrix). The gene expression profiles were analysed using the GeneSpring software version 12.1 (Agilent Technologies, Santa Clara, CA, USA) that calculated a robust multiarray average of background-adjusted, normalized, and log-transformed intensity values applying the robust multiarray average algorithm (RMA). The normalized data were transformed to the log2 scale. The unpaired t-test was performed to determine which genes were modulated at a significant level (), and values were corrected for multiple testing by using Bonferroni correction. Finally, statistically significant genes were chosen for final consideration when their expression was at least 1.5-fold different in the test sample versus control sample. Genes that passed both the p value and the FC restriction were submitted to functional and pathway enrichment analysis according to the Gene Ontology (GO) annotations employing the Panther expression analysis tools (http://pantherdb.org/).

2.4. Protein-Protein Interaction (PPI) Network Construction and Network Modular Analysis

All the possible interactions among the protein products of DEGs were analysed with Search Tool for the Retrieval of Interacting Genes (STRING version 1.0; http://string-db.org/) a web-based database that includes experimental as well as predicted interaction information and covers more than 1100 sequenced organisms. Only protein-protein interaction (PPI) pairs that were confirmed by experimental studies were selected, and a score of ≥0.7 for each PPI pair was used to build a PPI network.

Cytoscape software [8] was used to define the topology of the built network, and the Molecular Complex Detection (MCODE) [9] was used to find densely connected region (modules) of the network that could be involved in the modulation of biological processes that are relevant for the disease pathogenesis. To find locally dense regions of a graph, MCODE applies a vertex-weighting scheme based on a clustering coefficient that is a measure of the degree to which nodes in a graph tend to cluster together.

The following settings in MCODE were used: degree cutoff = 2, K-core = 3, and max. depth = 100. Functional enrichment for a given module was assessed quantitatively using the Panther tool.

2.5. Analysis of the Association between DEGs and Human Diseases

We used the software Ingenuity Pathway Analysis (IPA, Ingenuity Systems) to evaluate diseases and disorders that could be statistically significantly associated to gene modulation observed in NCGS samples. The statistical significance of gene-disease associations was calculated in IPA by the Fisher’s exact test ().

2.6. Detection of Soluble Mediators in GS Sera

Serum levels of sCTLA-4, s PD-1, and sgp130/IL6ST were detected before and after gluten-free diet using commercially available ELISA kits according to the manufacturer’s instructions. ELISA kits were purchased from Bender MedSystems (Milano, Italy) (sCTLA-4), from R&D Systems (Minneapolis, United States) (sgp130), and from EMELCA Bioscience (Clinge, Netherlands) (sPD-1).

2.7. FACS Analysis

Cells collected from patients and normal controls were cultured at a concentration of 1106 cells/mL in 2 mL tubes containing 1 mL of RPMI 1640 + FCS 10% (Lonza, Basel, CH). Cells were stimulated overnight with Dynabeads Human T-Activator CD3/CD28 (Life Technologies, Carlsbad, CA, USA). The detection of IL-17 production was analysed using the IL-17 Secretion Assay (Miltenyi Biotec, Bergisch Gladbach, D) following the manufacturer’s instruction. Briefly, cells were washed with 2 mL of cold buffer at 300 ×g for 5 minutes at 4°C, and the pellet was resuspended in 90 μL of cold medium. Cells were then incubated with 10 μL of IL-17 Catch Reagent for 5 minutes in ice and cultured in 1 mL of warm medium at 37°C for 45 minutes under slow continuous rotation. Cells were then washed with cold buffer and resuspended in 75 μL of cold buffer; 10 μL of IL-17 Detection Antibody APC, 10 μL of anti-CD3 PerCP (Becton Dickinson, Franklin Lakes, NJ, USA), and 5 μL of anti-CD4 APC-H7 (Becton Dickinson) monoclonal antibodies were added. Incubation was carried out in ice for 10 minutes. Finally, cells were washed and resuspended in an appropriate volume of PBS and acquired on a FACSCanto II cytometer (Becton Dickinson). Analysis was performed with FlowJo 9.3.3 software (Tree Star, Ashland, OR, USA).

2.8. Statistical Analysis

Data obtained from the analysis of the soluble mediators CTLA-4, gp130, and PD-1 and from the detection of antigliadin antibodies were submitted to statistical testing using the Wilcoxon nonparametric statistical hypothesis test for paired samples.

Data obtained from the ELISA test for the detection of antirotavirus VP7 peptide antibodies were submitted to statistical testing using the Mann–Whitney nonparametric test. Statistical analysis was performed using GraphPad Prism Software version 5.00 (GraphPad Software, La Jolla, California, USA, http://www.graphpad.com).

3. Results and Discussion

Many aspects of NCGS are still unknown; in particular, it is still not clear whether the disease is permanent or transient or whether the disease has features of autoimmunity. The pathogenesis of NCGS is also unclear and data obtained so far suggest a prevalent activation of innate immune responses [2].

We aimed at clarifying some aspects of NCGS pathogenesis using a gene array approach which we successfully used in the study of many immune-mediated diseases [6, 1012].

In order to identify specific gene signatures typically associated with NCGS, we compared the gene expression profiles of 8 PBC samples obtained from individual NCGS patients with 10 PBC samples obtained from healthy age- and sex-matched donors. We observed that the disease has a profound impact on gene expression profiles since a large number of differentially expressed genes (DEGs) (1293, represented by 1521 modulated probe sets) complied with the Bonferroni-corrected value criterion () and the fold change criterion (FC ≥ 1.5) showing robust and statistically significant variation between healthy controls and NCGS samples. In particular, 695 and 598 genes resulted to be up- and downregulated, respectively (Additional Table 1).

DEGs were submitted to functional enrichment analysis according to terms of the Gene Ontology (GO) biological processes (BP) and canonical pathways. The most enriched biological process was “immune system” followed by “intracellular signal transduction” (Table 1). In addition, several enriched terms were related to the immune response gene category, including “leukocyte differentiation,” “leukocyte activation involved in immune response,” “T cell differentiation,” “neutrophil degranulation,” “adaptive immune response,” and “defense response.” Interestingly, we observed an enrichment in “cellular response to organic substance,” “cellular response to endogenous stimulus,” and “viral process.” The BP named “viral process” is defined by the Gene Ontology Consortium as a “multi-organism process in which a virus is a participant and the other participant is the host.” This term is related to the infection of a host cell, the replication of the viral genome, the viral transcription, and the assembly of progeny virus particles.


Biological processes value
Immune system process6.3 × 10−26
Intracellular signal transduction4.6 × 10−16
Cellular response to organic substance1.5 × 10−13
Cell surface receptor signaling pathway8.2 × 10−10
Leukocyte differentiation6.3 × 10−9
Viral process7.7 × 10−9
Leukocyte activation involved in immune response8.0 × 10−8
Apoptotic process2.2 × 10−6
Cellular response to endogenous stimulus3.0 × 10−6
T cell differentiation5.6 × 10−5
Neutrophil degranulation5.6 × 10−5
Adaptive immune response6.5 × 10−5
Defense response6.8 × 10−5
Pathways value
Inflammation mediated by chemokine and cytokine signaling pathway2.1 × 10−7
Apoptosis signaling pathway1.6 × 10−4
Angiogenesis4.1 × 10−4
T cell activation5.3 × 10−4
B cell activation5.7 × 10−4
Integrin signaling pathway7.8 × 10−4
EGF receptor signaling pathway4.0 × 10−3
Toll like receptor signaling pathway4.6 × 10−3
PI3 kinase pathway7.6 × 10−3
Interleukin signaling pathway8.1 × 10−3
JAK/STAT signaling pathway1.6 × 10−2

Bonferroni corrected.

Pathway enrichment analysis showed that the most enriched signaling pathways were “inflammation mediated by chemokine and cytokine,” “apoptosis,” and “angiogenesis,” followed by “T cell activation” and “B cell activation” (Table 1). Other enriched pathways were: “integrin signaling,” “EGF receptor signaling,” “Toll-like receptor signaling,” “PI3 kinase,” “interleukin signaling,” and JAK/STAT signaling. Since the majority of the top-enriched functional classes and pathways were related to the immune system, we selected, within the entire data set, all modulated genes associated to the “Immune response” GO term to better characterize the immunological processes that are involved in NCGS pathogenesis. Although both innate and adaptive immunity play a crucial role in the development of CD, NCGS has been mainly associated with activation of the innate immune response [2].

It is therefore surprising to notice that both transcripts involved in the innate immune response as well as genes of the adaptive immune response were well represented in our dataset (Table 2).


Probe set ID valueGene symbolGene titleFCRepresentative public ID

T cell activation
203809_s_at<0.001AKT2v-akt murine thymoma viral oncogene homolog 22.36NM_001626
211861_x_at<0.001CD28CD28 molecule2.75AF222343
205456_at<0.001CD3ECD3e molecule, epsilon (CD3-TCR complex)2.67NM_000733
206804_at<0.001CD3GCD3g molecule, gamma (CD3-TCR complex)2.13NM_000073
211027_s_at<0.001IKBKBInhibitor of kappa light polyp. gene enhancer in B cells, kinase β2.69NM_001190720
213281_at0.007JUNjun proto-oncogene3.07NM_002228.3
204890_s_at<0.001LCKLymphocyte-specific protein tyrosine kinase2.05U07236
213490_s_at<0.001MAP2K2Mitogen-activated protein kinase kinase 21.83NM_030662
214786_at0.013MAP3K1Mitogen-activated protein kinase kinase kinase 11.52NM_005921
210671_x_at<0.001MAPK8Mitogen-activated protein kinase 82.33NM_001278548
211230_s_at<0.001PIK3CDPhosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic sub. Δ1.88U57843
212249_at0.002PIK3R1Phosphoinositide-3-kinase, regulatory subunit 1 (alpha)2.76NM_181523
216551_x_at0.001PLCG1Phospholipase C, gamma 11.53NM_002660
208640_at<0.001RAC1Rho family, small GTP-binding protein Rac1−1.92NM_006908
207419_s_at<0.001RAC2Rho family, small GTP-binding protein Rac22.31NM_002872
217576_x_at0.002SOS2Son of sevenless homolog 21.90NM_006939
216042_at<0.001TNFRSF25Tumor necrosis factor receptor superfamily, member 252.40NM_148965
221331_x_at<0.001CTLA4Cytotoxic T-lymphocyte-associated protein 42.26NM_005214
206569_at<0.001IL24Interleukin 242.84NM_006850
203828_s_at0.003IL32Interleukin 322.10NM_004221
B cell mediated immune response
211027_s_at<0.001IKBKBInhibitor of kappa light polyp. gene enhancer in B cells, kinase β2.69NM_001190720
213281_at0.007JUNjun proto-oncogene3.07NM_002228.3
202626_s_at0.004LYNv-yes-1 Yamaguchi sarcoma viral related oncogene homolog−2.22AI356412
213490_s_at<0.001MAP2K2Mitogen-activated protein kinase kinase 21.83NM_030662
210671_x_at<0.001MAPK8Mitogen-activated protein kinase 82.33NM_001278548
211230_s_at<0.001PIK3CDPhosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic sub. Δ1.88U57843
32540_at<0.001PPP3CCProtein phosphatase 3, catalytic subunit, gamma isozyme2.00NM_001243975
208640_at<0.001RAC1Rho family, small GTP-binding protein Rac1−1.92NM_006908
207419_s_at<0.001RAC2Family, small GTP-binding protein Rac22.31NM_002872
217576_x_at0.002SOS2Son of sevenless homolog 21.90NM_006939
207540_s_at0.008SYKSpleen tyrosine kinase−1.92NM_003177
207224_s_at0.003SIGLEC7Sialic acid-binding Ig-like lectin 7−2.21NM_016543
206150_at0.004CD27CD27 molecule1.96NM_001242
214447_at0.005ETS1v-ets erythroblastosis virus E26 oncogene homolog 12.25NM_005238
201328_at0.012ETS2v-ets erythroblastosis virus E26 oncogene homolog 2−1.83NM_005239
212420_at0.001ELF1E74-like factor 1 (ets domain transcription factor)1.94KJ896761
211825_s_at<0.001FLI1Friend leukemia virus integration 12.28AF327066
215967_s_at<0.001LY9Lymphocyte antigen 92.08NM_002348
210690_at0.001KLRC4Killer cell lectin-like receptor subfamily C, member 42.23U96845
204116_at<0.001IL2RGInterleukin 2 receptor, gamma1.84NM_000206
217489_s_at<0.001IL6RInterleukin 6 receptor1.79S72848
204863_s_at<0.001IL6STInterleukin 6 signal transducer (gp130, oncostatin M receptor)4.52NM_002184
206966_s_at<0.001KLF12Kruppel-like factor 121.83AH010423
219878_s_at<0.001KLF13Kruppel-like factor 131.89NM_015995
219386_s_at<0.001SLAMF8SLAM family member 8−2.27NM_020125
210405_x_at0.003TNFRSF10BTumor necrosis factor receptor superfamily, member 10b1.50NM_003842
219386_s_at<0.001SLAMF8SLAM family member 8−2.27NM_020125
210405_x_at0.003TNFRSF10BTumor necrosis factor receptor superfamily, member 10b1.50NM_003842
203508_at0.005TNFRSF1BTumor necrosis factor receptor superfamily, member 1B−2.06NM_001066
216042_at<0.001TNFRSF25Tumor necrosis factor receptor superfamily, member 252.40NM_148965
218856_at0.008TNFRSF21Tumor necrosis factor receptor superfamily, member 21−1.68NM_014452
206181_at0.003SLAMF1Signaling lymphocytic activation molecule family member 11.65NM_003037
210796_x_at<0.001SIGLEC6Sialic acid-binding Ig-like lectin 61.58D86359
211192_s_at<0.001CD84CD84 molecule2.55AF054818
220132_s_at<0.001CLEC2DC-type lectin domain family 2, member D3.18NM_013269
204773_at0.005IL11RAInterleukin 11 receptor, alpha1.56AY532110
210850_s_at<0.001ELK1ELK1, member of ETS oncogene family1.60AF000672
209894_at0.002LEPRLeptin receptor−2.10U50748
203005_at0.006LTBRLymphotoxin beta receptor (TNFR superfamily, member 3)−1.92NM_002342
NK cell activation
220132_s_at<0.001CLEC2DC-type lectin domain family 2, member D3.18NM_013269
203233_at0.014IL4RInterleukin 4 receptor1.50NM_000418
210152_at0.007LILRB4Leukocyte immunoglobulin-like receptor, subfamily B, member 4−1.83NM_001278426
210784_x_at0.012LILRA6Leukocyte immunoglobulin-like receptor, subfamily A, member 6−1.74NM_024318
211405_x_at0.003IFNA17Interferon, alpha 171.59NM_021268
210660_at0.008LILRA1Leukocyte immunoglobulin-like receptor, subfamily A, member 1−2.81NM_001278319
207857_at0.016LILRA2Leukocyte immunoglobulin-like receptor, subfamily A, member 2−2.35NM_006866
210690_at0.001KLRC4Killer cell lectin-like receptor subfamily C, member 42.23U96845
206881_s_at0.013LILRA3Leukocyte immunoglobulin-like receptor, subfamily A, member 3−2.96NM_006865
210313_at0.003LILRA4Leukocyte immunoglobulin-like receptor, subfamily A, member 4−1.83NM_012276
215838_at0.012LILRA5Leukocyte immunoglobulin-like receptor, subfamily A, member 5−3.15NM_181985
210146_x_at0.004LILRB2Leukocyte immunoglobulin-like receptor, subfamily B, member 2−3.41AF004231
208982_at0.008PECAM1Platelet/endothelial cell adhesion molecule 1−1.73M37780
203828_s_at0.003IL32Interleukin 322.10NM_004221
Macrophage activation
210405_x_at0.003TNFRSF10BTumor necrosis factor receptor superfamily, member 10b1.50NM_003842
221900_at0.003COL8A2Collagen, type VIII, alpha 2−1.62NM_005202
205819_at<0.001MARCOMacrophage receptor with collagenous structure−3.01NM_006770
208602_x_at<0.001CD6CD6 molecule3.67NM_006725
207540_s_at0.008SYKSpleen tyrosine kinase−1.92NM_003177
203508_at0.005TNFRSF1BTumor necrosis factor receptor superfamily, member 1B−2.06NM_001066
204438_at0.012MRC1Mannose receptor, C type 1−2.04NM_002438
202269_x_at0.006GBP1Guanylate binding protein 1, interferon-inducible−1.77NM_002053
208982_at0.008PECAM1Platelet/endothelial cell adhesion molecule 1−1.73M37780
Complement activation
205500_at0.006C5Complement component 5−1.60NM_001735
206244_at0.003CR1Complement component (3b/4b) receptor 1 (Knops blood group)−1.79NM_000573
Response to gamma interferon
205831_at0.001CD2CD2 molecule2.00NM_001767
205468_s_at0.015IRF5Interferon regulatory factor 51.52NM_032643
219386_s_at<0.001SLAMF8SLAM family member 8−2.27NM_020125
211192_s_at<0.001CD84CD84 molecule2.55AF054818
202269_x_at0.006GBP1Guanylate-binding protein 1, interferon-inducible−1.77NM_002053
202621_at<0.001IRF3Interferon regulatory factor 31.67NM_001571
33148_at<0.001ZFRZinc finger RNA binding protein2.19NM_016107
206181_at0.003SLAMF1Signaling lymphocytic activation molecule family member 11.65NM_003037
215967_s_at<0.001LY9Lymphocyte antigen 92.08NM_002348
201461_s_at0.011MAPKAPK2Mitogen-activated protein kinase-activated protein kinase 21.85NM_004759
216450_x_at<0.001HSP90B1Heat shock protein 90 kDa beta (Grp94), member 13.76AK025862
214370_at<0.001S100A8S100 calcium-binding protein A83.65AW238654
Antigen processing and presentation
206050_s_at0.010RNH1Ribonuclease/angiogenin inhibitor 1−1.53NM_002939
204770_at<0.001TAP2Transporter 2, ATP-binding cassette, sub-family B (MDR/TAP)1.86NM_000544
TH17 related genes
203233_at0.014IL4RInterleukin 4 receptor1.50NM_000418
204116_at<0.001IL2RGInterleukin 2 receptor, gamma1.84NM_000206
204863_s_at<0.001IL6STInterleukin 6 signal transducer (gp130, oncostatin M receptor)4.52NM_002184
205067_at0.015IL1BInterleukin 1, beta1.52NM_000576
205798_at0.011IL7RInterleukin 7 receptor1.55NM_002185
201332_s_at0.013STAT6Signal transducer and activator of transcription 61.54AH006951
205026_at<0.001STAT5BSignal transducer and activator of transcription 5B1.60NM_012448
206360_s_at<0.001SOCS3Suppressor of cytokine signaling 31.83NM_003955
209774_x_at0.015CXCL2Chemokine (C-X-C motif) ligand 21.53M57731
Type I interferon signaling
211405_x_at0.003IFNA17Interferon, alpha 171.59NM_021268
205468_s_at0.015IRF5Interferon regulatory factor 51.52NM_032643
202621_at<0.001IRF3Interferon regulatory factor 31.67NM_001571
217199_s_at<0.001STAT2Signal transducer and activator of transcription 2, 113 kDa1.59S81491
M97935_5_at<0.001STAT1Signal transducer and activator of transcription 1, 91 kDa2.73NM_007315
210370_s_at<0.001LY9Lymphocyte antigen 92.05NM_002348

In this regard, 14 genes involved in NK activity were modulated in NCGS samples (i.e., LILRA1, LILRA2, CLEC2D, and KLRC4). Moreover, several genes involved in macrophage activation were modulated in NCGS including TNFRSF10B, the ligand of the death receptors TRAIL that play important roles in set up both innate and adaptive immune responses against pathogens [13], and the scavenger receptors MRC1/CD206 [14] and MARCO, a member of the class A scavenger receptor family strongly upregulated in MΦ by various microbial stimuli in a TLR-dependent manner [15].

Noteworthy, 38 genes prevalently related to B cell activity (i.e., IL2RG, IL6R, KLF12, and CD27) were also modulated, indicating an important role for this cell subset in NCGS, 20 genes involved in T cell activation were upregulated in NCGS samples (i.e., CD28, CD3E, CD3G, and CTLA-4). Remarkably, Th17-lymphocyte-related genes and transcripts that can modulate Th17 cell development and functions were overexpressed including IL4R, IL2RG, IL6ST, IL1B, IL7R, STAT6, STAT5B, SOCS3, and CXCL2.

DEGs indicate therefore active involvement of both arms of the adaptive immune response (i.e., T and B cells response) and a prevalent upregulation of several Th17-related genes in the T cell response category. It is well known that Th17 cells play an important role in autoimmunity and have been implicated in the pathogenesis of psoriasis and in the amplification of inflammation in rheumatoid synovitis and in lupus nephritis [1618].

In the NCGS dataset, 6 type I interferon inducible genes (IFIG) were upregulated (IFNA17, IRF5, IRF3, STAT2, STAT1, and LY9), thus indicating the presence of an IFN type I signature, typically associated with autoimmune disease such as systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), Crohn’s disease, and Sjogren syndrome [1925].

In this respect, it is well known that Th17 cells and related cytokines are crucial in promoting autoimmunity, in particular, when they act in synergy with type I IFN-driven inflammation. In the presence of IFN type I signature, CCR6+ memory T-helper cells producing IL-17A, IL-17F, IL-21, and/or IL-22 are increased in SLE, [26] indicating that, in the pathogenesis of systemic autoimmune diseases, IFN type I signature coacts with Th17 cells and related cytokines.

In order to further confirm our gene expression data on overexpression of IFIG and Th17 pathways, we analysed the presence of IL-17-producing CD4+ T cells and found a significantly () increased percentage of these cells in PBMC of patients with NCGS compared with normal subjects (Figure 1).

The analysis of genes modulated in gluten sensitivity was paralleled by the detection of some of the corresponding soluble mediators in the sera of NCGS patients. We analysed selected molecules that are widely recognized to be associated to an autoimmune response, including sCTLA-4, sPD-1, and sgp130/IL6ST. Figure 2 shows the concentration of these molecules in the sera of NCGS patients before and after gluten-free diet. The serum levels of all the molecules tested were significantly higher in NCGS before GFD than after GFD.

In order to gain further insights into the molecular mechanisms relevant in NCGS pathogenesis, we constructed a protein-protein interaction (PPI) network starting from all the 1293 DEGs. The resulted PPI network contained 853 nodes and 3512 edges (Figure 3). By performing a modular analysis of the constructed PPI network, we were able to identify clusters of the most densely interconnected nodes (modules) and to extrapolate 15 main modules of genes displaying the highest degree of connection. Figure 4 shows a graphical representation of such modules, where the nodes represent proteins and the edges indicate their relations.

All modules were submitted to enrichment analysis to find enriched GO biological processes and pathways.

Among the 15 modules in particular, five (module 1, 3, 7, 10, and 14) showed a prevalent enrichment in BP and pathways associated to the activation of T cells. Similarly, “B cell activation” pathways were significantly enriched in modules 1, 9, 10, and 14. Interestingly, in modules 3, 10, and 11, we observed an enrichment in the JAK–STAT signaling pathway, which is highly relevant to human autoimmunity [27] and plays a role in the intestinal mucosal immune homeostasis as well as in intestinal epithelial repair and regeneration [28]. We also observed that module 11 contained several genes involved in Th-17 cell functions (i.e., IL2RG, IL4R, IL6ST, IL7R, SOCS3, STAT5B, and STAT6) and several IFIG, including IFNA17, STAT1, and STAT2. Other IFIG genes were ascribed to module 9 which also shows an enrichment in BPs associated to type I interferon signaling, including positive regulation of type I interferon production, positive regulation of interferon-beta production, and type I interferon biosynthetic process (Table 3).


Biological processes valuePathways value

M0
Exocytosis<0.001None
Secretion by cell<0.001
Secretion<0.001
Vesicle-mediated transport0.0018
Single-organism transport0.0220
Single-organism localization0.0308
M1
T cell receptor signaling pathway<0.001T cell activation<0.001
Transmembrane receptor protein tyrosine kinase signaling pathway<0.001B cell activation0.0012
T cell costimulation<0.001Cadherin signaling pathway0.0056
Viral process<0.001Integrin signaling pathway0.0081
Fc-gamma receptor signaling pathway involved in phagocytosis<0.001
Peptidyl-tyrosine modification0.0016
Adaptive immune response0.0017
Positive regulation of antigen receptor-mediated signaling pathway0.0029
Positive regulation of alpha-beta T cell proliferation0.0038
Phosphatidylinositol phosphorylation0.0060
Phosphatidylinositol-mediated signaling0.0162
Positive regulation of calcium-mediated signaling0.0192
T cell selection0.0244
Leukocyte migration0.0303
Interleukin-2-mediated signaling pathway0.0324
MAPK cascade0.0371
Positive regulation of immune effector process0.0466
Positive regulation of defense response0.0485
M2
mRNA export from nucleus<0.001None
Spliceosomal complex assembly<0.001
Termination of RNA polymerase II transcription<0.001
Regulation of mRNA splicing, via spliceosome<0.001
Positive regulation of RNA splicing<0.001
mRNA 3′-end processing<0.001
Regulation of gene silencing by miRNA<0.001
tRNA export from nucleus0.0010
Viral gene expression0.0054
Intracellular transport of virus0.0078
Protein sumoylation0.0294
Regulation of cellular response to heat0.0310
Fibroblast growth factor receptor signaling pathway0.0414
M3
Positive regulation of T cell activation0.0035T cell activation<0.001
Interleukin-2-mediated signaling pathway0.0065Interleukin signaling pathway<0.001
Interleukin-4-mediated signaling pathway0.0065PDGF signaling pathway0.0010
Protein phosphorylation0.0349Integrin signaling pathway0.0017
JAK/STAT signaling pathway0.0057
Hypoxia response via HIF activation0.0110
Insulin/IGF pathway-protein kinase B signaling cascade0.0136
p53 pathway feedback loops 20.0176
PI3 kinase pathway0.0182
VEGF signaling pathway0.0238
Endothelin signaling pathway0.0284
p53 pathway0.0290
M4
Pospholipase C-activating G-protein-coupled receptor signaling pathway<0.001Heterotrimeric G-protein signal. pathway-Gq α and Go α med. pathway<0.001
G-protein coupled acetylcholine receptor signaling pathway<0.001
Activation of phospholipase C activity<0.001PI3 kinase pathway<0.001
Positive regulation of cytosolic calcium ion concentration<0.001Endothelin signaling pathway0.0013
Adenylate cyclase-modulating G-protein-coupled receptor signaling pathway0.0048Wnt signaling pathway0.0015
M5
Translational initiation<0.001None
Nuclear-transcribed mRNA catabolic process, nonsense mediated decay<0.001
SRP-dependent cotranslational protein targeting to membrane<0.001
rRNA processing<0.001
Ribosomal small subunit assembly0.0083
M6
Regulation of small GTPase-mediated signal transduction<0.001None
Positive regulation of GTPase activity<0.001
Small GTPase-mediated signal transduction<0.001
Actin cytoskeleton organization0.0108
M7
T cell costimulation<0.001T cell activation<0.001
Phosphatidylinositol-mediated signaling<0.001Integrin signaling pathway0.0041
T cell receptor signaling pathway<0.001
Phosphatidylinositol phosphorylation<0.001
Transmembrane receptor protein tyrosine kinase signaling pathway0.0016
Peptidyl-tyrosine autophosphorylation0.0033
Viral process0.0035
Fc receptor signaling pathway0.0050
Regulation of apoptotic process0.0055
Leukocyte differentiation0.0122
Leukocyte migration0.0232
Lymphocyte activation0.0237
B cell receptor signaling pathway0.0256
Positive regulation of defense response0.0340
M8
Response to unfolded protein<0.001None
Response to topologically incorrect protein<0.001
Chaperone-mediated protein complex assembly<0.001
Protein folding<0.001
Protein transmembrane transport<0.001
Response to stress<0.001
M9
Activation of innate immune response<0.001Toll-like receptor signaling pathway<0.001
Positive regulation of innate immune response<0.001Ras pathway<0.001
Toll-like receptor signaling pathway<0.001Apoptosis signaling pathway<0.001
Fc-epsilon receptor signaling pathway0.0020T cell activation<0.001
MAPK cascade0.0026p38 MAPK pathway<0.001
Positive regulation of type I interferon production0.0029Oxidative stress response<0.001
Positive regulation of cytokine production0.0035Angiogenesis<0.001
TRIF-dependent toll-like receptor signaling pathway0.0136B cell activation<0.001
Positive regulation of interferon-beta production0.0202FGF signaling pathway<0.001
Response to lipopolysaccharide0.0268EGF receptor signaling pathway<0.001
Type I interferon biosynthetic process0.0419Integrin signaling pathway0.0024
Inflammation mediated by chemokine and cytokine signaling pathway0.0079
Interleukin signaling pathway0.0104
M10
T cell receptor signaling pathway<0.001T cell activation<0.001
T cell costimulation<0.001EGF receptor signaling pathway<0.001
Fc-epsilon receptor signaling pathway<0.001Integrin signaling pathway<0.001
phosphatidylinositol phosphorylation<0.001p53 pathway feedback loops 2<0.001
Peptidyl-tyrosine autophosphorylation<0.001VEGF signaling pathway<0.001
Fc-gamma receptor signaling pathway involved in phagocytosis<0.001B cell activation<0.001
Leukocyte migration<0.001Ras pathway<0.001
Growth hormone receptor signaling pathway<0.001Angiogenesis<0.001
Regulation of defense response to virus<0.001Insulin/IGF pathway-protein kinase B signaling cascade<0.001
Innate immune response<0.001
Positive regulation of MAP kinase activity<0.001Inflammation mediated by chemokine and cytokine signaling pathway<0.001
T cell differentiation<0.001
Regulation of apoptotic process<0.001PI3 kinase pathway<0.001
JAK–STAT cascade0.0011p53 pathway<0.001
Positive regulation of immune effector process0.0031Interferon-gamma signaling pathway<0.001
MAPK cascade0.0056FGF signaling pathway<0.001
Adaptive immune response0.0088Endothelin signaling pathway0.0101
B cell receptor signaling pathway0.0121JAK/STAT signaling pathway0.0176
Phosphatidylinositol 3-kinase signaling0.0214
Stimulatory C-type lectin receptor signaling pathway0.0363
Innate immune response activ. cell surface receptor signal. pathway0.0387
M11
Cellular response to cytokine stimulus<0.001JAK/STAT signaling pathway<0.001
JAK–STAT cascade involved in growth hormone signaling pathway<0.001Interleukin signaling pathway<0.001
Positive regulation of cytokine production<0.001PDGF signaling pathway<0.001
Response to interleukin-2<0.001Interferon-gamma signaling pathway<0.001
Positive regulation of T cell differentiation<0.001EGF receptor signaling pathway<0.001
Positive regulation of tyrosine phosphorylation of STAT protein<0.001Integrin signaling pathway<0.001
Regulation of interferon-gamma-mediated signaling pathway<0.001Inflammation mediated by chemokine and cytokine signaling pathway<0.001
MAPK cascade<0.001
Adaptive immune response<0.001p53 pathway feedback loops 20.0025
Innate immune response0.0014PI3 kinase pathway0.0027
Positive regulation of T cell proliferation0.0022VEGF signaling pathway0.0045
Positive regulation of inflammatory response0.0025B cell activation0.0045
Antigen receptor-mediated signaling pathway0.0072Ras pathway0.0050
T cell differentiation0.0085T cell activation0.0078
Inflammatory response0.0194Cadherin signaling pathway0.0201
Positive regulation of antigen receptor-mediated signaling pathway0.0227
Transcription factor import into nucleus0.0313
T cell costimulation0.0396
M12Inflammation mediated by chemokine and cytokine signaling pathway<0.001
G-protein-coupled receptor signaling pathway<0.001
Chemokine-mediated signaling pathway<0.001Heterotrimeric G-protein signaling pathway-Gi alpha and Gs alpha-mediated pathway0.0473
Positive regulation of cytosolic calcium ion concentration<0.001
Inflammatory response<0.001
Cell chemotaxis<0.001
Positive regulation of neutrophil chemotaxis0.0136
Response to lipopolysaccharide0.0268
M13
Adherens junction assembly<0.001Integrin signaling pathway<0.001
Phosphatidylinositol phosphorylation0.0015Cadherin signaling pathway<0.001
Vesicle-mediated transport0.0026
Positive regulation of protein localization to nucleus0.0043
Actin cytoskeleton organization0.0105
Cell differentiation0.0308
M14
Positive regulation of T cell activation0.0035T cell activation<0.001
Interleukin-2-mediated signaling pathway0.0065Integrin signaling pathway<0.001
Interleukin-4-mediated signaling pathway0.0065Angiogenesis0.0032
Regulation of immune response0.0430Toll like receptor signaling pathway0.0269
VEGF signaling pathway0.0387
B cell activation0.0387
Ras pathway0.0431

Loss of the intestinal barrier integrity is a typical feature of CD and represents an important mechanism of autoimmunization through the passage of antigens across the intestinal epithelium [29]. However, Sapone et al. [29] have shown that NCGS patients have normal intestinal permeability when compared to CD patients, as assessed by the lactulose-mannitol test.

Indeed, in module 13, in which the most enriched BP was “adherent junction assembly,” we observed a reduced expression of molecules involved in cell adhesion including CDH1 (epithelial cadherin), CTNNA1, VCL, and CTTN, a molecule expressed on the apical surface of the polarized epithelium. In the same module, we also observed underexpression of Rac1, a critical regulator of intestinal epithelial barrier functions [30] and EGF, known to protect intestinal barrier integrity by stabilizing the microtubule cytoskeleton [31] and upregulation of FYN and PIK3R1, both involved in the signaling pathway by which IFNγ increases intestinal permeability [32].

The gene expression data would therefore indicate deregulation of adherent junctions and altered intestinal permeability also in NCGS, which seems to be in contrast with the data of Sapone et al. Nevertheless, it is important to point out that the lactulose-mannitol test may not be sensitive enough to detect mild alterations of the intestinal barrier function in patients with NCGS.

In module 12, the most enriched pathway was “inflammation mediated by chemokine and cytokine signaling”; this pathway was also enriched in modules 9, 10, and 11, which is consistent with inflammatory/autoimmune origin of NCGS.

Moreover, modules 1, 2, 7, and 10 were enriched in BPs related to viral infection including “viral process,” “viral gene expression,” “intracellular transport of virus,” and “regulation of defense response to virus.”

In addition, we observed that modules 10 and 11 showed enrichments in the gamma interferon pathways typically associated to the innate response to viruses [33].

Therefore, to further clarify the relationship between viral infections and NCGS, we searched in the IPA software database to find all diseases that are most likely to be statistically significantly associated to the genes modulated in the NCGS dataset. We found that, in the resulting list of most significantly associated diseases, “Infectious diseases” ranked first and, among these, “Viral infection” showed the best statistical p value (Figure 5(a)). Moreover, we could find a cluster of 134 DEGs that, in our NCGS dataset, showed a modulation that was consistent with a process of viral infection (Figure 5(b)). Based on these data, we aimed at investigating whether rotavirus, known to be linked to CD, [5, 6, 34] could also play a role in NCGS.

In the second part of our study, we made a comparison between the dataset obtained from our previous analysis of intestinal human T84 cells treated with anti-VP7 antibodies (that we indicate in this paper as “T84 dataset”) and genes modulated in NCGS. We found that 529 genes modulated in NCGS (accounting for the 41% of genes modulated in this dataset) were also modulated in treated T84 cells. Interestingly, several DEGs that were shared by the two datasets are involved in BP that may be related to the pathogenesis of celiac disease, including apoptosis, inflammatory and immune response, cell proliferation, cell differentiation, cell junctions, matrix metalloproteases, receptors and signal transducers, cytoskeleton components, ion transport and exchange, and EGF receptor pathway. Table 4 shows a selection of genes ascribed to the abovementioned functional classes. As a whole in NCGS dataset, the modulation of genes ascribed to the abovementioned categories indicated an upregulation of apoptotic genes accompanied by a downregulation of genes involved in cell differentiation and an increased transcription of proliferative genes. All these observation are in agreement with what we described on human T84 cells treated with antirotavirus Vp7 peptide antibodies and are related to the typical features of celiac disease. Indeed in CD, an increased apoptosis is the main cause of villous atrophy that is also sustained by a dysregulation of cell differentiation [35]. Moreover, it has been observed that the increase of intestinal cell proliferation leads to crypt hyperplasia seen in celiac disease [35]. Other aspects of CD previously observed in our T84 treated cells, that are paralleled by the gene modulated observed in NCGS, are the upregulation of members of the epidermal growth factor receptor (EGFR) signaling pathway and the concomitant downregulation of cell adhesion molecules beside a deregulation of ion transport. Noteworthy, the activation of EGFR signaling has been already observed in CD [36], and dysfunction of cell adhesion and transport are typical features of epithelial cells from active CD [37].


Gene symbolAccession numberGene titleFC NCGS PBCsFC T84 treated cells

Apoptosis
SOCS3NM_003955Suppressor of cytokine signaling 31.832.75
ANXA6NM_001155Annexin A61.572.72
SOS2NM_006939Son of sevenless homolog 2 (Drosophila)1.901.75
DEDDAF064605Death effector domain containing1.781.47
Immune response
IFNA17NM_021268Interferon, alpha 171.591.56
IL6RS72848Interleukin 6 receptor1.792.76
IRF5NM_03264335Interferon regulatory factor 51.521.52
CD84AF054818CD84 molecule2.553.40
Inflammatory response
IL1BNM_000576Interleukin 1, beta1.521.80
IL24NM_006850Interleukin 242.842.19
IL2RAK03122Interleukin 2 receptor, alpha1.861.48
S100A8AW238654S100 calcium-binding protein A83.651.86
Cell proliferation
FGFR2NM_022975Fibroblast growth factor receptor 21.562.89
RAC2NM_002872Ras-related C3 botulinum toxin substrate 22.311.53
CDK2AB012305Cyclin-dependent kinase 21.631.78
DLG1AL121981Discs, large homolog 1 (Drosophila)1.571.74
Cell differentiation
GAS7BC006454Growth arrest-specific 7−2.03−1.90
SRD5A1NM_001047Steroid-5-alpha-reductase, alpha polypeptide 1−2.53−1.54
VAMP5NM_006634Vesicle-associated membrane protein 5−1.71−1.58
ZAKNM_016653Sterile alpha motif and leucine zipper containing kinase AZK−2.02−1.71
Cell–cell junctions
VCLNM_014000Vinculin−1.68−1.56
CTNND1NM_001331Catenin (cadherin-associated protein), delta 1−2.33−1.75
CTNNA1NM_001903Catenin (cadherin-associated protein), alpha 1, 102 kDa−2.49−1.57
COL8A2NM_005202Collagen, type VIII, alpha 2−1.62−1.64
Metalloproteases
ADAM8AI814527ADAM metallopeptidase domain 81.941.57
ADAM9NM_003816ADAM metallopeptidase domain 92.811.48
ADAM17AI797833ADAM metallopeptidase domain 171.511.56
Receptors and signal transduction
IL2RAK03122Interleukin 2 receptor, alpha1.861.48
IRF5NM_03264335Interferon regulatory factor 51.521.52
IL6RS72848Interleukin 6 receptor1.792.76
Cytoskeleton
FGD6NM_018351FYVE, RhoGEF, and pH domain containing 6−2.40−1.48
ABLIM3NM_014945Actin-binding LIM protein family, member 31.861.49
PFN2NM_002628Profilin 21.511.47
Ion transport
SLC24A1AF026132Solute carrier family 24 (Na/K/Ca exchanger), member 11.591.95
SLC30A1AI972416Solute carrier family 30 (zinc transporter), member 11.941.55
SLC4A4AF069510Solute carrier family 4, NaHCO3 cotransporter, member 41.521.92
EGFR signaling pathway
AKT2NM_001626v-akt murine thymoma viral oncogene homolog 22.362.19
PIK3R1NM_181523Phosphoinositide-3-kinase, regulatory subunit 1 (alpha)2.761.54
PTPN12S69182Protein tyrosine phosphatase, nonreceptor type 122.271.50

In this regard, it is worthwhile mentioning that patients with NCGS have normal to mildly inflamed mucosa (Marsh 0-1), while partial or subtotal villous atrophy and crypt hyperplasia are hallmarks of CD. Nevertheless, we cannot exclude that some NCGS patients, especially those positive for HLA-DQ2 and/or DQ8, may switch to classical CD in the course of the follow-up.

Since a large part of DEGs in the NCGS paralleled the modulation of genes seen in human T84 cells treated with antirotavirus Vp7 peptide antibodies, we next aimed at identifying the presence of such antibodies in sera of NCGS patients. We therefore tested in ELISA assay the sera from 16 NCGS patients and 20 healthy subjects for the detection of antirotavirus VP7 peptide antibodies. We found that these antibodies were present in 6 out of 16 (37%) NCGS patients while were not detected in the sera of healthy subjects. Figure 5(c) shows that the levels of such antibodies are significantly different in the two set of tested samples (). The detection of these antibodies in NCGS patients may be relevant to the pathogenesis of the NCGS given their ability to modulate sets of genes in intestinal epithelial cells as we previously demonstrated [6].

Taken together, the modulation of highly connected genes associated to the viral infection process and the presence of anti-VP7 antibodies in the sera of some NCGS patients may suggest that a link also exists between immune response to rotavirus infection and NCGS.

In this perspective, since anti-VP7 rotavirus antibodies are often present before the onset of CD, preceding the detection of celiac specific autoantibodies, [6] it is tempting to speculate that NCGS patients with CD genetic predisposition (DQ2/DQ8) and presence of anti-VP7 antibodies may develop CD in the course of the follow-up.

Therefore, to further clarify the relationship between rotavirus infection and NCGS, we decided to perform an integrative bioinformatics analysis using the dataset GSE50628 downloaded from GEO (Gene Expression Omnibus) database (http://www.ncbi.nlm.nih.gov/geo/) that included samples of peripheral blood cells from patients affected by acute rotavirus infection (named in the paper “Rotavirus infection dataset”). This dataset was analysed to detect significantly modulated genes (Additional Table 2), and a comprehensive GO analysis was carried out on all datasets including NCGS, Rotavirus infection, and T84 datasets that we analysed in our previous work [6].

We then searched on the four datasets for the presence of genes associated to GO terms containing the words “virus” and/or “viral” and we found in all datasets a great number of such terms to which modulated genes were connected/related.

The searched terms explored a wide range of biological processes associated to viral infection from the entry of virus in the host cell, viral transcription and gene expression, modulation of host physiology by virus to cellular response to virus.

All the GO terms retrieved in the three datasets are listed in Additional Table 3.

Table 5 shows selected genes modulated in the three datasets that are ascribed to the most representative GO terms, including viral transcription, viral gene expression, response to virus, viral genome replication, and viral life cycle.


Gene symbolGene titleFC

NCGS dataset
Viral transcription/gene expression
  RANBP2RAN-binding protein 21.98
  RPL27ARibosomal protein L27a3.22
  RPL37ARibosomal protein L37a2.94
  RPLP2Ribosomal protein, large, P22.15
  RPS10Ribosomal protein S102.66
  RPS11Ribosomal protein S112.49
  TPRTranslocated promoter region, nuclear basket protein4.40
Response to virus
  RELAv-rel reticuloendotheliosis viral oncogene homolog A (avian)1.54
  IKBKBInhibitor of kappa light polypeptide gene enhancer in B cells, kinase beta2.69
  IRF5Interferon regulatory factor 51.52
  IFNA17Interferon, alpha 171.59
  DDX3XDEAD (Asp-Glu-Ala-Asp) box polypeptide 3, X-linked3.22
  STAT2Signal transducer and activator of transcription 2, 113 kDa1.59
  STAT1Signal transducer and activator of transcription 1, 91 kDa2.73
  IRF3Interferon regulatory factor 31.67
  DDX17DEAD (Asp-Glu-Ala-Asp) box helicase 174.75
Viral life cycle
  TPRTranslocated promoter region, nuclear basket protein4.40
  ATG16L1Autophagy-related 16-like 1 (S. cerevisiae)1.87
  HSP90AB1Heat shock protein 90 kDa alpha (cytosolic), class B member 11.87
  RANBP2RAN-binding protein 21.98
  DPP4Dipeptidyl-peptidase 41.61
  DDX6DEAD (Asp-Glu-Ala-Asp) box helicase 64.70
  HTATSF1HIV-1 Tat specific factor 12.23
  SLAMF1Signaling lymphocytic activation molecule family member 11.65
  T84 dataset
Viral transcription/gene expression
  RPL27ARibosomal protein L27a1.68
  RPS2Ribosomal protein S21.99
  RPS6Ribosomal protein S61.51
Response to virus
  IFIH1Interferon induced with helicase C domain 11.52
  IFNA7Interferon, alpha 71.53
  IFIT3Interferon-induced protein with tetratricopeptide repeats 31.46
  IFNA4Interferon, alpha 41.73
  IFI44Interferon-induced protein 441.46
  IFNGR1Interferon gamma receptor 11.67
  IFNA17Interferon, alpha 171.56
Viral life cycle
  CTBP1C-terminal-binding protein 11.58
  ADRBK1Adrenergic, beta, receptor kinase 11.46
  HCRP1Hepatocellular carcinoma-related HCRP11.61
  C9Orf28Chromosome 9 open reading frame 281.56
Rotavirus infection dataset
Viral transcription/gene expression
  NUP58Nucleoporin 58 kDa6.38
  RPS16Ribosomal protein S162.10
  DENRDensity-regulated protein2.11
Response to virus
  XPR1Xenotropic and polytropic retrovirus receptor 11.72
  CNOT7CCR4-NOT transcription complex subunit 73.54
  CD40CD40 molecule, TNF receptor superfamily member 52.72
  ITCHItchy E3 ubiquitin protein ligase2.26
  ARF1ADP-ribosylation factor 11.91
  BCL2L11BCL2-like 11 (apoptosis facilitator)3.21
  BCL2L1BCL2-like 13.37
  IKBKEInhibitor of kappa light polypeptide gene enhancer in B cells, kinase ɛ1.50
  DDX17DEAD (Asp-Glu-Ala-Asp) box helicase 172.13
Viral life cycle
  NUP153Nucleoporin 153 kDa2.01
  VPS37AVacuolar protein sorting 37 homolog A (S. cerevisiae)1.90
  XPR1Xenotropic and polytropic retrovirus receptor 11.72
  UBBUbiquitin B1.75
  ITCHItchy E3 ubiquitin protein ligase2.26
  NUP58Nucleoporin 58 kDa6.38
  TNFRSF4Tumor necrosis factor receptor superfamily, member 41.94
  SCARB2Scavenger receptor class B, member 21.96

Moreover, the GO analysis of the abovementioned datasets was complemented by searching for transcripts involved in immune response.

In the “T84 dataset,” we found upregulation for the T cell costimulatory molecule ICOSLG, the transcriptional regulator that is crucial for the development and inhibitory function of regulatory T cells, [38] interleukin-6 that is pivotal for the development of Th-17 cells [39], and FCGR2B that is involved in the phagocytosis of immune complexes and in modulation of antibody production by B cells [40] (Table 6).


Gene symbolGene titleFC

Immune response
CCR2Chemokine (C-C motif) receptor 2−1.48
CXCL1Chemokine (C-X-C motif) ligand 11.81
CXCL13Chemokine (C-X-C motif) ligand 13−5.52
GATA3GATA-binding protein 3−6.62
TROVE2TROVE domain family, member 2−1.64
ICOSLGInducible T cell costimulator ligand2.51
FCGR1AFc fragment of IgG, high affinity Ia, receptor (CD64)2.00
FOXP3Forkhead box P31.49
ULBP1UL16-binding protein 1−1.77
ITGA4Integrin, alpha 4 (antigen CD49D, alpha 4 subunit of VLA-4 receptor)1.48
CXCL9Chemokine (C-X-C motif) ligand 91.59
CSF3Colony-stimulating factor 3 (granulocyte)1.46
IL6Interleukin 6 (interferon, beta 2)1.51
CD84CD84 molecule3.40
FCGR2BFc fragment of IgG, low affinity IIb, receptor (CD32)1.77
LAT2Linker for activation of T cells family, member 21.85
C7Complement component 73.11
CCR1Chemokine (C-C motif) receptor 13.27
CCR3Chemokine (C-C motif) receptor 32.80
CFPComplement factor properdin2.92
IL24Interleukin 242.19
IL8Interleukin 81.86
CXCL10Chemokine (C-X-C motif) ligand 101.82
IL1F7Interleukin 1 family, member 7 (zeta)−2.26
IKBKBInhibitor of kappa light polypeptide gene enhancer in B cells, kinase beta−2.25
CCL11Chemokine (C-C motif) ligand 111.96
Type I interferon signaling
Cellular response to interferon alpha
 FCARFc fragment of IgA, receptor for2.15
Type I interferon signaling
 IFNA16Interferon, alpha 161.58
 STAT1Signal transducer and activator of transcription 1, 91 kDa−1.46
 IFNA17Interferon, alpha 171.56
 YY1YY1 transcription factor−2.24
 IFNA4Interferon, alpha 41.73
 IRF8Interferon regulatory factor 8 interferon regulatory factor 8−1.68
 IFNA5Interferon, alpha 5−2.85
 IRF2Interferon regulatory factor 21.58
 IFNA8Interferon, alpha 82.23
 IRF5Interferon regulatory factor 51.52
 IFI6Interferon, alpha-inducible protein 61.56
 IFNA6Interferon, alpha 62.08
Positive regulation of interferon alpha production
 IRF5Interferon regulatory factor 51.52
Positive regulation of interferon beta production
 DDX3XDEAD (Asp-Glu-Ala-Asp) box polypeptide 3, X-linked−1.49
 IRF5Interferon regulatory factor 51.52
Negative regulation of interferon beta production
 LILRB1Leukocyte immunoglobulin-like receptor, subfamily B, member 1−1.60
Positive regulation of Type I interferon production
 IFI16Interferon, gamma-inducible protein 16−1.68
 CREBBPCREB-binding protein (Rubinstein-Taybi syndrome)1.51
Negative regulation of Type I interferon production
 CYLDCylindromatosis (turban tumor syndrome)−3.04
Gamma interferon signaling
Cellular response to Interferon Gamma signaling
 FCARFc fragment of IgA, receptor for2.15
 MRC1Mannose receptor, C type 12.52
 SYNCRIPSynaptotagmin-binding, cytoplasmic RNA-interacting protein−1.69
 CCL8chemokine (C-C motif) ligand 81.63
Interferon gamma signaling
 STAT1Signal transducer and activator of transcription 1, 91 kDa−1.46
 MID1Midline 1 (Opitz/BBB syndrome)−1.99
 HLA-DRB4Major histocompatibility complex, class II, DR beta 42.39
 SDK1Sidekick homolog 1 (chicken)1.61
 IFNGR1Interferon gamma receptor 1 interferon gamma receptor 11.67
Negative regulation of gamma interferon production
 LILRB1Leukocyte immunoglobulin-like receptor, subfamily B, member 1−1.60
 CD244CD244 molecule, natural killer cell receptor 2B4−1.69
 IL10Interleukin 10−3.56
Positive regulation of gamma interferon production
 FOXP3Forkhead box P31.49
 IL1BInterleukin 1, beta1.80
Toll-like receptor signaling
TANKTRAF family member-associated NFKB activator−1.91
CHUKConserved helix-loop-helix ubiquitous kinase−1.72
ELK1ELK1, member of ETS oncogene family3.70
MAP3K8Mitogen-activated protein kinase kinase kinase 8−2.16
TLR6Toll-like receptor 62.43
TLR1Toll-like receptor 11.57
TLR7Toll-like receptor 7−1.64
MAP3K7Mitogen-activated protein kinase kinase kinase 7−1.89
LY96Lymphocyte antigen 96−1.81
NFKB2Nuclear factor of kappa light polypeptide gene enhancer in B cells 2 (p49/p100)1.54
RELv-rel reticuloendotheliosis viral oncogene homolog (avian)−1.82
PTGS2Prostaglandin-endoperoxide synthase 2 (prostaglandin G/H synthase and cyclooxygenase)1.76
TNFAIP3Tumor necrosis factor, alpha-induced protein 31.73
MAP2K3Mitogen-activated protein kinase kinase 31.59
IKBKBInhibitor of kappa light polypeptide gene enhancer in B cells, kinase beta−2.25
TLR3Toll-like receptor 3−2.03
IFNB1Interferon, beta 1, fibroblast−1.84
IRAK3Interleukin-1 receptor-associated kinase 31.70
TLR4Toll-like receptor 41.46
IKBKEInhibitor of kappa light polypeptide gene enhancer in B cells, kinase epsilon2.06
MAP2K2Mitogen-activated protein kinase kinase 21.98
TLR2Toll-like receptor 2−2.30

In the “Rotavirus infection” dataset, we found upregulation for molecules that are crucial in the immune response including the BLK gene, involved in transmitting signals through surface immunoglobulins, supporting the pro-B to pre-B transition, [41] MR1/MAIT playing a role in the development of the mucosal-associated invariant T cells (MAIT), [42] TNFRSF4 involved in T cell proliferation [43], and HCST/DAP10 playing a role in triggering cytotoxicity against both stressed and infected by virus target cells [44] (Table 7).


Gene symbolGene titleFC

Immune response
ADGRE3Adhesion G protein-coupled receptor E3;ADGRE3;ortholog−3.35
ADIPOQAdiponectin, C1Q and collagen domain containing−1.60
BLKBLK proto-oncogene, Src family tyrosine kinase1.72
BRAFB-Raf proto-oncogene, serine/threonine kinase1.57
BTKBruton agammaglobulinemia tyrosine kinase−1.59
C1QTNF9C1q and tumor necrosis factor related protein 9−1.69
CD109CD109 molecule−1.84
CD79BCD79b molecule, immunoglobulin-associated beta−1.67
CLEC7AC-type lectin domain family 7, member A−1.62
CMIPc-Maf inducing protein−3.50
CSF2RAColony-stimulating factor 2 receptor, alpha, low-affinity (granulocyte-macrophage)−2.30
CXCL2Chemokine (C-X-C motif) ligand 2−3.76
CXCL8Chemokine (C-X-C motif) ligand 8−8.65
FCER1AFc fragment of IgE, high affinity I, receptor for; alpha polypeptide−5.64
HCSTHematopoietic cell signal transducer1.85
IL18BPInterleukin 18 binding protein1.56
JAG1Jagged 1−2.06
KLRB1Killer cell lectin-like receptor subfamily B, member 1−5.99
MAP3K11Mitogen-activated protein kinase kinase kinase 111.55
MASP1Mannan-binding lectin serine peptidase 1−1.50
MR1Major histocompatibility complex, class I-related8.43
PLEKHN1Pleckstrin homology domain containing, family N member 1−1.99
PPP2R2CProtein phosphatase 2, regulatory subunit B, gamma−1.84
PPP3CAProtein phosphatase 3, catalytic subunit, alpha isozyme−1.89
PSME3Proteasome activator subunit 31.91
PVRPoliovirus receptor−1.59
STAT5BSignal transducer and activator of transcription 5B−2.06
TNFRSF10CTumor necrosis factor receptor superfamily, member 10c decoy without an intracellular domain−1.75
TNFRSF4Tumor necrosis factor receptor superfamily, member 41.94
Type I interferon signaling
Positive regulation of Type I interferon production
 EP300E1A-binding protein p300−1.56
 POLR3GPolymerase (RNA) III (DNA directed) polypeptide G (32kD)−1.98
 CREBBPCREB-binding protein−1.83
 LRRFIP1Leucine rich repeat (in FLII) interacting protein 1−2.14
 SOCS1Suppressor of cytokine signaling 12.32
Negative regulation of Type I interferon production
 UBBUbiquitin B1.75
 ITCHItchy E3 ubiquitin protein ligase2.26
 TAX1BP1Tax1 (human T cell leukemia virus type I) binding protein 1−4.01
Negative regulation of Type I interferon pathway
 PTPN2Protein tyrosine phosphatase, nonreceptor type 22.10
Positive regulation of interferon beta production
 ZBTB20Zinc finger and BTB domain containing 204.27
Negative regulation of interferon Beta production
 PTPRSProtein tyrosine phosphatase, receptor type, S−2.00
 CACTINCactin, spliceosome C complex subunit−2.53
Cellular response to interferon alpha
 TPRTranslocated promoter region, nuclear basket protein−2.55
Negative regulation of interferon alpha production
 PTPRSProtein tyrosine phosphatase, receptor type, S−2.00
Type I interferon signaling pathway
 JAK1Janus kinase 11.79
 IFI27Interferon, alpha-inducible protein 2775.26
 IFI27L2Interferon, alpha-inducible protein 27-like 2−1.59
 IKBKEInhibitor of kappa light polypeptide gene enhancer in B cells, kinase epsilon1.50
 TPRTranslocated promoter region, nuclear basket protein−2.55
Positive regulation of Type I interferon pathway
 MMEMembrane metallo-endopeptidase−5.54
Gamma interferon signaling
JAK1Janus kinase 11.79
HLADQB1Major histocompatibility complex, class II, DQ beta 1−36.43
HLADQA1Major histocompatibility complex, class II, DQ alpha 1−37.95
PIAS3Protein inhibitor of activated STAT 32.11
HLADRB1Major histocompatibility complex, class II, DR beta 1−10.91
MAPK8Mitogen-activated protein kinase 8−2.28
MAPK1Mitogen-activated protein kinase 1−2.23
Regulation of interferon gamma signaling pathway
 PTPN2Protein tyrosine phosphatase, nonreceptor type 22.10
Positive regulation of interferon gamma production
 PDE4BPhosphodiesterase 4B, cAMP-specific−1.77
 ZFPM1Zinc finger protein, FOG family member 11.75
Negative regulation of interferon gamma production
 HLADRB1Major histocompatibility complex, class II, DR beta 1−10.91
 RARARetinoic acid receptor, alpha−7.60
 FOXP3Forkhead box P3−2.14
Cellular response to interferon gamma
 SLC26A6Solute carrier family 26 (anion exchanger), member 61.95
 DAPK3Death-associated protein kinase 3−1.62
 CD40CD40 molecule, TNF receptor superfamily member 52.72
 MEFVMediterranean fever−4.83
 SNCASynuclein alpha8.62
 MRC1Mannose receptor, C type 1−1.93
Toll-like receptors signaling pathway
TANKTRAF family member-associated NFKB activator−1.91
NFKBIANuclear factor of kappa light polypeptide gene enhancer in B cells inhibitor, alpha−1.76
MAPK8Mitogen-activated protein kinase 8−2.28
IKBKEInhibitor of kappa light polypeptide gene enhancer in B cells, kinase epsilon1.50
MAPK1Mitogen-activated protein kinase 1−2.23
JUNjun proto-oncogene−1.91

Interestingly, in all the datasets, we found the presence of modulated genes involved in the type I interferon signaling, that is central in autoimmunity, and in molecular pathways involved in the immune response to viral infection, including the Toll-like receptors, and the type I and gamma interferon pathways (see Tables 2, 6, and 7).

Taken together, our data seem to indicate that NCGS has features of autoimmunity and that an immune response to rotavirus may play a role in some cases of NCGS.

4. Conclusions

NCGS is an emerging new clinical entity lacking specific diagnostic biomarkers which has been reported to occur in 6–10% of the population. Interestingly, up to 50% of these patients carry HLA-DQ2 and/or HLA-DQ8 genes. NCGS patients may complain gastrointestinal (e.g., diarrhoea/constipation, abdominal pain, bloating) and/or extraintestinal symptoms (“foggy mind,” headache, dermatitis, etc.) which recede with GFD. The pathogenesis of NCGS is still unclear and the data, so far obtained, suggest a predominant activation of the innate immune responses.

Our data indicate a concomitant involvement of the adaptive immune system and suggest that NCGS may have an autoimmune origin. This is based both on gene expression data (i.e., TH17-IFNA I signatures) and on the presence of TH17 cells and of serological markers of autoimmunity in NCGS. Our results also indicate a possible involvement of rotavirus infection in the pathogenesis of NCGS, similarly to what we have previously shown in CD.

Conflicts of Interest

The authors declare that there is no conflict of interest regarding the publication of this paper.

Authors’ Contributions

Antonio Puccetti, Daniele Saverino, Roberta Opri, Claudio Lunardi, and Marzia Dolcino equally contributed to this paper.

Supplementary Materials

Supplementary 1. Additional Table 1: genes modulated in NGCS samples versus healthy controls.

Supplementary 2. Additional Table 2: genes modulated in the “Rotavirus infection” dataset.

Supplementary 3. Additional Table 3: GO terms containing the words “virus” and “viral” to which are associated genes modulated in the three datasets.

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