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Journal of Immunology Research
Volume 2018, Article ID 9419204, 26 pages
https://doi.org/10.1155/2018/9419204
Research Article

Immune Response to Rotavirus and Gluten Sensitivity

1Immunology Area, Pediatric Hospital Bambino Gesù, Viale San Paolo 15, 00146 Rome, Italy
2Department of Experimental Medicine, Section of Histology, University of Genova, Via G.B. Marsano 10, 16132 Genova, Italy
3Department of Experimental Medicine, Section of Human Anatomy, University of Genova, Via De Toni 14, 16132 Genova, Italy
4Immunology Unit, University Hospital of Verona, Piazzale L.A. Scuro 10, 37134 Verona, Italy
5Department of Medicine, University of Verona, Piazzale L.A. Scuro 10, 37134 Verona, Italy

Correspondence should be addressed to Marzia Dolcino; moc.liamg@oniclodaizram

Received 31 July 2017; Revised 18 December 2017; Accepted 25 December 2017; Published 15 March 2018

Academic Editor: Peirong Jiao

Copyright © 2018 Antonio Puccetti et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.

Table 1: Biological processes and pathways that were enriched in the NCGS dataset.

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).

Table 2: Genes modulated in NCGS patients that are involved in immune response and molecular signalings.

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).

Figure 1: Flow cytometric analysis of CD4+T cells releasing IL-17 in patients with NCGS. Panel displays the mean percentage of CD4+T cells releasing IL-17 of 10 healthy donors and 8 NCGS patients. PBMCs were stimulated overnight with anti-CD3/-CD28-coated beads. value calculated with the Mann–Whitney nonparametric statistical test was 0.0159.

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.

Figure 2: Serum levels of selected soluble mediators in NCGS patients and in normal subject sera. The histograms represent the mean of the results obtained in 20 healthy donors and in 16 NCGS patients. values calculated with the Wilcoxon nonparametric statistical test for paired samples were: for sCTLA-4, for sPD-1, and for sgp130.

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.

Figure 3: Protein-protein interaction (PPI) network of DEGs in NCGS patients.
Figure 4: Modules originated from the network analysis of DEGs in NCGS patients.

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).

Table 3: Biological processes and pathways enriched in the 15 modules.

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.

Figure 5: (a) List of diseases which are most likely to be statistically significantly associated and compatible with the transcriptional profile observed in NCGS. (b) DEGs in NCGS showing a modulation consistent with a viral infection process. (c) Detection of antibodies directed against the rotavirus VP7 peptide in the sera of patients with NCGS. Each circle represents a measurement for one patient, and the dashed horizontal line indicates the threshold for positivity (O.D. 0.140). The statistical value was calculated with the Mann–Whitney test ().

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].

Table 4: Selection of DEGs in NCGS that are also modulated in human T84 cells after stimulation with anti-VP7 rotavirus peptide antibodies.

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.

Table 5: Genes modulated in the three datasets playing a role in selected GO BPs related to the viral infection process.

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).

Table 6: Selection of genes modulated in human T84 cells after stimulation with anti-VP7 rotavirus peptide antibodies, involved in immune response and in molecular signaling related to the viral infection process.

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).

Table 7: Selection of genes modulated in PBCs in course of the acute phase of rotavirus infection, involved in immune response and in molecular signaling related to the viral infection process.

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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