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Subclass Profile of IgG Antibody Response to Gluten Differentiates Nonceliac Gluten Sensitivity From Celiac Disease

  • Author Footnotes
    ∗ Authors share co-first authorship.
    Melanie Uhde
    Footnotes
    ∗ Authors share co-first authorship.
    Affiliations
    Department of Medicine, Columbia University Medical Center, New York, New York

    Institute of Human Nutrition, Columbia University Medical Center, New York, New York

    Celiac Disease Center, Columbia University Medical Center, New York, New York
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  • Author Footnotes
    ∗ Authors share co-first authorship.
    Giacomo Caio
    Footnotes
    ∗ Authors share co-first authorship.
    Affiliations
    Department of Medical Sciences, University of Ferrara, Arcispedale St Anna, Ferrara, Italy

    Celiac Disease Center and Mucosal Immunology and Biology Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
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  • Roberto De Giorgio
    Affiliations
    Department of Medical Sciences, University of Ferrara, Arcispedale St Anna, Ferrara, Italy
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  • Peter H. Green
    Affiliations
    Department of Medicine, Columbia University Medical Center, New York, New York

    Celiac Disease Center, Columbia University Medical Center, New York, New York
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  • Umberto Volta
    Affiliations
    Department of Medical and Surgical Sciences, University of Bologna, Italy
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  • Armin Alaedini
    Correspondence
    Correspondence Address correspondence to: Armin Alaedini, PhD, Columbia University Medical Center, 1130 Saint Nicholas Avenue, New York, New York 10032. fax: (212) 851-4590.
    Affiliations
    Department of Medicine, Columbia University Medical Center, New York, New York

    Institute of Human Nutrition, Columbia University Medical Center, New York, New York

    Celiac Disease Center, Columbia University Medical Center, New York, New York

    Department of Medicine, New York Medical College, Valhalla, New York
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  • Author Footnotes
    ∗ Authors share co-first authorship.
Open AccessPublished:July 20, 2020DOI:https://doi.org/10.1053/j.gastro.2020.07.032

      Keywords

      Abbreviations used in this paper:

      CD (celiac disease), NCGS (nonceliac gluten or wheat sensitivity)
      Celiac disease (CD) is an autoimmune enteropathy triggered by exposure to gluten proteins, leading to intestinal inflammation and villous atrophy in genetically predisposed individuals. It is associated with robust B cell and antibody responses to gluten and to the transglutaminase 2 autoantigen.
      • Caio G.
      • et al.
      In contrast, nonceliac gluten or wheat sensitivity (NCGS) is a poorly understood clinical entity defined by onset of symptoms in response to ingestion of gluten-containing food without the prerequisite serologic or histologic features of CD.
      • Volta U.
      • et al.
      There are no established biomarkers yet for NCGS, but recent research points to a biological basis, revealing a state of systemic immune activation in conjunction with a compromised intestinal epithelium.
      • Volta U.
      • et al.
      ,
      • Uhde M.
      • et al.
      We and others have demonstrated a significant increase in IgG antibody to gluten in NCGS at levels similar to CD.
      • Volta U.
      • et al.
      ,
      • Uhde M.
      • et al.
      Accordingly, it has been speculated that an enhanced IgG response to gluten may be a common link between CD and NCGS.
      • Volta U.
      • et al.
      However, whether and how B cell reactivity to gluten may differ in these conditions, especially in the context of possible relevance to intestinal pathology, have not been examined.
      In this study, we extend earlier data to show that the anti-gluten IgG antibody in NCGS is significantly different from CD in subclass distribution and in its relationship to intestinal cell damage. The findings are suggestive of a sustained primary B cell response to gluten in CD, despite the condition’s chronicity, and a more advanced and tolerogenic immune response to gluten in NCGS.

      Methods

      Detailed methods are available in the Supplementary Material.

      Results

      Demographic and clinical characteristics of study cohorts are included in Supplementary Table 1.
      The anti-gliadin IgG response in CD patients was composed primarily of IgG1 and IgG3, which were significantly increased in comparison with the healthy and NCGS cohorts (Figure 1A and C). There was a modest elevation in anti-gliadin IgG2 compared with the healthy group and no comparative increase in the IgG4 subclass (Figure 1B and D). Within the NCGS cohort, however, the lower contributions of anti-gliadin IgG1 and IgG3 in comparison with CD was compensated by significantly elevated IgG4 (compared with CD and healthy cohorts) and IgG2 (compared with healthy cohort) (Figure 1AD). No significant association was detected in this cohort between any anti-gliadin IgG subclass and the Marsh type, HLA-DQ2/DQ8 status, or eligibility for irritable bowel syndrome or functional dyspepsia diagnostic criteria.
      Figure thumbnail gr1
      Figure 1Distribution of IgG subclass antibody reactivity to wheat gluten and relationship with intestinal epithelial cell damage. (A–D) Serum levels of IgG1 (A), IgG2 (B), IgG3 (C), and IgG4 (D) antibody to Prolamine Working Group gliadin in cohorts of healthy controls and IgG anti-gliadin–positive CD and NCGS patients, as determined by enzyme-linked immunosorbent assay. Horizontal red lines indicate the median for each cohort. (E) Principal component analysis score plot of the entire anti-gliadin IgG subclass dataset (IgG1, IgG2, IgG3, and IgG4) for CD (red) and NCGS (green) patients. Subjects are plotted in 3 dimensions using the first through third principal components (PC1, PC2, and PC3). (F–M) Relationship between FABP2 expression and IgG subclass antibody reactivity to gluten in CD and NCGS patients. Serum FABP2 concentrations in CD patients correlated with levels of anti-gliadin IgG3 antibody (H). In contrast, the NCGS cohort was characterized by a correlation between the levels of anti-gliadin IgG4 antibody and FABP2 concentration (M) and a weaker correlation between anti-gliadin IgG1 antibody and FABP2 (J).
      The score plot for the principal component analysis of the IgG subclass data demonstrated clustering of the CD and NCGS subjects into discernible groups, further demonstrating the contrasting subclass distributions and suggesting potential biomarker value in these data (Figure 1E).
      Serum concentrations of intestinal FABP2, a specific marker of intestinal epithelial cell damage,
      • Pelsers M.M.
      • et al.
      were similarly elevated in the CD and NCGS groups in comparison with healthy cohort (P < .0001 for each).
      • Uhde M.
      • et al.
      Within the CD group, only the anti-gliadin IgG3 correlated with FABP2 (Figure 1H). This correlation was similar in strength to that between anti-gliadin IgG3 and anti–transglutaminase 2 IgA (r = 0.505, P = .001). In contrast, FABP2 levels in the NCGS group correlated with anti-gliadin IgG4 and weakly with IgG1 (Figure 1M and J).

      Discussion

      The observed contrast in the IgG subclass distribution and relationship with FABP2 release in NCGS vs CD are likely reflective of differences in the evolution and disease relevance of B cell immune responses in the 2 conditions. Among IgG subclasses, IgG1 and IgG3 are the most potent activators of complement and efficient at binding a wide range of FcγRs.
      • Vidarsson G.
      • et al.
      In contrast, IgG2 antibodies generally require higher epitope densities for complement activation and display limited binding to FcγRs.
      • Vidarsson G.
      • et al.
      IgG4 antibodies contain structural properties that further distinguish them from other immunoglobulin isotypes and IgG subclasses. They bind weakly to Fc receptors and to complement, and are inefficient at crosslinking of antigens or forming immune complexes.
      • Vidarsson G.
      • et al.
      IgG4 has also been shown to induce an anti-inflammatory M2-like macrophage phenotype through inhibition of interferon-gamma signaling.
      • Swisher J.F.
      • et al.
      Considering these properties, the observed increase in the gluten-reactive IgG2 and IgG4 subclasses and the correlation between the IgG4 subclass and FABP2 in NCGS may point to a protective response aimed at dampening the inflammatory effect of other antibodies and immune cells. It is intriguing that these antibody responses are largely absent in CD, where there is instead a correlation between the IgG3 and FABP2.
      The evolution in subclass switching of the IgG response to an antigen follows a 1-way direction from IgG3 to IgG1, IgG2, and IgG4 over time. Once a B cell has switched to a downstream subclass, it does not return to a preceding one.
      • Valenzuela N.M.
      • et al.
      It has been suggested that IgG2 and IgG4 are part of the immunologic memory toward harmless and recurring antigens—an advanced immune response stimulated by a more extensive antigen exposure.
      • de Jong B.G.
      • et al.
      In addition, the variable regions of IgG2 and IgG4 usually display greater levels of somatic hypermutation than IgG1 or IgG3, which can result in higher affinity for target antigens.
      • Valenzuela N.M.
      • et al.
      As such, the prominence of the IgG3 subclass and its relationship with the autoimmune response and intestinal cell turnover in CD is suggestive of repeated activation of gluten-specific naïve B cells rather than of memory cells, in response to gluten exposure, despite the chronic nature of the disease. Pathways involved in this phenomenon may represent a source of molecular targets for therapeutic intervention. Possible shortfalls of this study include the lack of other disease controls and the fact that these observational data cannot establish a causal connection between subclass differences and the disease process.
      These data warrant further examination of the evolution of gluten-reactive B-cell response and subclass switching in CD and NCGS. In addition, information on other aspects of B cell and antibody variability, including affinity, glycosylation profile, and epitope specificity, is expected to contribute to a greater understanding of differences in the immune response to gluten and its relationship with disease pathophysiology in the two conditions. In conjunction with other previously identified markers, these components of the immune response to gluten are expected to provide additional biomarkers that may be informative in the context of stratifying potential disease subsets with varying mechanisms, prognoses, and responses to therapy.

      Acknowledgments

      The authors thank Dr Mary Ajamian for technical support and critical review of the manuscript.

      CRediT Authorship Contributions

      Melanie Uhde, PhD (Data curation: Lead; Formal analysis: Lead; Methodology: Equal; Writing – original draft: Supporting). Giacomo Caio, MD (Data curation: Supporting; Methodology: Equal; Resources: Equal; Writing – review & editing: Supporting). Roberto De Giorgio, MD (Data curation: Supporting; Investigation: Supporting; Resources: Supporting; Writing – review & editing: Supporting). Peter Green, MD (Investigation: Supporting; Methodology: Supporting; Resources: Supporting; Writing – review & editing: Supporting). Umberto Volta, MD (Data curation: Supporting; Funding acquisition: Supporting; Investigation: Supporting; Resources: Supporting; Writing – review & editing: Supporting). Armin Alaedini, PhD (Conceptualization: Lead; Data curation: Lead; Funding acquisition: Lead; Investigation: Supporting; Methodology: Supporting; Project administration: Lead; Resources: Lead; Supervision: Lead; Writing – original draft: Lead).

      Supplementary Methods

       Patients and Controls

      The study included 80 individuals with NCGS who met the diagnostic criteria proposed by an expert group
      • Catassi C.
      • et al.
      and who were identified using a previously described structured symptom questionnaire
      • Volta U.
      • et al.
      ,
      • Uhde M.
      • et al.
      (a modified version of the Gastrointestinal Symptom Rating Scale designed to rate symptoms commonly associated with NCGS). All NCGS subjects reported experiencing gastrointestinal or extra-intestinal symptoms after ingestion of gluten-containing foods, including wheat, rye, or barley. The most common gastrointestinal symptoms included bloating, abdominal pain, diarrhea, nausea, and heartburn, and the most prominent extra-intestinal symptoms were fatigue, headache, anxiety, cognitive difficulties, and numbness in arms and legs. The reported symptoms in all subjects improved or disappeared when those foods were withdrawn for a period of 6 months, and recurred when they were re-introduced for a period of up to 1 month. Individuals were excluded if they were already on a restrictive diet or had used nonsteroidal anti-inflammatory drugs within the past 6 months, if they were positive for the CD-specific intestinal histologic findings or the IgA anti-endomysial or -transglutaminase 2 autoantibodies, or if they were positive for wheat allergy-specific IgE serology or skin prick test. A history of autoimmunity or autoantibody reactivity was present in 20 NCGS patients (25%), represented mainly by Hashimoto’s thyroiditis and by antinuclear antibody positivity (demonstrated by indirect immunofluorescence on HEp-2 cells), similar to previously published data.
      • Pelsers M.M.
      • et al.
      ,
      • Vidarsson G.
      • et al.
      In addition, 49 patients (61.2%) met criteria for irritable bowel syndrome and 63 (78.8%) for functional dyspepsia according to Rome IV.
      • Swisher J.F.
      • et al.
      ,
      • Valenzuela N.M.
      • et al.
      All patients underwent an esophagogastroduodenoscopy with gastric biopsy to rule out Helicobacter pylori infection. A total of 6 intestinal biopsies, including 2 from the duodenal bulb and 4 from the distal duodenum, were taken from each individual. The study also included 40 patients with biopsy-proven CD and 40 healthy subjects, recruited as part of the same protocol that included the NCGS individuals. All cases of CD were positive for IgA anti-endomysial and IgA anti-transglutaminase 2 autoantibodies, biopsy-proven, and diagnosed according to established criteria.
      • Rubio-Tapia A.
      • et al.
      Rome IV,
      • Swisher J.F.
      • et al.
      ,
      • Catassi C.
      • et al.
      Gastrointestinal Symptom Rating Scale,
      • Svedlund J.
      • et al.
      and SF-36 Health Survey
      • Ware Jr., J.E.
      • et al.
      were utilized to evaluate the general health of unaffected controls. Individuals who had a history of liver disease, liver function blood test results (total protein, aspartate transaminase, alanine transaminase, alkaline phosphatase, albumin, globulin, and bilirubin) outside of normal range, or a recent infection were excluded from all cohorts in the study. Cases of IgA deficiency and IgG subclass deficiency were excluded from all cohorts. Inflammatory bowel disease was ruled out in all cases.
      All samples were collected at time of study entry while participants were on an unrestricted (gluten-containing) diet with written informed consent under Institutional Review Board–approved protocols at St Orsola-Malpighi Hospital, Bologna, Italy. Serum specimens were kept at –80°C to maintain stability. This study was approved by the Institutional Review Board of Columbia University Medical Center.

       Assays

      Serum levels of total IgG reactivity to gluten and individual IgG subclass reactivities to gluten were measured separately by an enzyme-linked immunosorbent assay, similar to our earlier studies.
      • Carroccio A.
      • et al.
      ,
      • Volta U.
      • et al.
      The antigen used for the assays was the Prolamine Working Group reference gliadin, as described and characterized previously.
      • Carroccio A.
      • et al.
      ,

      Mearin F, et al. Gastroenterology doi: 10.1053/j.gastro.2016.02.031.

      A 2-mg/mL stock solution of the Prolamine Working Group gliadin was prepared in 70% ethanol. Wells of 96-well Maxisorp round-bottom polystyrene plates (Nunc, Roskilde, Denmark) were coated with 50 μL/well of a 0.01-mg/mL solution of protein in 0.1 M carbonate buffer (pH 9.6) or left uncoated to serve as controls. After incubation at 37°C for 1 hour, wells were washed and blocked by incubation with 1% bovine serum albumin in phosphate-buffered saline containing 0.05% Tween-20 for 1.5 hours at room temperature. Serum samples were diluted at 1:300, added at 50 μL/well in duplicates, and incubated for 1 hour. Each plate contained a positive control sample with a high level of relevant IgG subclass reactivity to gluten, as determined in a preliminary screen. After washing, the wells were incubated with horseradish peroxidase–conjugated anti-human IgG1 (Life Technologies, Carlsbad, CA), IgG2 (Life Technologies), IgG3 (Life Technologies), or IgG4 (Southern Biotech, Birmingham, AL) secondary antibodies for 50 minutes. Plates were washed and 50 μL of developing solution, containing 27 mM citric acid, 50 mM Na2HPO4, 5.5 mM o-phenylenediamine, and 0.01% H2O2 (pH 5), was added to each well. Absorbance was measured at 450 nm after 20 minutes. All samples were tested in duplicate. Absorbance values were corrected for nonspecific binding by subtraction of the mean absorbance of the associated bovine serum albumin–coated control wells. The corrected values were first normalized according to the mean value of the positive control duplicate on each plate. The mean antibody level for the healthy control cohort was then set as 1.0 AU and all other results were normalized to this value. The cutoff value for anti-gliadin IgG positivity was assigned as 2 SDs above the mean for the healthy control group.
      Serum levels of intestinal FABP2 were measured, as we have described previously.
      • Uhde M.
      • et al.
      FABP2 is a cytosolic protein specific to intestinal epithelial cells that is released into systemic circulation upon cellular damage.
      • Pelsers M.M.
      • et al.
      Increased concentrations of circulating FABP2 reflect epithelial cell loss and enhanced enterocyte turnover rate
      • Pelsers M.M.
      • et al.
      • Pelsers M.M.
      • et al.
      • Sandler N.G.
      • et al.
      and have been associated with both CD and NCGS.
      • Uhde M.
      • et al.
      IgA antibody to recombinant human TG2, a sensitive and specific serologic marker for CD,
      • Rostom A.
      • et al.
      was measured in all serum samples, as outlined previously.
      • Uhde M.
      • et al.
      HLA genotyping to assess CD genetic predisposition was done as reported previously.
      • Moeller S.
      • et al.

       Data Analysis

      Group differences were analyzed by the Kruskal-Wallis 1-way analysis of variance with post-hoc testing. Correction for multiple comparisons was done using Dunn’s statistical hypothesis testing and the multiplicity-adjusted P values are reported for each comparison. Correlation analysis was performed using Spearman’s r. A multivariate principal component analysis was carried out on the entire IgG subclass dataset to assess clustering. All P values were 2-sided and differences were considered statistically significant at P < .05. Statistical analyses were performed with Prism, version 8 (GraphPad, La Jolla, CA) and Minitab, version 19 (Minitab, Chicago, IL).
      Supplementary Table 1Demographic and Clinical Characteristics of Study Cohorts
      Subject groupNo. of subjectsAge, y, mean (SD)Female sex, n (%)CD-associated HLA DQ2 and/or DQ8, n (%)Intestinal biopsy histologic grade: Marsh 0; Marsh 1; Marsh 3, n (%)
      NCGS8034.6 (10.3)
      No statistically significant differences exist among the NCGS, CD, and healthy cohorts.
      62 (78)
      No statistically significant differences exist among the NCGS, CD, and healthy cohorts.
      21 (26)
      Statistically significant differences exist between the CD and NCGS cohorts (P < .0001 for all comparisons).
      48 (60); 32 (40); 0
      Statistically significant differences exist between the CD and NCGS cohorts (P < .0001 for all comparisons).
      CD4034.5 (13.7)
      No statistically significant differences exist among the NCGS, CD, and healthy cohorts.
      30 (75)
      No statistically significant differences exist among the NCGS, CD, and healthy cohorts.
      40 (100)
      Statistically significant differences exist between the CD and NCGS cohorts (P < .0001 for all comparisons).
      0; 0; 40 (100)
      Statistically significant differences exist between the CD and NCGS cohorts (P < .0001 for all comparisons).
      Healthy4035.0 (12.8)
      No statistically significant differences exist among the NCGS, CD, and healthy cohorts.
      30 (75)
      No statistically significant differences exist among the NCGS, CD, and healthy cohorts.
      a No statistically significant differences exist among the NCGS, CD, and healthy cohorts.
      b Statistically significant differences exist between the CD and NCGS cohorts (P < .0001 for all comparisons).

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