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Fowler A, FitzPatrick M, Shanmugarasa A, Ibrahim ASF, Kockelbergh H, Yang HC, Williams-Walker A, Luu Hoang KN, Evans S, Provine N, Klenerman P, Soilleux EJ. An Interpretable Classification Model Using Gluten-Specific TCR Sequences Shows Diagnostic Potential in Coeliac Disease. Biomolecules 2023; 13:1707. [PMID: 38136579 PMCID: PMC10742135 DOI: 10.3390/biom13121707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 11/18/2023] [Accepted: 11/21/2023] [Indexed: 12/24/2023] Open
Abstract
Coeliac disease (CeD) is a T-cell mediated enteropathy triggered by dietary gluten which remains substantially under-diagnosed around the world. The diagnostic gold-standard requires histological assessment of intestinal biopsies taken at endoscopy while consuming a gluten-containing diet. However, there is a lack of concordance between pathologists in histological assessment, and both endoscopy and gluten challenge are burdensome and unpleasant for patients. Identification of gluten-specific T-cell receptors (TCRs) in the TCR repertoire could provide a less subjective diagnostic test, and potentially remove the need to consume gluten. We review published gluten-specific TCR sequences, and develop an interpretable machine learning model to investigate their diagnostic potential. To investigate this, we sequenced the TCR repertoires of mucosal CD4+ T cells from 20 patients with and without CeD. These data were used as a training dataset to develop the model, then an independently published dataset of 20 patients was used as the testing dataset. We determined that this model has a training accuracy of 100% and testing accuracy of 80% for the diagnosis of CeD, including in patients on a gluten-free diet (GFD). We identified 20 CD4+ TCR sequences with the highest diagnostic potential for CeD. The sequences identified here have the potential to provide an objective diagnostic test for CeD, which does not require the consumption of gluten.
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Affiliation(s)
- Anna Fowler
- Department of Health Data Science, Institute of Population Health, University of Liverpool, Liverpool L69 3GF, UK
| | - Michael FitzPatrick
- Translational Gastroenterology Unit, Nuffield Department of Medicine, University of Oxford, Oxford OX3 9DU, UK; (M.F.); (P.K.)
| | | | - Amro Sayed Fadel Ibrahim
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (A.S.F.I.); (H.-C.Y.); (A.W.-W.); (K.N.L.H.); (S.E.); (E.J.S.)
| | - Hannah Kockelbergh
- Department of Health Data Science, Institute of Population Health, University of Liverpool, Liverpool L69 3GF, UK
| | - Han-Chieh Yang
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (A.S.F.I.); (H.-C.Y.); (A.W.-W.); (K.N.L.H.); (S.E.); (E.J.S.)
| | - Amelia Williams-Walker
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (A.S.F.I.); (H.-C.Y.); (A.W.-W.); (K.N.L.H.); (S.E.); (E.J.S.)
| | - Kim Ngan Luu Hoang
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (A.S.F.I.); (H.-C.Y.); (A.W.-W.); (K.N.L.H.); (S.E.); (E.J.S.)
| | - Shelley Evans
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (A.S.F.I.); (H.-C.Y.); (A.W.-W.); (K.N.L.H.); (S.E.); (E.J.S.)
| | - Nicholas Provine
- Translational Gastroenterology Unit, Nuffield Department of Medicine, University of Oxford, Oxford OX3 9DU, UK; (M.F.); (P.K.)
| | - Paul Klenerman
- Translational Gastroenterology Unit, Nuffield Department of Medicine, University of Oxford, Oxford OX3 9DU, UK; (M.F.); (P.K.)
- Peter Medawar Building for Pathogen Research, University of Oxford, Oxford OX1 3SY, UK
| | - Elizabeth J. Soilleux
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (A.S.F.I.); (H.-C.Y.); (A.W.-W.); (K.N.L.H.); (S.E.); (E.J.S.)
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Kockelbergh H, Evans S, Deng T, Clyne E, Kyriakidou A, Economou A, Luu Hoang KN, Woodmansey S, Foers A, Fowler A, Soilleux EJ. Utility of Bulk T-Cell Receptor Repertoire Sequencing Analysis in Understanding Immune Responses to COVID-19. Diagnostics (Basel) 2022; 12:diagnostics12051222. [PMID: 35626377 PMCID: PMC9140453 DOI: 10.3390/diagnostics12051222] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 05/09/2022] [Accepted: 05/10/2022] [Indexed: 01/27/2023] Open
Abstract
Measuring immunity to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 19 (COVID-19), can rely on antibodies, reactive T cells and other factors, with T-cell-mediated responses appearing to have greater sensitivity and longevity. Because each T cell carries an essentially unique nucleic acid sequence for its T-cell receptor (TCR), we can interrogate sequence data derived from DNA or RNA to assess aspects of the immune response. This review deals with the utility of bulk, rather than single-cell, sequencing of TCR repertoires, considering the importance of study design, in terms of cohort selection, laboratory methods and analysis. The advances in understanding SARS-CoV-2 immunity that have resulted from bulk TCR repertoire sequencing are also be discussed. The complexity of sequencing data obtained by bulk repertoire sequencing makes analysis challenging, but simple descriptive analyses, clonal analysis, searches for specific sequences associated with immune responses to SARS-CoV-2, motif-based analyses, and machine learning approaches have all been applied. TCR repertoire sequencing has demonstrated early expansion followed by contraction of SARS-CoV-2-specific clonotypes, during active infection. Maintenance of TCR repertoire diversity, including the maintenance of diversity of anti-SARS-CoV-2 response, predicts a favourable outcome. TCR repertoire narrowing in severe COVID-19 is most likely a consequence of COVID-19-associated lymphopenia. It has been possible to follow clonotypic sequences longitudinally, which has been particularly valuable for clonotypes known to be associated with SARS-CoV-2 peptide/MHC tetramer binding or with SARS-CoV-2 peptide-induced cytokine responses. Closely related clonotypes to these previously identified sequences have been shown to respond with similar kinetics during infection. A possible superantigen-like effect of the SARS-CoV-2 spike protein has been identified, by means of observing V-segment skewing in patients with severe COVID-19, together with structural modelling. Such a superantigen-like activity, which is apparently absent from other coronaviruses, may be the basis of multisystem inflammatory syndrome and cytokine storms in COVID-19. Bulk TCR repertoire sequencing has proven to be a useful and cost-effective approach to understanding interactions between SARS-CoV-2 and the human host, with the potential to inform the design of therapeutics and vaccines, as well as to provide invaluable pathogenetic and epidemiological insights.
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Affiliation(s)
- Hannah Kockelbergh
- Department of Health Data Science, Institute of Population Health, University of Liverpool, Liverpool L69 3GF, UK;
| | - Shelley Evans
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (S.E.); (T.D.); (E.C.); (K.N.L.H.); (S.W.)
| | - Tong Deng
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (S.E.); (T.D.); (E.C.); (K.N.L.H.); (S.W.)
| | - Ella Clyne
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (S.E.); (T.D.); (E.C.); (K.N.L.H.); (S.W.)
| | - Anna Kyriakidou
- School of Clinical Medicine, University of Cambridge, Cambridge CB2 1QP, UK; (A.K.); (A.E.)
| | - Andreas Economou
- School of Clinical Medicine, University of Cambridge, Cambridge CB2 1QP, UK; (A.K.); (A.E.)
| | - Kim Ngan Luu Hoang
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (S.E.); (T.D.); (E.C.); (K.N.L.H.); (S.W.)
| | - Stephen Woodmansey
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (S.E.); (T.D.); (E.C.); (K.N.L.H.); (S.W.)
- Department of Respiratory Medicine, University Hospitals of Morecambe Bay, Kendal LA9 7RG, UK
| | - Andrew Foers
- Kennedy Institute of Rheumatology, University of Oxford, Oxford OX3 7YF, UK;
| | - Anna Fowler
- Department of Health Data Science, Institute of Population Health, University of Liverpool, Liverpool L69 3GF, UK;
- Correspondence: (A.F.); (E.J.S.)
| | - Elizabeth J. Soilleux
- Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK; (S.E.); (T.D.); (E.C.); (K.N.L.H.); (S.W.)
- Correspondence: (A.F.); (E.J.S.)
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