A new clustering method identifies multiple sclerosis‐specific T‐cell receptors

Abstract

ObjectiveTo characterize T‐cell receptors (TCRs) and identify target epitopes in multiple sclerosis (MS).MethodsPeripheral blood mononuclear cells were obtained from 39 MS patients and 19 healthy controls (HCs). TCR repertoires for α/β/δ/γ chains, TCR diversity, and V/J usage were determined by next‐generation sequencing. TCR β chain repertoires were compared with affectation status using a novel clustering method, Grouping of Lymphocyte Interactions by Paratope Hotspots (GLIPH). Cytomegalovirus (CMV)‐IgG was measured in an additional 113 MS patients and 93 HCs. Regulatory T cells (Tregs) were measured by flow cytometry.ResultsTCR diversity for all four chains decreased with age. TCRα and TCRβ diversity was higher in MS patients (P = 0.0015 and 0.024, respectively), even after age correction. TRAJ56 and TRBV4‐3 were more prevalent in MS patients than in HCs (pcorr = 0.027 and 0.040, respectively). GLIPH consolidated 208,674 TCR clones from MS patients into 1,294 clusters, among which two candidate clusters were identified. The TRBV4‐3 cluster was shared by HLA‐DRB1*04:05‐positive patients (87.5%) and predicted to recognize CMV peptides (CMV‐TCR). MS Severity Score (MSSS) was lower in patients with CMV‐TCR than in those without (P = 0.037). CMV‐IgG‐positivity was associated with lower MSSS in HLA‐DRB1*04:05 carriers (P = 0.0053). HLA‐DRB1*04:05‐positive individuals demonstrated higher CMV‐IgG titers than HLA‐DRB1*04:05‐negative individuals (P = 0.017). CMV‐IgG‐positive patients had more Tregs than CMV‐IgG‐negative patients (P = 0.054).InterpretationHigh TCRα/TCRβ diversity, regardless of age, is characteristic of MS. Association of a CMV‐recognizing TCR with mild disability indicates CMV’s protective role in HLA‐DRB1*04:05‐positive MS.

Elevated mycobacterium avium subsp. paratuberculosis (MAP) antibody titer in Japanese multiple sclerosis

“…Previous reports have shown that immune responses of MS patients to certain viruses, such as EBV, cytomegalovirus and JC virus, alter depending on the presence or absence of HLA-DRB1 risk alleles (Olsson et al, 2016;Hayashi et al, 2021;Watanabe et al, 2020). This indicates that HLA alleles may play roles in virus-associated immune responses that are related to MS pathogenesis.…”

Immunosenescence and Autoimmunity: Exploiting the T-Cell Receptor Repertoire to Investigate the Impact of Aging on Multiple Sclerosis

“…Recently, Hayashi et al. ( 21 ) characterized the TCR repertoire by HTS in peripheral blood of 39 MS and 19 HD by using the newly developed Grouping of Lymphocyte Interactions by Paratope Hotspots (GLIPH), a clustering method that allows to group data based on chosen parameters, e.g. TCRVβ chain distribution or HLA haplotype.…”

“…The relationship between aging and MS pathogenesis and progression is well known: immunosenescence and skewed T-cell compartment diversity in MS patients have been linked to a higher risk of developing a potentially fatal neurological disorder, the Progressive Multifocal Leukoencephalopathy (PML) ( 18 ); furthermore, patient’s age differentially impacts treatment outcome ( 19 , 20 ). A recent study investigated the TCR repertoire dynamics in MS patients of different ages and enlightened interesting results showing that, despite the physiological decline of TCR repertoire diversity with age, this does not significantly differ between MS and healthy people ( 21 ).…”

Biological controls for standardization and interpretation of adaptive immune receptor repertoire profiling

“…AIRR sequencing (AIRR-seq) provides insights into the immune status of an individual at steady-state or in altered conditions such as malignancy, autoimmune disease, immunodeficiency, infectious disease, or vaccination, and allows comparison of B- and T-cell populations between individuals and time points ( Benichou et al, 2012 ; Kirsch et al, 2015 ; Dziubianau et al, 2013 ; Hou et al, 2016 ; Ghraichy et al, 2018 ). AIRR-seq permits the description and quantification of global diversity and characteristics of AIRR, the identification of clonal expansions, the tracking of particular clonotypes, and the prediction of their specificities ( Miho et al, 2018 ; Zvyagin et al, 2020 ; Sidhom et al, 2018 ; Glanville et al, 2017 ; Huang et al, 2020 ; Jokinen et al, 2021 ; Akbar et al, 2021 ; Hayashi et al, 2021 ) as well as the antibody selection through phage display ( Rouet et al, 2018 ; Ravn et al, 2013 ), thereby providing opportunities for new biomarker identification ( Gittelman, 2021 ; Dines, 2020 ), therapeutic antibody discovery ( Akbar et al, 2021 ; Richardson et al, 2021 ), CAR-T cell bioengineering ( Sheih et al, 2020 ), vaccine development, cancer diagnostics and treatment ( Linette et al, 2019 ; Zhang et al, 2018 ; Lu et al, 2018 ), including neoantigen discovery ( Chiou et al, 2021 ; Richters et al, 2019 ) and immune intervention monitoring in diverse pathologies, such as stem cell transplantation ( Robinson, 2015 ; Fink, 2019 ; Jiang et al, 2019 ; Jacobsen et al, 2017 ; Theil, 2017 ; Link-Rachner et al, 2019 ; Rubelt et al, 2017 ; Parola et al, 2018 ; Georgiou et al, 2014 ; Arnaout et al, 2021 ; Anand et al, 2021 ).…”

“…Furthermore, whether individuals used controls or did not, they appeared to agree on the types of issues in analyzing and interpreting AIRR-seq data that would benefit from the use of controls - most importantly measuring and controlling for sample quality, assay sensitivity and specificity, and calibration for the quantification of clonal size. Also, with the progress regarding antigen-specificity inference using computational tools ( Glanville et al, 2017 ; Huang et al, 2020 ; Jokinen et al, 2021 ; Akbar et al, 2021 ; Hayashi et al, 2021 ; Richardson et al, 2021 ; Galson et al, 2015 ; Shomuradova et al, 2020 ; Chronister et al, 2021 ; Sidhom et al, 2021 ; Pogorelyy et al, 2019 ; Dash et al, 2017 ) or more conventionally through technologically challenging using antigen-binding approaches, including single-cell ( Johnson et al, 2020 ; Fuchs et al, 2019 ), having controls would be of major interest to ensure the accuracy of the TR or IG identified. It is unlikely that a single control can fulfill all of these needs across all methods and applications.…”