Under conditions of normal immune function, T cells defend the body against foreign antigens. However, aberrant responses to self- and non-self-antigens result in autoimmune disease, in which healthy cells are attacked by the host’s immune system. (1,2) There are a number of contributing factors to autoimmune disease (Figure 1). With more than 80 known diseases affecting 3–5% of the general population, autoimmune diseases cause a significant burden on healthcare systems. (1,2) The chronic nature of autoimmune diseases, along with the associated cost to healthcare systems and their prevalence in young people during the prime of their working and reproductive years, also add to the clinical burden. (3)
Figure 1. Contributing factors to autoimmune diseases. AIRE: autoimmune regulator; APC: antigen-presenting cell; CTLA-4: cytotoxic T-lymphocyte protein 4; FOXP3: forkhead box protein P3; HLA: human leukocyte antigen; IL-2: interleukin-2; Tregs: regulatory T cells. Adapted from Rosenblum et al. (3)
Autoimmune disease: an unmet clinical need
The etiologies of autoimmune diseases are not fully understood, and currently available therapies are not sufficient. Autoimmune diseases, therefore, present a significant unmet clinical need that requires the application of new and existing research tools to elucidate the molecular mechanisms underlying them, as well as novel biomarkers for prediction, early diagnosis, prognosis, treatment response, and therapeutic strategies.
An improved understanding of these factors would represent a promising future in the battle against autoimmune diseases and could potentially improve the quality of life of people living with these diseases.
Role of T cells in autoimmune disease pathology
T- and B-cell populations are vital mediators of the adaptive immune system that are continually changing in response to exposure to both foreign and self-antigens, as is the case in autoimmune diseases. (2,3) These immune cells recognize antigens via their surface receptors [i.e., T-cell receptors (TCRs) and B-cell receptors (BCRs)], resulting in the selective proliferation of a population of cells expressing TCRs and BCRs that are specific for particular antigens. These are known as T- and B-cell repertoires. (2,3)
As shown in Figure 1, defective T-cell responses play an important role in autoimmune disease pathology, with CD4+ and CD8+ T cells being the main culprits in autoimmune disease pathology. (2,3)
Currently available therapies
While current therapies such as cytokine antagonists are effective in the treatment of many autoimmune diseases, most do not target the fundamental mechanisms underlying the initiation and progression of disease, and thus provide only short-term resolution to disease symptoms. (3)
This issue is exacerbated by the fact that the etiologies of many autoimmune diseases are not fully understood. (1–3) Therefore, the goal of new autoimmune disease therapies should include boosting regulatory mechanisms to establish robust and long-term disease resolution. (3)
The development of such new therapies requires a solid understanding of both the underlying dysfunction and regulatory mechanisms surrounding autoimmune diseases. (2,3)
Large-scale immunosequencing: a reliable tool to study autoimmunity
The changes that are initiated in T- and B-cell repertoires can be characterized by large-scale immunosequencing, a powerful method that enables the study of the adaptive immune system, including immune responses to antigen exposure, disease history, disease dynamics and severity, biomarkers, and therapeutic responses.
What is large-scale immunosequencing and how does the immunoSEQ® Assay work?
Before exploring how large-scale immunosequencing can be used to advance autoimmune disease research, it is helpful to understand what it is and how the immunoSEQ® Assay works.
Large-scale immunosequencing is a next-generation sequencing-based technology that enables the high-throughput characterization of TCRs and BCRs. (4) Our immunoSEQ Assay is a powerful and highly sensitive PCR-based assay that permits scalable, precise, and quantitative sequencing of the immune repertoire to reveal important insights into normal and aberrant biology.
During T-cell maturation, TCR and BCR genes undergo somatic recombination, leading to a huge diversity in the number of final DNA sequences. (5) Somatic recombination of TCRs and BCRs creates regions of DNA with high variability. (5) The immunoSEQ Assay sequences the highly variable genomic complementarity determining region 3 (CDR3) of TCRs and BCRs, which essentially serves as a unique barcode for each cell (Figure 2). (4)
Figure 2. Somatic recombination in the V(D)J region of TCRs and BCRs creates unique DNA barcodes that can be analyzed by the immunoSEQ Assay to profile the adaptive immune system.
As a result, the immunoSEQ Assay captures the depth and breadth of the adaptive immune system without the issue of amplification bias commonly associated with multiplex PCR. To learn more about this technology, view our webinar on Exploring Repertoire Development and Dynamics with the immunoSEQ Assay.
How can the immunoSEQ Assay improve our understanding of autoimmune diseases?
A significant challenge in understanding autoimmune disease pathology is the identification of relevant T-cell clones. (6) This is partly due to major variabilities in repertoire composition and diversity between individuals. (6) Therefore, large cross-sectional studies are unlikely to reveal informative differences between groups. Instead, the identification of informative T-cell clones, which are likely private (i.e. largely observed in one individual and rarely observed in multiple individuals), requires longitudinal study with rapid changes in disease activity and remission over that time. (7)
MONITORING AUTOIMMUNE DISEASE DYNAMICS
All autoimmune diseases are thought to progress through sequential stages of initiation, propagation, and resolution, with each stage being associated with erroneous regulatory mechanisms (Figure 3). (3) The resolution stage is characterized by a partial and often short-term restoration in the balance between effector and regulatory responses. (3)
Figure 3. Three distinct phases of autoimmune disease. Autoimmunity is triggered by genetic and environmental factors and is associated with three major phases. Symptoms are subclinical in the initiation phase. Clinical disease usually manifests during the propagation phase owing to continual inflammation and tissue damage caused by cytokine production, epitope spreading, and an imbalance in effector T cells (Teff) and regulatory T cells (Tregs). The third phase involves the resolution of symptoms due to inhibitory pathways and Treg mechanisms, which restore the Teff/Treg imbalance. In this resolution phase, patients are often plagued with relapsing and remitting disease due to the constant battle between pathogenic effector responses and regulatory mechanisms. Adapted from Rosenblum et al. (3)
In this context, our immunoSEQ Assay is an invaluable tool for studying disease dynamics because it enables researchers to track the temporal changes in TCR and BCR repertoires during active and inactive autoimmune disease, as well as in response to therapies. These data can be compared with equivalent data from healthy individuals, or individuals with other diseases, to provide important insights into the mechanisms of immunopathology in different autoimmune diseases.
Monitoring disease dynamics in multiple sclerosis: How pregnancy is helping our understanding of multiple sclerosis
As described previously, one of the biggest challenges in unraveling the complexity of autoimmune disease pathology is detecting relevant T-cell clones. However, because these T-cell clones are expected to be private, one way to identify them is to undertake longitudinal studies in individuals with autoimmune disease that is associated with rapid changes in disease activity and remission over that time. One example of such a situation is autoimmunity during pregnancy.
Pregnancy induces a pronounced, clinically relevant, and time-dependent impact on maternal autoimmunity. This is supported by data illustrating the protective effects of pregnancy in many autoimmune disorders. (8–10) One profound example is in multiple sclerosis (MS), where the relapse rate is reduced by 70–80% in the third trimester of pregnancy. (9,10) This exceeds the efficacy of many autoimmune disease therapies. Pregnancy could, therefore, serve as a richly informative model to study relevant T-cell clones during active and inactive MS. (6)
Indeed, a recent study used the immunoSEQ Assay to characterize the T-cell repertoires of healthy women and women with MS before pregnancy, at each trimester during pregnancy, and 3 months postpartum. Analyses of the clonal composition in peripheral blood mononuclear cells (PBMCs) revealed that while the number of circulating T cells was unaltered, there was a significant decrease in clonality during pregnancy in women with MS, but not in healthy individuals (Figure 4). (6)
Figure 4. Pregnancy changes T-cell clonality in MS. T-cell clonality data generated by large-scale high-throughput immunosequencing of PBMCs in women with MS (A) and healthy women (B) before, during, and after pregnancy. There is a significant (p = 0.004) time-dependent decrease in T-cell clonality during pregnancy, which is restored to baseline postpartum. This is not the case for healthy pregnant women. HC: healthy controls; MS: multiple sclerosis. Adapted from Ramien et al. (6)
In addition, to identify the clones responsible for inducing changes in T-cell clonality, the authors of this study used the immunoSEQ® Analyzer to compare the frequency of all unique TCRB CDR3 amino acid sequences. Analysis of these data revealed statistically significant changes in 25 of the most abundant clonotypes in each of the 11 pregnant MS study participants (Figure 5A) but in none of the 12 healthy pregnant participants (Figure 5B). (6)
Figure 5. Pregnancy significantly alters a small number of private T-cell clones in MS. Heat map showing the prevalence of 25 of the most abundant T-cell clonotypes in bulk PBMCs in each MS participant (A) and healthy control (B) during pregnancy. Study participants are listed on the left with a specific identifier and each column represents a trimester. Adapted from Ramien et al. (6)
Intriguingly, this study also identified one MS participant (MS15) who showed the largest number of altered clones during pregnancy and postpartum. Coincidentally, participant MS15 also experienced a clinical relapse at 3 months postpartum. This specific case was especially informative because it reflected the epidemiological pattern of MS disease activity in pregnancy.
Subsequently, the top 100 clonotypes in this participant were identified and retrospectively tracked throughout the pregnancy. These relapse-associated clones demonstrated a statistically significant and time-dependent downregulation during pregnancy. Taken together, these data identified several interesting clones beyond the typical MS-related antigens, thereby illustrating the utility and application of the immunoSEQ Assay in monitoring disease dynamics in research. (6)
MONITORING AUTOIMMUNE DISEASE SEVERITY
Autoimmune diseases vary greatly in their clinical manifestations depending on the affected tissues and organs, and some can also be categorized into sub-groups depending on the severity of the disease. Large-scale immunosequencing can be used to monitor disease severity and its effect on the immune repertoires of different individuals. Importantly, such data can reveal important insights into the mechanisms of immunopathology, which can in turn be used to inform and accelerate medical discovery.
Monitoring disease severity: a rheumatoid arthritis case study
Rheumatoid arthritis (RA) is an autoimmune disease characterized by chronic inflammation and T-cell-mediated autoantibody production. (11) This disease targets the synovial tissue in joints and is typically classified as seropositive (SP-RA) and seronegative (SN-RA) according to the presence or absence of anti-cyclic citrullinated peptide (CCP) antibodies. (11,12) Interestingly, CCP-negative destructive (CND) RA, a uniquely destructive form of RA, is resistant to conventional antirheumatic therapy, and the underlying mechanisms of disease pathology are unclear. (13)
Kelkka et al. (11) used the immunoSEQ Assay to characterize the CD8+ T-cell repertoires of subjects with CND-RA (n = 8), SP-RA (n = 51), and SN-RA (n = 11). CD8+ TCR repertoires were found to be significantly more clonal in CND-RA subjects than in any other subject cohort (Figure 6). (11)
Figure 6. TCRB repertoire analysis of subjects with CND-RA, SN-RA, and SP-RA. Differences in clonality index were determined by analysis of the TCRB repertoire diversity. Diversity is reduced in CND-RA subjects compared with healthy controls, and SN-RA and SP-RA subjects. Adapted from Kelkka et al. (11)
Given that many autoimmune diseases are associated with viral infections, the authors analyzed these data in the VDJdb clone database, the largest TCR database containing specific annotated epitopes, (14) and uncovered an increased abundance of public cytomegalovirus (CMV)-reactive T-cell clones in CND-RA samples, but decreased influenza-A-reactive CD8+ cells in CND-RA compared with healthy controls and other RA subtypes (Figure 5). In addition, this study also identified a unique CD8+ T-cell signature in CND-RA. (11)
Conventional anti-RA therapies do not affect CND-RA. (13) An improved understanding of the role of CD8+ T cells in disease progression may therefore have significant implications for research on new targets and therapeutic strategies, particularly those that target T cells. Taken together, these data provide some important insights into the molecular basis of CND-RA and highlight the utility of the immunoSEQ Assay in identifying factors implicated in disease severity.
IDENTIFYING MARKERS OF THERAPEUTIC RESPONSE
Just as the immunoSEQ Assay can be leveraged to study temporal changes during different phases of autoimmune disease, it can also be used to track changes in T-cell repertoires before, during, and after therapeutic interventions.
Monitoring the therapeutic response to autologous hematopoietic stem cell transplantation
Autologous hematopoietic stem cell transplantation (AHSCT), in which the autoreactive immune system is replaced with a new immune repertoire derived from the individual’s own stem cells that may be more self-tolerant, has been postulated as a potential therapy for aggressive autoimmune disorders. (15)
The High-Dose Immunosuppression and Autologous Transplantation for Multiple Sclerosis (HALT-MS) study reported a Phase II trial of AHSCT in patients with treatment-resistant relapsing-remitting MS (RRMS) that showed AHSCT therapy could achieve durable remissions of at least 5 years. (16)
Sequencing of peripheral CD4+ and CD8+ T cells using the immunoSEQ Assay showed that more than 80% of the CD4+ T-cell repertoire was replaced by new clones at 12, 24, and 48 months post-AHSCT therapy. (16) However, ablation of the original CD8+ T-cell clones was much reduced and more variable across the same time points (Figure 7). The remaining CD4+ and CD8+ clones persisted and expanded following therapy. (16)
Figure 7. AHSCT induces the ablation of pre-existing peripheral T-cell repertoires after 12, 24, and 48 months. Proportion of undetectable (teal) versus detected (orange) clones by ultra-deep sequencing of TCR repertoires in CD4+ T cells and CD8+ T cells. Adapted from Harris et al. (16)
The application of the immunoSEQ Assay was significant in this work because it clearly showed that in subjects with RRMS, AHSCT resulted in the loss of most CD4+ T cells. In comparison, the ablation of CD8+ T cells was much reduced. Thus, the authors demonstrate one mode of action behind AHSCT therapy, and they also demonstrate that this observation persists for up to 48 months. (16) These data may be important to inform the future development and potential widespread use of AHSCT as a therapy for RRMS.
Infiltration of inflammatory T cells into the central nervous system (CNS) is known to drive disease progression in MS. (17) After entering the CNS, these inflammatory T cells re-circulate in the cerebrospinal fluid (CSF) and gain direct access to the site of disease. (16,17) As a result, T cells found in the CSF may contain more pathological clonotypes that are directly involved in MS progression. However, ex vivo characterization of T cells from the CSF has been limited partly because of the invasive nature of obtaining CSF samples. (16)
To understand the effect of AHSCT on T cells in the CNS, Harris et al. (16) used the immunoSEQ Assay to characterize CD4+ and CD8+ T-cell repertoires in the CSF and in the peripheral blood of participants in the HALT-MS clinical trial. (16) While some clones persisted, AHSCT therapy ablated >90% of the pre-existing T-cell repertoire in the CSF up to 48 months after therapy (Figure 8A). Before AHSCT therapy, an average of 62.3 ± 6.1% of clones found in the CSF were also detected in the peripheral blood. After AHSCT therapy, the number of shared clones between the compartments was significantly reduced to 40.6 ± 7% (Figure 8B). (16)
Figure 8. Replacement of pre-existing CSF T-cell repertoire and number of shared T-cell clones between the CSF and peripheral blood before and after AHSCT therapy. (A) The percentage of clones that were undetectable (teal) versus detected (orange) was determined using the TCR overlap percentage, calculated by comparing deep sequencing results pre therapy to months 24 or 48 post therapy for each participant. (B) Proportion of shared clones in the CSF that were either undetectable (teal) or detected (orange) in peripheral blood CD4+ or CD8+ T cells before therapy versus 24 months after therapy. Adapted from Harris et al. (16)
The above experiments underscore the utility and application of the highly sensitive immunoSEQ Assay in tracking temporal changes and overlap between T-cell repertoires to evaluate the full complexity of the CSF, which is limited in T-cell abundance compared with blood. (16)
IDENTIFYING MARKERS OF DISEASE RECURRENCE
The immunoSEQ Assay allows for in-depth profiling of T-cell responses to understand changes before, during, and after autoimmune disease recurrence. These data can be decoded to identify markers of disease relapse to inform disease management and accelerate drug discovery research.
Identifying markers of recurrence in Crohn’s disease
Crohn’s disease (CD), a complex form of inflammatory bowel disease (IBD), is characterized by chronic inflammation of the gastrointestinal tract. (18) Genetic analyses suggest that defects in the integrity and function of the intestinal mucosal barrier and immune regulation stimulate the immune system to attack the intestinal microbiota. (18)
As in MS, the infiltration of activated immune cells into the target organ (in this case, the intestinal mucosa) is associated with CD pathology. (18) One of the main approaches to disease management is the removal of diseased segments of the intestines, but this is not a cure as most patients will suffer subsequent disease recurrence. (18)
Previous studies suggest that clonal expansion of T cells in the inflamed mucosa of CD subjects may be associated with disease relapse. To identify biomarkers of early post-operative disease recurrence, Allez et al. (18) used the immunoSEQ Assay to sequence the TCR repertoires of 57 subjects with CD before surgery and 6 months after surgery.
Data analysis revealed that an increase in the proportion of high-frequency T-cell clones in the mucosa is linked to CD recurrence following the surgical removal of diseased segments of the intestines (Figure 9). (18) Moreover, most study participants with major clonal expansions at the time of surgery suffered post-operative endoscopic recurrence, thereby suggesting that these individuals may represent a subgroup with poor clinical outcomes. (18)
Figure 9. Comparison of TCR repertoires (Simpson diversity index) stratified according to the endoscopic recurrence Rutgeerts score (i0: no recurrence; i1-4: recurrence) determined 6 months after surgery (Mann–Whitney test). Adapted from Allez et al. (18)
How the immunoSEQ Assay is helping us understand disease pathogenesis
IDENTIFYING MECHANISMS OF AUTOIMMUNE DISEASES
Insights into the role of somatic mutations in driving autoimmune diseases
As well as being important oncogenic drivers, somatic mutations also accumulate in T cells undergoing clonal expansion following antigen recognition. (12) The mutation rate in lymphoid precursors has been estimated to be approximately 106 per cell division, thereby increasing the likelihood of an accumulation of DNA replication errors during cell proliferation. (19,20) The accumulation of somatic mutations in non-malignant disorders such as autoimmune disease had not, until recently, been studied.
Using flow cytometry data, which were supported by data from our immunoSEQ Assay, Savola et al. (12) showed that subjects with recently diagnosed RA have expanded CD8+ T-cell clones and that 20% of these subjects harbored somatic mutations. Only one mutation in the CD8+ T-cell compartment was identified in the healthy study participants. These mutations were found only in the expanded CD8+ T-cell repertoire and they persisted during follow-up. (12)
Importantly, these mutations were predicted to alter protein function in genes that have previously been associated with autoimmunity (Figure 10). (12) These data provide a link between a cancerous process and autoimmunity, providing some interesting insights into mechanisms involved in autoimmune disease while illustrating the utility of large-scale immunosequencing in research.
Figure 10. A comparison of sequencing data in a panel of 986 immune-related genes (i.e. Immunopanel) identified somatic mutations in newly diagnosed RA subjects and in one healthy control (A). Variant allele frequencies in CD8+ T cells are indicated as percentages below the gene names. Proliferation-associated genes (orange); immune-related genes (teal); other (green). (B) Non-synonymous coding, nonsense-, frameshift-, and splice-site mutation frequencies are indicated as percentages of all identified mutations. Adapted from Savola et al. (12)
IDENTIFYING TOP CLONES
An individual’s TCR repertoire is influenced by a variety of factors during somatic recombination and by the ensuing expansions and deletions of certain T-cell clones following antigen recognition. (3) Somatic recombination leads to the production of diverse TCR repertoires, which act as a hallmark of the adaptive immune system. Importantly, T-cell clonality can be quantified by analyzing these repertoires. (21)
In healthy individuals, the TCR repertoire is polyclonal and non-static. (21) Clonal populations are characteristic of malignancy, while clonal or oligoclonal T- and B-cell populations also occur in non-malignant conditions such as human immunodeficiency virus (HIV) and Epstein–Barr virus infections (21) and some autoimmune diseases including Sjogren’s syndrome and systemic lupus erythematosus (SLE). (22) Once identified, expanded clones can be tracked over time in individuals with autoimmune disease and other immune disorders. (21,22)
Insights into psoriasis
Psoriasis, an autoimmune skin disease mediated by T cells and interleukin-17 (IL-17), is characterized by inflamed skin lesions. (23) While these lesions can be resolved by therapy, they often recur in the same areas once therapy stops. Immunosequencing can provide an improved understanding of the phenotype and antigen specificity of pathogenic T cells in psoriasis to inform new therapeutic targets and strategies. (23)
To study the role of T cells in psoriasis, Matos et al. (23) used the immunoSEQ Assay to sequence the TCR repertoires of skin lesion biopsies from subjects with psoriasis before and after clinical resolution. T-cell populations in inflamed skin lesions were very diverse; over 93% of the T-cell clones found in active disease were abolished following anti-inflammatory therapy. The authors also identified 15 unique TCRB and 4 TCRA CDR3 sequences in multiple psoriasis subjects but not in healthy controls. (23)
The immunoSEQ Assay was crucial in this context because it helped to reveal the presence of IL-17-producing αβ T-cell clones with psoriasis-specific antigen receptors in clinically resolved psoriatic skin lesions. This led the authors to conclude that in psoriasis, these cells probably represent disease-initiating pathogenic T cells, thereby suggesting that long-term control of this disease may necessitate the suppression of these resident T-cell populations. (23)
CHARACTERIZING CLONAL OVERLAP
Once identified, top clones can be tracked longitudinally as well as in different compartments within the body to determine clonal overlap. The identification of shared clones across different compartments and between individuals is important as it allows us to better understand the mechanisms of autoimmune disease pathology and predisposition to disease.
Understanding Rasmussen encephalitis
Rasmussen encephalitis (RE), a rare neuroinflammatory disease affecting children, is characterized by intractable seizures and unilateral brain atrophy. (24) If untreated, RE leads to permanent deficits in motor and sensory systems. (24) While immunosuppressive therapies have been partially effective, there is no known cure or etiology for RE. (24,25) Studies of resected brain tissue suggest that RE-associated inflammation involves infiltration of immunomodulatory cells, including CD8+ T cells. (25)
Previous studies have shown that clonal expansion of αβ T cells occurs in brain tissue and blood from individuals with RE. To further understand the involvement of αβ T cells in disease progression, Dandekar et al. (25) utilized the immunoSEQ Assay to analyze T-cell clonality in blood and brain tissue samples from 14 RE subjects and 100 matched controls. (25) TCR clonality was significantly higher in brain tissue samples than in matched blood, and some of the T-cell clones found in the brain were also found in circulation (Figure 11). (25)
Figure 11. T-cell clonality in blood and resected brain tissue samples from subjects with RE. Significantly higher clonality was observed in brain tissue (orange) than in matched blood samples (teal) collected at the time of surgery. Adapted from Dandekar et al. (25)
The authors also identified several shared human leukocyte antigen (HLA) class I alleles in the 24 studied RE cases, thereby suggesting the involvement of antigen-specific major histocompatibility complex (MHC) class I-restricted T cells in RE. The authors subsequently concluded that two of the overlapping HLA class I alleles (HLA-C*03:01:01:01 and HLA-C*07:01:01:01) may increase an individual’s risk of developing autoimmunity. In addition, four of the enrolled RE subjects also presented with four different autoimmune diseases [Hashimoto thyroiditis, ulcerative colitis (UC), CD, and SLE], lending further support to their hypothesis.
Role of integrin α4β7-expressing memory CD3+ T cells in Crohn’s disease and ulcerative colitis
Integrin α4β7 expression is upregulated on activated T cells and thought to mediate the targeting of T and B cells to peripheral sites such as the intestines. (26)
To assess the involvement of α4β7-expressing memory CD3+ T cells from blood samples of subjects with CD and UC, Gamliel et al. (27) sorted cells into ɑ4β7+ and α4β7– populations and sequenced their TCRB repertoires using the immunoSEQ Assay.
Immunophenotyping of these cells showed that the frequency of CD3+CD45RO+ memory T cells and α4β7+ cells was similar between subjects with UC or CD and healthy controls. The proportion of α4β7+ memory T cells was also similar in all three participant groups. In addition, there was significant clonal sharing between α4β7– and α4β7+ memory T-cell subpopulations and clones that were specific for each group could not be identified, highlighting that expression of this integrin was not confined to specific clones. (27)
The above studies highlight the power of the immunoSEQ Assay to study adaptive immune function in different diseases, including the demonstration of oligoclonal T-cell expansion in the inflamed gut of patients with IBD.
Characterizing the immune response to self-antigens
Immunosequencing can be used to characterize potential disease-related T-cell signatures by identifying and tracking specific T-cell clones, including clones that are linked to a specific disease-related antigen. These types of disease signatures may be used as biomarkers in clinical research trials to understand whether the T cells correlate with important disease characteristics, such as disease progression or treatment responses.
IDENTIFYING AND TRACKING SELF-REACTIVE CLONES IN NARCOLEPSY
Narcolepsy, a rare and chronic sleep disorder, manifests as excessive daytime drowsiness, hallucinations, sleep paralysis, and sudden loss of muscle tone while awake. (28,29) Idiopathic sporadic narcolepsy, the main form of the disorder, is typified by selective neurodegeneration of hypocretin (HCRT)-producing neurons in the hypothalamus. While some studies suggest that narcolepsy is an autoimmune disease, prior to work by Latorre et al. (30), there was little evidence of the involvement of autoreactive T cells.
Latorre et al. (30) used the immunoSEQ Assay to sequence the immune repertoire of peripheral blood samples from 19 individuals with a clinical diagnosis of narcolepsy and 13 healthy individuals. The data revealed the presence of autoreactive HCRT-specific CD4+ T cells and, in some instances, CD8+ T cells in individuals with narcolepsy in both the blood and CSF. (30)
Through identifying HCRT-reactive T-cell subpopulations across different subjects, these data (accessible via the immuneACCESS® database) point to the existence of public clonotypes in narcolepsy, thereby providing scope for further research into novel approaches for the rapid diagnosis and treatment of this disease.
IDENTIFYING SELF-REACTIVE CLONES IN PARKINSON’S DISEASE
Several studies have demonstrated the role of the neuronal protein, ⍺-synuclein (⍺-syn), in the neuropathology of Parkinson’s disease (PD). (31) Recent studies have even identified anti-⍺-syn T cells in subjects with PD. (32)
Singhania et al. (33) used the immunoSEQ TCRB Assay to characterize the ⍺-syn-specific T-cell repertoire from six subjects with PD and reported surprising diversity. Moreover, no common TCRs were identified between the six study participants (Figure 12).
The authors hypothesized that the lack of shared clones may have been due to HLA differences between study participants, since each subject displayed a unique HLA type.
Figure 12. Overlap heatmap of ⍺-syn-peptide-specific TCRs between patients with PD, with darker blue representing a higher number of overlapping clones, and white representing no overlap. Adapted from Singhania et al. (33)
The authors of this study provide the first characterization of ⍺-syn-peptide-specific TCR clonotypes in subjects with PD. Subsequent studies may use HLA-matched subjects to identify shared clones that could be useful in tracking changes during PD progression. (33)
TRACKING B CELLS THAT SECRETE AUTOANTIBODIES
Myasthenia gravis (MG) is a neuromuscular autoimmune disease caused by autoantibodies targeted to postsynaptic proteins, mainly the acetylcholine receptor (AChR), which act to suppress signaling at the neuromuscular junction. The thymus acts as a reservoir for pathogenic AChR autoantibody-producing B cells. (34)
The immunoSEQ Assay is not limited to use in identifying and tracking disease-specific T-cell clones. The human and mouse immunoSEQ IGH Assays target the heavy chain that forms part of the BCR to provide insights into the B-cell repertoire. Jiang et al. (34) used the immunoSEQ Assay to characterize the thymic B-cell repertoire in subjects with MG. Their findings can be summarized as follows:
- Disease-associated B-cell clones developed in the thymus before entering the circulation.
- These clones persisted in circulation 12 months after thymectomy in MG subjects.
- Persistence was associated with poor clinical outcomes, disease management, and autoantibody titer.
- Poor outcomes following thymectomy were related to the persistence of thymus-associated B cells in the circulation.
The conclusions drawn from this study suggest that tracking the persistence of thymus-derived B-cell clones after thymectomy may represent a novel biomarker for the future management of subjects with MG. (34)
The immunoSEQ Assay is a highly sensitive, quantitative, cost-effective, and flexible multiplex PCR-based method that allows for sequencing of the entire T-cell or B-cell repertoire from a variety of samples, including but not limited to whole blood, PBMCs, CSF, and/or formalin-fixed paraffin-embedded (FFPE) tissues.
A major challenge in developing novel and efficacious therapies for autoimmune diseases is a lack of knowledge regarding the biology of specific T- and B-cell populations and their roles in disease progression. However, the advent of the scalable, cost-effective, and versatile immunoSEQ Assay has allowed researchers to gain novel mechanistic insights into the pathology of various autoimmune diseases. The innovative work discussed in this article highlights the importance of the immunoSEQ Assay in unraveling disease severity and potential immunopathological mechanisms in autoimmune disease.
As showcased in this article, the immunoSEQ Assay can be applied in a variety of ways to answer specific research questions. For example, researchers have used our immunoSEQ Technology to reveal insights into disease dynamics, immunological markers of disease recurrence, and therapeutic response, as well as to identify pathological clones (see Table 1 for an overview).
Table 1: Applications of the immunoSEQ Assay in autoimmune disease research
|Autoimmune disease||Applications of the immunoSEQ Assay||Reference|
|Multiple sclerosis in pregnancy||Monitoring disease dynamics||Ramien et al. (6)|
|Rheumatoid arthritis||Monitoring disease severity||Kelkka et al. (11), Savola et al. (12)|
|Autologous hematopoietic stem cell transplantation in multiple sclerosis||Identifying and monitoring markers of therapeutic response||Harris et al. (16)|
|Crohn’s disease||Identifying markers of disease recurrence||Allez et al. (18)|
|Rheumatoid arthritis||Identifying drivers of autoimmune disease pathology||Savola et al. (12)|
|Psoriasis||Identifying top clones||Matos et al. (23)|
|Rasmussen encephalitis||Identifying clonal overlaps||Dandekar et al. (25)|
|Narcolepsy and Parkinson’s disease||Identifying and tracking immune responses to self-reactive clones||Singhania et al. (5), Latorre et al. (30)|
|Myasthenia gravis||Tracking B cells that secrete autoantibodies||Jiang et al. (33)|
Once generated, immunoSEQ Data can be explored in the immunoSEQ Analyzer, our powerful and easy-to-use analytics platform. View our series of tutorials to see how simple data analysis is in the immunoSEQ Analyzer. The immunoSEQ Analyzer provides several tools that allow users to:
- Explore and visualize large data sets with sophisticated and intuitive analysis tools.
- Share data with individuals, groups, or reviewers prior to manuscript submission. Users can also make their data sets publicly available at any point.
- Fully export data to other more advanced analytical tools for metadata analyses.
- Add samples directly to their project or easily incorporate millions of sequences from publicly available data sets into their project and analysis pipeline using our immuneACCESS collection—the world’s largest open-access database of T- and B-cell receptor sequences. Learn more about our immuneACCESS database and how it can help to accelerate your research here.
For more information, you can visit our immunoSEQ Assay products page.
Get in touch with our product team if you need help getting started.
For Research Use Only. Not for use in diagnostic procedures.
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- Ramien C, Yusko EC, Engler JB, Gamradt S, Patas K, Schweingruber N, et al. T cell repertoire dynamics during pregnancy in multiple sclerosis. Cell Rep. 2019;29(4):810–15.e4.
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