We describe the establishment and current content of the ImmuneCODE™ database, which includes hundreds of millions of T-cell Receptor (TCR) sequences from over 1,400 subjects exposed to or infected with the SARS-CoV-2 virus, as well as over 135,000 high-confidence SARS-CoV-2-specific TCRs. This database is made freely available, and the data contained in it can be downloaded and analyzed online or offline to assist with the global efforts to understand the immune response to the SARS-CoV-2 virus and develop new interventions.
Lyme disease, the most common tick-borne illness in the United States, is most frequently caused by infection with Borrelia burgdorferi. Although early antibiotic treatment can prevent development of severe illness and late manifestations, diagnosis is challenging in patients who do not present with a typical erythema migrans rash. To support a diagnosis of Lyme disease in such cases, guidelines recommend 2-tiered serologic testing. However, 2-tiered testing has numerous limitations, including ambiguity in interpretation and lower sensitivity in early disease. We developed a diagnostic approach for Lyme disease based on the T-cell response to B. burgdorferi infection by immunosequencing T-cell receptor (TCR) repertoires in blood samples from 3 independent cohorts of patients with laboratory-confirmed or clinically diagnosed early Lyme disease, as well as endemic and non-endemic controls. We identified 251 public, Lyme-associated TCRs that were used to train a classifier for detection of early Lyme disease with 99% specificity. In a validation cohort of individuals with early Lyme disease, TCR testing demonstrated a 1.9-fold increase in sensitivity compared to standard 2-tiered testing (STTT; 56% versus 30%), with a 3.1-fold increase <=4 days from the onset of symptoms (44% versus 14%). TCR positivity predicted subsequent seroconversion in 37% of initially STTT-negative patients, suggesting that the T-cell response is detectable before the humoral response. While positivity for both tests declined after treatment, greater declines in posttreatment sensitivity were observed for STTT compared to TCR testing. Higher TCR scores were associated with clinical measures of disease severity, including abnormal liver function test results, disseminated rash, and number of symptoms. A subset of Lyme-associated TCRs mapped to B. burgdorferi antigens, demonstrating high specificity of a TCR immunosequencing approach. These results support the clinical utility of T-cell-based testing as a sensitive and specific diagnostic for early Lyme disease, particularly in the initial days of illness.
Background T cells, as part of the adaptive immune system, are a significant driver of inflammation in Crohn’s disease (CD), yet specific T-cell targets are largely unknown. Genetic factors contribute to a small portion of CD risk including several HLA alleles, such as DRB1*07:01 and HLA-DRB1*01:03, associated with CD. The involvement of HLAs suggests that studying specific T cells could lead to new insights into CD development and progression. In this study, we use established immunoSEQ® technology to profile T-cell receptors (TCRs) and identify TCRs associated with CD and CD characteristics. Methods We analyzed TCRs from blood of 1,738 CD cases and 4,970 healthy controls. TCRs that were statistically enriched in cases, but not healthy controls (p <0.001), were termed Enhanced Sequences (ES) associated with CD. An independent cohort of 434 CD cases was used for validation. We inferred associations between the ES and 145 common HLA alleles using data from a separate, HLA-typed dataset. We defined ES clusters by correlating TCRs with single amino acid substitutions. Results We identified 1,121 CD-associated ES in the exploratory cohort. These were also enriched in CD cases in our validation cohort (Fig 1A). Using intestinal tissue samples from a subset of cases, we found that a median of 14% ES from individual cases were shared between blood and tissue samples (Fig. 1B). ES breadth (ES diversity relative to total TCR diversity) was significantly associated with history of CD-related surgery (Fig 1C, p < 1x10-15), with stricturing or fistulizing phenotypes (Fig 1D, p < 1x10-5 for B1 versus B2 or B3), and with ileal or ileocolonic location (Fig 1E, p < 1x10-7 for L2 versus L1 or L3). We found that 202 ES formed clusters of similar sequences consisting of 2–23 members (Fig. 2A). We confidently (p < 0.0001) associated 398 ES to a specific HLA allele (Fig 2B), including 134 of the ES assigned to clusters (Fig 2A). Some clusters, including the largest, had no members that could be assigned to an HLA allele, raising the possibility that these ES clusters bind non-canonical HLAs. Conclusion Our discovery set of public TCRs associated with CD indicates that the immune system of CD patients responds to a consistent set of antigens. Importantly, CD ES were present in both tissue and blood, demonstrating that evaluating TCRs in blood may be a surrogate of TCRs in tissue. The HLA allele associations of these ES potentially point to new risk factors and disease insights, such as the involvement of DP and DQ alleles. The association of ES frequency with CD characteristics strongly suggested that further examination of these TCRs may impact CD patient care and advance understanding of the pathophysiology of the disease.
Background Changing climate and demographic trends have led to recent increases in the incidence of tick-borne illnesses. Early diagnosis of Lyme disease (LD) is critical for initiation of antibiotics to mitigate symptoms and prevent late manifestations. In patients not presenting with a typical erythema migrans rash, 2-tiered serologic testing is recommended to support a diagnosis of LD. However, 2-tiered testing is limited by ambiguity in interpretation and low sensitivity in early disease, highlighting an unmet clinical need for alternative diagnostic approaches. We identified a clinical signal for early LD based on evaluation of the T-cell response to B. burgdorferi infection. Methods We immunosequenced T-cell receptor (TCR) repertoires in blood samples from 3 independent cohorts of patients with laboratory-confirmed or clinically diagnosed early LD and endemic/non-endemic controls to identify 251 public, LD-associated TCRs. These TCRs were used to train a classifier that identified early LD with 99% specificity. Classifier sensitivity was evaluated in 211 LD cases and 2631 endemic controls and compared to that of standard 2-tiered testing (STTT). Biologic specificity was assessed by correlating TCR assay scores with clinical measures and by mapping the antigen specificity of Lyme-associated TCRs to B. burgdorferi antigens. Figure 1. LD-associated TCRs distinguish cases (orange) from controls (blue) in training cohorts. (A) Logistic-growth curve used to define a scoring function. (B) Positive-call threshold (99th percentile in endemic controls). Results In early LD, TCR testing demonstrated a 1.9-fold increase in sensitivity compared to STTT (56% vs 30%), with a 3.1-fold increase ≤4 days from the onset of symptoms (44% vs 14%). TCR positivity predicted subsequent seroconversion in 37% of initially STTT-negative patients, suggesting the T-cell response is detectable before the humoral response. While positivity for both tests declined following treatment, greater declines in posttreatment sensitivity were observed for STTT compared to TCR testing. Higher TCR scores were associated with measures of disease severity, including abnormal liver function tests, disseminated rash, and number of symptoms. A subset of LD-associated TCRs mapped to B. burgdorferi antigens, demonstrating the high specificity of a TCR immunosequencing approach. Figure 2. Validation of the TCR classifier in the JHU cohort and other holdout endemic controls. Distribution of model scores (A) and assay sensitivity (B). Model scores (C) and ROC (D) curves by serostatus. Figure 3. Clinical correlates of TCR scoring. (A) Liver function test; (B) lymphocyte count, (C) rash presentation, (D) number of symptoms. Conclusion T-cell-based testing has potential clinical utility as a sensitive and specific diagnostic for early LD, particularly in the initial days of illness. Disclosures Sudeb C. Dalai, MD, PhD, Adaptive Biotechnologies (Employee, Shareholder) Julia Greissl, PhD, Microsoft (Employee, Shareholder) Mitch Pesesky, PhD, Adaptive Biotechnologies (Employee, Shareholder) Allison W. Rebman, MPH, Global Lyme Alliance (Research Grant or Support)Steven and Alexandra Cohen Foundation (Research Grant or Support) Mark J. Soloski, PhD, NIH grant P30 AR070254 (Grant/Research Support)Steven and Alexandra Cohen Foundation (Research Grant or Support) Elizabeth J. Horn, PhD, Adaptive Biotechnologies (Research Grant or Support)Bay Area Lyme Foundation (Research Grant or Support)Lyme Disease Biobank (Employee)Steven and Alexandra Cohen Foundation (Research Grant or Support) Jennifer N. Dines, MD, Adaptive Biotechnologies (Employee, Shareholder) Rachel M. Gittelman, PhD, Adaptive Biotechnologies (Employee, Shareholder) Thomas M. Snyder, PhD, Adaptive Biotechnologies (Employee, Shareholder) Ryan O. Emerson, PhD, Adaptive Biotechnologies (Other Financial or Material Support, Employment with Adaptive Biotechnologies during the time of this study) Edward Meeds, PhD, Microsoft (Employee, Shareholder) Thomas Manley, MD, Adaptive Biotechnologies (Other Financial or Material Support, Declares employment with Adaptive Biotechnologies during the time of this study) Ian M. Kaplan, PhD, Adaptive Biotechnologies (Employee, Shareholder) Lance Baldo, MD, Adaptive Biotechnologies (Employee, Shareholder, Leadership Interest) Jonathan M. Carlson, PhD, Microsoft (Employee, Shareholder) Harlan S. Robins, PhD, Adaptive Biotechnologies (Board Member, Employee, Shareholder) John Aucott, MD, Adaptive Biotechnologies (Advisor or Review Panel member)Bay Area Lyme Foundation (Other Financial or Material Support, Scientific Advisory Board member)Department of Health and Human Services (Other Financial or Material Support, Past Chair, 2018, HHS Tick-borne Disease Working Group, Office of HIV/AIDS and Infectious Disease Policy, Office of the Assistant Secretary of Health)Expert testimony (Other Financial or Material Support, Expert testimony)Global Lyme Alliance (Research Grant or Support)Pfizer (Consultant)Steven and Alexandra Cohen Foundation (Research Grant or Support)Tarsus Pharmaceuticals (Consultant)
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