Immunoglobulin gene analysis as a tool for investigating human immune responses

Serum immunoglobulins and biomarkers of dementia: a population-based study

BACKGROUND

Inflammation plays a key role in the development of dementia, but its link to early biomarkers, particularly those in plasma or neuroimaging, remains elusive. This study aimed to investigate the association between serum immunoglobulins and biomarkers of dementia.

METHODS

Between 1997 and 2009, serum immunoglobulins (IgA, IgG and IgM) were measured in dementia-free participants of the population-based Rotterdam Study. A random subset of participants had assessment of biomarkers in plasma (total tau (t-tau), neurofilament light chain (NfL), amyloid-β40 (Aβ-40), amyloid-β42 (Aβ-42), while another subset of participants underwent neuroimaging to quantify brain volume, white matter structural integrity and markers of cerebral small vessel disease. Linear regression models were constructed to determine cross-sectional associations between IgA, IgG, IgM and biomarkers of dementia, with adjustment for potential confounders. Multiple testing correction was applied using the false discovery rate. As a sensitivity analysis, we re-ran the models for participants within the reference range of immunoglobulins, excluding those using immunomodulating drugs, and conducted a stratified analysis by APOE-ε4 carriership and sex.

RESULTS

Of 8,768 participants with serum immunoglobulins, 3,455 participants (65.8 years [interquartile range (IQR): 61.5-72.0], 57.2% female) had plasma biomarkers available and 3,139 participants (57.4 years [IQR: 52.7-60.7], 54.4% female) had neuroimaging data. Overall, no associations between serum immunoglobulins and biomarkers of dementia remained significant after correction for multiple testing. However, several suggestive associations were noted: higher serum IgA levels concurred with lower plasma levels of Aβ-42 (standardized adjusted mean difference: -0.015 [95% confidence interval (CI): -0.029--0.002], p = 2.8 × 10-2), and a lower total brain volume, mainly driven by less gray matter (-0.027 [-0.046--0.008], p = 6.0 × 10-3) and more white matter hyperintensities (0.047 [0.016 - 0.077], p = 3.0 × 10-3). In sensitivity analyses, higher IgM was linked to lower t-tau, Aβ-40, and Aβ-42, but also a loss of white matter microstructural integrity. Stratified analyses indicate that these associations potentially differ between carriers and non-carriers of the APOE-ε4 allele and men and women.

CONCLUSIONS

While associations between serum immunoglobulins and early markers of dementia could not be established in this population-based sample, it may be valuable to consider factors such as APOE-ε4 allele carriership and sex in future investigations.

Long-Term Use of Amoxicillin Is Associated with Changes in Gene Expression and DNA Methylation in Patients with Low Back Pain and Modic Changes

Long-term antibiotics are prescribed for a variety of medical conditions, recently including low back pain with Modic changes. The molecular impact of such treatment is unknown. We conducted longitudinal transcriptome and epigenome analyses in patients (n = 100) receiving amoxicillin treatment or placebo for 100 days in the Antibiotics in Modic Changes (AIM) study. Gene expression and DNA methylation were investigated at a genome-wide level at screening, after 100 days of treatment, and at one-year follow-up. We identified intra-individual longitudinal changes in gene expression and DNA methylation in patients receiving amoxicillin, while few changes were observed in patients receiving placebo. After 100 days of amoxicillin treatment, 28 genes were significantly differentially expressed, including the downregulation of 19 immunoglobulin genes. At one-year follow-up, the expression levels were still not completely restored. The significant changes in DNA methylation (n = 4548 CpGs) were mainly increased methylation levels between 100 days and one-year follow-up. Hence, the effects on gene expression occurred predominantly during treatment, while the effects on DNA methylation occurred after treatment. In conclusion, unrecognized side effects of long-term amoxicillin treatment were revealed, as alterations were observed in both gene expression and DNA methylation that lasted long after the end of treatment.

Development and implementation of an automated and highly accurate reporting process for NGS-based clonality testing

B and T cells undergo random recombination of the VH/DH/JH portions of the immunoglobulin loci (B cell) and T-cell receptors before becoming functional cells. When one V-J rearrangement is over-represented in a population of B or T cells indicating an origin from a single cell, this indicates a clonal process. Clonality aids in the diagnosis and monitoring of lymphoproliferative disorders and evaluation of disease recurrence. This study aimed to develop objective criteria, which can be automated, to classify B and T cell clonality results as positive (clonal), No evidence of clonality, or invalid (failed). Using clinical samples with "gold standard" clonality data obtained using PCR/CE testing, we ran NGS-based amplicon clonality assays and developed our own model for clonality reporting. To assess the performance of our model, we analyzed the NGS results across other published models. Our model for clonality calling using NGS-based technology increases the assay's sensitivity, more accurately detecting clonality. In addition, we have built a computational pipeline to use our model to objectively call clonality in an automated fashion. Collectively the results outlined below will have a direct clinical impact by expediting the review and sign-out process for concise clonality reporting.

Application of germline antibody features to vaccine development, antibody discovery, antibody optimization and disease diagnosis

Although the efficacy and commercial success of vaccines and therapeutic antibodies have been tremendous, designing and discovering new drug candidates remains a labor-, time- and cost-intensive endeavor with high risks. The main challenges of vaccine development are inducing a strong immune response in broad populations and providing effective prevention against a group of highly variable pathogens. Meanwhile, antibody discovery faces several great obstacles, especially the blindness in antibody screening and the unpredictability of the developability and druggability of antibody drugs. These challenges are largely due to poorly understanding of germline antibodies and the antibody responses to pathogen invasions. Thanks to the recent developments in high-throughput sequencing and structural biology, we have gained insight into the germline immunoglobulin (Ig) genes and germline antibodies and then the germline antibody features associated with antigens and disease manifestation. In this review, we firstly outline the broad associations between germline antibodies and antigens. Moreover, we comprehensively review the recent applications of antigen-specific germline antibody features, physicochemical properties-associated germline antibody features, and disease manifestation-associated germline antibody features on vaccine development, antibody discovery, antibody optimization, and disease diagnosis. Lastly, we discuss the bottlenecks and perspectives of current and potential applications of germline antibody features in the biotechnology field.

Prediction of Antibody-Antigen Binding via Machine Learning: Development of Data Sets and Evaluation of Methods

BACKGROUND

The mammalian immune system is able to generate antibodies against a huge variety of antigens, including bacteria, viruses, and toxins. The ultradeep DNA sequencing of rearranged immunoglobulin genes has considerable potential in furthering our understanding of the immune response, but it is limited by the lack of a high-throughput, sequence-based method for predicting the antigen(s) that a given immunoglobulin recognizes.

OBJECTIVE

As a step toward the prediction of antibody-antigen binding from sequence data alone, we aimed to compare a range of machine learning approaches that were applied to a collated data set of antibody-antigen pairs in order to predict antibody-antigen binding from sequence data.

METHODS

Data for training and testing were extracted from the Protein Data Bank and the Coronavirus Antibody Database, and additional antibody-antigen pair data were generated by using a molecular docking protocol. Several machine learning methods, including the weighted nearest neighbor method, the nearest neighbor method with the BLOSUM62 matrix, and the random forest method, were applied to the problem.

RESULTS

The final data set contained 1157 antibodies and 57 antigens that were combined in 5041 antibody-antigen pairs. The best performance for the prediction of interactions was obtained by using the nearest neighbor method with the BLOSUM62 matrix, which resulted in around 82% accuracy on the full data set. These results provide a useful frame of reference, as well as protocols and considerations, for machine learning and data set creation in the prediction of antibody-antigen binding.

CONCLUSIONS

Several machine learning approaches were compared to predict antibody-antigen interaction from protein sequences. Both the data set (in CSV format) and the machine learning program (coded in Python) are freely available for download on GitHub.

AIRRscape: An interactive tool for exploring B-cell receptor repertoires and antibody responses

The sequencing of antibody repertoires of B-cells at increasing coverage and depth has led to the identification of vast numbers of immunoglobulin heavy and light chains. However, the size and complexity of these Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) datasets makes it difficult to perform exploratory analyses. To aid in data exploration, we have developed AIRRscape, an R Shiny-based interactive web browser application that enables B-cell receptor (BCR) and antibody feature discovery through comparisons among multiple repertoires. Using AIRR-seq data as input, AIRRscape starts by aggregating and sorting repertoires into interactive and explorable bins of germline V-gene, germline J-gene, and CDR3 length, providing a high-level view of the entire repertoire. Interesting subsets of repertoires can be quickly identified and selected, and then network topologies of CDR3 motifs can be generated for further exploration. Here we demonstrate AIRRscape using patient BCR repertoires and sequences of published monoclonal antibodies to investigate patterns of humoral immunity to three viral pathogens: SARS-CoV-2, HIV-1, and DENV (dengue virus). AIRRscape reveals convergent antibody sequences among datasets for all three pathogens, although HIV-1 antibody datasets display limited convergence and idiosyncratic responses. We have made AIRRscape available as a web-based Shiny application, along with code on GitHub to encourage its open development and use by immuno-informaticians, virologists, immunologists, vaccine developers, and other scientists that are interested in exploring and comparing multiple immune receptor repertoires.

Minimal residual disease detection by next-generation sequencing in multiple myeloma: Promise and challenges for response-adapted therapy

Assessment of minimal residual disease (MRD) is becoming a standard diagnostic tool for curable hematological malignancies such as chronic and acute myeloid leukemia. Multiple myeloma (MM) remains an incurable disease, as a major portion of patients even in complete response eventually relapse, suggesting that residual disease remains. Over the past decade, the treatment landscape of MM has radically changed with the introduction of new effective drugs and the availability of immunotherapy, including targeted antibodies and adoptive cell therapy. Therefore, conventional serological and morphological techniques have become suboptimal for the evaluation of depth of response. Recently, the International Myeloma Working Group (IMWG) introduced the definition of MRD negativity as the absence of clonal Plasma cells (PC) with a minimum sensitivity of <10⁻⁵ either by next-generation sequencing (NGS) using the LymphoSIGHT platform (Sequenta/Adaptative) or by next-generation flow cytometry (NGF) using EuroFlow approaches as the reference methods. While the definition of the LymphoSIGHT platform (Sequenta/Adaptive) as the standard method derives from its large use and validation in clinical studies on the prognostic value of NGS-based MRD, other commercially available options exist. Recently, the LymphoTrack assay has been evaluated in MM, demonstrating a sensitivity level of 10⁻⁵, hence qualifying as an alternative effective tool for MRD monitoring in MM. Here, we will review state-of-the-art methods for MRD assessment by NGS. We will summarize how MRD testing supports clinical trials as a useful tool in dynamic risk-adapted therapy. Finally, we will also discuss future promise and challenges of NGS-based MRD determination for clinical decision-making. In addition, we will present our real-life single-center experience with the commercially available NGS strategy LymphoTrack-MiSeq. Even with the limitation of a limited number of patients, our results confirm the LymphoTrack-MiSeq platform as a cost-effective, readily available, and standardized workflow with a sensitivity of 10⁻⁵. Our real-life data also confirm that achieving MRD negativity is an important prognostic factor in MM.

Antibody repertoire sequencing analysis

High-throughput sequencing for B cell receptor (BCR) repertoire provides useful insights for the adaptive immune system. With the continuous development of the BCR-seq technology, many efforts have been made to develop methods for analyzing the ever-increasing BCR repertoire data. In this review, we comprehensively outline different BCR repertoire library preparation protocols and summarize three major steps of BCR-seq data analysis, i. e., V(D)J sequence annotation, clonal phylogenetic inference, and BCR repertoire profiling and mining. Different from other reviews in this field, we emphasize background intuition and the statistical principle of each method to help biologists better understand it. Finally, we discuss data mining problems for BCR-seq data and with a highlight on recently emerging multiple-sample analysis.

Pandemic, Epidemic, Endemic: B Cell Repertoire Analysis Reveals Unique Anti-Viral Responses to SARS-CoV-2, Ebola and Respiratory Syncytial Virus

Immunoglobulin gene heterogeneity reflects the diversity and focus of the humoral immune response towards different infections, enabling inference of B cell development processes. Detailed compositional and lineage analysis of long read IGH repertoire sequencing, combining examples of pandemic, epidemic and endemic viral infections with control and vaccination samples, demonstrates general responses including increased use of IGHV4-39 in both Zaire Ebolavirus (EBOV) and COVID-19 patient cohorts. We also show unique characteristics absent in Respiratory Syncytial Virus or yellow fever vaccine samples: EBOV survivors show unprecedented high levels of class switching events while COVID-19 repertoires from acute disease appear underdeveloped. Despite the high levels of clonal expansion in COVID-19 IgG1 repertoires there is a striking lack of evidence of germinal centre mutation and selection. Given the differences in COVID-19 morbidity and mortality with age, it is also pertinent that we find significant differences in repertoire characteristics between young and old patients. Our data supports the hypothesis that a primary viral challenge can result in a strong but immature humoral response where failures in selection of the repertoire risk off-target effects.

Ymir: A 3D structural affinity model for multi-epitope vaccine simulations

Vaccine development is challenged by the hierarchy of immunodominance between target antigen epitopes and the emergence of antigenic variants by pathogen mutation. The strength and breadth of antibody responses relies on selection and mutation in the germinal center and on the structural similarity between antigens. Computational methods for assessing the breadth of germinal center responses to multivalent antigens are critical to speed up vaccine development. Yet, such methods have poorly reflected the 3D antigen structure and antibody breadth. Here, we present Ymir, a new 3D-lattice-based framework that calculates in silico antibody-antigen affinities. Key physiological properties naturally emerge from Ymir such as affinity jumps, cross-reactivity, and differential epitope accessibility. We validated Ymir by replicating known features of germinal center dynamics. We show that combining antigens with mutated but structurally related epitopes enhances vaccine breadth. Ymir opens a new avenue for understanding vaccine potency based on the structural relationship between vaccine antigens.

Clonal diversity of the B cell receptor repertoire in patients with coronary in-stent restenosis and type 2 diabetes

Type 2 diabetes mellitus (T2DM) is known as a risk factor for coronary in-stent restenosis (ISR) in patients with coronary artery disease (CAD). Evidence suggests that B cells play a functional role in the progression of atherosclerotic lesions. However, the B cell receptor (BCR) repertoire in patients with ISR remains unclear. This study aims to profile the BCR repertoire in patients with coronary ISR/T2DM. A total of 21 CAD patients with or without ISR/T2DM were enrolled. PBMCs were isolated and examined for BCR repertoire profiles using DNA-seq. Our results showed that the diversity of amino acid sequences in ISR DM patients was higher than that in ISR -DM patients. The frequencies of 21 V/J paired genes differed between ISR DM and -ISR DM patients, while frequencies of 5 V/J paired genes differed between ISR DM and ISR -DM. The -ISR -DM group presented the highest clonotype overlap rate, while ISR DM patients presented the lowest overlap rate. Our study presented the BCR repertoires in patients with ISR/T2DM. The data suggested different BCR signatures between patients with ISR and T2DM. Further analysis of BCR profiles would enhance understanding of ISR.

hIgDFc-Ig inhibits B cell function by regulating the BCR-Syk-Btk-NF-κB signalling pathway in mice with collagen-induced arthritis

Rheumatoid arthritis (RA) is an autoimmune disease targeting the synovium. Previous studies have found that IgD may be a potential target for the treatment of RA. We designed a new type of fusion protein, hIgDFc-Ig (DG), to block the binding of IgD to IgD receptor (IgDR). In this study, we found that DG has a significant therapeutic effect in mice with collagen-induced arthritis (CIA). DG improved the claw of irritation symptoms in these mice, inhibited the pathological changes in spleen and joint tissues, and had a moderating effect on B cell subsets at different inflammatory stages. Moreover, DG could also decrease the levels of IgA, IgD, IgM and IgG subtypes of immunoglobulin in the serum of mice with CIA. In vitro, B cell antigen receptor (BCR) knockout Ramos cells were established using the CRISPR/Cas9 technology to further study the activation of BCR signalling by IgD and the effect of DG. We found that the therapeutic effect of DG in mice with CIA may be achieved by inhibiting the activation of BCR signalling by IgD, which may be related to the activation of Igβ. In summary, DG may be a potential biological agent for the treatment of RA and it has broad application prospects in the future.

Shared transcriptional profiles of atypical B cells suggest common drivers of expansion and function in malaria, HIV, and autoimmunity

Chronic infectious diseases have a substantial impact on the human B cell compartment including a notable expansion of B cells here termed atypical B cells (ABCs). Using unbiased single-cell RNA sequencing (scRNA-seq), we uncovered and characterized heterogeneities in naïve B cell, classical memory B cells, and ABC subsets. We showed remarkably similar transcriptional profiles for ABC clusters in malaria, HIV, and autoimmune diseases and demonstrated that interferon-γ drove the expansion of ABCs in malaria. These observations suggest that ABCs represent a separate B cell lineage with a common inducer that further diversifies and acquires disease-specific characteristics and functions. In malaria, we identified ABC subsets based on isotype expression that differed in expansion in African children and in B cell receptor repertoire characteristics. Of particular interest, IgD⁺IgM^lo and IgD^-IgG⁺ ABCs acquired a high antigen affinity threshold for activation, suggesting that ABCs may limit autoimmune responses to low-affinity self-antigens in chronic malaria.

Single-Cell Transcriptomic Analyses Define Distinct Peripheral B Cell Subsets and Discrete Development Pathways

Separation of B cells into different subsets has been useful to understand their different functions in various immune scenarios. In some instances, the subsets defined by phenotypic FACS separation are relatively homogeneous and so establishing the functions associated with them is straightforward. Other subsets, such as the “Double negative” (DN, CD19+CD27-IgD-) population, are more complex with reports of differing functionality which could indicate a heterogeneous population. Recent advances in single-cell techniques enable an alternative route to characterize cells based on their transcriptome. To maximize immunological insight, we need to match prior data from phenotype-based studies with the finer granularity of the single-cell transcriptomic signatures. We also need to be able to define meaningful B cell subsets from single cell analyses performed on PBMCs, where the relative paucity of a B cell signature means that defining B cell subsets within the whole is challenging. Here we provide a reference single-cell dataset based on phenotypically sorted B cells and an unbiased procedure to better classify functional B cell subsets in the peripheral blood, particularly useful in establishing a baseline cellular landscape and in extracting significant changes with respect to this baseline from single-cell datasets. We find 10 different clusters of B cells and applied a novel, geometry-inspired, method to RNA velocity estimates in order to evaluate the dynamic transitions between B cell clusters. This indicated the presence of two main developmental branches of memory B cells. A T-independent branch that involves IgM memory cells and two DN subpopulations, culminating in a population thought to be associated with Age related B cells and the extrafollicular response. The other, T-dependent, branch involves a third DN cluster which appears to be a precursor of classical memory cells. In addition, we identify a novel DN4 population, which is IgE rich and closely linked to the classical/precursor memory branch suggesting an IgE specific T-dependent cell population.

Minimal residual disease in multiple myeloma: defining the role of next generation sequencing and flow cytometry in routine diagnostic use

For patients diagnosed with multiple myeloma (MM) there have been significant treatment advances over the past decade, reflected in an increasing proportion of patients achieving durable remissions. Clinical trials repeatedly demonstrate that achieving a deep response to therapy, with a bone marrow assessment proving negative for minimal residual disease (MRD), confers a significant survival advantage. To accurately assess for minute quantities of residual cancer requires highly sensitive methods; either multiparameter flow cytometry or next generation sequencing are currently recommended for MM response assessment. Under optimal conditions, these methods can detect one aberrant cell amongst 1,000,000 normal cells (a sensitivity of 10^-6). Here, we will review the practical use of MRD assays in MM, including challenges in implementation for the routine diagnostic laboratory, standardisation across laboratories and clinical trials, the clinical integration of MRD status assessment into MM management and future directions for ongoing research.

[Clonality analysis in practice]

Malignant lymphomas are derived from a common progenitor cell with a unique rearrangement of immunoglobulin or T‑cell receptor genes. Polymerase chain reaction (PCR)-based analyses allow detection of the clone and are an important adjunct for the diagnosis of difficult lymphoproliferations, e.g. for the discrimination of reactive versus malignant lesions. Further applications are detection of disease dissemination and evaluation of the clonal relationship of two lymphomas. However, clonality analysis is not a stand-alone test and must always be considered in context with clinical, histological and immunophenotypic data. For the correct use of clonality analysis, comprehensive knowledge of the biological basis, technical requirements and interpretation are needed in order to avoid incorrect conclusions.

Benchmarking of T cell receptor repertoire profiling methods reveals large systematic biases

Monitoring the T cell receptor (TCR) repertoire in health and disease can provide key insights into adaptive immune responses, but the accuracy of current TCR sequencing (TCRseq) methods is unclear. In this study, we systematically compared the results of nine commercial and academic TCRseq methods, including six rapid amplification of complementary DNA ends (RACE)-polymerase chain reaction (PCR) and three multiplex-PCR approaches, when applied to the same T cell sample. We found marked differences in accuracy and intra- and inter-method reproducibility for T cell receptor α (TRA) and T cell receptor β (TRB) TCR chains. Most methods showed a lower ability to capture TRA than TRB diversity. Low RNA input generated non-representative repertoires. Results from the 5' RACE-PCR methods were consistent among themselves but differed from the RNA-based multiplex-PCR results. Using an in silico meta-repertoire generated from 108 replicates, we found that one genomic DNA-based method and two non-unique molecular identifier (UMI) RNA-based methods were more sensitive than UMI methods in detecting rare clonotypes, despite the better clonotype quantification accuracy of the latter.

RNase H-dependent PCR enables highly specific amplification of antibody variable domains from single B-cells

Immunization-based antibody discovery platforms require robust and effective protocols for the amplification, cloning, expression, and screening of antibodies from large numbers of B-cells in order to effectively capture the diversity of an experienced Ig-repertoire. Multiplex PCR using a series of forward and reverse primers designed to recover antibodies from a range of different germline sequences is challenging because primer design requires the recovery of full length antibody sequences, low starting template concentrations, and the need for all the primers to function under the same PCR conditions. Here we demonstrate several advantages to incorporating RNase H2-dependent PCR (rh-PCR) into a high-throughput, antibody-discovery platform. Firstly, rh-PCR eliminated primer dimer synthesis to below detectable levels, thereby eliminating clones with a false positive antibody titer. Secondly, by increasing the specificity of PCR, the rh-PCR primers increased the recovery of cognate antibody variable regions from single B-cells, as well as downstream recombinant antibody titers. Finally, we demonstrate that rh-PCR primers provide a more homogeneous sample pool and greater sequence quality in a Next Generation Sequencing-based approach to obtaining DNA sequence information from large numbers of cloned antibody cognate pairs. Furthermore, the higher specificity of the rh-PCR primers allowed for a better match between native antibody germline sequences and the VL/VH fragments amplified from single B-cells.

Proteogenomic analysis of granulocyte macrophage colony- stimulating factor autoantibodies in the blood of a patient with autoimmune pulmonary alveolar proteinosis

Recently, attempts to reveal the structures of autoantibodies comprehensively using improved proteogenomics technology, have become popular. This technology identifies peptides in highly purified antibodies by using an Orbitrap device to compare spectra from liquid chromatography-tandem mass spectrometry against a cDNA database obtained through next-generation sequencing. In this study, we first analyzed granulocyte-macrophage colony-stimulating factor (GM-CSF) autoantibodies in a patient with autoimmune pulmonary alveolar proteinosis, using the trapped ion mobility spectrometry coupled with quadrupole time-of-flight (TIMS-TOF) instrument. The TIMS-TOF instrument identified peptides that partially matched sequences in up to 156 out of 162 cDNA clones. Complementarity-determining region 3 (CDR3) was fully and partially detected in nine and 132 clones, respectively. Moreover, we confirmed one unique framework region 4 (FR4) and at least three unique across CDR3 to FR4 peptides via de novo peptide sequencing. This new technology may thus permit the comprehensive identification of autoantibody structure.

Monitoring minimal residual disease in the bone marrow using next generation sequencing

Achieving minimal residual disease (MRD) negativity in the bone marrow is one of the strongest prognostic factors in multiple myeloma. Consequently, MRD testing is routinely performed in clinical trials and moving towards standard of care. This review focuses on the role of next generation sequencing (NGS) of tumor-specific immunoglobulin V(D)J sequences for MRD tracking. The immunoglobulin variable regions are ideal targets for tracking, because every tumor cell shares an identical gene sequence, which is stable over time and generally distinct from the immunoglobulin sequences of normal B-cells. Several excellent assays for NGS-based MRD testing are available, both commercial and community-based, including one that is FDA-approved. These assays can achieve the gold standard analytical sensitivity of one tumor cell per million (10^-6), requiring a minimum input of 3 million bone marrow cells. On-going clinical trials will outline how MRD testing should be used to inform dynamic risk-adopted therapy.

Stability and uniqueness of clonal immunoglobulin CDR3 sequences for MRD tracking in multiple myeloma

Minimal residual disease (MRD) tracking, by next generation sequencing of immunoglobulin sequences, is moving towards clinical implementation in multiple myeloma. However, there is only sparse information available to address whether clonal sequences remain stable for tracking over time, and to what extent light chain sequences are sufficiently unique for tracking. Here, we analyzed immunoglobulin repertoires from 905 plasma cell myeloma and healthy control samples, focusing on the third complementarity determining region (CDR3). Clonal heavy and/or light chain expression was identified in all patients at baseline, with one or more subclones related to the main clone in 3.2%. In 45 patients with 101 sequential samples, the dominant clonal CDR3 sequences remained identical over time, despite differential clonal evolution by whole exome sequencing in 49% of patients. The low frequency of subclonal CDR3 variants, and absence of evolution over time in active multiple myeloma, indicates that tumor cells at this stage are not under selective pressure to undergo antibody affinity maturation. Next, we establish somatic hypermutation and non-templated insertions as the most important determinants of light chain clonal uniqueness, identifying a potentially trackable sequence in the majority of patients. Taken together, we show that dominant clonal sequences identified at baseline are reliable biomarkers for long-term tracking of the malignant clone, including both IGH and the majority of light chain clones.

Cutting Edge: Ig H Chains Are Sufficient to Determine Most B Cell Clonal Relationships

B cell clonal expansion is vital for adaptive immunity. High-throughput BCR sequencing enables investigating this process but requires computational inference to identify clonal relationships. This inference usually relies on only the BCR H chain, as most current protocols do not preserve H:L chain pairing. The extent to which paired L chains aids inference is unknown. Using human single-cell paired BCR datasets, we assessed the ability of H chain-based clonal clustering to identify clones. Of the expanded clones identified, <20% grouped cells expressing inconsistent L chains. H chains from these misclustered clones contained more distant junction sequences and shared fewer V segment mutations than the accurate clones. This suggests that additional H chain information could be leveraged to refine clonal relationships. Conversely, L chains were insufficient to refine H chain-based clonal clusters. Overall, the BCR H chain alone is sufficient to identify clonal relationships with confidence.

Nasal Vaccination Drives Modifications of Nasal and Systemic Antibody Repertoires in Rainbow Trout

Bony fish represent the most basal vertebrate branch with a dedicated mucosal immune system, which comprises immunologically heterogeneous microenvironments armed with innate and adaptive components. In rainbow trout (Oncorhynchus mykiss), a nasopharynx-associated lymphoid tissue (NALT) was recently described as a diffuse network of myeloid and lymphoid cells located in the olfactory organ of fish. Several studies have demonstrated high levels of protection conferred by nasal vaccines against viral and bacterial pathogens; however, the mechanisms underlying the observed protection are not well understood. We applied 5'RACE and a deep sequencing-based approach to investigate the clonal structure of the systemic and mucosal rainbow trout B cell repertoire. The analysis of Ig repertoire in control trout suggests different structures of IgM and IgT spleen and NALT repertoires, with restricted repertoire diversity in NALT. Nasal and injection vaccination with a bacterial vaccine revealed unique dynamics of IgM and IgT repertoires at systemic and mucosal sites and the remarkable ability of nasal vaccines to induce spleen Ig responses. Our findings provide an important immunological basis for the effectiveness of nasal vaccination in fish and other vertebrate animals and will help the design of future nasal vaccination strategies.

TLR9 agonist MGN1703 enhances B cell differentiation and function in lymph nodes

Background

TLR9 agonists are being developed as immunotherapy against malignancies and infections. TLR9 is primarily expressed in B cells and plasmacytoid dendritic cells (pDCs). TLR9 signalling may be critically important for B cell activity in lymph nodes but little is known about the in vivo impact of TLR9 agonism on human lymph node B cells. As a pre-defined sub-study within our clinical trial investigating TLR9 agonist MGN1703 (lefitolimod) treatment in the context of developing HIV cure strategies (NCT02443935), we assessed TLR9 agonist-mediated effects in lymph nodes.

Methods

Participants received MGN1703 for 24 weeks concurrent with antiretroviral therapy. Seven participants completed the sub-study including lymph node resection at baseline and after 24 weeks of treatment. A variety of tissue-based immunologic and virologic parameters were assessed.

Findings

MGN1703 dosing increased B cell differentiation; activated pDCs, NK cells, and T cells; and induced a robust interferon response in lymph nodes. Expression of Activation-Induced cytidine Deaminase, an essential regulator of B cell diversification and somatic hypermutation, was highly elevated. During MGN1703 treatment IgG production increased and antibody glycosylation patterns were changed.

Interpretation

Our data present novel evidence that the TLR9 agonist MGN1703 modulates human lymph node B cells in vivo. These findings warrant further considerations in the development of TLR9 agonists as immunotherapy against cancers and infectious diseases.

Fund

This work was supported by Aarhus University Research Foundation, the Danish Council for Independent Research and the NovoNordisk Foundation. Mologen AG provided study drug free of charge.

Baseline identification of clonal V(D)J sequences for DNA-based minimal residual disease detection in multiple myeloma

Tracking of clonal immunoglobulin V(D)J rearrangement sequences by next generation sequencing is highly sensitive for minimal residual disease in multiple myeloma. However, previous studies have found variable rates of V(D)J sequence identification at baseline, which could limit tracking. Here, we aimed to define the factors influencing the identification of clonal V(D)J sequences. Bone marrow mononuclear cells from 177 myeloma patients underwent V(D)J sequencing by the LymphoTrack assays (Invivoscribe). As a molecular control for tumor cell content, we sequenced the samples using our in-house myeloma panel myTYPE. V(D)J sequence clonality was identified in 81% of samples overall, as compared with 95% in samples where tumor-derived DNA was detectable by myTYPE. Clonality was detected more frequently in patients with lambda-restricted disease, mainly because of increased detection of kappa gene rearrangements. Finally, we describe how the tumor cell content of bone marrow aspirates decrease gradually in sequential pulls because of hemodilution: From the initial pull used for aspirate smear, to the final pull that is commonly used for research. In conclusion, baseline clonality detection rates of 95% or higher are feasible in multiple myeloma. Optimal performance depends on the use of good quality aspirates and/or subsequent tumor cell enrichment.

Immunoglobulin gene analysis as a tool for investigating human immune responses

The human immunoglobulin repertoire is a hugely diverse set of sequences that are formed by processes of gene rearrangement, heavy and light chain gene assortment, class switching and somatic hypermutation. Early B cell development produces diverse IgM and IgD B cell receptors on the B cell surface, resulting in a repertoire that can bind many foreign antigens but which has had self-reactive B cells removed. Later antigen-dependent development processes adjust the antigen affinity of the receptor by somatic hypermutation. The effector mechanism of the antibody is also adjusted, by switching the class of the antibody from IgM to one of seven other classes depending on the required function. There are many instances in human biology where positive and negative selection forces can act to shape the immunoglobulin repertoire and therefore repertoire analysis can provide useful information on infection control, vaccination efficacy, autoimmune diseases, and cancer. It can also be used to identify antigen-specific sequences that may be of use in therapeutics. The juxtaposition of lymphocyte development and numerical evaluation of immune repertoires has resulted in the growth of a new sub-speciality in immunology where immunologists and computer scientists/physicists collaborate to assess immune repertoires and develop models of immune action.