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Record W1531341897 · doi:10.1002/acn3.230

Sequencing the immunopathologic heterogeneity in multiple sclerosis

2015· article· en· W1531341897 on OpenAlexaff
Jack P. Antel, Samuel K. Ludwin, Amit Bar‐Or

Bibliographic record

VenueAnnals of Clinical and Translational Neurology · 2015
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsMedicineMultiple sclerosisDermatologyImmunology

Abstract

fetched live from OpenAlex

Plenas et al. are to be congratulated on the application of cutting edge cell and molecular biologic techniques to address central issues regarding the immune-pathogenesis multiple sclerosis (MS) of lesions.1 This was a demanding study with regard to acquisition of patient material, experimental design, quality and quantity of labor involved, and cost. As emphasized in this report, a challenge in MS is to define the immunologic events ongoing in actual lesions and then determine whether and how these may be reflected or monitored by analysis of more readily available tissue samples such as cerebrospinal fluid (CSF) or blood. The authors specifically address the concept of there being distinct phenotypes of early lesions among MS patients, categorized as patterns 1–4.2 Pattern 2 lesions have been described to feature immunoglobulin (Ig) and complement deposition in addition to inflammatory cell infiltration and myelin destruction and were the most frequent lesion pattern observed in the initial combined biopsy and autopsy sample. Data supporting the distinct features of pattern 2 lesions include therapeutic responses to plasma exchange therapy3 and potentially presence of unique serum autoantibody signatures.4 The authors acknowledge the controversy that exists regarding this concept, providing rationale for generating more direct evidence as in this study. This study evolves from an in depth molecular analysis, using next-generation sequencing techniques, of lesions found at autopsy in a case with an extremely aggressive course of MS. The core of the cellular immune data presented is derived from one very active lesion that shows Ig/complement deposition characteristic of pattern 2. Data from two less active lesions are in keeping with observations that the disease process is homogenous in individual cases. The data confirm previous studies based on T-cell receptor (TcR) phenotyping that CD8 T cells are the most frequent T-cell type present in such lesions and that they have a restricted repertoire suggesting that they are responding to a specific antigen. This study now identifies CD4 T cells with identical CDR3 TcR sequences but using different Vβ segments indicating that CD4 T cells are also responding to specific antigen, although no mutations in DNA sequences were detected. The authors derive further information about these clones by identifying the presence of such clones in the CSF of the patient based on having identical CDR3 sequences. They were able to expand these CSF clones non-selectively using phytohemagglutinin and thus derive sufficient cell numbers to examine extensively their cellular properties. As a result of the large amount of work involved, they could identify six CD4 T cell clones (TCCs) in the CSF that based on sequencing results, were also present in lesions. Not all lesion clones, including the most common ones, were present in the CSF. The authors suggest this could reflect that the most active clones are exhausted (limiting the capacity to expand them), technical issues such as availability of full range of regents to select all clones, and of particular clinical relevance that “CSF was not an ideal surrogate for the central nervous system (CNS)”. Ongoing work should further clarify how representative CSF-derived clones are of the entire array present in the MS lesions. A provocative postulate arising from this study is that Th2-biased CD4 clones are present in pattern 2 MS lesions and play a role in lesion pathogenesis by supporting antigen-specific B cell/Ig responses. When re-visiting the original Witebsky criteria to establish causality in autoimmune disease, Rose and Bona5 stated that direct evidence requires adoptive transfer of disease; this, however, is still not readily achievable for a primary human-cell-mediated disorder. Indirect evidence includes “isolation of autoantibodies or self reactive T cells from the organs which represent the major target of autoimmune disease” and reproduction in an animal model (see later comment). The current data indicate that three of the six CD4 clones expanded from the CSF and that corresponded to clones found in the lesions were of the Th2 phenotype; the others, however, did have Th1 properties. Clones derived from another clinical case in which a biopsy showed Type III pathology were all Th1. This study does not address the issue of antigen specificity of the clones. Recent data indicate that although frequency of myelin basic protein (MBP) reactive CD4 T cells in the systemic compartment may not differ between MS patients and controls, their functional properties are distinct with regard to production of proinflammatory cytokines (Th1 and Th17).6 Now recognized is that T-cell support of antibody production extends beyond the initial Th2 versus Th1 paradigms with identification of multifunctional T cells such as Th1 cells coexpressing IFN-γ and IL-10, the identification of follicular helper T cells (Tfh) as a predominant CD4(+) T helper subset for B cells, and the inherent plasticity of different CD4(+) T cells.”7 Furthermore, not all CNS autoreactive antibodies need impact disease expression; these may be part of a person's normal humoral repertoire8 and even contribute to tissue protection or repair. Autoreactive CD4 TCCs could still themselves induce tissue injury through bystander mechanisms mediated by production of effector molecules or by acquisition under inflammatory conditions of promiscuous cytotoxic capability linked to expression of NKG2 molecules that interact with corresponding ligands on the target cells within the lesions.9 The limited access to active MS lesions and scope of work involved makes confirming the results of this study a formidable task. This study could not detect cytokines in the CSF indicating the need for focus on cell analysis, a technically demanding task using the limited number of cells available, with concerns that all the cells will be expanded. Since the type 2 lesion phenotype is common, one asks whether existent reports describing properties of expanded T-cell lines derived from MS patient CSF should have already indicated this Th2 bias. Reproducing the Th1 bias seen in the single pattern 3 case including in those with a Balo's phenotype, would be welcome. This study also puts forth the challenge to those using the animal model experimental autoimmune encephalomyelitis to re-produce the findings reported here in the actual human disease, fulfilling one of the criteria for autoimmunity mentioned above. One notes a parallel of the type of approach used in this study with studies in neuromyelitis optica that initially identified the presence of Ig in the lesions leading to subsequent identification of a specific pathogenic antibody; hopefully similar successes will be achieved in MS. Overall, the current report illustrates the complexities and challenges of applying cutting edge cell and molecular biologic techniques to actual case material but also the potential of using these approaches to answer the important questions that arise from the study. None declared.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.620
GPT teacher head0.464
Teacher spread0.156 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2015
Admission routes1
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