Longitudinal analysis of peripheral blood T cell receptor diversity in patients with systemic lupus erythematosus by next-generation sequencing
Bibliographic record
Abstract
INTRODUCTION: T cells play an important role in the pathogenesis of systemic lupus erythematosus (SLE). Clonal expansion of T cells correlating with disease activity has been observed in peripheral blood (PB) of SLE subjects. Recently, next-generation sequencing (NGS) of the T cell receptor (TCR) β loci has emerged as a sensitive way to measure the T cell repertoire. In this study, we utilized NGS to assess whether changes in T cell repertoire diversity in PB of SLE patients correlate with or predict changes in disease activity. METHODS: Total RNA was isolated from the PB of 11 SLE patients. Each subject had three samples, collected at periods of clinical quiescence and at a flare. Twelve age-matched healthy controls (HC) were used for reference. NGS was used to profile the complementarity-determining region 3 (CDR3) of the rearranged TCR β loci. RESULTS: Relative to the HC, SLE patients (at quiescence) demonstrated a 2.2-fold reduction in repertoire diversity in a given PB volume (P <0.0002), a more uneven distribution of the repertoire (Gini coefficient, HC vs SLE, P = 0.015), and a trend toward increased percentage of expanded clones in the repertoire (clone size >1.0%, HC vs SLE, P = 0.078). No significant correlation between the overall repertoire diversity and clinical disease activity was observed for most SLE patients with only two of eleven SLE patients showing a decreasing trend in repertoire diversity approaching the flare time point. We did not observe any overlap of CDR3 amino acid sequences or a preferential Vβ or Jβ gene usage among the top 100 expanded clones from all SLE patients. In both HC and SLE, the majority of the expanded clones were remarkably stable over time (HC = 5.5 ±0.5 months, SLE = 7.2 ±2.4 months). CONCLUSIONS: A significant decrease in T cell repertoire diversity was observed in PB of SLE patients compared to HC. However, in most SLE patients, repertoire diversity did not change significantly with increases in disease activity to a flare. Thus, without a priori knowledge of disease-specific clones, monitoring TCR repertoire in PB from SLE patients is not likely to be useful to predict changes in disease activity.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".