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INTRACYTOPLASMIC TOLL- LIKE RECEPTORS (TLR) 7, 9 AND MYD88 IN PERIPHERICAL B CELL SUBSETS AS A PREDICTOR OF RENAL RESPONSE IN PATIENTS WITH LUPUS NEPHRITIS

2025· article· en· W4410512912 on OpenAlexvenueno aff
Fabiola Cassiano-Quezada, Jennifer Balderas-Miranda, José Luis Maravillas‐Montero, Karina Santana-de Anda, Beatriz Alcalá‐Carmona, Nancy R. Mejía‐Domínguez, Yatzil Reyna-Juárez, María José Ostos-Prado, Guillermo Juárez‐Vega, Daniel Alberto Carrillo-Vázquez, Diana Gómez Martín

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLupus nephritisTollReceptorImmunologyNephritisToll-like receptorPathologyInternal medicineInnate immune systemDisease

Abstract

fetched live from OpenAlex

PV134 / #630 Poster Topic: AS16 - Lupus Nephritis-Pathogenesis Background/Purpose A gain of-function mutation within TLR7 was identified in a SLE murine model and increased the survival of B lymphocytes, age associated B cells (ABCs), extrafollicular B lymphocytes and autoantibodies production, mediated by MyD88. The aim of this study is to analyze the role of TLR7, 9 and MyD88 expression in diverse B cell subsets as renal response predictors in patients with lupus nephritis. Methods We included SLE patients who fulfilled the ACR/EULAR 2019 classification criteria and active proliferative LN (Class III or IV +/- V). A blood sample was taken at baseline and 6 months after induction treatment. Treatment with anti-CD20 drugs or IVIg were excluded. The outcome was the renal response. We measured the expression of TLR7, 9 and MyD88 in the B cell subsets: ABCs [CD19 pos CD21 neg/lo CD11c hi Tbet pos ], antibody-secreting cells (ASC) [CD19 pos CD27 hi CD38 hi ], classic memory cells (CMC) [CD19 pos CD27 pos IgD pos/neg ], double negative cells (DNC) [CD27 neg IgD neg ], naïve cells (NC), non-classic memory cells (NCMC) [CD27 neg ] and transitional cells (TrC) [CD21 neg/lo ]) from a peripheral blood sample, using a BD LSR Fortessa flow cytometer and FlowJo software. We quantified the absolute numbers and percentage of TLR7, TLR9, and MyD88, alongside determining the mean fluorescence intensity (MFI). Spearman correlation coefficient was used with quantitative variables. Wilcoxon signed-rank test was used to analyze variables before and after treatment. A logistic regression was used to address association between TLRs and MyD88 expression and renal response. Results 66% of 30 patients reached renal response. These, presented a lower expression of TLR7 in NC (MFI, 573 (498-792) vs 759 (544-873), p<0.05) and expansion of TLR9+ NCMC (1.4% (0.7-2.5) vs 0.3% (0.3-0.4), p<0.05) (Table 1). At follow-up, we observed an expansion of TLR9+ B cells (8.1% (2.6-15) vs 0.5% (0.2-0.6), p<0.05); TLR9+ TrC (MFI, 747 (537-767) vs 0 ((0.0-0.0), p<0.05); TLR7+ TrC (23% (11.1-44.5) vs 0 %(0.0-0.2), p<0.05); TLR7+ NC (27.4 %(7.9-63) vs 0.3 %(0.0-0.4); TLR9+ NCMC (MFI, 1128 (1006-1135) vs 0 (0.0-0.0), p<0.05); classical TLR9+ B cells (1.9 (1.1-3.2) vs 0.07 (0.02-0.09), p<0.05), and a decreased TLR9+ ABCs (0.8 % (0.4-24.4) vs 13% (2.4-67), p<0.05) (Table 2, Figure 2). Table 1. Comparison of B cells at baseline in patients who reached renal response and those who did not. Table 2: B cells at the end of follow-up in patients who reached renal response and those who did not. Figure 1: Paired median analysis with time as an aleatory variable, in patients with and without renal response. Conclusions Our data suggest that renal response is associated with enhanced TLR9 expression in the effector humoral compartment, which might be implicated in the mechanisms of renal damage in lupus nephritis.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.005
GPT teacher head0.243
Teacher spread0.238 · 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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Citations0
Published2025
Admission routes1
Has abstractyes

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