Molecular profiling of lupus b cells reveals expansion of somatic mutations in lymphoma-related pathways
Notice bibliographique
Résumé
Abstract Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterized by sustained immune activation, disrupted B cell tolerance, and multi-organ damage. SLE presentation and severity are highly variable, with some patients developing life-threatening complications. Among these, SLE patients exhibit a 2-7x increased lifetime risk of developing B-cell non-Hodgkin lymphoma (B-NHL) compared to the general population. While genetic alterations play an essential role in B-NHL pathogenesis, their contribution to SLE remains poorly defined, limiting our ability to provide risk assessment and intervene early in patients at risk for malignant transformation. Previous studies have shown minimal overlap in germline susceptibility loci for SLE and B-NHL. Conversely, case studies in other autoimmune syndromes suggest that autoreactive B cells can acquire somatic mutations, which may act as early hallmarks of transformation. Here, we hypothesized that double-negative B cells (DN; IgD⁻CD27⁻; the central autoreactive population in SLE) are especially prone to accumulating somatic mutations, including alterations capable of driving overt dysregulation and malignant transformation. To test this, we performed whole-exome sequencing (WES) on flow-sorted circulating naïve, memory, and DN B cells from 35 SLE patients. Matched hematopoietic stem/progenitor cells, monocytes, and buccal DNA were used to filter out germline and lineage-shared variants. Somatic mutations were called using Mutect2, Strelka2, and CaVEMan, retaining variants identified by ≥2 callers and absent in non–B compartments. This design enabled direct comparison of mutational burden and clonal dynamics across B cell subsets within each patient. Higher disease activity (SLEDAI-2K score) correlated with increased proportions of DN and memory B cells and reduced naïve B cells (ρ=0.54, p<0.001; ρ=0.42, p=0.013; ρ=-0.53, p=0.001, respectively), reflecting an imbalance toward antigen-experienced or autoreactive compartments under chronic inflammation. DN and memory B cells also had significantly higher somatic mutation burden than naïve B cells (p=0.001 and p=0.017, respectively). Notably, DN B cells harbored 1,723 unique mutations absent from both naïve and memory subsets. These were significantly enriched in JAK2 and PI3K-Akt-mTOR signaling pathways (FDR<0.05), which regulate B cell activation and differentiation and contribute to tolerance breakdown and sustained immune activation when dysregulated. To distinguish passive mutation accumulation from a clonal selection process, we analyzed variant allele frequencies (VAFs) of mutations shared between B cell subsets within each patient. Among shared mutations, 71.3% (382/536) had higher VAF in DN vs. naïve B cells, and 63.1% (512/812) in DN vs. memory B cells, consistent with selective clonal expansion in the DN compartment. DN B cells also had a higher proportion of non-synonymous shared mutations than memory B cells (71.7% vs. 63.0%, p=0.020). Notably, among DN-expanded mutations, those enriched in canonical B-NHL-associated pathways, including NF-κB and BCR signaling (FDR < 0.05), had significantly higher predicted pathogenicity compared to DN-expanded mutations not in these pathways (CADD score, p = 0.032). Together, these findings suggest that both de novo acquisition and clonal expansion of somatic mutations contribute to the elevated mutational burden and pathogenic potential of DN B cells. Supporting their involvement in transformation events, DN were significantly more likely than memory B cells to carry mutations in genes recurrently mutated in B-NHL (p=0.019), including CARD11, MYD88, and MTOR. Over half of patients (19/35) harbored at least one non-synonymous mutation in a known lymphoma driver gene in the DN compartment. Collectively, these results identify DN B cells as a clonally evolving population that acquires a high burden of mutations under chronic inflammatory conditions in SLE, with some variants affecting genes and pathways relevant to malignant transformation. The accumulation of protein-altering variants in oncogenic signaling pathways further highlights DN cells as a plausible cell of origin for transformation in SLE. These results underscore the value of DN-focused molecular profiling to identify SLE patients with high-risk clonal features, improving monitoring of disease progression and lymphoma transformation potential.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».