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Record W4389231411 · doi:10.1182/blood-2023-182314

Multi-Omic Insights into the Mutational Landscape and Dysregulated Transcriptional Programs of Autoimmune B-Cells in Systemic Lupus Erythematosus

2023· article· en· W4389231411 on OpenAlexaff
Arghavan Ashouri, Pathum Kossinna, Xuyao Li, Jahin Kabir, Jianfan Nie, Artem Kushnirenko, Ilham Abbasi, Leandro Venturutti, Zahi Touma, Federico Gaiti

Bibliographic record

VenueBlood · 2023
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreSpinal Cord Injury BCUniversity of British ColumbiaUniversity Health Network
Fundersnot available
KeywordsImmunologyBiologyEpigeneticsGeneticsB cellImmune dysregulationGeneImmune systemAntibody

Abstract

fetched live from OpenAlex

Systemic Lupus Erythematosus (SLE) is an autoimmune disease with diverse manifestations, from mild and sporadic to severe and life-threatening. SLE heterogeneity arises from various factors, including genetic, epigenetic, and immune niche-related features (Kaul et al., 2016; Jenks et al., 2018). However, the exact interactions and hierarchy between these features remain unclear. Recent studies have found somatic mutations in genes typically mutated in B-cell lymphomas, in subsets of B-cells that are associated with SLE pathogenesis (Piotrowski et al., 2015; Pullabhatla et al., 2018; Singh et al., 2020; Brown et al., 2022). These mutations may support B-cell clonal bursts, but direct information from clinical specimens on the impact of these mutations on B-cell lineages and their influence on SLE progression or malignant transformation is missing. To define the somatic mutational landscape of B-cells in SLE, we first profiled peripheral blood mononuclear cells obtained from a pilot cohort of four SLE patients using whole-exome sequencing (WES; 200X depth). Following GATK best practices (Van der Auwera and O'Connor, 2020), we identified somatic alterations in DDX11 [variant allele frequency (VAF): 10.2%], DNMT3A [VAF: 3.4%]; PMS2 [VAF: 47.9%], and BICD1 [VAF: 47.3%]; these genes have been linked to lymphoid malignancies and SLE pathogenesis (Piotrowski et al., 2015; Pullabhatla et al., 2018; Niroula et al., 2021; Saeed et al., 2021). We validated the presence of the top-identified mutations using droplet digital PCR technology on sorted B-cell subsets (naïve, memory, and double-negative [DN; CD19 hiIgD loCD27 lo]) from these SLE patients. DN cells are a heterogeneous subtype of autoreactive memory B-cells that play a crucial role in SLE pathogenesis being the precursors of autoantibody producing plasma cells (Wei et al., 2007; Jenks et al., 2018). To investigate the transcriptional and epigenetic alterations in the mutation-harboring B-cells, we then conducted single-cell multi-omic sequencing. We profiled sorted activated B-cells (CD19 hiIgD lo) from the four SLE cases, to largely exclude non-autoreactive naïve B-cells. To maintain a comparison with naïve B cells, we included a small proportion of these cells in the input. In total, we analyzed 35,339 cells, and identified different B-cell subsets with distinct gene expression patterns, including DN cells ( n = 1,437 cells; ZEB2 hiTRAF5 lo, Jenks et al., 2018). To uncover, in an unbiased way, transcriptional differences between B-cell subsets, we catalogued variation in transcriptomic signatures derived from the scRNA data using consensus non-negative matrix factorization. We found a unique gene expression program exclusively present in DN cells ( Panel A), which includes key genes implicated in immune regulation and the development of autoimmunity, such as PTPN22 (Chung & Criswell, 2007; Tizaoui et al., 2021) . Pathway analysis of the DN-specific program revealed an enrichment of complement system genes (FDR = 0.074; Hallmark), which are crucial for immune regulation and tolerance, such as CBLB (Tang et al., 2019). Notably, in DN cells from one of the SLE samples carrying lymphoma/SLE-associated mutations in BICD1, PMS2, DDX11, we observed an altered expression of this gene program compared to DN cells from other samples ( P-value = 3.6x10 -11; Panel A, inset), suggesting that a malfunctioning complement system in DN cells may lead to an overly active immune response (Weinstein et al., 2021). In line with this notion, using chromatin accessibility profiles as a measure of transcription factor (TF) regulatory activities, we showed increased activity of TFs involved in interferon-dependent innate immune response and in B-cell activation and differentiation (RFX and OCT-1, respectively; FDR < 0.05), in the DN B-cells of this sample ( Panel B). In summary, we uncovered a unique transcriptional program associated with autoimmune DN B-cells. This program showed enrichment in key genes and pathways involved in immune response regulation. The disruption of this program, accompanied by the somatic SLE-associated mutations, may lead to overactivation of DN B cells, ultimately contributing to autoimmunity. Further analyses involving a larger cohort of clinical specimens are needed to directly link B-cell genotypes with their transcriptional and epigenetic programs and to elucidate the role of the identified mutations in SLE pathobiology.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.270
Teacher spread0.249 · 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 designBench or experimental
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".

Quick stats

Citations2
Published2023
Admission routes1
Has abstractyes

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