Multimodal computational framework identifies B cell convergence in autoimmunity and ageing
Lou, H.; Zhang, M.; Zhang, B.; Lu, Q.; Zheng, J.; Cao, X.
Show abstract
Identification of the origin of pathogenic immune cells is crucial for therapeutic interventions and diagnosis but pseudotime methods struggle to trace immune cells accurately. Current trajectory inference methods for B cell development and response in health and disease either ignore or underutilize antigen receptor sequence information, limiting their ability to resolve developmental pathways, particularly for pathogenic populations. Widely used methods such as Monocle 3, reconstruct developmental paths from transcriptomic similarity alone, discarding the features from immune receptors. Dandelion has combined the immune receptor features with transcriptomics but it struggles to simulate the trajectory path of B cells. Here we present ClonoTrace, a computational framework that integrates BCR sequence features with transcriptomic trajectory inference through gated fusion of multimodal embeddings. In fetal B cell development and germinal centre development, ClonoTrace achieves higher trajectory inference accuracy than Monocle 3 and Dandelion. Applied to systemic lupus erythematosus, ClonoTrace identifies memory B cell extrafollicular maturation pathway in addition to naive B cell, accompanied by induction of ZEB2 with a concomitant decline of BACH2 along the trajectory, as the alternative origin of pathogenic double negative 2 B cells (DN2) in systemic lupus erythematosus (SLE) patients. In healthy ageing, ClonoTrace identified three pathways from naive, IgM+ memory B cells and switched-memory B cells mature through a DN2-associated transcriptional state that precedes age-associated B cells. ClonoTrace's fate probability algorithm indicated that IgM+memory B cell to ABC transition emerged as the leading candidate age-associated transition, that is a process distinct from SLE DN2 maturation. ClonoTrace provides a generalizable framework for receptor-informed trajectory inference, revealing the developmental pathways of pathogenic B cell populations that are untraceable to single modality approaches in autoimmunity and aging.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Dynamics of genome architecture and chromatin function during human B cell differentiation and neoplastic transformation 96%
- Single Cell Characterization of Myeloma and its Precursor Conditions Reveals Transcriptional Signatures of Early Tumorigenesis 96%
- APMAT analysis reveals the association between CD8 T cell receptors, cognate antigen, and T cell phenotype and persistence 96%
Similar papers in this journal
Similar papers in this journal
- Impact of disease-associated chromatin accessibility QTLs across immune cell types and contexts 96%
- Functional Inference of Gene Regulation using Single-Cell Multi-Omics 95%
- Gene regulatory network inference from CRISPR perturbations in primary CD4+ T cells elucidates the genomic basis of immune disease 95%
Similar papers in this journal
- Biologically informed deep learning to infer gene program activity in single cells 95%
- Lineage-determining transcription factors constrain cohesin to drive multi-enhancer oncogene regulation 95%
- Combined single-cell and spatial transcriptomics reveals the molecular, cellular and spatial bone marrow niche organization 94%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.