Publications

Single-cell analysis has rapidly expanded to produce cell atlases encompassing all human tissues. However, computational methods to deconvolute bulk samples using single-cell reference data have failed to keep pace with the increasing data size. Here we present cellGeometry, which uses non-negative geometric deconvolution (NGD), an intuitive vector projection method featuring non-negative matrix regularisation. Using matrix operations, cellGeometry scales to massive datasets and is ultrafast. Benchmarked using simulations from single-cell/nucleus RNA-Seq datasets with >3 million cells, cellGeometry is more accurate than existing methods and more robust against noise simulating different sequencing chemistries. It identifies outlying residual genes which may unveil pathogenic changes in gene expression and the presence of cell types absent from the reference. cellGeometry's flexible architecture allows merging of single-cell reference signatures to expand the range of cell types being deconvoluted. Validated against real bulk RNA blood and tissue samples, cellGeometry produces more accurate and realistic results.

The T cell receptor (TCR) has long been studied through the lens of antigen recognition, with decades of work characterizing how the TCR sequence specifies the peptide-MHC ligands a T cell can engage. Yet a growing body of evidence indicates that the TCR sequence carries another dimension of functional information: it biases the transcriptional fate a T cell is likely to adopt. In this review, we synthesize the evidence that TCR sequence features shape T cell differentiation during both thymic development and peripheral responses. We provide an overview of the landscape of T cell fates and the TCR structure, describe advancements in technologies to profile T cell phenotype and TCR sequence, and outline computational strategies for modeling the relationship between them. We specifically examine four reproducible axes of covariation between TCR sequence and T cell fate, including innate-like lineages, regulatory T cells, CD4 versus CD8 commitment, and peripheral memory formation. Understanding the probabilistic fate biases encoded by the TCR may advance our ability to interpret repertoires in health and disease and engineer next-generation cellular therapies.

Thousands of genetic variants are associated with autoimmune diseases, but causal variants, their mechanisms, and the pathogenic context in which they act are elusive. Knowledge of pathogenic contexts may enable effective targeted therapies, instead of broad immunosuppressive approaches. First, to focus on the genetics of immune response, we used surface marker CITE-seq data from 1,055,857 peripheral blood mononuclear cells from 356 individuals. We defined genetic associations to 148 surface proteins across eight cell types. We observed a signal in the CD40 locus, implicated in rheumatoid arthritis (RA) and other autoimmune conditions. RA risk variants increased CD40 protein expression by ∼20% on B cells, but with minimal mRNA effects. Second, we deployed base-resolution genome editing, with CRAFT-seq, capturing genomic DNA sequence at the edited site and multimodal phenotypes at single-cell resolution. We defined a single causal allele, rs1883832, within the Kozak motif. Third, we edited this allele, in primary B cells and conducted CRAFTseq to demonstrate trans -effects in >200 genes. These effects were only in the light zone germinal center-like state. Importantly, these trans -effects were not seen in population-scale cohorts of unstimulated B cells. This represents a framework to define disease causal alleles, their cis - and trans -effects. It demonstrates the power of defining causal genetic variation to find trans -effects through editing, which cannot easily be found in population studies.

Lupus nephritis (LN), a severe manifestation of systemic lupus erythematosus (SLE), is a heterogeneous disease driven by diverse immune and tissue cell types. We obtained 538,194 single-cell and 142,881 single-nuclear profiles from kidney biopsies of 155 patients with LN and 30 preimplantation transplant biopsy controls, along with 327,326 single-cell blood profiles. We characterized key stromal and immune cell types and cell states; moreover, we distinguished cell states that were tissue specific from those that were also present in the blood. We observed that LN pathological features were associated with particular cell states. For example, after controlling for the effects of chronic tissue damage, we observed that expansion of glomerular and scar-associated macrophage populations correlated with increasing inflammatory disease activity. Scar-associated macrophages appear to drive LN fibrosis and, in active disease, infiltrate the glomeruli more than other myeloid cells. These observations support that therapeutic targeting of myeloid populations may offer a strategy to prevent renal inflammation and ongoing kidney damage in LN.

Regulatory T cells (Treg cells), characterized by FOXP3 expression, maintain immune homeostasis, but their function is impaired in autoimmune diseases such as rheumatoid arthritis (RA). Here we used single-cell RNA sequencing to analyze Treg cells in synovial tissues from patients with RA. We identified two predominant Treg states, CD25hiCXCR6pos Treg cells and dysfunctional CD25loAREGpos Treg cells, both enriched in synovial tissues but not in blood. Cortisol, activated by fibroblasts, drove AREG expression and impaired suppressive function in CD25loAREGpos Treg cells, and AREG promoted an inflammatory phenotype in synovial fibroblasts. By contrast, CD25hiCXCR6pos Treg cells remained highly suppressive and were supported by membrane-bound tumor necrosis factor (TNF)-expressing macrophages. TNFR2 engagement prevented or reversed the dysfunctional Treg cell state. These two Treg cell subsets were also observed in juvenile idiopathic arthritis, indicating shared mechanisms across inflammatory arthritis. These findings define distinct pathways driving functional and dysfunctional Treg cell states in inflamed tissues and implicate potential therapeutic strategies.

T cell receptors (TCR) orchestrate adaptive immunity, yet the complex, repetitive architecture of the TCR loci has impeded systematic characterization of human genetic variation in the genes encoding the TCR. Using public long-read sequencing data from the Human Pangenome Reference Consortium and All of Us consortia spanning 2719 donors, we build a near-complete map of common alleles in TCR V, D, and J genes, revealing amino acid variation at almost every position within V genes. We observe allele frequency differences between populations for many individual TCR genes. We present evidence of natural selection on TCR genes, including signals of balancing selection and positive selection in the alpha chain locus. We find TCR allelic polymorphism alters core functional properties of T cells, including thymic fate commitment and cell-surface receptor abundance. Collectively, these findings position inherited variation in TCR genes as a key axis of immunological diversity that may shape interindividual differences in immune responses.

OBJECTIVE: We aimed to characterize CD4+ T cell plasticity in human SLE by leveraging TCR repertoire features as markers of prior lineage states, integrating TCR and transcriptomic profiling to delineate plasticity patterns and evaluate their association with clinical disease activity.

METHODS: We utilized T cell receptor (TCR) repertoire data as molecular signatures alongside a transcriptomic dataset. Using a large-scale ImmuNexUT database of autoimmune disease patients including 117 SLE cases, we quantified T cell plasticity across 13 fine-grained T cell-types. We analyzed 6,392 samples in total. We defined "cell-type" and "disease" signatures and evaluated plasticity by correlations between these signatures and by within-donor TCR clonotype overlap. Replication was performed in independent bulk and single-cell cohorts.

RESULTS: We identified two orthogonal signatures of repertoire and transcriptome, the cell-type and disease signatures, allowing us to investigate CD4+ T cell plasticity comprehensively. Among all possible patterns, the strongest signal was observed between effector regulatory T cells (eTreg) and Th1 cells, and this was replicated in an independent cohort. SLE Th1 cells exhibited Treg-like TCR features and transcriptomic profiles, and eTreg showed increased clonotype sharing with Th1 compared with healthy controls. Th1 "Tregness" score positively correlated with SLE disease activity.

CONCLUSION: Our study identifies a Treg-associated Th1 state in human SLE, consistent with Treg-to-Th1 plasticity.

OBJECTIVES: Lupus nephritis (LN) is a common, potentially fatal manifestation of systemic lupus erythematosus. We aimed to gain new insights into the immune responses underlying LN and their relation to the histologic heterogeneity observed in this disease, focusing on myeloid cells.

METHODS: We used single-cell RNA-sequencing (scRNA-seq) data of dissociated kidney samples from 156 patients with LN and 30 healthy individuals. We applied spatial transcriptomics (ST), utilising a gene panel designed to capture all myeloid subsets identified in the scRNA-seq data, to profile kidney samples acquired from 6 patients with LN and 2 controls.

RESULTS: We generated a catalogue of the myeloid subsets found in LN kidneys. Our analyses indicated that an increase in irreversible tissue damage, as measured by the National Institutes of Health chronicity index (CI), is associated with a gradual switch of the local immune response from one dominated by monocytes and macrophages to one featuring expanded CD4 T, GZMK+ CD8 T, B, and dendritic cells, with a parallel decrease in the interferon response. In proliferative/mixed LN only, the degree of active inflammation correlates with the expansion of disease-specific macrophage (DMac) subsets, which later contract as the CI increases. Trajectory analysis of the scRNA-seq data suggested that DMacs arise from both infiltrating monocytes and tissue-resident macrophages; this was supported by the ST data, as well as cell cultures. DMacs are implied to interact with parietal epithelial cells, promoting the development of glomerulosclerosis.

CONCLUSIONS: We suggest a detailed picture of the changes in the kidney immune mechanisms in LN as this disease progresses.

Understanding the genetic regulation of RNA abundance is essential for defining disease mechanisms. Conventional expression quantitative trait locus (eQTL) studies measure steady-state RNA and capture effects across the entire transcript lifecycle. While most eQTL likely affect transcription by altering promoter or enhancer function within the nucleus, others may act post-transcriptionally through RNA modification or stability in the cytosol. To distinguish these mechanisms, we compare eQTL from mature cellular RNA and recently transcribed nuclear RNA in brain and kidney. We identify distinct causal variants underlying cellular and nuclear eQTL at the same eGenes. Cellular eQTL are enriched in transcribed regions (P = 3.3×10⁻¹²⁶), suggesting post-transcriptional regulation, whereas nuclear eQTL are enriched in distal regulatory elements (P = 7.0×10⁻³²), consistent with transcriptional control. For example, stop-gain variants likely acting through nonsense-mediated decay appear only in cellular eQTL. Conversely, nuclear eQTL variants (e.g., TUBGCP4) within enhancers sometimes uniquely colocalize with disease loci (schizophrenia), revealing distinct regulatory mechanisms.

Lupus nephritis (LN), a severe manifestation of Systemic Lupus Erythematosus (SLE), is a heterogeneous disease driven by diverse immune and tissue cell types. We obtained 538K single-cell and 140K single-nuclear profiles from kidney biopsies of 155 LN patients and 30 pre-implantation transplant biopsy controls, along with 325K single-cell blood profiles overlapping many of these patients. We identified key tissue cell types and cell states, and immune cell states; we were able to determine cell states that were tissue specific, and those that were present in the blood. We observed that LN pathological features are significantly associated with cell states using differential gene expression and Covarying Neighborhood Analysis (CNA). These analyses revealed broad changes in cell states associated with irreversible chronic tissue damage. After controlling for the effects of ongoing tissue damage, we observed that expansion of key glomerular and Scar Associated Macrophages (SAMs) populations tracked with increasing inflammatory disease activity. SAMs appear to drive LN fibrosis and, in active disease, infiltrate the glomeruli more than other myeloid cells. These observations strongly support that therapeutic targeting of myeloid populations may offer an as-of-yet unproven strategy to prevent renal inflammation and ongoing kidney damage in LN.