Publications

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.

Integrating single cell RNA-seq profiles is posing new challenges as datasets are rapidly expanding, now with over 100 million cells in the public domain. We present the latest version of the Harmony integration software, which efficiently scales to >100M cells and >1K datasets without specialized hardware. Moreover, optimizations to the underlying algorithm help prevent overintegration in biologically heterogeneous datasets. Harmony2 enables efficient, accurate integration of large, complex single-cell atlases.

Aging of the blood system impacts systemic health and can be traced to hematopoietic stem cells (HSCs). Despite multiple reports on human HSC aging, a unified map detailing their molecular age-related changes is lacking. We developed a consensus map of gene expression in HSCs by integrating seven single-cell datasets. This map reveals previously unappreciated heterogeneity within the HSC population. It also links inflammatory pathway activation (TNF/NFκB, AP-1) and quiescence within a single gene expression program. This program dominates an inflammatory HSC subpopulation that increases with age, highlighting a potential target for further experimental studies and anti-aging interventions.

Identifying response expression quantitative trait loci (reQTLs) can help to elucidate mechanisms of disease associations. Typically, such studies model the effect of perturbation as discrete conditions. However, perturbation experiments usually affect perturbed cells heterogeneously. Here we show that modeling of per-cell perturbation state enhances detection of reQTLs. We use single-cell data to study the effect of perturbations with influenza A virus, Candida albicans, Pseudomonas aeruginosa and Mycobacterium tuberculosis on gene regulation. We found on average 36.9% more reQTLs by accounting for single-cell heterogeneity compared to the standard discrete reQTL model. For example, we detected a decrease in the expression quantitative trait loci effect for PXK with influenza A virus. Furthermore, we found that, on average, 25% of reQTLs have cell-type-specific effects. For example, the reQTL effect for RPS26 was stronger in B cells. Our work provides a general model for more accurate reQTL identification and underscores the value of modeling cell-level variation.

Regulatory T cells (Tregs), characterized by FOXP3 expression, are essential for maintaining immune homeostasis by controlling inflammation. However, in autoimmune diseases such as rheumatoid arthritis (RA), impaired Treg function contributes to immune dysregulation and disease pathology. While most studies of human Tregs have focused on blood, here we analyzed Tregs in synovial tissues from RA patients using single cell RNA sequencing (scRNAseq). We identified two predominant Treg states, CD25 hi CXCR6 pos Tregs with strong suppressive function, and CD25 lo AREG pos Tregs, a dysfunctional state exclusively enriched in synovial tissues but not in blood. Computational and in vitro analyses revealed that cortisol induced AREG expression, suppressed glycolysis, and impaired the suppressive function of CD25 lo AREG pos Tregs. In turn, AREG promoted an IL-33 + inflammatory phenotype in synovial fibroblasts. Importantly, we found that TNFR2 engagement can prevent or reverse this dysfunctional Treg state. In contrast to CD25 lo AREG pos Tregs, CD25 hi CXCR6 pos Tregs were highly suppressive, showed coordinated abundance with macrophages in synovial tissue, and functionally interacted with membrane-bound TNFα expressed by macrophages, which promoted their functional suppressive state. These two Treg subsets were similarly found in the synovial tissue in Juvenile Idiopathic Arthritis (JIA), another inflammatory arthritic disorder, indicating conserved mechanisms across arthritic diseases. Together, our findings define distinct pathways driving divergent functional and dysfunctional Treg states in inflamed tissues and point to interventions that may prevent or reverse the development of the dysfunctional state.

Aging of the blood system impacts systemic health and can be traced to hematopoietic stem cells (HSCs). Despite multiple reports on human HSC aging, a unified map detailing their molecular age-related changes is lacking. We developed a consensus map of gene expression in HSCs by integrating seven single-cell datasets. This map revealed previously unappreciated heterogeneity within the HSC population. It also links inflammatory pathway activation (TNF/NFκB, AP-1) and quiescence within a single gene expression program. This program dominates an inflammatory HSC subpopulation that increases with age, highlighting a potential target for further experimental studies and anti-aging interventions.