Ricardo Melo Ferreira

Integrating heterogeneous spatial multi-omics data to uncover underlying biological and pathological mechanisms remains a major challenge, while existing approaches generally lack mathematically justified distances for comparing complex spatial tissues. We introduce Spatial Optimal Transport (SpaOT), a spatial multi-omics integration framework based on a theoretically grounded semi-metric formulation of unbalanced optimal transport. Utilizing a total-variation-relaxed Fused Partial Gromov-Wasserstein strategy, SpaOT establishes a mathematically consistent distance geometry that enables stable biological comparison, representative tissue barycenters, and robust downstream analyses while accommodating differences in cellular composition, measurement technologies, spatial resolution, and noise. Across multiple studies with diverse spatial omics, SpaOT enables robust and accurate alignment, integration, and stratifications across samples, resolutions, and omics modalities in complex disease-related biological systems. These capabilities facilitate the identification of biologically meaningful cellular organization, molecular signatures, and spatial relationships, establishing SpaOT as a general foundation for spatial multi-omics integration and comparative analysis.

Identifying mechanisms of kidney disease commonly involves comparing diseased samples to healthy reference tissues; however, the effects of variability in tissue procurement, storage, and donor characteristics remain underexplored. In this study, we systematically evaluated three reference tissue types—tumor nephrectomy (TN), pre-transplant biopsies from living donors (LD), and percutaneous biopsies from healthy control volunteers (HC)—to determine their impact on differential gene expression across three diabetic kidney disease (DKD) states. We observed distinct injury markers, cell state proportions, and gene signatures associated with procurement method, sex, and donor age. Adjustment for these confounding factors significantly influenced pathway analysis results. Specifically, correcting for age and sex eliminated significant enrichment of interferon gamma response in the diabetes mellitus–resilient (DM-R) versus HC comparison. Processes related to biological aging were enriched in older reference tissues, potentially confounding disease-specific interpretations. Importantly, tumor necrosis factor signaling via nuclear factor-κB remained enriched in LD and TN samples relative to HC, even after accounting for confounders. These results underscore the critical importance of selecting appropriate control tissues and rigorously adjusting for confounding variables to reliably discern the molecular mechanisms underlying kidney diseases.

Systemic lupus erythematosus (SLE) shows marked clinical and molecular heterogeneity, yet patient stratification often relies on gene expression signatures lacking multicellular context. Here we construct a transcriptional patient map of SLE by analyzing 1,167 total samples (783 SLE, 384 healthy controls) across different resolutions, including single-cell and bulk blood as well as spatially resolved kidney tissue transcriptomes. Using an unsupervised approach we inferred patient-level transcriptomic immune programs from two independent single-cell RNA sequencing cohorts of peripheral blood mononuclear cells (PBMCs), capturing both differences between SLE and health as well as within-SLE heterogeneity. Specifically, we identified four conserved programs comprising two multicellular inflammatory programs driven by interferon and TNF/NFkB activity across immune cells, and two cell type-specific programs reflecting CD8 T cell cytotoxicity and a CD4 T cell naive-to-effector state. Functional analysis of these programs revealed a rewiring of both cell-to-cell interactions and task allocation across cell types during disease activation. In addition, mapping these programs onto an external longitudinal blood transcriptomic cohort predicted flare risk and identified candidate blood protein biomarkers detectable by proteomics. Finally, we showed that these blood programs were enriched in immune-infiltrated glomerular regions from kidney biopsies of individuals with lupus nephritis using spatially resolved transcriptomic data, thereby linking systemic immune programs to local tissue pathology. Graphical

Cannabidiol (CBD) use has increased in America due to its widespread availability. Cannabidiol is metabolized by multiple polymorphic enzymes including CYP3A, CYP2C9, and CYP2C19. We sought to evaluate the genotype‐specific adverse events and pharmacokinetic profiles of cannabidiol, 7‐OH cannabidiol (an active metabolite), and 7‐COOH cannabidiol. We completed a secondary analysis of an open‐label, fixed‐sequence, single‐center study of cannabidiol in 33 healthy subjects. Patients first received a single dose of cannabidiol 5 mg/kg orally with serial plasma concentrations measured. Later, patients were titrated to 5 mg/kg twice daily for 14 days to reach steady state with serial plasma concentrations measured. CYP3A, CYP2C9, and CYP2C19 genotypes were assessed. Pharmacokinetic parameters were calculated by noncompartmental analysis. Diarrhea was observed more frequently in individuals with both CYP3A5 poor metabolism and CYP2C19 intermediate/normal metabolism (39%) compared to individuals with other genotypes (7%, p = 0.0463). Individuals with both CYP3A5 poor metabolism and CYP2C19 intermediate/normal metabolism had increased 7‐OH cannabidiol and 7‐COOH cannabidiol exposure at steady state. Cannabidiol parent drug exposure varied by CYP2C19 metabolizer status, with lower cannabidiol exposure and parent to metabolite ratios in intermediate metabolizers after single dose ( p = 0.014) and at steady state ( p = 0.0033). Similar CYP2C19 genotype‐specific exposure was observed in an external validation cohort. Minor differences in exposure of cannabidiol and its metabolites were observed between CYP3A5 and CYP2C9 genotype groups. Significant changes in pharmacokinetics were observed between CYP2C9, CYP2C19, and CYP3A5 genotype groups. Future studies should assess whether pharmacogenomics can predict intestinal concentrations of CBD, its metabolites, and diarrhea.

Building upon a foundational Human Kidney resource, we present a comprehensive multi-modal atlas that defines spatially resolved versus unresolved repair states and mechanisms in human kidney disease. Homeostatic interactions between injured kidney epithelium and its surrounding milieu determine successful repair outcomes, while pathogenic signaling promotes unresolved inflammation and fibrosis leading to chronic disease. We integrated multiple single-cell and spatial modalities across ∼700 samples from >350 patients (∼250 research biopsies), analyzing ∼1.7 million cells alongside complementary mouse multi-omic profiles spanning acute-to-chronic injury and aging (>300,000 cells) and spatial transcriptomic analysis of >150 human biopsies. This cross-species atlas delineates functional pathways and druggable targets across the nephron and defines gene regulatory networks and chromatin landscapes governing tubular, fibroblast, and immune cell transitions from injury to either recovery or failed repair states. We identified distinct cellular states associated with specific pathological features that show dynamic distributions between acute kidney injury (AKI) and chronic kidney disease (CKD), organized within unique spatial niches that reveal progression mechanisms from early injury to unresolved disease. Gene regulatory analyses prioritized key transcription factor activities (SOX4, SOX9, NFKB1, REL, KLFs) and their target networks establishing disease states and tissue microenvironments. These regulatory programs were directly linked to clinical outcomes, identifying molecular signatures of recovery and secreted biomarkers predictive of AKI-to-CKD progression, providing a key resource for therapeutic development and precision medicine approaches in kidney disease.

Spatial technologies examining the cell and tissue microenvironment at near single-cell resolution are revealing important molecular insights. However, few tools enable integrated, interactive analysis of spatial-omics with tissue morphology in the same functional tissue unit. Here, we present FUSION (Functional Unit State Identification in Whole Slide Images), a web-based platform for visualizing and analyzing spatial-omics data with high-resolution histology. FUSION provides workflows for assessing cell compositions, quantitative morphometrics, and comparative tissue analyses. We demonstrate applicability across spatial assays, including 10x Visium, Visium HD, 10x Xenium, Cell DIVE, and PhenoCycler, applied to healthy and diseased tissues from kidney, small intestine, lung, and skin in the Human BioMolecular Atlas Program. FUSION is cloud-based, open-source, and accessible at https://fusion.hubmapconsortium.org/, hosting over 50 paired datasets and tutorials. In a series of use cases, we show its capacity to distinguish renal glomeruli injury states, quantify morphometric changes, and characterize fibrosis with immune infiltration.

The organizational principles of nephronal segments are based on anatomical and physiological attributes that are linked to the homeostatic functions of the kidney. Recent molecular approaches have uncovered layers of deeper signatures and states in tubular cells that arise at various time points on the disease trajectory. Here, we introduce an analytical pipeline of multiplexed spatial protein imaging integrated with RNA expression to characterize proximal tubular subpopulations and neighborhoods in human kidney tissue. We demonstrate that, in reference tissue, a large proportion of S1 proximal tubular epithelial cells expresses thymus antigen 1 (THY1), a mesenchymal stromal and stem cell marker that regulates differentiation. Kidney disease is associated with loss of THY1 and transition toward expression of prominin 1 (PROM1), another stem cell marker recently linked to failed repair. Our data support a model in which the interplay between THY1 and PROM1 expression in proximal tubules associates with their regenerative potential and marks the timeline of disease progression.

Cannabidiol is widely available and often used for pain management. Individuals with kidney disease or renal allografts have limited analgesia options. We conducted a Phase 1 human study to compare the peripheral immune cell distribution before (pre-cannabidiol) and after exposure to cannabidiol at steady state (post-cannabidiol). This ex vivo study included specimens from 23 participants who received oral cannabidiol (up to 5 mg/kg twice daily) for 11 days. Lymphocytes were isolated and stimulated with anti-CD3/CD28 antibodies, with or without tacrolimus. Pharmacodynamic responses were assessed via CellTiter-Glo® proliferation, scRNA-seq, cytokine assays, and flow cytometry. Steady-state plasma concentrations of CBD were quantified via tandem mass spectrometry. We identified an increased proportion of T effector memory (TEM) cells post-cannabidiol (22% increase, P-value of 3.2 x 10 ^-32 ), which correlated with CBD plasma concentrations ( Pearson Corr= 0.77, P-value < 0.01 ). Post-cannabidiol cytokine assays revealed elevated proinflammatory IL-6 protein levels and anti-inflammatory IL-10 levels ( adjusted P-values < 0.0001 ). Cannabidiol reduced overall T and B lymphocyte proliferation with additive immunosuppressive effects to tacrolimus. In flow cytometry, the proportion of TEM and TEMRA increased post-cannabidiol with tacrolimus ( P-values < 0.05 ). Cannabidiol exhibits mixed immunomodulatory effects with pro- and anti-inflammatory signals. Understanding the clinical safety of cannabidiol use is important given the paucity of pain control options available for immunocompromised transplant populations.

10X Xenium is an in situ spatial transcriptomics platform that enables single-cell and subcellular-level gene expression analysis. In Xenium data analysis, defining matched keypoints to align H&E and spatial transcriptomic images is critical for cross-referencing sequencing and histology. Currently, it is labor-intensive for domain experts to manually place keypoints to perform image registration in the Xenium Explorer software. We present Xenium-Align, a keypoint identification method that automatically generates keypoint files for image registration in Xenium Explorer. We validated our proposed method on 14 human kidney samples and one human skin Xenium sample representing healthy and diseased states, with expert manually marked results. These results show that Xenium-Align could generate accurate keypoints for automatically implementing image alignment in the Xenium Explorer software for spatial transcriptomics studies. Our future research aims to optimize the method’s runtime efficiency and usability for image alignment applications.

The maintenance of a healthy epithelial-endothelial juxtaposition requires cross-talk within glomerular cellular niches. We sought to understand the spatially-anchored regulation and transition of endothelial and mesangial cells from health to injury in DKD. From 74 human kidney samples, an integrated multi-omics approach was leveraged to identify cellular niches, cell-cell communication, cell injury trajectories, and regulatory transcription factor (TF) networks in glomerular capillary endothelial (EC-GC) and mesangial cells. Data were culled from single nucleus RNA and ATAC sequencing and three orthogonal spatial transcriptomic technologies for correlation with histopathological and clinical trial data. We identified a cellular niche in diabetic glomeruli enriched in a proliferative endothelial cell subtype (prEC) and altered vascular smooth muscle cells (VSMCs). Cellular communication within this niche maintained pro-angiogenic signaling with loss of anti-angiogenic factors. We identified a TF network of MEF2C, MEF2A, and TRPS1 which regulated SEMA6A and PLXNA2, a receptor-ligand pair opposing angiogenesis. In silico knockout of the TF network accelerated the transition from healthy EC-GCs toward a degenerative (injury) endothelial phenotype, with concomitant disruption of EC-GC and prEC expression patterns. Glomeruli enriched in the prEC niche had histologic evidence of neovascularization. MEF2C activity was increased in diabetic glomeruli with nodular mesangial sclerosis. The gene regulatory network (GRN) of MEF2C was dysregulated in EC-GCs of patients with DKD, but sodium glucose transporter-2 inhibitor (SGLT2i) treatment reversed the MEF2C GRN effects of DKD. The MEF2C, MEF2A, and TRPS1 TF network carefully balances the fate of the EC-GC in DKD. When the TF network is “on” or over-expressed in DKD, EC-GCs may progress to a prEC state, while TF suppression leads to cell death. SGLT2i therapy may restore the balance of MEF2C activity.