Biology subjects

Hodgin, J.

Publications and source records attributed to Hodgin, J..

5 recordsLinked to original sources

bioRxiv2025

Deep profiling of lupus nephritis kidneys reveals dynamic changes in myeloid cells associated with disease progression

ObjectivesLupus nephritis (LN) is a common, potentially fatal manifestation of systemic lupus erythematosus. We aim 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. MethodsSingle-cell RNA-sequencing (scRNA-seq) was used to profile dissociated kidney samples from 156 LN patients and 30 healthy individuals. Spatial transcriptomics (ST), utilizing a gene panel designed to capture all myeloid subsets identified in the scRNA-seq data, was applied to kidney samples acquired from 6 LN patients and 2 healthy controls. ResultsWe generated a full catalog of the myeloid subsets found in LN kidneys. Our analyses indicated that an increase in irreversible tissue damage, as measured by the NIH 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 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 indicated to interact with parietal epithelial cells, promoting the development of glomerulosclerosis. ConclusionsWe suggest a detailed picture of the changes in the kidney immune mechanisms in LN as this disease progresses.

immunology↗

bioRxiv2024

ComPRePS: An Automated Cloud-based Image Analysis tool to democratize AI in Digital Pathology

Digital pathology using whole slide imaging (WSI) and artificial intelligence (AI) has the potential to transform diagnostic workflows, but adoption remains limited by technical complexity and scalability. We developed the Computational Renal Pathology Suite (ComPRePS), a scalable cloud-based platform that automates WSI ingestion, compartmental segmentation, feature extraction, and AI-assisted interpretation through an integrated high-performance architecture. ComPRePS was evaluated in two use cases. First, using 213 procurement biopsies, we compared conventional assessments with automated AI analyses and a hybrid AI-assisted expert workflow. ComPRePS AI-assisted methods achieved higher precision and significantly improved interobserver agreement for key lesions, including global glomerulosclerosis, interstitial fibrosis and tubular atrophy, and arterial intimal thickening. Second, ComPRePS enabled high-throughput quantitative profiling of glomerular and tubular features across minimal change disease, diabetic nephropathy, and amyloid nephropathy revealing disease-specific phenotypic patterns inaccessible to manual evaluation. Overall, ComPRePS improves reproducibility, interpretability, and objectivity in renal pathology, bridging computation with clinical practice.

pathology↗

bioRxiv2023

Intrarenal myeloid subsets associated with kidney injury are comparable in mice and patients with lupus nephritis

Resident macrophages and infiltrating monocytes in kidneys of patients with lupus nephritis are altered both in frequency and function relative to their counterparts in healthy kidneys. The extent to which mouse models might be useful in developing approaches to target these cells for treating lupus nephritis is poorly understood. Here, we studied four common lupus mouse models that share clinical, serologic, and histopathologic kidney changes with humans. Using single-cell profiling and multiplex spatial imaging to analyze the intrarenal myeloid compartment with the onset of clinical disease in these models, we identified monocyte and macrophage subsets that expand or contract in kidneys with clinical nephritis. A unique subset of classical monocytes expanded with the onset of disease and expressed genes such as CD9, Spp1, Ctsd, Cd63, Apoe, and Trem2 that were previously shown to be induced by tissue injury and play a role in inflammation, lipid metabolism and tissue repair in other organs. Resident macrophages transitioned from a pro-inflammatory to a similar injury-associated state with onset of disease. To test whether these findings in mouse models were also observed in humans, we re-analyzed monocytes and macrophages in a single-cell RNAseq dataset of kidney biopsies from 155 patients with lupus nephritis and 30 healthy donors, collected by the NIH AMP RA/SLE consortium. Human monocytes and macrophages showed conserved changes in gene expression programs associated with lupus nephritis disease indices, and localized to similar kidney microenvironments as in mice. By identifying myeloid subsets and disease-associated alterations in biological processes that are conserved across species, we provide a strong rationale for functional studies of these cells and pathways in mice to uncover mechanisms and find targets relevant to human lupus nephritis. One sentence summaryThis study characterizes intrarenal myeloid cells from four lupus mouse models and 155 patients with lupus nephritis using single-cell RNA-seq and imaging, and identifies novel infiltrating and resident myeloid subsets that are conserved between mouse and human lupus nephritis, thus providing a map and strong rationale for functional studies in mice with relevance to human disease.

immunology↗

bioRxiv2020

Novel Human Kidney Cell Subsets Identified by Mux-Seq

BackgroundThe kidney is a highly complex organ that performs multiple functions necessary to maintain systemic homeostasis, with complex interplay from different kidney sub-structures and the coordinated response of diverse cell types, few known and likely many others, as yet undiscovered. Traditional global sequencing techniques are limited in their ability to identify unique and functionally diverse cell types in complex tissues. MethodsHerein we characterize over 45,000 cells from 10 normal human kidneys using unbiased single-cell RNA sequencing. We also apply, for the first time, an approach of multiplexing kidney samples (Mux-Seq), pooled from different individuals, to save input sample amount and cost. We applied the computational tool Demuxlet to assess differential expression across multiple individuals by pooling human kidney cells for scRNA sequencing, utilizing individual genetic variability to determine the identity of each cell. ResultsMultiplexed droplet single-cell RNA sequencing results were highly correlated with the singleplexed sample run data. One hundred distinct cell cluster populations in total were identified across the major cell types of the kidney, with varied functional states. Proximal tubular and collecting duct cells were the most heterogeneous, displaying multiple clusters with unique ontologies. Novel proximal tubular cell subsets were identified with regenerative potential. Trajectory analysis demonstrated evolution of cell states between intercalated and principal cells in the collecting duct. ConclusionsHealthy kidney tissue has been successfully analyzed to detect all known renal cell types, inclusive of resident and infiltrating immune cells in the kidney. Mux-Seq is a unique method that allows for rapid and cost-effective single cell, in depth, transcriptional analysis of human kidney tissue. Significance StatementUse of renal biopsies for single cell transcriptomics is limited by small tissue availability and batch effects. In this study, we have successfully employed the use of Mux-Seq for the first time in kidney. Mux-Seq allows the use of single cell technology at a much more cost-effective manner by pooling samples from multiple individuals for a single sequencing run. This is even more relevant in the case of patient biopsies where the input of tissue is significantly limited. We show that the data from overlapping tissue samples are highly correlated between Mux-Seq and traditional Singleplexed RNA seq. Furthermore, the results from Mux-Seq of 4 pooled samples are highly correlated with singleplexed data from 10 singleplex samples despite the inherent variability among individuals.

genomics↗

bioRxiv2018

Organoid single-cell profiling identifies a transcriptional signature of glomerular disease

Podocyte injury is central to many forms of kidney disease, but transcriptional signatures reflecting podocyte injury and compensation mechanisms are challenging to analyze in vivo. Human kidney organoids derived from pluripotent stem cells (PSCs), a new model for disease and regeneration, present an opportunity to explore the transcriptional plasticity of podocytes. Here, transcriptional profiling of over 12,000 single cells from human PSC-derived kidney organoid cultures was used to identify robust and reproducible cell-lineage gene expression signatures shared with developing human kidneys based on trajectory analysis. Surprisingly, the gene expression signature characteristic of developing glomerular epithelial cells was also observed in glomerular tissue from a kidney disease cohort. This signature correlated with proteinuria and inverse eGFR, and was confirmed in an independent podocytopathy cohort. Three genes in particular were further identified as critical components of the glomerular disease signature. We conclude that cells in human PSC-derived kidney organoids reliably recapitulate the developmental transcriptional program of podocytes and other cell lineages in the human kidney, and that the early transcriptional profile seen in developing podocytes is reactivated in glomerular disease. Our findings demonstrate an innovative approach to identifying novel molecular programs involved in the pathogenesis of glomerulopathies.

systems biology↗