Biology subjects

Gurajala, S.

Publications and source records attributed to Gurajala, S..

4 recordsLinked to original sources

bioRxiv2026

Rethinking the Benign Nature of Class II Lupus Nephritis

Introduction: Class II lupus nephritis (LN) is considered clinically benign, yet up to 50% of patients progress to more severe disease and no molecular characterization exists. We aimed to define the single-cell landscape of Class II LN and identify cellular and transcriptional features associated with kidney outcome. Methods: We performed single-cell RNA sequencing on kidney biopsies from fifteen Class II LN patients (eight de novo, seven regressed from prior proliferative or membranous disease) and six healthy controls, integrated with 155 LN and 30 healthy-control samples from the Accelerating Medicines Partnership in SLE spanning proliferative, membranous, and mixed LN. Findings were correlated with 52-week renal response and supported by urinary proteomics. Results: Despite histologically minimal changes, Class II LN exhibited marked immune cell expansion comparable to proliferative and membranous LN, including CCL3+ CCL4+ intermediate monocytes producing TNF, FOLR2+ SIGLEC1+ macrophages producing TGF{beta} and PDGF, and CD69+ CD8+ effector memory T cells producing IFN{gamma}. Fibroblasts and myofibroblasts were significantly expanded and displayed divergent transcriptional programs: pro-fibrotic and inflammatory myofibroblast modules were associated with worse 52-week outcomes, while interferon-responsive and matrix-remodeling fibroblast programs were associated with improvement. Pathogenic and protective fibroblast populations received overlapping immune-derived signals, suggesting that fibroblast transcriptional state, rather than the identity of incoming signals, shapes the stromal response. Baseline chronicity index captured this stromal heterogeneity and was the clinical parameter most associated with outcome. Urinary proteomics aligned Class II with proliferative rather than membranous disease. Conclusions: Class II LN harbors substantial molecular activity not captured by routine histology. Fibroblast transcriptional programs and baseline chronicity index are candidate correlates of kidney outcome that warrant validation in larger, prospectively followed cohorts.

genomics↗

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↗

bioRxiv2025

A population-scale atlas of blood and tissue in lupus nephritis

One Sentence SummaryA single-cell atlas of paired blood and tissue samples from Lupus Nephritis patients and healthy controls identified stromal and immune populations within renal tissue, including the scar-associated macrophage populations, which correlate with and may drive renal disease activity. 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.

molecular biology↗

bioRxiv2022

A statistical genetics guide to identifying HLA alleles driving complex disease

The human leukocyte antigen (HLA) locus is associated with more human complex diseases than any other locus. In many diseases it explains more heritability than all other known loci combined. Investigators have now demonstrated the accuracy of in silico HLA imputation methods. These approaches enable rapid and accurate estimation of HLA alleles in the millions of individuals that are already genotyped on microarrays. HLA imputation has been used to define causal variation in autoimmune diseases, such as type I diabetes, and infectious diseases, such as HIV infection control. However, there are few guidelines on performing HLA imputation, association testing, and fine-mapping. Here, we present comprehensive statistical genetics guide to impute HLA alleles from genotype data. We provide detailed protocols, including standard quality control measures for input genotyping data and describe options to impute HLA alleles and amino acids including a web-based Michigan Imputation Server. We updated the HLA imputation reference panel representing global populations (African, East Asian, European and Latino) available at the Michigan Imputation Server (n = 20,349) and achived high imputation accuracy (mean dosage correlation r = 0.981). We finally offer best practice recommendations to conduct association tests in order to define the alleles, amino acids, and haplotypes affecting human traits. This protocol will be broadly applicable to the large-scale genotyping data and contribute to defining the role of HLA in human diseases across global populations.

genetics↗