Biology subjects

Lee, C.-Y.

Publications and source records attributed to Lee, C.-Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Evaluations of retrospective frequency and phase correction methods for single-voxel MR spectroscopy at 7T

Subject motion and gradient heating-induced frequency and phase offsets result in spectral misalignment during single-voxel MR spectroscopy (SVS) acquisitions. Several methods have been presented to align the spectra, but their performance on a 7T system is unclear. This study aimed to evaluate the practical importance of four retrospective correction methods, namely creatine fitting, residual water, spectral registration, and cross-correlation. SVS data were collected from 127 participants (88/39 female/male, 39{+/-}15 years) using a semi-localization by adiabatic selective refocusing sequence at 7T. Changes in the spectral linewidth, signal-to-noise ratio (SNR), similarity (mean similarity matrix (SImean)), and metabolite quantification (concentration, relative Cramer-Rao lower bounds (rCRLB)) after correction were evaluated. A Wilcoxon signed rank test was used to evaluate these changes. The p-values were adjusted using the false discovery rate (q<0.05) for multiple comparisons. For significant changes, the effect size was further calculated using the Rosenthal formula. The results demonstrated that all correction methods resulted in a significant decrease in the spectral linewidth and significant increases in the spectral SNR and SImean. The mean changes by using the four methods were 0.76-0.99 Hz for the spectral linewidth change (effect sizes:0.73-0.86), 5.79-6.95 for the SNR change (effect size:0.60-0.72), and 0.03-0.03 for the SImean change (effect size:0.87-0.87). The correction also significantly increased the estimates of the metabolite concentrations of PCr, Gln, Glu, GPC, Ins, NAA, Scyllo, and Tau (effect size:0.25-0.57), and significantly decreased the rCRLBs (effect size:0.26-0.42) of Scyllo, Tau, and Gly. These results indicate that each method provides practical benefits in improving the spectral linewidth, SNR, and similarity by showing a strong to very strong effect of the improvements (effect size>0.60). The correction only showed a weak to moderate effect of the changes in the metabolite quantification (effect size<0.60), suggesting that whether the correction results in more reliable metabolite quantification requires further validation.

bioengineering↗

bioRxiv2026

Serial Immunohistochemistry for High-Dimensional Single-Cell Spatial Analysis of Human Kidney Biopsies

BackgroundTraditional immunohistochemistry (IHC) with chromogen detection has limited multiplex capacity, detecting at most 4 protein markers per tissue section simultaneously, thereby restricting comprehensive spatial analysis of valuable human biopsies. We developed and validated a robust serial IHC (sIHC) staining method to detect multiple antigens on a single kidney biopsy slide, maximizing data yield for diagnosing and studying complex kidney diseases. MethodsFormalin-fixed, paraffin-embedded kidney biopsy sections were subjected to repeated IHC/imaging cycles with antibody removal using an optimized sodium dodecyl sulfate-glycerol buffer stripping protocol. Images were then co-registered, and analysis was performed using a variety of methodologies, including color deconvolution, cell segmentation, and spatial clustering. ResultsThis optimized sIHC method successfully detected up to 20 antigens on a single slide. Combining image analysis and artificial intelligence software, for example with HALO (Indica Labs), the assay assembles high-dimensional images and enables quantitative histology and single-cell spatial analysis. Using this advanced method, we were able to identify rare cell populations, such as double-negative T cells, that are challenging to detect conventionally. ConclusionWe have developed a validated, high-capacity sIHC protocol that uses standard IHC procedures with commercially available, clinically validated off-the-shelf antibodies. This method is a valuable, cost-effective tool for obtaining extensive, high-dimensional single-cell-resolved spatial data from limited pathology samples, such as a human kidney biopsy.

pathology↗

bioRxiv2026

Prospective pan-cancer phosphoproteomics at clinical scale extends therapeutic options in precision oncology

Genomics-guided precision oncology has improved survival in cancer entities with actionable mutations but cannot capture oncogenic signaling that manifests at the protein level. Here, we report a prospective, real-world pan-cancer study profiling proteomes and phosphoproteomes of 1,998 tumor samples from adults and children with rare or advanced cancers enrolled in the German precision oncology programs DKFZ/NCT/DKTK MASTER, CATCH and INFORM and their molecular tumor boards (MTBs). We developed tumor proteome activity status (TOPAS) scores for 46 clinically relevant kinases, an immune activity score capturing antigen presentation and T-cell activation and identified therapeutically targetable cell-surface proteins for 94% of patients. These readouts enhance MTB recommendations by exposing actionable non-genomic kinase activity, refining interpretation of oncogenic genome alterations, and highlighting cell-surface treatment options. Three proof-of-concept analyses indicate clinical utility including kinase activity-stratified pazopanib response in sarcoma, immune activity score-tracked checkpoint-inhibitor outcomes pan-cancer, and a phosphoproteomic biomarker distinguishing EGFR-inhibitor response in chordoma.

cancer biology↗

bioRxiv2026

Reverse genetics in humanized mice reveals CARD8-mediated pyroptosis causing pancytopenia in human DPP9 deficiency

Loss of function mutation in the human DPP9 gene causes Hatipoglu syndrome leading to severe inflammasomopathy. A key feature of the disease is pancytopenia and patients require bone marrow transplantation, but the mechanism of cell loss is unclear since Dpp9 mutant mice have normal hematopoiesis, suggesting that a distinct mechanism of disease occurs in humans. Here, we present a model of human DPP9 deficiency leveraging reverse genetics in the MISTRG6 humanized mice. We found that CRISPR editing of human CD34+ hematopoietic stem and progenitor cells (HSPCs) led to very efficient and persistent gene deletion in vivo. Human DPP9 deletion recapitulated cytopenia in peripheral blood and in the bone marrow, and cell loss was cell intrinsic. However, DPP9 deletion led to little transcriptional changes suggesting post-transcriptional regulation in human HSPCs. Mechanistically, DPP9 deficiency led to the activation of the CARD8 inflammasome resulting in HSPC pyroptosis, whereas NLRP1 was dispensable for cell death. Thus, our results reveal a unique human mechanism of disease and offer therapeutic insight for this inflammasomopathy.

immunology↗

bioRxiv2025

Decoding isozyme-specific substrate recognition in protein arginine deiminases by proteome-wide citrullination mapping

Protein arginine deiminases (PADs) convert arginine to citrulline, altering protein structure and function. Of the five human isozymes, PAD1-4 are catalytically active with distinct tissue-specificities, yet isozyme-specific substrate recognition remains poorly defined. We profiled PAD1-4 substrate landscapes via mass spectrometry, identifying [~]30,000 citrullination sites across [~]5,500 proteins. Only 14% of sites were shared among all four, reflecting distinct sequence preferences: PAD1-2 showed broad specificity, whereas PAD3-4 favored arginines flanked by acidic or glycine residues. These preferences persisted over 10 min-16 h, indicating sequence context rather than temporal dynamics drives specificity. Mutation analysis of eleven PAD4 variants revealed Q346, G403, R639, and H640 as key determinants distinguishing substrate recognition from that of PAD2. This work provides the most comprehensive PADs substrate atlas to date, defining isozyme-specific motifs and molecular determinants, and guiding development of selective inhibitors and probes to interrogate citrullination mechanisms in health and disease.

biochemistry↗

bioRxiv2025

Chemical proteomics decrypts the kinases that shape the dynamic human phosphoproteome

Mass-spectrometry-based phosphoproteomics enables the analysis of thousands of protein phosphorylation events across the human proteome. However, there is a lack of scalable, hypothesis-free, and statistically sound approaches for discovering, evaluating, and falsifying kinase::substrate relationships (KSRs). Here, we developed a new concept termed potency-coherence analysis. By measuring and integrating 17 million peptidoform-specific dose-response curves for 133 kinase inhibitors with known targets and affinities, we could critically re-evaluate published KSRs and discover thousands of potency-coherent and motif-plausible new KSRs for 96 human kinases. Application of these high-confidence KSRs enabled the estimation of kinase and signaling pathway activities in cancer patient biopsies. This unified and extendable framework has been implemented in ProteomicsDB to aid researchers in understanding the human phosphoproteome in health and disease.

systems biology↗

bioRxiv2025

Assessment of Visual Function in Mice Using Light/Dark Box and Multi-Feature Machine Learning

The light/dark box test can be used to assess visual function in rodents based on their spontaneous behavior in response to light. Commonly used assay relies on a single behavioral metric, dwell time in the light or dark compartment, which may be influenced by factors other than vision, leading to unreliable assessment results. To overcome this, we developed a multi-feature machine learning paradigm by extracting multiple mouse behavioral metrics, standardizing them as features to train machine learning models, thereby achieving reliable and automated vision assessment. We systematically compared the classification performance of single-metric versus multi-feature machine learning approaches in sighted and blind mice, using wild-type and rhodopsin-deficient mice, with a subset further subjected to double optic nerve crush. We found that the multi-feature method can improve classification performance and exhibit great robustness to different experimental settings. Additionally, we further improved model performance by applying feature importance analysis and constructing an optimized feature subset. These findings suggest that the reliability of commonly used single dwell time measure for vision assessment could become unreliable, as shown in our experiment, probably because in addition to vision other factors also impact dwell time. Our study demonstrated an improved assessment method based on a combination of multiple behavior features through machine learning. Author SummaryAssessing visual function in mice is essential for studying eye diseases and drug development. The light/dark box test evaluates visual function by measuring the spontaneous behavioral response of mice to light, providing a training-free behavioral approach that helps simplify the assessment process and improve research efficiency. However, traditional light/dark box tests rely on a single behavioral metric, dwell time in the light or dark compartment, to assess visual function, which may be influenced by factors other than vision, such as anxiety and exploratory behavior, leading to limited reliability of assessment results. Here, we demonstrate that integrating multiple behavioral features through machine learning can improve the reliability and stability of vision assessment. By automatically tracking and analyzing various behavioral metrics of mice, such as movement patterns, speed, and spatial preferences, the proposed method can more reliably distinguish between sighted and blind mice. Furthermore, the method demonstrates stable performance across different experimental settings, showing good applicability. This automated, reliable, and easily generalizable method can provide a convenient and efficient means for visual assessment in preclinical research, facilitating vision disease research and drug development.

animal behavior and cognition↗

bioRxiv2025

gAIRR-wgs: An Algorithm to Genotype T Cell Receptor Alleles Using Whole Genome Sequencing Data

T cell receptor (TR) genes, including variable (TR_V), diversity (TR_D), and joining (TR_J) segments, exhibit allelic diversity that is critical to adaptive immunity. Growing evidence has identified associations between TR genes and immune-related diseases. Germline variants may influence TR gene function and subsequent usage, highlighting the importance of accurate TR allele profiling. However, accurately identifying germline TR from standard WGS data remains challenging due to short read lengths, limited depth, and high sequence similarity. To address these challenges, we developed gAIRR-wgs, for WGS-based TR allele typing. By incorporating novel alleles from HPRC individuals, gAIRR-wgs exhibited excellent performance in allele calling, with F1 scores of 100.0% for TR_D, 99.8% for TR_J, and 98.3% for TR_V. Applying this pipeline to 1,492 individuals from the Taiwan Biobank (TWB), we identified 449 novel TR alleles, 277 of which overlapped with HPRC release 1 data of mixed ethnicity and are absent in the IMGT database. Further population comparison analysis revealed significant TR allele distribution differences across global populations, showing population-specific patterns and diversity variations between ethnic groups. We also discovered TWB-specific deletion polymorphisms affecting contiguous TRGV and TRBV genes, which are not recorded in the gnomAD database and undetected by standard structural variant callers, highlighting the need for tailored approaches to resolve complex immune gene regions. In conclusion, gAIRR-wgs enables accurate TR allele calling from standard WGS data using feasible computational resources and reveals substantial immunogenetic diversity in population cohorts.

bioinformatics↗

bioRxiv2025

Differential usage of two, distinct DNA-binding domains regulates tissue-specific occupancy of the pioneer factor Zelda

Pioneer transcription factors act at the top of gene-regulatory networks by promoting accessible chromatin at the cis-regulatory regions that drive gene expression. Despite their ability to bind closed chromatin, pioneer factors occupy distinct binding sites in different tissues. The pioneer factor Zelda promotes the undifferentiated fate in both the early Drosophila embryo and in the neural stem cells (neuroblasts) of the larval brain. Tissue-specific binding by Zelda identifies cell-type specific enhancers, which are enriched for different DNA-sequence motifs. We investigated the features that promoted cell-type specific occupancy by testing the role of conserved, structured protein domains in the capacity of Zelda to promote the embryonic and neuroblast cell fates. We unexpectedly identified that the most deeply conserved region in Zelda, the second zinc finger, has opposing functions in the embryo and neuroblasts. We showed that this zinc finger is a previously unrecognized DNA-binding domain that is specifically required for Zelda binding to a G-rich motif in larval neuroblasts. The pioneering function of Zelda depends largely on the C-terminal cluster of zinc fingers that promotes binding in the early embryo, suggesting that pioneer function may depend on how Zelda engages the genome. As opposed to co-factor expression or chromatin environment, our data identify tissue-specific usage of two, widely separated DNA-binding domains as the mechanism controlling tissue-specific binding and activity.

developmental biology↗

bioRxiv2025

A double-assurance mechanism restrains generation of high potential transit-amplifying progenitors during neurogenesis

Stem cells can generate differentiated progeny directly or indirectly through transit-amplifying progenitors (TAPs), which are vulnerable to tumorigenic transformation. Despite clinical relevance, how stem cells regulate TAP production is unclear. Drosophila brains contain Asense+ stem cells (Type1 neuroblasts; T1NBs) that generate low neurogenic potential TAPs and Asense- stem cells (Type2 neuroblasts; T2NBs) that produce high-potential TAPs [Intermediate Neural Progenitors (INPs)]. Unexpectedly, cell-type-specific enhancers of genes essential for INP formation are poised in T1NBs despite never generating INP progeny. Thus, both NB types are competent to generate INPs. Inducing T1NBs to generate INPs is more efficient upon asense knockdown. The progeny of T2NBs expressing elevated Asense adopt a low-potential TAP identity instead of INPs. Elevated Asense expression limits tumor NB expansion driven by stalled INPs halting tumor expansion. We propose that a double-assurance mechanism characterized by dynamic superimposition of lineage-specific activators upon basal-state determinants defines NB capability to generate high-potential TAPs.

developmental biology↗

bioRxiv2025

High-resolution single-cell RNA sequencing using canFam4 reveals novel immune subsets and checkpoint programs in healthy dogs

Single-cell RNA sequencing (scRNA-seq) enables high-resolution profiling of immune heterogeneity. Although previous studies have mapped the single-cell transcriptomic atlases of peripheral leukocytes in healthy dogs, the identification and functional characterization of distinct immune subsets remain incomplete. We constructed a single-cell atlas of peripheral leukocytes from six healthy small-breed dogs using the 10x Genomics platform and the updated canFam4 genome. Analysis of 30,040 high-quality transcriptomes revealed 51 distinct immune subsets, including CD14{square}CD33{square} monocytes, XCR1{square}CD1D{square} dendritic cells, CEACAM1{square}CD24{square} neutrophils, and IL32{square}BATF{square} regulatory T cells, which were underrepresented in canFam3.1-based studies. Interferon-enriched CD14{square} monocytes and CD4{square} T subsets associated with myxomatous mitral valve disease were also identified. Functional analysis revealed that PDCD1 attenuates TCR signaling, LAG3 modulates malate metabolism in CD4{square} T cells, and suppresses TBX21 in CD8{square} T cells associated with viral response. CD274 encoding PD-L1 was linked to IL-10 production in neutrophils, and CTLA4 represented an initial activation of double-negative T subsets. T cell exhaustion scores and proliferative fractions varied across cohorts, reflecting differences in environmental antigenic exposures. Our study represents the first comprehensive, gene-resolved single-cell analysis that reveals immunoregulatory checkpoint mechanisms underlying immune homeostasis in healthy dogs. Our dataset will serve as a valuable resource for future comparative and translational immunology research in dogs.

immunology↗

bioRxiv2025

An ancient evolutionary origin for IL-1 cytokines as mediators of immunity

Inflammation is a hallmark of immune responses. Its mechanistic underpinnings in mammals are well-defined: pro-inflammatory cytokines of the interleukin 1 (IL-1) superfamily establish and support microenvironments that promote immune cell activities. Despite a growing number of reports on inflammatory processes and components of the IL-1 signaling axis in several invertebrate lineages, orthologs of these central cytokines have not been detected outside of the jawed vertebrates. Here, protein structure prediction algorithms were applied to identify genes encoding a family of IL-1 proteins with homologs throughout Eumetazoa (termed "IL-1anc" to reflect their ancestral evolutionary origin). Using Petromyzon marinus (sea lamprey) and Strongylocentrotus purpuratus (purple sea urchin) as model systems, we demonstrate that IL-1anc proteins share important features with mammalian IL-1/IL-1{beta} including expression patterns, protein localization, and processing. Together, our data indicate that the IL-1 superfamily and associated circuitry represent a foundational module of animal immunity that far predates the jawed vertebrates.

immunology↗

bioRxiv2025

Single-nucleus epigenomic dysregulation unmasks genetic risk-associated neurodegenerative glia states

The accumulation of abnormal tau protein selectively affects distinct brain regions and specific populations of neurons and glial cells in tau-related dementias, such as Alzheimers disease (AD), Picks disease (PiD), and progressive supranuclear palsy (PSP). Although the three disorders share the feature of tau protein pathology, the regulatory circuitry of non-coding genetic variants underlying risk-associated cell states remains to be elucidated. Using paired single-nucleus profiling of chromatin accessibility and gene expression across AD, PiD, and PSP, we define cell-type-specific cis-regulatory elements (CREs) across six cell types and fifty subclasses. Comparing disease-dynamic CREs across three disorders, we find that glia overrepresent disorder-specific gene regulation related to dynamic cellular response to stress. We show that human genetic variants affecting microglial gene regulation converge into distinct and co-regulated modules affecting specific cellular functions. Moreover, polygenic risk modifiers are maximally co-accessible in disorder-specific glial states, modifying distinct pathways such as sphingomyelin regulation in PiD. Our study informs glial regulators linked to polygenic modifiers of primary tauopathy, introducing modifiable pathways governing resilience for therapeutic consideration.

genomics↗

bioRxiv2025

High-throughput chemical proteomics workflow for profiling protein citrullination dynamics

Citrullination is a post-translational modification implicated in autoimmune and inflammatory diseases, yet its low abundance and lack of effective enrichment tools have limited proteome-wide analysis. Here, we developed a robust chemical proteomics workflow with improved specificity and throughput. This method builds upon glyoxal-based derivatization and incorporates a cleavable biotin linker for efficient peptide enrichment, release, and identification via mass spectrometry. Benchmarking across biological systems demonstrated a >10-fold increase in the detection of citrullinated peptides (> 150-fold increase in intensity) at sub-0.1% abundance. Applying the workflow to mouse brain tissue and human primary neutrophils revealed dynamics and condition-specific changes in the citrullinome, including previously uncharacterized sites and regulatory processes. Notably, extensive citrullination of linker histone H1 and structural proteins such as lamin B1 in ionomycin-activated neutrophils suggests broad remodeling of cell architecture via citrullination. This workflow enables proteome-wide mapping of citrullination sites and facilitates its study across diverse biological contexts.

biochemistry↗

bioRxiv2025

Development of Motif-Specific Monoclonal Antibodies for Global Protein Citrullination Detection with Minimal Cross-Reactivity to Homocitrullination

Protein citrullination, a post-translational modification (PTM) catalyzed by peptidylarginine deiminases (PADs), plays critical roles in biological processes such as immunity, gene regulation, and inflammation. Dysregulated citrullination is implicated in diseases including rheumatoid arthritis, multiple sclerosis, and cancer, making it a potential biomarker and therapeutic target. Immunodetection is the most commonly used technique to study citrullination. However, most commercially available antibodies against citrullination are either protein-specific or lack the sensitivity and specificity of the broad variety of modified proteins. In addition, existing anti-pan citrullination antibodies often fail to distinguish citrullination from homocitrullination, a chemically similar modification on lysine. This cross-reactivity limits their utility in deciphering the distinct biological roles of these PTMs. To address these challenges, we employed a motif-based strategy to generate monoclonal antibodies against citrullination. This approach leverages PAD enzyme sequence preferences from human proteome, enhancing specificity for citrullination while minimizing cross-reactivity with homocitrullination. We immunized rats with a pool of over 490,000 citrullinated peptides, designed to represent common citrullination motifs in human tissue proteomes. Two monoclonal antibody clones were established and validated for sensitivity and specificity using ELISA and western blot against in vitro citrullinated and homocitrullinated proteomes, as well as ionomycin-activated human neutrophils. Both clones demonstrated great sensitivity to diverse citrullinated proteins, robust discrimination against homocitrullination, and quantitative readout in biological samples. These novel antibodies provide powerful tools for studying global citrullination dynamics and hold promise for biomarker discovery and diagnostic applications in diseases involving PAD dysregulation.

molecular biology↗

bioRxiv2025

Effective Multiple Scattering Correction for Accurate Quantitative OCT

We present an effective approach to compensate for multiple scattering effects in Quantitative Optical Coherence Tomography (qOCT) imaging, with the goal of accurately extracting tissue attenuation coefficients, which is crucial for precise clinical diagnosis. In clinical practice, especially for intra-operative imaging, an increased working distance is often necessary to avoid interference with surgical instruments and workflow. However, this increased working distance corresponds to an increased beam spot size, leading to more multiply scattered photons in the OCT signal and thereby underestimating the optical attenuation. To address this challenge, we investigated errors in attenuation coefficient quantification under different beam spot sizes. Monte Carlo simulations were employed to generate virtual OCT signals for two distinct beam spot sizes, enabling us to quantify the errors induced by multiple scattering across a range of true optical attenuation coefficients. Based on this analysis, we developed a compensation function to correct these errors. The proposed method was validated through experimental measurements using tissue-mimicking phantoms and demonstrated a significant improvement in the accuracy of attenuation coefficient quantification. Our results underscore the potential of this easy-to-implement technique to enhance the diagnostic reliability of qOCT, facilitating its broader application in clinical settings for accurate tissue characterization.

bioengineering↗

bioRxiv2024

Single-nucleus RNA sequencing of human periventricular white matter in vascular dementia

Vascular dementia (VaD) refers to a variety of dementias driven by cerebrovascular disease and is the second leading cause of dementia globally. VaD may be caused by ischemic strokes, intracerebral hemorrhage, and/or cerebral small vessel disease, commonly identified as white matter hyperintensities on MRI. The mechanisms underlying these white matter lesions in the periventricular brain are poorly understood. In this study we perform an extensive transcriptomic analysis on human postmortem periventricular white matter lesions in patients with VaD with the goal of identifying molecular pathways in the disease. We find increased cellular stress responses in astrocytes, oligodendrocytes, and oligodendrocyte precursor cells as well as transcriptional and translational repression in microglia in our dataset. We show that several genes identified by GWAS as being associated with white matter disease are differentially expressed in cells in VaD. Finally, we compare our dataset to an independent snRNAseq dataset of PVWM in VaD and a scRNAseq dataset on human iPSC-derived microglia exposed to oxygen glucose deprivation (OGD). We identify the increase of the heat shock protein response as a conserved feature of VaD across celltypes and show that this increase is not linked to OGD exposure. Overall, our study is the first to show that increased heat shock protein responses are a common feature of lesioned PVWM in VaD and may represent a potential therapeutic target.

neuroscience↗

bioRxiv2024

Inflammation in Areas of Fibrosis Precedes Loss of Kidney Function in Lupus Nephritis

BackgroundInterstitial fibrosis in lupus nephritis (LN) is often infiltrated by immune cells but typically regarded as nonspecific "scar reaction." This study aimed to investigate the relationship between inflammatory fibrosis and kidney disease progression in LN. MethodsInterstitial fibrosis and tubular atrophy (IFTA) were scored in 124 LN kidney biopsies. Inflammation in areas of IFTA (i-IFTA) was graded 0-3 according to the Banff Classification of Allograft Pathology. Significant glomerular filtration rate (GFR) loss was defined as a decline of >15 ml/min at 3 years from biopsy. Immune cell phenotype was defined by serial immunohistochemistry (13-plex). ResultsIFTA was observed in 88/124 (71%) biopsies, and i-IFTA was identified in 76/88 (86%) cases. The distribution of i-IFTA grades was heterogenous across all IFTA grades. In patients with moderate-to-severe IFTA (>25%), the degree of i-IFTA was associated with a higher risk of significant GFR loss: 0/2 (0%), 1/3 (33%), 3/4 (75%), and 7/9 (78%) for i-IFTA grades 0, 1, 2, and 3, respectively (p = 0.028). Multiplexed histology revealed that i-IFTA was mostly composed of CD163+ macrophages and CD4 T cells, followed by CD8 T cells and granulocytes. ConclusionI-IFTA is frequently observed in LN and is dominated by macrophages and T cells. For patients with baseline IFTA >25%, the degree of i-IFTA emerged as a predictor of GFR loss. These data support the routine scoring of i-IFTA in LN due to its prognostic implications and nominate i-IFTA as a potential therapeutic target. LAY SUMMARYScar tissue often contains immune cells, but we still do not fully understand their role. In lupus nephritis (LN), this is typically dismissed as "nonspecific inflammation". However, our study analyzed kidney biopsies from 124 people with LN and found that inflammation in scarred areas may predict future kidney function loss. Specifically, we identified a type of immune cell, CD163+ macrophages, that may contribute to scarring and kidney damage. Our findings suggest that routinely assessing inflammation in scarred areas could help predict kidney health in LN patients and highlight a possible new target for therapies to prevent kidney damage.

immunology↗