Browsing by Author "Kiryluk, Krzysztof"

Now showing 1 - 5 of 5
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    An atlas of healthy and injured cell states and niches in the human kidney
    (Springer Nature, 2023) Lake, Blue B.; Menon, Rajasree; Winfree, Seth; Hu, Qiwen; Ferreira, Ricardo Melo; Kalhor, Kian; Barwinska, Daria; Otto, Edgar A.; Ferkowicz, Michael; Diep, Dinh; Plongthongkum, Nongluk; Knoten, Amanda; Urata, Sarah; Mariani, Laura H.; Naik, Abhijit S.; Eddy, Sean; Zhang, Bo; Wu, Yan; Salamon, Diane; Williams, James C.; Wang, Xin; Balderrama, Karol S.; Hoover, Paul J.; Murray, Evan; Marshall, Jamie L.; Noel, Teia; Vijayan, Anitha; Hartman, Austin; Chen, Fei; Waikar, Sushrut S.; Rosas, Sylvia E.; Wilson, Francis P.; Palevsky, Paul M.; Kiryluk, Krzysztof; Sedor, John R.; Toto, Robert D.; Parikh, Chirag R.; Kim, Eric H.; Satija, Rahul; Greka, Anna; Macosko, Evan Z.; Kharchenko, Peter V.; Gaut, Joseph P.; Hodgin, Jeffrey B.; KPMP Consortium; Eadon, Michael T.; Dagher, Pierre C.; El-Achkar, Tarek M.; Zhang, Kun; Kretzler, Matthias; Jain, Sanjay; Medicine, School of Medicine
    Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.
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    Clinical Characteristics and Treatment Patterns of Children and Adults With IgA Nephropathy or IgA Vasculitis: Findings From the CureGN Study
    (Elsevier, 2018-08-03) Selewski, David T.; Ambruzs, Josephine M.; Appel, Gerald B.; Bomback, Andrew S.; Matar, Raed Bou; Cai, Yi; Cattran, Daniel C.; Chishti, Aftab S.; D’Agati, Vivette D.; D’Alessandri-Silva, Cynthia J.; Gbadegesin, Rasheed A.; Hogan, Jonathan J.; Iragorri, Sandra; Jennette, J. Charles; Julian, Bruce A.; Khalid, Myda; Lafayette, Richard A.; Liapis, Helen; Lugani, Francesca; Mansfield, Sarah A.; Mason, Sherene; Nachman, Patrick H.; Nast, Cynthia C.; Nester, Carla M.; Noone, Damien G.; Novak, Jan; O’Shaughnessy, Michelle M.; Reich, Heather N.; Rheault, Michelle N.; Rizk, Dana V.; Saha, Manish K.; Sanghani, Neil S.; Sperati, C. John; Sreedharan, Rajasree; Srivastava, Tarak; Swiatecka-Urban, Agnieszka; Twombley, Katherine; Vasylyeva, Tetyana L.; Weaver, Donald J.; Yin, Hong; Zee, Jarcy; Falk, Ronald J.; Gharavi, Ali G.; Gillespie, Brenda W.; Gipson, Debbie S.; Greenbaum, Larry A.; Holzman, Lawrence B.; Kretzler, Matthias; Robinson, Bruce M.; Smoyer, William E.; Flessner, Michael; Guay-Woodford, Lisa M.; Kiryluk, Krzysztof; CureGN Consortium; Pediatrics, School of Medicine
    Introduction: The Cure Glomerulonephropathy Network (CureGN) is a 66-center longitudinal observational study of patients with biopsy-confirmed minimal change disease, focal segmental glomerulosclerosis, membranous nephropathy, or IgA nephropathy (IgAN), including IgA vasculitis (IgAV). This study describes the clinical characteristics and treatment patterns in the IgA cohort, including comparisons between IgAN versus IgAV and adult versus pediatric patients. Methods: Patients with a diagnostic kidney biopsy within 5 years of screening were eligible to join CureGN. This is a descriptive analysis of clinical and treatment data collected at the time of enrollment. Results: A total of 667 patients (506 IgAN, 161 IgAV) constitute the IgAN/IgAV cohort (382 adults, 285 children). At biopsy, those with IgAV were younger (13.0 years vs. 29.6 years, P < 0.001), more frequently white (89.7% vs. 78.9%, P = 0.003), had a higher estimated glomerular filtration rate (103.5 vs. 70.6 ml/min per 1.73 m2, P < 0.001), and lower serum albumin (3.4 vs. 3.8 g/dl, P < 0.001) than those with IgAN. Adult and pediatric individuals with IgAV were more likely than those with IgAN to have been treated with immunosuppressive therapy at or prior to enrollment (79.5% vs. 54.0%, P < 0.001). Conclusion: This report highlights clinical differences between IgAV and IgAN and between children and adults with these diagnoses. We identified differences in treatment with immunosuppressive therapies by disease type. This description of baseline characteristics will serve as a foundation for future CureGN studies.
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    Dimension-agnostic and granularity-based spatially variable gene identification using BSP
    (Springer Nature, 2023-11-14) Wang, Juexin; Li, Jinpu; Kramer, Skyler T.; Su, Li; Chang, Yuzhou; Xu, Chunhui; Eadon, Michael T.; Kiryluk, Krzysztof; Ma, Qin; Xu, Dong; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
    Identifying spatially variable genes (SVGs) is critical in linking molecular cell functions with tissue phenotypes. Spatially resolved transcriptomics captures cellular-level gene expression with corresponding spatial coordinates in two or three dimensions and can be used to infer SVGs effectively. However, current computational methods may not achieve reliable results and often cannot handle three-dimensional spatial transcriptomic data. Here we introduce BSP (big-small patch), a non-parametric model by comparing gene expression pattens at two spatial granularities to identify SVGs from two or three-dimensional spatial transcriptomics data in a fast and robust manner. This method has been extensively tested in simulations, demonstrating superior accuracy, robustness, and high efficiency. BSP is further validated by substantiated biological discoveries in cancer, neural science, rheumatoid arthritis, and kidney studies with various types of spatial transcriptomics technologies.
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    Rationale and design of the Kidney Precision Medicine Project
    (Elsevier, 2021) de Boer, Ian H.; Alpers, Charles E.; Azeloglu, Evren U.; Balis, Ulysses G. J.; Barasch, Jonathan M.; Barisoni, Laura; Blank, Kristina N.; Bomback, Andrew S.; Brown, Keith; Dagher, Pierre C.; Dighe, Ashveena L.; Eadon, Michael T.; El-Achkar, Tarek M.; Gaut, Joseph P.; Hacohen, Nir; He, Yongqun; Hodgin, Jeffrey B.; Jain, Sanjay; Kellum, John A.; Kiryluk, Krzysztof; Knight, Richard; Laszik, Zoltan G.; Lienczewski, Chrysta; Mariani, Laura H.; McClelland, Robyn L.; Menez, Steven; Moledina, Dennis G.; Mooney, Sean D.; O'Toole, John F.; Palevsky, Paul M.; Parikh, Chirag R.; Poggio, Emilio D.; Rosas, Sylvia E.; Rosengart, Matthew R.; Sarwal, Minnie M.; Schaub, Jennifer A.; Sedor, John R.; Sharma, Kumar; Steck, Becky; Toto, Robert D.; Troyanskaya, Olga G.; Tuttle, Katherine R.; Vazquez, Miguel A.; Waikar, Sushrut S.; Williams, Kayleen; Wilson, Francis Perry; Zhang, Kun; Iyengar, Ravi; Kretzler, Matthias; Himmelfarb, Jonathan; Kidney Precision Medicine Project; Medicine, School of Medicine
    Chronic kidney disease (CKD) and acute kidney injury (AKI) are common, heterogeneous, and morbid diseases. Mechanistic characterization of CKD and AKI in patients may facilitate a precision-medicine approach to prevention, diagnosis, and treatment. The Kidney Precision Medicine Project aims to ethically and safely obtain kidney biopsies from participants with CKD or AKI, create a reference kidney atlas, and characterize disease subgroups to stratify patients based on molecular features of disease, clinical characteristics, and associated outcomes. An additional aim is to identify critical cells, pathways, and targets for novel therapies and preventive strategies. This project is a multicenter prospective cohort study of adults with CKD or AKI who undergo a protocol kidney biopsy for research purposes. This investigation focuses on kidney diseases that are most prevalent and therefore substantially burden the public health, including CKD attributed to diabetes or hypertension and AKI attributed to ischemic and toxic injuries. Reference kidney tissues (for example, living-donor kidney biopsies) will also be evaluated. Traditional and digital pathology will be combined with transcriptomic, proteomic, and metabolomic analysis of the kidney tissue as well as deep clinical phenotyping for supervised and unsupervised subgroup analysis and systems biology analysis. Participants will be followed prospectively for 10 years to ascertain clinical outcomes. Cell types, locations, and functions will be characterized in health and disease in an open, searchable, online kidney tissue atlas. All data from the Kidney Precision Medicine Project will be made readily available for broad use by scientists, clinicians, and patients.
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    The chromatin landscape of healthy and injured cell types in the human kidney
    (Springer Nature, 2024-01-10) Gisch, Debora L.; Brennan, Michelle; Lake, Blue B.; Basta, Jeannine; Keller, Mark S.; Ferreira, Ricardo Melo; Akilesh, Shreeram; Ghag, Reetika; Lu, Charles; Cheng, Ying-Hua; Collins, Kimberly S.; Parikh, Samir V.; Rovin, Brad H.; Robbins, Lynn; Stout, Lisa; Conklin, Kimberly Y.; Diep, Dinh; Zhang, Bo; Knoten, Amanda; Barwinska, Daria; Asghari, Mahla; Sabo, Angela R.; Ferkowicz, Michael J.; Sutton, Timothy A.; Kelly, Katherine J.; De Boer, Ian H.; Rosas, Sylvia E.; Kiryluk, Krzysztof; Hodgin, Jeffrey B.; Alakwaa, Fadhl; Winfree, Seth; Jefferson, Nichole; Türkmen, Aydın; Gaut, Joseph P.; Gehlenborg, Nils; Phillips, Carrie L.; El-Achkar, Tarek M.; Dagher, Pierre C.; Hato, Takashi; Zhang, Kun; Himmelfarb, Jonathan; Kretzler, Matthias; Mollah, Shamim; Kidney Precision Medicine Project (KPMP); Jain, Sanjay; Rauchman, Michael; Eadon, Michael T.; Medicine, School of Medicine
    There is a need to define regions of gene activation or repression that control human kidney cells in states of health, injury, and repair to understand the molecular pathogenesis of kidney disease and design therapeutic strategies. Comprehensive integration of gene expression with epigenetic features that define regulatory elements remains a significant challenge. We measure dual single nucleus RNA expression and chromatin accessibility, DNA methylation, and H3K27ac, H3K4me1, H3K4me3, and H3K27me3 histone modifications to decipher the chromatin landscape and gene regulation of the kidney in reference and adaptive injury states. We establish a spatially-anchored epigenomic atlas to define the kidney's active, silent, and regulatory accessible chromatin regions across the genome. Using this atlas, we note distinct control of adaptive injury in different epithelial cell types. A proximal tubule cell transcription factor network of ELF3, KLF6, and KLF10 regulates the transition between health and injury, while in thick ascending limb cells this transition is regulated by NR2F1. Further, combined perturbation of ELF3, KLF6, and KLF10 distinguishes two adaptive proximal tubular cell subtypes, one of which manifested a repair trajectory after knockout. This atlas will serve as a foundation to facilitate targeted cell-specific therapeutics by reprogramming gene regulatory networks.