Browsing by Author "Kidney Precision Medicine Project"

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    A Participant-Centered Approach to Understanding Risks and Benefits of Participation in Research Informed by the Kidney Precision Medicine Project
    (Elsevier, 2022) Butler, Catherine R.; Appelbaum, Paul S.; Ascani, Heather; Aulisio, Mark; Campbell, Catherine E.; de Boer, Ian H.; Dighe, Ashveena L.; Hall, Daniel E.; Himmelfarb, Jonathan; Knight, Richard; Mehl, Karla; Murugan, Raghavan; Rosas, Sylvia E.; Sedor, John R.; O'Toole, John F.; Tuttle, Katherine R.; Waikar, Sushrut S.; Freeman, Michael; Kidney Precision Medicine Project; Medicine, School of Medicine
    An understanding of the ethical underpinnings of human subjects research that involves some risk to participants without anticipated direct clinical benefit-such as the kidney biopsy procedure as part of the Kidney Precision Medicine Project (KPMP)-requires a critical examination of the risks as well as the diverse set of countervailing potential benefits to participants. This kind of deliberation has been foundational to the development and conduct of the KPMP. Herein, we use illustrative features of this research paradigm to develop a more comprehensive conceptualization of the types of benefits that may be important to research participants, including respecting pluralistic values, supporting the opportunity to act altruistically, and enhancing benefits to a participant's community. This approach may serve as a model to help researchers, ethicists, and regulators to identify opportunities to better respect and support participants in future research that entails some risk to these participants as well as to improve the quality of research for people with kidney disease.
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    Integrated single-cell sequencing and histopathological analyses reveal diverse injury and repair responses in a participant with acute kidney injury: a clinical-molecular-pathologic correlation
    (Elsevier, 2022) Menon, Rajasree; Bomback, Andrew S.; Lake, Blue B.; Stutzke, Christy; Grewenow, Stephanie M.; Menez, Steven; D’Agati, Vivette D.; Jain, Sanjay; Kidney Precision Medicine Project; Medicine, School of Medicine
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    Large-scale, three-dimensional tissue cytometry of the human kidney: a complete and accessible pipeline
    (Elsevier, 2021) Ferkowicz, Michael J.; Winfree, Seth; Sabo, Angela R.; Kamocka, Malgorzata M.; Khochare, Suraj; Barwinska, Daria; Eadon, Michael T.; Cheng, Ying-Hua; Phillips, Carrie L.; Sutton, Timothy A.; Kelly, Katherine J.; Dagher, Pierre C.; El-Achkar, Tarek M.; Dunn, Kenneth W.; Kidney Precision Medicine Project; Anatomy, Cell Biology and Physiology, School of Medicine
    The advent of personalized medicine has driven the development of novel approaches for obtaining detailed cellular and molecular information from clinical tissue samples. Tissue cytometry is a promising new technique that can be used to enumerate and characterize each cell in a tissue and, unlike flow cytometry and other single-cell techniques, does so in the context of the intact tissue, preserving spatial information that is frequently crucial to understanding a cell's physiology, function, and behavior. However, the wide-scale adoption of tissue cytometry as a research tool has been limited by the fact that published examples utilize specialized techniques that are beyond the capabilities of most laboratories. Here we describe a complete and accessible pipeline, including methods of sample preparation, microscopy, image analysis, and data analysis for large-scale three-dimensional tissue cytometry of human kidney tissues. In this workflow, multiphoton microscopy of unlabeled tissue is first conducted to collect autofluorescence and second-harmonic images. The tissue is then labeled with eight fluorescent probes, and imaged using spectral confocal microscopy. The raw 16-channel images are spectrally deconvolved into 8-channel images, and analyzed using the Volumetric Tissue Exploration and Analysis (VTEA) software developed by our group. We applied this workflow to analyze millimeter-scale tissue samples obtained from human nephrectomies and from renal biopsies from individuals diagnosed with diabetic nephropathy, generating a quantitative census of tens of thousands of cells in each. Such analyses can provide useful insights that can be linked to the biology or pathology of kidney disease. The approach utilizes common laboratory techniques, is compatible with most commercially-available confocal microscope systems and all image and data analysis is conducted using the VTEA image analysis software, which is available as a plug-in for ImageJ.
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    Molecular Signatures of Diabetic Kidney Disease Hiding in a Patient with Hypertension-Related Kidney Disease: A Clinical Pathologic Molecular Correlation
    (Wolters Kluwer, 2022) Patel, Jiten; Torrealba, Jose R.; Poggio, Emilio D.; Bebiak, Jack; Alpers, Charles E.; Grewenow, Stephanie M.; Toto, Robert D.; Eadon, Michael T.; Kidney Precision Medicine Project; Medicine, School of Medicine
    The Kidney Precision Medicine Project (KPMP) seeks to establish a molecular atlas of the kidney in health and disease and improve our understanding of the molecular drivers of CKD and AKI. Herein, we describe the case of a 66-year-old woman with CKD who underwent a protocol KPMP kidney biopsy. Her clinical history included well-controlled diabetes mellitus, hypertension, and proteinuria. The patient’s histopathology was consistent with modest hypertension-related kidney injury, without overt diabetic kidney disease. Transcriptomic signatures of the glomerulus, interstitium, and tubular subsegments were obtained from laser microdissected tissue. The molecular signatures that were uncovered revealed evidence of early diabetic kidney disease adaptation and ongoing active tubular injury with enriched pathways related to mesangial cell hypertrophy, glycosaminoglycan biosynthesis, and apoptosis. Molecular evidence of diabetic kidney disease was found across the nephron. Novel molecular assays can supplement and enrich the histopathologic diagnosis obtained from a kidney biopsy.
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    Molecular Signatures of Glomerular Neovascularization in a Patient with Diabetic Kidney Disease
    (Wolters Kluwer, 2024) Ferkowicz, Michael J.; Verma, Ashish; Barwinska, Daria; Ferreira, Ricardo Melo; Henderson, Joel M.; Kirkpatrick, Mary; Silva, Paolo S.; Steenkamp, Devin W.; Phillips, Carrie L.; Waikar, Sushrut S.; Sutton, Timothy A.; Kidney Precision Medicine Project; Medicine, School of Medicine
    The Kidney Precision Medicine Project (KPMP) aims to create a kidney tissue atlas, define disease subgroups, and identify critical cells, pathways, and targets for novel therapies through molecular investigation of human kidney biopsies obtained from participants with AKI or CKD. We present the case of a 66-year-old woman with diabetic kidney disease who underwent a protocol KPMP kidney biopsy. Her clinical history included diabetes mellitus complicated by neuropathy and eye disease, increased insulin resistance, hypertension, albuminuria, and relatively preserved glomerular filtration rate (early CKD stage 3a). The patient's histopathology was consistent with diabetic nephropathy and arterial and arteriolar sclerosis. Three-dimensional, immunofluorescence imaging of the kidney biopsy specimen revealed extensive periglomerular neovascularization that was underestimated by standard histopathologic approaches. Spatial transcriptomics was performed to obtain gene expression signatures at discrete areas of the kidney biopsy. Gene expression in the areas of glomerular neovascularization revealed increased expression of genes involved in angiogenic signaling, proliferation, and survival of endothelial cells, as well as new vessel maturation and stability. This molecular correlation provides additional insights into the development of kidney disease in patients with diabetes and spotlights how novel molecular techniques used by the KPMP can supplement and enrich the histopathologic diagnosis obtained from a kidney biopsy.
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    Multi-Scalar Data Integration Links Glomerular Angiopoietin-Tie Signaling Pathway Activation With Progression of Diabetic Kidney Disease
    (American Diabetes Association, 2022) Liu, Jiahao; Nair, Viji; Zhao, Yi-yang; Chang, Dong-yuan; Limonte, Christine; Bansal, Nisha; Fermin, Damian; Eichinger, Felix; Tanner, Emily C.; Bellovich, Keith A.; Steigerwalt, Susan; Bhat, Zeenat; Hawkins, Jennifer J.; Subramanian, Lalita; Rosas, Sylvia E.; Sedor, John R.; Vasquez, Miguel A.; Waikar, Sushrut S.; Bitzer, Markus; Pennathur, Subramaniam; Brosius, Frank C.; De Boer, Ian; Chen, Min; Kretzler, Matthias; Ju, Wenjun; Kidney Precision Medicine Project; Michigan Translational Core C-PROBE Investigator Group; Medicine, School of Medicine
    Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease (ESKD). Prognostic biomarkers reflective of underlying molecular mechanisms are critically needed for effective management of DKD. A three-marker panel was derived from a proteomics analysis of plasma samples by an unbiased machine learning approach from participants (N = 58) in the Clinical Phenotyping and Resource Biobank study. In combination with standard clinical parameters, this panel improved prediction of the composite outcome of ESKD or a 40% decline in glomerular filtration rate. The panel was validated in an independent group (N = 68), who also had kidney transcriptomic profiles. One marker, plasma angiopoietin 2 (ANGPT2), was significantly associated with outcomes in cohorts from the Cardiovascular Health Study (N = 3,183) and the Chinese Cohort Study of Chronic Kidney Disease (N = 210). Glomerular transcriptional angiopoietin/Tie (ANG-TIE) pathway scores, derived from the expression of 154 ANG-TIE signaling mediators, correlated positively with plasma ANGPT2 levels and kidney outcomes. Higher receptor expression in glomeruli and higher ANG-TIE pathway scores in endothelial cells corroborated potential functional effects in the kidney from elevated plasma ANGPT2 levels. Our work suggests that ANGPT2 is a promising prognostic endothelial biomarker with likely functional impact on glomerular pathogenesis in DKD.
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    Plasma proteomics of acute tubular injury
    (Springer Nature, 2024-08-27) Schmidt, Insa M.; Surapaneni, Aditya L.; Zhao, Runqi; Upadhyay, Dhairya; Yeo, Wan-Jin; Schlosser, Pascal; Huynh, Courtney; Srivastava, Anand; Palsson, Ragnar; Kim, Taesoo; Stillman, Isaac E.; Barwinska, Daria; Barasch, Jonathan; Eadon, Michael T.; El-Achkar, Tarek M.; Henderson, Joel; Moledina, Dennis G.; Rosas, Sylvia E.; Claudel, Sophie E.; Verma, Ashish; Wen, Yumeng; Lindenmayer, Maja; Huber, Tobias B.; Parikh, Samir V.; Shapiro, John P.; Rovin, Brad H.; Stanaway, Ian B.; Sathe, Neha A.; Bhatraju, Pavan K.; Coresh, Josef; Kidney Precision Medicine Project; Rhee, Eugene P.; Grams, Morgan E.; Waikar, Sushrut S.; Medicine, School of Medicine
    The kidney tubules constitute two-thirds of the cells of the kidney and account for the majority of the organ’s metabolic energy expenditure. Acute tubular injury (ATI) is observed across various types of kidney diseases and may significantly contribute to progression to kidney failure. Non-invasive biomarkers of ATI may allow for early detection and drug development. Using the SomaScan proteomics platform on 434 patients with biopsy-confirmed kidney disease, we here identify plasma biomarkers associated with ATI severity. We employ regional transcriptomics and proteomics, single-cell RNA sequencing, and pathway analysis to explore biomarker protein and gene expression and enriched biological pathways. Additionally, we examine ATI biomarker associations with acute kidney injury (AKI) in the Kidney Precision Medicine Project (KPMP) (n = 44), the Atherosclerosis Risk in Communities (ARIC) study (n = 4610), and the COVID-19 Host Response and Clinical Outcomes (CHROME) study (n = 268). Our findings indicate 156 plasma proteins significantly linked to ATI with osteopontin, macrophage mannose receptor 1, and tenascin C showing the strongest associations. Pathway analysis highlight immune regulation and organelle stress responses in ATI pathogenesis.
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    Precision Medicine in Nephrology: An Integrative Framework of Multidimensional Data in the Kidney Precision Medicine Project
    (Elsevier, 2024) El-Achkar, Tarek M.; Eadon, Michael T.; Kretzler, Matthias; Himmelfarb, Jonathan; Kidney Precision Medicine Project; Medicine, School of Medicine
    Chronic kidney disease (CKD) and acute kidney injury (AKI) are heterogeneous syndromes defined clinically by serial measures of kidney function. Each condition possesses strong histopathologic associations, including glomerular obsolescence or acute tubular necrosis, respectively. Despite such characterization, there remains wide variation in patient outcomes and treatment responses. Precision medicine efforts, as exemplified by the Kidney Precision Medicine Project (KPMP), have begun to establish evolving, spatially anchored, cellular and molecular atlases of the cell types, states, and niches of the kidney in health and disease. The KPMP atlas provides molecular context for CKD and AKI disease drivers and will help define subtypes of disease that are not readily apparent from canonical functional or histopathologic characterization but instead are appreciable through advanced clinical phenotyping, pathomic, transcriptomic, proteomic, epigenomic, and metabolomic interrogation of kidney biopsy samples. This perspective outlines the structure of the KPMP, its approach to the integration of these diverse datasets, and its major outputs relevant to future patient care.
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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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    A reference tissue atlas for the human kidney
    (American Association for the Advancement of Science, 2022) Hansen, Jens; Sealfon, Rachel; Menon, Rajasree; Eadon, Michael T.; Lake, Blue B.; Steck, Becky; Anjani, Kavya; Parikh, Samir; Sigdel, Tara K.; Zhang, Guanshi; Velickovic, Dusan; Barwinska, Daria; Alexandrov, Theodore; Dobi, Dejan; Rashmi, Priyanka; Otto, Edgar A.; Rivera, Miguel; Rose, Michael P.; Anderton, Christopher R.; Shapiro, John P.; Pamreddy, Annapurna; Winfree, Seth; Xiong, Yuguang; He, Yongqun; de Boer, Ian H.; Hodgin, Jeffrey B.; Barisoni, Laura; Naik, Abhijit S.; Sharma, Kumar; Sarwal, Minnie M.; Zhang, Kun; Himmelfarb, Jonathan; Rovin, Brad; El-Achkar, Tarek M.; Laszik, Zoltan; He, John Cijiang; Dagher, Pierre C.; Valerius, M. Todd; Jain, Sanjay; Satlin, Lisa M.; Troyanskaya, Olga G.; Kretzler, Matthias; Iyengar, Ravi; Azeloglu, Evren U.; Kidney Precision Medicine Project; Medicine, School of Medicine
    Kidney Precision Medicine Project (KPMP) is building a spatially specified human kidney tissue atlas in health and disease with single-cell resolution. Here, we describe the construction of an integrated reference map of cells, pathways, and genes using unaffected regions of nephrectomy tissues and undiseased human biopsies from 56 adult subjects. We use single-cell/nucleus transcriptomics, subsegmental laser microdissection transcriptomics and proteomics, near-single-cell proteomics, 3D and CODEX imaging, and spatial metabolomics to hierarchically identify genes, pathways, and cells. Integrated data from these different technologies coherently identify cell types/subtypes within different nephron segments and the interstitium. These profiles describe cell-level functional organization of the kidney following its physiological functions and link cell subtypes to genes, proteins, metabolites, and pathways. They further show that messenger RNA levels along the nephron are congruent with the subsegmental physiological activity. This reference atlas provides a framework for the classification of kidney disease when multiple molecular mechanisms underlie convergent clinical phenotypes.