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Browsing by Author "Shapiro, John P."
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Item 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 MedicineThe 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.Item 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 MedicineKidney 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.