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Kim T, Surapaneni AL, Schmidt IM, Eadon MT, Kalim S, Srivastava A, Palsson R, Stillman IE, Hodgin JB, Menon R, Otto EA, Coresh J, Grams ME, Waikar SS, Rhee EP. Plasma Proteins associated with Chronic Histopathologic Lesions on Kidney Biopsy. J Am Soc Nephrol 2024:00001751-990000000-00298. [PMID: 38656806 DOI: 10.1681/asn.0000000000000358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 04/17/2024] [Indexed: 04/26/2024] Open
Abstract
BACKGROUND The severity of chronic histopathologic lesions on kidney biopsy is independently associated with higher risk of progressive chronic kidney disease (CKD). Because kidney biopsies are invasive, identification of blood markers that report on underlying kidney histopathology has the potential to enhance CKD care. METHODS We examined the association between 6592 plasma protein levels measured by aptamers and the severity of interstitial fibrosis and tubular atrophy (IFTA), glomerulosclerosis, arteriolar sclerosis, and arterial sclerosis among 434 participants of the Boston Kidney Biopsy Cohort. For proteins significantly associated with at least one histologic lesion, we assessed renal arteriovenous protein gradients among 21 individuals who had undergone invasive catheterization and assessed the expression of the cognate gene among 47 individuals with single cell RNA sequencing data in the Kidney Precision Medicine Project. RESULTS In models adjusted for estimated glomerular filtration rate (eGFR), proteinuria, and demographic factors, we identified 35 proteins associated with one or more chronic histologic lesions, including 20 specific for IFTA, 8 specific for glomerulosclerosis, and 1 specific for arteriolar sclerosis. In general, higher levels of these proteins were associated with more severe histologic score and lower eGFR. Exceptions included testican-2 and NELL1, which were associated with less glomerulosclerosis and IFTA, respectively, and higher eGFR; notably, both of these proteins demonstrated significantly higher levels from artery to renal vein, demonstrating net kidney release. In the Kidney Precision Medicine Project, 13 of the 35 protein hits had cognate gene expression enriched in one or more cell types in the kidney, including podocyte expression of select glomerulosclerosis markers (including testican-2) and tubular expression of several IFTA markers (including NELL1). CONCLUSIONS Proteomic analysis identified circulating proteins associated with chronic histopathologic lesions, some of which have concordant site-specific expression within the kidney.
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Affiliation(s)
- Taesoo Kim
- Division of Nephrology, Department of Medicine, Massachusetts General Hospital, Boston, MA
| | - Aditya L Surapaneni
- Department of Medicine, New York University Langone School of Medicine, New York, NY
| | - Insa M Schmidt
- Section of Nephrology, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine and Boston Medical Center, Boston, MA
| | - Michael T Eadon
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - Sahir Kalim
- Division of Nephrology, Department of Medicine, Massachusetts General Hospital, Boston, MA
| | - Anand Srivastava
- Division of Nephrology, University of Illinois Chicago, Chicago, IL
| | - Ragnar Palsson
- Division of Nephrology, Department of Medicine, Massachusetts General Hospital, Boston, MA
| | - Isaac E Stillman
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY
| | | | - Rajasree Menon
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI
| | - Edgar A Otto
- Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Morgan E Grams
- Department of Medicine, New York University Langone School of Medicine, New York, NY
| | - Sushrut S Waikar
- Section of Nephrology, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine and Boston Medical Center, Boston, MA
| | - Eugene P Rhee
- Division of Nephrology, Department of Medicine, Massachusetts General Hospital, Boston, MA
- Endocrine Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA
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El-Achkar TM, Eadon MT, Kretzler M, Himmelfarb J. Precision Medicine in Nephrology: An Integrative Framework of Multidimensional Data in the Kidney Precision Medicine Project. Am J Kidney Dis 2024; 83:402-410. [PMID: 37839688 PMCID: PMC10922684 DOI: 10.1053/j.ajkd.2023.08.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 08/20/2023] [Accepted: 08/25/2023] [Indexed: 10/17/2023]
Abstract
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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Affiliation(s)
- Tarek M El-Achkar
- Division of Nephrology, School of Medicine, Indiana University, and Richard L. Roudebush Veteran Affairs Medical Center, Indianapolis, Indiana
| | - Michael T Eadon
- Division of Nephrology, School of Medicine, Indiana University, and Richard L. Roudebush Veteran Affairs Medical Center, Indianapolis, Indiana
| | - Matthias Kretzler
- Department of Computational Medicine & Bioinformatics, and Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Jonathan Himmelfarb
- Kidney Research Institute and Division of Nephrology, University of Washington, Seattle, Washington.
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Jones BA, Gisch DL, Myakala K, Sadiq A, Cheng YH, Taranenko E, Panov J, Korolowicz K, Wang X, Rosenberg AZ, Jain S, Eadon MT, Levi M. Nicotinamide riboside activates renal metabolism and protects the kidney in a model of Alport syndrome. bioRxiv 2024:2024.02.26.580911. [PMID: 38464264 PMCID: PMC10925224 DOI: 10.1101/2024.02.26.580911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Chronic kidney disease (CKD) is associated with renal metabolic disturbances, including impaired fatty acid oxidation (FAO). Nicotinamide adenine dinucleotide (NAD + ) is a small molecule that participates in hundreds of metabolism-related reactions. NAD + levels are decreased in CKD, and NAD + supplementation is protective. However, both the mechanism of how NAD + supplementation protects from CKD, as well as the cell types most responsible, are poorly understood. Using a mouse model of Alport syndrome, we show that nicotinamide riboside (NR), an NAD + precursor, stimulates renal peroxisome proliferator-activated receptor α signaling and restores FAO in the proximal tubules, thereby protecting from CKD in both sexes. Bulk RNA-sequencing shows that renal metabolic pathways are impaired in Alport mice and dramatically activated by NR in both sexes. These transcriptional changes are confirmed by orthogonal imaging techniques and biochemical assays. Single nuclei RNA-sequencing and spatial transcriptomics, both the first of their kind from Alport mice, show that NAD + supplementation restores FAO in the proximal tubules with minimal effects on the podocytes. Finally, we also report, for the first time, sex differences at the transcriptional level in this Alport model. Male Alport mice had more severe inflammation and fibrosis than female mice at the transcriptional level. In summary, the data herein identify both the protective mechanism and location of NAD + supplementation in this model of CKD.
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Gisch DL, Brennan M, Lake BB, Basta J, Keller MS, Melo Ferreira R, Akilesh S, Ghag R, Lu C, Cheng YH, Collins KS, Parikh SV, Rovin BH, Robbins L, Stout L, Conklin KY, Diep D, Zhang B, Knoten A, Barwinska D, Asghari M, Sabo AR, Ferkowicz MJ, Sutton TA, Kelly KJ, De Boer IH, Rosas SE, Kiryluk K, Hodgin JB, Alakwaa F, Winfree S, Jefferson N, Türkmen A, Gaut JP, Gehlenborg N, Phillips CL, El-Achkar TM, Dagher PC, Hato T, Zhang K, Himmelfarb J, Kretzler M, Mollah S, Jain S, Rauchman M, Eadon MT. The chromatin landscape of healthy and injured cell types in the human kidney. Nat Commun 2024; 15:433. [PMID: 38199997 PMCID: PMC10781985 DOI: 10.1038/s41467-023-44467-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 12/14/2023] [Indexed: 01/12/2024] Open
Abstract
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.
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Affiliation(s)
- Debora L Gisch
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | | | - Blue B Lake
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
- San Diego Institute of Science, Altos Labs, San Diego, CA, USA
| | - Jeannine Basta
- Washington University in Saint Louis, St. Louis, MO, 63103, USA
| | | | | | | | - Reetika Ghag
- Washington University in Saint Louis, St. Louis, MO, 63103, USA
| | - Charles Lu
- Washington University in Saint Louis, St. Louis, MO, 63103, USA
| | - Ying-Hua Cheng
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | | | - Samir V Parikh
- Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Brad H Rovin
- Ohio State University Wexner Medical Center, Columbus, OH, 43210, USA
| | - Lynn Robbins
- St. Louis Veteran Affairs Medical Center, St. Louis, MO, 63106, USA
| | - Lisa Stout
- Washington University in Saint Louis, St. Louis, MO, 63103, USA
| | - Kimberly Y Conklin
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Dinh Diep
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Bo Zhang
- Washington University in Saint Louis, St. Louis, MO, 63103, USA
| | - Amanda Knoten
- Washington University in Saint Louis, St. Louis, MO, 63103, USA
| | - Daria Barwinska
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Mahla Asghari
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Angela R Sabo
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | | | - Timothy A Sutton
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | | | | | - Sylvia E Rosas
- Joslin Diabetes Center, Harvard Medical School, Boston, MA, 02215, USA
| | | | | | | | - Seth Winfree
- University of Nebraska Medical Center, Omaha, NE, 68198, USA
| | - Nichole Jefferson
- Kidney Precision Medicine Project Community Engagement Committee, Dallas, TX, USA
| | - Aydın Türkmen
- Istanbul School of Medicine, Division of Nephrology, Istanbul, Turkey
| | - Joseph P Gaut
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | | | | | | | - Pierre C Dagher
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Takashi Hato
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Kun Zhang
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | | | | | - Shamim Mollah
- Washington University in Saint Louis, St. Louis, MO, 63103, USA
| | - Sanjay Jain
- Washington University in Saint Louis, St. Louis, MO, 63103, USA.
| | - Michael Rauchman
- Washington University in Saint Louis, St. Louis, MO, 63103, USA.
| | - Michael T Eadon
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
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Wang J, Li J, Kramer ST, Su L, Chang Y, Xu C, Eadon MT, Kiryluk K, Ma Q, Xu D. Dimension-agnostic and granularity-based spatially variable gene identification using BSP. Nat Commun 2023; 14:7367. [PMID: 37963892 PMCID: PMC10645821 DOI: 10.1038/s41467-023-43256-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 11/03/2023] [Indexed: 11/16/2023] Open
Abstract
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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Affiliation(s)
- Juexin Wang
- Department of BioHealth Informatics, Luddy School of Informatics, Computing, and Engineering, Indiana University Indianapolis, Indianapolis, IN, 46202, USA.
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, 65211, USA.
| | - Jinpu Li
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO, 65211, USA
- Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, 65211, USA
| | - Skyler T Kramer
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO, 65211, USA
- Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, 65211, USA
| | - Li Su
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO, 65211, USA
- Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, 65211, USA
| | - Yuzhou Chang
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA
- Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH, 43210, USA
| | - Chunhui Xu
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO, 65211, USA
- Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, 65211, USA
| | - Michael T Eadon
- Department of Medicine, Indiana University, Indianapolis, IN, 46202, USA
| | - Krzysztof Kiryluk
- Division of Nephrology, Department of Medicine, Vagelos College of Physicians & Surgeons, Columbia University Irving Medical Center, New York, NY, 10027, USA
| | - Qin Ma
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA.
- Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH, 43210, USA.
| | - Dong Xu
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, 65211, USA.
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO, 65211, USA.
- Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, 65211, USA.
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6
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Heruye S, Myslinski J, Zeng C, Zollman A, Makino S, Nanamatsu A, Mir Q, Janga SC, Doud EH, Eadon MT, Maier B, Hamada M, Tran TM, Dagher PC, Hato T. Inflammation primes the kidney for recovery by activating AZIN1 A-to-I editing. bioRxiv 2023:2023.11.09.566426. [PMID: 37986799 PMCID: PMC10659426 DOI: 10.1101/2023.11.09.566426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
The progression of kidney disease varies among individuals, but a general methodology to quantify disease timelines is lacking. Particularly challenging is the task of determining the potential for recovery from acute kidney injury following various insults. Here, we report that quantitation of post-transcriptional adenosine-to-inosine (A-to-I) RNA editing offers a distinct genome-wide signature, enabling the delineation of disease trajectories in the kidney. A well-defined murine model of endotoxemia permitted the identification of the origin and extent of A-to-I editing, along with temporally discrete signatures of double-stranded RNA stress and Adenosine Deaminase isoform switching. We found that A-to-I editing of Antizyme Inhibitor 1 (AZIN1), a positive regulator of polyamine biosynthesis, serves as a particularly useful temporal landmark during endotoxemia. Our data indicate that AZIN1 A-to-I editing, triggered by preceding inflammation, primes the kidney and activates endogenous recovery mechanisms. By comparing genetically modified human cell lines and mice locked in either A-to-I edited or uneditable states, we uncovered that AZIN1 A-to-I editing not only enhances polyamine biosynthesis but also engages glycolysis and nicotinamide biosynthesis to drive the recovery phenotype. Our findings implicate that quantifying AZIN1 A-to-I editing could potentially identify individuals who have transitioned to an endogenous recovery phase. This phase would reflect their past inflammation and indicate their potential for future recovery.
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Affiliation(s)
- Segewkal Heruye
- Department of Medicine, Indiana University School of Medicine
| | - Jered Myslinski
- Department of Medicine, Indiana University School of Medicine
| | - Chao Zeng
- Faculty of Science and Engineering, Waseda University, Tokyo
| | - Amy Zollman
- Department of Medicine, Indiana University School of Medicine
| | - Shinichi Makino
- Department of Medicine, Indiana University School of Medicine
| | - Azuma Nanamatsu
- Department of Medicine, Indiana University School of Medicine
| | - Quoseena Mir
- Luddy School of Informatics, Computing, and Engineering, Indiana University
| | | | - Emma H Doud
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine
| | - Michael T Eadon
- Department of Medicine, Indiana University School of Medicine
| | - Bernhard Maier
- Department of Medicine, Indiana University School of Medicine
| | - Michiaki Hamada
- Faculty of Science and Engineering, Waseda University, Tokyo
- AIST-Waseda University Computational Bio Big-Data Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, Tokyo
- Graduate School of Medicine, Nippon Medical School, Tokyo
| | - Tuan M Tran
- Department of Medicine, Indiana University School of Medicine
- Richard L. Roudebush Veterans Affairs Medical Center, Indianapolis
| | - Pierre C Dagher
- Department of Medicine, Indiana University School of Medicine
| | - Takashi Hato
- Department of Medicine, Indiana University School of Medicine
- Richard L. Roudebush Veterans Affairs Medical Center, Indianapolis
- Department of Medical and Molecular Genetics, Indiana University School of Medicine
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Eadon MT, Rosenman MB, Zhang P, Fulton CR, Callaghan JT, Holmes AM, Levy KD, Gupta SK, Haas DM, Vuppalanchi R, Benson EA, Kreutz RP, Tillman EM, Shugg T, Pierson RC, Gufford BT, Pratt VM, Zang Y, Desta Z, Dexter PR, Skaar TC. The INGENIOUS trial: Impact of pharmacogenetic testing on adverse events in a pragmatic clinical trial. Pharmacogenomics J 2023; 23:169-177. [PMID: 37689822 PMCID: PMC10805517 DOI: 10.1038/s41397-023-00315-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 08/20/2023] [Accepted: 08/23/2023] [Indexed: 09/11/2023]
Abstract
Adverse drug events (ADEs) account for a significant mortality, morbidity, and cost burden. Pharmacogenetic testing has the potential to reduce ADEs and inefficacy. The objective of this INGENIOUS trial (NCT02297126) analysis was to determine whether conducting and reporting pharmacogenetic panel testing impacts ADE frequency. The trial was a pragmatic, randomized controlled clinical trial, adapted as a propensity matched analysis in individuals (N = 2612) receiving a new prescription for one or more of 26 pharmacogenetic-actionable drugs across a community safety-net and academic health system. The intervention was a pharmacogenetic testing panel for 26 drugs with dosage and selection recommendations returned to the health record. The primary outcome was occurrence of ADEs within 1 year, according to modified Common Terminology Criteria for Adverse Events (CTCAE). In the propensity-matched analysis, 16.1% of individuals experienced any ADE within 1-year. Serious ADEs (CTCAE level ≥ 3) occurred in 3.2% of individuals. When combining all 26 drugs, no significant difference was observed between the pharmacogenetic testing and control arms for any ADE (Odds ratio 0.96, 95% CI: 0.78-1.18), serious ADEs (OR: 0.91, 95% CI: 0.58-1.40), or mortality (OR: 0.60, 95% CI: 0.28-1.21). However, sub-group analyses revealed a reduction in serious ADEs and death in individuals who underwent pharmacogenotyping for aripiprazole and serotonin or serotonin-norepinephrine reuptake inhibitors (OR 0.34, 95% CI: 0.12-0.85). In conclusion, no change in overall ADEs was observed after pharmacogenetic testing. However, limitations incurred during INGENIOUS likely affected the results. Future studies may consider preemptive, rather than reactive, pharmacogenetic panel testing.
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Affiliation(s)
- Michael T Eadon
- Indiana University School of Medicine, Department of Medicine, Indianapolis, IN, USA
| | - Marc B Rosenman
- Ann & Robert H. Lurie Children's Hospital of Chicago, and Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Pengyue Zhang
- Indiana University School of Medicine, Department of Biostatistics and Heath Data Science, Indianapolis, IN, USA
| | - Cathy R Fulton
- Luddy School of Informatics, Computing, and Engineering, Indianapolis, IN, 46202, USA
| | - John T Callaghan
- Indiana University School of Medicine, Department of Medicine, Indianapolis, IN, USA
| | - Ann M Holmes
- Indiana University Richard M. Fairbanks School of Public Health, Indianapolis, IN, 46202, USA
| | - Kenneth D Levy
- Indiana University School of Medicine, Department of Medicine, Indianapolis, IN, USA
| | - Samir K Gupta
- Indiana University School of Medicine, Department of Medicine, Indianapolis, IN, USA
| | - David M Haas
- Indiana University School of Medicine, Department of Obstetrics and Gynecology, Indianapolis, IN, USA
| | - Raj Vuppalanchi
- Indiana University School of Medicine, Department of Medicine, Indianapolis, IN, USA
| | - Eric A Benson
- Indiana University School of Medicine, Department of Medicine, Indianapolis, IN, USA
| | - Rolf P Kreutz
- Indiana University School of Medicine, Department of Medicine, Indianapolis, IN, USA
| | - Emma M Tillman
- Indiana University School of Medicine, Department of Medicine, Indianapolis, IN, USA
| | - Tyler Shugg
- Indiana University School of Medicine, Department of Medicine, Indianapolis, IN, USA
| | - Rebecca C Pierson
- Indiana University School of Medicine, Department of Medicine, Indianapolis, IN, USA
- Indiana University School of Medicine, Department of Obstetrics and Gynecology, Indianapolis, IN, USA
- Community Fertility Specialty Care, Indianapolis, IN, USA
| | - Brandon T Gufford
- Indiana University School of Medicine, Department of Medicine, Indianapolis, IN, USA
| | - Victoria M Pratt
- Indiana University School of Medicine, Department of Medical and Molecular Genetics, Indianapolis, IN, USA
| | - Yong Zang
- Indiana University School of Medicine, Department of Biostatistics and Heath Data Science, Indianapolis, IN, USA
| | - Zeruesenay Desta
- Indiana University School of Medicine, Department of Medicine, Indianapolis, IN, USA
| | - Paul R Dexter
- Indiana University School of Medicine, Department of Medicine, Indianapolis, IN, USA
| | - Todd C Skaar
- Indiana University School of Medicine, Department of Medicine, Indianapolis, IN, USA.
- Indiana University School of Medicine, Department of Medical and Molecular Genetics, Indianapolis, IN, USA.
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8
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Kouri AM, Caza TN, Beck LH, Misurac JM, Evans MD, Phillips CL, Eadon MT, Larsen CP, Andreoli SP, Bu L, Rheault MN, Khalid M. Clinical and Histopathologic Characteristics of Pediatric Patients With Primary Membranous Nephropathy. Kidney Int Rep 2023; 8:2368-2375. [PMID: 38025223 PMCID: PMC10658230 DOI: 10.1016/j.ekir.2023.08.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 08/05/2023] [Accepted: 08/14/2023] [Indexed: 12/01/2023] Open
Abstract
Introduction Primary membranous nephropathy (PMN) is uncommon in children. Therefore, data on the clinical course of affected children are scarce. In recent years, several novel antigens have been implicated in the pathogenesis of PMN. However, the histopathologic characteristics of pediatric patients with PMN remain poorly represented in the literature. Methods We have retrospectively analyzed the clinical presentation and outcomes data of 21 children with PMN from 3 centers in the United States. In addition, we have identified novel antigens in biopsy specimens from these patients and correlated their presence or absence to clinical outcomes. Finally, we compared the results of the novel antigen staining from our clinical cohort to a validation cohort of 127 biopsy specimens from children with PMN at Arkana Laboratories. Results The data from the 2 cohorts demonstrated similar overall antigen positivity rates of 62% to 63%, with phospholipase A2 receptor (PLA2R) and exostosin 1 (EXT1) being the most commonly found antigens. Results from the clinical cohort showed that overall, the kidney prognosis for children with PMN was good, with 17 of 21 patients entering a complete or partial remission. Children who were positive for PLA2R or EXT1 were significantly more likely to enter remission than those in the antigen negative group. Conclusion Approximately 60% of pediatric membranous cases are positive for a novel antigen on kidney biopsy and the clinical prognosis is generally favorable. More studies are needed to understand the clinical implications of each specific novel antigen.
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Affiliation(s)
- Anne M. Kouri
- Division of Pediatric Nephrology, University of Minnesota Masonic Children’s Hospital, Minneapolis, Minnesota, USA
| | | | - Laurence H. Beck
- Boston University Chobanian and Avedisian School of Medicine and Boston Medical Center, Boston, Massachusetts, USA
| | - Jason M. Misurac
- Division of Pediatric Nephrology, Dialysis and Transplantation, University of Iowa Stead Family Children’s Hospital, Iowa City, Iowa, USA
| | - Michael D. Evans
- Clinical and Translational Science Institute, University of Minnesota, Minneapolis, Minnesota, USA
| | - Carrie L. Phillips
- Department of Pathology and Laboratory Medicine, Indiana University, Indianapolis, Indiana, USA
| | - Michael T. Eadon
- Division of Nephrology, Indiana University, Indianapolis, Indiana, USA
| | | | - Sharon P. Andreoli
- Riley Hospital for Children at IU Health, Division of Pediatric Nephrology and Hypertension, Indianapolis, Indiana, USA
| | - Lihong Bu
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Michelle N. Rheault
- Division of Pediatric Nephrology, University of Minnesota Masonic Children’s Hospital, Minneapolis, Minnesota, USA
| | - Myda Khalid
- Riley Hospital for Children at IU Health, Division of Pediatric Nephrology and Hypertension, Indianapolis, Indiana, USA
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9
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Ferreira RM, de Almeida R, Culp C, Witzmann F, Wang M, Kher R, Nagami GT, Mohallem R, Andolino CJ, Aryal UK, Eadon MT, Bacallao RL. Proteomic analysis of murine kidney proximal tubule sub-segment derived cell lines reveals preferences in mitochondrial pathway activity. J Proteomics 2023; 289:104998. [PMID: 37657718 PMCID: PMC10843797 DOI: 10.1016/j.jprot.2023.104998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 07/16/2023] [Accepted: 08/28/2023] [Indexed: 09/03/2023]
Abstract
The proximal tubule (PT) is a nephron segment that is responsible for the majority of solute and water reabsorption in the kidney. Each of its sub-segments have specialized functions; however, little is known about the genes and proteins that determine the oxidative phosphorylation capacity of the PT sub-segments. This information is critical to understanding kidney function and will provide a comprehensive landscape of renal cell adaptations to injury, physiologic stressors, and development. This study analyzed three immortalized murine renal cell lines (PT S1, S2, and S3 segments) for protein content and compared them to a murine fibroblast cell line. All three proximal tubule cell lines generate ATP predominantly by oxidative phosphorylation while the fibroblast cell line is glycolytic. The proteomic data demonstrates that the most significant difference in proteomic signatures between the cell lines are proteins known to be localized in the nucleus followed by mitochondrial proteins. Mitochondrial metabolic substrate utilization assays were performed using the proximal tubule cell lines to determine substrate utilization kinetics thereby providing a physiologic context to the proteomic dataset. This data will allow researchers to study differences in nephron-specific cell lines, between epithelial and fibroblast cells, and between actively respiring cells and glycolytic cells. SIGNIFICANCE: Proteomic analysis of proteins expressed in immortalized murine renal proximal tubule cells was compared to a murine fibroblast cell line proteome. The proximal tubule segment specific cell lines: S1, S2 and S3 are all grown under conditions whereby the cells generate ATP by oxidative phosphorylation while the fibroblast cell line utilizes anaerobic glycolysis for ATP generation. The proteomic studies allow for the following queries: 1) comparisons between the proximal tubule segment specific cell lines, 2) comparisons between polarized epithelia and fibroblasts, 3) comparison between cells employing oxidative phosphorylation versus anaerobic glycolysis and 4) comparisons between cells grown on clear versus opaque membrane supports. The data finds major differences in nuclear protein expression and mitochondrial proteins. This proteomic data set will be an important baseline dataset for investigators who need immortalized renal proximal tubule epithelial cells for their research.
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Affiliation(s)
- Ricardo Melo Ferreira
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
| | - Rita de Almeida
- Instituto de Física and Instituto Nacional de Ciência e Tecnologia, Universidade Federal do Rio Grande do Sul, 91501-970 Porto Alegre, RS, Brazil.
| | - Clayton Culp
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
| | - Frank Witzmann
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
| | - Mu Wang
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
| | - Rajesh Kher
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
| | - Glenn T Nagami
- Division of Nephrology, VA Greater Los Angeles Healthcare System, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.
| | - Rodrigo Mohallem
- Department of Comparative Pathobiology, Purdue University, West Lafayette, IN 47907, USA; Purdue Proteomics Facility, Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA.
| | - Chaylen Jade Andolino
- Purdue Proteomics Facility, Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA.
| | - Uma K Aryal
- Department of Comparative Pathobiology, Purdue University, West Lafayette, IN 47907, USA; Purdue Proteomics Facility, Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA.
| | - Michael T Eadon
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
| | - Robert L Bacallao
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
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10
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Janosevic D, De Luca T, Ferreira RM, Gisch DL, Hato T, Luo J, Yang Y, Hodgin JB, Dagher PC, Eadon MT. miRNA and mRNA Signatures in Human Acute Kidney Injury Tissue. bioRxiv 2023:2023.09.11.557054. [PMID: 37745313 PMCID: PMC10515816 DOI: 10.1101/2023.09.11.557054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Acute kidney injury (AKI) is an important contributor to the development of chronic kidney disease (CKD). There is a need to understand molecular mediators that drive either recovery or progression to CKD. In particular, the role of miRNA and its regulatory role in AKI is poorly understood. We performed miRNA and mRNA sequencing on biobanked human kidney tissues obtained in the routine clinical care of patients with the diagnoses of AKI and minimal change disease (MCD), in addition to nephrectomized (Ref) tissue from individuals without known kidney disease. Transcriptomic analysis of mRNA revealed that Ref tissues exhibited a similar injury signature to AKI, not identified in MCD samples. The transcriptomic signature of human AKI was enriched with genes in pathways involved in cell adhesion and epithelial-to-mesenchymal transition (e.g., CDH6, ITGB6, CDKN1A ). miRNA DE analysis revealed upregulation of miRNA associated with immune cell recruitment and inflammation (e.g., miR-146a, miR-155, miR-142, miR-122). These miRNA (i.e., miR-122, miR-146) are also associated with downregulation of mRNA such as DDR2 and IGFBP6 , respectively. These findings suggest integrated interactions between miRNAs and target mRNAs in AKI-related processes such as inflammation, immune cell activation and epithelial-to-mesenchymal transition. These data contribute several novel findings when describing the epigenetic regulation of AKI by miRNA, and also underscores the importance of utilizing an appropriate reference control tissue to understand canonical pathway alterations in AKI.
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11
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Menon R, Otto EA, Barisoni L, Melo Ferreira R, Limonte CP, Godfrey B, Eichinger F, Nair V, Naik AS, Subramanian L, D'Agati V, Henderson JM, Herlitz L, Kiryluk K, Moledina DG, Moeckel GW, Palevsky PM, Parikh CR, Randhawa P, Rosas SE, Rosenberg AZ, Stillman I, Toto R, Torrealba J, Vazquez MA, Waikar SS, Alpers CE, Nelson RG, Eadon MT, Kretzler M, Hodgin JB. Defining the molecular correlate of arteriolar hyalinosis in kidney disease progression by integration of single cell transcriptomic analysis and pathology scoring. medRxiv 2023:2023.06.14.23291150. [PMID: 37398386 PMCID: PMC10312894 DOI: 10.1101/2023.06.14.23291150] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Arteriolar hyalinosis in kidneys is an independent predictor of cardiovascular disease, the main cause of mortality in chronic kidney disease (CKD). The underlying molecular mechanisms of protein accumulation in the subendothelial space are not well understood. Using single cell transcriptomic data and whole slide images from kidney biopsies of patients with CKD and acute kidney injury in the Kidney Precision Medicine Project, the molecular signals associated with arteriolar hyalinosis were evaluated. Co-expression network analysis of the endothelial genes yielded three gene set modules as significantly associated with arteriolar hyalinosis. Pathway analysis of these modules showed enrichment of transforming growth factor beta / bone morphogenetic protein (TGFβ / BMP) and vascular endothelial growth factor (VEGF) signaling pathways in the endothelial cell signatures. Ligand-receptor analysis identified multiple integrins and cell adhesion receptors as over-expressed in arteriolar hyalinosis, suggesting a potential role of integrin-mediated TGFβ signaling. Further analysis of arteriolar hyalinosis associated endothelial module genes identified focal segmental glomerular sclerosis as an enriched term. On validation in gene expression profiles from the Nephrotic Syndrome Study Network cohort, one of the three modules was significantly associated with the composite endpoint (> 40% reduction in estimated glomerular filtration rate (eGFR) or kidney failure) independent of age, sex, race, and baseline eGFR, suggesting poor prognosis with elevated expression of genes in this module. Thus, integration of structural and single cell molecular features yielded biologically relevant gene sets, signaling pathways and ligand-receptor interactions, underlying arteriolar hyalinosis and putative targets for therapeutic intervention.
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12
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Tillman E, Nikirk MG, Chen J, Skaar TC, Shugg T, Maddatu JP, Sharfuddin AA, Eadon MT. Implementation of Clinical Cytochrome P450 3A Genotyping for Tacrolimus Dosing in a Large Kidney Transplant Program. J Clin Pharmacol 2023; 63:961-967. [PMID: 37042314 PMCID: PMC10478012 DOI: 10.1002/jcph.2249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 04/03/2023] [Indexed: 04/13/2023]
Abstract
Tacrolimus is a calcineurin inhibitor with a narrow therapeutic range and is metabolized by cytochrome P450 (CYP) isoenzymes CYP3A4 and CYP3A5. The Clinical Pharmacogenetic Implementation Consortium published evidence-based guidelines for CYP3A5 normal/intermediate metabolizers prescribed tacrolimus, yet few transplant centers have implemented routine testing. The objective of this study was to implement preemptive CYP3A genotyping into clinical practice in a large kidney transplant program and to evaluate workflow feasibility, potential clinical benefit, and reimbursement to identify barriers and determine sustainability. Preemptive pharmacogenetic testing for CYP3A5 and CYP3A4 was implemented in all patients listed for a kidney transplant as part of standard clinical care. Genotyping was performed at the listing appointment, results were reported as discrete data in the electronic medical record, and education and clinical decision support alerts were developed to provide pharmacogenetic-recommended tacrolimus dosing. During this initial phase, all patients were administered standard tacrolimus dosing, and clinical and reimbursement outcomes were collected. Greater than 99.5% of genotyping claims were reimbursed by third-party payers. CYP3A5 normal/intermediate metabolizers had significantly fewer tacrolimus trough concentrations within the target range and a significantly longer time to their first therapeutic trough compared to poor metabolizers. The challenge of tacrolimus dosing is magnified in the African American population. The US Food and Drug Administration drug label recommends increased starting doses in African ancestry, yet only ≈66% of African Americans in our cohort were normal/intermediate metabolizers who required higher doses. Routine CYP3A5 genotyping may overcome this issue by using genotype over race as a more accurate predictor of drug response.
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Affiliation(s)
- Emma Tillman
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Miley G. Nikirk
- Department of Pharmacy, Indiana University Health, Indianapolis, Indiana, USA
| | - Jeanne Chen
- Department of Pharmacy, Indiana University Health, Indianapolis, Indiana, USA
| | - Todd C. Skaar
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Tyler Shugg
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Judith P. Maddatu
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Asif A. Sharfuddin
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Michael T. Eadon
- Department of Pharmacy, Indiana University Health, Indianapolis, Indiana, USA
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
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13
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Canela VH, Bowen WS, Ferreira RM, Syed F, Lingeman JE, Sabo AR, Barwinska D, Winfree S, Lake BB, Cheng YH, Gaut JP, Ferkowicz M, LaFavers KA, Zhang K, Coe FL, Worcester E, Jain S, Eadon MT, Williams JC, El-Achkar TM. A spatially anchored transcriptomic atlas of the human kidney papilla identifies significant immune injury in patients with stone disease. Nat Commun 2023; 14:4140. [PMID: 37468493 PMCID: PMC10356953 DOI: 10.1038/s41467-023-38975-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 05/24/2023] [Indexed: 07/21/2023] Open
Abstract
Kidney stone disease causes significant morbidity and increases health care utilization. In this work, we decipher the cellular and molecular niche of the human renal papilla in patients with calcium oxalate (CaOx) stone disease and healthy subjects. In addition to identifying cell types important in papillary physiology, we characterize collecting duct cell subtypes and an undifferentiated epithelial cell type that was more prevalent in stone patients. Despite the focal nature of mineral deposition in nephrolithiasis, we uncover a global injury signature characterized by immune activation, oxidative stress and extracellular matrix remodeling. We also identify the association of MMP7 and MMP9 expression with stone disease and mineral deposition, respectively. MMP7 and MMP9 are significantly increased in the urine of patients with CaOx stone disease, and their levels correlate with disease activity. Our results define the spatial molecular landscape and specific pathways contributing to stone-mediated injury in the human papilla and identify associated urinary biomarkers.
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Affiliation(s)
- Victor Hugo Canela
- Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - William S Bowen
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Ricardo Melo Ferreira
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Farooq Syed
- Center for Diabetes and Metabolic Diseases, Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN, USA
| | - James E Lingeman
- Department of Urology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Angela R Sabo
- Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Daria Barwinska
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Seth Winfree
- Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE, USA
| | - Blue B Lake
- San Diego Institute of Science, Altos Labs, San Diego, CA, USA
| | - Ying-Hua Cheng
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Joseph P Gaut
- Department of Pathology and Immunology, Washington University, St. Louis, MO, USA
| | - Michael Ferkowicz
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kaice A LaFavers
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kun Zhang
- San Diego Institute of Science, Altos Labs, San Diego, CA, USA
| | - Fredric L Coe
- Department of Medicine, Division of Nephrology, University of Chicago, Chicago, IL, USA
| | - Elaine Worcester
- Department of Medicine, Division of Nephrology, University of Chicago, Chicago, IL, USA
| | - Sanjay Jain
- Department of Medicine, Division of Nephrology, Washington University, St. Louis, MO, USA.
| | - Michael T Eadon
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.
| | - James C Williams
- Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, IN, USA.
| | - Tarek M El-Achkar
- Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Medicine, Indianapolis VA Medical Center, Indianapolis, IN, USA.
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14
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Lake BB, Menon R, Winfree S, Hu Q, Melo Ferreira R, Kalhor K, Barwinska D, Otto EA, Ferkowicz M, Diep D, Plongthongkum N, Knoten A, Urata S, Mariani LH, Naik AS, Eddy S, Zhang B, Wu Y, Salamon D, Williams JC, Wang X, Balderrama KS, Hoover PJ, Murray E, Marshall JL, Noel T, Vijayan A, Hartman A, Chen F, Waikar SS, Rosas SE, Wilson FP, Palevsky PM, Kiryluk K, Sedor JR, Toto RD, Parikh CR, Kim EH, Satija R, Greka A, Macosko EZ, Kharchenko PV, Gaut JP, Hodgin JB, Eadon MT, Dagher PC, El-Achkar TM, Zhang K, Kretzler M, Jain S. An atlas of healthy and injured cell states and niches in the human kidney. Nature 2023; 619:585-594. [PMID: 37468583 PMCID: PMC10356613 DOI: 10.1038/s41586-023-05769-3] [Citation(s) in RCA: 63] [Impact Index Per Article: 63.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 01/30/2023] [Indexed: 07/21/2023]
Abstract
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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Affiliation(s)
- Blue B Lake
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
- San Diego Institute of Science, Altos Labs, San Diego, CA, USA
| | - Rajasree Menon
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Seth Winfree
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE, USA
| | - Qiwen Hu
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Ricardo Melo Ferreira
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kian Kalhor
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Daria Barwinska
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Edgar A Otto
- Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI, USA
| | - Michael Ferkowicz
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Dinh Diep
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
- San Diego Institute of Science, Altos Labs, San Diego, CA, USA
| | - Nongluk Plongthongkum
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Amanda Knoten
- Department of Medicine, Washington University School of Medicine, St Louis, MO, USA
| | - Sarah Urata
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Laura H Mariani
- Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI, USA
| | - Abhijit S Naik
- Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI, USA
| | - Sean Eddy
- Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI, USA
| | - Bo Zhang
- Department of Medicine, Washington University School of Medicine, St Louis, MO, USA
| | - Yan Wu
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
- San Diego Institute of Science, Altos Labs, San Diego, CA, USA
| | - Diane Salamon
- Department of Medicine, Washington University School of Medicine, St Louis, MO, USA
| | - James C Williams
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Xin Wang
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | | | - Paul J Hoover
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Evan Murray
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | | | - Teia Noel
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Anitha Vijayan
- Department of Medicine, Washington University School of Medicine, St Louis, MO, USA
| | | | - Fei Chen
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Sushrut S Waikar
- Section of Nephrology, Boston University School of Medicine and Boston Medical Center, Boston, MA, USA
| | - Sylvia E Rosas
- Kidney and Hypertension Unit, Joslin Diabetes Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Francis P Wilson
- Department of Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Paul M Palevsky
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | | | - John R Sedor
- Lerner Research and Glickman Urology and Kidney Institutes, Cleveland Clinic, Cleveland, OH, USA
| | - Robert D Toto
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - Chirag R Parikh
- Division of Nephrology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Eric H Kim
- Department of Surgery, Washington University School of Medicine, St Louis, MO, USA
| | | | - Anna Greka
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | | | - Peter V Kharchenko
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- San Diego Institute of Science, Altos Labs, San Diego, CA, USA
| | - Joseph P Gaut
- Department of Pathology and Immunology, Washington University School of Medicine, St Louis, MO, USA
| | - Jeffrey B Hodgin
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Michael T Eadon
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
| | - Pierre C Dagher
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
| | - Tarek M El-Achkar
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
| | - Kun Zhang
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.
- San Diego Institute of Science, Altos Labs, San Diego, CA, USA.
| | - Matthias Kretzler
- Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI, USA.
| | - Sanjay Jain
- Department of Medicine, Washington University School of Medicine, St Louis, MO, USA.
- Department of Pathology and Immunology, Washington University School of Medicine, St Louis, MO, USA.
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15
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Gisch DL, Brennan M, Lake BB, Basta J, Keller M, Ferreira RM, Akilesh S, Ghag R, Lu C, Cheng YH, Collins KS, Parikh SV, Rovin BH, Robbins L, Conklin KY, Diep D, Zhang B, Knoten A, Barwinska D, Asghari M, Sabo AR, Ferkowicz MJ, Sutton TA, Kelly KJ, Boer IHD, Rosas SE, Kiryluk K, Hodgin JB, Alakwaa F, Jefferson N, Gaut JP, Gehlenborg N, Phillips CL, El-Achkar TM, Dagher PC, Hato T, Zhang K, Himmelfarb J, Kretzler M, Mollah S, Jain S, Rauchman M, Eadon MT. The chromatin landscape of healthy and injured cell types in the human kidney. bioRxiv 2023:2023.06.07.543965. [PMID: 37333123 PMCID: PMC10274789 DOI: 10.1101/2023.06.07.543965] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
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. However, comprehensive integration of gene expression with epigenetic features that define regulatory elements remains a significant challenge. We measured 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 established a comprehensive and spatially-anchored epigenomic atlas to define the kidney's active, silent, and regulatory accessible chromatin regions across the genome. Using this atlas, we noted distinct control of adaptive injury in different epithelial cell types. A proximal tubule cell transcription factor network of ELF3 , KLF6 , and KLF10 regulated the transition between health and injury, while in thick ascending limb cells this transition was regulated by NR2F1 . Further, combined perturbation of ELF3 , KLF6 , and KLF10 distinguished 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.
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16
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Winfree S, McNutt AT, Khochare S, Borgard TJ, Barwinska D, Sabo AR, Ferkowicz MJ, Williams JC, Lingeman JE, Gulbronson CJ, Kelly KJ, Sutton TA, Dagher PC, Eadon MT, Dunn KW, El-Achkar TM. Integrated Cytometry With Machine Learning Applied to High-Content Imaging of Human Kidney Tissue for In Situ Cell Classification and Neighborhood Analysis. J Transl Med 2023; 103:100104. [PMID: 36867975 PMCID: PMC10293106 DOI: 10.1016/j.labinv.2023.100104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 12/12/2022] [Accepted: 01/07/2023] [Indexed: 02/05/2023] Open
Abstract
The human kidney is a complex organ with various cell types that are intricately organized to perform key physiological functions and maintain homeostasis. New imaging modalities, such as mesoscale and highly multiplexed fluorescence microscopy, are increasingly being applied to human kidney tissue to create single-cell resolution data sets that are both spatially large and multidimensional. These single-cell resolution high-content imaging data sets have great potential to uncover the complex spatial organization and cellular makeup of the human kidney. Tissue cytometry is a novel approach used for the quantitative analysis of imaging data; however, the scale and complexity of such data sets pose unique challenges for processing and analysis. We have developed the Volumetric Tissue Exploration and Analysis (VTEA) software, a unique tool that integrates image processing, segmentation, and interactive cytometry analysis into a single framework on desktop computers. Supported by an extensible and open-source framework, VTEA's integrated pipeline now includes enhanced analytical tools, such as machine learning, data visualization, and neighborhood analyses, for hyperdimensional large-scale imaging data sets. These novel capabilities enable the analysis of mesoscale 2- and 3-dimensional multiplexed human kidney imaging data sets (such as co-detection by indexing and 3-dimensional confocal multiplexed fluorescence imaging). We demonstrate the utility of this approach in identifying cell subtypes in the kidney on the basis of labels, spatial association, and their microenvironment or neighborhood membership. VTEA provides an integrated and intuitive approach to decipher the cellular and spatial complexity of the human kidney and complements other transcriptomics and epigenetic efforts to define the landscape of kidney cell types.
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Affiliation(s)
- Seth Winfree
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana; Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, Indiana; Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, Nebraska.
| | - Andrew T McNutt
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Suraj Khochare
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Tyler J Borgard
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Daria Barwinska
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Angela R Sabo
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana; Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Michael J Ferkowicz
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - James C Williams
- Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, Indiana
| | - James E Lingeman
- Department of Clinical Urology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Connor J Gulbronson
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Katherine J Kelly
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Timothy A Sutton
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Pierre C Dagher
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Michael T Eadon
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Kenneth W Dunn
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Tarek M El-Achkar
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana; Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, Indiana.
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Powell NR, Shugg T, Leighty J, Martin M, Kreutz RP, Eadon MT, Lai D, Lu T, Skaar TC. Analysis of the Combined Effect of rs699 and rs5051 on Angiotensinogen Expression and Hypertension. bioRxiv 2023:2023.04.07.536073. [PMID: 37066278 PMCID: PMC10104131 DOI: 10.1101/2023.04.07.536073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Hypertension (HTN) involves genetic variability in the renin-angiotensin system and characterizing this variability will help advance precision antihypertensive treatments. We previously reported that angiotensinogen (AGT) mRNA is endogenously bound by mir-122-5p and that rs699 A>G significantly decreases reporter mRNA in the functional mirSNP assay PASSPORT-seq. The AGT promoter variant rs5051 C>T is in linkage disequilibrium (LD) with rs699 A>G and increases AGT transcription. We hypothesized that the increased AGT by rs5051 C>T counterbalances AGT decrease by rs699 A>G, and when these variants occur independently, would translate to HTN-related phenotypes. The independent effect of each of these variants is understudied due to their LD, therefore, we used in silico, in vitro, in vivo, and retrospective clinical and biobank analyses to assess HTN and AGT expression phenotypes where rs699 A>G occurs independently from rs5051 C>T. In silico, rs699 A>G is predicted to increase mir-122-5p binding strength by 3%. Mir-eCLIP assay results show that rs699 is 40-45 nucleotides from the strongest microRNA binding site in the AGT mRNA. Unexpectedly, rs699 A>G increases AGT mRNA in a plasmid cDNA HepG2 expression model. GTEx and UK Biobank analyses demonstrate that liver AGT expression and HTN phenotypes were not different when rs699 A>G occurs independently from rs5051 C>T, allowing us to reject the original hypothesis. However, both GTEx and our in vitro experiments suggest rs699 A>G confers cell-type specific effects on AGT mRNA abundance. We found that rs5051 C>T and rs699 A>G significantly associate with systolic blood pressure in Black participants in the UK Biobank, demonstrating a 4-fold larger effect than in White participants. Further studies are warranted to determine if the altered antihypertensive response in Black individuals might be due to rs5051 C>T or rs699 A>G. Studies like this will help clinicians move beyond the use of race as a surrogate for genotype.
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Affiliation(s)
- Nicholas R. Powell
- Indiana University School of Medicine, Department of Medicine, Division of Clinical Pharmacology, Indianapolis IN
| | - Tyler Shugg
- Indiana University School of Medicine, Department of Medicine, Division of Clinical Pharmacology, Indianapolis IN
| | - Jacob Leighty
- Indiana University School of Medicine, Department of Medicine, Division of Clinical Pharmacology, Indianapolis IN
| | - Matthew Martin
- Indiana University School of Medicine, Department of Pharmacology and Toxicology, Indianapolis IN
| | - Rolf P. Kreutz
- Indiana University School of Medicine, Department of Cardiology, Krannert Institute of Cardiology, Indianapolis IN
| | - Michael T. Eadon
- Indiana University School of Medicine, Department of Medicine, Division of Nephrology, Indianapolis IN
- Indiana University School of Medicine, Department of Medical and Molecular Genetics, Indianapolis IN
| | - Dongbing Lai
- Indiana University School of Medicine, Department of Medical and Molecular Genetics, Indianapolis IN
| | - Tao Lu
- Indiana University School of Medicine, Department of Pharmacology and Toxicology, Indianapolis IN
| | - Todd C. Skaar
- Indiana University School of Medicine, Department of Medicine, Division of Clinical Pharmacology, Indianapolis IN
- Indiana University School of Medicine, Department of Medical and Molecular Genetics, Indianapolis IN
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18
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Border S, Lucarelli N, Eadon MT, El-Achkar TM, Jain S, Sarder P. Computational Pathology Fusing Spatial Technologies. Clin J Am Soc Nephrol 2023; 18:01277230-990000000-00103. [PMID: 36913267 PMCID: PMC10278855 DOI: 10.2215/cjn.0000000000000146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 03/06/2023] [Indexed: 03/14/2023]
Affiliation(s)
- Samuel Border
- Department of Biomedical Engineering, University of Florida College of Engineering, Gainesville, Florida
| | - Nicholas Lucarelli
- Department of Biomedical Engineering, University of Florida College of Engineering, Gainesville, Florida
| | - Michael T. Eadon
- Department of Medicine–Division of Nephrology and Hypertension, Indiana University School of Medicine, Indianapolis, Indiana
| | - Tarek M. El-Achkar
- Department of Medicine–Division of Nephrology and Hypertension, Indiana University School of Medicine, Indianapolis, Indiana
| | - Sanjay Jain
- Department of Medicine–Division of Nephrology, Washington University School of Medicine, St. Louis, Missouri
| | - Pinaki Sarder
- Department of Biomedical Engineering, University of Florida College of Engineering, Gainesville, Florida
- Department of Medicine–Quantitative Health, University of Florida College of Medicine, Gainesville, Florida
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, Florida
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19
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Moledina DG, Eadon MT, Calderon F, Yamamoto Y, Shaw M, Perazella MA, Simonov M, Luciano R, Schwantes-An TH, Moeckel G, Kashgarian M, Kuperman M, Obeid W, Cantley LG, Parikh CR, Wilson FP. Development and external validation of a diagnostic model for biopsy-proven acute interstitial nephritis using electronic health record data. Nephrol Dial Transplant 2022; 37:2214-2222. [PMID: 34865148 PMCID: PMC9755995 DOI: 10.1093/ndt/gfab346] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Patients with acute interstitial nephritis (AIN) can present without typical clinical features, leading to a delay in diagnosis and treatment. We therefore developed and validated a diagnostic model to identify patients at risk of AIN using variables from the electronic health record. METHODS In patients who underwent a kidney biopsy at Yale University between 2013 and 2018, we tested the association of >150 variables with AIN, including demographics, comorbidities, vital signs and laboratory tests (training set 70%). We used least absolute shrinkage and selection operator methodology to select prebiopsy features associated with AIN. We performed area under the receiver operating characteristics curve (AUC) analysis with internal (held-out test set 30%) and external validation (Biopsy Biobank Cohort of Indiana). We tested the change in model performance after the addition of urine biomarkers in the Yale AIN study. RESULTS We included 393 patients (AIN 22%) in the training set, 158 patients (AIN 27%) in the test set, 1118 patients (AIN 11%) in the validation set and 265 patients (AIN 11%) in the Yale AIN study. Variables in the selected model included serum creatinine {adjusted odds ratio [aOR] 2.31 [95% confidence interval (CI) 1.42-3.76]}, blood urea nitrogen:creatinine ratio [aOR 0.40 (95% CI 0.20-0.78)] and urine dipstick specific gravity [aOR 0.95 (95% CI 0.91-0.99)] and protein [aOR 0.39 (95% CI 0.23-0.68)]. This model showed an AUC of 0.73 (95% CI 0.64-0.81) in the test set, which was similar to the AUC in the external validation cohort [0.74 (95% CI 0.69-0.79)]. The AUC improved to 0.84 (95% CI 0.76-0.91) upon the addition of urine interleukin-9 and tumor necrosis factor-α. CONCLUSIONS We developed and validated a statistical model that showed a modest AUC for AIN diagnosis, which improved upon the addition of urine biomarkers. Future studies could evaluate this model and biomarkers to identify unrecognized cases of AIN.
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Affiliation(s)
| | - Michael T Eadon
- Indiana University School of Medicine, Indianapolis, IN, USA
| | - Frida Calderon
- Section of Nephrology and Clinical and Translational Research Accelerator, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Yu Yamamoto
- Section of Nephrology and Clinical and Translational Research Accelerator, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Melissa Shaw
- Section of Nephrology and Clinical and Translational Research Accelerator, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Mark A Perazella
- Section of Nephrology and Clinical and Translational Research Accelerator, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Michael Simonov
- Section of Nephrology and Clinical and Translational Research Accelerator, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Randy Luciano
- Section of Nephrology and Clinical and Translational Research Accelerator, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | | | - Gilbert Moeckel
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | | | | | | | - Lloyd G Cantley
- Section of Nephrology and Clinical and Translational Research Accelerator, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
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20
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Eadon MT, Cavanaugh KL, Orlando LA, Christian D, Chakraborty H, Steen-Burrell KA, Merrill P, Seo J, Hauser D, Singh R, Beasley CM, Fuloria J, Kitzman H, Parker AS, Ramos M, Ong HH, Elwood EN, Lynch SE, Clermont S, Cicali EJ, Starostik P, Pratt VM, Nguyen KA, Rosenman MB, Calman NS, Robinson M, Nadkarni GN, Madden EB, Kucher N, Volpi S, Dexter PR, Skaar TC, Johnson JA, Cooper-DeHoff RM, Horowitz CR. Design and rationale of GUARDD-US: A pragmatic, randomized trial of genetic testing for APOL1 and pharmacogenomic predictors of antihypertensive efficacy in patients with hypertension. Contemp Clin Trials 2022; 119:106813. [PMID: 35660539 PMCID: PMC9928488 DOI: 10.1016/j.cct.2022.106813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 05/25/2022] [Accepted: 05/30/2022] [Indexed: 11/28/2022]
Abstract
RATIONALE AND OBJECTIVE APOL1 risk alleles are associated with increased cardiovascular and chronic kidney disease (CKD) risk. It is unknown whether knowledge of APOL1 risk status motivates patients and providers to attain recommended blood pressure (BP) targets to reduce cardiovascular disease. STUDY DESIGN Multicenter, pragmatic, randomized controlled clinical trial. SETTING AND PARTICIPANTS 6650 individuals with African ancestry and hypertension from 13 health systems. INTERVENTION APOL1 genotyping with clinical decision support (CDS) results are returned to participants and providers immediately (intervention) or at 6 months (control). A subset of participants are re-randomized to pharmacogenomic testing for relevant antihypertensive medications (pharmacogenomic sub-study). CDS alerts encourage appropriate CKD screening and antihypertensive agent use. OUTCOMES Blood pressure and surveys are assessed at baseline, 3 and 6 months. The primary outcome is change in systolic BP from enrollment to 3 months in individuals with two APOL1 risk alleles. Secondary outcomes include new diagnoses of CKD, systolic blood pressure at 6 months, diastolic BP, and survey results. The pharmacogenomic sub-study will evaluate the relationship of pharmacogenomic genotype and change in systolic BP between baseline and 3 months. RESULTS To date, the trial has enrolled 3423 participants. CONCLUSIONS The effect of patient and provider knowledge of APOL1 genotype on systolic blood pressure has not been well-studied. GUARDD-US addresses whether blood pressure improves when patients and providers have this information. GUARDD-US provides a CDS framework for primary care and specialty clinics to incorporate APOL1 genetic risk and pharmacogenomic prescribing in the electronic health record. TRIAL REGISTRATION ClinicalTrials.govNCT04191824.
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Affiliation(s)
- Michael T Eadon
- Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | | | - Lori A Orlando
- Duke University School of Medicine, Durham, NC 27720, USA
| | - David Christian
- Institute for Health Equity Research, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Hrishikesh Chakraborty
- Duke University School of Medicine, Durham, NC 27720, USA; Duke Clinical Research Institute, Durham, NC 27720, USA
| | | | - Peter Merrill
- Duke Clinical Research Institute, Durham, NC 27720, USA
| | - Janet Seo
- Institute for Health Equity Research, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Diane Hauser
- Institute for Health Equity Research, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Institute for Family Health, New York, NY 10029, USA
| | - Rajbir Singh
- Meharry Medical College, Nashville, TN 37208, USA
| | - Cherry Maynor Beasley
- McKenzie-Elliott School of Nursing, University of North Carolina at Pembroke, Pembroke, NC 28372, USA
| | - Jyotsna Fuloria
- Office of Research, University Medical Center New Orleans, New Orleans, LA 70112, USA
| | - Heather Kitzman
- Baylor Scott & White Health, Baylor University, Robbins Institute for Health Policy & Leadership, Dallas, TX 75246, USA
| | - Alexander S Parker
- University of Florida College of Medicine - Jacksonville, Jacksonville, FL 32209, USA
| | - Michelle Ramos
- Institute for Health Equity Research, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Henry H Ong
- Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Erica N Elwood
- University of Florida, College of Pharmacy, Gainesville, FL 32610, USA
| | - Sheryl E Lynch
- Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Sabrina Clermont
- Institute for Health Equity Research, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Emily J Cicali
- University of Florida, College of Pharmacy, Gainesville, FL 32610, USA
| | - Petr Starostik
- University of Florida, College of Medicine, Gainesville, FL 32610, USA
| | - Victoria M Pratt
- Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Khoa A Nguyen
- University of Florida, College of Pharmacy, Gainesville, FL 32610, USA
| | - Marc B Rosenman
- Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Neil S Calman
- Institute for Health Equity Research, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Institute for Family Health, New York, NY 10029, USA
| | | | - Girish N Nadkarni
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ebony B Madden
- Division of Genomic Medicine, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Natalie Kucher
- Division of Genomic Medicine, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Simona Volpi
- Division of Genomic Medicine, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Paul R Dexter
- Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Todd C Skaar
- Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Julie A Johnson
- University of Florida, College of Pharmacy, Gainesville, FL 32610, USA
| | | | - Carol R Horowitz
- Institute for Health Equity Research, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
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21
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Gaddy A, Schwantes-An TH, Moorthi RN, Phillips CL, Eadon MT, Moe SM. Incidence and Importance of Calcium Deposition in Kidney Biopsy Specimens. Am J Nephrol 2022; 53:526-533. [PMID: 35871513 PMCID: PMC10503271 DOI: 10.1159/000525647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 06/15/2022] [Indexed: 08/05/2023]
Abstract
INTRODUCTION Calcification on native kidney biopsy specimens is often noted by pathologists, but the consequence is unknown. METHODS We searched the pathology reports in the Biopsy Biobank Cohort of Indiana for native biopsy specimens with calcification. RESULTS Of the 4,364 specimens, 416 (9.8%) had calcification. We compared clinical and histopathology findings in those with calcification (n = 429) compared to those without calcification (n = 3,936). Patients with calcification were older, had more comorbidities, lower estimated glomerular filtration rates (eGFR), were more likely to have hyaline arteriosclerosis, interstitial fibrosis/tubular atrophy, and a primary pathologic diagnosis of acute tubular injury or acute tubular necrosis when compared to patients without calcification. Patients with calcium oxalate deposition alone, compared to calcium phosphate or mixed calcifications, had fewer comorbidities but were more likely to have a history of gastric bypass surgery or malabsorption and take vitamin D. In patients with two or more years of follow-up, multivariate analyses showed the presence of calcification (HR 0.59, 0.38-0.92, p = 0.02) and higher eGFR (HR 0.76, 0.73-0.79, p < 0.001), was associated with decreased likelihood of progressing to end-stage renal disease. The presence of calcification was also associated with a reduced slope/decline in eGFR compared to known biopsy and clinical risk factors for decline in kidney function. We hypothesized this was due to more recoverable acute kidney injury (AKI) and found more severe acute kidney injury network stage in patients with kidney calcification but also greater improvement over time. DISCUSSION/CONCLUSION In summary, we demonstrated that calcification on kidney biopsy specimens was associated with a better prognosis than those without calcification due to the association with recoverable AKI.
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Affiliation(s)
- Anna Gaddy
- Division of Nephrology and Hypertension, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Tae-Hwi Schwantes-An
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Ranjani N. Moorthi
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Carrie L. Phillips
- Department of Pathology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Michael T. Eadon
- Division of Nephrology and Hypertension, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Sharon M. Moe
- Division of Nephrology and Hypertension, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
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22
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Hansen J, Sealfon R, Menon R, Eadon MT, Lake BB, Steck B, Anjani K, Parikh S, Sigdel TK, Zhang G, Velickovic D, Barwinska D, Alexandrov T, Dobi D, Rashmi P, Otto EA, Rivera M, Rose MP, Anderton CR, Shapiro JP, Pamreddy A, Winfree S, Xiong Y, He Y, de Boer IH, Hodgin JB, Barisoni L, Naik AS, Sharma K, Sarwal MM, Zhang K, Himmelfarb J, Rovin B, El-Achkar TM, Laszik Z, He JC, Dagher PC, Valerius MT, Jain S, Satlin LM, Troyanskaya OG, Kretzler M, Iyengar R, Azeloglu EU. A reference tissue atlas for the human kidney. Sci Adv 2022; 8:eabn4965. [PMID: 35675394 PMCID: PMC9176741 DOI: 10.1126/sciadv.abn4965] [Citation(s) in RCA: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 04/20/2022] [Indexed: 05/08/2023]
Abstract
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.
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Affiliation(s)
- Jens Hansen
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rachel Sealfon
- Princeton University, Princeton, NJ, USA
- Flatiron Institute, New York, NY, USA
| | - Rajasree Menon
- University of Michigan School of Medicine, Ann Arbor, MI, USA
| | | | - Blue B. Lake
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Becky Steck
- University of Michigan School of Medicine, Ann Arbor, MI, USA
| | - Kavya Anjani
- University of California San Francisco School of Medicine, San Francisco, CA, USA
| | - Samir Parikh
- Ohio State University College of Medicine, Columbus, OH, USA
| | - Tara K. Sigdel
- University of California San Francisco School of Medicine, San Francisco, CA, USA
| | - Guanshi Zhang
- University of Texas–Health San Antonio School of Medicine, San Antonio, TX, USA
| | | | - Daria Barwinska
- Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Dejan Dobi
- University of California San Francisco School of Medicine, San Francisco, CA, USA
| | - Priyanka Rashmi
- University of California San Francisco School of Medicine, San Francisco, CA, USA
| | - Edgar A. Otto
- University of Michigan School of Medicine, Ann Arbor, MI, USA
| | - Miguel Rivera
- University of California San Francisco School of Medicine, San Francisco, CA, USA
| | - Michael P. Rose
- University of Michigan School of Medicine, Ann Arbor, MI, USA
| | - Christopher R. Anderton
- University of Texas–Health San Antonio School of Medicine, San Antonio, TX, USA
- Pacific Northwest National Laboratory, Richland, WA, USA
| | - John P. Shapiro
- Ohio State University College of Medicine, Columbus, OH, USA
| | - Annapurna Pamreddy
- University of Texas–Health San Antonio School of Medicine, San Antonio, TX, USA
| | - Seth Winfree
- Indiana University School of Medicine, Indianapolis, IN, USA
| | - Yuguang Xiong
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yongqun He
- University of Michigan School of Medicine, Ann Arbor, MI, USA
| | - Ian H. de Boer
- Schools of Medicine and Public Health, University of Washington, Seattle, WA, USA
| | | | | | - Abhijit S. Naik
- University of Michigan School of Medicine, Ann Arbor, MI, USA
| | - Kumar Sharma
- University of Texas–Health San Antonio School of Medicine, San Antonio, TX, USA
| | - Minnie M. Sarwal
- University of California San Francisco School of Medicine, San Francisco, CA, USA
| | - Kun Zhang
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Jonathan Himmelfarb
- Schools of Medicine and Public Health, University of Washington, Seattle, WA, USA
| | - Brad Rovin
- Ohio State University College of Medicine, Columbus, OH, USA
| | | | - Zoltan Laszik
- University of California San Francisco School of Medicine, San Francisco, CA, USA
| | | | | | - M. Todd Valerius
- Brigham and Women’s Hospital, Harvard Medical School, Cambridge, MA, USA
| | - Sanjay Jain
- Washington University in Saint Louis School of Medicine, St. Louis, MS, USA
| | - Lisa M. Satlin
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Olga G. Troyanskaya
- Princeton University, Princeton, NJ, USA
- Flatiron Institute, New York, NY, USA
| | | | - Ravi Iyengar
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Kidney Precision Medicine Project
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Princeton University, Princeton, NJ, USA
- Flatiron Institute, New York, NY, USA
- University of Michigan School of Medicine, Ann Arbor, MI, USA
- Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
- University of California San Francisco School of Medicine, San Francisco, CA, USA
- Ohio State University College of Medicine, Columbus, OH, USA
- University of Texas–Health San Antonio School of Medicine, San Antonio, TX, USA
- Pacific Northwest National Laboratory, Richland, WA, USA
- European Molecular Biology Laboratory, Heidelberg, Germany
- Schools of Medicine and Public Health, University of Washington, Seattle, WA, USA
- Duke University School of Medicine, Durham, NC, USA
- Brigham and Women’s Hospital, Harvard Medical School, Cambridge, MA, USA
- Washington University in Saint Louis School of Medicine, St. Louis, MS, USA
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23
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Abstract
PURPOSE OF REVIEW The application of spatial transcriptomics technologies to the interrogation of kidney tissue is a burgeoning effort. These technologies share a common purpose in mapping both the expression of individual molecules and entire transcriptomic signatures of kidney cell types and structures. Such information is often superimposed upon a histologic image. The resulting datasets are readily merged with other imaging and transcriptomic techniques to establish a spatially anchored atlas of the kidney. This review provides an overview of the various spatial transcriptomic technologies and recent studies in kidney disease. Potential applications gleaned from the interrogation of other organ systems, but relative to the kidney, are also discussed. RECENT FINDINGS Spatial transcriptomic technologies have enabled localization of whole transcriptome mRNA expression, correlation of mRNA to histology, measurement of in situ changes in expression across time, and even subcellular localization of transcripts within the kidney. These innovations continue to aid in the development of human cellular atlases of the kidney, the reclassification of disease, and the identification of important therapeutic targets. SUMMARY Spatial localization of gene expression will complement our current understanding of disease derived from single cell RNA sequencing, histopathology, protein immunofluorescence, and electron microscopy. Although spatial technologies continue to evolve rapidly, their importance in the localization of disease signatures is already apparent. Further efforts are required to integrate whole transcriptome and subcellular expression signatures into the individualized assessment of human kidney disease.
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Affiliation(s)
- Ricardo Melo Ferreira
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis IN, USA
| | - Debora Gisch
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis IN, USA
| | - Michael T. Eadon
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis IN, USA
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24
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Patel J, Torrealba JR, Poggio ED, Bebiak J, Alpers CE, Grewenow SM, Toto RD, Eadon MT. Molecular Signatures of Diabetic Kidney Disease Hiding in a Patient with Hypertension-Related Kidney Disease: A Clinical Pathologic Molecular Correlation. Clin J Am Soc Nephrol 2022; 17:594-601. [PMID: 34911732 PMCID: PMC8993486 DOI: 10.2215/cjn.10350721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
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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Affiliation(s)
- Jiten Patel
- Division of Nephrology, Department of Medicine, University of Texas Southwestern, Dallas, Texas
| | - Jose R. Torrealba
- Department of Pathology, University of Texas Southwestern, Dallas, Texas
| | - Emilio D. Poggio
- Department of Nephrology, Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio
| | - Jack Bebiak
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Charles E. Alpers
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington
| | - Stephanie M. Grewenow
- Kidney Research Institute and Division of Nephrology, University of Washington, Seattle, Washington
| | - Robert D. Toto
- Division of Nephrology, Department of Medicine, University of Texas Southwestern, Dallas, Texas
| | - Michael T. Eadon
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
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25
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Collins KS, Eadon MT, Cheng YH, Barwinska D, Melo Ferreira R, McCarthy TW, Janosevic D, Syed F, Maier B, El-Achkar TM, Kelly KJ, Phillips CL, Hato T, Sutton TA, Dagher PC. Alterations in Protein Translation and Carboxylic Acid Catabolic Processes in Diabetic Kidney Disease. Cells 2022; 11:cells11071166. [PMID: 35406730 PMCID: PMC8997785 DOI: 10.3390/cells11071166] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 03/22/2022] [Accepted: 03/28/2022] [Indexed: 12/27/2022] Open
Abstract
Diabetic kidney disease (DKD) remains the leading cause of end-stage kidney disease despite decades of study. Alterations in the glomerulus and kidney tubules both contribute to the pathogenesis of DKD although the majority of investigative efforts have focused on the glomerulus. We sought to examine the differential expression signature of human DKD in the glomerulus and proximal tubule and corroborate our findings in the db/db mouse model of diabetes. A transcriptogram network analysis of RNAseq data from laser microdissected (LMD) human glomerulus and proximal tubule of DKD and reference nephrectomy samples revealed enriched pathways including rhodopsin-like receptors, olfactory signaling, and ribosome (protein translation) in the proximal tubule of human DKD biopsy samples. The translation pathway was also enriched in the glomerulus. Increased translation in diabetic kidneys was validated using polyribosomal profiling in the db/db mouse model of diabetes. Using single nuclear RNA sequencing (snRNAseq) of kidneys from db/db mice, we prioritized additional pathways identified in human DKD. The top overlapping pathway identified in the murine snRNAseq proximal tubule clusters and the human LMD proximal tubule compartment was carboxylic acid catabolism. Using ultra-performance liquid chromatography–mass spectrometry, the fatty acid catabolism pathway was also found to be dysregulated in the db/db mouse model. The Acetyl-CoA metabolite was down-regulated in db/db mice, aligning with the human differential expression of the genes ACOX1 and ACACB. In summary, our findings demonstrate that proximal tubular alterations in protein translation and carboxylic acid catabolism are key features in both human and murine DKD.
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Affiliation(s)
- Kimberly S. Collins
- Division of Nephrology and Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (K.S.C.); (M.T.E.); (R.M.F.)
| | - Michael T. Eadon
- Division of Nephrology and Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (K.S.C.); (M.T.E.); (R.M.F.)
| | - Ying-Hua Cheng
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (Y.-H.C.); (D.B.); (T.W.M.); (D.J.); (B.M.); (T.M.E.-A.); (K.J.K.); (T.H.)
| | - Daria Barwinska
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (Y.-H.C.); (D.B.); (T.W.M.); (D.J.); (B.M.); (T.M.E.-A.); (K.J.K.); (T.H.)
| | - Ricardo Melo Ferreira
- Division of Nephrology and Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (K.S.C.); (M.T.E.); (R.M.F.)
| | - Thomas W. McCarthy
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (Y.-H.C.); (D.B.); (T.W.M.); (D.J.); (B.M.); (T.M.E.-A.); (K.J.K.); (T.H.)
| | - Danielle Janosevic
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (Y.-H.C.); (D.B.); (T.W.M.); (D.J.); (B.M.); (T.M.E.-A.); (K.J.K.); (T.H.)
| | - Farooq Syed
- Department of Pediatrics and Herman B. Wells Center, Indiana University School of Medicine, Indianapolis, IN 46202, USA;
| | - Bernhard Maier
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (Y.-H.C.); (D.B.); (T.W.M.); (D.J.); (B.M.); (T.M.E.-A.); (K.J.K.); (T.H.)
| | - Tarek M. El-Achkar
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (Y.-H.C.); (D.B.); (T.W.M.); (D.J.); (B.M.); (T.M.E.-A.); (K.J.K.); (T.H.)
| | - Katherine J. Kelly
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (Y.-H.C.); (D.B.); (T.W.M.); (D.J.); (B.M.); (T.M.E.-A.); (K.J.K.); (T.H.)
| | - Carrie L. Phillips
- Department of Pathology, Indiana University School of Medicine, Indianapolis, IN 46202, USA;
| | - Takashi Hato
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (Y.-H.C.); (D.B.); (T.W.M.); (D.J.); (B.M.); (T.M.E.-A.); (K.J.K.); (T.H.)
| | - Timothy A. Sutton
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (Y.-H.C.); (D.B.); (T.W.M.); (D.J.); (B.M.); (T.M.E.-A.); (K.J.K.); (T.H.)
- Correspondence: (T.A.S.); (P.C.D.); Tel.: +1-317-274-7543 (T.A.S.); +1-317-278-2867 (P.C.D.); Fax: 317-274-8575 (T.A.S. & P.C.D.)
| | - Pierre C. Dagher
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (Y.-H.C.); (D.B.); (T.W.M.); (D.J.); (B.M.); (T.M.E.-A.); (K.J.K.); (T.H.)
- Correspondence: (T.A.S.); (P.C.D.); Tel.: +1-317-274-7543 (T.A.S.); +1-317-278-2867 (P.C.D.); Fax: 317-274-8575 (T.A.S. & P.C.D.)
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26
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Abstract
PURPOSE OF REVIEW Traditional histopathology of the kidney biopsy specimen has been an essential and successful tool for the diagnosis and staging of kidney diseases. However, it is likely that the full potential of the kidney biopsy has not been tapped so far. Indeed, there is now a concerted worldwide effort to interrogate kidney biopsy samples at the cellular and molecular levels with unprecedented rigor and depth. This review examines these novel approaches to study kidney biopsy specimens and highlights their potential to refine our understanding of the pathophysiology of kidney disease and lead to precision-based diagnosis and therapy. RECENT FINDINGS Several consortia are now active at studying kidney biopsy samples from various patient cohorts with state-of-the art cellular and molecular techniques. These include advanced imaging approaches as well as deep molecular interrogation with tools such as epigenetics, transcriptomics, proteomics and metabolomics. The emphasis throughout is on rigor, reproducibility and quality control. SUMMARY Although these techniques to study kidney biopsies are complementary, each on its own can yield novel ways to define and classify kidney disease. Therefore, great efforts are needed in order to generate an integrated output that can propel the diagnosis and treatment of kidney disease into the realm of precision medicine.
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Affiliation(s)
- Michael T Eadon
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
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27
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Sabo AR, Winfree S, Bledsoe SB, Phillips CL, Lingeman JE, Eadon MT, Williams JC, El‐Achkar TM. Label-free imaging of non-deparaffinized sections of the human kidney to determine tissue quality and signatures of disease. Physiol Rep 2022; 10:e15167. [PMID: 35133089 PMCID: PMC8822874 DOI: 10.14814/phy2.15167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 12/18/2021] [Accepted: 12/22/2021] [Indexed: 11/24/2022] Open
Abstract
Label-free fluorescence imaging of kidney sections can provide important morphological information, but its utility has not been tested in a histology processing workflow. We tested the feasibility of label-free imaging of paraffin-embedded sections without deparaffinization and its potential usefulness in generating actionable data. Kidney tissue specimens were obtained during percutaneous nephrolithotomy or via diagnostic needle biopsy. Unstained non-deparaffinized sections were imaged using widefield fluorescence microscopy to capture endogenous fluorescence. Some samples were also imaged with confocal microscopy and multiphoton excitation to collect second harmonic generation (SHG) signal to obtain high-quality autofluorescence images with optical sectioning. To adjudicate the label-free signal, the samples or corresponding contiguous sections were subsequently deparaffinized and stained with Lillie's allochrome. Label-free imaging allowed the recognition of various kidney structures and enabled morphological qualification for adequacy. SHG and confocal imaging yielded quantifiable high-quality images for tissue collagens and revealed specific patterns in glomeruli and various tubules. Disease specimens from patients with diabetic kidney disease and focal segmental glomerulosclerosis showed distinctive signatures compared to specimens from healthy controls with normal kidney function. Quantitative cytometry could also be performed when DAPI is added in situ before imaging. These results show that label-free imaging of non-deparaffinized sections provides useful information about tissue quality that could be beneficial to nephropathologists by maximizing the use of scarce kidney tissue. This approach also provides quantifiable features that could inform on the biology of health and disease.
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Affiliation(s)
- Angela R. Sabo
- Department of Anatomy, Cell Biology, and PhysiologyIndiana University School of MedicineIndianapolisIndianaUSA
- Department of MedicineIndiana University School of MedicineIndianapolisIndianaUSA
| | - Seth Winfree
- Department of Pathology and MicrobiologyEppley InstituteUniversity of Nebraska Medical CenterOmahaNebraskaUSA
| | - Sharon B. Bledsoe
- Department of Anatomy, Cell Biology, and PhysiologyIndiana University School of MedicineIndianapolisIndianaUSA
| | - Carrie L. Phillips
- Department of PathologyIndiana University School of MedicineIndianapolisIndianaUSA
| | - James E. Lingeman
- Department of UrologyIndiana University School of MedicineIndianapolisIndianaUSA
| | - Michael T. Eadon
- Department of MedicineIndiana University School of MedicineIndianapolisIndianaUSA
| | - James C. Williams
- Department of Anatomy, Cell Biology, and PhysiologyIndiana University School of MedicineIndianapolisIndianaUSA
| | - Tarek M. El‐Achkar
- Department of Anatomy, Cell Biology, and PhysiologyIndiana University School of MedicineIndianapolisIndianaUSA
- Department of MedicineIndiana University School of MedicineIndianapolisIndianaUSA
- Indianapolis VA Medical CenterIndianapolisIndianaUSA
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28
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Melo Ferreira R, Freije BJ, Eadon MT. Deconvolution Tactics and Normalization in Renal Spatial Transcriptomics. Front Physiol 2022; 12:812947. [PMID: 35095570 PMCID: PMC8793484 DOI: 10.3389/fphys.2021.812947] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 12/02/2021] [Indexed: 01/16/2023] Open
Abstract
The kidney is composed of heterogeneous groups of epithelial, endothelial, immune, and stromal cells, all in close anatomic proximity. Spatial transcriptomic technologies allow the interrogation of in situ expression signatures in health and disease, overlaid upon a histologic image. However, some spatial gene expression platforms have not yet reached single-cell resolution. As such, deconvolution of spatial transcriptomic spots is important to understand the proportion of cell signature arising from these varied cell types in each spot. This article reviews the various deconvolution strategies discussed in the 2021 Indiana O'Brien Center for Microscopy workshop. The unique features of Seurat transfer score methodology, SPOTlight, Robust Cell Type Decomposition, and BayesSpace are reviewed. The application of normalization and batch effect correction across spatial transcriptomic samples is also discussed.
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Affiliation(s)
| | | | - Michael T. Eadon
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, ID, United States
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29
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Eadon MT, Maddatu J, Moe SM, Sinha AD, Melo Ferreira R, Miller BW, Sher SJ, Su J, Pratt VM, Chapman AB, Skaar TC, Moorthi RN. Pharmacogenomics of Hypertension in CKD: The CKD-PGX Study. Kidney360 2021; 3:307-316. [PMID: 35342886 PMCID: PMC8953763 DOI: 10.34067/kid.0005362021] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Background Patients with CKD often have uncontrolled hypertension despite polypharmacy. Pharmacogenomic drug-gene interactions (DGIs) may affect the metabolism or efficacy of antihypertensive agents. We report changes in hypertension control after providing a panel of 11 pharmacogenomic predictors of antihypertensive response. Methods A prospective cohort with CKD and hypertension was followed to assess feasibility of pharmacogenomic testing implementation, self-reported provider utilization, and BP control. The analysis population included 382 subjects with hypertension who were genotyped for cross-sectional assessment of DGIs, and 335 subjects followed for 1 year to assess systolic BP (SBP) and diastolic BP (DBP). Results Most participants (58%) with uncontrolled hypertension had a DGI reducing the efficacy of one or more antihypertensive agents. Subjects with a DGI had 1.85-fold (95% CI, 1.2- to 2.8-fold) higher odds of uncontrolled hypertension, as compared with those without a DGI, adjusted for race, health system (safety-net hospital versus other locations), and advanced CKD (eGFR <30 ml/min). CYP2C9-reduced metabolism genotypes were associated with losartan response and uncontrolled hypertension (odds ratio [OR], 5.2; 95% CI, 1.9 to 14.7). CYP2D6-intermediate or -poor metabolizers had less frequent uncontrolled hypertension compared with normal metabolizers taking metoprolol or carvedilol (OR, 0.55; 95% CI, 0.3 to 0.95). In 335 subjects completing 1-year follow-up, SBP (-4.0 mm Hg; 95% CI, 1.6 to 6.5 mm Hg) and DBP (-3.3 mm Hg; 95% CI, 2.0 to 4.6 mm Hg) were improved. No significant difference in SBP or DBP change were found between individuals with and without a DGI. Conclusions There is a potential role for the addition of pharmacogenomic testing to optimize antihypertensive regimens in patients with CKD.
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Affiliation(s)
- Michael T. Eadon
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana,Richard L. Roudebush Veterans Administration Medical Center, Indianapolis, Indiana
| | - Judith Maddatu
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Sharon M. Moe
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Arjun D. Sinha
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana,Richard L. Roudebush Veterans Administration Medical Center, Indianapolis, Indiana
| | - Ricardo Melo Ferreira
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Brent W. Miller
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - S. Jawad Sher
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Jing Su
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana
| | - Victoria M. Pratt
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | | | - Todd C. Skaar
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
| | - Ranjani N. Moorthi
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
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30
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Melo Ferreira R, Sabo AR, Winfree S, Collins KS, Janosevic D, Gulbronson CJ, Cheng YH, Casbon L, Barwinska D, Ferkowicz MJ, Xuei X, Zhang C, Dunn KW, Kelly KJ, Sutton TA, Hato T, Dagher PC, El-Achkar TM, Eadon MT. Integration of spatial and single-cell transcriptomics localizes epithelial cell-immune cross-talk in kidney injury. JCI Insight 2021; 6:147703. [PMID: 34003797 PMCID: PMC8262485 DOI: 10.1172/jci.insight.147703] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Single-cell sequencing studies have characterized the transcriptomic signature of cell types within the kidney. However, the spatial distribution of acute kidney injury (AKI) is regional and affects cells heterogeneously. We first optimized coordination of spatial transcriptomics and single-nuclear sequencing data sets, mapping 30 dominant cell types to a human nephrectomy. The predicted cell-type spots corresponded with the underlying histopathology. To study the implications of AKI on transcript expression, we then characterized the spatial transcriptomic signature of 2 murine AKI models: ischemia/reperfusion injury (IRI) and cecal ligation puncture (CLP). Localized regions of reduced overall expression were associated with injury pathways. Using single-cell sequencing, we deconvoluted the signature of each spatial transcriptomic spot, identifying patterns of colocalization between immune and epithelial cells. Neutrophils infiltrated the renal medulla in the ischemia model. Atf3 was identified as a chemotactic factor in S3 proximal tubules. In the CLP model, infiltrating macrophages dominated the outer cortical signature, and Mdk was identified as a corresponding chemotactic factor. The regional distribution of these immune cells was validated with multiplexed CO-Detection by indEXing (CODEX) immunofluorescence. Spatial transcriptomic sequencing complemented single-cell sequencing by uncovering mechanisms driving immune cell infiltration and detection of relevant cell subpopulations.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Xiaoling Xuei
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Chi Zhang
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | | | | | | | | | | | | | - Michael T Eadon
- Department of Medicine and.,Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
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31
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de Boer IH, Alpers CE, Azeloglu EU, Balis UGJ, Barasch JM, Barisoni L, Blank KN, Bomback AS, Brown K, Dagher PC, Dighe AL, Eadon MT, El-Achkar TM, Gaut JP, Hacohen N, He Y, Hodgin JB, Jain S, Kellum JA, Kiryluk K, Knight R, Laszik ZG, Lienczewski C, Mariani LH, McClelland RL, Menez S, Moledina DG, Mooney SD, O'Toole JF, Palevsky PM, Parikh CR, Poggio ED, Rosas SE, Rosengart MR, Sarwal MM, Schaub JA, Sedor JR, Sharma K, Steck B, Toto RD, Troyanskaya OG, Tuttle KR, Vazquez MA, Waikar SS, Williams K, Wilson FP, Zhang K, Iyengar R, Kretzler M, Himmelfarb J. Rationale and design of the Kidney Precision Medicine Project. Kidney Int 2021; 99:498-510. [PMID: 33637194 PMCID: PMC8330551 DOI: 10.1016/j.kint.2020.08.039] [Citation(s) in RCA: 78] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 08/08/2020] [Accepted: 08/14/2020] [Indexed: 02/07/2023]
Abstract
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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Affiliation(s)
- Ian H de Boer
- Department of Medicine, University of Washington, Seattle, Washington, USA.
| | - Charles E Alpers
- Department of Pathology, University of Washington, Seattle, Washington, USA
| | - Evren U Azeloglu
- Department of Medicine, Icahn School of Medicine at Mt. Sinai, New York, New York, USA
| | - Ulysses G J Balis
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
| | | | - Laura Barisoni
- Department of Pathology, Duke University, Durham, North Carolina, USA
| | - Kristina N Blank
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Andrew S Bomback
- Department of Medicine, Columbia University, New York, New York, USA
| | - Keith Brown
- Patient Representative, Kidney Precision Medicine Project Steering Committee Member
| | - Pierre C Dagher
- Department of Medicine, Indiana University, Indianapolis, Indiana, USA
| | - Ashveena L Dighe
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Michael T Eadon
- Department of Medicine, Indiana University, Indianapolis, Indiana, USA
| | - Tarek M El-Achkar
- Department of Medicine, Indiana University, Indianapolis, Indiana, USA
| | - Joseph P Gaut
- Department of Pathology, Washington University School of Medicine, St. Louis, St. Louis, Missouri, USA
| | - Nir Hacohen
- Broad Institute, Cambridge, Massachusetts, USA
| | - Yongqun He
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
| | - Jeffrey B Hodgin
- Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
| | - Sanjay Jain
- Department of Medicine, Washington University School of Medicine, St. Louis, St. Louis, Missouri, USA
| | - John A Kellum
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Krzysztof Kiryluk
- Department of Medicine, Columbia University, New York, New York, USA
| | - Richard Knight
- American Association of Kidney Patients, Kidney Precision Medicine Project Patient Partner
| | - Zoltan G Laszik
- Department of Pathology, University of California, San Francisco, San Francisco, California, USA
| | - Chrysta Lienczewski
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Laura H Mariani
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Robyn L McClelland
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Steven Menez
- Department of Medicine, Johns Hopkins Medicine, Baltimore, Maryland, USA
| | - Dennis G Moledina
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Sean D Mooney
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA
| | - John F O'Toole
- Department of Nephrology and Hypertension, Cleveland Clinic, Cleveland, Ohio, USA
| | - Paul M Palevsky
- Renal-Electrolyte Division, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA; Renal Section, Veterans Administration Pittsburgh Healthcare System, Pittsburgh, Pennsylvania, USA
| | - Chirag R Parikh
- Department of Medicine, Johns Hopkins Medicine, Baltimore, Maryland, USA
| | - Emilio D Poggio
- Department of Nephrology and Hypertension, Cleveland Clinic, Cleveland, Ohio, USA
| | | | - Matthew R Rosengart
- Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Minnie M Sarwal
- Department of Surgery, University of California, San Francisco, San Francisco, California, USA
| | - Jennifer A Schaub
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - John R Sedor
- Department of Nephrology and Hypertension, Cleveland Clinic, Cleveland, Ohio, USA
| | - Kumar Sharma
- Department of Medicine, UT Health San Antonio, San Antonio, Texas, USA
| | - Becky Steck
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Robert D Toto
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Olga G Troyanskaya
- Department of Computer Science, Princeton University, Princeton, New Jersey, USA
| | - Katherine R Tuttle
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Miguel A Vazquez
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Sushrut S Waikar
- Department of Medicine, Boston University Medical Center, Boston, Massachusetts, USA
| | - Kayleen Williams
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Francis Perry Wilson
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Kun Zhang
- Institute for Genomic Sciences, University of California, San Diego, California, USA
| | - Ravi Iyengar
- Mount Sinai Institute for Systems Biomedicine, Mount Sinai, New York, New York, USA
| | - Matthias Kretzler
- Renal-Electrolyte Division, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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32
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Schneider TM, Eadon MT, Cooper-DeHoff RM, Cavanaugh KL, Nguyen KA, Arwood MJ, Tillman EM, Pratt VM, Dexter PR, McCoy AB, Orlando LA, Scott SA, Nadkarni GN, Horowitz CR, Kannry JL. Multi-Institutional Implementation of Clinical Decision Support for APOL1, NAT2, and YEATS4 Genotyping in Antihypertensive Management. J Pers Med 2021; 11:jpm11060480. [PMID: 34071920 PMCID: PMC8226809 DOI: 10.3390/jpm11060480] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 05/21/2021] [Accepted: 05/25/2021] [Indexed: 01/13/2023] Open
Abstract
(1) Background: Clinical decision support (CDS) is a vitally important adjunct to the implementation of pharmacogenomic-guided prescribing in clinical practice. A novel CDS was sought for the APOL1, NAT2, and YEATS4 genes to guide optimal selection of antihypertensive medications among the African American population cared for at multiple participating institutions in a clinical trial. (2) Methods: The CDS committee, made up of clinical content and CDS experts, developed a framework and contributed to the creation of the CDS using the following guiding principles: 1. medical algorithm consensus; 2. actionability; 3. context-sensitive triggers; 4. workflow integration; 5. feasibility; 6. interpretability; 7. portability; and 8. discrete reporting of lab results. (3) Results: Utilizing the principle of discrete patient laboratory and vital information, a novel CDS for APOL1, NAT2, and YEATS4 was created for use in a multi-institutional trial based on a medical algorithm consensus. The alerts are actionable and easily interpretable, clearly displaying the purpose and recommendations with pertinent laboratory results, vitals and links to ordersets with suggested antihypertensive dosages. Alerts were either triggered immediately once a provider starts to order relevant antihypertensive agents or strategically placed in workflow-appropriate general CDS sections in the electronic health record (EHR). Detailed implementation instructions were shared across institutions to achieve maximum portability. (4) Conclusions: Using sound principles, the created genetic algorithms were applied across multiple institutions. The framework outlined in this study should apply to other disease-gene and pharmacogenomic projects employing CDS.
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Affiliation(s)
- Thomas M. Schneider
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; (C.R.H.); (J.L.K.)
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Correspondence:
| | - Michael T. Eadon
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (M.T.E.); (E.M.T.); (P.R.D.)
| | - Rhonda M. Cooper-DeHoff
- Center for Pharmacogenetics and Precision Medicine and Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida Gainesville, Gainesville, FL 32610, USA; (R.M.C.-D.); (K.A.N.); (M.J.A.)
- Division of Cardiovascular Medicine, College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Kerri L. Cavanaugh
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
| | - Khoa A. Nguyen
- Center for Pharmacogenetics and Precision Medicine and Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida Gainesville, Gainesville, FL 32610, USA; (R.M.C.-D.); (K.A.N.); (M.J.A.)
| | - Meghan J. Arwood
- Center for Pharmacogenetics and Precision Medicine and Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida Gainesville, Gainesville, FL 32610, USA; (R.M.C.-D.); (K.A.N.); (M.J.A.)
| | - Emma M. Tillman
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (M.T.E.); (E.M.T.); (P.R.D.)
| | - Victoria M. Pratt
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA;
| | - Paul R. Dexter
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (M.T.E.); (E.M.T.); (P.R.D.)
| | - Allison B. McCoy
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
| | - Lori A. Orlando
- Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, 101 Science Drive, Box 3382, Durham, NC 27708, USA;
| | - Stuart A. Scott
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA;
| | - Girish N. Nadkarni
- Department of Nephrology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA;
| | - Carol R. Horowitz
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; (C.R.H.); (J.L.K.)
- Department of Population Health Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Joseph L. Kannry
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; (C.R.H.); (J.L.K.)
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
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Ferkowicz MJ, Winfree S, Sabo AR, Kamocka MM, Khochare S, Barwinska D, Eadon MT, Cheng YH, Phillips CL, Sutton TA, Kelly KJ, Dagher PC, El-Achkar TM, Dunn KW. Large-scale, three-dimensional tissue cytometry of the human kidney: a complete and accessible pipeline. J Transl Med 2021; 101:661-676. [PMID: 33408350 PMCID: PMC8363780 DOI: 10.1038/s41374-020-00518-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 11/05/2020] [Accepted: 11/07/2020] [Indexed: 02/08/2023] Open
Abstract
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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Affiliation(s)
- Michael J Ferkowicz
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Seth Winfree
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Angela R Sabo
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Malgorzata M Kamocka
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Suraj Khochare
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Daria Barwinska
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Michael T Eadon
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Ying-Hua Cheng
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Carrie L Phillips
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Division of Pathology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Timothy A Sutton
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Katherine J Kelly
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Pierre C Dagher
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Tarek M El-Achkar
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
| | - Kenneth W Dunn
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
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34
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Ginsburg GS, Cavallari LH, Chakraborty H, Cooper-DeHoff RM, Dexter PR, Eadon MT, Ferket BS, Horowitz CR, Johnson JA, Kannry J, Kucher N, Madden EB, Orlando LA, Parker W, Peterson J, Pratt VM, Rakhra-Burris TK, Ramos MA, Skaar TC, Sperber N, Steen-Burrell KA, Van Driest SL, Voora D, Wiisanen K, Winterstein AG, Volpi S. Establishing the value of genomics in medicine: the IGNITE Pragmatic Trials Network. Genet Med 2021; 23:1185-1191. [PMID: 33782552 PMCID: PMC8263480 DOI: 10.1038/s41436-021-01118-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 02/01/2021] [Accepted: 02/02/2021] [Indexed: 12/20/2022] Open
Abstract
PURPOSE A critical gap in the adoption of genomic medicine into medical practice is the need for the rigorous evaluation of the utility of genomic medicine interventions. METHODS The Implementing Genomics in Practice Pragmatic Trials Network (IGNITE PTN) was formed in 2018 to measure the clinical utility and cost-effectiveness of genomic medicine interventions, to assess approaches for real-world application of genomic medicine in diverse clinical settings, and to produce generalizable knowledge on clinical trials using genomic interventions. Five clinical sites and a coordinating center evaluated trial proposals and developed working groups to enable their implementation. RESULTS Two pragmatic clinical trials (PCTs) have been initiated, one evaluating genetic risk APOL1 variants in African Americans in the management of their hypertension, and the other to evaluate the use of pharmacogenetic testing for medications to manage acute and chronic pain as well as depression. CONCLUSION IGNITE PTN is a network that carries out PCTs in genomic medicine; it is focused on diversity and inclusion of underrepresented minority trial participants; it uses electronic health records and clinical decision support to deliver the interventions. IGNITE PTN will develop the evidence to support (or oppose) the adoption of genomic medicine interventions by patients, providers, and payers.
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Affiliation(s)
- Geoffrey S Ginsburg
- Duke Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC, USA.
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | | | - Rhonda M Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Paul R Dexter
- School of Medicine, Indiana University, Indianapolis, IN, USA
| | - Michael T Eadon
- Division of Clinical Pharmacology, Indiana University, Indianapolis, IN, USA
| | - Bart S Ferket
- Department of Population Health Science and Policy, Mount Sinai, New York, NY, USA
| | - Carol R Horowitz
- Department of Population Health Science and Policy, Mount Sinai, New York, NY, USA
| | - Julie A Johnson
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Joseph Kannry
- Department of Population Health Science and Policy, Mount Sinai, New York, NY, USA
| | - Natalie Kucher
- Division of Genomic Medicine, National Human Genome Research Institute, NIH, Bethesda, MD, USA
| | - Ebony B Madden
- Division of Genomic Medicine, National Human Genome Research Institute, NIH, Bethesda, MD, USA
| | - Lori A Orlando
- Duke Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC, USA
| | - Wanda Parker
- Duke Clinical Research Institute, Duke University, Durham, NC, USA
| | - Josh Peterson
- Department of Biomedical Informatics, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Victoria M Pratt
- Department of Medical and Molecular Genetics, Indiana University, Indianapolis, IN, USA
| | | | - Michelle A Ramos
- Department of Population Health Science and Policy, Mount Sinai, New York, NY, USA
| | - Todd C Skaar
- Division of Clinical Pharmacology, Indiana University, Indianapolis, IN, USA
| | - Nina Sperber
- Duke Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC, USA.,Department of Population Health Sciences, Duke Margolis Center for Health Policy, Durham VA Health Services Research & Development Service, Duke Center for Applied Genomics & Precision Medicine, Durham, NC, USA
| | | | - Sara L Van Driest
- Department of Pediatrics, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Deepak Voora
- Duke Center for Applied Genomics & Precision Medicine, Duke University, Durham, NC, USA
| | - Kristin Wiisanen
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Almut G Winterstein
- Department of Pharmaceutical Outcomes and Policy, Center for Drug Evaluation and Safety, University of Florida, Gainesville, FL, USA
| | - Simona Volpi
- Division of Genomic Medicine, National Human Genome Research Institute, NIH, Bethesda, MD, USA
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35
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Eadon MT, Lampe S, Baig MM, Collins KS, Melo Ferreira R, Mang H, Cheng YH, Barwinska D, El-Achkar TM, Schwantes-An TH, Winfree S, Temm CJ, Ferkowicz MJ, Dunn KW, Kelly KJ, Sutton TA, Moe SM, Moorthi RN, Phillips CL, Dagher PC. Clinical, histopathologic and molecular features of idiopathic and diabetic nodular mesangial sclerosis in humans. Nephrol Dial Transplant 2021; 37:72-84. [PMID: 33537765 DOI: 10.1093/ndt/gfaa331] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Idiopathic nodular mesangial sclerosis, also called idiopathic nodular glomerulosclerosis (ING), is a rare clinical entity with an unclear pathogenesis. The hallmark of this disease is the presence of nodular mesangial sclerosis on histology without clinical evidence of diabetes mellitus or other predisposing diagnoses. To achieve insights into its pathogenesis, we queried the clinical, histopathologic and transcriptomic features of ING and nodular diabetic nephropathy (DN). METHODS All renal biopsy reports accessioned at Indiana University Health from 2001 to 2016 were reviewed to identify 48 ING cases. Clinical and histopathologic features were compared between individuals with ING and DN (n = 751). Glomeruli of ING (n = 5), DN (n = 18) and reference (REF) nephrectomy (n = 9) samples were isolated by laser microdissection and RNA was sequenced. Immunohistochemistry of proline-rich 36 (PRR36) protein was performed. RESULTS ING subjects were frequently hypertensive (95.8%) with a smoking history (66.7%). ING subjects were older, had lower proteinuria and had less hyaline arteriolosclerosis than DN subjects. Butanoate metabolism was an enriched pathway in ING samples compared with either REF or DN samples. The top differentially expressed gene, PRR36, had increased expression in glomeruli 248-fold [false discovery rate (FDR) P = 5.93 × 10-6] compared with the REF and increased 109-fold (FDR P = 1.85 × 10-6) compared with DN samples. Immunohistochemistry revealed a reduced proportion of cells with perinuclear reaction in ING samples as compared to DN. CONCLUSIONS Despite similar clinical and histopathologic characteristics in ING and DN, the uncovered transcriptomic signature suggests that ING has distinct molecular features from nodular DN. Further study is warranted to understand these relationships.
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Affiliation(s)
- Michael T Eadon
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Sam Lampe
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Mirza M Baig
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kimberly S Collins
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Ricardo Melo Ferreira
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Henry Mang
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Ying-Hua Cheng
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Daria Barwinska
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Tarek M El-Achkar
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Tae-Hwi Schwantes-An
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Seth Winfree
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.,Department of Cellular and Integrative Physiology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Constance J Temm
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Michael J Ferkowicz
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kenneth W Dunn
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Katherine J Kelly
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Timothy A Sutton
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Sharon M Moe
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Ranjani N Moorthi
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Carrie L Phillips
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Pierre C Dagher
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
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36
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Barwinska D, El-Achkar TM, Melo Ferreira R, Syed F, Cheng YH, Winfree S, Ferkowicz MJ, Hato T, Collins KS, Dunn KW, Kelly KJ, Sutton TA, Rovin BH, Parikh SV, Phillips CL, Dagher PC, Eadon MT. Molecular characterization of the human kidney interstitium in health and disease. Sci Adv 2021; 7:7/7/eabd3359. [PMID: 33568476 PMCID: PMC7875540 DOI: 10.1126/sciadv.abd3359] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Accepted: 12/23/2020] [Indexed: 05/23/2023]
Abstract
The gene expression signature of the human kidney interstitium is incompletely understood. The cortical interstitium (excluding tubules, glomeruli, and vessels) in reference nephrectomies (N = 9) and diabetic kidney biopsy specimens (N = 6) was laser microdissected (LMD) and sequenced. Samples underwent RNA sequencing. Gene signatures were deconvolved using single nuclear RNA sequencing (snRNAseq) data derived from overlapping specimens. Interstitial LMD transcriptomics uncovered previously unidentified markers including KISS1, validated with in situ hybridization. LMD transcriptomics and snRNAseq revealed strong correlation of gene expression within corresponding kidney regions. Relevant enriched interstitial pathways included G-protein coupled receptor. binding and collagen biosynthesis. The diabetic interstitium was enriched for extracellular matrix organization and small-molecule catabolism. Cell type markers with unchanged expression (NOTCH3, EGFR, and HEG1) and those down-regulated in diabetic nephropathy (MYH11, LUM, and CCDC3) were identified. LMD transcriptomics complements snRNAseq; together, they facilitate mapping of interstitial marker genes to aid interpretation of pathophysiology in precision medicine studies.
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Affiliation(s)
- Daria Barwinska
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Tarek M El-Achkar
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
- Roudebush Veteran Affairs Medical Center, Indianapolis, IN 46202, USA
- Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Ricardo Melo Ferreira
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Farooq Syed
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Ying-Hua Cheng
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Seth Winfree
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
- Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Michael J Ferkowicz
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Takashi Hato
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Kimberly S Collins
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Kenneth W Dunn
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Katherine J Kelly
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
- Roudebush Veteran Affairs Medical Center, Indianapolis, IN 46202, USA
| | - Timothy A Sutton
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Brad H Rovin
- Division of Nephrology, Department of Medicine, Ohio State University Wexner Medical Center, OH 433210, USA
| | - Samir V Parikh
- Division of Nephrology, Department of Medicine, Ohio State University Wexner Medical Center, OH 433210, USA
| | - Carrie L Phillips
- Division of Pathology, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Pierre C Dagher
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA
- Roudebush Veteran Affairs Medical Center, Indianapolis, IN 46202, USA
| | - Michael T Eadon
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
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37
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Janosevic D, Myslinski J, McCarthy TW, Zollman A, Syed F, Xuei X, Gao H, Liu YL, Collins KS, Cheng YH, Winfree S, El-Achkar TM, Maier B, Melo Ferreira R, Eadon MT, Hato T, Dagher PC. The orchestrated cellular and molecular responses of the kidney to endotoxin define a precise sepsis timeline. eLife 2021; 10:62270. [PMID: 33448928 PMCID: PMC7810465 DOI: 10.7554/elife.62270] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Accepted: 12/13/2020] [Indexed: 12/14/2022] Open
Abstract
Sepsis is a dynamic state that progresses at variable rates and has life-threatening consequences. Staging patients along the sepsis timeline requires a thorough knowledge of the evolution of cellular and molecular events at the tissue level. Here, we investigated the kidney, an organ central to the pathophysiology of sepsis. Single-cell RNA-sequencing in a murine endotoxemia model revealed the involvement of various cell populations to be temporally organized and highly orchestrated. Endothelial and stromal cells were the first responders. At later time points, epithelial cells upregulated immune-related pathways while concomitantly downregulating physiological functions such as solute homeostasis. Sixteen hours after endotoxin, there was global cell–cell communication failure and organ shutdown. Despite this apparent organ paralysis, upstream regulatory analysis showed significant activity in pathways involved in healing and recovery. This rigorous spatial and temporal definition of murine endotoxemia will uncover precise biomarkers and targets that can help stage and treat human sepsis.
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Affiliation(s)
- Danielle Janosevic
- Department of Medicine, Indiana University School of Medicine, Indianapolis, United States
| | - Jered Myslinski
- Department of Medicine, Indiana University School of Medicine, Indianapolis, United States
| | - Thomas W McCarthy
- Department of Medicine, Indiana University School of Medicine, Indianapolis, United States
| | - Amy Zollman
- Department of Medicine, Indiana University School of Medicine, Indianapolis, United States
| | - Farooq Syed
- Department of Pediatrics and the Herman B. Wells Center, Indiana University School of Medicine, Indianapolis, United States
| | - Xiaoling Xuei
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, United States
| | - Hongyu Gao
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, United States
| | - Yun-Long Liu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, United States
| | - Kimberly S Collins
- Department of Medicine, Indiana University School of Medicine, Indianapolis, United States
| | - Ying-Hua Cheng
- Department of Medicine, Indiana University School of Medicine, Indianapolis, United States
| | - Seth Winfree
- Department of Medicine, Indiana University School of Medicine, Indianapolis, United States
| | - Tarek M El-Achkar
- Department of Medicine, Indiana University School of Medicine, Indianapolis, United States.,Roudebush Indianapolis Veterans Affairs Medical Center, Indianapolis, United States
| | - Bernhard Maier
- Department of Medicine, Indiana University School of Medicine, Indianapolis, United States
| | - Ricardo Melo Ferreira
- Department of Medicine, Indiana University School of Medicine, Indianapolis, United States
| | - Michael T Eadon
- Department of Medicine, Indiana University School of Medicine, Indianapolis, United States
| | - Takashi Hato
- Department of Medicine, Indiana University School of Medicine, Indianapolis, United States
| | - Pierre C Dagher
- Department of Medicine, Indiana University School of Medicine, Indianapolis, United States.,Roudebush Indianapolis Veterans Affairs Medical Center, Indianapolis, United States
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38
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Edwards ME, De Luca T, Ferreira CR, Collins KS, Eadon MT, Benson EA, Sobreira TJP, Cooks RG. Multiple reaction monitoring profiling as an analytical strategy to investigate lipids in extracellular vesicles. J Mass Spectrom 2021; 56:e4681. [PMID: 33210411 PMCID: PMC7941191 DOI: 10.1002/jms.4681] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 11/06/2020] [Accepted: 11/09/2020] [Indexed: 06/11/2023]
Abstract
Extracellular vesicles (EVs) convey information used in cell-to-cell interactions. Lipid analysis of EVs remains challenging because of small sample amounts available. Lipid discovery using traditional mass spectrometry platforms based on liquid chromatography and high mass resolution typically employs milligram sample amounts. We report a simple workflow for lipid profiling of EVs based on multiple reaction monitoring (MRM) profiling that uses microgram amounts of sample. After liquid-liquid extraction, individual EV samples were injected directly into the electrospray ionization (ESI) ion source at low flow rates (10 μl/min) and screened for 197 MRM transitions chosen to be a characteristic of several classes of lipids. This choice was based on a discovery experiment, which applied 1,419 MRMs associated with multiple lipid classes to a representative pooled sample. EVs isolated from 12 samples of human lymphocytes and 16 replicates from six different rat cells lines contained an estimated amount of total lipids of 326 to 805 μg. Samples showed profiles that included phosphatidylcholine (PC), sphingomyelin (SM), cholesteryl ester (CE), and ceramide (Cer) lipids, as well as acylcarnitines. The lipid profiles of human lymphocyte EVs were distinguishable using principal component and cluster analysis in terms of prior antibody and drug exposure. Lipid profiles of rat cell lines EV's were distinguishable by their tissue of origin.
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Affiliation(s)
- Madison E Edwards
- Department of Chemistry, Purdue University, West Lafayette, Indiana, 47907, USA
| | - Thomas De Luca
- Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, Indiana, 46202, USA
| | - Christina R Ferreira
- Department of Chemistry, Purdue University, West Lafayette, Indiana, 47907, USA
- Bindley Bioscience Center, Purdue University, West Lafayette, Indiana, 47907, USA
| | - Kimberly S Collins
- Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, Indiana, 46202, USA
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, 46202, USA
| | - Michael T Eadon
- Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, Indiana, 46202, USA
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, 46202, USA
| | - Eric A Benson
- Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, Indiana, 46202, USA
| | - Tiago J P Sobreira
- Bindley Bioscience Center, Purdue University, West Lafayette, Indiana, 47907, USA
| | - Robert Graham Cooks
- Department of Chemistry, Purdue University, West Lafayette, Indiana, 47907, USA
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El-Achkar TM, Eadon MT, Menon R, Lake BB, Sigdel TK, Alexandrov T, Parikh S, Zhang G, Dobi D, Dunn KW, Otto EA, Anderton CR, Carson JM, Luo J, Park C, Hamidi H, Zhou J, Hoover P, Schroeder A, Joanes M, Azeloglu EU, Sealfon R, Winfree S, Steck B, He Y, D’Agati V, Iyengar R, Troyanskaya OG, Barisoni L, Gaut J, Zhang K, Laszik Z, Rovin BH, Dagher PC, Sharma K, Sarwal MM, Hodgin JB, Alpers CE, Kretzler M, Jain S. A multimodal and integrated approach to interrogate human kidney biopsies with rigor and reproducibility: guidelines from the Kidney Precision Medicine Project. Physiol Genomics 2021; 53:1-11. [PMID: 33197228 PMCID: PMC7847045 DOI: 10.1152/physiolgenomics.00104.2020] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
Comprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate three-dimensional (3-D) molecular atlases of healthy and diseased kidney biopsies by using multiple state-of-the-art omics and imaging technologies across several institutions. Obtaining rigorous and reproducible results from disparate methods and at different sites to interrogate biomolecules at a single-cell level or in 3-D space is a significant challenge that can be a futile exercise if not well controlled. We describe a "follow the tissue" pipeline for generating a reliable and authentic single-cell/region 3-D molecular atlas of human adult kidney. Our approach emphasizes quality assurance, quality control, validation, and harmonization across different omics and imaging technologies from sample procurement, processing, storage, shipping to data generation, analysis, and sharing. We established benchmarks for quality control, rigor, reproducibility, and feasibility across multiple technologies through a pilot experiment using common source tissue that was processed and analyzed at different institutions and different technologies. A peer review system was established to critically review quality control measures and the reproducibility of data generated by each technology before their being approved to interrogate clinical biopsy specimens. The process established economizes the use of valuable biopsy tissue for multiomics and imaging analysis with stringent quality control to ensure rigor and reproducibility of results and serves as a model for precision medicine projects across laboratories, institutions and consortia.
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Affiliation(s)
| | | | - Rajasree Menon
- 2University of Michigan School of Medicine, Ann Arbor, Michigan
| | - Blue B. Lake
- 3Jacobs School of Engineering, University of California, San Diego, California
| | - Tara K. Sigdel
- 4University of California San Francisco School of Medicine, San Francisco, California
| | | | - Samir Parikh
- 6Ohio State University College of Medicine, Columbus, Ohio
| | - Guanshi Zhang
- 7UT-Health San Antonio School of Medicine, San Antonio, Texas
| | - Dejan Dobi
- 4University of California San Francisco School of Medicine, San Francisco, California
| | - Kenneth W. Dunn
- 1Indiana University School of Medicine, Indianapolis, Indiana
| | - Edgar A. Otto
- 2University of Michigan School of Medicine, Ann Arbor, Michigan
| | - Christopher R. Anderton
- 7UT-Health San Antonio School of Medicine, San Antonio, Texas,8Pacific Northwest National Laboratory, Richland, Washington
| | - Jonas M. Carson
- 9Schools of Medicine and Public Health, University of Washington, Seattle, Washington
| | - Jinghui Luo
- 2University of Michigan School of Medicine, Ann Arbor, Michigan
| | - Chris Park
- 9Schools of Medicine and Public Health, University of Washington, Seattle, Washington
| | - Habib Hamidi
- 2University of Michigan School of Medicine, Ann Arbor, Michigan
| | - Jian Zhou
- 12Princeton University, Princeton, New Jersey,14Columbia University School of Medicine, New York City, New York
| | - Paul Hoover
- 10Harvard University School of Medicine, Boston Massachusetts
| | - Andrew Schroeder
- 4University of California San Francisco School of Medicine, San Francisco, California
| | - Marianinha Joanes
- 4University of California San Francisco School of Medicine, San Francisco, California
| | | | - Rachel Sealfon
- 12Princeton University, Princeton, New Jersey,14Columbia University School of Medicine, New York City, New York
| | - Seth Winfree
- 1Indiana University School of Medicine, Indianapolis, Indiana
| | - Becky Steck
- 2University of Michigan School of Medicine, Ann Arbor, Michigan
| | - Yongqun He
- 2University of Michigan School of Medicine, Ann Arbor, Michigan
| | - Vivette D’Agati
- 14Columbia University School of Medicine, New York City, New York
| | - Ravi Iyengar
- 11Icahn School of Medicine at Mount Sinai, New York City, New York
| | - Olga G. Troyanskaya
- 12Princeton University, Princeton, New Jersey,14Columbia University School of Medicine, New York City, New York
| | - Laura Barisoni
- 15Duke University School of Medicine, Durham, North Carolina
| | - Joseph Gaut
- 16Washington University in Saint Louis School of Medicine, St. Louis, Missouri
| | - Kun Zhang
- 3Jacobs School of Engineering, University of California, San Diego, California
| | - Zoltan Laszik
- 4University of California San Francisco School of Medicine, San Francisco, California
| | - Brad H. Rovin
- 6Ohio State University College of Medicine, Columbus, Ohio
| | | | - Kumar Sharma
- 7UT-Health San Antonio School of Medicine, San Antonio, Texas
| | - Minnie M. Sarwal
- 4University of California San Francisco School of Medicine, San Francisco, California
| | | | - Charles E. Alpers
- 9Schools of Medicine and Public Health, University of Washington, Seattle, Washington
| | | | - Sanjay Jain
- 16Washington University in Saint Louis School of Medicine, St. Louis, Missouri
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40
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Woloshuk A, Khochare S, Almulhim AF, McNutt AT, Dean D, Barwinska D, Ferkowicz MJ, Eadon MT, Kelly KJ, Dunn KW, Hasan MA, El-Achkar TM, Winfree S. In Situ Classification of Cell Types in Human Kidney Tissue Using 3D Nuclear Staining. Cytometry A 2020; 99:707-721. [PMID: 33252180 DOI: 10.1002/cyto.a.24274] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 10/29/2020] [Accepted: 11/26/2020] [Indexed: 12/30/2022]
Abstract
To understand the physiology and pathology of disease, capturing the heterogeneity of cell types within their tissue environment is fundamental. In such an endeavor, the human kidney presents a formidable challenge because its complex organizational structure is tightly linked to key physiological functions. Advances in imaging-based cell classification may be limited by the need to incorporate specific markers that can link classification to function. Multiplex imaging can mitigate these limitations, but requires cumulative incorporation of markers, which may lead to tissue exhaustion. Furthermore, the application of such strategies in large scale 3-dimensional (3D) imaging is challenging. Here, we propose that 3D nuclear signatures from a DNA stain, DAPI, which could be incorporated in most experimental imaging, can be used for classifying cells in intact human kidney tissue. We developed an unsupervised approach that uses 3D tissue cytometry to generate a large training dataset of nuclei images (NephNuc), where each nucleus is associated with a cell type label. We then devised various supervised machine learning approaches for kidney cell classification and demonstrated that a deep learning approach outperforms classical machine learning or shape-based classifiers. Specifically, a custom 3D convolutional neural network (NephNet3D) trained on nuclei image volumes achieved a balanced accuracy of 80.26%. Importantly, integrating NephNet3D classification with tissue cytometry allowed in situ visualization of cell type classifications in kidney tissue. In conclusion, we present a tissue cytometry and deep learning approach for in situ classification of cell types in human kidney tissue using only a DNA stain. This methodology is generalizable to other tissues and has potential advantages on tissue economy and non-exhaustive classification of different cell types.
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Affiliation(s)
- Andre Woloshuk
- Department of Medicine, Division of Nephrology and Hypertension, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Suraj Khochare
- Department of Medicine, Division of Nephrology and Hypertension, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Aljohara F Almulhim
- Department of Computer Science, Indiana University Purdue University, Indianapolis, Indiana, USA
| | - Andrew T McNutt
- Department of Medicine, Division of Nephrology and Hypertension, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Dawson Dean
- Department of Medicine, Division of Nephrology and Hypertension, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Daria Barwinska
- Department of Medicine, Division of Nephrology and Hypertension, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Michael J Ferkowicz
- Department of Medicine, Division of Nephrology and Hypertension, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Michael T Eadon
- Department of Medicine, Division of Nephrology and Hypertension, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Katherine J Kelly
- Department of Medicine, Division of Nephrology and Hypertension, Indiana University School of Medicine, Indianapolis, Indiana, USA.,Department of Medicine, Indianapolis VA Medical Center, Indianapolis, Indiana, USA
| | - Kenneth W Dunn
- Department of Medicine, Division of Nephrology and Hypertension, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Mohammad A Hasan
- Department of Computer Science, Indiana University Purdue University, Indianapolis, Indiana, USA
| | - Tarek M El-Achkar
- Department of Medicine, Division of Nephrology and Hypertension, Indiana University School of Medicine, Indianapolis, Indiana, USA.,Department of Medicine, Indianapolis VA Medical Center, Indianapolis, Indiana, USA.,Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Seth Winfree
- Department of Medicine, Division of Nephrology and Hypertension, Indiana University School of Medicine, Indianapolis, Indiana, USA.,Department of Medicine, Indianapolis VA Medical Center, Indianapolis, Indiana, USA.,Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, Indiana, USA
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41
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Nguyen KA, Eadon MT, Yoo R, Milway E, Kenneally A, Fekete K, Oh H, Duong K, Whipple EC, Schleyer TK. Risk Factors for Bleeding and Clinical Ineffectiveness Associated With Clopidogrel Therapy: A Comprehensive Meta-Analysis. Clin Transl Sci 2020; 14:645-655. [PMID: 33202084 PMCID: PMC7993261 DOI: 10.1111/cts.12926] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 10/05/2020] [Indexed: 01/13/2023] Open
Abstract
Although clopidogrel is a frequently used antiplatelet medication to treat and prevent atherothrombotic disease, clinicians must balance its clinical effectiveness with the potential side effect of bleeding. However, many previous studies have evaluated beneficial and adverse factors separately. The objective of our study was to perform a comprehensive meta‐analysis of studies of clopidogrel’s clinical effectiveness and/or risk of bleeding in order to identify and assess all reported risk factors, thus helping clinicians to balance patient safety with drug efficacy. We analyzed randomized controlled trials (RCTs) of maintenance use in four stages: search for relevant primary articles; abstract and full article screening; quality assessment and data extraction; and synthesis and data analysis. Screening of 7,109 articles yielded 52 RCTs that met the inclusion criteria. Twenty‐seven risk factors were identified. “Definite risk factors” were defined as those with aggregated odds ratios (ORs) > 1 and confidence intervals (CIs) > 1 if analyzed in more than one study. Definite risk factors for major bleeding were concomitant aspirin use (OR 2.83, 95% CI 2.04–3.94) and long duration of clopidogrel therapy (> 6 months) (OR 1.74, 95% CI 1.21–2.50). Dual antiplatelet therapy, extended clopidogrel therapy, and high maintenance dose (150 mg/day) of clopidogrel were definite risk factors for any bleeding. Reduced renal function, both mild and severe, was the only definite risk factor for clinical ineffectiveness. These findings can help clinicians predict the risks and effectiveness of clopidogrel use for their patients and be used in clinical decision support tools.
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Affiliation(s)
- Khoa A Nguyen
- College of Pharmacy, University of Florida, Gainesville, Florida, USA.,Regenstrief Institute, Indianapolis, Indiana, USA
| | - Michael T Eadon
- School of Medicine, Indiana University, Indianapolis, Indiana, USA
| | - Ryan Yoo
- College of Pharmacy, Purdue University, West Lafayette, Indiana, USA
| | - Evan Milway
- College of Pharmacy, Purdue University, West Lafayette, Indiana, USA
| | - Allison Kenneally
- College of Pharmacy, Purdue University, West Lafayette, Indiana, USA
| | - Kevin Fekete
- College of Pharmacy, Purdue University, West Lafayette, Indiana, USA
| | - Hyun Oh
- College of Pharmacy, Purdue University, West Lafayette, Indiana, USA
| | - Khanh Duong
- College of Pharmacy, Purdue University, West Lafayette, Indiana, USA
| | | | - Titus K Schleyer
- Regenstrief Institute, Indianapolis, Indiana, USA.,School of Medicine, Indiana University, Indianapolis, Indiana, USA
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42
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Ni P, Clinkenbeard EL, Noonan ML, Richardville JM, McClintick J, Hato T, Janosevic D, Cheng YH, El-Achkar TM, Eadon MT, Dagher PC, White KE. Targeting fibroblast growth factor 23-responsive pathways uncovers controlling genes in kidney mineral metabolism. Kidney Int 2020; 99:598-608. [PMID: 33159963 DOI: 10.1016/j.kint.2020.10.024] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Revised: 09/21/2020] [Accepted: 10/09/2020] [Indexed: 12/17/2022]
Abstract
Fibroblast Growth Factor 23 (FGF23) is a bone-derived hormone that reduces kidney phosphate reabsorption and 1,25(OH)2 vitamin D synthesis via its required co-receptor alpha-Klotho. To identify novel genes that could serve as targets to control FGF23-mediated mineral metabolism, gene array and single-cell RNA sequencing were performed in wild type mouse kidneys. Gene array demonstrated that heparin-binding EGF-like growth factor (HBEGF) was significantly up-regulated following one-hour FGF23 treatment of wild type mice. Mice injected with HBEGF had phenotypes consistent with partial FGF23-mimetic activity including robust induction of Egr1, and increased Cyp24a1 mRNAs. Single cell RNA sequencing showed overlapping HBEGF and EGF-receptor expression mostly in the proximal tubule, and alpha-Klotho expression in proximal and distal tubule segments. In alpha-Klotho-null mice devoid of canonical FGF23 signaling, HBEGF injections significantly increased Egr1 and Cyp24a1 with correction of basally elevated Cyp27b1. Additionally, mice placed on a phosphate deficient diet to suppress FGF23 had endogenously increased Cyp27b1 mRNA, which was rescued in mice receiving HBEGF. In HEK293 cells with stable alpha-Klotho expression, FGF23 and HBEGF increased CYP24A1 mRNA expression. HBEGF, but not FGF23 bioactivity was blocked with EGF-receptor inhibition. Thus, our findings support that the paracrine/autocrine factor HBEGF could play novel roles in controlling genes downstream of FGF23 via targeting common signaling pathways.
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Affiliation(s)
- Pu Ni
- Department of Medical and Molecular Genetics, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Erica L Clinkenbeard
- Department of Medical and Molecular Genetics, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Megan L Noonan
- Department of Medical and Molecular Genetics, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Joseph M Richardville
- Department of Medical and Molecular Genetics, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Jeanette McClintick
- Department of Biochemistry and Molecular Biology, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Takashi Hato
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Danielle Janosevic
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ying-Hua Cheng
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Tarek M El-Achkar
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Michael T Eadon
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Pierre C Dagher
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Kenneth E White
- Department of Medical and Molecular Genetics, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA; Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA.
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43
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Collins KS, Raviele ALJ, Elchynski AL, Woodcock AM, Zhao Y, Cooper-DeHoff RM, Eadon MT. Genotype-Guided Hydralazine Therapy. Am J Nephrol 2020; 51:764-776. [PMID: 32927458 DOI: 10.1159/000510433] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Accepted: 07/24/2020] [Indexed: 12/17/2022]
Abstract
BACKGROUND Despite its approval in 1953, hydralazine hydrochloride continues to be used in the management of resistant hypertension, a condition frequently managed by nephrologists and other clinicians. Hydralazine hydrochloride undergoes metabolism by the N-acetyltransferase 2 (NAT2) enzyme. NAT2 is highly polymorphic as approximately 50% of the general population are slow acetylators. In this review, we first evaluate the link between NAT2 genotype and phenotype. We then assess the evidence available for genotype-guided therapy of hydralazine, specifically addressing associations of NAT2 acetylator status with hydralazine pharmacokinetics, antihypertensive efficacy, and toxicity. SUMMARY There is a critical need to use hydralazine in some patients with resistant hypertension. Available evidence supports a significant link between genotype and NAT2 enzyme activity as 29 studies were identified with an overall concordance between genotype and phenotype of 92%. The literature also supports an association between acetylator status and hydralazine concentration, as fourteen of fifteen identified studies revealed significant relationships with a consistent direction of effect. Although fewer studies are available to directly link acetylator status with hydralazine antihypertensive efficacy, the evidence from this smaller set of studies is significant in 7 of 9 studies identified. Finally, 5 studies were identified which support the association of acetylator status with hydralazine-induced lupus. Clinicians should maintain vigilance when prescribing maximum doses of hydralazine. Key Messages: NAT2 slow acetylator status predicts increased hydralazine levels, which may lead to increased efficacy and adverse effects. Caution should be exercised in slow acetylators with total daily hydralazine doses of 200 mg or more. Fast acetylators are at risk for inefficacy at lower doses of hydralazine. With appropriate guidance on the usage of NAT2 genotype, clinicians can adopt a personalized approach to hydralazine dosing and prescription, enabling more efficient and safe treatment of resistant hypertension.
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Affiliation(s)
- Kimberly S Collins
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Anthony L J Raviele
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Amanda L Elchynski
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, Florida, USA
| | - Alexander M Woodcock
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Yang Zhao
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, Florida, USA
| | - Rhonda M Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, Florida, USA
| | - Michael T Eadon
- Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA,
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Barwinska D, Ferkowicz MJ, Cheng YH, Winfree S, Dunn KW, Kelly KJ, Sutton TA, Rovin BH, Parikh SV, Phillips CL, Dagher PC, El-Achkar TM, Eadon MT. Application of Laser Microdissection to Uncover Regional Transcriptomics in Human Kidney Tissue. J Vis Exp 2020. [PMID: 32597856 DOI: 10.3791/61371] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
Gene expression analysis of human kidney tissue is an important tool to understand homeostasis and disease pathophysiology. Increasing the resolution and depth of this technology and extending it to the level of cells within the tissue is needed. Although the use of single nuclear and single cell RNA sequencing has become widespread, the expression signatures of cells obtained from tissue dissociation do not maintain spatial context. Laser microdissection (LMD) based on specific fluorescent markers would allow the isolation of specific structures and cell groups of interest with known localization, thereby enabling the acquisition of spatially-anchored transcriptomic signatures in kidney tissue. We have optimized an LMD methodology, guided by a rapid fluorescence-based stain, to isolate five distinct compartments within the human kidney and conduct subsequent RNA sequencing from valuable human kidney tissue specimens. We also present quality control parameters to enable the assessment of adequacy of the collected specimens. The workflow outlined in this manuscript shows the feasibility of this approach to isolate sub-segmental transcriptomic signatures with high confidence. The methodological approach presented here may also be applied to other tissue types with substitution of relevant antibody markers.
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Affiliation(s)
- Daria Barwinska
- Department of Medicine, Indiana University School of Medicine
| | | | - Ying-Hua Cheng
- Department of Medicine, Indiana University School of Medicine
| | - Seth Winfree
- Department of Medicine, Indiana University School of Medicine; Department of Cellular & Integrative Physiology, Indiana University School of Medicine
| | - Kenneth W Dunn
- Department of Medicine, Indiana University School of Medicine
| | | | | | - Brad H Rovin
- Division of Nephrology, Department of Medicine, Ohio State University Wexner Medical Center
| | - Samir V Parikh
- Division of Nephrology, Department of Medicine, Ohio State University Wexner Medical Center
| | | | - Pierre C Dagher
- Department of Medicine, Indiana University School of Medicine
| | | | - Michael T Eadon
- Department of Medicine, Indiana University School of Medicine;
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45
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Collins KS, Cheng YH, Ferreira RM, Gao H, Dollins MD, Janosevic D, Khan NA, White C, Dagher PC, Eadon MT. Interindividual Variability in Lymphocyte Stimulation and Transcriptomic Response Predicts Mycophenolic Acid Sensitivity in Healthy Volunteers. Clin Transl Sci 2020; 13:1137-1149. [PMID: 32415749 PMCID: PMC7719379 DOI: 10.1111/cts.12795] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 03/23/2020] [Indexed: 11/30/2022] Open
Abstract
Mycophenolic acid (MPA) is an immunosuppressant commonly used to prevent renal transplant rejection and treat glomerulonephritis. MPA inhibits IMPDH2 within stimulated lymphocytes, reducing guanosine synthesis. Despite the widespread use of MPA, interindividual variability in response remains with rates of allograft rejection up to 15% and approximately half of individuals fail to achieve complete remission to lupus nephritis. We sought to identify contributors to interindividual variability in MPA response, hypothesizing that the HPRT1 salvage guanosine synthesis contributes to variability. MPA sensitivity was measured in 40 healthy individuals using an ex vivo lymphocyte viability assay. Measurement of candidate gene expression (n ± 40) and single‐cell RNA‐sequencing (n ± 6) in lymphocytes was performed at baseline, poststimulation, and post‐MPA treatment. After stimulation, HPRT1 expression was 2.1‐fold higher in resistant individuals compared with sensitive individuals (P ± 0.049). Knockdown of HPRT1 increased MPA sensitivity (12%; P ± 0.003), consistent with higher expression levels in resistant individuals. Sensitive individuals had higher IMPDH2 expression and 132% greater stimulation. In lymphocyte subpopulations, differentially expressed genes between sensitive and resistant individuals included KLF2 and LTB. Knockdown of KLF2 and LTB aligned with the predicted direction of effect on proliferation. In sensitive individuals, more frequent receptor‐ligand interactions were observed after stimulation (P ± 0.0004), but fewer interactions remained after MPA treatment (P ± 0.0014). These data identify a polygenic transcriptomic signature in lymphocyte subpopulations predictive of MPA response. The degree of lymphocyte stimulation, HPRT1, KLF2, and LTB expression may serve as markers of MPA efficacy.
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Affiliation(s)
- Kimberly S Collins
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA.,Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ying-Hua Cheng
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ricardo M Ferreira
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA.,Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Hongyu Gao
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Matthew D Dollins
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Danielle Janosevic
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Nida A Khan
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Chloe White
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Pierre C Dagher
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Michael T Eadon
- Department of Medicine, Division of Nephrology, Indiana University School of Medicine, Indianapolis, Indiana, USA.,Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, Indiana, USA
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46
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Eadon MT, Schwantes-An TH, Phillips CL, Roberts AR, Greene CV, Hallab A, Hart KJ, Lipp SN, Perez-Ledezma C, Omar KO, Kelly KJ, Moe SM, Dagher PC, El-Achkar TM, Moorthi RN. Kidney Histopathology and Prediction of Kidney Failure: A Retrospective Cohort Study. Am J Kidney Dis 2020; 76:350-360. [PMID: 32336487 DOI: 10.1053/j.ajkd.2019.12.014] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Accepted: 12/30/2019] [Indexed: 12/30/2022]
Abstract
RATIONALE & OBJECTIVE The use of kidney histopathology for predicting kidney failure is not established. We hypothesized that the use of histopathologic features of kidney biopsy specimens would improve prediction of clinical outcomes made using demographic and clinical variables alone. STUDY DESIGN Retrospective cohort study and development of a clinical prediction model. SETTING & PARTICIPANTS All 2,720 individuals from the Biopsy Biobank Cohort of Indiana who underwent kidney biopsy between 2002 and 2015 and had at least 2 years of follow-up. NEW PREDICTORS & ESTABLISHED PREDICTORS Demographic variables, comorbid conditions, baseline clinical characteristics, and histopathologic features. OUTCOMES Time to kidney failure, defined as sustained estimated glomerular filtration rate ≤ 10mL/min/1.73m2. ANALYTICAL APPROACH Multivariable Cox regression model with internal validation by bootstrapping. Models including clinical and demographic variables were fit with the addition of histopathologic features. To assess the impact of adding a histopathology variable, the amount of variance explained (r2) and the C index were calculated. The impact on prediction was assessed by calculating the net reclassification index for each histopathologic variable and for all combined. RESULTS Median follow-up was 3.1 years. Within 5 years of biopsy, 411 (15.1%) patients developed kidney failure. Multivariable analyses including demographic and clinical variables revealed that severe glomerular obsolescence (adjusted HR, 2.03; 95% CI, 1.51-2.03), severe interstitial fibrosis and tubular atrophy (adjusted HR, 1.99; 95% CI, 1.52-2.59), and severe arteriolar hyalinosis (adjusted HR, 1.53; 95% CI, 1.14-2.05) were independently associated with the primary outcome. The addition of all histopathologic variables to the clinical model yielded a net reclassification index for kidney failure of 5.1% (P < 0.001) with a full model C statistic of 0.915. Analyses addressing the competing risk for death, optimism, or shrinkage did not significantly change the results. LIMITATIONS Selection bias from the use of clinically indicated biopsies and exclusion of patients with less than 2 years of follow-up, as well as reliance on surrogate indicators of kidney failure onset. CONCLUSIONS A model incorporating histopathologic features from kidney biopsy specimens improved prediction of kidney failure and may be valuable clinically. Future studies will be needed to understand whether even more detailed characterization of kidney tissue may further improve prognostication about the future trajectory of estimated glomerular filtration rate.
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Affiliation(s)
- Michael T Eadon
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN.
| | - Tae-Hwi Schwantes-An
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
| | - Carrie L Phillips
- Department of Pathology, Indiana University School of Medicine, Indianapolis, IN
| | - Anna R Roberts
- Regenstrief Institute, Indiana University School of Medicine, Indianapolis, IN
| | - Colin V Greene
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN
| | - Ayman Hallab
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN
| | - Kyle J Hart
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN
| | - Sarah N Lipp
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN
| | | | - Khawaja O Omar
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN
| | - Katherine J Kelly
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN; Indiana University School of Medicine and Roudebush Veterans Administration Medical Center, Indianapolis, IN
| | - Sharon M Moe
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN; Indiana University School of Medicine and Roudebush Veterans Administration Medical Center, Indianapolis, IN
| | - Pierre C Dagher
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN; Indiana University School of Medicine and Roudebush Veterans Administration Medical Center, Indianapolis, IN
| | - Tarek M El-Achkar
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN; Indiana University School of Medicine and Roudebush Veterans Administration Medical Center, Indianapolis, IN
| | - Ranjani N Moorthi
- Division of Nephrology, Indiana University School of Medicine, Indianapolis, IN.
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Spiech KM, Tripathy PR, Woodcock AM, Sheth NA, Collins KS, Kannegolla K, Sinha AD, Sharfuddin AA, Pratt VM, Khalid M, Hains DS, Moe SM, Skaar TC, Moorthi RN, Eadon MT. Implementation of a Renal Precision Medicine Program: Clinician Attitudes and Acceptance. Life (Basel) 2020; 10:life10040032. [PMID: 32224869 PMCID: PMC7235993 DOI: 10.3390/life10040032] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 03/19/2020] [Accepted: 03/20/2020] [Indexed: 12/11/2022] Open
Abstract
A precision health initiative was implemented across a multi-hospital health system, wherein a panel of genetic variants was tested and utilized in the clinical care of chronic kidney disease (CKD) patients. Pharmacogenomic predictors of antihypertensive response and genomic predictors of CKD were provided to clinicians caring for nephrology patients. To assess clinician knowledge, attitudes, and willingness to act on genetic testing results, a Likert-scale survey was sent to and self-administered by these nephrology providers (N = 76). Most respondents agreed that utilizing pharmacogenomic-guided antihypertensive prescribing is valuable (4.0 ± 0.7 on a scale of 1 to 5, where 5 indicates strong agreement). However, the respondents also expressed reluctance to use genetic testing for CKD risk stratification due to a perceived lack of supporting evidence (3.2 ± 0.9). Exploratory sub-group analyses associated this reluctance with negative responses to both knowledge and attitude discipline questions, thus suggesting reduced exposure to and comfort with genetic information. Given the evolving nature of genomic implementation in clinical care, further education is warranted to help overcome these perception barriers.
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Affiliation(s)
- Katherine M. Spiech
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (K.M.S.); (P.R.T.); (A.M.W.); (N.A.S.); (K.S.C.); (K.K.); (A.D.S.); (A.A.S.); (S.M.M.); (T.C.S.); (R.N.M.)
| | - Purnima R. Tripathy
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (K.M.S.); (P.R.T.); (A.M.W.); (N.A.S.); (K.S.C.); (K.K.); (A.D.S.); (A.A.S.); (S.M.M.); (T.C.S.); (R.N.M.)
| | - Alex M. Woodcock
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (K.M.S.); (P.R.T.); (A.M.W.); (N.A.S.); (K.S.C.); (K.K.); (A.D.S.); (A.A.S.); (S.M.M.); (T.C.S.); (R.N.M.)
| | - Nehal A. Sheth
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (K.M.S.); (P.R.T.); (A.M.W.); (N.A.S.); (K.S.C.); (K.K.); (A.D.S.); (A.A.S.); (S.M.M.); (T.C.S.); (R.N.M.)
| | - Kimberly S. Collins
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (K.M.S.); (P.R.T.); (A.M.W.); (N.A.S.); (K.S.C.); (K.K.); (A.D.S.); (A.A.S.); (S.M.M.); (T.C.S.); (R.N.M.)
| | - Karthik Kannegolla
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (K.M.S.); (P.R.T.); (A.M.W.); (N.A.S.); (K.S.C.); (K.K.); (A.D.S.); (A.A.S.); (S.M.M.); (T.C.S.); (R.N.M.)
| | - Arjun D. Sinha
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (K.M.S.); (P.R.T.); (A.M.W.); (N.A.S.); (K.S.C.); (K.K.); (A.D.S.); (A.A.S.); (S.M.M.); (T.C.S.); (R.N.M.)
| | - Asif A. Sharfuddin
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (K.M.S.); (P.R.T.); (A.M.W.); (N.A.S.); (K.S.C.); (K.K.); (A.D.S.); (A.A.S.); (S.M.M.); (T.C.S.); (R.N.M.)
| | - Victoria M. Pratt
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA;
| | - Myda Khalid
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (M.K.); (D.S.H.)
| | - David S. Hains
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (M.K.); (D.S.H.)
| | - Sharon M. Moe
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (K.M.S.); (P.R.T.); (A.M.W.); (N.A.S.); (K.S.C.); (K.K.); (A.D.S.); (A.A.S.); (S.M.M.); (T.C.S.); (R.N.M.)
| | - Todd C. Skaar
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (K.M.S.); (P.R.T.); (A.M.W.); (N.A.S.); (K.S.C.); (K.K.); (A.D.S.); (A.A.S.); (S.M.M.); (T.C.S.); (R.N.M.)
| | - Ranjani N. Moorthi
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (K.M.S.); (P.R.T.); (A.M.W.); (N.A.S.); (K.S.C.); (K.K.); (A.D.S.); (A.A.S.); (S.M.M.); (T.C.S.); (R.N.M.)
| | - Michael T. Eadon
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA; (K.M.S.); (P.R.T.); (A.M.W.); (N.A.S.); (K.S.C.); (K.K.); (A.D.S.); (A.A.S.); (S.M.M.); (T.C.S.); (R.N.M.)
- Correspondence: ; Tel.: 317-274-2502; Fax: 317-274-8575
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Tillman EM, Skaar TC, Eadon MT. Nephrotoxicity in a Patient With Inadequate Pain Control: Potential Role of Pharmacogenetic Testing for Cytochrome P450 2D6 and Apolipoprotein L1. Front Pharmacol 2020; 10:1511. [PMID: 31969823 PMCID: PMC6960206 DOI: 10.3389/fphar.2019.01511] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Accepted: 11/21/2019] [Indexed: 01/13/2023] Open
Abstract
A case is presented which demonstrates the perils of opioid inefficacy and how pharmacogenomic testing may have prevented nonsteroidal anti-inflammatory drug (NSAID)-induced nephrotoxicity and progression to chronic kidney disease (CKD). A 62 year-old female with back pain was treated with tramadol and hydrocodone; however, neither proved effective. Consequently, to control her pain, she resorted to cocaine, marijuana, and high dose nonsteroidal anti-inflammatory drugs (NSAIDs). She eventually developed CKD. To identify CKD contributors, she underwent genotyping for Apolipoprotein L1 (APOL1), a known risk factor of CKD, as well as relevant pharmacogenomic genes. Her APOL1 genotype was *G1(GM)/*G1(GM), placing her at increased risk of CKD progression. Her CYP2D6 genotype was *5/*17, consistent with intermediate metabolism, making opioid drugs reliant on CYP2D6 activation, such as tramadol and hydrocodone, relatively ineffective in this patient. Thus, this patient was at genetic risk for CKD and reduced opioid efficacy. We conclude that this genetic combination likely contributed to opioid inefficacy and the eventual progression to CKD.
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Lin H, Hargreaves KA, Li R, Reiter JL, Wang Y, Mort M, Cooper DN, Zhou Y, Zhang C, Eadon MT, Dolan ME, Ipe J, Skaar TC, Liu Y. RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants. Genome Biol 2019; 20:254. [PMID: 31779641 PMCID: PMC6883696 DOI: 10.1186/s13059-019-1847-4] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Accepted: 10/03/2019] [Indexed: 12/27/2022] Open
Abstract
Single nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure, and evolutionary conservation features. RegSNPs-intron showed excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of RegSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis.
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Affiliation(s)
- Hai Lin
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, 410 West 10th Street, Suite 5000, Indianapolis, IN, 46202, USA
| | - Katherine A Hargreaves
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, 950 W Walnut St, Suite 419, Indianapolis, IN, 46202, USA
| | - Rudong Li
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, 410 West 10th Street, Suite 5000, Indianapolis, IN, 46202, USA
| | - Jill L Reiter
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, 410 West 10th Street, Suite 5000, Indianapolis, IN, 46202, USA
| | - Yue Wang
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, 410 West 10th Street, Suite 5000, Indianapolis, IN, 46202, USA
| | - Matthew Mort
- Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff, CF14 4XN, UK
| | - David N Cooper
- Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff, CF14 4XN, UK
| | - Yaoqi Zhou
- Institute for Glycomics and School of Informatics and Communication Technology, Griffith University, Parklands Dr., Southport, QLD, 4215, Australia
| | - Chi Zhang
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, 410 West 10th Street, Suite 5000, Indianapolis, IN, 46202, USA
| | - Michael T Eadon
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - M Eileen Dolan
- Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, IL, 60637, USA
| | - Joseph Ipe
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, 950 W Walnut St, Suite 419, Indianapolis, IN, 46202, USA
| | - Todd C Skaar
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, 950 W Walnut St, Suite 419, Indianapolis, IN, 46202, USA.
| | - Yunlong Liu
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, 410 West 10th Street, Suite 5000, Indianapolis, IN, 46202, USA.
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Jawed A, Moe SM, Moorthi RN, Torke AM, Eadon MT. Increasing Nephrologist Awareness of Symptom Burden in Older Hospitalized End-Stage Renal Disease Patients. Am J Nephrol 2019; 51:11-16. [PMID: 31743896 DOI: 10.1159/000504333] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 10/21/2019] [Indexed: 11/19/2022]
Abstract
BACKGROUND End-stage renal disease (ESRD) patients have significant symptom burden. Reduced provider awareness of symptoms contributes to underutilization of symptom management resources. METHOD We hypothesized that improved nephrologist awareness of symptoms leads to symptom improvement. In this prospective, multicenter interventional study, 53 (age >65) ESRD inpatients underwent symptom assessment using the modified Edmonton Symptom Assessment System (ESAS) at admission and 1-week post-discharge. Physicians caring for the enrollees were asked if they felt their patients would die within the year, and then sequentially randomized to receive the results of the baseline survey (group 1) or to not receive the results (group 2). RESULTS Fifty-two patients completed the study; 1 died. Baseline characteristics were compared. For 70% of the total cohort, physicians reported that they would not be surprised if their patient died within a year. There was no difference in baseline scores of the patients between the 2 physician groups. Severity ratings were compared between in-hospital and post discharge scores and between physicians who received the results versus those that did not. Total ESAS scores improved more in group 1 (12.9) than in group 2 (9.2; p = 0.04). Among individual symptoms, there was greater improvement in pain control (p = 0.02), and nominal improvement in itching (p = 0.03) in group 1 as compared to group 2. There were 3 palliative care consults. CONCLUSIONS Our findings reinforce the high symptom burden prevalent in older ESRD patients. The improvement in total scores, and individual symptoms of pain and itching in group 1 indicates better symptom control when physician awareness is increased. Residual symptoms post hospitalization and low utilization of palliative care resources are suggestive of a missed opportunity by nephrologists to address the high symptom burden at the inpatient encounter, which is selective for sick patients and/or indication of inadequacy of dialysis to control these symptoms.
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Affiliation(s)
- Areeba Jawed
- Division of Nephrology, Department of Medicine, Wayne State University School of Medicine, Detroit, Michigan, USA,
| | - Sharon M Moe
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ranjani N Moorthi
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Alexis M Torke
- Indiana University Center for Aging Research, Regenstrief Institute, IU School of Medicine, Charles Warren Fairbanks Center for Medical Ethics, IU Health, IU Purdue University Indianapolis Research in Palliative and End of Life Communication and Training Center, Indianapolis, Indiana, USA
| | - Michael T Eadon
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
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