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Van Espen B, Prideaux EB, Wilson AR, Machado CRL, Sendo S, Parker J, Seumois G, Sacchetti C, Belongia AC, Perumal NB, Vijayanand P, Linnik MD, Benschop RJ, Wang W, Bottini N, Firestein GS, Stanford SM. Laser Capture Microscopy RNA Sequencing for Topological Mapping of Synovial Pathology During Rheumatoid Arthritis. Arthritis Rheumatol 2024. [PMID: 38556917 DOI: 10.1002/art.42853] [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: 06/22/2023] [Revised: 02/21/2024] [Accepted: 03/26/2024] [Indexed: 04/02/2024]
Abstract
OBJECTIVE Rheumatoid arthritis (RA) is an autoimmune disease in which the joint lining or synovium becomes highly inflamed and majorly contributes to disease progression. Understanding pathogenic processes in RA synovium is critical for identifying therapeutic targets. We performed laser capture microscopy (LCM) followed by RNA sequencing (LCM-RNAseq) to study regional transcriptomes throughout RA synovium. METHODS Synovial lining, sublining, and vessel samples were captured by LCM from seven patients with RA and seven patients with osteoarthritis (OA). RNAseq was performed on RNA extracted from captured tissue. Principal component analysis was performed on the sample set by disease state. Differential expression analysis was performed between disease states based on log2 fold change and q value parameters. Pathway analysis was performed using the Reactome Pathway Database on differentially expressed genes among disease states. Significantly enriched pathways in each synovial region were selected based on the false discovery rate. RESULTS RA and OA transcriptomes were distinguishable by principal component analysis. Pairwise comparisons of synovial lining, sublining, and vessel samples between RA and OA revealed substantial differences in transcriptional patterns throughout the synovium. Hierarchical clustering of pathways based on significance revealed a pattern of association between biologic function and synovial topology. Analysis of pathways uniquely enriched in each region revealed distinct phenotypic abnormalities. As examples, RA lining samples were marked by anomalous immune cell signaling, RA sublining samples were marked by aberrant cell cycle, and RA vessel samples were marked by alterations in heme scavenging. CONCLUSION LCM-RNAseq confirms reported transcriptional differences between the RA synovium and the OA synovium and provides evidence supporting a relationship between synovial topology and molecular anomalies in RA.
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Affiliation(s)
| | | | | | | | - Sho Sendo
- University of California, San Diego, La Jolla
| | | | | | | | | | | | - Pandurangan Vijayanand
- University of California, San Diego, and La Jolla Institute for Immunology, La Jolla, California
| | | | | | - Wei Wang
- University of California, San Diego, La Jolla
| | - Nunzio Bottini
- University of California, San Diego, La Jolla, and Kao Autoimmunity Institute, Cedars-Sinai Medical Center, Los Angeles, California
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4
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Kwan B, Fuhrer T, Zhang J, Darshi M, Van Espen B, Montemayor D, de Boer IH, Dobre M, Hsu CY, Kelly TN, Raj DS, Rao PS, Saraf SL, Scialla J, Waikar SS, Sharma K, Natarajan L. Metabolomic Markers of Kidney Function Decline in Patients With Diabetes: Evidence From the Chronic Renal Insufficiency Cohort (CRIC) Study. Am J Kidney Dis 2020; 76:511-520. [PMID: 32387023 DOI: 10.1053/j.ajkd.2020.01.019] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [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: 10/08/2019] [Accepted: 01/17/2020] [Indexed: 02/01/2023]
Abstract
RATIONALE & OBJECTIVE Biomarkers that provide reliable evidence of future diabetic kidney disease (DKD) are needed to improve disease management. In a cross-sectional study, we previously identified 13 urine metabolites that had levels reduced in DKD compared with healthy controls. We evaluated associations of these 13 metabolites with future DKD progression. STUDY DESIGN Prospective cohort. SETTING & PARTICIPANTS 1,001 Chronic Renal Insufficiency Cohort (CRIC) participants with diabetes with estimated glomerular filtration rates (eGFRs) between 20 and 70mL/min/1.73m2 were followed up prospectively for a median of 8 (range, 2-10) years. PREDICTORS 13 urine metabolites, age, race, sex, smoked more than 100 cigarettes in lifetime, body mass index, hemoglobin A1c level, blood pressure, urinary albumin, and eGFR. OUTCOMES Annual eGFR slope and time to incident kidney failure with replacement therapy (KFRT; ie, initiation of dialysis or receipt of transplant). ANALYTICAL APPROACH Several clinical metabolite models were developed for eGFR slope as the outcome using stepwise selection and penalized regression, and further tested on the time-to-KFRT outcome. A best cross-validated (final) prognostic model was selected based on high prediction accuracy for eGFR slope and high concordance statistic for incident KFRT. RESULTS During follow-up, mean eGFR slope was-1.83±1.92 (SD) mL/min/1.73m2 per year; 359 (36%) participants experienced KFRT. Median time to KFRT was 7.45 years from the time of entry to the CRIC Study. In our final model, after adjusting for clinical variables, levels of metabolites 3-hydroxyisobutyrate (3-HIBA) and 3-methylcrotonyglycine had a significant negative association with eGFR slope, whereas citric and aconitic acid were positively associated. Further, 3-HIBA and aconitic acid levels were associated with higher and lower risk for KFRT, respectively (HRs of 2.34 [95% CI, 1.51-3.62] and 0.70 [95% CI, 0.51-0.95]). LIMITATIONS Subgroups for whom metabolite signatures may not be optimal, nontargeted metabolomics by flow-injection analysis, and 2-stage modeling approaches. CONCLUSIONS Urine metabolites may offer insights into DKD progression. If replicated in future studies, aconitic acid and 3-HIBA could identify individuals with diabetes at high risk for GFR decline, potentially leading to improved clinical care and targeted therapies.
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Affiliation(s)
- Brian Kwan
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA; Moores Cancer Center, University of California, San Diego, La Jolla, CA
| | - Tobias Fuhrer
- Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Jing Zhang
- Moores Cancer Center, University of California, San Diego, La Jolla, CA
| | - Manjula Darshi
- Center of Renal Precision Medicine, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX
| | | | - Daniel Montemayor
- Center of Renal Precision Medicine, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX
| | - Ian H de Boer
- Department of Medicine, University of Washington, Seattle, WA
| | - Mirela Dobre
- Division of Nephrology and Hypertension, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, OH
| | - Chi-Yuan Hsu
- Department of Medicine, University of California, San Francisco, San Francisco, CA
| | - Tanika N Kelly
- Department of Epidemiology, Tulane University, New Orleans, LA
| | - Dominic S Raj
- Division of Kidney Disease and Hypertension, George Washington University, Washington, DC
| | - Panduranga S Rao
- Department of Medicine, University of Michigan, Ann Arbor, Ann Arbor, MI
| | - Santosh L Saraf
- Department of Medicine, University of Illinois at Chicago, Chicago, IL
| | - Julia Scialla
- Department of Medicine and Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC; Department of Medicine, University of Virginia School of Medicine, Charlottesville, VA; Department of Public Health Sciences, University of Virginia School of Medicine, Charlottesville, VA
| | - Sushrut S Waikar
- Renal Division, Brigham and Women's Hospital, Boston, MA; Renal Section, Boston University Medical Center, Boston, MA
| | - Kumar Sharma
- Center of Renal Precision Medicine, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX.
| | - Loki Natarajan
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA; Moores Cancer Center, University of California, San Diego, La Jolla, CA.
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5
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Garrett-Bakelman FE, Darshi M, Green SJ, Gur RC, Lin L, Macias BR, McKenna MJ, Meydan C, Mishra T, Nasrini J, Piening BD, Rizzardi LF, Sharma K, Siamwala JH, Taylor L, Vitaterna MH, Afkarian M, Afshinnekoo E, Ahadi S, Ambati A, Arya M, Bezdan D, Callahan CM, Chen S, Choi AMK, Chlipala GE, Contrepois K, Covington M, Crucian BE, De Vivo I, Dinges DF, Ebert DJ, Feinberg JI, Gandara JA, George KA, Goutsias J, Grills GS, Hargens AR, Heer M, Hillary RP, Hoofnagle AN, Hook VYH, Jenkinson G, Jiang P, Keshavarzian A, Laurie SS, Lee-McMullen B, Lumpkins SB, MacKay M, Maienschein-Cline MG, Melnick AM, Moore TM, Nakahira K, Patel HH, Pietrzyk R, Rao V, Saito R, Salins DN, Schilling JM, Sears DD, Sheridan CK, Stenger MB, Tryggvadottir R, Urban AE, Vaisar T, Van Espen B, Zhang J, Ziegler MG, Zwart SR, Charles JB, Kundrot CE, Scott GBI, Bailey SM, Basner M, Feinberg AP, Lee SMC, Mason CE, Mignot E, Rana BK, Smith SM, Snyder MP, Turek FW. The NASA Twins Study: A multidimensional analysis of a year-long human spaceflight. Science 2019; 364:364/6436/eaau8650. [PMID: 30975860 DOI: 10.1126/science.aau8650] [Citation(s) in RCA: 399] [Impact Index Per Article: 79.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Accepted: 02/28/2019] [Indexed: 12/11/2022]
Abstract
To understand the health impact of long-duration spaceflight, one identical twin astronaut was monitored before, during, and after a 1-year mission onboard the International Space Station; his twin served as a genetically matched ground control. Longitudinal assessments identified spaceflight-specific changes, including decreased body mass, telomere elongation, genome instability, carotid artery distension and increased intima-media thickness, altered ocular structure, transcriptional and metabolic changes, DNA methylation changes in immune and oxidative stress-related pathways, gastrointestinal microbiota alterations, and some cognitive decline postflight. Although average telomere length, global gene expression, and microbiome changes returned to near preflight levels within 6 months after return to Earth, increased numbers of short telomeres were observed and expression of some genes was still disrupted. These multiomic, molecular, physiological, and behavioral datasets provide a valuable roadmap of the putative health risks for future human spaceflight.
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Affiliation(s)
- Francine E Garrett-Bakelman
- Weill Cornell Medicine, New York, NY, USA.,University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Manjula Darshi
- Center for Renal Precision Medicine, University of Texas Health, San Antonio, TX, USA
| | | | - Ruben C Gur
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ling Lin
- Stanford University School of Medicine, Palo Alto, CA, USA
| | | | | | - Cem Meydan
- Weill Cornell Medicine, New York, NY, USA.,The Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, New York, NY, USA
| | | | - Jad Nasrini
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | | | | | - Kumar Sharma
- Center for Renal Precision Medicine, University of Texas Health, San Antonio, TX, USA
| | | | - Lynn Taylor
- Colorado State University, Fort Collins, CO, USA
| | | | | | - Ebrahim Afshinnekoo
- Weill Cornell Medicine, New York, NY, USA.,The Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, New York, NY, USA
| | - Sara Ahadi
- Stanford University School of Medicine, Palo Alto, CA, USA
| | - Aditya Ambati
- Stanford University School of Medicine, Palo Alto, CA, USA
| | | | - Daniela Bezdan
- Weill Cornell Medicine, New York, NY, USA.,The Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, New York, NY, USA
| | | | - Songjie Chen
- Stanford University School of Medicine, Palo Alto, CA, USA
| | | | | | | | - Marisa Covington
- National Aeronautics and Space Administration (NASA), Houston, TX, USA
| | - Brian E Crucian
- National Aeronautics and Space Administration (NASA), Houston, TX, USA
| | | | - David F Dinges
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | | | | | | | | | | | | | | | | | - Ryan P Hillary
- Stanford University School of Medicine, Palo Alto, CA, USA
| | | | | | | | - Peng Jiang
- Northwestern University, Evanston, IL, USA
| | | | | | | | | | | | | | | | - Tyler M Moore
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | | | - Hemal H Patel
- University of California, San Diego, La Jolla, CA, USA
| | | | - Varsha Rao
- Stanford University School of Medicine, Palo Alto, CA, USA
| | - Rintaro Saito
- University of California, San Diego, La Jolla, CA, USA
| | - Denis N Salins
- Stanford University School of Medicine, Palo Alto, CA, USA
| | | | | | | | - Michael B Stenger
- National Aeronautics and Space Administration (NASA), Houston, TX, USA
| | | | | | | | | | - Jing Zhang
- Stanford University School of Medicine, Palo Alto, CA, USA
| | | | - Sara R Zwart
- University of Texas Medical Branch, Galveston, TX, USA
| | - John B Charles
- National Aeronautics and Space Administration (NASA), Houston, TX, USA.
| | - Craig E Kundrot
- Space Life and Physical Sciences Division, NASA Headquarters, Washington, DC, USA.
| | - Graham B I Scott
- National Space Biomedical Research Institute, Baylor College of Medicine, Houston, TX, USA.
| | | | - Mathias Basner
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.
| | | | | | - Christopher E Mason
- Weill Cornell Medicine, New York, NY, USA. .,The Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, New York, NY, USA.,The Feil Family Brain and Mind Research Institute, New York, NY, USA.,The WorldQuant Initiative for Quantitative Prediction, New York, NY, USA
| | | | - Brinda K Rana
- University of California, San Diego, La Jolla, CA, USA.
| | - Scott M Smith
- National Aeronautics and Space Administration (NASA), Houston, TX, USA.
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Saito R, Rocanin-Arjo A, You YH, Darshi M, Van Espen B, Miyamoto S, Pham J, Pu M, Romoli S, Natarajan L, Ju W, Kretzler M, Nelson R, Ono K, Thomasova D, Mulay SR, Ideker T, D'Agati V, Beyret E, Belmonte JCI, Anders HJ, Sharma K. Systems biology analysis reveals role of MDM2 in diabetic nephropathy. JCI Insight 2016; 1:e87877. [PMID: 27777973 DOI: 10.1172/jci.insight.87877] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
To derive new insights in diabetic complications, we integrated publicly available human protein-protein interaction (PPI) networks with global metabolic networks using metabolomic data from patients with diabetic nephropathy. We focused on the participating proteins in the network that were computationally predicted to connect the urine metabolites. MDM2 had the highest significant number of PPI connections. As validation, significant downregulation of MDM2 gene expression was found in both glomerular and tubulointerstitial compartments of kidney biopsy tissue from 2 independent cohorts of patients with diabetic nephropathy. In diabetic mice, chemical inhibition of MDM2 with Nutlin-3a led to reduction in the number of podocytes, increased blood urea nitrogen, and increased mortality. Addition of Nutlin-3a decreased WT1+ cells in embryonic kidneys. Both podocyte- and tubule-specific MDM2-knockout mice exhibited severe glomerular and tubular dysfunction, respectively. Interestingly, the only 2 metabolites that were reduced in both podocyte and tubule-specific MDM2-knockout mice were 3-methylcrotonylglycine and uracil, both of which were also reduced in human diabetic kidney disease. Thus, our bioinformatics tool combined with multi-omics studies identified an important functional role for MDM2 in glomeruli and tubules of the diabetic nephropathic kidney and links MDM2 to a reduction in 2 key metabolite biomarkers.
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Affiliation(s)
- Rintaro Saito
- Institute of Metabolomic Medicine.,Center for Renal Translational Medicine, Division of Nephrology-Hypertension.,Division of Medical Genetics, Department of Medicine, UCSD, San Diego, California, USA
| | - Anaïs Rocanin-Arjo
- Medizinische Klinik und Poliklinik IV, Klinikum der Universität München, LMU Munich, Munich, Germany
| | - Young-Hyun You
- Center for Renal Translational Medicine, Division of Nephrology-Hypertension.,Division of Medical Genetics, Department of Medicine, UCSD, San Diego, California, USA
| | - Manjula Darshi
- Institute of Metabolomic Medicine.,Division of Medical Genetics, Department of Medicine, UCSD, San Diego, California, USA
| | - Benjamin Van Espen
- Institute of Metabolomic Medicine.,Division of Medical Genetics, Department of Medicine, UCSD, San Diego, California, USA
| | - Satoshi Miyamoto
- Center for Renal Translational Medicine, Division of Nephrology-Hypertension.,Division of Medical Genetics, Department of Medicine, UCSD, San Diego, California, USA
| | - Jessica Pham
- Center for Renal Translational Medicine, Division of Nephrology-Hypertension.,Division of Medical Genetics, Department of Medicine, UCSD, San Diego, California, USA
| | - Minya Pu
- Institute of Metabolomic Medicine.,Department of Family Medicine and Epidemiology, UCSD, San Diego, California, USA
| | - Simone Romoli
- Medizinische Klinik und Poliklinik IV, Klinikum der Universität München, LMU Munich, Munich, Germany
| | - Loki Natarajan
- Institute of Metabolomic Medicine.,Department of Family Medicine and Epidemiology, UCSD, San Diego, California, USA
| | - Wenjun Ju
- Department of Internal Medicine, Nephrology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
| | - Matthias Kretzler
- Department of Internal Medicine, Nephrology and Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
| | - Robert Nelson
- National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, Arizona, USA
| | - Keiichiro Ono
- Division of Medical Genetics, Department of Medicine, UCSD, San Diego, California, USA
| | - Dana Thomasova
- Medizinische Klinik und Poliklinik IV, Klinikum der Universität München, LMU Munich, Munich, Germany
| | - Shrikant R Mulay
- Medizinische Klinik und Poliklinik IV, Klinikum der Universität München, LMU Munich, Munich, Germany
| | - Trey Ideker
- Division of Medical Genetics, Department of Medicine, UCSD, San Diego, California, USA
| | - Vivette D'Agati
- Renal Pathology Laboratory, Columbia University, College of Physicians and Surgeons, Department of Pathology, New York, New York, USA
| | - Ergin Beyret
- Salk Institute for Biological Studies, San Diego, California, USA
| | | | - Hans Joachim Anders
- Medizinische Klinik und Poliklinik IV, Klinikum der Universität München, LMU Munich, Munich, Germany
| | - Kumar Sharma
- Institute of Metabolomic Medicine.,Center for Renal Translational Medicine, Division of Nephrology-Hypertension.,Division of Medical Genetics, Department of Medicine, UCSD, San Diego, California, USA.,Veterans Affairs Health Systems, San Diego, California, USA
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