Christine P Limonte1,2, Erkka Valo3,4,5, Viktor Drel6,7, Loki Natarajan8, Manjula Darshi6,7, Carol Forsblom3,4,5, Clark M Henderson9, Andrew N Hoofnagle2,9,10, Wenjun Ju11,12, Matthias Kretzler11,12, Daniel Montemayor6,7, Viji Nair11, Robert G Nelson13, John F O'Toole14, Robert D Toto15, Sylvia E Rosas16, John Ruzinski1,2, Niina Sandholm3,4,5, Insa M Schmidt17, Tomas Vaisar10, Sushrut S Waikar17, Jing Zhang8, Peter Rossing18,19, Tarunveer S Ahluwalia18,19,20, Per-Henrik Groop3,4,5, Subramaniam Pennathur21,22, Janet K Snell-Bergeon23, Tina Costacou24, Trevor J Orchard24, Kumar Sharma6,7, Ian H de Boer1,2. 1. Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA. 2. Kidney Research Institute, University of Washington, Seattle, WA. 3. Folkhälsan Institute of Genetics, Folkhälsan Research Center, Helsinki, Finland. 4. Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland. 5. Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland. 6. Division of Nephrology, The University of Texas Health Science Center at San Antonio, San Antonio, TX. 7. Center for Renal Precision Medicine, Division of Nephrology, Department of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, TX. 8. Division of Biostatistics and Bioinformatics, Department of Family Medicine and Public Health and Moores Cancer Center at UC San Diego Health, La Jolla, CA. 9. Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA. 10. Division of Metabolism, Endocrinology, and Nutrition, UW Medicine Diabetes Institute, University of Washington, Seattle, WA. 11. Division of Nephrology, University of Michigan, Ann Arbor, MI. 12. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI. 13. Chronic Kidney Disease Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ. 14. Department of Nephrology and Hypertension, Cleveland Clinic, Cleveland, OH. 15. Department of Internal Medicine, The University of Texas Southwestern Medical Center, Dallas, TX. 16. Joslin Diabetes Center, Boston, MA. 17. Section of Nephrology, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Boston, MA. 18. Steno Diabetes Center Copenhagen, Gentofte, Denmark. 19. Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark. 20. The Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark. 21. Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI. 22. Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI. 23. Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO. 24. University of Pittsburgh, Pittsburgh, PA.
Abstract
OBJECTIVE: Understanding mechanisms underlying rapid estimated glomerular filtration rate (eGFR) decline is important to predict and treat kidney disease in type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: We performed a case-control study nested within four T1D cohorts to identify urinary proteins associated with rapid eGFR decline. Case and control subjects were categorized based on eGFR decline ≥3 and <1 mL/min/1.73 m2/year, respectively. We used targeted liquid chromatography-tandem mass spectrometry to measure 38 peptides from 20 proteins implicated in diabetic kidney disease. Significant proteins were investigated in complementary human cohorts and in mouse proximal tubular epithelial cell cultures. RESULTS: The cohort study included 1,270 participants followed a median 8 years. In the discovery set, only cathepsin D peptide and protein were significant on full adjustment for clinical and laboratory variables. In the validation set, associations of cathepsin D with eGFR decline were replicated in minimally adjusted models but lost significance with adjustment for albuminuria. In a meta-analysis with combination of discovery and validation sets, the odds ratio for the association of cathepsin D with rapid eGFR decline was 1.29 per SD (95% CI 1.07-1.55). In complementary human cohorts, urine cathepsin D was associated with tubulointerstitial injury and tubulointerstitial cathepsin D expression was associated with increased cortical interstitial fractional volume. In mouse proximal tubular epithelial cell cultures, advanced glycation end product-BSA increased cathepsin D activity and inflammatory and tubular injury markers, which were further increased with cathepsin D siRNA. CONCLUSIONS: Urine cathepsin D is associated with rapid eGFR decline in T1D and reflects kidney tubulointerstitial injury.
OBJECTIVE: Understanding mechanisms underlying rapid estimated glomerular filtration rate (eGFR) decline is important to predict and treat kidney disease in type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: We performed a case-control study nested within four T1D cohorts to identify urinary proteins associated with rapid eGFR decline. Case and control subjects were categorized based on eGFR decline ≥3 and <1 mL/min/1.73 m2/year, respectively. We used targeted liquid chromatography-tandem mass spectrometry to measure 38 peptides from 20 proteins implicated in diabetic kidney disease. Significant proteins were investigated in complementary human cohorts and in mouse proximal tubular epithelial cell cultures. RESULTS: The cohort study included 1,270 participants followed a median 8 years. In the discovery set, only cathepsin D peptide and protein were significant on full adjustment for clinical and laboratory variables. In the validation set, associations of cathepsin D with eGFR decline were replicated in minimally adjusted models but lost significance with adjustment for albuminuria. In a meta-analysis with combination of discovery and validation sets, the odds ratio for the association of cathepsin D with rapid eGFR decline was 1.29 per SD (95% CI 1.07-1.55). In complementary human cohorts, urine cathepsin D was associated with tubulointerstitial injury and tubulointerstitial cathepsin D expression was associated with increased cortical interstitial fractional volume. In mouse proximal tubular epithelial cell cultures, advanced glycation end product-BSA increased cathepsin D activity and inflammatory and tubular injury markers, which were further increased with cathepsin D siRNA. CONCLUSIONS: Urine cathepsin D is associated with rapid eGFR decline in T1D and reflects kidney tubulointerstitial injury.
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Authors: Farsad Afshinnia; Thekkelnaycke M Rajendiran; Chenchen He; Jaeman Byun; Daniel Montemayor; Manjula Darshi; Jana Tumova; Jiwan Kim; Christine P Limonte; Rachel G Miller; Tina Costacou; Trevor J Orchard; Tarunveer S Ahluwalia; Peter Rossing; Janet K Snell-Bergeon; Ian H de Boer; Loki Natarajan; George Michailidis; Kumar Sharma; Subramaniam Pennathur Journal: Diabetes Care Date: 2021-07-08 Impact factor: 17.152