Supplementary Material for: A Targeted Multiomics Approach to Identify Biomarkers Associated with Rapid eGFR Decline in Type 1 Diabetes

  • Christine P. Limonte (Creator)
  • Erkka Valo (Creator)
  • Daniel Montemayor (Creator)
  • Farsad Afshinnia (Creator)
  • Tarunveer S. Ahluwalia (Creator)
  • Tina Costacou (Creator)
  • Manjula Darshi (Creator)
  • Carol Forsblom (Creator)
  • Andrew N. Hoofnagle (Creator)
  • P. H. Groop (Creator)
  • R. Miller (Creator)
  • Trevor J. Orchard (Creator)
  • Subramaniam Pennathur (Creator)
  • Peter Rossing (Creator)
  • Niina Sandholm (Creator)
  • Janet K. Snell-Bergeon (Creator)
  • Hongping Ye (Creator)
  • Jing Zhang (Creator)
  • Loki Natarajan (Creator)
  • Kumar Sharma (Creator)

Dataset

Description

Background: Individuals with type 1 diabetes (T1D) demonstrate varied trajectories of estimated glomerular filtration rate (eGFR) decline. The molecular pathways underlying rapid eGFR decline in T1D are poorly understood, and individual-level risk of rapid eGFR decline is difficult to predict. Methods: We designed a case-control study with multiple exposure measurements nested within 4 well-characterized T1D cohorts (FinnDiane, Steno, EDC, and CACTI) to identify biomarkers associated with rapid eGFR decline. Here, we report the rationale for and design of these studies as well as results of models testing associations of clinical characteristics with rapid eGFR decline in the study population, upon which “omics” studies will be built. Cases (n = 535) and controls (n = 895) were defined as having an annual eGFR decline of ≥3 and
Date made available2020
PublisherKarger Publishers

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