Abstract: FR-PO0532
Associations of Continuous Glucose Monitor Metrics with Biomarkers of Tubular Injury
Session Information
- CKM: Clinical - Trials, Epidemiology, and Biomarkers
October 23, 2026 | Location: Exhibit Hall A, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Cardiovascular-Kidney-Metabolic Health
- 602 Cardiovascular-Kidney-Metabolic Health: Clinical
Authors
- Kiernan, Elizabeth, University of Washington, Seattle, Washington, United States
- Prince, David K., University of Washington, Seattle, Washington, United States
- Limonte, Christine P., University of Washington, Seattle, Washington, United States
- Kestenbaum, Bryan R., University of Washington, Seattle, Washington, United States
- Hoofnagle, Andrew N., University of Washington, Seattle, Washington, United States
- Bhatraju, Pavan K., University of Washington, Seattle, Washington, United States
- Zelnick, Leila R., University of Washington, Seattle, Washington, United States
- Galecki, Andrzej, University of Michigan, Ann Arbor, Michigan, United States
- Hirsch, Irl B., University of Washington, Seattle, Washington, United States
- Shah, Hetal, Joslin Diabetes Center, Boston, Massachusetts, United States
- Mauer, Michael, University of Minnesota Twin Cities, Minneapolis, Minnesota, United States
- Doria, Alessandro, Joslin Diabetes Center, Boston, Massachusetts, United States
- de Boer, Ian, University of Washington, Seattle, Washington, United States
Background
Long-term and sustained glycemic control is the central determinant of kidney and other organ disease in Type 1 Diabetes (T1D). Continuous glucose monitoring (CGM) data identify patterns of glycemic variability that may otherwise not be apparent using hemoglobin A1c measurements. Tubular injury has been increasingly recognized as central to diabetic kidney pathology, though the role of glycemia in this remains poorly understood.
Methods
We evaluated a subset of 153 participants from the Preventing Early Renal Loss in Diabetes (PERL) trial who had biomarker measurements of kidney tubular injury and inflammation and CGM data. CGM metrics were used as predictors including Time In Range (TIR), defined as glucose 70-180mg/dL and coefficient of variation (CV). Outcomes included kidney injury-molecule-1 (KIM-1) and soluble tumor necrosis factor receptor 1 (sTNFR-1) which were measured at baseline, mid-trial and end of trial. Linear mixed-effects models with participant-level random intercepts were used to assess associations between repeated tubular biomarker measurements and participant-level weighted average CGM metrics, with and without a CGM x time interaction term, with adjustments for age, sex, diabetes duration, BMI and treatment assignment.
Results
CGM measurement time ranged from 252-1,671 hours. In cross-sectional analyses, TIR was associated with lower mean biomarkers of KIM-1 and sTNFR-1. Paradoxically, TIR was longitudinally associated with 2% faster annual increase of KIM-1 and 4% faster annual increase of sTNFR-1. At baseline, %CV was not significantly associated with mean level of KIM-1 or sTNFR-1, but longitudinally higher %CV was associated with 3% faster annual increase of KIM-1 and 3% higher annual increase of sTNFR-1 (Table 1).
Conclusion
Higher TIR and implicitly, tighter glycemic control, was associated with lower average levels of sTNFR-1 and KIM-1. The CV was significantly associated with faster rate of rise of KIM-1 and sTNFR-1. These data suggest that CGM metrics may offer additional insight into glycemia and kidney disease progression in populations with T1D.
Table 1. Continuous Glucose Monitoring and Tubular Biomarkers in PERL (n=153)
Funding
- NIDDK Support