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Abstract: SA-OR044

Carbamylation and the Risk of CKD Progression in the Chronic Renal Insufficiency Cohort (CRIC)

Session Information

  • Biomarkers in CKD
    November 09, 2019 | Location: 152, Walter E. Washington Convention Center
    Abstract Time: 05:42 PM - 05:54 PM

Category: CKD (Non-Dialysis)

  • 2101 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention

Authors

  • Kalim, Sahir, Massachusetts General Hospital/ Harvard Medical School, Cambridge, Massachusetts, United States
  • Karumanchi, S. Ananth, Cedars-Sinai Medical Center, Los Angeles, Massachusetts, United States
  • Allegretti, Andrew S., Massachusetts General Hospital, Cambridge, Massachusetts, United States
  • Nigwekar, Sagar U., Massachusetts General Hospital, Cambridge, Massachusetts, United States
  • Srivastava, Anand, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States
  • Raj, Dominic S., GWU Medical Faculty Associates, Washington, District of Columbia, United States
  • Frydrych, Anne, University of Illinois at Chicago, Chicago, Illinois, United States
  • Chen, Jing, Tulane School of Medicine, New Orleans, Louisiana, United States
  • Shafi, Tariq, University of Mississippi Medical Center, Jackson, Mississippi, United States
  • Weir, Matthew R., University of Maryland School of Medicine, Baltimore, Maryland, United States
  • Zhao, Sophia, Massachusetts General Hospital, Cambridge, Massachusetts, United States
  • Sondheimer, James H., Wayne State University School of Medicine, Detroit, Michigan, United States
  • Deo, Rajat, University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Thadhani, Ravi I., Cedars-Sinai, Los Angeles, California, United States
  • Lash, James P., University of Illinois at Chicago, Chicago, Illinois, United States
Background

Carbamylation is a posttranslational protein modification caused, in part, by exposure to urea’s dissociation product cyanate. While carbamylation associates with cardiovascular outcomes and mortality in ESRD, its effects in earlier stages of CKD are unknown.

Methods

In 2 independent nested case-control studies within CRIC, we first matched 75 subjects demonstrating CKD progression (cases, 50% reduction of eGFR or reaching ESRD) to 75 people not meeting this definition (controls, matched on baseline eGFR, 24-hour proteinuria, age, sex, and race). Regression models compared baseline levels of carbamylated albumin (C-Alb, a validated measure of total body carbamylation burden) between the groups. With the same matching approach, we next compared baseline C-Alb in 75 subjects who died during follow up (mortality cases) to 75 survivors (mortality controls).

Results

Table 1 shows baseline characteristics of the study groups. Other than urea (CKD progression) and smoking status (both CKD progression and mortality), there was no difference in any matched or other parameter. Adjusting for baseline differences, the top tertile of C-Alb was associated with an increased risk of CKD progression (OR [95% CI] 7.9 [1.9-32.8], P= 0.004) and mortality (OR 3.4 [1.0-11.4], P= 0.05) when compared to the bottom tertile.

Conclusion

In this first report of carbamylation and clinical outcomes in CKD patients not on dialysis, our data suggest carbamylation predicts CKD progression, beyond GFR and proteinuria. Impact on mortality was less robust in this small sample. Additional study is warrented as carbamylation is considered a modifiable risk factor.

Table 1 Select baseline characteristics of the study population
 CKD Progression
Case
CKD Progression
Control
P-valueMortality CaseMortality ControlP-value
Age, y58.4 (9.5)57.6 (9.8)0.6263.7 (7.4)62.6 (8.1)0.41
eGFR (CRIC, ml/min/1.73m^2)33 (22-38)34 (28-39)0.2036 (27-44)34 (26-42)0.51
Proteinuria (g/ 24 hour)1.2 (0.4-3.9)1.0 (0.3-2.4)0.230.3 (0.1-0.8)0.3 (0.1-1.0)0.85
Urea (mg/dL)32 (26-46)30 (24-38)0.0536 (27-46)33 (26-43)0.61
Carbamylated albumin (mmol/mol)6.9 (5.3-9.6)5.02 (4.3-7.1)0.00047.1 (5.4-10.3)6.5 (5.2-8.5)0.52
Current smoking, No. (%)21 (28)9 (12)0.0119 (25)8 (11)0.02

Data are presented as mean (SD), median (interquartile range Q1-Q3)), or count (%) as indicated. No other parameter differed by cases vs. controls across both outcomes.

Funding

  • NIDDK Support