Comparative CKD risk prediction using homocitrulline and carbamylated albumin: two circulating markers of protein carbamylation.


Journal

BMC nephrology
ISSN: 1471-2369
Titre abrégé: BMC Nephrol
Pays: England
ID NLM: 100967793

Informations de publication

Date de publication:
30 May 2024
Historique:
received: 10 01 2024
accepted: 20 05 2024
medline: 31 5 2024
pubmed: 31 5 2024
entrez: 30 5 2024
Statut: epublish

Résumé

Protein carbamylation, a post-translational protein modification primarily driven by urea, independently associates with adverse clinical outcomes in patients with CKD. Biomarkers used to quantify carbamylation burden have mainly included carbamylated albumin (C-Alb) and homocitrulline (HCit, carbamylated lysine). In this study, we aimed to compare the prognostic utility of these two markers in order to facilitate comparisons of existing studies employing either marker alone, and to inform future carbamylation studies. Both serum C-Alb and free HCit levels were assayed from the same timepoint in 1632 individuals with CKD stages 2-4 enrolled in the prospective Chronic Renal Insufficiency Cohort (CRIC) study. Adjusted Cox proportional hazard models were used to assess risks for the outcomes of death (primary) and end stage kidney disease (ESKD) using each marker. C-statistics, net reclassification improvement, and integrated discrimination improvement were used to compare the prognostic value of each marker. Participant demographics included mean (SD) age 59 (11) years; 702 (43%) females; 700 (43%) white. C-Alb and HCit levels were positively correlated with one another (Pearson correlation coefficient 0.64). Higher C-Alb and HCit levels showed similar increased risk of death (e.g., the adjusted hazard ratio [HR] for death in the 4th carbamylation quartile compared to the 1st was 1.90 (95% confidence interval [CI] 1.35-2.66) for C-Alb, and 1.89 [1.27-2.81] for HCit; and on a continuous scale, the adjusted HR for death using C-Alb was 1.24 [1.11 to 1.39] per standard deviation increase, and 1.27 [1.10-1.46] using HCit). Both biomarkers also had similar HRs for ESKD. The C-statistics were similar when adding each carbamylation biomarker to base models (e.g., for mortality models, the C-statistic was 0.725 [0.707-0.743] with C-Alb and 0.725 [0.707-0.743] with HCit, both compared to a base model 0.723). Similarities were also observed for the net reclassification improvement and integrated discrimination improvement metrics. C-Alb and HCit had similar performance across multiple prognostic assessments. The markers appear readily comparable in CKD epidemiological studies.

Sections du résumé

BACKGROUND BACKGROUND
Protein carbamylation, a post-translational protein modification primarily driven by urea, independently associates with adverse clinical outcomes in patients with CKD. Biomarkers used to quantify carbamylation burden have mainly included carbamylated albumin (C-Alb) and homocitrulline (HCit, carbamylated lysine). In this study, we aimed to compare the prognostic utility of these two markers in order to facilitate comparisons of existing studies employing either marker alone, and to inform future carbamylation studies.
METHODS METHODS
Both serum C-Alb and free HCit levels were assayed from the same timepoint in 1632 individuals with CKD stages 2-4 enrolled in the prospective Chronic Renal Insufficiency Cohort (CRIC) study. Adjusted Cox proportional hazard models were used to assess risks for the outcomes of death (primary) and end stage kidney disease (ESKD) using each marker. C-statistics, net reclassification improvement, and integrated discrimination improvement were used to compare the prognostic value of each marker.
RESULTS RESULTS
Participant demographics included mean (SD) age 59 (11) years; 702 (43%) females; 700 (43%) white. C-Alb and HCit levels were positively correlated with one another (Pearson correlation coefficient 0.64). Higher C-Alb and HCit levels showed similar increased risk of death (e.g., the adjusted hazard ratio [HR] for death in the 4th carbamylation quartile compared to the 1st was 1.90 (95% confidence interval [CI] 1.35-2.66) for C-Alb, and 1.89 [1.27-2.81] for HCit; and on a continuous scale, the adjusted HR for death using C-Alb was 1.24 [1.11 to 1.39] per standard deviation increase, and 1.27 [1.10-1.46] using HCit). Both biomarkers also had similar HRs for ESKD. The C-statistics were similar when adding each carbamylation biomarker to base models (e.g., for mortality models, the C-statistic was 0.725 [0.707-0.743] with C-Alb and 0.725 [0.707-0.743] with HCit, both compared to a base model 0.723). Similarities were also observed for the net reclassification improvement and integrated discrimination improvement metrics.
CONCLUSIONS CONCLUSIONS
C-Alb and HCit had similar performance across multiple prognostic assessments. The markers appear readily comparable in CKD epidemiological studies.

Identifiants

pubmed: 38816682
doi: 10.1186/s12882-024-03619-6
pii: 10.1186/s12882-024-03619-6
doi:

Substances chimiques

Citrulline 29VT07BGDA
homocitrulline 1190-49-4
Biomarkers 0
Serum Albumin 0

Types de publication

Journal Article Comparative Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

185

Subventions

Organisme : NHLBI NIH HHS
ID : R01HL133399
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01DK124453
Pays : United States

Investigateurs

Amanda H Anderson (AH)
Lawrence J Appel (LJ)
Debbie L Cohen (DL)
Laura M Dember (LM)
Alan S Go (AS)
Robert G Nelson (RG)
Mahboob Rahman (M)
Panduranga S Rao (PS)
Vallabh O Shah (VO)
Mark L Unruh (ML)

Informations de copyright

© 2024. The Author(s).

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Auteurs

Aya Awwad (A)

Department of Medicine, Division of Nephrology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

Eugene P Rhee (EP)

Department of Medicine, Division of Nephrology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

Morgan Grams (M)

Department of Medicine, New York University, New York, NY, USA.

Hernan Rincon Choles (HR)

Department of Nephrology, Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH, USA.

James Sondheimer (J)

Department of Medicine, Wayne State University, Detroit, MI, USA.

Jiang He (J)

Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA.

Jing Chen (J)

Department of Medicine, Tulane University School of Medicine, New Orleans, LA, USA.

Chi-Yuan Hsu (CY)

Division of Nephrology, University of California San Francisco School of Medicine, San Francisco, CA, USA.
Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.

Ramachandran S Vasan (RS)

Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA.
Department of Medicine, Sections of Preventive Medicine and Epidemiology and Cardiology, Boston University School of Medicine, Boston, MA, USA.

Paul L Kimmel (PL)

Division of Kidney, Urologic, and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), Bethesda, MD, USA.

Kendra Wulczyn (K)

Department of Medicine, Division of Nephrology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

Anders Berg (A)

Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.

Jim Lash (J)

Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA.

Mengyao Tang (M)

Department of Medicine, Division of Nephrology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

Sahir Kalim (S)

Department of Medicine, Division of Nephrology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. skalim@mgh.harvard.edu.

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