Abstract
BACKGROUND: Unlike the case with creatinine, conditions affecting the non-glomerular filtration rate (GFR) determinants of low-molecular-weight serum proteins, β-trace protein (BTP), β(2)-microglobulin (B2M), and cystatin C, are not well characterized. STUDY DESIGN: Pooled cross-sectional analysis of 3 studies. SETTING & PARTICIPANTS: 3,156 persons with chronic kidney disease from the MDRD (Modification of Diet in Renal Disease) Study, AASK (African American Study of Kidney Disease and Hypertension), and CRIC (Chronic Renal Insufficiency Cohort) Study. PREDICTORS: Demographic and clinical factors hypothesized to be associated with non-GFR determinants of the filtration markers, selected from literature review and physiologic and clinical considerations. OUTCOMES: Serum creatinine, BTP, B2M, and cystatin C levels. RESULTS: In multivariable-adjusted errors-in-variables regression models that included adjustment for measured GFR (mGFR) and mGFR measurement error, creatinine level had stronger associations with male sex, black race, and higher urine creatinine excretion than the other filtration markers. BTP was associated less strongly with age, similar in direction with sex, and opposite in direction with race than creatinine level. Like cystatin C, B2M level was associated less strongly with age, sex, and race than creatinine level. BTP, B2M, and cystatin C levels were associated more strongly than creatinine level with other factors, including urine protein excretion and weight for BTP, smoking and urine protein excretion for B2M, and smoking for cystatin C. LIMITATIONS: Findings may not be generalizable to populations without chronic kidney disease, and residual confounding with GFR due to incomplete adjustment for GFR measurement error. CONCLUSIONS: Like creatinine, serum levels of low-molecular-weight proteins are affected by conditions other than GFR. Knowledge of these conditions can aid the interpretation of GFR estimates and risk using these markers and guide the use of these filtration markers in developing GFR estimating equations.