MSACL 2025 Abstract

The Role of Measurement Science in Standardizing Clinical Urine Albumin Results for Kidney Disease

Ashley Beasley-Green
National Institute of Standards and Technology (NIST), Gaithersburg, MD

Ashley Beasley-Green, PhD (Presenter) NIST

Presenter Bio: Ashley Beasley-Green, PhD, received her BS in Biochemistry from Spelman College and obtained her PhD from the Department of Pharmacology and Molecular Sciences at The Johns Hopkins University School of Medicine. Dr. Green received a National Research Council Postdoctoral Fellowship at the National Institute of Standards and Technology (NIST) and is currently a Staff Scientist in the Biomolecular Measurement Division of the Materials Measurement Laboratory (MML) at NIST. Dr. Green’s research primarily focuses on the standardization of protein measurement science and the development of protein-based NIST Reference Materials and Standard Reference Materials to support basic research and clinical applications.

Relevant Financial Disclosures (within past 24 months, reported on Jan 14, 2026) No relevant financial relationship(s) to disclose.

INTRODUCTION:
The accuracy and consistency of clinical urine albumin results significantly influence the decisions made by healthcare practitioners regarding the diagnosis and treatment of kidney disease. It is essential for healthcare practitioners to have access to reliable and comparable results, which can be achieved through the standardization of clinical urine albumin results. When clinical urine albumin results are standardized, the result is independent of the methods or laboratories used. Standardization can be accomplished by establishing a reference measurement system for urine albumin. The reference measurement system serves as a traceability framework of reference materials and reference measurement procedures that creates a link between clinical urine albumin results and the International System of Units (SI).

OBJECTIVE(S):
The primary objective of this study was to establish a traceability framework that links fundamental units of measure to clinical urine albumin results.

METHODS:
To address urine albumin measurement accuracy and precision, several foundational components were developed: a multiplexed reference measurement procedure (RMP) that utilizes isotope dilution-mass spectrometry (ID-MS) and multiple reaction monitoring (MRM) to quantify urine albumin; a primary reference material to be used as a calibrator for higher-order urine albumin methods; and a matrix-based secondary reference material.

RESULTS:
The multiplexed RMP for urine albumin incorporates an isotopically labeled (15N) full-length recombinant human serum albumin (15N-rHSA) internal standard, which enables the absolute quantitation of albumin in human urine. Eleven peptides were selected from the tryptic digestion of HSA, with two transitions per peptide (23 MRM transitions), based on factors such as retention time reproducibility, peak intensity, and the extent of HSA sequence coverage. Calibration of the NIST RMP is traceable to the SI through the use of the primary calibrator (NIST SRM 2925), a highly characterized unlabeled recombinant HSA. A statistical approach was implemented to define and establish the measurement uncertainty of the NIST RMP. This methodology represents the first attempt to estimate the measurement uncertainty for an MS-based procedure aimed at the absolute quantification of a protein biomarker. The NIST RMP is utilized for the value assignment of albumin in human urine samples and the matrix-based secondary reference material, NIST SRM 3666 Albumin and Creatinine in Frozen Human Urine. NIST SRM 3666 is a four-level human urine material intended for use as a secondary reference material to support the accuracy and comparability of clinical urine albumin results.

CONCLUSION:
To enhance the quality and accuracy of routine clinical measurements of urine albumin, we have developed the foundational components of the urine albumin reference measurement system and utilized a statistical approach to establish measurement uncertainty of an MS-based quantitative proteomics method. Improving the quality and accuracy of urine albumin results will ultimately enhance confidence in clinical decisions for kidney disease.