= Emerging. More than 5 years before clinical availability. (16.60%, 2024)
= Expected to be clinically available in 1 to 4 years. (37.02%, 2024)
= Clinically available now. (46.38%, 2024)
MSACL 2024 : Gill

MSACL 2024 Abstract

Self-Classified Topic Area(s): Proteomics > Emerging Technologies > Assays Leveraging Technology

Podium Presentation in Steinbeck 2 on Thursday at 15:05 (Chair: Nicolás Morato)

Rapid Clinical Albuminuria Diagnostics Using Paper Spray Mass Spectrometry: High Throughput ACr Measurements and Non-Targeted Approaches Utilizing Machine Learning

Igor Pereira (1), Jindar N. S. Sboto (1), Jason L. Robinson (2), and Chris G. Gill (1, 3, 4, 5)
(1) Applied Environmental Research Laboratories (AERL), Chemistry Department, Vancouver Island University, Nanaimo, BC, Canada (2) Health PEI, Charlottetown, PEI, Canada (3) Chemistry Department, University of Victoria, Victoria, BC, Canada (4) Chemistry Department, Simon Fraser University, Burnaby, BC, Canada (5) Department of Occupational and Environmental Health Sciences, University of Washington, Seattle, WA, United States

Chris Gill, Ph.D. (Presenter)
Vancouver Island University

Presenter Bio: Chris is a Chemistry Professor at Vancouver Island University (Nanaimo, BC) as well as co-director of the Applied Environmental Research Laboratories (AERL). He maintains an active international collaboration network, including the tenure of visiting professorships during sabbaticals in Germany and Italy. He has been awarded the Distinguished Researcher Award at VIU, a Distinguished Chemistry Alumni Award at the University of British Columbia, and has recently moved his laboratories into expanded space in the recently completed VIU Health and Sciences Centre. The AERL conducts pure & applied research, with a central theme the development of direct, online mass spectrometry methods for measurements in complex samples. This has lead to numerous advances for direct environmental, industrial and clinical/bioanalytical measurements. The AERL’s development of mobilized direct mass spectrometry platforms for geospatially resolved quantitative environmental measurements as well as numerous hyphenated methodologies has transformed capacity for in field chemical determinations. Chris’ current research interests continue to involve the development of direct mass spectrometry instrumentation and their applications for direct, real-time chemical measurements. This includes high precision systems and approaches for improved environmental monitoring, clinical diagnostics, forensic testing, and the development and implementation of rapid, on-site drug testing strategies for use in the opioid overdose crisis.


INTRODUCTION: The applications of direct mass spectrometry strategies such as paper spray mass spectrometry (PS-MS) offer new alternatives to increase throughput in clinical workflows. In PS-MS, direct, measurements in complex samples such as biofluids can be made for small sample aliquots (i.e., ≤10µL). Samples are deposited on pointed paper strips with co-deposited internal standards for quantitative measurements. When the strips are moistened with a suitable solvent, and upon the application of high voltage, ions are generated in a manner akin to electrospray, allowing direct analyte quantitation via tandem mass spectrometry. The strips are inexpensive and disposed for each measurement, eliminating carryover. PS-MS offers the potential to make rapid, simultaneous measurements of both small and large molecules in a single run. Albuminuria is a clinical condition associated with poor kidney function, diagnosed by determining the ratio of albumin to creatinine concentrations in patient urine samples. We present a high-throughput paper spray mass spectrometry (PS-MS) method for simultaneous quantitation of urinary albumin and creatinine for potential diagnosis of albuminuria, and the use of high resolution accurate mass spectrometry (HRAM) PS-MS coupled with machine learning for the non-targeted detection of albuminuria progression.

OBJECTIVES: To demonstrate the use and effectiveness of PS-MS for the rapid, sensitive, and quantitative and simultaneous measurement of urinary albumin and creatinine as a candidate replacement for existing clinical albuminuria diagnostics. This includes the high throughput, quantitative ACr ratio determinations as well as the non-targeted detection of the progression of albuminuria utilizing PS-MS with high resolution accurate mass spectrometry.

METHODS: All quantitative ACr measurements were performed by paper spray tandem mass spectrometry with a high-throughput paper spray ion source (Thermo Scientific™ TSQ Altis™ triple quadrupole mass spectrometer with a VeriSpray™ source). Non-targeted HRAM-PS-MS was achieved with a bespoke PS-MS interface and an Exploris 120™ orbitrap mass spectrometer. For all quantitative ACr measurements, 10 uL urine samples were co-deposited with internal standards on PS-MS samples strips using barcode traceable VeriSpray™ PS-MS sample plates (24 strips/plate), allowing unattended measurement of up to 240 samples. Non-targeted measurements were made with the same sample volumes without using internal standards, deposited on individual PS-MS paper strips of the same geometry, but analyzed individually.

RESULTS: The analytical performance of the quantitative PS-MS ACr method was evaluated, achieving linear calibration curves (R2>0.99) with little inter-day variability in slopes (N = 5 days), and exhibiting coefficient of variation (CV) of 8% for albumin and 3% for creatinine. LOD and LOQ for albumin were 2.1 and 7.0 mg L-1, and for creatinine were 0.01 and 0.03 mmol L-1. Intra- and inter-day (N = 5) precisions (%CV) and accuracies (%bias) were <10% and ±11%, respectively, for both analytes. The method was applied to determine albumin-to-creatinine ratios in anonymous human patient urine samples (N = 56), and a correlation of R2 = 0.9744 was achieved between the PS-MS results and validated clinical method results utilizing the Jaffe method for creatinine and immunoturbidimetry for albumin. This work demonstrates the utility of PS-MS to simultaneously quantify a large (albumin) and a small (creatinine) molecule directly in patient urine samples with one method. Non-targeted HRAM-PS-MS measurements (full scan data) were analyzed using 80 samples (40 healthy, ACr <2 mg mmol-1; 40 diseased, ACr >3 mg mmol-1) in combination with the Random Forest machine learning method. Clinical diagnostic test parameters of accuracy (96.3%), sensitivity (92.5%), specificity (100.0%), positive predictive value (100.0%), and negative predictive value (93.0%) were obtained. These results demonstrate that HRAM-PS-MS combined with machine learning is a potential tool for rapid diagnosis of clinical albuminuria and its progression.

CONCLUSION: The 'one instrument' quantitative PS-MS measurement of urinary albumin/creatinine ratios and the use non-targeted HRAM-PS-MS combined with machine learning illustrate their potential as candidate new methods for clinical albuminuria diagnostics.

Financial Disclosure

GrantsyesThermo Fisher
Board Memberno
IP Royaltyno

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