Benchtop Proton NMR Spectroscopy for High-Throughput Lipoprotein Quantification in Human Serum and Plasma

We report the successful development and translation of high-field nuclear magnetic resonance (NMR) based comprehensive lipoprotein analysis to routine benchtop systems. This demonstrates the potential to reimagine population level cardiovascular disease risk analysis and individual level screening based on blood sampling. Using a quantitative calibration approach, we obtained stable and reproducible results from multiple sites, despite reduced spectral dispersion and sensitivity at lower field strengths. Our study shows that 25 out of 28 major lipoprotein parameters, including key cardiometabolic risk markers, were faithfully measured using benchtop NMR systems within 15 min. This development has significant implications for making a powerful diagnostic tool widely available, enhancing the potential for longitudinal personalized medicine through molecular phenotyping in the clinic.

Authors

Institutions

Publication Details

Journal
Analytical Chemistry
Published
2025-03-17
DOI
https://doi.org/10.1021/acs.analchem.4c04660
Citations
11
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
8.87

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Benchtop Proton NMR Spectroscopy for High-Throughput Lipoprotein Quantification in Human Serum and Plasma

Tammo Diercks, Manfred Spraul, Birk Schütz, Jeremy K. Nicholson et al.
11 citations
Analytical Chemistry
Metabolomics and Mass Spectrometry Studies
8.87
article

Benchtop Proton NMR Spectroscopy for High-Throughput Lipoprotein Quantification in Human Serum and Plasma

Tammo Diercks, Manfred Spraul, Birk Schütz, Jeremy K. Nicholson, Ricardo Conde, Maider Bizkarguenaga, Philipp Nitschke, Julien Wist, Elaine Holmes, Drew A. Hall, Miriam Cobo, Claire Cannet, Óscar Millet, Nieves Embade, Wenjun Wang, Samantha Lodge, Zhonglin Chai, Ángela de Diego, Hartmut Schäfer, Sudhir Kowlessur, Niels Pompe
article en
11 citations

Abstract

We report the successful development and translation of high-field nuclear magnetic resonance (NMR) based comprehensive lipoprotein analysis to routine benchtop systems. This demonstrates the potential to reimagine population level cardiovascular disease risk analysis and individual level screening based on blood sampling. Using a quantitative calibration approach, we obtained stable and reproducible results from multiple sites, despite reduced spectral dispersion and sensitivity at lower field strengths. Our study shows that 25 out of 28 major lipoprotein parameters, including key cardiometabolic risk markers, were faithfully measured using benchtop NMR systems within 15 min. This development has significant implications for making a powerful diagnostic tool widely available, enhancing the potential for longitudinal personalized medicine through molecular phenotyping in the clinic.

Analytical ChemistryVol. 97(12)
Murdoch University (AU), Diabetes Australia (AU), Australian Regenerative Medicine Institute (AU), Division of Chemistry (US), CIC bioGUNE (ES), Bruker (Germany) (DE), Ministry of Health and Quality of Life (MU), Imperial College London (GB), Monash University (AU), Universidad del Valle (CO)
McCusker Charitable Foundation, Spinnaker Health Research Foundation, Australian Research Council, National Health and Medical Research Council, Agencia Estatal de Investigación, Department of Jobs, Tourism, Science and Innovation, Government of Western Australia
Openalex Percentile: Top 2%
Metabolomics and Mass Spectrometry Studies
8.87
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.