Toward Reliable Lipoprotein Particle Predictions from NMR Spectra of Human Blood: An Interlaboratory Ring Test
Lipoprotein profiling of human blood by 1H nuclear magnetic resonance (NMR) spectroscopy is a rapid and promising approach to monitor health and disease states in medicine and nutrition. However, lack of standardization of measurement protocols has prevented the use of NMR-based lipoprotein profilin...
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| Published in | Analytical chemistry (Washington) Vol. 89; no. 15; pp. 8004 - 8012 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
American Chemical Society
01.08.2017
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| Subjects | |
| Online Access | Get full text |
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| Abstract | Lipoprotein profiling of human blood by 1H nuclear magnetic resonance (NMR) spectroscopy is a rapid and promising approach to monitor health and disease states in medicine and nutrition. However, lack of standardization of measurement protocols has prevented the use of NMR-based lipoprotein profiling in metastudies. In this study, a standardized NMR measurement protocol was applied in a ring test performed across three different laboratories in Europe on plasma and serum samples from 28 individuals. Data was evaluated in terms of (i) spectral differences, (ii) differences in LPD predictions obtained using an existing prediction model, and (iii) agreement of predictions with cholesterol concentrations in high- and low-density lipoproteins (HDL and LDL) particles measured by standardized clinical assays. ANOVA-simultaneous component analysis (ASCA) of the ring test spectral ensemble that contains methylene and methyl peaks (1.4–0.6 ppm) showed that 97.99% of the variance in the data is related to subject, 1.62% to sample type (serum or plasma), and 0.39% to laboratory. This interlaboratory variation is in fact smaller than the maximum acceptable intralaboratory variation on quality control samples. It is also shown that the reproducibility between laboratories is good enough for the LPD predictions to be exchangeable when the standardized NMR measurement protocol is followed. With the successful implementation of this protocol, which results in reproducible prediction of lipoprotein distributions across laboratories, a step is taken toward bringing NMR more into scope of prognostic and diagnostic biomarkers, reducing the need for less efficient methods such as ultracentrifugation or high-performance liquid chromatography (HPLC). |
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| AbstractList | Lipoprotein profiling of human blood by ¹H nuclear magnetic resonance (NMR) spectroscopy is a rapid and promising approach to monitor health and disease states in medicine and nutrition. However, lack of standardization of measurement protocols has prevented the use of NMR-based lipoprotein profiling in metastudies. In this study, a standardized NMR measurement protocol was applied in a ring test performed across three different laboratories in Europe on plasma and serum samples from 28 individuals. Data was evaluated in terms of (i) spectral differences, (ii) differences in LPD predictions obtained using an existing prediction model, and (iii) agreement of predictions with cholesterol concentrations in high- and low-density lipoproteins (HDL and LDL) particles measured by standardized clinical assays. ANOVA-simultaneous component analysis (ASCA) of the ring test spectral ensemble that contains methylene and methyl peaks (1.4–0.6 ppm) showed that 97.99% of the variance in the data is related to subject, 1.62% to sample type (serum or plasma), and 0.39% to laboratory. This interlaboratory variation is in fact smaller than the maximum acceptable intralaboratory variation on quality control samples. It is also shown that the reproducibility between laboratories is good enough for the LPD predictions to be exchangeable when the standardized NMR measurement protocol is followed. With the successful implementation of this protocol, which results in reproducible prediction of lipoprotein distributions across laboratories, a step is taken toward bringing NMR more into scope of prognostic and diagnostic biomarkers, reducing the need for less efficient methods such as ultracentrifugation or high-performance liquid chromatography (HPLC). Lipoprotein profiling of human blood by H nuclear magnetic resonance (NMR) spectroscopy is a rapid and promising approach to monitor health and disease states in medicine and nutrition. However, lack of standardization of measurement protocols has prevented the use of NMR-based lipoprotein profiling in metastudies. In this study, a standardized NMR measurement protocol was applied in a ring test performed across three different laboratories in Europe on plasma and serum samples from 28 individuals. Data was evaluated in terms of (i) spectral differences, (ii) differences in LPD predictions obtained using an existing prediction model, and (iii) agreement of predictions with cholesterol concentrations in high- and low-density lipoproteins (HDL and LDL) particles measured by standardized clinical assays. ANOVA-simultaneous component analysis (ASCA) of the ring test spectral ensemble that contains methylene and methyl peaks (1.4-0.6 ppm) showed that 97.99% of the variance in the data is related to subject, 1.62% to sample type (serum or plasma), and 0.39% to laboratory. This interlaboratory variation is in fact smaller than the maximum acceptable intralaboratory variation on quality control samples. It is also shown that the reproducibility between laboratories is good enough for the LPD predictions to be exchangeable when the standardized NMR measurement protocol is followed. With the successful implementation of this protocol, which results in reproducible prediction of lipoprotein distributions across laboratories, a step is taken toward bringing NMR more into scope of prognostic and diagnostic biomarkers, reducing the need for less efficient methods such as ultracentrifugation or high-performance liquid chromatography (HPLC). Lipoprotein profiling of human blood by 1H nuclear magnetic resonance (NMR) spectroscopy is a rapid and promising approach to monitor health and disease states in medicine and nutrition. However, lack of standardization of measurement protocols has prevented the use of NMR-based lipoprotein profiling in metastudies. In this study, a standardized NMR measurement protocol was applied in a ring test performed across three different laboratories in Europe on plasma and serum samples from 28 individuals. Data was evaluated in terms of (i) spectral differences, (ii) differences in LPD predictions obtained using an existing prediction model, and (iii) agreement of predictions with cholesterol concentrations in high- and low-density lipoproteins (HDL and LDL) particles measured by standardized clinical assays. ANOVA-simultaneous component analysis (ASCA) of the ring test spectral ensemble that contains methylene and methyl peaks (1.4-0.6 ppm) showed that 97.99% of the variance in the data is related to subject, 1.62% to sample type (serum or plasma), and 0.39% to laboratory. This interlaboratory variation is in fact smaller than the maximum acceptable intralaboratory variation on quality control samples. It is also shown that the reproducibility between laboratories is good enough for the LPD predictions to be exchangeable when the standardized NMR measurement protocol is followed. With the successful implementation of this protocol, which results in reproducible prediction of lipoprotein distributions across laboratories, a step is taken toward bringing NMR more into scope of prognostic and diagnostic biomarkers, reducing the need for less efficient methods such as ultracentrifugation or high-performance liquid chromatography (HPLC).Lipoprotein profiling of human blood by 1H nuclear magnetic resonance (NMR) spectroscopy is a rapid and promising approach to monitor health and disease states in medicine and nutrition. However, lack of standardization of measurement protocols has prevented the use of NMR-based lipoprotein profiling in metastudies. In this study, a standardized NMR measurement protocol was applied in a ring test performed across three different laboratories in Europe on plasma and serum samples from 28 individuals. Data was evaluated in terms of (i) spectral differences, (ii) differences in LPD predictions obtained using an existing prediction model, and (iii) agreement of predictions with cholesterol concentrations in high- and low-density lipoproteins (HDL and LDL) particles measured by standardized clinical assays. ANOVA-simultaneous component analysis (ASCA) of the ring test spectral ensemble that contains methylene and methyl peaks (1.4-0.6 ppm) showed that 97.99% of the variance in the data is related to subject, 1.62% to sample type (serum or plasma), and 0.39% to laboratory. This interlaboratory variation is in fact smaller than the maximum acceptable intralaboratory variation on quality control samples. It is also shown that the reproducibility between laboratories is good enough for the LPD predictions to be exchangeable when the standardized NMR measurement protocol is followed. With the successful implementation of this protocol, which results in reproducible prediction of lipoprotein distributions across laboratories, a step is taken toward bringing NMR more into scope of prognostic and diagnostic biomarkers, reducing the need for less efficient methods such as ultracentrifugation or high-performance liquid chromatography (HPLC). Lipoprotein profiling of human blood by 1H nuclear magnetic resonance (NMR) spectroscopy is a rapid and promising approach to monitor health and disease states in medicine and nutrition. However, lack of standardization of measurement protocols has prevented the use of NMR-based lipoprotein profiling in metastudies. In this study, a standardized NMR measurement protocol was applied in a ring test performed across three different laboratories in Europe on plasma and serum samples from 28 individuals. Data was evaluated in terms of (i) spectral differences, (ii) differences in LPD predictions obtained using an existing prediction model, and (iii) agreement of predictions with cholesterol concentrations in high- and low-density lipoproteins (HDL and LDL) particles measured by standardized clinical assays. ANOVA-simultaneous component analysis (ASCA) of the ring test spectral ensemble that contains methylene and methyl peaks (1.4-0.6 ppm) showed that 97.99% of the variance in the data is related to subject, 1.62% to sample type (serum or plasma), and 0.39% to laboratory. This interlaboratory variation is in fact smaller than the maximum acceptable intralaboratory variation on quality control samples. It is also shown that the reproducibility between laboratories is good enough for the LPD predictions to be exchangeable when the standardized NMR measurement protocol is followed. With the successful implementation of this protocol, which results in reproducible prediction of lipoprotein distributions across laboratories, a step is taken toward bringing NMR more into scope of prognostic and diagnostic biomarkers, reducing the need for less efficient methods such as ultracentrifugation or high-performance liquid chromatography (HPLC). Lipoprotein profiling of human blood by 1 H nuclear magnetic resonance (NMR) spectroscopy is a rapid and promising approach to monitor health and disease states in medicine and nutrition. However, lack of standardization of measurement protocols has prevented the use of NMR-based lipoprotein profiling in metastudies. In this study, a standardized NMR measurement protocol was applied in a ring test performed across three different laboratories in Europe on plasma and serum samples from 28 individuals. Data was evaluated in terms of (i) spectral differences, (ii) differences in LPD predictions obtained using an existing prediction model, and (iii) agreement of predictions with cholesterol concentrations in high- and low-density lipoproteins (HDL and LDL) particles measured by standardized clinical assays. ANOVA-simultaneous component analysis (ASCA) of the ring test spectral ensemble that contains methylene and methyl peaks (1.4–0.6 ppm) showed that 97.99% of the variance in the data is related to subject, 1.62% to sample type (serum or plasma), and 0.39% to laboratory. This interlaboratory variation is in fact smaller than the maximum acceptable intralaboratory variation on quality control samples. It is also shown that the reproducibility between laboratories is good enough for the LPD predictions to be exchangeable when the standardized NMR measurement protocol is followed. With the successful implementation of this protocol, which results in reproducible prediction of lipoprotein distributions across laboratories, a step is taken toward bringing NMR more into scope of prognostic and diagnostic biomarkers, reducing the need for less efficient methods such as ultracentrifugation or high-performance liquid chromatography (HPLC). |
| Author | Kristensen, Mette Fang, Fang Khakimov, Bekzod Monsonis Centelles, Sandra van Duynhoven, John Spraul, Manfred Jacobs, Doris M de Roo, Niels Cannet, Claire Smilde, Age K Ebrahimi, Parvaneh Humpfer, Eberhard Hoefsloot, Huub C. J Lind, Mads V Engelsen, Søren B Schäfer, Hartmut |
| AuthorAffiliation | Swammerdam Institute for Life Sciences Laboratory of Biophysics Department of Nutrition, Exercise and Sports University of Copenhagen Universiteit van Amsterdam Department of Food Science, Chemometrics and Analytical Technology, Faculty of Science Unilever R&D Wageningen University |
| AuthorAffiliation_xml | – name: Swammerdam Institute for Life Sciences – name: Laboratory of Biophysics – name: Department of Nutrition, Exercise and Sports – name: Universiteit van Amsterdam – name: Unilever R&D – name: Wageningen University – name: University of Copenhagen – name: Department of Food Science, Chemometrics and Analytical Technology, Faculty of Science |
| Author_xml | – sequence: 1 givenname: Sandra orcidid: 0000-0003-2539-8134 surname: Monsonis Centelles fullname: Monsonis Centelles, Sandra email: S.MonsonisCentelles@uva.nl organization: Universiteit van Amsterdam – sequence: 2 givenname: Huub C. J surname: Hoefsloot fullname: Hoefsloot, Huub C. J organization: Universiteit van Amsterdam – sequence: 3 givenname: Bekzod surname: Khakimov fullname: Khakimov, Bekzod – sequence: 4 givenname: Parvaneh surname: Ebrahimi fullname: Ebrahimi, Parvaneh – sequence: 5 givenname: Mads V surname: Lind fullname: Lind, Mads V – sequence: 6 givenname: Mette surname: Kristensen fullname: Kristensen, Mette – sequence: 7 givenname: Niels surname: de Roo fullname: de Roo, Niels organization: Unilever R&D – sequence: 8 givenname: Doris M surname: Jacobs fullname: Jacobs, Doris M organization: Unilever R&D – sequence: 9 givenname: John surname: van Duynhoven fullname: van Duynhoven, John organization: Wageningen University – sequence: 10 givenname: Claire surname: Cannet fullname: Cannet, Claire – sequence: 11 givenname: Fang surname: Fang fullname: Fang, Fang – sequence: 12 givenname: Eberhard surname: Humpfer fullname: Humpfer, Eberhard – sequence: 13 givenname: Hartmut surname: Schäfer fullname: Schäfer, Hartmut – sequence: 14 givenname: Manfred surname: Spraul fullname: Spraul, Manfred – sequence: 15 givenname: Søren B surname: Engelsen fullname: Engelsen, Søren B – sequence: 16 givenname: Age K surname: Smilde fullname: Smilde, Age K organization: Universiteit van Amsterdam |
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| Cites_doi | 10.1021/ja055336t 10.1007/s11306-010-0234-7 10.1021/ac503651e 10.1161/CIRCULATIONAHA.108.809582 10.1016/j.cll.2006.07.006 10.1161/01.ATV.0000155017.60171.88 10.1093/clinchem/28.9.1873 10.1016/0167-4838(90)90100-T 10.1021/ac402571z 10.1016/j.jmr.2009.11.012 10.1016/0731-7085(93)80145-Q 10.1161/CIRCGENETICS.114.000216 10.1186/1743-7075-7-43 10.1021/ac0517085 10.1021/ac5025039 10.14533/jbm.13.21 10.1016/S0022-2275(20)39710-8 10.1371/journal.pone.0016957 10.1038/nbt.3474 10.1038/nprot.2007.376 10.1007/s11306-010-0200-4 10.1161/circ.106.25.3143 10.3945/jn.114.192229 10.1016/j.pnmrs.2016.03.001 10.1373/clinchem.2004.046748 10.1002/cem.952 10.1021/acs.analchem.6b00442 10.1021/ac981422i |
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| References | ref9/cit9 ref6/cit6 ref3/cit3 ref18/cit18 ref11/cit11 ref25/cit25 Toshima G. (ref17/cit17) 2013; 13 Bock J. L. (ref1/cit1) 1982; 28 ref23/cit23 ref14/cit14 ref8/cit8 ref5/cit5 ref2/cit2 Kulkarni K. R. (ref16/cit16) 1995; 35 ref28/cit28 ref20/cit20 ref10/cit10 ref26/cit26 ref19/cit19 ref21/cit21 ref12/cit12 ref15/cit15 ref22/cit22 ref13/cit13 ref4/cit4 ref24/cit24 NCEP ATP III (ref27/cit27) 2002; 106 ref7/cit7 |
| References_xml | – ident: ref23/cit23 doi: 10.1021/ja055336t – ident: ref5/cit5 doi: 10.1007/s11306-010-0234-7 – ident: ref10/cit10 doi: 10.1021/ac503651e – ident: ref13/cit13 doi: 10.1161/CIRCULATIONAHA.108.809582 – ident: ref19/cit19 doi: 10.1016/j.cll.2006.07.006 – ident: ref15/cit15 doi: 10.1161/01.ATV.0000155017.60171.88 – volume: 28 start-page: 1873 issue: 9 year: 1982 ident: ref1/cit1 publication-title: Clin. Chem. doi: 10.1093/clinchem/28.9.1873 – ident: ref14/cit14 doi: 10.1016/0167-4838(90)90100-T – ident: ref9/cit9 doi: 10.1021/ac402571z – ident: ref25/cit25 doi: 10.1016/j.jmr.2009.11.012 – ident: ref7/cit7 doi: 10.1016/0731-7085(93)80145-Q – ident: ref2/cit2 doi: 10.1161/CIRCGENETICS.114.000216 – ident: ref11/cit11 doi: 10.1186/1743-7075-7-43 – ident: ref18/cit18 doi: 10.1021/ac0517085 – ident: ref6/cit6 doi: 10.1021/ac5025039 – volume: 13 start-page: 21 issue: 2 year: 2013 ident: ref17/cit17 publication-title: J. Biol. Macromol. doi: 10.14533/jbm.13.21 – volume: 35 start-page: 2291 year: 1995 ident: ref16/cit16 publication-title: J. Lipid Res. doi: 10.1016/S0022-2275(20)39710-8 – ident: ref8/cit8 doi: 10.1371/journal.pone.0016957 – ident: ref21/cit21 doi: 10.1038/nbt.3474 – ident: ref22/cit22 doi: 10.1038/nprot.2007.376 – ident: ref20/cit20 doi: 10.1007/s11306-010-0200-4 – volume: 106 start-page: 3143 year: 2002 ident: ref27/cit27 publication-title: Circulation doi: 10.1161/circ.106.25.3143 – ident: ref28/cit28 doi: 10.3945/jn.114.192229 – ident: ref4/cit4 doi: 10.1016/j.pnmrs.2016.03.001 – ident: ref12/cit12 doi: 10.1373/clinchem.2004.046748 – ident: ref26/cit26 doi: 10.1002/cem.952 – ident: ref3/cit3 doi: 10.1021/acs.analchem.6b00442 – ident: ref24/cit24 doi: 10.1021/ac981422i |
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| Snippet | Lipoprotein profiling of human blood by 1H nuclear magnetic resonance (NMR) spectroscopy is a rapid and promising approach to monitor health and disease states... Lipoprotein profiling of human blood by H nuclear magnetic resonance (NMR) spectroscopy is a rapid and promising approach to monitor health and disease states... Lipoprotein profiling of human blood by ¹H nuclear magnetic resonance (NMR) spectroscopy is a rapid and promising approach to monitor health and disease states... Lipoprotein profiling of human blood by 1 H nuclear magnetic resonance (NMR) spectroscopy is a rapid and promising approach to monitor health and disease... |
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| SubjectTerms | Adult Analytical chemistry Biofysica Biomarkers Biophysics Blood blood serum Chemistry Cholesterol Diagnostic systems Europe Female High density lipoprotein High performance liquid chromatography Humans Laboratories Laboratories - standards Laboratorium voor Biofysica Least-Squares Analysis Lipoproteins Lipoproteins, HDL - blood Lipoproteins, LDL - blood Lipoproteins, VLDL - blood Liquid chromatography Low density lipoprotein Measurement NMR Nuclear magnetic resonance nuclear magnetic resonance spectroscopy Nutrition prediction Prediction models Pregnancy Principal Component Analysis Proton Magnetic Resonance Spectroscopy - standards Quality control Reliability Reproducibility Spectra Spectroscopy Standardization Ultracentrifugation variance Variance analysis VLAG Young Adult |
| Title | Toward Reliable Lipoprotein Particle Predictions from NMR Spectra of Human Blood: An Interlaboratory Ring Test |
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