Quantification of lipoprotein profiles by nuclear magnetic resonance spectroscopy and multivariate data analysis

Violetta Aru; Chloie Lam; Bekzod Khakimov; Huub C J Hoefsloot; Gooitzen Zwanenburg; Mads Vendelbo Lind; Hartmut Schäfer; John van Duynhoven; Doris M Jacobs; Age K Smilde; Søren Balling Engelsen

doi:10.1016/j.trac.2017.07.009

Quantification of lipoprotein profiles by nuclear magnetic resonance spectroscopy and multivariate data analysis

Violetta Aru, Chloie Lam, Bekzod Khakimov, Huub C J Hoefsloot, Gooitzen Zwanenburg, Mads Vendelbo Lind, Hartmut Schäfer, John van Duynhoven, Doris M Jacobs, Age K Smilde, Søren Balling Engelsen

21 Citationer (Scopus)

106 Downloads (Pure)

Abstract

Lipoproteins and their subfraction profiles have been associated to diverse diseases including Cardio Vascular Disease (CVD). There is thus a great demand for measuring and quantifying the lipoprotein profile in an efficient and accurate manner.
Nuclear Magnetic Resonance (NMR) spectroscopy is uniquely able to measure the lipoprotein profile of a blood sample non-destructively due to its sensitivity to both lipid chemistry and lipid-micellar physics. However, the NMR spectra must be scaled/regressed to a primary method of reference, such as ultracentrifugation,
using multivariate regression methods.
This review provides an overview of the field and explains the methods at stake.

Originalsprog	Engelsk
Tidsskrift	Trends in Analytical Chemistry
Vol/bind	94
Sider (fra-til)	210-219
Antal sider	10
ISSN	0165-9936
DOI	https://doi.org/10.1016/j.trac.2017.07.009
Status	Udgivet - sep. 2017

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Det Natur- og Biovidenskabelige Fakultet

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10.1016/j.trac.2017.07.009Licens: CC BY

Aru et al_Trends in Analytical Chemistry_2017_Vol 94_210-219Forlagets udgivne version, 56,9 KBLicens: CC BY

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Aru, V., Lam, C., Khakimov, B., Hoefsloot, H. C. J., Zwanenburg, G., Lind, M. V., Schäfer, H., van Duynhoven, J., Jacobs, D. M., Smilde, A. K., & Engelsen, S. B. (2017). Quantification of lipoprotein profiles by nuclear magnetic resonance spectroscopy and multivariate data analysis. Trends in Analytical Chemistry, 94, 210-219. https://doi.org/10.1016/j.trac.2017.07.009

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title = "Quantification of lipoprotein profiles by nuclear magnetic resonance spectroscopy and multivariate data analysis",

abstract = "Lipoproteins and their subfraction profiles have been associated to diverse diseases including Cardio Vascular Disease (CVD). There is thus a great demand for measuring and quantifying the lipoprotein profile in an efficient and accurate manner.Nuclear Magnetic Resonance (NMR) spectroscopy is uniquely able to measure the lipoprotein profile of a blood sample non-destructively due to its sensitivity to both lipid chemistry and lipid-micellar physics. However, the NMR spectra must be scaled/regressed to a primary method of reference, such as ultracentrifugation,using multivariate regression methods.This review provides an overview of the field and explains the methods at stake.",

keywords = "Faculty of Science, Lipoprotein distribution, Lipoprotein subfractions, Ultracentrifugation, Nuclear magnetic resonance spectroscopy, Multivariate regression, LDL, HDL, VLDL, IDL, Chylomicrons",

author = "Violetta Aru and Chloie Lam and Bekzod Khakimov and Hoefsloot, {Huub C J} and Gooitzen Zwanenburg and Lind, {Mads Vendelbo} and Hartmut Sch{\"a}fer and {van Duynhoven}, John and Jacobs, {Doris M} and Smilde, {Age K} and Engelsen, {S{\o}ren Balling}",

note = "Corrigendum to “Quantification of lipoprotein profiles by nuclear magnetic resonance spectroscopy and multivariate data analysis” DOI: 10.1016/j.trac.2017.07.009",

year = "2017",

month = sep,

doi = "10.1016/j.trac.2017.07.009",

language = "English",

volume = "94",

pages = "210--219",

journal = "Trends in Analytical Chemistry",

issn = "0165-9936",

publisher = "Elsevier",

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TY - JOUR

T1 - Quantification of lipoprotein profiles by nuclear magnetic resonance spectroscopy and multivariate data analysis

AU - Aru, Violetta

AU - Lam, Chloie

AU - Khakimov, Bekzod

AU - Hoefsloot, Huub C J

AU - Zwanenburg, Gooitzen

AU - Lind, Mads Vendelbo

AU - Schäfer, Hartmut

AU - van Duynhoven, John

AU - Jacobs, Doris M

AU - Smilde, Age K

AU - Engelsen, Søren Balling

N1 - Corrigendum to “Quantification of lipoprotein profiles by nuclear magnetic resonance spectroscopy and multivariate data analysis” DOI: 10.1016/j.trac.2017.07.009

PY - 2017/9

Y1 - 2017/9

N2 - Lipoproteins and their subfraction profiles have been associated to diverse diseases including Cardio Vascular Disease (CVD). There is thus a great demand for measuring and quantifying the lipoprotein profile in an efficient and accurate manner.Nuclear Magnetic Resonance (NMR) spectroscopy is uniquely able to measure the lipoprotein profile of a blood sample non-destructively due to its sensitivity to both lipid chemistry and lipid-micellar physics. However, the NMR spectra must be scaled/regressed to a primary method of reference, such as ultracentrifugation,using multivariate regression methods.This review provides an overview of the field and explains the methods at stake.

AB - Lipoproteins and their subfraction profiles have been associated to diverse diseases including Cardio Vascular Disease (CVD). There is thus a great demand for measuring and quantifying the lipoprotein profile in an efficient and accurate manner.Nuclear Magnetic Resonance (NMR) spectroscopy is uniquely able to measure the lipoprotein profile of a blood sample non-destructively due to its sensitivity to both lipid chemistry and lipid-micellar physics. However, the NMR spectra must be scaled/regressed to a primary method of reference, such as ultracentrifugation,using multivariate regression methods.This review provides an overview of the field and explains the methods at stake.

KW - Faculty of Science

KW - Lipoprotein distribution

KW - Lipoprotein subfractions

KW - Ultracentrifugation

KW - Nuclear magnetic resonance spectroscopy

KW - Multivariate regression

KW - LDL

KW - HDL

KW - VLDL

KW - IDL

KW - Chylomicrons

UR - https://doi.org/10.1016/j.trac.2019.115631

U2 - 10.1016/j.trac.2017.07.009

DO - 10.1016/j.trac.2017.07.009

M3 - Journal article

SN - 0165-9936

VL - 94

SP - 210

EP - 219

JO - Trends in Analytical Chemistry

JF - Trends in Analytical Chemistry

ER -

Quantification of lipoprotein profiles by nuclear magnetic resonance spectroscopy and multivariate data analysis

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