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

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Quantification of lipoprotein profiles by nuclear magnetic resonance spectroscopy and multivariate data analysis. / Aru, Violetta; Lam, Chloie; Khakimov, Bekzod; Hoefsloot, Huub C J; Zwanenburg, Gooitzen; Lind, Mads Vendelbo; Schäfer, Hartmut; van Duynhoven, John; Jacobs, Doris M; Smilde, Age K; Engelsen, Søren Balling.

In: Trends in Analytical Chemistry, Vol. 94, 2017, p. 210-219.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Aru, V, Lam, C, Khakimov, B, Hoefsloot, HCJ, Zwanenburg, G, Lind, MV, Schäfer, H, van Duynhoven, J, Jacobs, DM, Smilde, AK & Engelsen, SB 2017, 'Quantification of lipoprotein profiles by nuclear magnetic resonance spectroscopy and multivariate data analysis', Trends in Analytical Chemistry, vol. 94, pp. 210-219. https://doi.org/10.1016/j.trac.2017.07.009

APA

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

Vancouver

Aru V, Lam C, Khakimov B, Hoefsloot HCJ, Zwanenburg G, Lind MV et al. Quantification of lipoprotein profiles by nuclear magnetic resonance spectroscopy and multivariate data analysis. Trends in Analytical Chemistry. 2017;94:210-219. https://doi.org/10.1016/j.trac.2017.07.009

Author

Aru, Violetta ; Lam, Chloie ; Khakimov, Bekzod ; Hoefsloot, Huub C J ; Zwanenburg, Gooitzen ; Lind, Mads Vendelbo ; Schäfer, Hartmut ; van Duynhoven, John ; Jacobs, Doris M ; Smilde, Age K ; Engelsen, Søren Balling. / Quantification of lipoprotein profiles by nuclear magnetic resonance spectroscopy and multivariate data analysis. In: Trends in Analytical Chemistry. 2017 ; Vol. 94. pp. 210-219.

Bibtex

@article{279fe211d9fc4600a241ce04702853e5,

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.2019.115631",

year = "2017",

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",

}

RIS

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.2019.115631

PY - 2017

Y1 - 2017

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

VL - 94

SP - 210

EP - 219

JO - Trends in Analytical Chemistry

JF - Trends in Analytical Chemistry

SN - 0165-9936

ER -

ID: 183501928