Literature DB >> 28593877

Advanced lipoprotein testing for cardiovascular diseases risk assessment: a review of the novel approaches in lipoprotein profiling.

Noémie Clouet-Foraison1, Francois Gaie-Levrel1, Philippe Gillery1, Vincent Delatour1.   

Abstract

With the increasing prevalence of cardiovascular diseases (CVD) worldwide, finding reliable and clinically relevant biomarkers to predict acute cardiovascular events has been a major aim of the scientific and medical community. Improvements of the understanding of the pathophysiological pathways of the disease highlighted the major role of lipoprotein particles, and these past decades have seen the emergence of a number of new methodologies to separate, measure and quantitate lipoproteins. Those methods, also known as advanced lipoprotein testing methods (ALT), have gained acceptance in the field of CVD risk assessment and have proven their clinical relevance. In the context of worldwide standardization and harmonization of biological assays, efforts have been initiated toward standardization of ALT methods. However, the complexity of lipoprotein particles and the multiple approaches and methodologies reported to quantify them have rendered these initiatives a critical issue. In this context and to better understand these challenges, this review presents a summary of the major methods available for ALT with the aim to point out the major differences in terms of procedures and quantities actually measured and to discuss the resulting comparability issues.

Entities:  

Keywords:  ES-DMA; LC-MS/MS; NMR; advanced lipoprotein testing; cardiovascular diseases; immunoassays

Mesh:

Substances:

Year:  2017        PMID: 28593877     DOI: 10.1515/cclm-2017-0091

Source DB:  PubMed          Journal:  Clin Chem Lab Med        ISSN: 1434-6621            Impact factor:   3.694


  6 in total

Review 1.  Lipoprotein Assessment in the twenty-first Century.

Authors:  Diego Lucero; Anna Wolska; Zahra Aligabi; Sarah Turecamo; Alan T Remaley
Journal:  Endocrinol Metab Clin North Am       Date:  2022-07-08       Impact factor: 4.748

2.  Development of internal standard for lipoprotein subclass analysis using dual detection gel-permeation high-performance liquid chromatography system.

Authors:  Mei Ogino; Takahiro Kameda; Yume Mutsuda; Hideko Tanaka; Junichiro Takahashi; Mitsuyo Okazaki; Masumi Ai; Ryunosuke Ohkawa
Journal:  Biosci Rep       Date:  2022-06-30       Impact factor: 3.976

3.  Particle number analysis of lipoprotein subclasses by gel permeation HPLC in patients with cholesteryl ester transfer protein deficiency.

Authors:  Takeshi Okada; Tohru Ohama; Mitsuyo Okazaki; Kotaro Kanno; Hibiki Matsuda; Masami Sairyo; Yinghong Zhu; Ayami Saga; Takuya Kobayashi; Daisaku Masuda; Masahiro Koseki; Makoto Nishida; Yasushi Sakata; Shizuya Yamashita
Journal:  PLoS One       Date:  2018-01-05       Impact factor: 3.240

4.  Machine learning modelling of blood lipid biomarkers in familial hypercholesterolaemia versus polygenic/environmental dyslipidaemia.

Authors:  Marta Correia; Eva Kagenaar; Daniël Bernardus van Schalkwijk; Mafalda Bourbon; Margarida Gama-Carvalho
Journal:  Sci Rep       Date:  2021-02-15       Impact factor: 4.379

Review 5.  NMR and Metabolomics-A Roadmap for the Future.

Authors:  David S Wishart; Leo L Cheng; Valérie Copié; Arthur S Edison; Hamid R Eghbalnia; Jeffrey C Hoch; Goncalo J Gouveia; Wimal Pathmasiri; Robert Powers; Tracey B Schock; Lloyd W Sumner; Mario Uchimiya
Journal:  Metabolites       Date:  2022-07-23

6.  Advanced Quantitative Lipoprotein Characteristics Do Not Relate to Healthy Dietary Patterns in Adults from a Mediterranean Area.

Authors:  Marina Idalia Rojo-López; Esmeralda Castelblanco; Jordi Real; Marta Hernández; Mireia Falguera; Núria Amigó; Josep Julve; Núria Alonso; Josep Franch-Nadal; Minerva Granado-Casas; Dídac Mauricio
Journal:  Nutrients       Date:  2021-12-06       Impact factor: 5.717

  6 in total

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