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A new phenotypic classification system for dyslipidemias based on the standard lipid panel
BACKGROUND: Dyslipoproteinemias can be classified by their distinct lipoprotein patterns, which helps determine atherosclerotic cardiovascular disease (ASCVD) risk and directs lipid management but this has required advanced laboratory testing. OBJECTIVE: To develop a new algorithm for classifying li...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8627634/ https://www.ncbi.nlm.nih.gov/pubmed/34838008 http://dx.doi.org/10.1186/s12944-021-01585-8 |
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author | Sampson, Maureen Ballout, Rami A. Soffer, Daniel Wolska, Anna Wilson, Sierra Meeusen, Jeff Donato, Leslie J. Fatica, Erica Otvos, James D. Brinton, Eliot A. Rosenson, Robert S. Wilson, Peter Amar, Marcelo Shamburek, Robert Karathanasis, Sotirios K. Remaley, Alan T. |
author_facet | Sampson, Maureen Ballout, Rami A. Soffer, Daniel Wolska, Anna Wilson, Sierra Meeusen, Jeff Donato, Leslie J. Fatica, Erica Otvos, James D. Brinton, Eliot A. Rosenson, Robert S. Wilson, Peter Amar, Marcelo Shamburek, Robert Karathanasis, Sotirios K. Remaley, Alan T. |
author_sort | Sampson, Maureen |
collection | PubMed |
description | BACKGROUND: Dyslipoproteinemias can be classified by their distinct lipoprotein patterns, which helps determine atherosclerotic cardiovascular disease (ASCVD) risk and directs lipid management but this has required advanced laboratory testing. OBJECTIVE: To develop a new algorithm for classifying lipoprotein disorders that only relies on the standard lipid panel. METHODS: Lipid thresholds for defining the different lipoprotein phenotypes were derived for Non-High-Density Lipoprotein-Cholesterol (NonHDL-C) and Triglycerides (TG) to be concordant when possible with the current US Multi-Society guidelines for blood cholesterol management. RESULTS: The new classification method categorizes patients into all the classical Fredrickson-like phenotypes except for Type III dysbetalipoproteinemia. In addition, a new hypolipidemic phenotype (Type VI) due to genetic mutations in apoB-metabolism is described. The validity of the new algorithm was confirmed by lipid analysis by NMR (N = 11,365) and by concordance with classification by agarose gel electrophoresis/beta-quantification (N = 5504). Furthermore, based on the Atherosclerosis Risk in Communities (ARIC) cohort (N = 14,742), the lipoprotein phenotypes differ in their association with ASCVD (TypeV>IIb > IVb > IIa > IVa > normolipidemic) and can be used prognostically as risk enhancer conditions in the management of patients. CONCLUSIONS: We describe a clinically useful lipoprotein phenotyping system that is only dependent upon the standard lipid panel. It, therefore, can be easily implemented for increasing compliance with current guidelines and for improving the care of patients at risk for ASCVD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12944-021-01585-8. |
format | Online Article Text |
id | pubmed-8627634 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-86276342021-11-30 A new phenotypic classification system for dyslipidemias based on the standard lipid panel Sampson, Maureen Ballout, Rami A. Soffer, Daniel Wolska, Anna Wilson, Sierra Meeusen, Jeff Donato, Leslie J. Fatica, Erica Otvos, James D. Brinton, Eliot A. Rosenson, Robert S. Wilson, Peter Amar, Marcelo Shamburek, Robert Karathanasis, Sotirios K. Remaley, Alan T. Lipids Health Dis Research BACKGROUND: Dyslipoproteinemias can be classified by their distinct lipoprotein patterns, which helps determine atherosclerotic cardiovascular disease (ASCVD) risk and directs lipid management but this has required advanced laboratory testing. OBJECTIVE: To develop a new algorithm for classifying lipoprotein disorders that only relies on the standard lipid panel. METHODS: Lipid thresholds for defining the different lipoprotein phenotypes were derived for Non-High-Density Lipoprotein-Cholesterol (NonHDL-C) and Triglycerides (TG) to be concordant when possible with the current US Multi-Society guidelines for blood cholesterol management. RESULTS: The new classification method categorizes patients into all the classical Fredrickson-like phenotypes except for Type III dysbetalipoproteinemia. In addition, a new hypolipidemic phenotype (Type VI) due to genetic mutations in apoB-metabolism is described. The validity of the new algorithm was confirmed by lipid analysis by NMR (N = 11,365) and by concordance with classification by agarose gel electrophoresis/beta-quantification (N = 5504). Furthermore, based on the Atherosclerosis Risk in Communities (ARIC) cohort (N = 14,742), the lipoprotein phenotypes differ in their association with ASCVD (TypeV>IIb > IVb > IIa > IVa > normolipidemic) and can be used prognostically as risk enhancer conditions in the management of patients. CONCLUSIONS: We describe a clinically useful lipoprotein phenotyping system that is only dependent upon the standard lipid panel. It, therefore, can be easily implemented for increasing compliance with current guidelines and for improving the care of patients at risk for ASCVD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12944-021-01585-8. BioMed Central 2021-11-27 /pmc/articles/PMC8627634/ /pubmed/34838008 http://dx.doi.org/10.1186/s12944-021-01585-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Sampson, Maureen Ballout, Rami A. Soffer, Daniel Wolska, Anna Wilson, Sierra Meeusen, Jeff Donato, Leslie J. Fatica, Erica Otvos, James D. Brinton, Eliot A. Rosenson, Robert S. Wilson, Peter Amar, Marcelo Shamburek, Robert Karathanasis, Sotirios K. Remaley, Alan T. A new phenotypic classification system for dyslipidemias based on the standard lipid panel |
title | A new phenotypic classification system for dyslipidemias based on the standard lipid panel |
title_full | A new phenotypic classification system for dyslipidemias based on the standard lipid panel |
title_fullStr | A new phenotypic classification system for dyslipidemias based on the standard lipid panel |
title_full_unstemmed | A new phenotypic classification system for dyslipidemias based on the standard lipid panel |
title_short | A new phenotypic classification system for dyslipidemias based on the standard lipid panel |
title_sort | new phenotypic classification system for dyslipidemias based on the standard lipid panel |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8627634/ https://www.ncbi.nlm.nih.gov/pubmed/34838008 http://dx.doi.org/10.1186/s12944-021-01585-8 |
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