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Evaluation of Adiposity-Related Biomarkers as Metabolic Syndrome Indicators
Recent studies have suggested a relationship of the increased circulating adipokines and inflammatory cytokine, and the risk of metabolic syndrome (MetS). The objective of this study was to identify adiposity-related factors that reflect MetS in order to establish early intervention targets. We perf...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Korean Society of Clinical Nutrition
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3728468/ https://www.ncbi.nlm.nih.gov/pubmed/23908975 http://dx.doi.org/10.7762/cnr.2013.2.2.91 |
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author | Bae, Yun-Jung Kim, Se-Hong Chung, Ju-Hye Song, Sang-Wook Kim, Kyung-Soo Kim, Mi-Kyung Kwon, Oran Choi, Myung-Sook Sung, Mi-Kyung |
author_facet | Bae, Yun-Jung Kim, Se-Hong Chung, Ju-Hye Song, Sang-Wook Kim, Kyung-Soo Kim, Mi-Kyung Kwon, Oran Choi, Myung-Sook Sung, Mi-Kyung |
author_sort | Bae, Yun-Jung |
collection | PubMed |
description | Recent studies have suggested a relationship of the increased circulating adipokines and inflammatory cytokine, and the risk of metabolic syndrome (MetS). The objective of this study was to identify adiposity-related factors that reflect MetS in order to establish early intervention targets. We performed a cross-sectional study which included 108 MetS subjects and 91 controls. Blood adiponectin, leptin, vascular-, and intercellular adhension molecules (VCAM, ICAM), monocyte chemoattractant protein 1 (MCP1), high-sensitivity C-reactive protein (hsCRP), oxidized LDL (oxLDL), tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6) were measured. The correlation analysis indicated that the MetS score (sum of the number of MetS risk factors) had an inverse relationship with adiponectin (p < 0.0001), and positive correlations with leptin (p < 0.05), ICAM (p < 0.01), MCP1 (p < 0.05), oxLDL (p < 0.05), TNF-α (p < 0.0001), IL-6 (p < 0.05) and hsCRP (p < 0.01). In multivariate logistic regression analyses, plasma triglyceride (TG) was independently associated with adiponectin, ICAM and TNF-α with the standardized β coefficients of -0.213, 0.197, and 0.193, respectively. Plasma HDL-cholesterol was independently associated with ICAM and hsCRP with the standardized β coefficients of -0.150 and -0.173. Adiponectin, TNF-α, and hsCRP were the most proximate markers reflecting MetS. Among MetS components, TG and HDL-cholesterol concentrations displayed the relationship with inflammatory markers measured in this study. |
format | Online Article Text |
id | pubmed-3728468 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | The Korean Society of Clinical Nutrition |
record_format | MEDLINE/PubMed |
spelling | pubmed-37284682013-08-01 Evaluation of Adiposity-Related Biomarkers as Metabolic Syndrome Indicators Bae, Yun-Jung Kim, Se-Hong Chung, Ju-Hye Song, Sang-Wook Kim, Kyung-Soo Kim, Mi-Kyung Kwon, Oran Choi, Myung-Sook Sung, Mi-Kyung Clin Nutr Res Original Article Recent studies have suggested a relationship of the increased circulating adipokines and inflammatory cytokine, and the risk of metabolic syndrome (MetS). The objective of this study was to identify adiposity-related factors that reflect MetS in order to establish early intervention targets. We performed a cross-sectional study which included 108 MetS subjects and 91 controls. Blood adiponectin, leptin, vascular-, and intercellular adhension molecules (VCAM, ICAM), monocyte chemoattractant protein 1 (MCP1), high-sensitivity C-reactive protein (hsCRP), oxidized LDL (oxLDL), tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6) were measured. The correlation analysis indicated that the MetS score (sum of the number of MetS risk factors) had an inverse relationship with adiponectin (p < 0.0001), and positive correlations with leptin (p < 0.05), ICAM (p < 0.01), MCP1 (p < 0.05), oxLDL (p < 0.05), TNF-α (p < 0.0001), IL-6 (p < 0.05) and hsCRP (p < 0.01). In multivariate logistic regression analyses, plasma triglyceride (TG) was independently associated with adiponectin, ICAM and TNF-α with the standardized β coefficients of -0.213, 0.197, and 0.193, respectively. Plasma HDL-cholesterol was independently associated with ICAM and hsCRP with the standardized β coefficients of -0.150 and -0.173. Adiponectin, TNF-α, and hsCRP were the most proximate markers reflecting MetS. Among MetS components, TG and HDL-cholesterol concentrations displayed the relationship with inflammatory markers measured in this study. The Korean Society of Clinical Nutrition 2013-07 2013-07-23 /pmc/articles/PMC3728468/ /pubmed/23908975 http://dx.doi.org/10.7762/cnr.2013.2.2.91 Text en © 2013 The Korean Society of Clinical Nutrition http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Bae, Yun-Jung Kim, Se-Hong Chung, Ju-Hye Song, Sang-Wook Kim, Kyung-Soo Kim, Mi-Kyung Kwon, Oran Choi, Myung-Sook Sung, Mi-Kyung Evaluation of Adiposity-Related Biomarkers as Metabolic Syndrome Indicators |
title | Evaluation of Adiposity-Related Biomarkers as Metabolic Syndrome Indicators |
title_full | Evaluation of Adiposity-Related Biomarkers as Metabolic Syndrome Indicators |
title_fullStr | Evaluation of Adiposity-Related Biomarkers as Metabolic Syndrome Indicators |
title_full_unstemmed | Evaluation of Adiposity-Related Biomarkers as Metabolic Syndrome Indicators |
title_short | Evaluation of Adiposity-Related Biomarkers as Metabolic Syndrome Indicators |
title_sort | evaluation of adiposity-related biomarkers as metabolic syndrome indicators |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3728468/ https://www.ncbi.nlm.nih.gov/pubmed/23908975 http://dx.doi.org/10.7762/cnr.2013.2.2.91 |
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