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Article: Combined use of serum adiponectin and tumor necrosis factor-alpha receptor 2 levels was comparable to 2-hour post-load glucose in diabetes prediction
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TitleCombined use of serum adiponectin and tumor necrosis factor-alpha receptor 2 levels was comparable to 2-hour post-load glucose in diabetes prediction
 
AuthorsWoo, YC2
Tso, AWK2
Xu, A2
Law, LSC2
Fong, CHY2
Lam, TH2
Lo, SV1
Wat, NMS2
Cheung, BMY2
Lam, KSL2
 
KeywordsBlood sampling
Diabetes mellitus
Disease association
Dyslipidemia
Family history
 
Issue Date2012
 
PublisherPublic Library of Science. The Journal's web site is located at http://www.plosone.org/home.action
 
CitationPlos One, 2012, v. 7 n. 5, article no. e36868 [How to Cite?]
DOI: http://dx.doi.org/10.1371/journal.pone.0036868
 
AbstractBackground: Adipose tissue inflammation and dysregulated adipokine secretion are implicated in obesity-related insulin resistance and type 2 diabetes. We evaluated the use of serum adiponectin, an anti-inflammatory adipokine, and several proinflammatory adipokines, as biomarkers of diabetes risk and whether they add to traditional risk factors in diabetes prediction. Methods: We studied 1300 non-diabetic subjects from the prospective Hong Kong Cardiovascular Risk Factor Prevalence Study (CRISPS). Serum adiponectin, tumor necrosis factor-alpha receptor 2 (TNF-α R2), interleukin-6 (IL-6), adipocyte-fatty acid binding protein (A-FABP) and high-sensitivity C-reactive protein (hsCRP) were measured in baseline samples. Results: Seventy-six participants developed diabetes over 5.3 years (median). All five biomarkers significantly improved the log-likelihood of diabetes in a clinical diabetes prediction (CDP) model including age, sex, family history of diabetes, smoking, physical activity, hypertension, waist circumference, fasting glucose and dyslipidaemia. In ROC curve analysis, "adiponectin + TNF-α R2" improved the area under ROC curve (AUC) of the CDP model from 0.802 to 0.830 (P = 0.03), rendering its performance comparable to the "CDP + 2-hour post-OGTT glucose" model (AUC = 0.852, P = 0.30). A biomarker risk score, derived from the number of biomarkers predictive of diabetes (low adiponectin, high TNF-α R2), had similar performance when added to the CDP model (AUC = 0.829 [95% CI: 0.808-0.849]). Conclusions: The combined use of serum adiponectin and TNF-α R2 as biomarkers provided added value over traditional risk factors for diabetes prediction in Chinese and could be considered as an alternative to the OGTT. © 2012 Woo et al.
 
ISSN1932-6203
2012 Impact Factor: 3.73
2012 SCImago Journal Rankings: 1.512
 
DOIhttp://dx.doi.org/10.1371/journal.pone.0036868
 
PubMed Central IDPMC3353952
 
ReferencesReferences in Scopus
 
DC FieldValue
dc.contributor.authorWoo, YC
 
dc.contributor.authorTso, AWK
 
dc.contributor.authorXu, A
 
dc.contributor.authorLaw, LSC
 
dc.contributor.authorFong, CHY
 
dc.contributor.authorLam, TH
 
dc.contributor.authorLo, SV
 
dc.contributor.authorWat, NMS
 
dc.contributor.authorCheung, BMY
 
dc.contributor.authorLam, KSL
 
dc.date.accessioned2012-08-16T05:54:09Z
 
dc.date.available2012-08-16T05:54:09Z
 
dc.date.issued2012
 
dc.description.abstractBackground: Adipose tissue inflammation and dysregulated adipokine secretion are implicated in obesity-related insulin resistance and type 2 diabetes. We evaluated the use of serum adiponectin, an anti-inflammatory adipokine, and several proinflammatory adipokines, as biomarkers of diabetes risk and whether they add to traditional risk factors in diabetes prediction. Methods: We studied 1300 non-diabetic subjects from the prospective Hong Kong Cardiovascular Risk Factor Prevalence Study (CRISPS). Serum adiponectin, tumor necrosis factor-alpha receptor 2 (TNF-α R2), interleukin-6 (IL-6), adipocyte-fatty acid binding protein (A-FABP) and high-sensitivity C-reactive protein (hsCRP) were measured in baseline samples. Results: Seventy-six participants developed diabetes over 5.3 years (median). All five biomarkers significantly improved the log-likelihood of diabetes in a clinical diabetes prediction (CDP) model including age, sex, family history of diabetes, smoking, physical activity, hypertension, waist circumference, fasting glucose and dyslipidaemia. In ROC curve analysis, "adiponectin + TNF-α R2" improved the area under ROC curve (AUC) of the CDP model from 0.802 to 0.830 (P = 0.03), rendering its performance comparable to the "CDP + 2-hour post-OGTT glucose" model (AUC = 0.852, P = 0.30). A biomarker risk score, derived from the number of biomarkers predictive of diabetes (low adiponectin, high TNF-α R2), had similar performance when added to the CDP model (AUC = 0.829 [95% CI: 0.808-0.849]). Conclusions: The combined use of serum adiponectin and TNF-α R2 as biomarkers provided added value over traditional risk factors for diabetes prediction in Chinese and could be considered as an alternative to the OGTT. © 2012 Woo et al.
 
dc.description.naturepublished_or_final_version
 
dc.identifier.citationPlos One, 2012, v. 7 n. 5, article no. e36868 [How to Cite?]
DOI: http://dx.doi.org/10.1371/journal.pone.0036868
 
dc.identifier.doihttp://dx.doi.org/10.1371/journal.pone.0036868
 
dc.identifier.hkuros205202
 
dc.identifier.hkuros213321
 
dc.identifier.issn1932-6203
2012 Impact Factor: 3.73
2012 SCImago Journal Rankings: 1.512
 
dc.identifier.issue5
 
dc.identifier.pmcidPMC3353952
 
dc.identifier.pmid22615828
 
dc.identifier.scopuseid_2-s2.0-84861210925
 
dc.identifier.urihttp://hdl.handle.net/10722/159698
 
dc.identifier.volume7
 
dc.languageeng
 
dc.publisherPublic Library of Science. The Journal's web site is located at http://www.plosone.org/home.action
 
dc.publisher.placeUnited States
 
dc.relation.ispartofPLoS ONE
 
dc.relation.referencesReferences in Scopus
 
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License
 
dc.subjectBlood sampling
 
dc.subjectDiabetes mellitus
 
dc.subjectDisease association
 
dc.subjectDyslipidemia
 
dc.subjectFamily history
 
dc.titleCombined use of serum adiponectin and tumor necrosis factor-alpha receptor 2 levels was comparable to 2-hour post-load glucose in diabetes prediction
 
dc.typeArticle
 
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<contributor.author>Xu, A</contributor.author>
<contributor.author>Law, LSC</contributor.author>
<contributor.author>Fong, CHY</contributor.author>
<contributor.author>Lam, TH</contributor.author>
<contributor.author>Lo, SV</contributor.author>
<contributor.author>Wat, NMS</contributor.author>
<contributor.author>Cheung, BMY</contributor.author>
<contributor.author>Lam, KSL</contributor.author>
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<description.abstract>Background: Adipose tissue inflammation and dysregulated adipokine secretion are implicated in obesity-related insulin resistance and type 2 diabetes. We evaluated the use of serum adiponectin, an anti-inflammatory adipokine, and several proinflammatory adipokines, as biomarkers of diabetes risk and whether they add to traditional risk factors in diabetes prediction. Methods: We studied 1300 non-diabetic subjects from the prospective Hong Kong Cardiovascular Risk Factor Prevalence Study (CRISPS). Serum adiponectin, tumor necrosis factor-alpha receptor 2 (TNF-&#945; R2), interleukin-6 (IL-6), adipocyte-fatty acid binding protein (A-FABP) and high-sensitivity C-reactive protein (hsCRP) were measured in baseline samples. Results: Seventy-six participants developed diabetes over 5.3 years (median). All five biomarkers significantly improved the log-likelihood of diabetes in a clinical diabetes prediction (CDP) model including age, sex, family history of diabetes, smoking, physical activity, hypertension, waist circumference, fasting glucose and dyslipidaemia. In ROC curve analysis, &quot;adiponectin + TNF-&#945; R2&quot; improved the area under ROC curve (AUC) of the CDP model from 0.802 to 0.830 (P = 0.03), rendering its performance comparable to the &quot;CDP + 2-hour post-OGTT glucose&quot; model (AUC = 0.852, P = 0.30). A biomarker risk score, derived from the number of biomarkers predictive of diabetes (low adiponectin, high TNF-&#945; R2), had similar performance when added to the CDP model (AUC = 0.829 [95% CI: 0.808-0.849]). Conclusions: The combined use of serum adiponectin and TNF-&#945; R2 as biomarkers provided added value over traditional risk factors for diabetes prediction in Chinese and could be considered as an alternative to the OGTT. &#169; 2012 Woo et al.</description.abstract>
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Author Affiliations
  1. Hong Kong Hospital Authority
  2. The University of Hong Kong