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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 2
Xu, A2 2
Law, LSC2
Fong, CHY2
Lam, TH2
Lo, SV1
Wat, NMS2
Cheung, BMY2 2
Lam, KSL2 2
 
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