title: Principal component 1 score calculated from metabolic syndrome diagnostic parameters is a possible marker for the development of metabolic syndrome in middle-aged Japanese men without treatment for metabolic diseases.
abstract: OBJECTIVE
  The risk of metabolic syndrome (MetS) is assessed based on the presence of risk factors that include dyslipidemia, hyperglycemia, hypertension and obesity. In this study, we assessed the risk of MetS using principle component (PC) analysis of MetS diagnostic parameters and examined whether the resulting eigenvalues are associated with the circulating concentrations of inflammatory cytokines [interleukin (IL)-1β and IL-6] and a marker for insulin sensitivity (adiponectin) in middle-aged Japanese men without treatment for metabolic diseases.
  
  
  METHODS
  We conducted a cross-sectional study of 308 Japanese men without treatment for metabolic diseases aged 40-69 years who participated in health checkups in Japan. We calculated the PC1 score from the following MetS diagnostic parameters: body mass index (BMI), fasting blood glucose, diastolic blood pressure, triacylglycerol and high-density lipoprotein cholesterol. We compared the relationship between PC1 scores and other clinical parameters, including IL-1β, IL-6 and adiponectin, by Spearman's rank correlation coefficient analyses and Jonckheere-Terpstra test.
  
  
  RESULTS
  The associations for most clinical parameters were higher with the PC1 score than with other MetS diagnostic parameters. Homeostasis model assessment-insulin resistance, an index of insulin resistance, showed stronger associations with PC1 score than with MetS diagnostic parameters. Significant associations for IL-1β, IL-6 and adiponectin were observed with the PC1 score, BMI and triacylglycerol; these associations were higher with the PC1 score than with BMI and triacylglycerol.
  
  
  CONCLUSIONS
  The present results show that the PC1 score is closely associated with parameters of MetS, inflammation and insulin resistance.
authors.affiliation: Laboratory of Nutritional Physiology and Global COE Program, School of Food and Nutritional Sciences, Graduate School of Nutritional and Environmental Sciences, University of Shizuoka, 52-1 Yada, Shizuoka-shi, Shizuoka, 422-8526, Japan.
authors.forename: Kazuki
authors.initials: K
authors.lastname: Mochizuki
authors.forename: Rie
authors.initials: R
authors.lastname: Miyauchi
authors.forename: Yasumi
authors.initials: Y
authors.lastname: Misaki
authors.forename: Yoko
authors.initials: Y
authors.lastname: Ichikawa
authors.forename: Toshinao
authors.initials: T
authors.lastname: Goda
mesh_terms: D052242:Adiponectin / Q000097:blood; D000328:Adult; D000368:Aged; D044466:Asian People; D015415:Biomarkers / Q000097:blood*; D001786:Blood Glucose / Q000032:analysis; D015992:Body Mass Index; D008076:Cholesterol, HDL / Q000097:blood; D003430:Cross-Sectional Studies; D006801:Humans; D007328:Insulin / Q000097:blood; D007333:Insulin Resistance; D053583:Interleukin-1beta / Q000097:blood; D015850:Interleukin-6 / Q000097:blood; D007564:Japan / Q000453:epidemiology; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood* / Q000175:diagnosis*; D008875:Middle Aged; D025341:Principal Component Analysis / Q000379:methods*; D012307:Risk Factors; D014280:Triglycerides / Q000097:blood
chemical_list: D052242:Adiponectin; D015415:Biomarkers; D001786:Blood Glucose; D008076:Cholesterol, HDL; D007328:Insulin; D053583:Interleukin-1beta; D015850:Interleukin-6; D014280:Triglycerides