代谢综合征与亚临床炎症的相关性研究
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摘要
背景:代谢综合征(Metabolic Syndrome, MS)是指肥胖、高甘油三酯血症、低高密度脂蛋白血症、胰岛素抵抗或高胰岛素血症、高血压等心血管危险因素在同一个体身上聚集的一种病理状态。近年来国内外MS发病率呈急剧上升趋势,MS已成为当今主要的社会现象和公共卫生问题之一,研究MS的流行病学趋势、危险因素、发病特征、病理生理机制对指导MS的预防、治疗均具有重要的意义。目前有观点认为MS是环境因素和遗传因素相互作用的结果,饮食方式不当和运动减少对MS的发生发展可能起着重要作用。MS的发病机制仍未完全明确,有研究认为MS是在肥胖的基础上产生胰岛素抵抗,脂肪组织参与的亚临床炎症在MS的发生发展中起着一定的作用。部分流行病学调查、临床研究和基础实验结果提示MS是一种慢性、低度、系统性的炎症状态,炎症通过各种复杂的细胞信号转导机制参与了MS的发生发展。慢性亚临床炎症正逐渐成为MS发生机制的一个研究热点,炎症也可能成为MS的有效治疗靶点。但是,就目前而言,MS与亚临床炎症的相关性尚未获充分证实。
目的:1.分析循环血中超敏C反应蛋白(hs-CRP)、白细胞介素-6(IL-6)、肿瘤坏死因子-α(TNF-α)、纤维蛋白原(Fg)、纤溶酶原激活物抑制物-1(PAI-1)等炎症标志物或炎症因子、凝血纤溶因子的浓度及白细胞(WBC)计数在MS人群及非MS人群中的差异;2.分析MS组分个数(0,1,2,3,4,5)与上述炎症标志物的相关性;3.分析上述炎症标志物与MS各组分(WC、SBP、DBP、TG、HDL-C、FBG)及IR的相关性;4.分析上述炎症标志物是否为MS的危险因素,能否成为MS的预测因子。
方法:对128例心内科的住院病人及32例体检中心健康体检者测量血压、腰围(WC)、身高和体重并计算体重指数(BMI);空腹抽血检查血常规、血糖、血脂、尿酸(UA)、凝血三项、空腹胰岛素、hs-CRP、IL-6、TNF-α、Fg、PAI-1、WBC计数。按IDF2005年MS诊断标准将总人群分为MS组与非MS组,采用t检验比较MS组与非MS组炎症标志物水平;按所含MS组分个数将总人群分成6组(0组,1组,2组,3组,4组,5组),6组炎症标志物均数比较采用ANOVA分析,6组炎症标志物之间均数两两比较采用SNK检验;炎症指标与MS各组分(WC、SBP、DBP、TG、HDL-C、FBG)的相关性分析采用Spearman相关分析;MS的危险因素分析采用Logistic回归分析。
结果:1.MS组炎症标志物水平比非MS组高:hs-CRP(3.69±0.80 vs 1.89±0.54,P<0.001)、IL-6(135.40±64.20 vs 110.83±73.20,P<0.001)、TNF-α(25.42±9.20 vs 15.45±5.24,P<0.001)、Fg(3.38±0.73 vs 3.13±0.48,P=0.025)、PAI-1(53.89±7.92 vs 32.02±5.28,P<0.001)、血白细胞计数(6.99±1.70 vs 6.53±1.71,P=0.034)。2.随着所含MS组分个数的增多(0,1,2,3,4,5),炎症指标水平逐渐增高:hs-CRP(1.69±0.62 vs 1.78±0.44 vs 2.09±0.52 vs 3.09±0.80 vs 3.49±0.74 vs 3.66±0.90,P=0.014)、IL-6(98.83±83.22 vs 106.83±74.28 vs 118.83±68.26 vs 124.40±64.36 vs 130.40±55.40 vs 138.42±82.33,P=0.013)、TNF-α(12.36±6.23 vs 14.27±7.34 vs 16.47±6.45 vs 23.45±7.24 vs 25.16±6.28 vs 26.42±10.22,P=0.022)、Fg(3.02±0.57 vs 3.09±0.36 vs 3.14±0.58 vs 3.26±0.73 vs 3.30±0.64 vs 3.40±0.84,P=0.042)、PAI-1(26.34±5.45 vs 30.12±6.38 vs 33.67±5.38 vs 48.23±7.28 vs 52.13±4.64 vs 56.23±5.92,P=0.045)、WBC(6.55±1.72 vs 6.45±1.88 vs 6.58±1.71 vs 6.68±1.63 vs 6.96±1.74 vs 6.98±1.93,P=0.028)。提示体内炎症指标水平的高低与MS组分多少密切相关。3. Spearman相关分析显示:hs-CRP与WC(r=0.490,P<0.01)、BMI(r=0.449,P<0.01)、TG(r=0.351,P<0.01)、FPG(r=0.237,P<0.01)、SBP(r=0.393,P<0.01)、DBP(r=0.222,P<0.01)正相关,与HDL-C(r=-0.182,P<0.05)负相关;IL-6与WC(r=0.430,P<0.01)、BMI(r=0.428,P<0.01)、TG(r=0.378,P<0.01)、FPG(r=0.231,P<0.01)、SBP(r=0.388,P<0.01)、DBP(r=0.230,P<0.01)正相关,与HDL-C(r=-0.185,P<0.05)负相关;TNF-α与WC(r=0.432,P<0.01)、BMI(r=0.434,P<0.01)、TG(r=0.396,P<0.01)、FPG(r=0.242,P<0.01)、SBP(r=0.372,P<0.01)、DBP(r=0.220,P<0.05)正相关,与HDL-C(r=-0.183,P<0.05)负相关;PAI-1与WC(r=0.320,P<0.01)、BMI(r=0.193,P<0.05)、TG(r=0.326,P<0.01)、FPG(r=0.231,P<0.01)、SBP(r=0.188,P<0.05)正相关,与HDL-C(r=-0.189,P<0.05)负相关;Fg与WC(r=0.365,P<0.01)、BMI(r=0.202,P<0.05)、TG(r=0.324,P<0.01)、FPG(r=0.224,P<0.01)、SBP(r=0.272,P<0.05)、DBP(r=0.290,P<0.01)正相关,与HDL-C(r=-0.186,P<0.05)负相关;WBC与WC(r=0.204,P<0.05)、BMI(r=0.197,P<0.05)、TG(r=0.229,P<0.01)、FPG(r=0.210,P<0.01),与HDL-C(r=-0.134,P<0.05)负相关。六个指标中,hs-CRP、IL-6、TNF-α与MS组分的相关性普遍强于其他三个炎症指标。4.Logistic回归分析显示:hs-CRP(OR=1.813,OR 95%CI:1.127-2.915,P=0.014)、IL-6(OR=1.987,OR 95%CI:1.204-3.012,P=0.018)、TNF-α(OR=2.151,OR 95%CI: 1.274-3.302,P=0.003)、Fg(OR=1.789,OR 95%CI:1.183-2.625,P=0.024)、PAI-1(OR=1.736,OR 95%CI:1.125-2.432,P=0.032)、WBC(OR=1.314,OR 95%CI: 1.097-1.574,P=0.008)为MS的危险因素,其中hs-CRP、IL-6、TNF-α与MS的相关性最大。5. HOMA-IR与hs-CRP(r=0.260,P<0.01)、IL-6(r=0.214,P<0.05)、TNF-α(r=0.223,P<0.01)、Fg(r=0.206,P<0.05)、PAI-1(r=0.157,P<0.05)、WBC(r=0.147,P<0.05)正相关。
结论:1.MS患者炎症标志物hs-CRP、IL-6、TNF-α、Fg、PAI-1、WBC水平增高,且上述炎症标志物与MS不同组分相关。随着所含MS组分个数的增多,炎症指标水平逐渐增高。提示慢性亚临床炎症与MS密切相关,可能是MS发生、发展的基础。2. hs-CRP、IL-6、TNF-α、Fg、PAI-1、WBC为MS的危险因素,其中hs-CRP、IL-6、TNF-α与MS的相关性最大,是MS有力的预测指标。3.慢性亚临床炎症促进MS的发生、发展可能与IR有关。
【Background】The metabolic syndrome is characterized as a group of cardiovascular risk factors including visceral obesity, hypertension, dyslipidemia, and impaired glucose tolerance.The pathogenesy of MS is not completely definite as yet. It is now realized that insulin resistance plays a principal role in initiating and perpetuating the pathologic manifestations of the metabolic syndrome. Some studies of epidemiology, clinic and basis showed that MS is a chronic,low-grade, systemic,inflammatory condition, of which inflammation maybe play a pivotal role from cell signal transduction mechanism. Chronic subclinical inflammation has been a hot spot of MS research and inflammation may become the effective therapy target point of MS.However,the association of chronic subclinical inflammation with metabolic syndrome has not been confirmed as yet.
【Objective】To investigate the association of inflammatory markers high sensitivity C-reactive protein (hs-CRP), Interleukin-6 (IL-6), tumor necrosis factor-alpha(TNF-α),fibrinogen (Fg), plasminogen activator inhibitor-1(PAI-1),white blood cell (WBC) with metabolic syndrome (MS), and explore the role of chronic subclinical inflammation play in the development of metabolic syndrome.
【Methods】160 subjects were enrolled, including 128 in-patients from Department of Cardiology and 32 health examinees. Baseline clinical measures included systolic blood pressure (SBP), diastolic pressure (DBP), waist circumference(WC), body mass index (BMI, kg/m2) was calculated based on weight and height. Plasma lipids, fasting blood glucose (FPG), fasting insulin, uric acid (UA), and the blood levels of hs-CRP, IL-6, TNF-α,Fg, PAI-1, WBC were also measured respectively. Association of the six inflammatory markers with MS components was analyzed.
【Results】(1)The blood level of hs-CRP ( 3.69±0.80 vs 1.89±0.54 ,P<0.001),IL-6(135.40±64.20 vs 110.83±73.20 , P<0.001),TNF-α(25.42±9.20 vs 15.45±5.24,P<0.001),Fg(3.38±0.73 vs 3.13±0.48,P=0.025),PAI-1(53.89±7.92 vs 32.02±5.28,P<0.001),WBC(6.99±1.70 vs 6.53±1.71,P=0.034) in patients with MS were higher than that of subjects without MS.(2)The level of hs-CRP(1.69±0.62 vs 1.78±0.44 vs 2.09±0.52 vs 3.09±0.80 vs 3.49±0.74 vs 3.66±0.90 ,P=0.014),IL-6(98.83±83.22 vs 106.83±74.28 vs 118.83±68.26 vs 124.40±64.36 vs 130.40±55.40 vs 138.42±82.33 ,P=0.013),TNF-α(12.36±6.23 vs 14.27±7.34 vs 16.47±6.45 vs 23.45±7.24 vs 25.16±6.28 vs 26.42±10.22,P=0.022),Fg(3.02±0.57 vs 3.09±0.36 vs 3.14±0.58 vs 3.26±0.73 vs 3.30±0.64 vs 3.40±0.84 ,P=0.042),PAI-1(26.34±5.45 vs 30.12±6.38 vs 33.67±5.38 vs 48.23±7.28 vs 52.13±4.64 vs 56.23±5.92,P=0.045),WBC(6.55±1.72 vs 6.45±1.88 vs 6.58±1.71 vs 6.68±1.63 vs 6.96±1.74 vs 6.98±1.93,P=0.028) were elevated in accordance with the number of MS components coun(t0,1,2,3,4,5).(3) Spearman correlation analysis showed that hs-CRP was associated with WC(r=0.490,P<0.01),BMI(r=0.449,P<0.01),TG(r=0.351,P<0.01),FPG(r=0.237,P<0.01),SBP(r=0.393,P<0.01),DBP(r=0.222,P<0.01)positively;IL-6 was associated with WC(r=0.430,P<0.01),BMI(r=0.428,P<0.01),TG(r=0.378,P<0.01),FPG(r=0.231,P<0.01),SBP(r=0.388,P<0.01),DBP(r=0.230,P<0.01) positively;TNF-αwas associated with WC(r=0.432,P<0.01),BMI(r=0.434,P<0.01),TG(r=0.396,P<0.01),FPG(r=0.242,P<0.01),SBP(r=0.372,P<0.01),DBP(r=0.220,P<0.05)positively;PAI-1 was associated with WC(r=0.320,P<0.01),BMI(r=0.193,P<0.05),TG(r=0.326,P<0.01),FPG(r=0.231,P<0.01),SBP(r=0.188,P<0.05)positively;Fg was associated with WC(r=0.365,P<0.01),BMI(r=0.202,P<0.05),TG(r=0.324,P<0.01),FPG(r=0.224,P<0.01),SBP(r=0.272,P<0.05),DBP(r=0.290,P<0.01)positively;WBC was associated with WC(r=0.204,P<0.05),BMI(r=0.197,P<0.05),TG(r=0.229, P<0.01),FPG(r=0.210,P<0.01)positively.hs-CRP,IL-6,TNF-α,PAI-1,Fg,WBC were associated with HDL-C negatively.hs-CRP、IL-6 and TNF-αshowed a stronger association with MS components than other three inflammatory markers. (4)Logistic regression analysis showed that hs-CRP(OR=1.813,OR 95%CI:1.127-2.915,P=0.014),IL-6(OR=1.987,OR 95%CI:1.204-3.012,P=0.018), TNF-α(OR=2.151,OR 95%CI:1.274-3.302,P=0.003), Fg(OR=1.789,OR 95%CI:1.183-2.625,P=0.024), PAI-1(OR=1.736,OR 95%CI:1.125-2.432,P=0.032),WBC (OR=1.314,OR 95%CI: 1.097-1.574,P=0.008)were risk factors of MS, and hs-CRP,IL-6,TNF-αwere strong predictors who showed a stronger association with MS than other three inflammatory markers.(5) HOMA-IR was associated with hs-CRP ( r=0.260 ,P<0.01),IL-6(r=0.214,P<0.05),TNF-α(r=0.223,P<0.01),Fg (r=0.206,P<0.05),PAI-1(r=0.157,P<0.05)and WBC(r=0.147,P<0.05)positively.
【Conclusions】1.The levels of inflammatory markers in patients with MS were higher than that of subjects without MS. Inflammatory markers were correlated to several components of MS.The level of inflammatory markers were elevated in accordance with the number of MS components count. It showed that chronic subclinical inflammation was associated with MS closely,and that may be the basis of generation and development about MS. 2. hs-CRP、IL-6、TNF-α、Fg、PAI-1、WBC were risk factors for MS and hs-CRP,IL-6,TNF-αwere strong predictors who showed a stronger association with MS than other three inflammatory markers. 3.Chronic subclinical inflammation may aggravate the development of MS through insulin resistance.
目的:1.分析循环血中超敏C反应蛋白(hs-CRP)、白细胞介素-6(IL-6)、肿瘤坏死因子-α(TNF-α)、纤维蛋白原(Fg)、纤溶酶原激活物抑制物-1(PAI-1)等炎症标志物或炎症因子、凝血纤溶因子的浓度及白细胞(WBC)计数在MS人群及非MS人群中的差异;2.分析MS组分个数(0,1,2,3,4,5)与上述炎症标志物的相关性;3.分析上述炎症标志物与MS各组分(WC、SBP、DBP、TG、HDL-C、FBG)及IR的相关性;4.分析上述炎症标志物是否为MS的危险因素,能否成为MS的预测因子。
方法:对128例心内科的住院病人及32例体检中心健康体检者测量血压、腰围(WC)、身高和体重并计算体重指数(BMI);空腹抽血检查血常规、血糖、血脂、尿酸(UA)、凝血三项、空腹胰岛素、hs-CRP、IL-6、TNF-α、Fg、PAI-1、WBC计数。按IDF2005年MS诊断标准将总人群分为MS组与非MS组,采用t检验比较MS组与非MS组炎症标志物水平;按所含MS组分个数将总人群分成6组(0组,1组,2组,3组,4组,5组),6组炎症标志物均数比较采用ANOVA分析,6组炎症标志物之间均数两两比较采用SNK检验;炎症指标与MS各组分(WC、SBP、DBP、TG、HDL-C、FBG)的相关性分析采用Spearman相关分析;MS的危险因素分析采用Logistic回归分析。
结果:1.MS组炎症标志物水平比非MS组高:hs-CRP(3.69±0.80 vs 1.89±0.54,P<0.001)、IL-6(135.40±64.20 vs 110.83±73.20,P<0.001)、TNF-α(25.42±9.20 vs 15.45±5.24,P<0.001)、Fg(3.38±0.73 vs 3.13±0.48,P=0.025)、PAI-1(53.89±7.92 vs 32.02±5.28,P<0.001)、血白细胞计数(6.99±1.70 vs 6.53±1.71,P=0.034)。2.随着所含MS组分个数的增多(0,1,2,3,4,5),炎症指标水平逐渐增高:hs-CRP(1.69±0.62 vs 1.78±0.44 vs 2.09±0.52 vs 3.09±0.80 vs 3.49±0.74 vs 3.66±0.90,P=0.014)、IL-6(98.83±83.22 vs 106.83±74.28 vs 118.83±68.26 vs 124.40±64.36 vs 130.40±55.40 vs 138.42±82.33,P=0.013)、TNF-α(12.36±6.23 vs 14.27±7.34 vs 16.47±6.45 vs 23.45±7.24 vs 25.16±6.28 vs 26.42±10.22,P=0.022)、Fg(3.02±0.57 vs 3.09±0.36 vs 3.14±0.58 vs 3.26±0.73 vs 3.30±0.64 vs 3.40±0.84,P=0.042)、PAI-1(26.34±5.45 vs 30.12±6.38 vs 33.67±5.38 vs 48.23±7.28 vs 52.13±4.64 vs 56.23±5.92,P=0.045)、WBC(6.55±1.72 vs 6.45±1.88 vs 6.58±1.71 vs 6.68±1.63 vs 6.96±1.74 vs 6.98±1.93,P=0.028)。提示体内炎症指标水平的高低与MS组分多少密切相关。3. Spearman相关分析显示:hs-CRP与WC(r=0.490,P<0.01)、BMI(r=0.449,P<0.01)、TG(r=0.351,P<0.01)、FPG(r=0.237,P<0.01)、SBP(r=0.393,P<0.01)、DBP(r=0.222,P<0.01)正相关,与HDL-C(r=-0.182,P<0.05)负相关;IL-6与WC(r=0.430,P<0.01)、BMI(r=0.428,P<0.01)、TG(r=0.378,P<0.01)、FPG(r=0.231,P<0.01)、SBP(r=0.388,P<0.01)、DBP(r=0.230,P<0.01)正相关,与HDL-C(r=-0.185,P<0.05)负相关;TNF-α与WC(r=0.432,P<0.01)、BMI(r=0.434,P<0.01)、TG(r=0.396,P<0.01)、FPG(r=0.242,P<0.01)、SBP(r=0.372,P<0.01)、DBP(r=0.220,P<0.05)正相关,与HDL-C(r=-0.183,P<0.05)负相关;PAI-1与WC(r=0.320,P<0.01)、BMI(r=0.193,P<0.05)、TG(r=0.326,P<0.01)、FPG(r=0.231,P<0.01)、SBP(r=0.188,P<0.05)正相关,与HDL-C(r=-0.189,P<0.05)负相关;Fg与WC(r=0.365,P<0.01)、BMI(r=0.202,P<0.05)、TG(r=0.324,P<0.01)、FPG(r=0.224,P<0.01)、SBP(r=0.272,P<0.05)、DBP(r=0.290,P<0.01)正相关,与HDL-C(r=-0.186,P<0.05)负相关;WBC与WC(r=0.204,P<0.05)、BMI(r=0.197,P<0.05)、TG(r=0.229,P<0.01)、FPG(r=0.210,P<0.01),与HDL-C(r=-0.134,P<0.05)负相关。六个指标中,hs-CRP、IL-6、TNF-α与MS组分的相关性普遍强于其他三个炎症指标。4.Logistic回归分析显示:hs-CRP(OR=1.813,OR 95%CI:1.127-2.915,P=0.014)、IL-6(OR=1.987,OR 95%CI:1.204-3.012,P=0.018)、TNF-α(OR=2.151,OR 95%CI: 1.274-3.302,P=0.003)、Fg(OR=1.789,OR 95%CI:1.183-2.625,P=0.024)、PAI-1(OR=1.736,OR 95%CI:1.125-2.432,P=0.032)、WBC(OR=1.314,OR 95%CI: 1.097-1.574,P=0.008)为MS的危险因素,其中hs-CRP、IL-6、TNF-α与MS的相关性最大。5. HOMA-IR与hs-CRP(r=0.260,P<0.01)、IL-6(r=0.214,P<0.05)、TNF-α(r=0.223,P<0.01)、Fg(r=0.206,P<0.05)、PAI-1(r=0.157,P<0.05)、WBC(r=0.147,P<0.05)正相关。
结论:1.MS患者炎症标志物hs-CRP、IL-6、TNF-α、Fg、PAI-1、WBC水平增高,且上述炎症标志物与MS不同组分相关。随着所含MS组分个数的增多,炎症指标水平逐渐增高。提示慢性亚临床炎症与MS密切相关,可能是MS发生、发展的基础。2. hs-CRP、IL-6、TNF-α、Fg、PAI-1、WBC为MS的危险因素,其中hs-CRP、IL-6、TNF-α与MS的相关性最大,是MS有力的预测指标。3.慢性亚临床炎症促进MS的发生、发展可能与IR有关。
【Background】The metabolic syndrome is characterized as a group of cardiovascular risk factors including visceral obesity, hypertension, dyslipidemia, and impaired glucose tolerance.The pathogenesy of MS is not completely definite as yet. It is now realized that insulin resistance plays a principal role in initiating and perpetuating the pathologic manifestations of the metabolic syndrome. Some studies of epidemiology, clinic and basis showed that MS is a chronic,low-grade, systemic,inflammatory condition, of which inflammation maybe play a pivotal role from cell signal transduction mechanism. Chronic subclinical inflammation has been a hot spot of MS research and inflammation may become the effective therapy target point of MS.However,the association of chronic subclinical inflammation with metabolic syndrome has not been confirmed as yet.
【Objective】To investigate the association of inflammatory markers high sensitivity C-reactive protein (hs-CRP), Interleukin-6 (IL-6), tumor necrosis factor-alpha(TNF-α),fibrinogen (Fg), plasminogen activator inhibitor-1(PAI-1),white blood cell (WBC) with metabolic syndrome (MS), and explore the role of chronic subclinical inflammation play in the development of metabolic syndrome.
【Methods】160 subjects were enrolled, including 128 in-patients from Department of Cardiology and 32 health examinees. Baseline clinical measures included systolic blood pressure (SBP), diastolic pressure (DBP), waist circumference(WC), body mass index (BMI, kg/m2) was calculated based on weight and height. Plasma lipids, fasting blood glucose (FPG), fasting insulin, uric acid (UA), and the blood levels of hs-CRP, IL-6, TNF-α,Fg, PAI-1, WBC were also measured respectively. Association of the six inflammatory markers with MS components was analyzed.
【Results】(1)The blood level of hs-CRP ( 3.69±0.80 vs 1.89±0.54 ,P<0.001),IL-6(135.40±64.20 vs 110.83±73.20 , P<0.001),TNF-α(25.42±9.20 vs 15.45±5.24,P<0.001),Fg(3.38±0.73 vs 3.13±0.48,P=0.025),PAI-1(53.89±7.92 vs 32.02±5.28,P<0.001),WBC(6.99±1.70 vs 6.53±1.71,P=0.034) in patients with MS were higher than that of subjects without MS.(2)The level of hs-CRP(1.69±0.62 vs 1.78±0.44 vs 2.09±0.52 vs 3.09±0.80 vs 3.49±0.74 vs 3.66±0.90 ,P=0.014),IL-6(98.83±83.22 vs 106.83±74.28 vs 118.83±68.26 vs 124.40±64.36 vs 130.40±55.40 vs 138.42±82.33 ,P=0.013),TNF-α(12.36±6.23 vs 14.27±7.34 vs 16.47±6.45 vs 23.45±7.24 vs 25.16±6.28 vs 26.42±10.22,P=0.022),Fg(3.02±0.57 vs 3.09±0.36 vs 3.14±0.58 vs 3.26±0.73 vs 3.30±0.64 vs 3.40±0.84 ,P=0.042),PAI-1(26.34±5.45 vs 30.12±6.38 vs 33.67±5.38 vs 48.23±7.28 vs 52.13±4.64 vs 56.23±5.92,P=0.045),WBC(6.55±1.72 vs 6.45±1.88 vs 6.58±1.71 vs 6.68±1.63 vs 6.96±1.74 vs 6.98±1.93,P=0.028) were elevated in accordance with the number of MS components coun(t0,1,2,3,4,5).(3) Spearman correlation analysis showed that hs-CRP was associated with WC(r=0.490,P<0.01),BMI(r=0.449,P<0.01),TG(r=0.351,P<0.01),FPG(r=0.237,P<0.01),SBP(r=0.393,P<0.01),DBP(r=0.222,P<0.01)positively;IL-6 was associated with WC(r=0.430,P<0.01),BMI(r=0.428,P<0.01),TG(r=0.378,P<0.01),FPG(r=0.231,P<0.01),SBP(r=0.388,P<0.01),DBP(r=0.230,P<0.01) positively;TNF-αwas associated with WC(r=0.432,P<0.01),BMI(r=0.434,P<0.01),TG(r=0.396,P<0.01),FPG(r=0.242,P<0.01),SBP(r=0.372,P<0.01),DBP(r=0.220,P<0.05)positively;PAI-1 was associated with WC(r=0.320,P<0.01),BMI(r=0.193,P<0.05),TG(r=0.326,P<0.01),FPG(r=0.231,P<0.01),SBP(r=0.188,P<0.05)positively;Fg was associated with WC(r=0.365,P<0.01),BMI(r=0.202,P<0.05),TG(r=0.324,P<0.01),FPG(r=0.224,P<0.01),SBP(r=0.272,P<0.05),DBP(r=0.290,P<0.01)positively;WBC was associated with WC(r=0.204,P<0.05),BMI(r=0.197,P<0.05),TG(r=0.229, P<0.01),FPG(r=0.210,P<0.01)positively.hs-CRP,IL-6,TNF-α,PAI-1,Fg,WBC were associated with HDL-C negatively.hs-CRP、IL-6 and TNF-αshowed a stronger association with MS components than other three inflammatory markers. (4)Logistic regression analysis showed that hs-CRP(OR=1.813,OR 95%CI:1.127-2.915,P=0.014),IL-6(OR=1.987,OR 95%CI:1.204-3.012,P=0.018), TNF-α(OR=2.151,OR 95%CI:1.274-3.302,P=0.003), Fg(OR=1.789,OR 95%CI:1.183-2.625,P=0.024), PAI-1(OR=1.736,OR 95%CI:1.125-2.432,P=0.032),WBC (OR=1.314,OR 95%CI: 1.097-1.574,P=0.008)were risk factors of MS, and hs-CRP,IL-6,TNF-αwere strong predictors who showed a stronger association with MS than other three inflammatory markers.(5) HOMA-IR was associated with hs-CRP ( r=0.260 ,P<0.01),IL-6(r=0.214,P<0.05),TNF-α(r=0.223,P<0.01),Fg (r=0.206,P<0.05),PAI-1(r=0.157,P<0.05)and WBC(r=0.147,P<0.05)positively.
【Conclusions】1.The levels of inflammatory markers in patients with MS were higher than that of subjects without MS. Inflammatory markers were correlated to several components of MS.The level of inflammatory markers were elevated in accordance with the number of MS components count. It showed that chronic subclinical inflammation was associated with MS closely,and that may be the basis of generation and development about MS. 2. hs-CRP、IL-6、TNF-α、Fg、PAI-1、WBC were risk factors for MS and hs-CRP,IL-6,TNF-αwere strong predictors who showed a stronger association with MS than other three inflammatory markers. 3.Chronic subclinical inflammation may aggravate the development of MS through insulin resistance.
引文
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[2].Grundy SM, Brewer HB, Cleeman J I, et al. Definition of metabolic syndrome: report of the national heart, lung, and blood institute/American heart association conference on scientific issues related to definition [J]. Circulation, 2004, 109:433-438.
[3].International Diabetes Federation. The IDF consensus worldwide definition of the metabolic syndrome.Berlin,2005.14.
[4].Chobanian AV, Bakris GL, Black HR, et a1.The Seventh Report of the Joint National Committee on prevention,detection,evaluation an d treatment of high blood pressure.JAMA, 2003,21:2560-2572.
[5].Andreas Festa, Ralph D’Agostino, Jr, George Howard, ET al.Chronic Subclinical Inflammation as Part of the Insulin Resistance Syndrome: The Insulin Resistance Atherosclerosis Study (IRAS) [J]. Circulation, 2000, 102:42-47.
[6].Nakanishi N, Suzuki K, Tatara K.White blood cell count and clustered features of metabolic syndrome in Japanese male office workers [J].Occup Med, 2002, 52(4): 213-218.
[7].Gomez-Fernandez P, Eady Alonso M, Ruiz A.Biomarkers of vascular inflammation and subclinical atherosclerosis in the metabolic syndrome[J]. MedClin (Barc).,2004,123(10):361-363.
[8].T. Mardi, S. Toker, S. Melamad, et al.Increased erythropoiesis and subclinical inflammation as part of the metabolic syndrome [J].Diabetes Research and Clinical Practice,2005,69:249-255. [9]Nickel J C. Prostatitis: lessons from the 20th century [J]. BJU International, 2000, 85(2): 179-185.
[9].Soro-Paavonen A, Westerbacka J, Ehnholm C, et al. Metabolic syndrome aggravates the increased endothelial activation and low-grade inflammation in subjects with familial low HDL [J]. Annals of Medicine, 2006, 38(3):229-238.
[10].Han TS, Sattar N, Williams K, Gonzalez-Villalpando C, et al.Prospective Studyof C-Reactive Protein in Relation to the Development of Diabetes and Metabolic Syndrome in the Mexico City Diabetes Study[J].Diabetes Care,2002, 25(11):2016– 2021.
[11].Laaksonen DE, Niskanen L, Nyyssonen K.C-reactive protein and the development of the metabolic syndrome and diabetes in middle-aged men[J], Diabetologia, 2004, 47(8): 1403-1410.
[12].Olivija Gustien, Rimvydas lapikas, Jurat Klumbien etal.The prevalence of metabolic syndrome in middle-aged in Kaunas population [J]. Medicina (Kaunas) 2005,41 (10): 867-876.
[13].Ishikawa S, Kayaba K, Gotoh T.Metabolic syndrome and C-reactive protein in the general population: JMS Cohort Study[J].Circ J. 2007, 71(1):26-31.
[14].PasceriV, WilersonJ T, YehE T.Direct proinflammatory effect of C-reactive protein on human endothelial cells [J].Circulation, 2000, 102:2165-2167.
[15].Venugopal SK, Devaraj S, Yuhanna I, et al.Demonstration that C-reactive protein decrease eNOS expression and bioactivity in human aortic endothelialc ells [J].Circulation, 2002, 106:1439-1441.
[16].Hottori Y, Matsumura M, Kasai K, et al.Vascular smooth muscle cell action by C-reactive protein [J]. Cardiovasc Res, 2003, 58:186-195.
[17].Pradhan AD,Cook NR,Buring JE,et a1.C-reactive protein is independently associated with fasting insulin in nondiabetic women [J].Arterioscler Thromb Vasc Bid,2003, 23:650-655.
[18].Freeman DJ, Norrie J, Caslake MJ, et al. C-reactive protein is an independent predictor of risk for the development of diabetes in the West of Scotland Coronary Prevention Study [J]. Diabetes, 2002, 51:1596–1600.
[19].Ridker PM, Rifai N, Rose L,et al.Comparison of C-reactive protein and low density lipoprotein cholesterol levels in the prediction of first cardiovascular events[J].N Eng J Med, 2002, 347:1557-1564.
[20].Rutter MK, Melgs JB, SullivanLM, eta1.C-reactive protein, the metabolic syndrome, and prediction of cardiovascular events in the Framingham offspringstudy [J].Circulation, 2004,110(4):380-385.
[21].Fernandez-Real JM,Broch M,Verdrell J,et al. Interleukin-6 gene poly-morphism and insulin sensitivity.Diabetes,2000,49:517-520.
[22].Lopatynski J, Mardarowicz G, Szczesniak G.A comparative evaluation of waist circumference, waist-to-hip ratio, waist-to-height ratio and body mass index as indicators of impaired glucose tolerance and as risk factors for type 2 diabetes mellitus [J].Ann Univ Mariae Curie Sklodowska [Med]. 2003, 58(1):413-419.
[23].Weisel JW.Fibrinogen and fibrin [J].Adv Protein Chem, 2005, 70:247-299.
[24].Dunn EJ, Ariens RA. Fibrinogen and fibrin clot structure in diabetes [J]. Herz,2004, 29 (5): 470-479.
[25].Hamsten A. The hemostatic system and coronary heard disease [J].Thromb Res1993, 70(1):1–38.
[26].Juhan-Vague I, Alessi MC, Morange PE, et al. Hypofibrinolysis and increased PAI-1 are linked to atherothrombosis via insulin resistance and obesity [J]. Ann Med, 2000, 32 (Suppl1) : 78-84.
[27].Bastard JP , Pieroni L, Hainque B. Relationship between plasma plasminogen activator inhibitor 1 and insulin resistance .Diabetes Metab Res Rev, 2000, 16(3) :192-201.
[28].Aso Y, Matsumoto S, Fujiwara Y, et al. Impaired fibrinolytic compensation for hypercoagulability in obese patients with type 2 diabetes : association with increased plasminogen activator inhibitor-1. Metabolism , 2002 , 51(4) :471-476
[29].Barbora V, Christian W, Robert S, et al.High white blood cell count is associated with a worsening of insulin sensitivity and predicts the development of type 2 diabetes[J].Diabetes,2002,51:455-461.
[30].Brown DW,Giles WH,Cmfl JB.White blood cell count:an independent predictor of coronary heart disease mortality among a national cohort[J].J Clin Epidemiol,2001,54(3):316-322.
[1].国际糖尿病联盟,国际糖尿病联盟代谢综合征全球共识定义[J].中华糖尿病杂志2005,13(3):178- 180.
[2]. Haffner SM. The metabolic syndrome: inflammation, diabetes mellitus, and cardiovascular disease.Am J Cardiol, 2006, 97(2A):3A-11A.
[3]. Vlachopoulos C, Rokkas K, Ioakeimidis N, et al. Inflammation, metabolic syndrome, erectile dysfunction, and coronary artery disease: common links. Eur Urol, 2007, 52(6):1590-1600.
[4]. Rayssiguier Y, Gueux E, Nowacki W, et al. High fructose consumption combined with low dietary magnesium intake may increase the incidence of the metabolic syndrome by inducing inflammation. Magnes Res, 2006, 19(4):237-243.
[5]. Weyer C, Funahashi T, Tanaka S, et al. Hypoadiponectinemia in obesity and type 2 diabetes: close association with insulin resistance and hyper-insulinemia [J]. J Clin Endocrinol Metab, 2001, 86:1930-1935.
[6]. Engstrom G, Hedblad B, Stavenow L,et al. Inflammation-sensitive plasma proteins are associated with future weight gain[J]. Diabetes. 2003, 52(8): 2097-2101.
[7]. Crook MA, Tutt P, Simpson H, et al. Serum sialic acid and acute phase proteins in type 1 and type 2 diabetes mellitus. Clin Chim Acta, 1993, 219(1-2):131-138.
[8]. Leinonen E, Hurt-Camejo E, Wiklund O, et al. Insulin resistance and adiposity correlate with acute-phase reaction and soluble cell adhesion molecules in type 2 diabetes. Atherosclerosis, 2003, 166(2):387-394.
[9]. Novo G, Corrado E, Muratori I, et al. Markers of inflammation and prevalence of vascular disease in patients with metabolic syndrome. Int Angiol, 2007, 26(4):312-317.
[10].Muntner P, He J, Chen J, et al. Prevalence of non-traditional cardiovascular disease risk factors among persons with impaired fasting glucose, impaired glucose tolerance, diabetes, and the metabolic syndrome: analysis of the Third National Health and Nutrition Examination Survey (NHANES III). Ann Epidemiol, 2004, 14(9):686-695.
[11]. Novo G, Corrado E, Muratori I, et al. Markers of inflammation and prevalence of vascular disease in patients with metabolic syndrome. Int Angiol, 2007, 26(4):312-317.
[12]. Kraja AT, Province MA, Arnett D, et al. Do inflammation and procoagulation biomarkers contribute to the metabolic syndrome cluster? Nutr Metab (Lond), 2007, 4(1):28.
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