首都医科大学学报 ›› 2015, Vol. 36 ›› Issue (4): 614-617.doi: 10.3969/j.issn.1006-7795.2015.04.020

• 基础研究 • 上一篇    下一篇

血浆糖基与代谢综合征血糖组分关联性研究

曹凯1,2, 王友信1,2, 刘相佟1,2, 陶丽新1,2, 郭晋1,2, 宋曼殳1,2, 于鑫玮1,2, 杨金奎3,4, 王嵬1,2, 郭秀花1,2, 杨光燃4, 魏文斌5   

  1. 1. 首都医科大学公共卫生学院流行病与卫生统计学系, 北京 100069;
    2. 临床流行病学北京市重点实验室, 北京 100069;
    3. 糖尿病防治研究北京市重点实验室, 北京 100005;
    4. 首都医科大学附属北京同仁医院内分泌科, 北京 100730;
    5. 首都医科大学附属北京同仁医院眼科, 北京 100730
  • 收稿日期:2015-02-15 出版日期:2015-08-21 发布日期:2015-07-17
  • 通讯作者: 王嵬, 郭秀花 E-mail:wei.wang@ccmu.edu.cn;statguo@ccmu.edu.cn
  • 基金资助:

    国家自然科学基金项目(81373099,81370083)。

Association between blood glycans and glucose of metabolic syndrome

Cao Kai1,2, Wang Youxin1,2, Liu Xiangtong1,2, Tao Lixin1,2, Guo Jin1,2, Song Manshu1,2, Yu Xinwei1,2, Yang Jinkui3,4, Wang Wei1,2, Guo Xiuhua1,2, Yang Guangran4, Wei Wenbin5   

  1. 1. Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing 100069, China;
    2. Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China;
    3. Beijng Key Laboratory of Diabetes Research and Care, Beijing 100005, China;
    4. Endocrinology Department, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China;
    5. Eye Department, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
  • Received:2015-02-15 Online:2015-08-21 Published:2015-07-17
  • Supported by:

    This study was supported by National Natural Science Foundation of China(81373099,81370083).

摘要:

目的 探讨血浆糖基与代谢综合征血糖组分的关联性。方法 将患者按有无代谢综合征血糖组分异常划分为2组(≥5.6 mmol/L为异常),采用秩和检验比较两组糖基差异性;将差异有统计学意义的糖基位点代入Logistic回归探讨代谢综合征血糖组分的影响因素。结果 Logistic回归结果显示:GP5、GP11和A2三个糖基位点对代谢综合征血糖组分的影响具有统计学意义(P<0.05)。结论 GP5、GP11和A2三个糖基位点是代谢综合征血糖组分异常的影响因素。

关键词: 糖基, 预测模型, 代谢综合征, 血糖组分

Abstract:

Objective To explore the association between blood glycans and glucose of metabolic syndrome. Methods Subjects are split into two groups according to glucose level(below 5.6 mmol/L is defined as normal). Wilcoxon rank sum test is applied to make comparison of glycan level between two groups and Logistic regression is applied to make sure the impact factors of blood glucose. Results GP5, GP11 and A2 are statistically significant with P value under 0.01. Conclusion GP5, GP11 and A2 are the impact factors of blood glucose.

Key words: glycans, predictive model, metabolic syndrome, blood glucose

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