Literature DB >> 16828905

Apolipoprotein B is associated with metabolic syndrome in Chinese families with familial combined hyperlipidemia, familial hypertriglyceridemia and familial hypercholesterolemia.

Wei-dong Pei1, Yu-hua Sun, Bin Lu, Qun Liu, Chao-yang Zhang, Jian Zhang, Yu-he Jia, Zong-liang Lu, Ru-tai Hui, Li-sheng Liu, Yue-jin Yang.   

Abstract

There is a paucity of data concerning the metabolic syndrome (MetS) in families with familial combined hyperlipidemia (FCHL), familial hypertriglyceridemia (FHTG), familial hypercholesterolemia (FH) and normolipidemic families in China. This study investigated the prevalence of MetS in these families and explored potential factors relevant to MetS. We recruited 70 families with 560 individuals > or = 20 years of age, including 43 FCHL families with 379 individuals, 3 FHTG families with 30 individuals, 16 FH families with 102 individuals and 8 normolipidemic families with 49 individuals. The definition of MetS is determined using modified criteria of National Cholesterol Education Program substituting body mass index for waist circumference. MetS is identified in 60.7% of FCHL patients and 71.4% of FHTG patients. The prevalence of MetS in family members is 36.7% for FCHL, 33.3% for FHTG, 17.6% for FH and 16.3% for normolipidemic families, with an odds ratio (OR) of 2.97 (95% CI 1.29-7.07, P=0.007) in FCHL families compared with normolipidemic families. Apolipoprotein B (apoB) is associated with MetS by multiple logistic analysis with an OR of 1.05 (1.03-1.07, P<0.001) in FCHL families, OR of 1.26 (1.03-1.55, P=0.026) in FHTG and OR of 1.07 (1.01-1.12, P=0.014) in FH families, independent of variables including age, gender, apolipoprotein A1, and low density lipoprotein cholesterol. Apolipoprotein A1 provided an OR of 0.95 (0.94-0.97, P<0.001) in FCHL families and OR of 0.94 (0.90-0.97, P=0.011) in FH families, but neither in FHTG nor in normolipidemic families (both P>0.05). Thus, apoB may be regarded as a relevant factor in the assessment of MetS in FCHL, FHTG and FH families. However, this finding needs to be verified by prospective studies in diverse ethnicities and warrants additional studies to elucidate possible mechanisms linking apoB to MetS.

Entities:  

Mesh:

Substances:

Year:  2006        PMID: 16828905     DOI: 10.1016/j.ijcard.2006.03.045

Source DB:  PubMed          Journal:  Int J Cardiol        ISSN: 0167-5273            Impact factor:   4.164


  5 in total

1.  Prevalence of metabolic syndrome and its risk factors among rural adults in Nantong, China.

Authors:  Jing Xiao; Chuan-Li Wu; Yue-Xia Gao; Shu-Lan Wang; Lei Wang; Qing-Yun Lu; Xiao-Jian Wang; Tian-Qi Hua; Huan Shen; Hui Cai
Journal:  Sci Rep       Date:  2016-11-30       Impact factor: 4.379

2.  A High Incidence of Metabolic Syndrome Traits in Mexicans Points at Obesity-Related Metabolic Dysfunction.

Authors:  Arsenio Vargas-Vázquez; Neftali Eduardo Antonio-Villa; Omar Yaxmehen Bello-Chavolla; Fabiola Mabel Del Razo-Olvera; Daniel Elías-López; Carlos A Aguilar-Salinas
Journal:  Diabetes Metab Syndr Obes       Date:  2021-03-09       Impact factor: 3.168

3.  Genetic spectrum of familial hypercholesterolemia and correlations with clinical expression: Implications for diagnosis improvement.

Authors:  Maria Donata Di Taranto; Carola Giacobbe; Daniela Palma; Gabriella Iannuzzo; Marco Gentile; Ilenia Calcaterra; Ornella Guardamagna; Renata Auricchio; Matteo Nicola Dario Di Minno; Giuliana Fortunato
Journal:  Clin Genet       Date:  2021-08-03       Impact factor: 4.296

4.  Abdominal obesity, blood glucose and apolipoprotein B levels are the best predictors of the incidence of hypercholesterolemia (2001-2006) among healthy adults: the ATTICA study.

Authors:  Demosthenes B Panagiotakos; Christos Pitsavos; Yannis Skoumas; Yannis Lentzas; Labros Papadimitriou; Christina Chrysohoou; Christodoulos Stefanadis
Journal:  Lipids Health Dis       Date:  2008-03-31       Impact factor: 3.876

5.  Gender differences in the prevalence and development of metabolic syndrome in Chinese population with abdominal obesity.

Authors:  Shaoyong Xu; Bin Gao; Ying Xing; Jie Ming; Junxiang Bao; Qiang Zhang; Yi Wan; Qiuhe Ji
Journal:  PLoS One       Date:  2013-10-23       Impact factor: 3.240

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.