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      Gender-specific interactions of MTHFR C677T and MTRR A66G polymorphisms with overweight/obesity on serum lipid levels in a Chinese Han population

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          Abstract

          Background

          Little is known regarding the interactions of methylenetetrahydrofolate reductase ( MTHFR) C677T and methionine synthase reductase ( MTRR) A66G polymorphisms with overweight/obesity on serum lipid profiles. The aim of the current study was to explore interactions between the two polymorphisms and overweight/obesity on four common lipid levels in a Chinese Han population and further to evaluate whether these interactions exhibit gender-specificity.

          Methods

          A total of 2239 participants (750 females and 1489 males) were enrolled into this study. The genotypes of the MTHFR C677T and MTRR A66G were determined by a TaqMan assay. Overweight and obesity were defined as a body mass index between 24 and 27.99 and ≥ 28 kg/m 2, respectively. The interactions were examined by factorial design covariance analysis, and further multiple comparisons were conducted by Bonferroni correction.

          Results

          There was no significant difference in the genotypic and allelic frequencies between females and males ( MTHFR 677 T allele: 54.47 % for females and 54.40 % for males; MTRR 66G allele: 24.73 % for females and 24.71 % for males). Interaction between the MTHFR C677T polymorphism and overweight/obesity on serum triglyceride levels, and interaction between the MTRR A66G polymorphism and overweight/obesity on serum high-density lipoprotein cholesterol levels were detected in women ( P = 0.015 and P = 0.056, respectively). For female subjects with overweight/obesity, the serum triglyceride levels in MTHFR 677TT genotype [1.09 (0.78–1.50) mmol/L] were significantly higher as compared with MTHFR 677CC genotype [0.90 (0.60–1.15) mmol/L, P = 0.007], and the MTRR 66GG genotype carriers had higher serum high-density lipoprotein cholesterol levels than those with MTRR 66AG genotype (1.46 ± 0.50 vs. 1.19 ± 0.31 mmol/L, P = 0.058). Furthermore, in male subjects with overweight/obesity, the MTHFR 677CT genotype carriers had higher low-density lipoprotein cholesterol levels than those with MTHFR 677TT genotype (2.96 ± 1.07 vs. 2.74 ± 0.88 mmol/L, P = 0.015).

          Conclusions

          Our results indicate that there exist interactive effects of the MTHFR C677T and MTRR A66G polymorphisms with overweight/obesity on some lipid traits in Chinese Han population, and the effects were gender-specific.

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          Most cited references 48

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          A candidate genetic risk factor for vascular disease: a common mutation in methylenetetrahydrofolate reductase.

          Hyperhomocysteinaemia has been identified as a risk factor for cerebrovascular, peripheral vascular and coronary heart disease. Elevated levels of plasma homocysteine can result from genetic or nutrient-related disturbances in the trans-sulphuration or re-methylation pathways for homocysteine metabolism. 5, 10-Methylenetetrahydrofolate reductase (MTHFR) catalyzes the reduction of 5, 10-methylenetetrahydrofolate to 5-methyltetrahydrofolate, the predominant circulatory form of folate and carbon donor for the re-methylation of homocysteine to methionine. Reduced MTHFR activity with a thermolabile enzyme has been reported in patients with coronary and peripheral artery disease. We have identified a common mutation in MTHFR which alters a highly-conserved amino acid; the substitution occurs at a frequency of approximately 38% of unselected chromosomes. The mutation in the heterozygous or homozygous state correlates with reduced enzyme activity and increased thermolability in lymphocyte extracts; in vitro expression of a mutagenized cDNA containing the mutation confirms its effect on thermolability of MTHFR. Finally, individuals homozygous for the mutation have significantly elevated plasma homocysteine levels. This mutation in MTHFR may represent an important genetic risk factor in vascular disease.
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            Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults--study on optimal cut-off points of body mass index and waist circumference in Chinese adults.

             ,  Bei Zhou (2002)
            For prevention of obesity in Chinese population, it is necessary to define the optimal range of healthy weight and the appropriate cut-off points of BMI and waist circumference for Chinese adults. The Working Group on Obesity in China under the support of International Life Sciences Institute Focal point in China organized a meta-analysis on the relation between BMI, waist circumference and risk factors of related chronic diseases (e.g., high diabetes, diabetes mellitus, and lipoprotein disorders). 13 population studies in all met the criteria for enrollment, with data of 239,972 adults (20-70 year) surveyed in the 1990s. Data on waist circumference was available for 111,411 persons and data on serum lipids and glucose were available for more than 80,000. The study populations located in 21 provinces, municipalities and autonomous regions in mainland China as well as in Taiwan. Each enrolled study provided data according to a common protocol and uniform format. The Center for data management in Department of Epidemiology, Fu Wai Hospital was responsible for statistical analysis. The prevalence of hypertension, diabetes, dyslipidemia and clustering of risk factors all increased with increasing levels of BMI or waist circumference. BMI at 24 with best sensitivity and specificity for identification of the risk factors, was recommended as the cut-off point for overweight, BMI at 28 which may identify the risk factors with specificity around 90% was recommended as the cut-off point for obesity. Waist circumference beyond 85 cm for men and beyond 80 cm for women were recommended as the cut-off points for central obesity. Analysis of population attributable risk percent illustrated that reducing BMI to normal range ( or = 28) with drugs could prevent 15%-17% clustering of risk factors. The waist circumference controlled under 85 cm for men and under 80 cm for women, could prevent 47%-58% clustering of risk factors. According to these, a classification of overweight and obesity for Chinese adults is recommended.
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              Dyslipidemia in Obesity: Mechanisms and Potential Targets

              Obesity has become a major worldwide health problem. In every single country in the world, the incidence of obesity is rising continuously and therefore, the associated morbidity, mortality and both medical and economical costs are expected to increase as well. The majority of these complications are related to co-morbid conditions that include coronary artery disease, hypertension, type 2 diabetes mellitus, respiratory disorders and dyslipidemia. Obesity increases cardiovascular risk through risk factors such as increased fasting plasma triglycerides, high LDL cholesterol, low HDL cholesterol, elevated blood glucose and insulin levels and high blood pressure. Novel lipid dependent, metabolic risk factors associated to obesity are the presence of the small dense LDL phenotype, postprandial hyperlipidemia with accumulation of atherogenic remnants and hepatic overproduction of apoB containing lipoproteins. All these lipid abnormalities are typical features of the metabolic syndrome and may be associated to a pro-inflammatory gradient which in part may originate in the adipose tissue itself and directly affect the endothelium. An important link between obesity, the metabolic syndrome and dyslipidemia, seems to be the development of insulin resistance in peripheral tissues leading to an enhanced hepatic flux of fatty acids from dietary sources, intravascular lipolysis and from adipose tissue resistant to the antilipolytic effects of insulin. The current review will focus on these aspects of lipid metabolism in obesity and potential interventions to treat the obesity related dyslipidemia.
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                Author and article information

                Affiliations
                [1 ]Research Center of Environment and Non-Communicable Disease, School of Public Health, China Medical University, No.77 Puhe Road, Shenyang North New Area, Shenyang, 110122 People’s Republic of China
                [2 ]Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080 China
                [3 ]Division of Molecular Preventive Medicine, Shanghai Institute of Targeted Therapy and Molecular Medicine, Shanghai, 200433 China
                [4 ]Brain Disease Center, Tianjin Dagang Oil Field General Hospital, Tianjin, 300280 China
                Contributors
                zhixy90smile@126.com
                yangby23@mail.sysu.edu.cn
                fanfan0721ykl@163.com
                wangyanxun@genechina.com
                weijiantianjin@163.com
                qmzheng@mail.cmu.edu.cn
                ORCID: http://orcid.org/0000-0001-5135-7059, +86 24 23261744 , gfsun@cmu.edu.cn
                Journal
                Lipids Health Dis
                Lipids Health Dis
                Lipids in Health and Disease
                BioMed Central (London )
                1476-511X
                28 October 2016
                28 October 2016
                2016
                : 15
                27793164 5084372 354 10.1186/s12944-016-0354-9
                © The Author(s). 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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                Research
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                © The Author(s) 2016

                Biochemistry

                mthfr c677t, mtrr a66g, overweight, obesity, lipid, interaction, gender-specificity

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