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Association of BUD13 polymorphisms with metabolic syndrome in Chinese population: a case-control study
Lipids in Health and Disease volume 16, Article number: 127 (2017)
BUD13 homolog (BUD13), one of submits of the retention and splicing complex, was identified in yeast as a splicing factor that affected nuclear pre-mRNA retention. While more and more studies demonstrated that BUD13 played a potential role in the pathogenesis of metabolic syndrome (MetS). This objective was to reassess whether novel locus of BUD13 were linked to MetS and individual complements in the northeast of China.
A total of 3850 individuals were recruited in this case-control study, including 1813 MetS cases and 2037 healthy controls. The diagnostic criteria was according to the International Diabetes Federation (IDF). Metabolic complements such as waist circumference (WC), triglyceride, high-density lipoprotein cholesterol (HDL-C), systolic and diastolic blood pressure (SBP and DBP), and fasting glucose were measured. We explored the association between two novel single nucleotide polymorphism (SNPs) of BUD13 (rs7118999 and rs10488698) and MetS and its complements.
Using binary logistic regression analysis we found that there were no significant associations between SNPs and MetS in different heritance models (all P > 0.05). However, novel locus of BUD13 were linked to individual complements in MetS cases. Rs7118999 conferred to risk of WC (P = 0.016) and the carrier of TT might have higher susceptibility to MetS. While rs10488698 was associated with HDL-C (P = 0.001) and the carrier of TT was significantly associated with higher level of HDL-C.
We concluded that novel mutations in BUD13 did not confer risk for MetS in our study population, but these mutations changed the level of metabolic complements.
Metabolic syndrome (MetS) is a cluster of metabolic abnormalities, including raised triglyceride levels, low high-density lipoprotein cholesterol levels, raised blood pressure, and raised glucose levels . Available evidences show that MetS is strongly increasing the risk of developing cardiovascular diseases, type 2 diabetes and all caused mortality [2,3,4]. Due to escalating prevalence rates and its risk for the development of several chronic diseases, MetS has become the most important health challenge at the global scale .
Previous studies indicated that the pathogenesis of MetS might be caused by genetics background, environmental factors and gene-environment interaction [2, 5, 6]. Furthermore, Henneman et al.  found that the heritability of MetS based on family study was 10.6%, indicating that gene played essential in the development of MetS. Knowledge of exact genetic factors underlying MetS development might help to explain the etiology of MetS. BUD13 was submits of the retention and splicing complex in yeast , while Lin et al.  demonstrated that its variant significantly influenced on human development of MetS. Furthermore, Meta-analysis indicated multiple genes linking to MetS, mostly of genes involving in lipids levels, and the heritability of individual components of MetS were range from 21.9–42.9% [7, 9]. Increased studies noted that BUD13 involved in lipid metabolism [5, 10, 11], suggesting BUD13 might played an essential role in the pathogenesis of MetS and its traits through changing lipid levels.
To the best of our knowledge, we selected novel SNPs (rs7118999 and rs10488698) of the BUD13 to evaluate their association with MetS and MetS complements in a sample of the Jilin province, using a case-control study design.
Materials and methods
This study incorporated subjects from Jilin province in the northeast of China, in order to evaluate whether novel locus of BUD13 was linked to MetS and individual complements. The study of community-based consisted of 3850 participants, including 1813 MetS and 2037 non-MetS. MetS was diagnosed according to IDF criteria , Which required that subjects with three or more of the following conditions were diagnosed as MetS a) Central obesity with a waist circumference ≥ 80 cm in females and ≥85 cm in males for Chinese subjects b) Triglycerides ≥ 1.7 mmol/L or using drug treatment to elevate triglycerides c) HDL-C < 1.00 mmol/L in males and <1.30 mmol/L for females, or using drug treatment to reduce HDL-C d) SBP ≥ 130 mmHg and DBP ≥ 85 mmHg, or using antihypertensive drug treatment in a patient with a history of hypertension and e) fasting plasma glucose ≥5.6 mmol/L or using anti-diabetic drug therapy.
The study was approved by the ethics committee of the School of Public Health, Jilin University. All subjects signed the approved informed consent.
The two SNPs (rs7118999 and rs10488698) of BUD13 were selected using the haploview 4.2 software (http://hapmap.ncbi.nlm.nih.gov/), and the minor allele frequency of the above two SNPs was greater than 0.05 in Chinese population.
DNA was isolated from peripheral blood samples using a commercial DNA extraction kit (Hangzhou, China). SNP genotyping was determined by MALDI-TOF-MS (Sequenom, San, Diego, CA, USA) using the Mass ARRAY system, and completed genotyping reactions were divided into a 384-well spectro CHIP. The detection rate of rs7118999 was 93.1% (1687/1813) in MetS cases, and the detection rate of rs10488698 was 99.8% (1810/1813) in MetS cases.
All statistical analyses were conducted using the SPSS program (version 21.0), and the online SNP Stats (http://bioinfo.iconcologia.net/SNPStats) program. Intergroup comparisons of means using the Student’s t-test. We conducted the chi-square test to compare the difference from two categorical data. For each SNP, Hardy-Weinberg disequilibrium was tested by χ2 test with 1 degree of freedom. Binary logistic regression analysis was used to evaluate the association of the chosen SNP with MetS by adjusted age, gender, smoking and drinking. There are three inheritance models in this study, including codominant model (TT vs CT vs CC), dominant model (CT + TT vs CC) and recessive model (TT vs CT + CC). Furthermore, we estimated the association of the investigated SNP with individual components of MetS using general linear model (GLM) by adjusted age, gender, smoking and drinking. P-value ≤0.05 was considered statistically significant.
Characteristics of the subjects
The characteristics of the study population, 1813 MetS cases and 2037 non-MetS subjects, were shown in Table 1. The prevalence of MetS in our cross-sectional survey was 47.1%. The distribution of age and gender were well matched. Moreover, MetS subjects showed significantly increased risk levels for all of the MetS component variables (Waist circumference, triglyceride, systolic blood pressure and diastolic blood pressure, high density lipoprotein, fasting glucose) and the habit of smoking and drinking (all P < 0.001).
Associations with MetS risk and quantitative metabolic traits
The distributions of rs7118999 and rs10488698 conformed to Hardy-Weinberg equilibrium among the subjects (P = 0.42, 0.73, respectively). The comparisons of genotype distributions of the polymorphisms in the BUD13 between subjects with and without MetS using different model of inheritance were shown in Table 2. We then explored the association of each SNP and MetS using binary logistic regression analysis of risk factors with adjustment for age, gender, smoking and drinking. In the case and control groups, no significant associations between SNPs and MetS were observed in different heritance models.
As shown in Table 3, we also explored to association between novel SNPs and metabolism complements in with MetS subjects. Rs7118999 associated with WC in MetS cases (P = 0.016) and the carrier of TT was significantly associated with higher WC. However, rs10488698 was associated with HDL-C in MetS cases (P = 0.001) and the carrier of TT was significantly associated with higher level of HDL-C. However, our results did not exhibit association between the two SNPs with the rest of MetS components (P>0.05).
This study incorporated subjects from community-based cross-sectional study with a sample of Jilin province in the northeast of China. According to the IDF diagnostic criteria , the prevalence of MetS was 47.1% in Jilin province in 2012. This prevalence was higher than the prevalence reported in China in 2010 (33.9%) . Here, we demonstrated that novel mutations in BUD13 did not confer risk for MetS among Jilin population, but these mutations changed the level of metabolic complements.
In this literature, we for the first time explored association between novel SNPs in BUD13 and MetS. It has been noted that genetic variants are linking to the development of MetS in different populations. Previous literatures showed that SNPs of rs10790162 [10, 14, 15], rs11216129  and rs623908  contributed to the susceptibility for MetS in Chinese [1, 2], India  and Taiwanese population . In this study, the distribution of genotype frequencies of rs7118999 and rs10488698 was no difference between subjects with and without MetS in different model of inheritance (P > 0.05).
Furthermore, novel locus of BUD13 were linked to individual complements in MetS cases. The carrier of TT in rs7118999 conferred to risk of MetS by increasing the level of WC. While rs10488698 might a protected factor by increasing the level of HDL-C. Similarly, many studies also investigated that BUD13 variants associated with triglyceride [5, 10, 14, 16, 17], LDL , total cholesterol  and HDL-C , but not discovered rs12286037 and rs28927680 with HDL in Finish . Therefore, the correlation of BUD13 variants with serum lipid levels was not yet clear. Firstly, factors like age, gender, ethnicity, lifestyle and genetic background influenced the association between SNPs with serum lipid levels . Secondly, inter-genetic variant might play an important role in the level of serum lipid . The gene regions of APOA1/C3/A4/A5/BUD13 and BUD13/ZNF were significantly influencing the association with lipid metabolism [10, 16, 21,22,23].
There are certain limitations to our study. Firstly, our studies subjects were coming from the cross-sectional study, which might limit its ability to detect association between BUD13 and MetS, largely because of bias . Secondly, the etiology of MetS might be caused by multiple factors, such as genetics background, nutritional status and environmental factors. Our study only discussed associations between gene and MetS in the northeast of China, so we could not evaluate the same association in other population. Lastly, the detection rate of SNPs might influence the distribution of MetS and its complements. Therefore, these peculiar characteristics might be contributing factors to the findings of our study.
We indicated that novel mutations in BUD13 did not confer risk for MetS in our study population, but these mutations changed the level of metabolic complements. The carrier of TT in rs7118999 conferred to risk of MetS by increasing the level of WC. While the carrier of TT in rs10488698 might be protective factor for MetS, who had high level of HDL-C. Considering the complex environment and genetic disease complex mechanism, independent replication studies are needed to provide further insights into the role of the BUD13.
diastolic blood pressure
high-density lipoprotein cholesterol
systolic blood pressure
single nucleotide polymorphism
Alberti KGMM, Zimmet P, Shaw J. The metabolic syndrome—a new worldwide definition. Lancet. 2005;366:1059–62.
Kaur J. A comprehensive review on metabolic syndrome. Cardiol Res Pract. 2014;2014:943162.
Grundy SM. Metabolic syndrome pandemic. Arterioscler Thromb Vasc Biol. 2008;28:629–36.
Prasad H, Ryan DA, Celzo MF, Stapleton D. Metabolic syndrome: definition and therapeutic implications. Postgrad Med. 2012;124:21–30.
Lin E, Kuo PH, Liu YL, Yang AC, Kao CF, Tsai SJ. Association and interaction of APOA5, BUD13, CETP, LIPA and health-related behavior with metabolic syndrome in a Taiwanese population. Sci Rep. 2016;6:36830.
Pollex RL, Hegele RA. Genetic determinants of the metabolic syndrome. Nat Clin Pract Cardiovasc Med. 2006;3:482–9.
Henneman P, Aulchenko YS, Frants RR, van Dijk KW, Oostra BA, van Duijn CM. Prevalence and heritability of the metabolic syndrome and its individual components in a Dutch isolate: the Erasmus Rucphen family study. J Med Genet. 2008;45:572–7.
Wahl MC, Luhrmann R, Becker S, Zweckstetter M, Tripsianes K, Friberg A, et al. A novel protein-protein interaction in the RES (REtention and splicing) complex. Nat Struct Mol Biol. 2014;289:28640–50.
Povel CM, Boer JM, Reiling E, Feskens EJ. Genetic variants and the metabolic syndrome: a systematic review. Obes Rev. 2011;12:952–67.
Aung LH, Yin RX, Wu DF, Wang W, Liu CW, Pan SL. Association of the variants in the BUD13-ZNF259 genes and the risk of hyperlipidaemia. J Cell Mol Med. 2014;18:1417–28.
O'Brien SE, Schrodi SJ, Ye Z, Brilliant MH, Virani SS, Brautbar A. Differential lipid response to statins is associated with variants in the BUD13-APOA5 Gene region. J Cardiovasc Pharmacol. 2015;66:183–8.
Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International diabetes Federation task force on Epidemiology and prevention; National Heart, Lung, and Blood Institute; American Heart Association; world Heart Federation; International atherosclerosis society; and International Association for the Study of obesity. Circulation. 2009;120:1640–5.
Lu J, Wang L, Li M, Xu Y, Jiang Y, Wang W, et al. Metabolic Syndrome among Adults in China - The 2010 China Noncommunicable Disease Surveillance. J Clin Endocrinol Metab. 2016:jc20162477.
Aung LH, Yin RX, Wu JZ, Wu DF, Wang W, Li H. Association between the MLX interacting protein-like, BUD13 homolog and zinc finger protein 259 gene polymorphisms and serum lipid levels. Sci Rep. 2014;4:5565.
Pranav Chand R, Kumar AS, Anuj K, Vishnupriya S, Mohan RB. Distinct patterns of Association of Variants at 11q23.3 chromosomal region with coronary artery disease and dyslipidemia in the population of Andhra Pradesh, India. PLoS One. 2016;11:e0153720.
Braun TR, Been LF, Singhal A, Worsham J, Ralhan S, Wander GS, et al. A replication study of GWAS-derived lipid genes in Asian Indians: the chromosomal region 11q23.3 harbors loci contributing to triglycerides. PloS one. 2012:7:e37056.
Laston SL, Voruganti VS, Haack K, Shah VO, Bobelu A, Bobelu J, et al. Genetics of kidney disease and related cardiometabolic phenotypes in Zuni Indians: the Zuni kidney project. Front Genet. 2015;6:6.
Sabatti C, Service SK, Hartikainen AL, Pouta A, Ripatti S, Brodsky J, et al. Genome-wide association analysis of metabolic traits in a birth cohort from a founder population. Nat Genet. 2009;41:35–46.
Khan RJ, Gebreab SY, Sims M, Riestra P, Xu R, Davis SK. Prevalence, associated factors and heritabilities of metabolic ndrome and its individual components in African Americans: the Jackson Heart Study. BMJ open. 2015;5(10):e008675.
Below JE, Parra EJ, Gamazon ER, Torres J, Krithika S, Candille S, et al. Meta-analysis of lipid-traits in Hispanics identifies novel loci, population-specific effects, and tissue-specific enrichment of eQTLs. Sci Rep. 2016;6:19429.
Wei W, Gyenesei A, Semple CA, Haley CS. Properties of local interactions and their potential value in complementing genome-wide association studies. PLoS One. 2013;8:e71203.
Wu Y, Yu Y, Zhao T, Wang S, Fu Y, Qi Y, et al. Interactions of environmental factors and APOA1-APOC3-APOA4-APOA5 Gene cluster Gene polymorphisms with metabolic syndrome. PLoS One. 2016;11:e0147946.
Lamina C, Haun M, Coassin S, Kloss-Brandstatter A, Gieger C, Peters A, et al. A systematic evaluation of short tandem repeats in lipid candidate genes: riding on the SNP-wave. PLoS One. 2014;9:e102113.
Manolio TA, Baileywilson JE, Collins FS. Genes, environment and the value of prospective cohort studies. Nat Rev Genet. 2006;7:812–20.
This work was supported by a competitive grant from the Scientific Research Foundation of the Health Bureau of Jilin Province, China (2011Z116).
Availability of data and materials
LZ, YY, YW, YZ, and CK designed and performed the study. LZ, YW, YZ, and YY analyzed the data. LZ drafted the manuscript. YY, MW, YS and XL participated in revising draft of the manuscript. All authors approved the final version of the manuscript.
The authors declare that they have no competing interests.
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The study was approved by the ethics committee of the School of Public Health, Jilin University. All subject signed the approved informed consent.
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Zhang, L., You, Y., Wu, Y. et al. Association of BUD13 polymorphisms with metabolic syndrome in Chinese population: a case-control study. Lipids Health Dis 16, 127 (2017). https://doi.org/10.1186/s12944-017-0520-8
- Metabolic syndrome
- Single nucleotide polymorphism