|Year : 2015 | Volume
| Issue : 2 | Page : 135-142
Strategy planning for shortening the list of the metabolic syndrome candidate genes
Assistant Prof and Head of Genetic Lab, Cellular and Molecular Endocrine Research Center, Shahid Beheshti University of Medical Science, Iran
|Date of Web Publication||5-Jul-2017|
M S Daneshpour
Assistant Prof and Head of Genetic Lab, Cellular and Molecular Endocrine Research Center, Shahid Beheshti University of Medical Sciences
Source of Support: None, Conflict of Interest: None
Most diseases involve many genes in complex interactions, in addition to environmental influences. The genetic susceptibility to a particular disease due to the presence of one or more gene mutations, and/or a combination of alleles need not necessarily be abnormal. Understanding genetic predisposition to disease and knowledge of lifestyle modifications that either exacerbates the condition or that lessen the potential for diseases is necessary for the societies to make informed choices. The aim of this narrative review is to identify an optimal candidate gene and its single nucleotide polymorphism in metabolic syndrome. The prevalence of non-communicable disorders such as metabolic syndrome (MetS) is high in developing countries such as Iran. The Tehran Lipid and Glucose Study (TLGS) was one of the first studies reporting this high incidence. The present review aims to discover the genetic variant reported in association with MetS. The database for genotypes and phenotypes (dbGaP) and the database for genetic associations and human genome (HuGE navigator) were utilized in order to search for genes and their corresponding polymorphisms related to MetS. Additionally, an electronic literature search for other Iranian studies and the genetic aspect of TLGS was completed using PubMed. The results distinguished six of the most important genetic regions found to have strong association with MetS.
Keywords: Tehran Lipid and Glucose Study, Metabolic syndrome, Genetic, Iran
|How to cite this article:|
Daneshpour M S. Strategy planning for shortening the list of the metabolic syndrome candidate genes. Acta Med Int 2015;2:135-42
| Introduction|| |
The incidence of non-communicable disorders (NCDs) is increasing worldwide. These diseases result from major risk factors including smoking, hypertension, dyslipidemia and impaired glucose homeostasis levels. Metabolic syndrome (MetS) is the combination of several risk factors giving rise to cardiovascular disease and type2 diabetes mellitus. There are some controversies toward definition of MetS., The factors associated with MetS are obesity, hypertriglyceridemia, glucose intolerance, hypertension, and insulin resistance., It has been shown that MetS is a risk factor for cardiovascular disease (CVD), diabetes and also elevated risk for mortality.
Numerous studies and reviews have published the prevalence of metabolic syndrome in their population.,,, Moreover, this syndrome occurs in individuals and inside families.,,, The heritability frequency of MetS is about 10% to 30%, and as a result, it is believed that metabolic syndrome is partially inheritable.,,,, Each of the factors of the MetS is associated with several genes and SNPs with pleiotropic effects.,
In order to study the genetic pattern of such complex traits we need to compare the association between genetic results from different databases. Because of the rapid increase in human genetic studies in the field of health related research, a large number of genetic databases have been established. In these databases, publications that are related to population based human genes studies extracted from trusted database and maintained. Generally, researchers need access to information at the molecular and the population level. Genetic polymorphism provide a starting point for investigating the functions of complex biological systems at molecular level but at the population level, data on genetic variation and association are used by epidemiologist for estimating the potential health impact of genetically directed interventions.
The database for Genotypes and Phenotypes (dbGaP) lists 38 studies that studied MetS as a trait. Tehran Lipid and Glucose Study (TLGS) also provide a large dataset for future health studies on Tehranian population. For example, a large clinical trial cohort is under way to assess the effects of several measures (i.e., education, dietary modification, physical activity, and metformin) on preventing the development of metabolic syndrome in this population. In addition, further biochemical, immunologic and genetic studies using sera bank and DNA bank for this study may shed more light on the etiology, pathogenesis and alterations in body composition related to NCDs and their risk factors.
In the present review, with respect to MetS studies among TLGS and Iranian population, we aimed to extract the short list of MetS candidate genes from articles and different genetic database such as HuGE navigator and PheGenI in order to shed more light on the genetic aspect of this syndrome especially for Iranian population.
An electronic literature search was conducted using, PubMed, HuGE Navigator and Phenotype-Genotype Integrator (PheGenI). In HuGE Navigator the phenopedia track were used, this database consist of genetic associations information related to human genome.
In all selected database, the search term “metabolic syndrome” was used. This search retrieved articles on the association between MetS and any genetic variant. The latest search was undertaken on 1nd of Janurary 2014. As HuGE Navigator only retrieves articles published since 2001, an additional PubMed search was done. For the PubMed search, the search term “metabolic syndrome” with limits on publication date from 1987/1/1 to 2013/12/31' was used.
The results obtained through the search in HuGE navigator were merged with nominated genes obtained from selected articles found in PubMed data base. In the next step, for evaluation of genes associated with the metabolic syndrome and its risk factors, gene prospector section of HuGE navigator database were used. In the last step, the Phenotype-Genotype Integrator (PheGenI) was used to search for genes and their corresponding polymorphisms related to the MetS in order to discover genetic variant associated with MetS. In fact, this database merges NHGRI genome-wide association study (GWAS) catalog data with several databases housed at the National Center for Biotechnology Information (NCBI), including Gene, dbGaP, OMIM, GTEx and dbSNP.
Finally, the candidate genes associated with MetS were selected by merging the results obtained through the search in PubMed, HuGE navigator and PheGenI, which leads to the selection of four genes and two cluster regions with the highest number of GWAS and Meta-analysis studies as well as the highest P-values.
The selected genes for this review were chosen from the entire 948 articles found in HuGE navigator. The nominated genes and single nucleotide polymorphisms (SNPs) extracted from PheGenI and HuGE navigator. For searching the PheGenI database the search term was “metabolic syndrome x [text MesH]” and its estimated 30 associated traits (listed in [Table 1]) were used.
Studies that included metabolic syndrome as outcome, published in English, original research and conducted in human population were included in the study. In order to evaluate the genetic study in Iran and Tehran lipid and glucose study (TLGS), we focused on the electronic literature search base on the studies done in TLGS and Iran which were implemented using PubMed. For this part, the search term was “metabolic syndrome” and “Tehran Lipid and Glucose Study”. From 123 articles which were found; 63 of them were eligible for inclusion in this study. Furthermore, in order to search for articles published in Iran, the search term was “metabolic syndrome” and “Iran”. According to this criteria, 359 articles were found and among them 308 article had appropriate criteria to be included in present article. The detail of paper selection is mentioned in [Figure 1].
|Figure 1: Material search criteria, (a) Beads on PubMed, (b) Beads on dbGap Navigator|
Click here to view
Genetic Factors Underlying Metabolic Syndrome
Studying the genetic factors underlying metabolic syndrome may help to explain why the features of MetS frequently co-occur with one individual. Various studies documented that heritability plays a valuable role for about 10-30%, of the incidence of metabolic syndrome., Genetics familial aggregation studies of the metabolic syndrome among Iranian families have showed that affected mothers have more influence on the future risk for their children than fathers with MetS. Genetic analysis searching for the associated genetic region with metabolic syndrome in the TLGS study revealed the important role of the lipid metabolism.,,,,,,,,,,
Many studies in this field present large amount of candidate genes in the relevant database. Among the risk factors of MetS, we selected four original MetS components: Obesity, diabetes, hypertension and lipids. For phenotype selection in PheGenI, 30 traits were chosen and after the analysis, 21 of them were in common results with MetS [Table 1]. After finding the common variation between traits and MetS, omitting the repeated SNPs, 173 variations were remained (Supplementary [Table 2]).
Associated trait candidate genes in relation with MetS as well as variations in the MetS components in the mentioned genes were studied in details [Table 1]. In order to replicate the valuable candidate variations in MetS in TLGS study, we need to overview the available evidence on the genetic of MetS.
The Most Important Genes Studied for Metabolic Syndrome
One of the controversial gene which rise susceptibility of MetS is the FTO (fat mass and obesity associated) gene. 2-oxoglutarate-dependent nucleic acid demethylase is present in several tissues and translates by the FTO gene. Most of the human genetic studies showed association with FTO genetic variations and type 2 diabetes,,, obesity,, and MetS. In most association studies and meta-analyses, a variation (rs9939609) is on the top with odds ratio of 1.19 (95% CI 1.12–1.27; P = 1.38 χ 10–7). In addition, there were significant odd ration for rs1421085 and rs8050136,,, in relation with MetS.,
The cholesterol ester transfer protein (CETP) is located on chromosome 16 and contributes in transmission of cholesterol esters in HDL-C to TG-rich lipoproteins. As a result of this process, HDL-C is reduced from plasma. It has been shown that CETP is related to metabolic syndrome. This gene has been considered in different GWAS studies. These GWA Studies showed that some of the CETP gene variations are verified to be susceptible loci in metabolic syndrome., Numerous variations in CETP gene have been studied. Among them, CETP (rs708272) Taq1B (G →A) is one of the most studied variations. Moreover, other SNPs such as rs173539 (P = 9.1 x10-9), rs3764261 (P = 3.3 x10-13), and rs9939224 (P= 6.9 x10-12) are found to be associated with components of metabolic syndrome. These polymorphism increase the HDL-C and reduce triglyceride levels and thereby CETP activity., CETP is widely expressed in the peripheral tissues and liver. Furthermore, rs247617 (P= 9.31 x10-60) have been proved to have a connection with HDL, which is one components of metabolic syndrome.
This gene cluster region is located on chromosome 11q23. Lipid elements of the metabolic syndrome such as triglyceride, cholesterol and HDL-C had been proven to be associated with this region.,,, Among all apolipoproteins in this gene cluster, APOA5 have been shown to have more connection with HDL-C. This gene cluster is proved to be associated with MetS in a GWAS in four study samples.
APOA1 is located on chromosome 11 at the described gene cluster. The product of this gene is a ligand for HDL binding to cellular receptors such as ABCA1. ATP-binding cassette transporter A1 (ABCA1) regulates transport of cholesterol and phospholipids throughout cell membranes and subsequently delivers them to apolipoprotein (APO) A1 molecules. ABCA1 proteins bind ATP so that the transition process occurs. The other role of ABCA1 is HDL formation and is expressed in pancreatic beta cells. Three polymorphisms in this gene have been reported to be associated with HDL level. These variations are rs670, rs5069 and rs5070. Disorders in apolipoprotein are often linked to Hyperlipidemia.
Apolipoprotein C3 (ApoC3) is secreted from liver and intestine. ApoC3 appears to have restraining effect on LPL. Also, triglyceride rich lipoproteins and HDL particles contain apolipoprotein C3. The variations connected to APOC3 gene are rs2854116 (-455T->C) and rs2854117 (–482C->T). The first one is responsible for high triglyceride concentration and the latter is associated with insulin resistance and dyslipidemia.
The human APOA5 contains three introns and four exons. APOA5 product is called APOA5 and is mainly detectable in very low-density lipoprotein (VLDL), high- density lipoprotein (HDL) and chylomicrons. The function of APOA5 in plasma triglyceride level regulation and inhibition of very low-density lipoprotein production have been proven in human and other organisms.,, One of the variations in this region is rs2266788 (P= 2.000 x 10-16), which has been shown to have pleiotropic associations among different traits including HDLC-TG, MetS, TG-BP and WC-TG. The other variation that has been considered in many studies including three meta-analysis studies is called T1131C (rs662799).,,, MetS development was considerably associated with the C allele of rs662799. Finally, the G allele of C56G (rs3135506) was correlated with metabolic syndrome in diverse studies. It has been shown that with regards to MetS, different populations associate with different polymorphisms in APOA5 gene.
ZNF259 (Zinc finger protein 259) and BUD13 (BUD13 homolog [S. cerevisiae]) are both map amongst APOA cluster on chromosome 11. BUD13 rs10790162 (P= 7.000 x 10-16) and ZNF259 rs2075290 (P= 2.000 x 10-9) have been proved to be notably correlated with some elements of MetS including TG, blood pressure HDL-C and glucose. Also, BUD13 rs11825181 (P= 3.000 x 10-9) is associated with traits such as TG and blood pressure. ZNF259 rs11820589 is associated with two individual binary traits which are TG and HDLC. Two other polymorphisms in ZNF259 are rs11823543 (P= 3.000 x 10-9) and rs12286037 (P= 1.000 x 10-8); the first is associated with TG-BP and the later with TG-GLUC.
The glucokinase regulator gene (GCKR) is mainly expressed in liver hepatocytes and pancreatic beta cells. The product of this gene is called glucokinase regulator protein (GKRP), which is responsible for regulation of glycolysis. Positive and negative associations between rs780094 (P= 6.000 x 10-20) and MetS components had been shown, as the positive relations are with TG and TG/HDL/WC and the negative with glucose concentration. Also, amongst different variations, the minor T-allele SNP is mostly studied. The other polymorphism in this gene is rs780093 (P= 2.000 x 10-12) and this SNP is associated with TG, WC and blood pressure., GCKR has been shown to be associated with metabolic syndrome in many aspects of its components. Some studies showed evidence of connection with lower insulin levels, fasting glucose and insulin resistance. Also, GCKR is associated with elevated serum triglyceride and 2-hour OGTT glucose levels.
The results showed that, ADIPOQ has the highest score in HuGE Navigator in terms of number of publications compares to other genes. Adiponectin is a cytokine and originated from adipose tissue. The adiponectin gene is located on chromosome 3q27. It has various functions such as anti-inflammation, anti-diabetic and anti-atherogenesis. Lower level of adiponectin is linked to metabolic syndrome, type 2 diabetes, insulin resistance and obesity. The gene encoding adiponectin is called ADIPOQ. As a result, polymorphisms in ADIPOQ gene and its receptors might act as mediator of metabolic syndrome. This association reported in 3 genome wide association study.,, and the relation confirmed in two studies using meta-analysis,,,, reported this associations. The most studied variation in ADIPOQ gene is ADIPOQ G276T (rs1501299). This SNP also had conflicting results on MetS and insulin resistance in different populations, On the other hand, several studies in China showed an association of ADIPOQ T45G (rs2241766) with MetS in their population. Thirteen studies were enclosed in this meta-analysis. However, these results are also unreliable due to their small sample sizes.,,, In overall, despite lots of valid articles, impressive p-value for ADIPOQ SNPs didn't find.
SNPs studied in Iran and TLGS
Because of the high prevalence of metabolic syndrome in Iran and also the first prevalence report was from the TLGS, some biochemical and genetic studies have done in this population. We will discuss some genetic finding here.
There are some controversies concerning the effect of ADIPOQ gene on Mets in different populations. Some studies in Iranian population also examine different single nucleotide polymorphisms at this gene locus. Esteghamati et al investigated the effect of two adiponectin SNPS on coronary artery disease and type2 diabetes. These polymorphisms are +45T>G and +276G>T. They found an association with T allele of +276G>T and reduced risk of CAD in type2 diabetes patients. Moreover, they reported two haplotypes, 45T-276T and 45G-276T, to be associated with decreased risk of CAD.
Another study also assessed the correlation between these SNPs and type2 diabetes in obese individuals. This study showed that, SNP +45G>T is more related than the other SNP to the chance of type2 diabetes in obese individuals.
A study in city of Rafsanjan in the southeast of Iran, besides the mentioned Variations, tested -11391G>A adiponectin SNP and its association with some component of MetS. This study stated that the observed genotypes are specific in genders regarding body mass index and waist circumference.
As, low HDL-C is the most common lipid disorder in Iranian population, some study have looked for genes and their variations responsible for this disease. ABCA1 gene is considered to have an association with reduced plasma HDL levels. A study in Tehran, Iran investigated rs2230806 SNP and its relation to lipid levels. This polymorphism is due to nucleotide change at position 1051 on chromosome 9. They observed no significant association with this polymorphism and lipid levels excepting ApoA1 concentration. As a result, this polymorphism is not a good marker to investigate HDL-C in our population.
Apo A1/C3/A5 gene cluster
The APOA1/C3/A5 gene cluster has been studied in TLGS population. Five SNPs of this gene cluster region were analyzed according to their connection to lipid levels. This study showed that the concentrations of TG, HDL-C, HDL2, ApoAI, and ApoB may be changed in the presence of some alleles of these SNPs. The results demonstrated that the lipid levels might somewhat regulate by haplotypes within APOA1/C3/A5 gene cluster.
To analyze the CETP gene a variation on the first intron of the CETP gene have been studied. This polymorphism is called TaqIB (Rs708272) and is correlated with elevated HDL-C concentrations and reduced CETP activity. The results have demonstrated that this SNP is highly associated with elevated HDL_C levels.
| Discussion|| |
Given the polygenic nature and multi-level complexity of dyslipidemia and MetS, a better understanding of the genetic determinants of each intermediate phenotype as well as the collective integration of these traits as unifying syndromes is needed, which will require more elegant statistical modeling methods and, perhaps, a paradigm shift in the way in which we think about dissecting genetic and environmental factors in complex traits.
It is obvious that there is considerable overlap between genetic variants associated with HDL-C, LDL-C and TG levels as well MetS as a unifying trait. As a result, there is great need to understand not only the aggregate effects of multiple variants in each of these genes but to also understand how the effects of variation in one gene are modified in the presence of other genes.
The present paper has summarized the candidate gene list of metabolic syndrome. It has also reviewed the most important genetic finding in this field in Iran and TLGS. According to our findings, four candidate genes are on the top of the association results and some SNPs replicated more than one time with significant association in mentioned regions [Table 2]. Lipid metabolism pathways have the key role in the genetic background of the MetS. Identifying major genes that are responsible for the metabolic syndrome may improve the medical care and clinical decision making for treating individuals with metabolic syndrome, and eventually may lead to personalized medicine in which treatment is tailored genetically to the patient's needs. In the years to come, we will require to do genetic replicate studies of tens of thousands of patients with metabolic syndrome. The present candidate regions is a respectable start to replicate genetic studies in large affected people in TLGS study which we hope leads us to improve our medical care in this field.
| References|| |
Boutayeb, A., S. Boutayeb, and W. Boutayeb, Multi-morbidity of non communicable diseases and equity in WHO Eastern Mediterranean countries. Int J Equity Health, 2013. 12(1): p. 60.
Hadaegh, F., et al., Do different metabolic syndrome definitions predict cerebrovascular events and coronary heart disease independent of their components?: 9 years follow-up of the tehran lipid and glucose study. Stroke, 2012. 43(6): p. 1669–71.
Alberti, K.G., 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(16): p. 1640–5.
Azizi, F., et al., Prevalence of metabolic syndrome in an urban population: Tehran Lipid and Glucose Study. Diabetes Res Clin Pract, 2003. 61(1): p. 29–37.
Reaven, G.M. and Y.D. Chen, Role of insulin in regulation of lipoprotein metabolism in diabetes. Diabetes Metab Rev, 1988. 4(7): p. 639–52.
Povel, C.M., J.M. Boer, and E.J. Feskens, Shared genetic variance between the features of the metabolic syndrome: heritability studies. Mol Genet Metab, 2011. 104(4): p. 666–9.
Zarkesh, M., et al., Heritability of the metabolic syndrome and its components in the Tehran Lipid and Glucose Study (TLGS). Genet Res (Camb), 2012. 94(6): p. 331–7.
Zarkesh, M., et al., The relationship between metabolic syndrome, cardiometabolic risk factors and inflammatory markers in a Tehranian population: the Tehran Lipid and Glucose Study. Intern Med, 2012. 51(24): p. 3329–35.
Azizi, F., et al., Familial Aggregation of the Metabolic Syndrome: Tehran Lipid and Glucose Stady. Ann Nutr Metab, 2009. 54(3): p. 189–96.
Povel, C.M., et al., Single nucleotide polymorphisms (SNPs) involved in insulin resistance, weight regulation, lipid metabolism and inflammation in relation to metabolic syndrome: an epidemiological study. Cardiovasc Diabetol, 2012. 11: p. 133.
Povel, C.M., et al., Genetic variants in lipid metabolism are independently associated with multiple features of the metabolic syndrome. Lipids Health Dis, 2011. 10: p. 118.
Povel, C.M., et al., Genetic variants and the metabolic syndrome: a systematic review. Obes Rev, 2011. 12(11): p. 952–67.
D Welter, J.M., J Morales, T Burdett, P Hall, H Junkins, A Klemm, P Flicek, T Manolio, L Hindorff, H Parkinson The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. 2014. 42.
Phenotype-Genotype Integrator. 2013, Bethesda: National Center for Biotechnology Information.
Povel, C.M., et al., Metabolic syndrome model definitions predicting type 2 diabetes and cardiovascular disease. Diabetes Care, 2013. 36(2): p. 362–8.
Azizi, F., et al., Familial aggregation of the metabolic syndrome: Tehran Lipid and Glucose Study. Ann Nutr Metab, 2009. 54(3): p. 189–96.
Daneshpour, M.S., et al., Allele frequency distribution data for D8S1132, D8S1779, D8S514, and D8S1743 in four ethnic groups in relation to metabolic syndrome: Tehran Lipid and Glucose Study. Biochem Genet, 2009. 47(9-10): p. 680–7.
Daneshpour, M.S., et al., Haplotype analysis of Apo AI-CIII-AIV gene cluster and lipids level: Tehran Lipid and Glucose Study. Endocrine, 2011. 41(1): p. 103–10.
Daneshpour, M.S., et al., Haplotype frequency distribution for 7 microsatellites in chromosome 8 and 11 in relation to the metabolic syndrome in four ethnic groups: Tehran Lipid and Glucose Study. Gene, 2012. 495(1): p. 62–4.
Daneshpour, M.S., et al., 8q24.3 and 11q25 chromosomal loci association with low HDL-C in metabolic syndrome. Eur J Clin Invest, 2011. 41(10): p. 1105–12.
Faam, B., et al., Association between TPO gene polymorphisms and Anti-TPO level in Tehranian population: TLGS. Gene, 2012. 498(1): p. 116–9.
Kashani Farid, M.A., et al., Association between CETP Taq1B and LIPC -514C/T polymorphisms with the serum lipid levels in a group of Tehran's population: a cross sectional study. Lipids Health Dis, 2010. 9: p. 96.
Sarbakhsh, P., et al., Logic regression analysis of association of gene polymorphisms with low HDL: Tehran Lipid and Glucose Study. Gene, 2013. 513(2): p. 278–81.
Zadeh-Vakili, A., et al., Genetic polymorphism of vitamin D receptor gene affects the phenotype of PCOS. Gene, 2013. 515(1): p. 193–6.
Daneshpour, M., et al., Association of genetic variants of Apo E gene with TG, Apo B and LDL-C in Tehranian individuals with or without Combined HDL/LDL-Cholesterol Phenotype, in 11th International Congress on Obesity. 2010: Stockholm.
Vasan, S.K., et al., FTO genetic variants and risk of obesity and type 2 diabetes: A meta-analysis of 28,394 Indians. Obesity (Silver Spring), 2014.
Kalnina, I., et al., Polymorphisms in FTO and near TMEM18 associate with type 2 diabetes and predispose to younger age at diagnosis of diabetes. Gene, 2013. 527(2): p. 462–8.
Freathy, R.M., et al., Common variation in the FTO gene alters diabetes-related metabolic traits to the extent expected given its effect on BMI. Diabetes, 2008. 57(5): p. 1419–26.
Attaoua, R., et al., Association of the FTO gene with obesity and the metabolic syndrome is independent of the IRS-2 gene in the female population of Southern France. Diabetes Metab, 2009. 35(6): p. 476–83.
Cheung, C.Y., et al., Genetic variants associated with persistent central obesity and the metabolic syndrome in a 12-year longitudinal study. Eur J Endocrinol, 2011. 164(3): p. 381–8.
Steemburgo, T., et al., The rs7204609 polymorphism in the fat mass and obesity-associated gene is positively associated with central obesity and microalbuminuria in patients with type 2 diabetes from Southern Brazil. J Ren Nutr, 2012. 22(2): p. 228–36.
Wang, H., et al., Genetic variants in FTO associated with metabolic syndrome: a meta- and gene-based analysis. Mol Biol Rep, 2012. 39(5): p. 5691–8.
Sjogren, M., et al., The search for putative unifying genetic factors for components of the metabolic syndrome. Diabetologia, 2008. 51(12): p. 2242–51.
Gaio, V., et al., Genetic variation at the CYP2C19 gene associated with metabolic syndrome susceptibility in a South Portuguese population: results from the pilot study of the European Health Examination Survey in Portugal. Diabetol Metab Syndr, 2014. 6(1): p. 23.
Hotta, K., et al., Association of variations in the FTO, SCG3 and MTMR9 genes with metabolic syndrome in a Japanese population. J Hum Genet, 2011. 56(9): p. 647–51.
Zhou, D., et al., Common variant (rs9939609) in the FTO gene is associated with metabolic syndrome. Mol Biol Rep, 2012. 39(6): p. 6555–61.
Kraja, A.T., et al., A bivariate genome-wide approach to metabolic syndrome: STAMPEED consortium. Diabetes, 2011. 60(4): p. 1329–39.
Zabaneh, D. and D.J. Balding, A genome-wide association study of the metabolic syndrome in Indian Asian men. PLoS One, 2010. 5(8): p. e11961.
Ranjith, N., R.J. Pegoraro, and L. Rom, Lipid profiles and associated gene polymorphisms in young Asian Indian patients with acute myocardial infarction and the metabolic syndrome. Metab Syndr Relat Disord, 2009. 7(6): p. 571–8.
Kristiansson, K., et al., Genome-wide screen for metabolic syndrome susceptibility Loci reveals strong lipid gene contribution but no evidence for common genetic basis for clustering of metabolic syndrome traits. Circ Cardiovasc Genet, 2012. 5(2): p. 242–9.
Boes, E., et al., Genetic-epidemiological evidence on genes associated with HDL cholesterol levels: a systematic in-depth review. Exp Gerontol, 2009. 44(3): p. 136–60.
Teslovich, T.M., et al., Biological, clinical and population relevance of 95 loci for blood lipids. Nature, 2010. 466(7307): p. 707–13.
Kathiresan, S., et al., Common variants at 30 loci contribute to polygenic dyslipidemia. Nat Genet, 2009. 41(1): p. 56–65.
Villarreal-Molina, M.T., et al., Association of the ATP-binding cassette transporter A1 R230C variant with early-onset type 2 diabetes in a Mexican population. Diabetes, 2008. 57(2): p. 509–13.
Karadeniz, M., et al., Effect Of G2706A and G1051A polymorphisms of the ABCA1 gene on the lipid, oxidative stress and homocystein levels in Turkish patients with polycystic ovary syndrome. Lipids Health Dis, 2011. 10: p. 193.
Niculescu, L.S., M. Vladica, and A.V. Sima, Association of APOA5 and APOC3 gene polymorphisms with plasma apolipoprotein A5 level in patients with metabolic syndrome. Biochem Biophys Res Commun, 2010. 391(1): p. 587–91.
Xu, C., et al., Effects of APOA5 -1131T>C (rs662799) on fasting plasma lipids and risk of metabolic syndrome: evidence from a case-control study in China and a meta-analysis. PLoS One, 2013. 8
(2): p. e56216.
Vasilopoulos, Y., et al., Association between polymorphisms in MTHFR and APOA5 and metabolic syndrome in the Greek population. Genet Test Mol Biomarkers, 2011. 15(9): p. 613–7.
Xu C Fau - Bai, R., et al., Effects of APOA5 -1131T>C (rs662799) on fasting plasma lipids and risk of metabolic syndrome: evidence from a case-control study in China and a meta-analysis. 2013(1932- 6203 (Electronic)).
Liu, C.F., et al., Apolipoprotein a5 gene polymorphism and risk for metabolic syndrome: a meta-analysis. Genet Test Mol Biomarkers, 16(10): p. 1241–5.
Jiang, C.Q., et al., A single nucleotide polymorphism in APOA5 determines triglyceride levels in Hong Kong and Guangzhou Chinese. Eur J Hum Genet, 2010. 18(11): p. 1255–60.
Bhaskar, S., et al., Association of PON1 and APOA5 gene polymorphisms in a cohort of Indian patients having coronary artery disease with and without type 2 diabetes. Genet Test Mol Biomarkers, 2011. 15(7-8): p. 507–12.
Bi, M., et al., Association of rs780094 in GCKR with metabolic traits and incident diabetes and cardiovascular disease: the ARIC Study. PLoS One, 2010. 5(7): p. e11690.
Mohammadzadeh, G. and N. Zarghami, Associations between single-nucleotide polymorphisms of the adiponectin gene, serum adiponectin levels and increased risk of type 2 diabetes mellitus in Iranian obese individuals. Scand J Clin Lab Invest, 2009. 69(7): p. 764–71.
von Frankenberg, A.D., et al., Major components of metabolic syndrome and adiponectin levels: a cross-sectional study. Diabetol Metab Syndr, 2014. 6(1): p. 26.
Peters, K.E., et al., A comprehensive investigation of variants in genes encoding adiponectin (ADIPOQ) and its receptors (ADIPOR1/R2), and their association with serum adiponectin, type 2 diabetes, insulin resistance and the metabolic syndrome. BMC Med Genet, 2013. 14: p. 15.
Qi, L., et al., Novel locus FER is associated with serum HMW adiponectin levels. Diabetes, 2011. 60(8): p. 2197–201.
Heid, I.M., et al., Clear detection of ADIPOQ locus as the major gene for plasma adiponectin: results of genome-wide association analyses including 4659 European individuals. Atherosclerosis, 2010. 208(2): p. 412–20.
Ling, H., et al., Genome-wide linkage and association analyses to identify genes influencing adiponectin levels: the GEMS Study. Obesity (Silver Spring), 2009. 17(4): p. 737–44.
Gao, M., et al., Association of genetic variants in the adiponectin gene with metabolic syndrome: a case-control study and a systematic meta-analysis in the chinese population. PLoS One, 8(4): p. e58412.
AlSaleh, A., et al., Single nucleotide polymorphisms at the ADIPOQ gene locus interact with age and dietary intake of fat to determine serum adiponectin in subjects at risk of the metabolic syndrome. Am J Clin Nutr, 2011. 94(1): p. 262–9.
Li, X., et al., Association of the adiponectin gene (ADIPOQ) +45 T > G polymorphism with the metabolic syndrome among Han Chinese in Sichuan province of China. Asia Pac J Clin Nutr, 2012. 21(2): p. 296–301.
Curti, M.L., et al., Associations of the TNF-alpha -308 G/A, IL6 -174 G/C and AdipoQ 45 T/G polymorphisms with inflammatory and metabolic responses to lifestyle intervention in Brazilians at high cardiometabolic risk. Diabetol Metab Syndr, 2012. 4(1): p. 49.
Esteghamati, A., et al., Association of +45(T/G) and +276(G/T) polymorphisms in the adiponectin gene with coronary artery disease in a population of Iranian patients with type 2 diabetes. Mol Biol Rep, 2012. 39(4): p. 3791–7.
Tabatabaei-Malazy, O., et al., Gender-specific differences in the association of adiponectin gene polymorphisms with body mass index. Rev Diabet Stud, 2010. 7(3): p. 241–6.
Halalkhor, S., et al., Association of ATP-binding cassette transporter-A1 polymorphism with apolipoprotein AI level in Tehranian population. J Genet, 2011. 90(1): p. 129–32.
Daneshpour, M.S., et al., Haplotype analysis of Apo AI-CIII-AIV gene cluster and lipids level: Tehran Lipid and Glucose Study. Endocrine, 2012. 41(1): p. 103–10.
[Table 1], [Table 2]