BACKGROUND: Altered expression of six-transmembrane epithelial antigen of prostate 4 (STEAP4) is linked to obesity, insulin insensitivity, metabolic homeostasis, and inflammation. This study assessed STEAP4 single nucleotide polymorphisms (SNPs) for association with a risk in developing metabolic syndrome in a Han Chinese population. METHODS: A total of 3375 Han Chinese subjects were included in this case-control study with 1583 metabolic syndrome (MetS) patients and 1792 healthy controls. Four SNPs (rs1981529, rs2040657, rs10263111, rs12386756) were genotyped using polymerase chain reaction and MALDI-TOF-MS. The associations between the STAMP4 SNPs and MetS were then analyzed statistically. RESULTS: There was no statistical difference in allele frequency of these four SNPs between the case and control populations. The genotype of rs12386756 was shown to be significantly associated with MetS (p = 0.035). Compared with the AA/GG genotypes, the GA genotype of rs12386756 significantly decreased the risk of developing MetS (OR = 0.77; 95% CI, 0.63-0.94; p = 0.0098). There was also no haplotype that could be associated with the risk of developing MetS. Furthermore, the SNP rs1981529 of STEAP4 was associated with body-mass index, waist circumference, and systolic blood pressure, while SNP rs10263111 was associated with waist circumference and fasting glucose levels. SNP rs12386756 was associated with waist and hip circumferences. CONCLUSION: Some SNPs of the STEAP4 gene altered the risk of developing a metabolic syndrome in the Han Chinese population. Further studies must be conducted to understand the role of the STEAP4 gene in the pathogenesis of metabolic syndrome.
BACKGROUND: Altered expression of six-transmembrane epithelial antigen of prostate 4 (STEAP4) is linked to obesity, insulin insensitivity, metabolic homeostasis, and inflammation. This study assessed STEAP4 single nucleotide polymorphisms (SNPs) for association with a risk in developing metabolic syndrome in a Han Chinese population. METHODS: A total of 3375 Han Chinese subjects were included in this case-control study with 1583 metabolic syndrome (MetS) patients and 1792 healthy controls. Four SNPs (rs1981529, rs2040657, rs10263111, rs12386756) were genotyped using polymerase chain reaction and MALDI-TOF-MS. The associations between the STAMP4 SNPs and MetS were then analyzed statistically. RESULTS: There was no statistical difference in allele frequency of these four SNPs between the case and control populations. The genotype of rs12386756 was shown to be significantly associated with MetS (p = 0.035). Compared with the AA/GG genotypes, the GA genotype of rs12386756 significantly decreased the risk of developing MetS (OR = 0.77; 95% CI, 0.63-0.94; p = 0.0098). There was also no haplotype that could be associated with the risk of developing MetS. Furthermore, the SNP rs1981529 of STEAP4 was associated with body-mass index, waist circumference, and systolic blood pressure, while SNP rs10263111 was associated with waist circumference and fasting glucose levels. SNP rs12386756 was associated with waist and hip circumferences. CONCLUSION: Some SNPs of the STEAP4 gene altered the risk of developing a metabolic syndrome in the Han Chinese population. Further studies must be conducted to understand the role of the STEAP4 gene in the pathogenesis of metabolic syndrome.
Authors: Susan Kralisch; Grit Sommer; Sebastian Weise; Jana Lipfert; Ulrike Lossner; Manja Kamprad; Kathleen Schröck; Matthias Bluher; Michael Stumvoll; Mathias Fasshauer Journal: FEBS Lett Date: 2009-03-14 Impact factor: 4.124
Authors: K G M M Alberti; Robert H Eckel; Scott M Grundy; Paul Z Zimmet; James I Cleeman; Karen A Donato; Jean-Charles Fruchart; W Philip T James; Catherine M Loria; Sidney C Smith Journal: Circulation Date: 2009-10-05 Impact factor: 29.690
Authors: Hannah M Gordon; Neil Majithia; Patrick E MacDonald; Jocelyn E Manning Fox; Poonam R Sharma; Frances L Byrne; Kyle L Hoehn; Carmella Evans-Molina; Linda Langman; Kenneth L Brayman; Craig S Nunemaker Journal: Endocrine Date: 2017-04-12 Impact factor: 3.633
Authors: Torstein Lindstad; Su Qu; Jørgen Sikkeland; Yang Jin; Alexandr Kristian; Gunhild M Mælandsmo; Philippe Collas; Fahri Saatcioglu Journal: Oncotarget Date: 2016-08-09