Several genome-wide association studies have already explored the associations between rs498872 polymorphism and glioma, but the results of these studies were not consistent. Consequently, we conducted a meta-analysis of relevant studies to better analyze the effects of rs498872 polymorphism on individual susceptibility to glioma. PubMed, Web of Science and Embase were searched for eligible studies. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Totally, 12 studies with 36,264 subjects were analyzed. A significant association with glioma was observed for the rs498872 polymorphism in CC versus CT + TT (dominant comparison, p < 0.0001, OR = 0.81, 95% CI 0.76–0.85), TT versus CC + CT (recessive comparison, p < 0.0001, OR = 1.23, 95% CI 1.13–1.34), CT versus CC + TT (overdominant comparison, p < 0.0001, OR = 1.15, 95% CI 1.09–1.21) and C versus T (allele comparison, p < 0.0001, OR = 0.86, 95% CI 0.84–0.90). Further subgroup analyses yielded similar positive results in both Asians and Caucasians. Our findings suggested that the rs498872 polymorphism may serve as a potential genetic biomarker of glioma in both Asians and Caucasians.
Rs498872 polymorphism Glioma Meta-analysis
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BC and YD conceived the study, and participated in its design. BC and YL conducted the systematic literature review. LC performed data analyses. BC and YD drafted the manuscript. All authors have read and approved the final manuscript.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
For this type of study formal consent is not required.
Zhang AS, Ostrom QT, Kruchko C, Rogers L, Peereboom DM, Barnholtz-Sloan JS (2017) Complete prevalence of malignant primary brain tumors registry data in the United States compared with other common cancers, 2010. Neuro Oncol 19:726–735Google Scholar
Ostrom QT, Gittleman H, Stetson L, Virk SM, Barnholtz-Sloan JS (2015) Epidemiology of gliomas. Cancer Treat Res 163:1–14CrossRefGoogle Scholar
Ohgaki H, Kleihues P (2005) Epidemiology and etiology of gliomas. Acta Neuropathol 109:93–108CrossRefGoogle Scholar
Shete S, Hosking FJ, Robertson LB et al (2009) Genome-wide association study identifies five susceptibility loci for glioma. Nat Genet 41:899–904CrossRefGoogle Scholar
Chen H, Chen Y, Zhao Y et al (2011) Association of sequence variants on chromosomes 20, 11, and 5 (20q13.33, 11q23.3, and 5p15.33) with glioma susceptibility in a Chinese population. Am J Epidemiol 173:915–922CrossRefGoogle Scholar
Schoemaker MJ, Robertson L, Wigertz A et al (2010) Interaction between 5 genetic variants and allergy in glioma risk. Am J Epidemiol 171:1165–1173CrossRefGoogle Scholar
Melin B, Dahlin AM, Andersson U et al (2013) Known glioma risk loci are associated with glioma with a family history of brain tumours—a case–control gene association study. Int J Cancer 132:2464–2468CrossRefGoogle Scholar
Rice T, Zheng S, Decker PA et al (2013) Inherited variant on chromosome 11q23 increases susceptibility to IDH-mutated but not IDH-normal gliomas regardless of grade or histology. Neuro Oncol 15:535–541CrossRefGoogle Scholar
Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA group (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med 151:264–269CrossRefGoogle Scholar
Stang A (2010) Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol 25:603–605CrossRefGoogle Scholar
Baskin R, Woods NT, Mendoza-Fandiño G, Forsyth P, Egan KM, Monteiro AN (2015) Functional analysis of the 11q23.3 glioma susceptibility locus implicates PHLDB1 and DDX6 in glioma susceptibility. Sci Rep 5:17367CrossRefGoogle Scholar
Li Z, Wang Y, Guo X, Zhang L, Dong C, Zhang J (2015) Assessment of glioma risk associated with an inherited variant at chromosome 11q23. Cell Biochem Biophys 71:69–75CrossRefGoogle Scholar
Xie X, Shi X, Liu M (2017) The roles of TLR gene polymorphisms in atherosclerosis: a systematic review and meta-analysis of 35,317 subjects. Scand J Immunol 86:50–58CrossRefGoogle Scholar
Shi X, Xie X, Jia Y, Li S (2016) Associations of insulin receptor and insulin receptor substrates genetic polymorphisms with polycystic ovary syndrome: a systematic review and meta-analysis. J Obstet Gynaecol Res 42:844–854CrossRefGoogle Scholar
Shi Y, Zhang J, Tan C, Xu W, Sun Q, Li J (2015) Matrix metalloproteinase-2 polymorphisms and incident coronary artery disease: a meta-analysis. Medicine (Baltimore) 94:e824CrossRefGoogle Scholar