SynthesisMolecular neurobiology2016
An Updated and Comprehensive Meta-Analysis of Association Between Seven Hot Loci Polymorphisms from Eight GWAS and Glioma Risk.
Synthesis in Molecular neurobiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Quantitative assessment of the associations between MTR and MTRR gene polymorphisms and glioma risk.Discover oncology · 2025Article
- Association ofGynecology and pelvic medicine · 2025Article
- The Long Non-Coding RNA ANRIL in Cancers.Cancers · 2023Review
- Burden and trends of brain and central nervous system cancer from 1990 to 2019 at the global, regional, and country levels.Archives of public health = Archives belges de sante publique · 2022Article
- Epidermal Growth Factor Receptor (EGFR) Gene Polymorphism May be a Modifier for Cadmium Kidney Toxicity.Genes · 2021Article
- Genetic Variants Related to Cell Cycle and Stability of Telomere in Patients with Glioma.Asian Pacific journal of cancer prevention : APJCP · 2019Article
- CCDC26 knockdown enhances resistance of gastrointestinal stromal tumor cells to imatinib by interacting with c-KIT.American journal of translational research · 2018Article
- Associations between EGFR gene polymorphisms and susceptibility to glioma: a systematic review and meta-analysis from GWAS and case-control studies.Oncotarget · 2017Article
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3 authors.
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Abstract
Eight genome-wide association studies (GWASs) found that seven loci (rs2736100, rs4295627, rs4977756, rs498872, rs11979158, rs2252586, rs6010620) polymorphisms could elevate the risk of glioma, one of the most common types of primary brain cancer in adults. However, the replication studies about these seven loci obtained inconsistent results. In order to derive a more accurate estimation about the relationship between the selected single-nucleotide polymorphism (SNP) and susceptibility to glioma, we conducted a meta-analysis containing all eligible published case control studies to evaluate the association. An overall literature search was conducted using the database of PubMed, Science Direct, China national knowledge infrastructure (CNKI), and Embase. Seventeen articles with 25 studies were included in the meta-analysis. Glioma risk (odds ratio, OR; 95 % confidential interval, 95 %CI) was estimated with the random-effect model or the fixed-effects model. STATA 12.0 was applied to analyze all statistical data. Results showed that seven hot loci were all associated with increased risk of glioma (rs2736100, OR = 1.28, 95 %CI = 1.23-1.32; rs4295627, OR = 1.34, 95 %CI = 1.21-1.47; rs4977756, OR = 1.24, 95 %CI = 1.20-1.28; rs498872, OR = 1.24, 95 %CI = 1.15-1.33; rs6010620, OR = 1.29, 95 %CI = 1.24-1.35; rs11979158: OR = 1.18, 95 %CI = 1.10-1.25; rs2252586: OR = 1.18, 95 %CI = 1.10-1.25). Additionally, subgroup analysis by stages of glioma found that variation of rs11979158 had stronger relationship with high-grade (OR = 1.32, 95 %CI = 1.19-1.45) than low-grade glioma (OR = 1.12, 95 % CI = 1.03-1.21). Similarly, stratified analysis of rs2252586 by stages revealed the similar trend, with OR of 1.26 (95 %CI = 1.17-1.35) in high-grade glioma and OR of 1.15 (95 %CI = 1.08-1.22) in low-grade glioma. In summary, the present study showed that mutations of the seven loci could elevate the risk of glioma significantly. However, more other factors that could be related with glioma should be considered in further studies.
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