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Translational Medicine and Reliability of Single-Nucleotide Polymorphism Studies: Can We Believe in SNP Reports or Not?

Background: The number of genetic association studies is increasing exponentially. Nonetheless, genetic association reports are prone to potential biases which may influence the reported outcome. Aim: We hypothesized that positive outcome for a determined polymorphism might be over-reported across g...

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Detalles Bibliográficos
Autores principales: Valachis, Antonis, Mauri, Davide, Neophytou, Christodoulos, Polyzos, Nikolaos P., Tsali, Lampriani, Garras, Antonios, Papanikolau, Evangelos G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3167098/
https://www.ncbi.nlm.nih.gov/pubmed/21897762
Descripción
Sumario:Background: The number of genetic association studies is increasing exponentially. Nonetheless, genetic association reports are prone to potential biases which may influence the reported outcome. Aim: We hypothesized that positive outcome for a determined polymorphism might be over-reported across genetic association studies analysing a small number of polymorphisms, when compared to studies analysing the same polymorphism together with a high number of other polymorphisms. Methods: We systematically reviewed published reports on the association of glutathione s-transferase (GST) single-nucleotide polymorphisms (SNPs) and cancer outcome. Result: We identified 79 eligible trials. Most of the studies examined the GSTM1, theGSTP1 Ile105Val mutation, and GSTT1polymorphisms (n = 54, 57 and 46, respectively). Studies analysing one to three polymorphisms (n = 39) were significantly more likely to present positive outcomes, compared to studies examining more than 3 polymorphisms (n=40) p = 0.004; this was particularly evident for studies analysing the GSTM1polymorphism (p =0.001). We found no significant associations between journal impact factor, number of citations, and probability of publishing positive studies or studies with 1-3 polymorphisms examined. Conclusions: We propose a new subtype of publication bias in genetic association studies. Positive results for genetic association studies analysing a small number of polymorphisms (n = 1-3) should be evaluated extremely cautiously, because a very large number of such studies are inconclusive and statistically under-powered. Indeed, publication of misleading reports may affect harmfully medical decision-making and use of resources, both in clinical and pharmacological development setting.