ArticleBlood research2024
Impact of CYP1A1 variants on the risk of acute lymphoblastic leukemia: evidence from an updated meta-analysis.
Article in Blood research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed, 1 citations in OpenAlex.
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6 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
objectiveOur study aimed to investigate the association between cytochrome P450 1A1 (CYP1A1) polymorphisms (T3801C and A2455G) and acute lymphoblastic leukemia (ALL) risk, considering genetic models and ethnicity. MATERIALS AND
methodsPubMed, Embase, Web of Knowledge, Scopus, and the Cochrane electronic databases were searched using combinations of keywords related to CYP1A1 polymorphisms and the risk of ALL. Studies retrieved from the database searches underwent screening based on strict inclusion and exclusion criteria.
resultsIn total, 2822 cases and 4252 controls, as well as 1636 cases and 2674 controls of the C3801T and A2455G variants of CYP1A1, respectively, were included in this meta-analysis. The T3801C polymorphism of CYP1A1 significantly increases the risk of ALL, particularly those observed in Asian and Hispanic populations, independent of age. Similarly, the A2455G polymorphism of CYP1A1 plays a significant role in the susceptibility to ALL in all genetic models, except the heterozygous form. This association was observed mainly in mixed populations and in both children and adults (except in the heterozygous model).
conclusionOur comprehensive analysis indicates that the T3801 and A2455G polymorphisms of CYP1A1 may increase the risk of ALL depending on ethnicity. Therefore, both variants should be considered promising biomarkers for ALL risk. Further large-scale investigations are necessary to assess other factors, such as gene-gene or gene-environment interactions.
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