학술논문

Components of one-carbon metabolism and renal cell carcinoma: a systematic review and meta-analysis.
Document Type
Article
Source
European Journal of Nutrition. Dec2020, Vol. 59 Issue 8, p3801-3813. 13p. 1 Diagram, 2 Charts, 2 Graphs.
Subject
*CARBON metabolism
*BIOMARKERS
*FOLIC acid
*MEDICAL information storage & retrieval systems
*INGESTION
*MEDLINE
*META-analysis
*RENAL cell carcinoma
*VITAMIN B6
*SYSTEMATIC reviews
*DISEASE risk factors
Language
ISSN
1436-6207
Abstract
Purpose: Little is known about the aetiology of renal cell carcinoma (RCC). Components of one-carbon (1C) metabolism, which are required for nucleotide synthesis and methylation reactions, may be related to risk of RCC but existing evidence is inconclusive. We conducted a systematic review and independent exposure-specific meta-analyses of dietary intake and circulating biomarkers of 1C metabolites and RCC risk. Methods: Medline and Embase databases were searched for observational studies investigating RCC or kidney cancer incidence or mortality in relation to components of 1C metabolism and 12 eligible articles were included in the meta-analyses. We used Bayesian meta-analyses to estimate summary relative risks (RRs) and 95% credible intervals (CrIs) comparing the highest versus lowest categories as well as the between-study heterogeneity. Results: We did not find convincing evidence of an association between any exposure (riboflavin, vitamin B6, folate, vitamin B12, methionine, homocysteine, choline, or betaine) and RCC risk. However, vitamin B6 biomarker status did have a protective (RR = 0.62) but imprecise (95% CrI 0.39–1.14) effect estimate and folate intake had a notable association as well (RR = 0.85, 95% CrI 0.71–1.01). Conclusion: There was a lack of precision due largely to the low number of studies. Further investigation is warranted, especially for folate and vitamin B6, which had consistent suggestive evidence of a protective effect for both dietary intake and biomarker status. A unique strength of this review is the use of Bayesian meta-analyses which allowed for robust estimation of between-study heterogeneity. [ABSTRACT FROM AUTHOR]