AUTHOR=Zhang Yanan , Wang Ruiqing , Tang Xinhua , Wang Yanjun , Guo Ping , Wang Shukang , Liu Jing 

TITLE=A Mendelian Randomization Study of the Effect of Tea Intake on Type 2 Diabetes

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.835917

DOI=10.3389/fgene.2022.835917

ISSN=1664-8021

ABSTRACT=Background: The association between tea intake and type 2 diabetes (T2D) is inconsistent and remains controversial. We aim to explore the causal relationship between genetically predicted tea intake and T2D and some T2D biomarkers. 
Methods: Two-sample Mendelian randomization (MR) was conducted with tea intake genome-wide association study (GWAS) data on European participants from UK Biobank (373,481 individuals) and the largest GWAS summary statistics of T2D from the DIAGRAM consortium (898,130 individuals with 74,124 cases and 824,006 controls). GWAS summary statistics on T2D biomarkers was from the Magic consortium. Findings were verified through sensitivity analyses using various MR methods with different model assumptions, as well as comprehensively evaluating the influence of pleiotropy effects and outliers. 
Results: Through two-sample MR with inverse variance weighted (IVW) method, the odds ratio (OR) per unit standard deviation change of tea intake (standard deviation: 2.85 cups/day) on T2D HbA1c, FPG, FSI and HOMA-IR levels is 0.949 (95%CI 0.844–1.067, p=0.383), 0.994 (95%CI 0.975–1.013, p=0.554), 0.996 (95%CI 0.978–1.015, p=0.703), 0.968 (95%CI 0.948–0.986, p=0.001), 0.953 (95%CI 0.900–1.009, p=0.102). More importantly, the results are consistent from other six methods with different model assumptions, suggesting the findings were robust and convincing. Various sensitive analyses regarding the outlier removal, pleiotropy detection as well as leave-one-out analysis were also performed. 
Conclusion: Our MR results did not genetically support the causal effect of tea intake on T2D and the crucial T2D biomarkers. The findings may suggest that previous observational studies may have been confounded.