Background: High levels of serum gamma-glutamyltransferase (GGT) are associated with increased risk of prediabetes and type 2 diabetes in observational studies. It is unclear whether this relationship is causal, arises from residual confounding or is a consequence of reverse causation. Methods: We used data from a prospective population-based cohort study, compromising 8611 individuals without diabetes at baseline. Cox proportional hazard models were used to study the association between serum GGT levels and incident prediabetes and diabetes. A Mendelian randomization (MR) study was performed using a genetic risk score consisting of 26 GGT-related variants, based on a genome-wide association study (GWAS) on liver enzymes. Association with diabetes and glycaemic traits were investigated within the Rotterdam Study and large-scale GWAS. Results: During follow-up, 1125 cases of prediabetes (mean follow-up 5.7 years) and 811 cases of type 2 diabetes (6.9 years) were ascertained. The predicted hazard ratios per standard deviation (SD) change in GGT levels in the multivariable model were 1.10 for prediabetes [95% confidence interval (CI): 1.02-1.19] and 1.19 for type 2 diabetes (95% CI: 1.10-1.30). The genetic risk score associated with increased GGT levels (beta per SD log GGT = 0.41, 95% CI: 0.35-0.47), explaining 3.5% of the observed variation in GGT. MR analysis did not provide evidence for a causal role of GGT, with a causal relative risk for prediabetes and type 2 diabetes per SD of log GGT of 0.97 (95% CI: 0.91-1.04) and 0.96 (95% CI: 0.89-1.04), respectively. Multiple instrumental analysis using genetic associations with type 2 diabetes and glycaemic traits from previous GWA studies detected no causal effect of GGT. Conclusions: MR analyses did not support a causal role of GGT on the risk of prediabetes or diabetes. The association of GGT with diabetes in observational studies is likely to be driven by reverse causation or confounding bias. As such, therapeutics targeted at lowering GGT levels are unlikely to be effective in preventing diabetes.
Background: High levels of serum gamma-glutamyltransferase (GGT) are associated with increased risk of prediabetes and type 2 diabetes in observational studies. It is unclear whether this relationship is causal, arises from residual confounding or is a consequence of reverse causation. Methods: We used data from a prospective population-based cohort study, compromising 8611 individuals without diabetes at baseline. Cox proportional hazard models were used to study the association between serum GGT levels and incident prediabetes and diabetes. A Mendelian randomization (MR) study was performed using a genetic risk score consisting of 26 GGT-related variants, based on a genome-wide association study (GWAS) on liver enzymes. Association with diabetes and glycaemic traits were investigated within the Rotterdam Study and large-scale GWAS. Results: During follow-up, 1125 cases of prediabetes (mean follow-up 5.7 years) and 811 cases of type 2 diabetes (6.9 years) were ascertained. The predicted hazard ratios per standard deviation (SD) change in GGT levels in the multivariable model were 1.10 for prediabetes [95% confidence interval (CI): 1.02-1.19] and 1.19 for type 2 diabetes (95% CI: 1.10-1.30). The genetic risk score associated with increased GGT levels (beta per SD log GGT = 0.41, 95% CI: 0.35-0.47), explaining 3.5% of the observed variation in GGT. MR analysis did not provide evidence for a causal role of GGT, with a causal relative risk for prediabetes and type 2 diabetes per SD of log GGT of 0.97 (95% CI: 0.91-1.04) and 0.96 (95% CI: 0.89-1.04), respectively. Multiple instrumental analysis using genetic associations with type 2 diabetes and glycaemic traits from previous GWA studies detected no causal effect of GGT. Conclusions: MR analyses did not support a causal role of GGT on the risk of prediabetes or diabetes. The association of GGT with diabetes in observational studies is likely to be driven by reverse causation or confounding bias. As such, therapeutics targeted at lowering GGT levels are unlikely to be effective in preventing diabetes.
Authors: Stephanie Gängler; Melanie Waldenberger; Anna Artati; Jerzy Adamski; Jurjen N van Bolhuis; Elin Pettersen Sørgjerd; Jana van Vliet-Ostaptchouk; Konstantinos C Makris Journal: Metabolomics Date: 2019-04-08 Impact factor: 4.290
Authors: M Arfan Ikram; Guy Brusselle; Mohsen Ghanbari; André Goedegebure; M Kamran Ikram; Maryam Kavousi; Brenda C T Kieboom; Caroline C W Klaver; Robert J de Knegt; Annemarie I Luik; Tamar E C Nijsten; Robin P Peeters; Frank J A van Rooij; Bruno H Stricker; André G Uitterlinden; Meike W Vernooij; Trudy Voortman Journal: Eur J Epidemiol Date: 2020-05-04 Impact factor: 8.082
Authors: Junxi Liu; Shiu Lun Au Yeung; Man Ki Kwok; June Yue Yan Leung; Shi Lin Lin; Lai Ling Hui; Gabriel Matthew Leung; C Mary Schooling Journal: Sci Rep Date: 2019-11-14 Impact factor: 4.379