Gamma-glutamyltransferase and Risk of Cardiovascular Disease Mortality in People with and Without Diabetes: Pooling of Three British Health Surveys

Background & Aims: The relation between gamma-glutamyltransferase (GGT) and mortality risk has been little explored in people with diabetes. We examined (a) the association of GGT with cardiovascular disease (CVD) and all-cause mortality in people with and without diabetes; and (b) the predictive validity observed when adding GGT to a CVD risk algorithm.

Methods: Participants were 17,852 adults from three British cohorts representative of the general population in England (N=1) and Scotland (N=2). Follow-up was to December 2009 (Scottish cohorts) and February 2008 (English cohort). Cox models were used to compute the hazard ratio (HR) and 95% confidence interval (95% CI) for a standard deviation (SD) increase log(e)(GGT) in relation to mortality according to diabetes status. The value of adding GGT to a CVD risk engine was assessed through c-statistic and relative integrated discrimination improvement.

Results: In an analytical sample of 17,852 participants, 583 (3.3%) had baseline diabetes. During 10.1 years of follow-up, there were 235 deaths from all causes (77 from CVD) in diabetics. Corresponding results for non-diabetics were 2859 and 719. The age- and sex-adjusted HR (95%CI) for a one SD increase in log(e)(GGT) in relation to CVD mortality risk in participants with diabetes was 1.43 (1.13-1.81) and in those without diabetes was 1.27 (1.18-1.37). Corresponding results for total mortality were 1.24 (1.08-1.44) and 1.30 (1.25-1.34). Thus, there was no evidence that diabetes status modified the strength of the GGT-mortality relationship (p value for interaction ≥0.16). Adding GGT to model with classical predictors only marginally enhanced the prediction of CVD in both people with and without diabetes.

Conclusions: Higher GGT levels are a risk factor for all-cause and cardiovascular disease death in people with and without diabetes. However, knowledge of GGT does not improve cardiovascular predictions beyond traditional risk factors.