EClinicalMedicine (Jun 2022)
Association of gamma-glutamyltransferase levels with total mortality, liver-related and cardiovascular outcomes: A prospective cohort study in the UK Biobank
Abstract
Summary: Background: Gamma-glutamyltransferase (GGT) levels in the blood can be a sensitive marker of liver injury but the extent to which they give insight into risk across multiple outcomes in a clinically useful way remains uncertain. Methods: Using data from 293,667 UK Biobank participants, the relationship of GGT concentrations to self-reported alcohol intake and adiposity markers were investigated. We next investigated whether GGT predicted liver-related, cardiovascular (CV) or all-cause mortality, and potentially improved CV risk prediction. Findings: Higher alcohol intake and greater waist circumference (WC) were associated with higher GGT; the association was stronger for alcohol with evidence of a synergistic effect of WC. Higher GGT concentrations were associated with multiple outcomes. Compared to a GGT of 14.5 U/L (lowest decile), values of 48 U/L for women and 60 U/L for men (common upper limits of ‘normal’) had hazard ratios (HRs) for liver-related mortality of 1.83 (95% CI 1.60–2.11) and 3.25 (95% CI 2.38–4.42) respectively, for CV mortality of 1.21 (95% CI 1.14–1.28) and 1.43 (95% CI 1.27–1.60) and for all-cause mortality of 1.15 (95% CI 1.12–1.18) and 1.31 (95% CI 1.24–1.38). Adding GGT to a risk algorithm for CV mortality reclassified an additional 1.24% (95% CI 0.14–2.34) of participants across a binary 5% 10-year risk threshold. Interpretation: Our study suggests that a modest elevation in GGT levels should trigger a discussion with the individual to review diet and lifestyle including alcohol intake and consideration of formal liver disease and CV risk assessment if not previously done. Funding: British Heart Foundation Centre of Research Excellence Grant (grant number RE/18/6/34217), NHS Research Scotland (grant number SCAF/15/02), the Medical Research Council (grant number MC_UU_00022/2); and the Scottish Government Chief Scientist Office (grant number SPHSU17).
