UDP-glycosyltransferase 1A1 (UGT1A1) metabolizes unconjugated bilirubin to conjugated bilirubin by means of glucuronic acid and is the major enzyme influencing bilirubin levels. Additionally, UGT1A1 plays an important role in the detoxification and excretion of endogenous and exogenous lipophilic compounds .
A polymorphism in the promoter of the UGT1A1 gene, UGT1A1*28 (rs3064744) is characterized by six or seven TA repeats in the TATA-Box. The UGT1A1*28 variant (seven repeats) results in lower gene expression and subsequently lower enzymatic activity compared with the wild-type UGT1A1*1 variant (six repeats) , .
Although a meta-analysis provided clear evidence of an association between serum bilirubin and cardiovascular disease , the UGT1A1*28 variant seems to have no influence on cardiovascular risk , , , . In chronic hemodialysis patients, the UGT1A1*28 variant has been associated with reduced overall mortality .
The aim of the present study was to investigate the role of the UGT1A1*28 polymorphism for long-term outcome in a well-characterized cohort of patients referred for coronary angiography.
Materials and methods
The Ludwigshafen Risk and Cardiovascular Health (LURIC) study includes consecutive Caucasian patients hospitalized for coronary angiography between June 1997 and January 2000. The Ethics Review Committee at the “Landesärztekammer Rheinland-Pfalz” (Mainz, Germany) has approved the study and the participant obtained a written informed consent in accordance to the Helsinki Declaration.
A detailed description of the LURIC study design and baseline characteristics has been published . Briefly, the study population comprised 3316 participants. According to the classification of the American Heart Association, coronary artery disease (CAD) was defined as the presence of a visible luminal narrowing (≥20% stenosis) in at least one of 15 coronary segments . Individuals with stenosis <20% were considered as not having CAD. Cardiovascular risk factors such as type 2 diabetes, hypertension and smoking were assessed. Hypertension was defined as a systolic and/or diastolic blood pressure exceeding 140 and/or 90 mmHg or a history of hypertension documented in medical records. Individuals with either high-density lipoprotein cholesterol <0.91 mmol/L or total cholesterol more than 6.24 mmol/L or triglycerides more than 1.71 mmol/L were considered dyslipidemic . Data on smoking habits were retrieved using questionnaires. Type 2 diabetes mellitus was diagnosed according to the criteria of the American Diabetes Association. Further, individuals with a history of type 2 diabetes or those receiving oral antidiabetics or insulin were considered diabetic . To detect “hidden” smokers, plasma cotinine concentrations were determined using a commercial radioimmunoassay (cotinine RIA; DPC). Individuals suffering from acute illnesses other than acute coronary syndromes, chronic non-cardiac diseases and a history of malignancy within the past 5 years were not eligible.
Fasting blood samples were obtained in the morning before coronary angiography. Selected variables were measured after samples were frozen and stored at −80°C. Information on mortality rates was obtained from local registries. Death certificates were used to classify the diseased into those who died from cardiovascular versus non-cardiovascular causes. This classification was done independently by two experienced clinicians who were blinded to any data on the study participants except the information that was required to classify the causes of death.
Genomic DNA was extracted from the white blood cells in 9 mL of EDTA blood using a salting out method. UGT1A1 genotypes were determined on an ABI 3730 sequencing system (Applied Biosystems, Vienna, Austria). Briefly, polymerase chain reaction was performed using a fluorescence labeled forward primer (FAM-GTCACGTGACACAGTCAAACATTAAC) and an unlabeled reverse primer (5′-ACAAGTGGGCGTCCGCC). Two microliters of the polymerase chain reaction product was mixed with 10 μL Hi-Di™ Formamide (Applied Biosystems) and 0.5 mL Genscan 400HD ROX size standard (Applied Biosystems). After denaturation (95°C for 2 min) and cooling (4°C for 5 min), fragments were analyzed on the ABI 3730 sequencing system. Genotyping was done using the GeneMapper version 3.7 software (Applied Biosystems).
Statistical analysis was done using SPSS 23.0 software (IBM). Continuous variables were compared between groups by univariate analysis of variance. A linear regression model was performed to identify predictors of bilirubin levels. Cox regression was used to estimate effects on mortality. For regression analyses, an allelic model based on additive gene-dose effects was used, and genotypes were coded as 0 (“wildtype”, homozygous *1*1 genotype), 1 (heterozygous *1*28 genotype) or 2 (homozygous *28*28 genotype). The criterion for statistical significance was p<0.05.
Baseline data of the LURIC cohort are presented in Table 1. Genotypes for the UGT1A1*28 gene polymorphism were determined in 3245 (97.9%) members of the LURIC study. UGT1A1 genotype frequencies were 42.2% (*1/*1), 45.4% (*1/*28) and 12.4% (*28/*28) and did not deviate from those predicted by the Hardy-Weinberg equilibrium.
As expected, UGT1A1 genotypes were strongly associated with bilirubin levels, with levels in carriers of the *28/*28 genotype being almost twice as high as in carriers of the *1/*1 genotype (Table 1). In a multivariate regression analysis, baseline bilirubin levels were predicted by UGT1A1 genotype, sex, age, CAD, smoking status and alanine aminotransferase (ALT) level (p<0.001 for all predictors).
During a median follow-up of 10.4 years, 995 (30.0%) subjects died. In a multivariate regression analysis adjusting for age, sex, CAD, smoking, type 2 diabetes, dyslipidemia, baseline ALT und baseline bilirubin levels, the UGT1A1*28 variant predicted lower overall mortality (hazard ratio [HR], 0.86; 95% confidence interval [CI], 0.78–0.95; p=0.003) in a dose-dependent manner (Figure 1). Contrary to expected, in the same model higher baseline bilirubin levels predicted increased mortality (HR, 1.014; 95% CI, 1.002–1.025; p=0.019). Analysis of various subgroups showed a stable association of UGT1A1*28 variant with lower overall, cardiovascular and non-cardiovascular mortality (Figures 1 and 2).
In the present study, the number of UGT1A1*28 alleles was associated with lower cardiovascular or overall mortality. This association remained significant when adjusted for baseline bilirubin levels and conventional risk factors, indicating a genotype effect independent of bilirubin levels.
Some studies reported a protective effect of bilirubin on cardiovascular disease and/or mortality, but results have been inconsistent and conflicting , , , , . In the present study, higher baseline bilirubin levels were associated with higher mortality, which was seemingly contradictive to the protective effects of the UGT1A1*28 allele. Current data suggest a complex network of UGT1A1 genotypes, traditional cardiovascular risk factors and bilirubin influencing mortality. Some conventional risk factors, such as age, are associated with elevated bilirubin levels, while others, such as smoking or male sex, are associated with decreased bilirubin levels . Furthermore, liver disease leads to strongly elevated bilirubin levels, and bilirubin levels are directly related to liver-related mortality , . Beyond being a marker for other risk factors, bilirubin itself could additionally show causal effects on mortality by acting as inhibitor of low-density lipoprotein oxidation and platelet activation , . The net effects of bilirubin levels on mortality are therefore hard to predict, strongly dependent on other risk factors, and may change during life time .
Nevertheless, the main aim of the present study was to investigate the role of UGT1A1 genotypes in mortality. UGT1A1 genotype was, independent of baseline bilirubin levels, a stable and causal predictor of cardiovascular and overall mortality. UGT1A1 conjugates a variety of other endogenous and exogenous substances other than bilirubin . The UGT1A1*28 variant, leading to reduced UGT1A1 activity, leads therefore pleiotropic effects, including reduced conjugation of hormones or drugs. It is likely that these effects, rather than bilirubin levels, are responsible for the decreased mortality conferred by the UGT1A1*28 allele.
Our results are in line with several other studies, showing an association of the UGT1A1*28 allele with reduced mortality in the general population as well as cohorts with different underlying diseases , , . The strengths of the present study include the large number of participants from an ethnic homogenous population, as well as its prospective design. Nevertheless, some limitations of the present study should be kept in mind: LURIC is a hospital-based cohort, and the majority of participants had a prevalent CAD, resulting in a higher mortality compared with the general population. Effect sizes of the UGT1A1*28 variant may depend on the risk profile of the study participants and cannot be extrapolated to other populations.
In the present study, UGT1A1*28 was not associated with a lower prevalence of CAD or MI, which is in contrast to data from the Framingham study . Furthermore, no association of UGT1A1 genotypes with severity of CAD was seen in the present study (data not shown). The present study consisted of patients admitted for coronary angiography, resulting in a large proportion of subjects with CAD or previous MI. This may have obscured the potential associations of UGT1A1 genotypes with CAD risk.
In conclusion, we show that the UGT1A1*28 variant is independently associated with reduced mortality. The mechanisms for this association remain to be established, but are likely other than bilirubin metabolism.
The authors thank the patients of the LURIC study for their willing to participate in data collection and assessment. We also thank the LURIC study team either temporarily or permanently involved in patient recruitment and sample and data handling, the laboratory staff at the Ludwigshafen General Hospital and the Universities of Freiburg, Ulm, Graz and Heidelberg. We also thank and the German registration offices and local public health departments for their assistance.
Sugatani J. Function, genetic polymorphism, and transcriptional regulation of human UDP-glucuronosyltransferase (UGT) 1A1. Drug Metab Pharmacokinet 2013;28:83–92. CrossrefPubMedWeb of ScienceGoogle Scholar
Bosma PL, Chowdhury JR, Bakker C, Gantla S, de Boer A, Oostra BA, et al. The genetic basis of the reduced expression of bilirubin UDP glucuronosyltransferase in Gilbert’s syndrome. N Engl J Med 1995;333:1171–5. PubMedCrossrefGoogle Scholar
Gajdos V, Petit FM, Perret C, Mollet-Boudjemline A, Colin P, Capel L, et al. Further evidence that the UGT1A1*28 allele is not associated with coronary heart disease: the ECTIM Study. Clin Chem 2006;52:2313–4. CrossrefPubMedGoogle Scholar
Lingenhel A, Kollerits B, Schwaiger JP, Hunt SC, Gress R, Hopkins PN, et al. Serum bilirubin levels, UGT1A1 polymorphisms and risk for coronary artery disease. Exp Gerontol 2008;43:1102–7. PubMedCrossrefWeb of ScienceGoogle Scholar
Papez MJ, Civalier CJ, Thorne LB, Gulley ML. UGT1A1 promoter genotype is not strongly associated with severity of coronary artery disease. Diagn Mol Pathol 2009;18:226–31. CrossrefPubMedWeb of ScienceGoogle Scholar
Chen YH, Hung SC, Tarng DC. Serum bilirubin links UGT1A1*28 polymorphism and predicts long-term cardiovascular events and mortality in chronic hemodialysis patients. Clin J Am Soc Nephrol 2011;6:567–74. PubMedWeb of ScienceCrossrefGoogle Scholar
Winkelmann BR, März W, Boehm BO, Zotz R, Hager J, Hellstern P, et al. Rationale and design of the LURIC study- a resource for functional genomics, pharmacogenomics and long-term prognosis of cardiovascualar disease. Pharmacogenomics 2001;2(Suppl. 1):S1–73. CrossrefGoogle Scholar
Austen WG, Edwards JE, Frye RL, Gensini GG, Gott VL, Griffith LS, et al. A reporting system on patients evaluated for coronary artery disease. Report of the Ad Hoc Committee for Grading of Coronary Artery Disease, Council on Cardiovascular Surgery, American Heart Association. Circulation 1975;51(Suppl. 4): 5–40. PubMedCrossrefGoogle Scholar
Expert Committee on the Diagnosis and Classification of Diabetes Mellitus, report of the Expert Committee on the diagnosis and classification of diabetes mellitus. Diabetes Care 1997;20:1183–97. PubMedGoogle Scholar
McCallum L, Panniyammakal J, Hastie CE, Hewitt J, Patel R, Jones GC, et al. Longitudinal blood pressure control, long-term mortality, and predictive utility of serum liver enzymes and bilirubin in hypertensive patients. Hypertension 2015;66:37–43. PubMedWeb of ScienceCrossrefGoogle Scholar
Lee YM, Wai CT, Da Costa M, Lee KH, Sutedja D, Tan KC, et al. Bilirubin appears to be the only independent variable affecting mortality on liver transplant waiting list if waiting time exceeds 1 year. Transplant Proc 2005;37:4365–6. CrossrefPubMedGoogle Scholar
Malinchoc M, Kamath PS, Gordon FD, Peine CJ, Rank J, ter Borg PC. A model to predict poor survival in patients undergoing transjugular intrahepatic portosystemic shunts. Hepatology 2000;31:864–71. PubMedCrossrefGoogle Scholar
Bulmer AC, Blanchfield JT, Toth I, Fassett RG, Coombes JS. Improved resistance to serum oxidation in Gilbert’s syndrome: a mechanism for cardiovascular protection. Atherosclerosis 2008;199:390–6. PubMedCrossrefWeb of ScienceGoogle Scholar
Kundur AR, Singh I, Bulmer AC. Bilirubin, platelet activation and heart disease: a missing link to cardiovascular protection in Gilbert’s syndrome? Atherosclerosis 2015; 239:73–84. Web of SciencePubMedCrossrefGoogle Scholar
Cox AJ, Ng MC, Xu J, Langefeld CD, Koch KL, Dawson PA, et al. Association of SNPs in the UGT1A gene cluster with total bilirubin and mortality in the Diabetes Heart Study. Atherosclerosis 2013;229:155–60. PubMedWeb of ScienceCrossrefGoogle Scholar
Lin JP, O’Donnell CJ, Schwaiger JP, Cupples LA, Lingenhel A, Hunt SC, et al. Association between the UGT1A1*28 allele, bilirubin levels, and coronary heart disease in the Framingham Heart Study. Circulation 2006;114:1476–81. CrossrefPubMedGoogle Scholar
About the article
Published Online: 2017-12-07
Published in Print: 2018-03-28
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: None declared.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.