Liver Function Tests and Risk Prediction of Incident Type 2 Diabetes: Evaluation in Two Independent Cohorts

Abbasi, Ali; Bakker, Stephan J. L.; Corpeleijn, Eva; A, Daphne L. van der; Gansevoort, Ron T.; Gans, Rijk O. B.; Peelen, Linda M.; Schouw, Yvonne T. van der; Stolk, Ronald P.; Navis, Gerjan; Spijkerman, Annemieke M.W.; Beulens, Joline W.J.

doi:10.1371/journal.pone.0051496

Cited by 35 publications

(30 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Abbasi and colleagues found no significant association in one of their cohorts of men and women aged 28-75 years [13]. In the Atherosclerosis Risk in Communities study [8], low serum albumin was associated with an increased risk of type 2 diabetes among men and women aged 45-65 years in analyses [6,11,12], cancer mortality [6] and allcause mortality [11].…”

Section: Discussionmentioning

confidence: 96%

“…A limited number of prospective studies have been published reporting on the associations between baseline serum albumin concentrations and risk of type 2 diabetes [8,13,14], but their results have been inconsistent. Whereas some studies have shown inverse associations [13,14], other studies have found no association between serum albumin and type 2 diabetes [8,13], giving rise to uncertainty regarding the nature of the association. To help characterise and quantify more reliably the nature and magnitude of the association, we report a detailed assessment of the association of serum albumin concentration with incident type 2 diabetes in a population-based sample of 1,785 non-diabetic men from eastern Finland.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Serum albumin concentration and incident type 2 diabetes risk: new findings from a population-based cohort study

2015

View full text Add to dashboard Cite

Aims/hypothesis Serum albumin concentrations may be associated with future risk of type 2 diabetes, but the epidemiological evidence is limited and uncertain. We prospectively assessed the association between baseline values of serum albumin and incident type 2 diabetes risk in the Kuopio Ischaemic Heart Disease population-based cohort study. Methods We analysed the data of 1,785 men aged 42-61 years with no known history of diabetes at baseline. Participants' serum albumin concentrations were measured at baseline. HRs and 95% CIs for type 2 diabetes events were subsequently assessed.Results During a mean follow-up of 20.4 years, 382 participants developed diabetes. Serum albumin concentrations were weakly correlated with several established risk factors for diabetes. Serum albumin was approximately linearly associated with type 2 diabetes risk. In analyses adjusted for several conventional risk factors, the HR for type 2 diabetes per 1 SD increase in serum albumin was 1.15 (95% CI 1.03, 1.28; p=0.016), which persisted after further adjustment for triacylglycerol, Creactive protein, γ-glutamyltransferase, estimated glomerular filtration rate and total energy intake (HR 1.15; 95% CI 1.02, 1.29; p=0.018). The findings were generally consistent across several clinical subgroups. Addition of information on serum albumin to a diabetes risk prediction model containing conventional risk factors led to no significant change in C-index (0.0126; 95% CI −0.0055, 0.0306; p=0.17). Conclusions/interpretation A near linear, positive and independent association was found between serum albumin and type 2 diabetes, but this did not improve event discrimination. Further work is warranted to evaluate the causal relevance of these findings.

show abstract

Section: Discussionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Serum albumin concentration and incident type 2 diabetes risk: new findings from a population-based cohort study

2015

View full text Add to dashboard Cite

show abstract

“…The hope of groups investigating other biomarkers is that they will enhance prediction further. Our review suggests that over a time horizon of 5–10 years, additional biomarkers have failed to improve prediction metrics over a model consisting of traditional diabetes predictors, glucose and HbA1c [51][4][40,52] which are, of course, measures used in the diagnosis of diabetes. In this context, the utility of biomarkers (or variables) is clinically-relevant for predicting the future risk of T2D [4,16,48,49], while individuals are not necessarily in prediabetes state.…”

Section: Discussionmentioning

confidence: 99%

A Systematic Review of Biomarkers and Risk of Incident Type 2 Diabetes: An Overview of Epidemiological, Prediction and Aetiological Research Literature

et al. 2016

Self Cite

View full text Add to dashboard Cite

BackgroundBlood-based or urinary biomarkers may play a role in quantifying the future risk of type 2 diabetes (T2D) and in understanding possible aetiological pathways to disease. However, no systematic review has been conducted that has identified and provided an overview of available biomarkers for incident T2D. We aimed to systematically review the associations of biomarkers with risk of developing T2D and to highlight evidence gaps in the existing literature regarding the predictive and aetiological value of these biomarkers and to direct future research in this field.Methods and FindingsWe systematically searched PubMed MEDLINE (January 2000 until March 2015) and Embase (until January 2016) databases for observational studies of biomarkers and incident T2D according to the 2009 PRISMA guidelines. We also searched availability of meta-analyses, Mendelian randomisation and prediction research for the identified biomarkers. We reviewed 3910 titles (705 abstracts) and 164 full papers and included 139 papers from 69 cohort studies that described the prospective relationships between 167 blood-based or urinary biomarkers and incident T2D. Only 35 biomarkers were reported in large scale studies with more than 1000 T2D cases, and thus the evidence for association was inconclusive for the majority of biomarkers. Fourteen biomarkers have been investigated using Mendelian randomisation approaches. Only for one biomarker was there strong observational evidence of association and evidence from genetic association studies that was compatible with an underlying causal association. In additional search for T2D prediction, we found only half of biomarkers were examined with formal evidence of predictive value for a minority of these biomarkers. Most biomarkers did not enhance the strength of prediction, but the strongest evidence for prediction was for biomarkers that quantify measures of glycaemia.ConclusionsThis study presents an extensive review of the current state of the literature to inform the strategy for future interrogation of existing and newly described biomarkers for T2D. Many biomarkers have been reported to be associated with the risk of developing T2D. The evidence of their value in adding to understanding of causal pathways to disease is very limited so far. The utility of most biomarkers remains largely unknown in clinical prediction. Future research should focus on providing good genetic instruments across consortia for possible biomarkers in Mendelian randomisation, prioritising biomarkers for measurement in large-scale cohort studies and examining predictive utility of biomarkers for a given context.

show abstract

“…In a recent study from the Netherlands, liver function tests, including ALT, AST, GGT and albumin, modestly improved the prediction of incident diabetes in models with fasting glucose and other readily available clinical variables . In that report, liver function tests had little incremental predictive value after adding HbA 1c to the model . In the present study, ALT improved discrimination after considering glucose tolerance.…”

Section: Discussionmentioning

confidence: 96%

Discriminatory value of alanine aminotransferase for diabetes prediction: the Insulin Resistance Atherosclerosis Study

et al. 2015

View full text Add to dashboard Cite

Aims To examine the incremental usefulness of adding alanine aminotransferase to established risk factors for predicting future diabetes. Methods The study population of the Insulin Resistance Atherosclerosis Study included 724 people aged 40–69 years. We excluded people who had excessive alcohol intake or were treated with lipid-lowering agents. Incident diabetes was assessed after a mean follow-up period of 5.2 years. Results Alanine aminotransferase had a non-linear relationship with incident diabetes (Wald chi-squared test, P <0.001; P for linearity = 0.005) independent of demographic variables, family history of diabetes, BMI and fasting glucose; therefore, we used Youden’s J statistic to dichotomize alanine aminotransferase [threshold ≥0.43 μkat/L (≥26 IU/l)]. Dichotomized alanine aminotransferase increased the area under the receiver-operating characteristic curve (0.805 vs. 0.823; P = 0.007) of a model that included demographic variables, family history of diabetes, BMI and fasting glucose as independent variables. The net reclassification improvement was 9.6% (95% CI 1.8–17.4; P = 0.016), and the integrated discrimination improvement was 0.031 (95% CI 0.011–0.050; P = 0.002). Dichotomized alanine aminotransferase reclassified a net of 9.6% of individuals more appropriately. Conclusions Alanine aminotransferase may be useful for classifying individuals who are at risk of future diabetes after accounting for the effect of other risk factors, including family history, adiposity and plasma glucose.

show abstract

Liver Function Tests and Risk Prediction of Incident Type 2 Diabetes: Evaluation in Two Independent Cohorts

Cited by 35 publications

References 32 publications

Serum albumin concentration and incident type 2 diabetes risk: new findings from a population-based cohort study

Serum albumin concentration and incident type 2 diabetes risk: new findings from a population-based cohort study

A Systematic Review of Biomarkers and Risk of Incident Type 2 Diabetes: An Overview of Epidemiological, Prediction and Aetiological Research Literature

Discriminatory value of alanine aminotransferase for diabetes prediction: the Insulin Resistance Atherosclerosis Study

Contact Info

Product

Resources

About