Dataset Information

Thirty-one novel biomarkers as predictors for clinically incident diabetes.

ABSTRACT:

Background

The prevalence of diabetes is increasing in all industrialized countries and its prevention has become a public health priority. However, the predictors of diabetes risk are insufficiently understood. We evaluated, whether 31 novel biomarkers could help to predict the risk of incident diabetes.

Methods and findings

The biomarkers were evaluated primarily in the FINRISK97 cohort (n = 7,827; 417 cases of clinically incident diabetes during the follow-up). The findings were replicated in the Health 2000 cohort (n = 4,977; 179 cases of clinically incident diabetes during the follow-up). We used Cox proportional hazards models to calculate the relative risk of diabetes, after adjusting for the classic risk factors, separately for each biomarker. Next, we assessed the discriminatory ability of single biomarkers using receiver operating characteristic curves and C-statistics, integrated discrimination improvement (IDI) and net reclassification improvement (NRI). Finally, we derived a biomarker score in the FINRISK97 cohort and validated it in the Health 2000 cohort. A score consisting of adiponectin, apolipoprotein B, C-reactive protein and ferritin almost doubled the relative risk of diabetes in the validation cohort (HR per one standard deviation increase 1.88, p = 2.8 e-5). It also improved discrimination of the model (IDI = 0.0149, p<0.0001) and reclassification of diabetes risk (NRI = 11.8%, p = 0.006). Gender-specific analyses suggested that the best score differed between men and women. Among men, the best results were obtained with the score of four biomarkers: adiponectin, apolipoprotein B, ferritin and interleukin-1 receptor antagonist, which gave an NRI of 25.4% (p<0.0001). Among women, the best score included adiponectin, apolipoprotein B, C-reactive protein and insulin. It gave an NRI of 13.6% (p = 0.041).

Conclusions

We identified novel biomarkers that were associated with the risk of clinically incident diabetes over and above the classic risk factors. This gives new insights into the pathogenesis of diabetes and may help with targeting prevention and treatment.

SUBMITTER: Salomaa V

PROVIDER: S-EPMC2852424 | biostudies-literature | 2010 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Thirty-one novel biomarkers as predictors for clinically incident diabetes.

Salomaa Veikko V Havulinna Aki A Saarela Olli O Zeller Tanja T Jousilahti Pekka P Jula Antti A Muenzel Thomas T Aromaa Arpo A Evans Alun A Kuulasmaa Kari K Blankenberg Stefan S

PloS one 20100409 4

<h4>Background</h4>The prevalence of diabetes is increasing in all industrialized countries and its prevention has become a public health priority. However, the predictors of diabetes risk are insufficiently understood. We evaluated, whether 31 novel biomarkers could help to predict the risk of incident diabetes.<h4>Methods and findings</h4>The biomarkers were evaluated primarily in the FINRISK97 cohort (n = 7,827; 417 cases of clinically incident diabetes during the follow-up). The findings wer ...[more]

PMID: 20396381

Similar Datasets

Project description:Rationale & objectiveBiomarkers of kidney disease progression have been identified in individuals with diabetes and underlying chronic kidney disease (CKD). Whether or not these markers are associated with the development of CKD in a general population without diabetes or CKD is not well established.Study designProspective observational cohort.Setting & participantsIn the Atherosclerosis Risk in Communities) study, 948 participants were studied.ExposuresThe baseline plasma biomarkers of kidney injury molecule-1 (KIM-1), monocyte chemoattractant protein-1 (MCP-1), soluble urokinase plasminogen activator receptor (suPAR), tumor necrosis factor receptor 1 (TNFR-1), tumor necrosis factor receptor 2 (TNFR-2), and human cartilage glycoprotein-39 (YKL-40) measured in 1996-1998.OutcomeIncident CKD after 15 years of follow-up defined as ≥40% estimated glomerular filtration rate decline to <60 mL/min/1.73 m2 or dialysis dependence through United States Renal Data System linkage.Analytical approachLogistic regression and C statistics.ResultsThere were 523 cases of incident CKD. Compared with a random sample of 425 controls, there were greater odds of incident CKD per 2-fold higher concentration of KIM-1 (OR, 1.49; 95% CI, 1.25-1.78), suPAR (OR, 2.57; 95% CI, 1.74-3.84), TNFR-1 (OR, 2.20; 95% CI, 1.58-3.09), TNFR-2 (OR, 2.03; 95% CI, 1.37-3.04). After adjustment for all biomarkers, KIM-1 (OR, 1.42; 95% CI, 1.19-1.71), and suPAR (OR, 1.86; 95% CI, 1.18-2.92) remained associated with incident CKD. Compared with traditional risk factors, the addition of all 6 biomarkers improved the C statistic from 0.695-0.731 (P < 0.01) and using the observed risk of 12% for incident CKD, the predicted risk gradient changed from 5%-40% (for the 1st-5th quintile) to 4%-44%.LimitationsBiomarkers and creatinine were measured at one time point.ConclusionsHigher levels of KIM-1, suPAR, TNFR-1, and TNFR-2 were associated with higher odds of incident CKD among individuals without diabetes.Plain-language summaryFor people with diabetes or kidney disease, several biomarkers have been shown to be associated with worsening kidney disease. Whether these biomarkers have prognostic significance in people without diabetes or kidney disease is less studied. Using the Atherosclerosis Risk in Communities study, we followed individuals without diabetes or kidney disease for an average of 15 years after biomarker measurement to see if these biomarkers were associated with the development of kidney disease. We found that elevated levels of KIM-1, suPAR, TNFR-1, and TNFR-2 were associated with the development of kidney disease. These biomarkers may help identify individuals who would benefit from interventions to prevent the development of kidney disease.

Project description:Objective:To conduct a descriptive analysis of the sweat test (ST), associating ST results with epidemiological data, CFTR (cystic fibrosis transmembrane conductance regulator) mutations and reasons to indicate the ST, as well as correlating sweat sodium and sweat chloride concentrations in subjects. Methods:Retrospective survey and descriptive analysis of 5,721 ST at a university referral center. Results:The inclusion of the subjects was based on clinical data related with cystic fibrosis (CF) phenotype. The samples were grouped by (i) sweat chloride concentrations (mEq/L): <30: 3,249/5,277 (61.6%); ?30 to <60: 1,326/5,277 (25.1%); ?60: 702/5,277 (13.3%) and (ii) age: (Group A--GA) 0 to <6?months; (Group B--GB) ?6?months to <18?years; (Group C--GC) ?18?years. Digestive symptoms showed higher prevalence ratio for the CF diagnosis as well as association between younger age and higher values of sweat chloride, sweat sodium, and chloride/sodium ratio. The indication of ST due to respiratory symptoms was higher in GB and associated with greater age, lower values of sweat chloride, sweat sodium, and chloride/sodium ratio. There was higher prevalence of ST with sweat chloride levels <30?mEq/L in GB, ?60?mEq/L in GC, and with borderline level in GB. There was positive correlation between sweat sodium and sweat chloride. Sweat chloride/sweat sodium and sweat sodium-sweat chloride indexes showed association with sex, reason for ST indication, and CFTR mutations. Sex alters some values presented in the ST. The number of ST/year performed before and after the newborn screening implementation was the same; however, we observed a higher number of borderlines values. A wide spectrum of CFTR mutation was found. Severe CFTR mutations and F508del/F508del genotype were associated with highest probability of ST chloride levels ?60?mEq/L, and the absence of CFTR mutations identified was associated with borderline ST and respiratory symptoms. Conclusions:ST data showed wide variability dependent on age, sex, reason for examination indication, CFTR mutations, and weight of the collected sweat sample. Sweat sodium concentration is directly correlated with sweat chloride levels and it could be used as a quality parameter.

Project description:Aims/hypothesisWe compared the associations of circulating biomarkers of inflammation, endothelial and adipocyte dysfunction and coagulation with incident diabetes in the placebo, lifestyle and metformin intervention arms of the Diabetes Prevention Program, a randomised clinical trial, to determine whether reported associations in general populations are reproduced in individuals with impaired glucose tolerance, and whether these associations are independent of traditional diabetes risk factors. We further investigated whether biomarker-incident diabetes associations are influenced by interventions that alter pathophysiology, biomarker concentrations and rates of incident diabetes.MethodsThe Diabetes Prevention Program randomised 3234 individuals with impaired glucose tolerance into placebo, metformin (850 mg twice daily) and intensive lifestyle groups and showed that metformin and lifestyle reduced incident diabetes by 31% and 58%, respectively compared with placebo over an average follow-up period of 3.2 years. For this study, we measured adiponectin, leptin, tissue plasminogen activator (as a surrogate for plasminogen activator inhibitor 1), high-sensitivity C-reactive protein, IL-6, monocyte chemotactic protein 1, fibrinogen, E-selectin and intercellular adhesion molecule 1 at baseline and at 1 year by specific immunoassays. Traditional diabetes risk factors were defined as family history, HDL-cholesterol, triacylglycerol, BMI, fasting and 2 h glucose, HbA1c, systolic blood pressure, inverse of fasting insulin and insulinogenic index. Cox proportional hazard models were used to assess the effects of each biomarker on the development of diabetes assessed semi-annually and the effects of covariates on these.ResultsE-selectin, (HR 1.19 [95% CI 1.06, 1.34]), adiponectin (0.84 [0.71, 0.99]) and tissue plasminogen activator (1.13 [1.03, 1.24]) were associated with incident diabetes in the placebo group, independent of diabetes risk factors. Only the association between adiponectin and diabetes was maintained in the lifestyle (0.69 [0.52, 0.92]) and metformin groups (0.79 [0.66, 0.94]). E-selectin was not related to diabetes development in either lifestyle or metformin groups. A novel association appeared for change in IL-6 in the metformin group (1.09 [1.021, 1.173]) and for baseline leptin in the lifestyle groups (1.31 [1.06, 1.63]).Conclusions/interpretationThese findings clarify associations between an extensive group of biomarkers and incident diabetes in a multi-ethnic cohort with impaired glucose tolerance, the effects of diabetes risk factors on these, and demonstrate differential modification of associations by interventions. They strengthen evidence linking adiponectin to diabetes development, and argue against a central role for endothelial dysfunction. The findings have implications for the pathophysiology of diabetes development and its prevention.

Dataset Information

Thirty-one novel biomarkers as predictors for clinically incident diabetes.

Background

Methods and findings

Conclusions

Publications

Thirty-one novel biomarkers as predictors for clinically incident diabetes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets