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Multiplex proteomics for prediction of major cardiovascular events in type 2 diabetes.

ABSTRACT: AIMS/HYPOTHESIS:Multiplex proteomics could improve understanding and risk prediction of major adverse cardiovascular events (MACE) in type 2 diabetes. This study assessed 80 cardiovascular and inflammatory proteins for biomarker discovery and prediction of MACE in type 2 diabetes. METHODS:We combined data from six prospective epidemiological studies of 30-77-year-old individuals with type 2 diabetes in whom 80 circulating proteins were measured by proximity extension assay. Multivariable-adjusted Cox regression was used in a discovery/replication design to identify biomarkers for incident MACE. We used gradient-boosted machine learning and lasso regularised Cox regression in a random 75% training subsample to assess whether adding proteins to risk factors included in the Swedish National Diabetes Register risk model would improve the prediction of MACE in the separate 25% test subsample. RESULTS:Of 1211 adults with type 2 diabetes (32% women), 211 experienced a MACE over a mean (±SD) of 6.4?±?2.3 years. We replicated associations (<5% false discovery rate) between risk of MACE and eight proteins: matrix metalloproteinase (MMP)-12, IL-27 subunit ? (IL-27a), kidney injury molecule (KIM)-1, fibroblast growth factor (FGF)-23, protein S100-A12, TNF receptor (TNFR)-1, TNFR-2 and TNF-related apoptosis-inducing ligand receptor (TRAIL-R)2. Addition of the 80-protein assay to established risk factors improved discrimination in the separate test sample from 0.686 (95% CI 0.682, 0.689) to 0.748 (95% CI 0.746, 0.751). A sparse model of 20 added proteins achieved a C statistic of 0.747 (95% CI 0.653, 0.842) in the test sample. CONCLUSIONS/INTERPRETATION:We identified eight protein biomarkers, four of which are novel, for risk of MACE in community residents with type 2 diabetes, and found improved risk prediction by combining multiplex proteomics with an established risk model. Multiprotein arrays could be useful in identifying individuals with type 2 diabetes who are at highest risk of a cardiovascular event.

SUBMITTER: Nowak C

PROVIDER: S-EPMC6061158 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Multiplex proteomics for prediction of major cardiovascular events in type 2 diabetes.

Nowak Christoph C Carlsson Axel C AC Östgren Carl Johan CJ Nyström Fredrik H FH Alam Moudud M Feldreich Tobias T Sundström Johan J Carrero Juan-Jesus JJ Leppert Jerzy J Hedberg Pär P Henriksen Egil E Cordeiro Antonio C AC Giedraitis Vilmantas V Lind Lars L Ingelsson Erik E Fall Tove T Ärnlöv Johan J

Diabetologia 20180524 8

<h4>Aims/hypothesis</h4>Multiplex proteomics could improve understanding and risk prediction of major adverse cardiovascular events (MACE) in type 2 diabetes. This study assessed 80 cardiovascular and inflammatory proteins for biomarker discovery and prediction of MACE in type 2 diabetes.<h4>Methods</h4>We combined data from six prospective epidemiological studies of 30-77-year-old individuals with type 2 diabetes in whom 80 circulating proteins were measured by proximity extension assay. Multiv ...[more]

PMID: 29796748

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Project description:ImportanceWhether optimal cardiovascular health metrics may counteract the risk of cardiovascular events among patients with prediabetes or diabetes is unclear.ObjectiveTo investigate the associations of ideal cardiovascular health metrics (ICVHMs) with subsequent development of cardiovascular disease (CVD) among participants with prediabetes or diabetes as compared with participants with normal glucose regulation.Design, setting, and participantsThe China Cardiometabolic Disease and Cancer Cohort Study was a nationwide, population-based, prospective cohort study of 20 communities from various geographic regions in China. The study included 111 765 participants who were free from CVD or cancer at baseline. Data were analyzed between 2011 and 2016.ExposuresPrediabetes and diabetes were defined according to the American Diabetes Association 2010 criteria. Seven ICVHMs were adapted from the American Heart Association recommendations.Main outcomes and measuresThe composite of incident fatal or nonfatal CVD, including cardiovascular death, myocardial infarction, stroke, and hospitalized or treated heart failure.ResultsOf the 111 765 participants, 24 881 (22.3%) had normal glucose regulation, 61 024 (54.6%) had prediabetes, and 25 860 (23.1%) had diabetes. Mean (SD) age ranged from 52.9 (8.6) years to 59.4 (8.7) years. Compared with participants with normal glucose regulation, among participants with prediabetes, the multivariable-adjusted hazard ratio for CVD was 1.34 (95% CI, 1.16-1.55) for participants who had 1 ICVHM or less and 0.57 (95% CI, 0.43-0.75) for participants who had at least 5 ICVHMs; among participants with diabetes, the hazard ratios for CVD were 2.05 (95% CI, 1.76-2.38) and 0.80 (95% CI, 0.56-1.15) for participants who had 1 ICVHM or less and at least 5 ICVHMs, respectively. Such pattern of association between ICVHMs and CVD was more prominent for participants younger than 55 years (prediabetes and at least 5 ICVHMs: hazard ratio [HR], 0.32; 95% CI, 0.16-0.63; 1 ICVHM or less: HR, 1.58; 95% CI, 1.13-2.21; diabetes and at least 5 ICVHMs: HR, 0.99; 95% CI, 0.44-2.26; 1 ICVHM or less: HR, 2.46; 95% CI, 1.71-3.54; compared with normal glucose regulation) than for participants 65 years or older (prediabetes and at least 5 ICVHMs: HR, 0.80; 95% CI, 0.50-1.26; 1 ICVHM or less: HR, 1.01; 95% CI, 0.79-1.31; diabetes and at least 5 ICVHMs: HR, 0.79; 95% CI, 0.46-1.35; 1 ICVHM or less: HR, 1.73; 95% CI, 1.36-2.22, compared with normal glucose regulation; P values for interaction ≤.02). Additionally, the hazard ratio for CVD per additional ICVHM was 0.82 (95% CI, 0.79-0.86) among participants with prediabetes and was 0.85 (95% CI, 0.80-0.89) among participants with diabetes.Conclusions and relevanceParticipants with prediabetes or diabetes who had 5 or more ICVHMs exhibited lower or no significant excess CVD risks compared with the participants with normal glucose regulation.

Project description:BackgroundThe triglyceride-glucose (TyG) index is a reliable surrogate marker of insulin resistance and is associated with major adverse cardiovascular events (MACEs) in patients with type 2 diabetes mellitus (T2DM). However, the long-term effect of the TyG index on the incidence of MACEs remains unclear. We aimed to investigate the association between the cumulative TyG index and the risk of MACEs in patients with T2DM.MethodsThis post-hoc analysis of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial assessed patients' (T2DM > 3 months) cumulative TyG index and MACE data from the study database. Five fasting blood glucose and triglyceride measurements, at baseline and the first four visits, were taken from 5695 participants who had not experienced MACEs. Cumulative exposure to the TyG index was calculated as the weighted sum of the mean TyG index value for each time interval (value × time). Multivariable-adjusted Cox proportional hazard models and restricted cubic spline analysis were used to determine the association between the cumulative TyG index and MACEs. The incremental predictive value of the cumulative TyG index was further assessed.ResultsOver a median follow-up of 5.09 years, 673 (11.82%) MACEs occurred, including 256 (4.50%) cardiovascular disease (CVD) deaths, 288 (5.06%) non-fatal myocardial infarctions (MIs), and 197 (3.46%) strokes. The risk of developing MACEs increased with the cumulative TyG index quartile. After adjusting for multiple potential confounders, the hazard ratios for the very high cumulative TyG index group versus the low group were 1.59 (95% confidence interval [CI], 1.17-2.16), 1.97 (95% CI 1.19-3.26), and 1.66 (95% CI 1.02-2.70) for overall MACEs, CVD death, and non-fatal MI, respectively. Restricted cubic spline analysis also showed a cumulative increase in the risk of MACEs with an increase in the magnitude of the cumulative TyG index. The addition of the cumulative TyG index to a conventional risk model for MACEs improved the C-statistics, net reclassification improvement value, and integrated discrimination improvement value.ConclusionsIn patients with T2DM, the cumulative TyG index independently predicts the incidence of MACEs, and monitoring the long-term TyG index may assist with optimized-for-risk stratification and outcome prediction for MACEs. Trial registration URL: http://www.Clinicaltrialsgov . Unique identifier: NCT00000620.

Project description:Importance:The comparative cardiovascular safety of analogue and human insulins in adults with type 2 diabetes who initiate insulin therapy in usual care settings has not been carefully evaluated using machine learning and other rigorous analytic methods. Objective:To examine the association of analogue vs human insulin use with mortality and major cardiovascular events. Design, Setting, and Participants:This retrospective cohort study included 127 600 adults aged 21 to 89 years with type 2 diabetes at 4 health care delivery systems who initiated insulin therapy from January 1, 2000, through December 31, 2013. Machine learning and rigorous inference methods with time-varying exposures were used to evaluate associations of continuous exposure to analogue vs human insulins with mortality and major cardiovascular events. Data were analyzed from September 1, 2017, through June 30, 2018. Exposures:On the index date (first insulin dispensing), participants were classified as using analogue insulin with or without human insulin or human insulin only. Main Outcomes and Measures:Overall mortality, mortality due to cardiovascular disease (CVD), myocardial infarction (MI), stroke or cerebrovascular accident (CVA), and hospitalization for congestive heart failure (CHF) were evaluated. Marginal structural modeling (MSM) with inverse probability weighting was used to compare event-free survival in separate per-protocol analyses. Adjusted and unadjusted hazard ratios and cumulative risk differences were based on logistic MSM parameterizations for counterfactual hazards. Propensity scores were estimated using a data-adaptive approach (machine learning) based on 3 nested covariate adjustment sets. Sensitivity analyses were conducted to address potential residual confounding from unmeasured differences in risk factors across delivery systems. Results:The 127 600 participants (mean [SD] age, 59.4 [12.6] years; 68 588 men [53.8%]; mean [SD] body mass index, 32.3 [7.1]) had a median follow-up of 4 quarters (interquartile range, 3-9 quarters) and experienced 5464 deaths overall (4.3%), 1729 MIs (1.4%), 1301 CVAs (1.0%), and 3082 CHF hospitalizations (2.4%). There were no differences in adjusted hazard ratios for continuous analogue vs human insulin exposure during 10 quarters for overall mortality (1.15; 95% CI, 0.97-1.34), CVD mortality (1.26; 95% CI, 0.86-1.66), MI (1.11; 95% CI, 0.77-1.45), CVA (1.30; 95% CI, 0.81-1.78), or CHF hospitalization (0.93; 95% CI, 0.75-1.11). Conclusions and Relevance:Insulin-naive adults with type 2 diabetes who initiate and continue treatment with human vs analogue insulins had similar observed rates of major cardiovascular events, CVD mortality, and overall mortality.

Project description:BackgroundPrevious studies reported the prognostic value of the atherogenic index of plasma (AIP) in the course of atherosclerosis and other cardiovascular diseases (CVDs). Still, the predictive utility of the AIP is unknown among patients with type 2 diabetes mellitus (T2DM).MethodsThis was a secondary analysis of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study, which randomized 10,251 patients with long-lasting T2DM. ROC curve analysis was used to determine an optimal threshold for AIP, and the study population was divided into high and low AIP groups. Univariable and multivariable Cox proportional hazards regression analyses were used to determine the association between AIP and primary (major adverse cardiovascular events [MACEs], including nonfatal myocardial infarction, nonfatal stroke, and/or death from cardiovascular causes) and secondary outcomes (all-cause mortality). Stratified analyses were performed to control for the confounding factors.ResultsAIP was an independent risk factor for the prognosis of T2DM (HR = 1.309; 95% CI 1.084-1.581; P = 0.005). The threshold for AIP was determined to be 0.34 in the study population. After adjustments for confounding factors, multivariable analysis showed that AIP was associated with the risk of MACEs (Model 1: HR = 1.333, 95% CI 1.205-1.474, P < 0.001; Model 2: HR = 1.171, 95% CI 1.030-1.333, P = 0.016; Model 3: HR = 1.194, 95% CI 1.049-1.360, P = 0.007), all-cause mortality (Model 1: HR = 1.184, 95% CI 1.077-1.303, P < 0.001), cardiovascular death (Model 1: HR = 1.422, 95% CI 1.201-1.683, P < 0.001; Model 3: HR = 1.264, 95% CI 1.015-1.573, P = 0.036), and nonfatal myocardial infarction (Model 1: HR = 1.447, 95% CI 1.255-1.669, P < 0.001; Model 2: HR = 1.252, 95% CI 1.045-1.499, P = 0.015; Model 3: HR = 1.284, 95% CI 1.071-1.539, P = 0.007). Subgroup stratified analyses showed that AIP might interact with sex, a classical risk factor of cardiovascular events.ConclusionsThis study showed that AIP might be a strong biomarker that could be used to predict the risk of cardiovascular events in patients with T2DM.Trial registrationURL: http://www.clinicaltrials.gov . Unique identifier: NCT00000620.

Project description:BackgroundAdvanced glycation end-products play a role in diabetic vascular complications. Their optical properties allow to estimate their accumulation in tissues by measuring the skin autofluorescence (SAF). We searched for an association between SAF and major adverse cardiovascular events (MACE) incidence in subjects with Type 1 Diabetes (T1D) during a 7 year follow-up.MethodsDuring year 2009, 232 subjects with T1D were included. SAF measurement, clinical [age, sex, body mass index (BMI), comorbidities] and biological data (HbA1C, blood lipids, renal parameters) were recorded. MACE (myocardial infarction, stroke, lower extremity amputation or a revascularization procedure) were registered at visits in the center or by phone call to general practitioners until 2016.ResultsThe participants were mainly men (59.5%), 51.5 ± 16.7 years old, with BMI 25.0 ± 4.1 kg/m2, diabetes duration 21.5 ± 13.6 years, HbA1C 7.6 ± 1.1%. LDL cholesterol was 1.04 ± 0.29 g/L, estimated Glomerular Filtration Rates (CKD-EPI): 86.3 ± 26.6 ml/min/1.73 m2. Among these subjects, 25.1% were smokers, 45.3% had arterial hypertension, 15.9% had elevated AER (≥ 30 mg/24 h), and 9.9% subjects had a history of previous MACE. From 2009 to 2016, 22 patients had at least one new MACE: 6 myocardial infarctions, 1 lower limb amputation, 15 revascularization procedures. Their SAF was 2.63 ± 0.73 arbitrary units (AU) vs 2.08 ± 0.54 for other patients (p = 0.002). Using Cox-model, after adjustment for age (as the scale time), sex, diabetes duration, BMI, hypertension, smoking status, albumin excretion rates, statin treatment and a previous history of MACE, higher baseline levels of SAF were significantly associated with an increased risk of MACE during follow-up (HR = 4.13 [1.30-13.07]; p = 0.02 for 1 AU of SAF) and Kaplan-Meier curve follow-up showed significantly more frequent MACE in group with SAF upper the median (p = 0.001).ConclusionA high SAF predicts MACE in patients with T1D.

Project description:To identify possible differences in cardiovascular (CV) risk among different insulin therapies, we performed pre-specified meta-analyses across the clinical program for basal insulin peglispro (BIL), in patients randomized to treatment with BIL or comparator insulin [glargine (IG) or NPH].One phase 2 (12-week) and 6 phase 3 (26 to 78-week) randomized studies of BIL compared to IG or NPH, in patients with type 1 or type 2 diabetes, were included. The participants were diverse with respect to demographics, baseline glycemic control, and concomitant disease or medications, but treatment groups were comparable in each study. For any potential CV or neurovascular event, relevant medical information was provided to a blinded external clinical events committee (C5Research, Cleveland Clinic, Cleveland, OH, USA) for adjudication. Cox regression analysis was used to compare treatment groups. The primary endpoint was a composite of adjudicated MACE+ [CV death, myocardial infarction (MI), stroke, or hospitalization for unstable angina].The pooled population included 5862 patients in the safety evaluation, with randomization to BIL:IG:NPH of 3578:2072:212. Mean age was 54.1 years, 27 % had type 1 diabetes, 56 % were male, and 88 % were white. Baseline demographic and clinical characteristics, including use of statins or other lipid-lowering drugs, were comparable between BIL and comparators. A total of 83 patients experienced at least 1 MACE+ and 70 patients experienced at least 1 MACE (CV death, MI, or stroke). Overall, there were no treatment-associated differences in time to MACE+ [hazard ratio (HR) for BIL versus comparator insulin (95 % CI): 0.82 (0.53-1.27)] or MACE [0.83 (0.51-1.33)]. In 4297 patients with type 2 diabetes, there were 71 MACE+ events [HR: 1.02 (95 % CI: 0.63-1.65), p = 0.94]. In 1565 patients with type 1 diabetes, there were only 12 MACE+ [0.24 (0.07-0.85), p = 0.027]. There were no differences in all-cause death between BIL and comparators. Sub-group analyses did not identify any sub-population with increased risk with BIL versus comparator insulins.Treatment with BIL versus comparator insulin in patients with type 1 diabetes or type 2 diabetes was not associated with increased risk for major CV events in the studies analyzed.

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Multiplex proteomics for prediction of major cardiovascular events in type 2 diabetes.

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Multiplex proteomics for prediction of major cardiovascular events in type 2 diabetes.

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