Dissatisfaction with teeth in type 2 diabetes is associated with increased risk of cardiovascular disease

Background and aim Poor dental health status has been linked to increased risk of cardiovascular events in type 2 diabetes (T2D). Less is known about self-perceived dental health and cardiovascular risk. Our aim with this study was to investigate this association. Methods Recruitment of T2D patients took place between 2005 and 2008 in Swedish primary care. Teeth satisfaction was assessed by questionnaire at baseline. The major adverse cardiovascular events (MACE) in this study were hospitalization due to myocardial infarction, stroke or cardiovascular death. Cox regression models were used. Results Out of 761 participants 601 had complete data. Ninety-two MACEs occurred (median follow-up time: 11.6 years). Those satisfied with their teeth (n = 458) had 61 events (1.2 events per 100 person-years), while those dissatisfied with teeth (n = 143) had 31 events (2.2 events per 100 person-years). Dissatisfaction with teeth was associated with an increased risk of MACE independent of age, sex and levels of CRP (HR 1.85, 95% CI 1.20 – 2.86). Conclusions In patients with T2D, dissatisfaction with teeth was associated with increased risk of MACE and may be considered as a marker of risk.Funding agencies: This work was supported by grant support from FORSS, the Medical Research Council of Southeast Sweden.</p

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

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 (&lt; 5% false discovery rate) between risk of MACE and eight proteins: matrix metalloproteinase (MMP)-12, IL-27 subunit alpha (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

The association between plasma proteomics and incident cardiovascular disease identifies MMP-12 as a promising cardiovascular risk marker in patients with chronic kidney disease

Background and aims: Previous proteomics efforts in patients with chronic kidney disease (CKD) have predominantly evaluated urinary protein levels. Therefore, our aim was to investigate the association between plasma levels of 80 cardiovascular disease-related proteins and the risk of major adverse cardiovascular events (MACE) in patients with CKD. Methods: Individuals with CKD stages 3-5 (eGFR below 60 ml min-1 [1.73 m]-2) from three community-based cohorts (PIVUS, ULSAM, SAVA), one diabetes cohort (CARDIPP) and one cohort with peripheral artery disease patients (PADVA) with information on 80 plasma protein biomarkers, assessed with a proximity extension assay, and follow-up data on incident MACE, were used as discovery sample. To validate findings and to asses generalizability to patients with CKD in clinical practice, an outpatient CKD-cohort (Malnutrition, Inflammation and Vascular Calcification (MIVC)) was used as replication sample. Results: In the discovery sample (total n = 1316), 249 individuals experienced MACE during 7.0 +/- 2.9 years (range 0.005-12.9) of follow-up, and in the replication sample, 71 MACE events in 283 individuals over a mean +/- SD change of 2.9 +/- 1.2 years (range 0.1-4.0) were documented. Applying Bonferroni correction, 18 proteins were significantly associated with risk of MACE in the discovery cohort, adjusting for age and sex in order of significance, GDF-15, FGF-23, REN, FABP4, IL6, TNF-R1, AGRP, MMP-12, AM, KIM-1, TRAILR2, TNFR2, CTSL1, CSF1, PlGF, CA-125, CCL20 and PAR-1 (p &lt; 0.000625 for all). Only matrix metalloproteinase 12 (MMP-12) was significantly associated with an increased risk of MACE in the replication sample (hazard ratio (HR) per SD increase, 1.36, 95% CI (1.07-1.75), p = 0.013). Conclusions: Our proteomics analyses identified plasma MMP-12 as a promising cardiovascular risk marker in patients with CKD

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

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 (&lt; 5% false discovery rate) between risk of MACE and eight proteins: matrix metalloproteinase (MMP)-12, IL-27 subunit alpha (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

Plasma Protein Profile of Carotid Artery Atherosclerosis and Atherosclerotic Outcomes : Meta-Analyses and Mendelian Randomization Analyses

OBJECTIVE: To identify causal pathophysiological mechanisms for atherosclerosis and incident cardiovascular events using protein measurements. Approach and Results: Carotid artery atherosclerosis was assessed by ultrasound, and 86 cardiovascular-related proteins were measured using the Olink CVD-I panel in 7 Swedish prospective studies (11 754 individuals). The proteins were analyzed in relation to intima-media thickness in the common carotid artery (IMT-CCA), plaque occurrence, and incident cardiovascular events (composite end point of myocardial infarction or ischemic stroke) using a discovery/replication approach in different studies. After adjustments for traditional cardiovascular risk factors, 11 proteins remained significantly associated with IMT-CCA in the replication stage, whereas 9 proteins were replicated for plaque occurrence and 17 proteins for incident cardiovascular events. NT-proBNP (N-terminal pro-B-type natriuretic peptide) and MMP (matrix metalloproteinase)-12 were associated with both IMT-CCA and incident events, but the overlap was considerably larger between plaque occurrence and incident events, including MMP-12, TIM-1 (T-cell immunoglobulin and mucin domain 1), GDF (growth/differentiation factor)-15, IL (interleukin)-6, U-PAR (urokinase plasminogen activator surface receptor), LOX-1 (lectin-like oxidized LDL [low-density lipoprotein] receptor 1), and TRAIL-R2 (TNF [tumor necrosis factor]-related apoptosis-inducing ligand receptor 2). Only MMP-12 was associated with IMT-CCA, plaque, and incident events with a positive and concordant direction of effect. However, a 2-sample Mendelian randomization analysis suggested that increased MMP-12 may be protective against ischemic stroke (P=5.5×10-7), which is in the opposite direction of the observational analyses.CONCLUSIONS: The present meta-analysis discovered several proteins related to carotid atherosclerosis that partly differed in their association with IMT-CCA, plaque, and incident atherosclerotic disease. Mendelian randomization analysis for the top finding, MMP-12, suggests that the increased levels of MMP-12 could be a consequence of atherosclerotic burden rather than the opposite chain of events