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Uric Acid Variability as a Predictive Marker of Newly Developed Cardiovascular Events in Type 2 Diabetes.

ABSTRACT: Background: Cardiovascular disease (CVD) is associated with morbidity and mortality in patients with type 2 diabetes mellitus (T2D). However, the role of serum uric acid as a risk factor for developing cardiovascular disease is controversial. This study investigated whether uric acid variability was associated with new-onset symptomatic CVD in patients with T2D, requiring percutaneous coronary intervention. Methods: A total of 1,071 patients were enrolled in this retrospective cross-sectional study after propensity score matching. Patients with T2D and new-onset symptomatic CVD who received percutaneous coronary intervention for the first time, and with at least three consecutive 6-monthly measurements of serum uric acid were recruited from Severance Hospital between January 2015 and December 2019. Uric acid variability was measured by average successive variability (ASV) and analyzed to evaluate a possible correlation with the risk of developing CVD. Results: The patients were divided into quartiles based on the uric acid variability. Patients in the highest quartile were older and presented lower renal function and a higher mortality from CVD. There was a linear association between a high uric acid variability and the development of CVD. Compared to the lowest quartile, patients in the higher quartiles had a higher risk of CVD [quartile 3: adjusted odds ratio (aOR) = 1.76; 95% confidence interval (CI), 1.20-2.82; P = 0.019; quartile 4 aOR = 2.89; 95% CI, 1.74-4.80; P < 0.001]. Conclusion: High uric acid variability is independently associated with an increased risk of new-onset symptomatic CVD requiring percutaneous coronary intervention in patients with T2D. Thus, maintaining serum uric acid in a narrow range by prescribing effective medications is essential to prevent new-onset CVD in patients with T2D. Nonetheless, the potential use of uric acid variability as a predictive marker of CVD in patients with T2D needs further validation.

SUBMITTER: Kim HK

PROVIDER: S-EPMC8674506 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:AimsWe recently identified a metabolic signature of three amino acids (tyrosine, phenylalanine, and isoleucine) that strongly predicts diabetes development. As novel modifiable targets for intervention are needed to meet the expected increase of cardiovascular disease (CVD) caused by the diabetes epidemic, we investigated whether this diabetes-predictive amino acid score (DM-AA score) predicts development of CVD and its functional consequences.Methods and resultsWe performed a matched case-control study derived from the population-based Malmö Diet and Cancer Cardiovascular Cohort (MDC-CC), all free of CVD. During 12 years of follow-up, 253 individuals developed CVD and were matched for age, sex, and Framingham risk score with 253 controls. Amino acids were profiled in baseline plasma samples, using liquid chromatography-tandem mass spectrometry, and relationship to incident CVD was assessed using conditional logistic regression. We further examined whether the amino acid score also correlated with anatomical [intima-media thickness (IMT) and plaque formation] and functional (exercise-induced myocardial ischaemia) abnormalities. Compared with the lowest quartile of the DM-AA score, the odds ratio (95% confidence interval) for incident CVD in subjects belonging to quartiles 2, 3, and 4 was 1.27 (0.72-2.22), 1.96 (1.07-3.60), and 2.20 (1.12-4.31) (Ptrend = 0.010), respectively, after multivariate adjustment. Increasing quartile of the DM-AA score was cross-sectionally related to carotid IMT (Ptrend = 0.037) and with the presence of at least one plaque larger than 10 mm(2) (Ptrend = 0.001). Compared with the lowest quartile of the DM-AA score, the odds ratio (95% confidence interval) for inducible ischaemia in subjects belonging to quartiles 2, 3, and 4 was 3.31 (1.05-10.4), 4.24 (1.36-13.3), and 4.86 (1.47-16.1) (Ptrend = 0.011), respectively.ConclusionThis study identifies branched-chain and aromatic amino acids as novel markers of CVD development and as an early link between diabetes and CVD susceptibility.

Project description:BackgroundHigh blood pressure is a major risk factor for cardiovascular disease. Visit-to-visit blood pressure variability (BPV) has recently been shown to predict cardiovascular outcomes. We investigated the predictive value of BPV for major adverse cardiovascular events (MACE) among patients with coronary artery disease (CAD), with and without type 2 diabetes mellitus (T2DM).MethodsPatients with stable CAD were enrolled and monitored for new MACE. Visit-to-visit BPV was defined as the coefficient of variation (CV) of systolic and diastolic BP across clinic visits. Multivariable logistic regression analysis was performed to evaluate the association of BPV with MACE. Area under the receiver operating characteristic curve (AUC) was used to assess its predictive ability.ResultsAmong 1140 Chinese patients with stable CAD, 192 (17%) experienced a new MACE. In multivariable analyses, the risk of MACE was significantly associated with CV of systolic BP (odds ratio [OR] for highest versus lowest quartile, 3.30; 95% CI 1.97-5.54), and diastolic BP (OR for highest versus lowest quartile, 2.39; 95% CI 1.39-4.11), after adjustment for variables of the risk factor model (age, gender, T2DM, hypertension, antihypertensive agents, number of BP measurements) and mean BP. The risk factor model had an AUC of 0.70 for prediction of MACE. Adding systolic/diastolic CV into the risk factor model with mean BP significantly increased the AUC to 0.73/0.72 (P = 0.002/0.007). In subgroup analyses, higher CV of systolic BP remained significantly associated with an increased risk for MACE in patients with and without T2DM, whereas the association of CV of diastolic BP with MACE was observed only in those without T2DM.ConclusionsVisit-to-visit variability of systolic BP and of diastolic BP was an independent predictor of new MACE and provided incremental prognostic value beyond mean BP and conventional risk factors in patients with stable CAD. The association of BPV in CAD patients without T2DM with subsequent risk for MACE was stronger than in those with T2DM.

Project description:ObjectiveTo explore the predictive value of carotid femoral artery pulse wave velocity (CF-PWV), carotid radial artery pulse wave velocity (CR-PWV), cardio-ankle vascular index (CAVI), and ankle brachial index (ABI) on coronary heart disease (CHD) and cerebral infarction (CI), and the preliminary validation of Beijing vascular health stratification (BVHS).MethodsSubjects with at least 2 in-patient records were included into the study between 2010 and 2017 from Vascular Medicine Center of Peking University Shougang Hospital. Subjects with CHD or CI, and without data of vascular function at baseline were excluded. Eventually, 467 subjects free of CHD [cohort 1, mean age: (63.4±12.3) years, female 42.2%] and 658 subjects free of CI [cohort 2, mean age: (64.3±12.2) years, female 48.7%] at baseline were included. The first in-patient records were as the baseline data, the second in-patient records were as a following-up data. Cox proportional hazard regression was used to establish the predictive models of CHD or CI derived from BVHS by multivariable-adjusted analysis.ResultsThe median follow-up time of cohort 1 and cohort 2 was 1.9 years and 2.1 years, respectively. During the follow-up, 164 first CHD events occurred in cohort 1 and 117 first CI events occurred in cohort 2. Four indicators were assessed as continuous variables simultaneously by multivariable-adjusted analysis. In cohort 1, CF-PWV, CR-PWV, ABI, and CAVI reached statistical significance in the multivariable-adjusted models (P<0.05). In cohort 2, only CAVI (P<0.05) was of statistical significance. In addition, the higher CF-PWV became a protector of CHD or CI (P<0.05). The prediction value of BVHS reached the statistical significance for CHD and CI in the unadjusted models (all P<0.05), however, BVHS could only predict the incidence of CHD (P<0.05), but not the incidence of CI (P>0.05) in the multivariable-adjusted models. CF-PWV, CR-PWV, ABI, and CAVI were associated factors of CHD independent of each other (P<0.05), only CAVI (P<0.05) was the risk factor of CI independent of the other three.ConclusionThe different vascular indicators might have different effect on CHD or CI. CAVI might be a stable predictor of both CHD and CI. Higher baseline CF-PWV was not necessarily a risk factor of CHD or CI because of proper vascular health management. BVHS was a potential factor for the prediction of CHD, and further research is needed to explore the prediction value for CI.

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Uric Acid Variability as a Predictive Marker of Newly Developed Cardiovascular Events in Type 2 Diabetes.

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