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          Abstract

          Background

          To determine whether the pro-inflammatory cytokine interleukin (IL)-1beta, as a marker of the nucleotide binding and oligomerization domain-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome activation, can be used to predict cardiovascular disease (CVD) risk in patients with newly diagnosed, drug-naïve type 2 diabetes mellitus (T2DM).

          Methods

          A total of 110 subjects with no history of diabetes were enrolled and divided into control subjects (non-DM group, n=52) and patients with newly diagnosed, drug-naïve T2DM (DM group, n=58).

          Results

          Serum IL-1beta levels were not different between the two groups. The Framingham CVD risk score (F-score) was positively correlated with the serum IL-1beta level in the DM group. Multivariate regression analyses showed that the F-score was independently associated with the serum IL-1beta level in the DM group. Patients with an intermediate to high CVD risk (F-score ≥10%) also had significantly higher serum IL-1beta levels than did those with a low CVD risk (F-score <5%). Smokers in the DM group had higher IL-1beta levels than did those in the non-DM group, regardless of the F-score.

          Conclusions

          These results suggest that serum IL-1beta levels might be useful as an independent risk factor predicting CVD risk in patients with newly diagnosed, drug naïve T2DM, particularly those who smoke.

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          Most cited references44

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          General cardiovascular risk profile for use in primary care: the Framingham Heart Study.

          Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease (CVD) events, ie, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and heart failure. The present report presents a single multivariable risk function that predicts risk of developing all CVD and of its constituents. We used Cox proportional-hazards regression to evaluate the risk of developing a first CVD event in 8491 Framingham study participants (mean age, 49 years; 4522 women) who attended a routine examination between 30 and 74 years of age and were free of CVD. Sex-specific multivariable risk functions ("general CVD" algorithms) were derived that incorporated age, total and high-density lipoprotein cholesterol, systolic blood pressure, treatment for hypertension, smoking, and diabetes status. We assessed the performance of the general CVD algorithms for predicting individual CVD events (coronary heart disease, stroke, peripheral artery disease, or heart failure). Over 12 years of follow-up, 1174 participants (456 women) developed a first CVD event. All traditional risk factors evaluated predicted CVD risk (multivariable-adjusted P<0.0001). The general CVD algorithm demonstrated good discrimination (C statistic, 0.763 [men] and 0.793 [women]) and calibration. Simple adjustments to the general CVD risk algorithms allowed estimation of the risks of each CVD component. Two simple risk scores are presented, 1 based on all traditional risk factors and the other based on non-laboratory-based predictors. A sex-specific multivariable risk factor algorithm can be conveniently used to assess general CVD risk and risk of individual CVD events (coronary, cerebrovascular, and peripheral arterial disease and heart failure). The estimated absolute CVD event rates can be used to quantify risk and to guide preventive care.
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            Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man.

            The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from varying degrees beta-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient beta-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and beta-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (Rs = 0.88, p less than 0.0001), the fasting insulin concentration (Rs = 0.81, p less than 0.0001), and the hyperglycaemic clamp, (Rs = 0.69, p less than 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient beta-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (Rs = 0.61, p less than 0.01) and with the estimate from the intravenous glucose tolerance test (Rs = 0.64, p less than 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for beta-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop.
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              Pathophysiology and treatment of type 2 diabetes: perspectives on the past, present, and future.

              Glucose metabolism is normally regulated by a feedback loop including islet β cells and insulin-sensitive tissues, in which tissue sensitivity to insulin affects magnitude of β-cell response. If insulin resistance is present, β cells maintain normal glucose tolerance by increasing insulin output. Only when β cells cannot release sufficient insulin in the presence of insulin resistance do glucose concentrations rise. Although β-cell dysfunction has a clear genetic component, environmental changes play an essential part. Modern research approaches have helped to establish the important role that hexoses, aminoacids, and fatty acids have in insulin resistance and β-cell dysfunction, and the potential role of changes in the microbiome. Several new approaches for treatment have been developed, but more effective therapies to slow progressive loss of β-cell function are needed. Recent findings from clinical trials provide important information about methods to prevent and treat type 2 diabetes and some of the adverse effects of these interventions. However, additional long-term studies of drugs and bariatric surgery are needed to identify new ways to prevent and treat type 2 diabetes and thereby reduce the harmful effects of this disease. Copyright © 2014 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                Ann Transl Med
                Ann Transl Med
                ATM
                Annals of Translational Medicine
                AME Publishing Company
                2305-5839
                2305-5847
                March 2020
                March 2020
                : 8
                : 5
                : 225
                Affiliations
                [1 ]Department of International Medicine, Chungnam National University College of Medicine, Daejeon, Republic of Korea;
                [2 ]Department of Medical Science, Chungnam National University College of Medicine, Daejeon, Republic of Korea
                Author notes

                Contributions: (I) Conception and design: KH Joung, JM Kim, BJ Ku; (II) Administrative support: None; (III) Provision of study materials or patients: KH Joung, JM Kim; (IV) Collection and assembly of data: KH Joung, JM Kim; (V) Data analysis and interpretation: All authors; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

                [#]

                These authors contributed equally to this work.

                Correspondence to: Bon Jeong Ku. Department of Internal Medicine, Chungnam National University College of Medicine, Daejeon 34134, Republic of Korea. Email: bonjeong@ 123456cnu.ac.kr .
                Article
                atm-08-05-225
                10.21037/atm.2020.01.17
                7154468
                32309372
                a74bf3ad-37c0-43c4-aa3d-49adec3bd565
                2020 Annals of Translational Medicine. All rights reserved.

                Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0.

                History
                : 13 November 2019
                : 27 December 2019
                Categories
                Original Article

                cardiovascular disease risk,il-1beta,type 2 diabetes mellitus

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